Lack of exercise is a major cause of chronic diseases

Compr Physiol. Author manuscript; available in PMC 2014 Nov 23.

Published in final edited form as:

PMCID: PMC4241367


, Ph.D.,1, Ph.D.,2 and , Ph.D.3


Chronic diseases are major killers in the modern era. Physical inactivity is a
primary cause of most chronic diseases. The initial third of the article considers:
activity and prevention definitions; historical evidence showing physical inactivity is
detrimental to health and normal organ functional capacities; cause vs. treatment;
physical activity and inactivity mechanisms differ; gene-environment interaction
[including aerobic training adaptations, personalized medicine, and co-twin physical
activity]; and specificity of adaptations to type of training. Next, physical
activity/exercise is examined as primary prevention against 35 chronic conditions
[Accelerated biological aging/premature death, low cardiorespiratory fitness
(VO2max), sarcopenia, metabolic syndrome, obesity, insulin resistance,
prediabetes, type 2 diabetes, non-alcoholic fatty liver disease, coronary heart disease,
peripheral artery disease, hypertension, stroke, congestive heart failure, endothelial
dysfunction, arterial dyslipidemia, hemostasis, deep vein thrombosis, cognitive
dysfunction, depression and anxiety, osteoporosis, osteoarthritis, balance, bone
fracture/falls, rheumatoid arthritis, colon cancer, breast cancer, endometrial cancer,
gestational diabetes, preeclampsia, polycystic ovary syndrome, erectile dysfunction, pain,
diverticulitis, constipation, and gallbladder diseases]. The article ends with
consideration of deterioration of risk factors in longer-term sedentary groups; clinical
consequences of inactive childhood/adolescence; and public policy. In summary, the body
rapidly maladapts to insufficient physical activity, and if continued, results in
substantial decreases in both total and quality years of life. Taken together, conclusive
evidence exists that physical inactivity is one important cause of most chronic diseases.
In addition, physical activity primarily prevents, or delays, chronic diseases, implying
that chronic disease need not be an inevitable outcome during life.

1. Organization of article

1.1 Entire article

An underappreciated primary cause of most chronic conditions is the lack of
sufficient daily physical activity (“physical inactivity”). Overwhelming
evidence proves the notion that reductions in daily physical activity are primary causes
of chronic diseases/conditions and that physical activity/exercise is rehabilitative
treatment (therapy) from the inactivity-caused dysfunctions. The general strategy of
presentation divides the article into three major sections: 1) Conceptual information
forming the foundation to understand the remaining article; 2) Primary literature
supporting physical inactivity as a primary cause to a myriad of chronic
conditions/diseases, and 3) additional considerations. The aim of the entire article is to
bring better understanding and insight into the observation that a lack of physical
activity at ancestral levels initiates 35 pathological and clinical conditions.

1.2 First third of article

Conceptual information is presented in five parts in the first third of the
article. 1) Definitions of forms of physical activity, functional capacity, types of
fitness, chronic diseases, types of prevention so that the reader understands how the
article employs these words; 2) A brief chronology of the three-millennia history that
recognizes that physical inactivity reduces functional capacity and health; 3) Cause vs.
treatment are discussed to emphasize that physical inactivity is a primary cause of
chronic conditions/diseases; 4) Growing evidence that mechanisms by which inactivity
causes disease differ from mechanisms by which physical activity is a therapy/treatment to
act as a primary preventer of disease; and 5) Gene-environment interactions have varying
degrees of gene involvement in the magnitude of change to physical activity.

1.3 Center portion of article

Physical inactivity is a primary cause initiating 35 separate pathological and
clinical conditions. Many of the 35 conditions are subdivided under major categories, such
as loss of functional capacities with chronological aging; metabolic syndrome, obesity,
insulin resistance, prediabetes/type 2 diabetes, non-alcoholic liver disease,
cardiovascular diseases, cognitive functions and diseases, bone and connective tissue
disorders, cancer, reproductive diseases, and diseases of digestive tract, pulmonary, and

1.4 Final portion of article

The article ends with considerations of clinical significance, increasing risk
factors during long-term sedentarism, the developmental and clinical consequences of
inactive childhood/adolescence, and policy.

2. Definitions

2.1 CDC definitions of forms of physical activity

Verbatim definitions for exercise and health are from the US Centers for Disease
Control and Prevention (CDC) are used where possible due to the authority they carry
(90). US governmental definitions were selected
for the article to provide the framework for this article’s discussions of how 1)
exercise/physical activity prevents chronic diseases and 2) lack of physical activity is a
primary event that causes chronic diseases.


“A subcategory of physical activity that is planned, structured,
repetitive, and purposive in the sense that the improvement or maintenance of one or
more components of physical fitness is the objective”, as defined by CDC (90).

Exercise training

“Physical activity performed during leisure time with the primary
purpose of improving or maintaining physical fitness, physical performance, or
health”, as defined by CDC (90).

Physical activity

“Any bodily movement produced by the contraction of skeletal muscle that
increases energy expenditure above a basal level. Physical activity generally refers to
the subset of physical activity that enhances health”, as defined by CDC (90).


“A human condition with physical, social and psychological dimensions,
each characterized on a continuum with positive and negative poles”, as defined
by CDC (90).

Health-enhancing physical activity

“Activity that, when added to baseline activity, produces health
benefits. Brisk walking, jumping rope, dancing, playing tennis or soccer, lifting
weights, climbing on playground equipment at recess, and doing yoga are all examples of
health-enhancing physical activity”, as defined by CDC (90).

As previously stated, this article will concentrate on the use of physical
activity to prevent physical inactivity, and, thus, prevent many chronic diseases.

2.2 Definition of physical inactivity

CDC definitions for exercise do not include a definition of “physical
inactivity”. We define physical inactivity as “physical activity levels less
than those required for optimal health and prevention of premature death”. Further
consideration of the definition is given in section entitled, “Prevention of death
by primary prevention of physical inactivity”.

2.3 Definition of functional capacity

We define “functional capacity” as the ability of a cell, organ,
system, or body to maintain homeostasis within their narrow limits of survival in response
to a specified stress. If an external stress disrupts homeostasis beyond an organism’s
functional capacity, life may not be sustained. Diminished ability to adapt to stressors
increases the likelihood of death. Functional capacity is pliable; declining rapidly with
extreme physical inactivity or more slowly with aging, while preventing inactivity can
increase functional capacity (considered in specific detail in the aging section).
Importantly, a direct relationship between functional capacity and survival is a
cornerstone of general medicine theory. A major predictor of functional capacity is
maximal aerobic capacity (VO2max), which while directly testing cardiovascular
fitness and integrity also represents a combination of other physiologic components. For
instance, VO2max also depends on pulmonary and muscle function, health status
of other organ systems, nutritional status, medications, orthopedic limitations, and
others (352). An aerobic functional capacity in
patients under 4-metabolic equivalents (METs), a typical demand during normal daily
activities, increases postoperative (time from admission to discharge from surgery)
cardiac and long-term risks (155). In another
study, patients were grouped by MET capacity in relationship to complication prevalence
after they underwent angiographically verified coronary artery disease and subsequent open
abdominal nonvascular surgery. (265). Those from
the group < 4 METs had cardiologic complications in 64% of cases, the 4–7
METs group had 29%, and the 7–10 METs group had 8%. These remarkable findings can
be extrapolated to other stresses where the probability of complications, and even
survival, is dependent upon the functional capacity needed to maintain homeostasis.

2.4 Physical fitness vs. physical activity

Some people incorrectly use physical fitness and physical activity
interchangeably. The CDC defines physical fitness as “The ability to carry out
daily tasks with vigor and alertness, without undue fatigue, and with ample energy to
enjoy leisure-time pursuits and respond to emergencies. Physical fitness includes a number
of components consisting of cardiorespiratory endurance (aerobic power), skeletal muscle
endurance, skeletal muscle strength, skeletal muscle power, flexibility, balance, speed of
movement, reaction time, and body composition”. The CDC defines physical activity
as “Any bodily movement produced by the contraction of skeletal muscle that
increases energy expenditure above a basal level” (90)..

Inherited genes and their interaction with physical activity levels determine
physical fitness. However, chronic physical activity levels themselves modulate fitness.
Further, the levels of physical activity, themselves, modulate whether fitness improves.
For example, Sisson et al. (478) concluded that
the most important finding of their study was that greater volumes of exercise were
associated with a lower probability of being a nonresponder. The percentage of
non-responders at a given level of training progressively decreased as the exercise volume

2.5 Cardiorespiratory fitness (CRF)

We define CRF as the capacity of the cardiovascular (heart and blood vessels)
and respiratory (lungs) systems to supply oxygen-rich blood to the working skeletal
muscles and the capacity of the muscles to use oxygen to produce energy for movement. The
gold standard to determine CRF is the aforementioned VO2max, or maximum aerobic
fitness. However in large clinical human studies, an acceptable surrogate for
VO2max is the length of time running or cycling in standardized test,
assuming appropriate physiological/biochemical/psychological proof of exhaustion is
obtained (65, 263).

The majority of data about fitness and physical activity is focused on aerobic
fitness. Data indicates that rapid, severe physical inactivity can rapidly decrease CRF.
For instance, in the Dallas Bed Rest study, healthy, young males’ VO2max
decreased 27% after 20 days of continuous bed rest (454) and another study in Denmark 2 weeks of reducing daily step number from
10,501 to 1344 VO2max decreased 7% (389).

2.6 Strength fitness

We define strength fitness as the capacity of the skeletal muscle to move an
external load. Strength is highly dependent upon skeletal muscle mass, which contains a
major genetic component (Discussed later in Twin studies-Modulation of twin health by
physical activity), and is sensitive to decreased mechanical loading resulting in skeletal
muscle atrophy regardless of endowed muscle mass (49, 508).

2.7 Balance and flexibility fitness

We define balance fitness as the ability to control the body’s position
throughout movement,and flexibility fitness as the ability to achieve an extended range of
motion. Both have components of genetic inheritability and are also trainable (Discussed
later in Twin studies-Modulation of twin health by physical activity).

2.8 Definition of chronic diseases and their prevalence

We define chronic disease as a disease slow in its progress (decades) and long
in its continuance, as opposed to acute disease, which is characterized by a swift onset
and short course.

Medicine, public health, pharmaceutical industry, and educational systems have
reduced infectious diseases and early life mortality resulting in record average life
spans for much of the human population. In place of infectious diseases most people in the
US now die of chronic diseases.

The CDC Website states, “Chronic diseases—such as heart disease,
cancer, and diabetes—are the leading causes of death and disability in the United
States. Chronic diseases account for 70% of all deaths in the U.S., which is 1.7 million
each year (85). These diseases also cause major
limitations in daily living for almost 1 out of 10 Americans or about 25 million people
(85), The CDC further wrote, “Chronic
diseases – such as heart disease, stroke, cancer, diabetes, and arthritis –
are among the most common, costly, and preventable of all health problems
in the U.S.” (86). In addition to the CDC,
former US Secretary of Health and Human Services, the Honorable Michael O. Leavitt in the
2008 Physical Activity Guidelines for Americans, wrote,

Along with President Bush, I believe that physical activity should be an
essential component of any comprehensive disease prevention and health promotion
strategy for Americans. We know that sedentary behavior contributes to a host of
chronic diseases, and regular physical activity is an important component of an
overall healthy lifestyle. There is strong evidence that physically active people have
better health-related physical fitness and are at lower risk of developing many
disabling medical conditions than inactive people (532).

2.9 Definitions of types of prevention

For the purposes of this article, physical activity is
presented as primary prevention of physical inactivity. The CDC defines
physical inactivity as an actual cause of chronic conditions (213, 345). Physical activity,
itself, rarely causes chronic conditions, e.g., participation in specific sports improves
general health, but can increase the risk of osteoarthritis in specific populations (71); discussed later in section
“Osteoarthritis”. The next definitions are taken from a commissioned paper
by the U.S. Institute of Medicine (267).


Prevent implies taking advanced measures against something possible or
probable. Prevention in medicine has been divided into three progressive stages –
primary, secondary, and tertiary (267).

Primary prevention

“Primary prevention refers to health promotion, which fosters wellness
in general and thus reduces the likelihood of disease, disability, and premature death
in a nonspecific manner, as well as specific protection against the inception of
disease” (267).

Secondary prevention

“Secondary prevention refers to the detection and management of
pre-symptomatic disease, and the prevention of its progression to symptomatic disease.
Screening is the dominant practice…The margins between primary and secondary
prevention can at times blur (268).”…For example, `”If hypertension is defined as a
disease, its treatment is secondary prevention; if defined as a risk factor for coronary
disease that does not yet exist, it is primary prevention” (267).

Tertiary prevention

“Tertiary prevention refers to the treatment of symptomatic disease in
an effort to slow its further progression to disability, or premature death…there
is a legitimate focus on prevention even after disease develops, such as the prevention
of early cancer from metastasizing, or the prevention of coronary disease from inducing
a myocardial infarction or heart failure. This domain also encompasses rehabilitation,
the purpose of which is to preserve or restore functional ability, and thus prevent its
degeneration” (267).

2.11 Application of exercise to prevention categories

Examples for our view that exercise is a primary, secondary, and tertiary
preventer of disease are as follows: 1) Primary prevention (direct treatment of cause to
prevent disease occurrence) is voluntary avoidance of physical inactivity or treatment of
physical inactivity with physical activity; 2) Secondary treatment [eliminating one cause
(physical inactivity) of existing hypertension by eliminating physical inactivity] is
treatment of existing hypertension with physical activity; and 3) Tertiary prevention with
physical activity is cardiac rehabilitation where exercise benefits do not reverse the
anatomical pathology from myocardial infarction. We propose that the greatest health
benefit of physical activity is primary prevention of 35 chronic diseases/conditions to
become clinically overt. This article is largely restricted to consideration of primary
prevention of inactivity as an actual cause of chronic conditions.

3. Overview for next three sections

While, concerns that physical inactivity is detrimental to health have been
documented for over three millennia, much remains unknown, e.g., a) how to change the
sedentary behavior of the 92% of U.S. adolescents and > 95% of adults who do not met
the U.S. Department of Health and Human Services guidelines for physical activity (527), b) how to have health care professionals provide
effective individualized exercise prescriptions, and c) what are the molecular links between
inactivity and chronic disease that will provide a policy tool in the same way as the
molecular link between the carcinogen in tobacco and lung cancer did (129).

4. Summary of daily step reductions from antiquity

Historical evidence shows that physical inactivity is prevalent in today’s society
relative to historical levels (385). Estimated daily
step numbers have declined ~50% to ~70% since the introduction of powered
machinery. ().

Table 1

Estimated historical reductions in daily steps by humans.

Population Year Steps per day References
Paleolithic (~20,000 BC) ~13,200–21,120 (men) ~10,560 (women) (385)
Amish (2002) 18,425 (men) 14,196 (women) (27)
Mean of 26 studies (1966–2007) 7,473 (mainly women) (63)
Colorado (2002) 6,733 (men) 6,384 (women) (573)
US adults (2010) 5,340 (men) 4,912 (women) (26)

5. History of inactivity’s compromising effects on function and health

Three millennia of evidence exist to indicate historical recognition that physical
inactivity is detrimental to health by reducing the functional capacity of most organ
systems in humans, mammals, and rodents.

5.1 Ancient India (~1500–600 BC)

A historical review by Tipton (519)
described the tridosa doctrine in India, which contended that the three humors regulated
all functions of the body. When humors were in equilibrium, good health was present.
However, sedentary living and lack of exercise could displace one or more of the humors,
impairing health and potentially leading to illness and death. Susruta (600 BC) was
convinced a sedentary lifestyle elevate the kapha humor to a level that could disrupt
humoral equilibrium resulting in a disease state and potential death. He included exercise
in his recommendations to prevent the occurrence of diseases.

5.2 Hippocrates (~450 BC)

Quotations attributed to Hippocrates promote the primary prevention of disease
by physical activity.

“If we could give every individual the right amount of nourishment
and exercise, not too little and not too much, we would have found the safest way to
health” (240).

“If there is any deficiency in food and exercise the body will fall
sick” (477).

“Walking is man’s best medicine” (240).

“All parts of the body, if used in moderation and exercised in labors
to which each is accustomed, become thereby healthy and well developed and age slowly;
but if they are unused and left idle, they become liable to disease, defective in
growth and age quickly” (278).

5.3 Bed rest (1945–1955)

Three days of physical inactivity produces glucose intolerance (47). Paul Dudley White, one of Dwight Eisenhower’s
cardiologists after the President’s heart attack on September 24, 1955, prescribed
physical activity to President Eisenhower long before the end of the standard treatment of
6-months bed rest for a heart attack. The medical community followed White’s practice of
substituting physical activity for bed rest in management of acute coronary syndromes,
with bed durations progressively decreasing to 2 weeks in 1980 in 2005 (340). A 2011 meta-analysis concludes that exercise
training has greatest beneficial effects on left ventricular remodeling in clinically
stable post-MI patients when training starts one week following the MI (227).

5.4 Initial epidemiology (1949–1953)

Jeremiah Morris is recognized as the person who first used physical activity in
epidemiology (his history is available (43). In
1953, Morris and co-workers compared bus drivers, who are sedentary in their occupation,
with the physically active bus conductors, who were constantly moving up and down
double-decker buses to collect fares in London. Physically active conductors had a 30%
lower incidence rate of coronary heart disease (CHD) than the physically inactive bus
drivers (353). Furthermore, even the physically
active conductors who did develop CHD with age were better off, presenting with less
severe disease and lower fatality rates than the inactive bus drivers (353). However, while VO2max was not
determined in Morris’ report, others have since shown that workers in physically active
occupations have higher aerobic capacity than their inactive peers (220). Morris’ 1953 report (353) is a milestone as the initial publication documenting daily physical
inactivity is associated with increased morbidity and mortality (43).

In his 10th decade of Morris’ life, he wrote, “We in the West
are the first generation in human history in which the mass of the population has to
deliberately exercise to be healthy. How can society’s collective adaptations
match?” (43, 354).

5.5 Primary prevention: Human space flight (1957–1961)

The Space Race for national security began in earnest in 1954 leading to the
successful launch and orbit of Sputnik from the USSR on October 4, 1957. Four years later
on April 12, 1961 Yuri Gagarin became the first human in outer space and the first to
orbit the Earth. The Space Race hastened physiological exploration that the microgravity
experienced in space reduced human functional capacities. As an outcome, NASA researched
countermeasures to the microgravity-induced functional loss during spaceflight that relied
on experimental bed rest on Earth, an extreme form of inactivity. However, interest in the
primary mechanisms of inactivity was a lower priority.

Today over 6500 publications arise from a PubMed search for the terms
spaceflight and physiology. Inspection of this body of literature led Vernikos and
Schneider (540) to contend that spaceflight
results in losses of functional capacities in multiple organ systems, similar to an
accelerated model mimicking aging. For example, they conclude that bone atrophy occurs
10-times faster in spaceflight than with aging. Similarly, reductions in immune function,
sensitivity of arterial baroreflex, maximal stroke volume, maximal cardiac output, and
VO2max also occur more rapidly in spaceflight than in aging (540, 561).
(Cross-reference: Importance of exercise in microgravity)

5.6 Bed rest book (1965)

The preface of Browse’s book “The Physiology and Pathology of Bed
Rest”, published in 1965 states that the principle purpose of the book,

…is to lay bare our ignorance of the whole subject, to stimulate
research…The dangers of bed rest are so many, and in some cases so final, that
we should always be striving to discard it from our therapeutic
armamentarium…and to emphasize the absurdity of using a non-specific treatment
for specific diseases without reason or proven value (68).

The book carefully documents the widespread systemic deterioration of the body
when continuous bed rest occurs. Some of the pathologies documented are: postural
hypotension, tachycardia, kidney stones (renal calculi), loss of skeletal muscle mass,
weakness in antigravity muscles, pressure ulcers, osteoporosis, constipation, deep vein
thrombosis, pulmonary embolism, pneumonia, and difficulty with micturition.

5.7 Dallas Bed Rest Study (1960’s)

Saltin, et al. (454) studied five
healthy college-age males during 20 days of continuous bed rest. During acute exercise
following bed rest reductions of 28%, 11%, 26%, and 29% in VO2max, ventricular
volume (ml), maximal cardiac output, and maximal stroke volume occurred, without a change
in maximal A-VO2 difference. Further detrimental changes with bed rest were
increased heart rate at a submaximal workload of 600 kpm/min from 129 to 154 beats/min and
total peripheral resistance (TPR) increasing from 449 to 520 TPR units. From the
10th–20th day of bed rest day resting heart rate increased
from 47 to 51 beats/min.. (Cross-reference: Cardiac Function; Cardiac output during
exercise: contribution of the cardiac, circulatory and respiratory systems)

5.8 Sitting studies (2000’s)

A perspective was proposed as to whether too much sitting is distinct from too
little exercise (218, 317, 392, 393). Owen et al.’s 2010 review states,

Further evidence from prospective studies, intervention trials, and
population-based behavioral studies is required…many scientific questions
remain to be answered before it can be concluded with a high degree of certainty that
these adverse health consequences are uniquely caused by too much sitting, or if what
has been observed so far can be accounted for by too little light, moderate, and/or
vigorous activity (392).

A 2010 review co-authored from multiple research sites concluded from an
examination of 43 papers, “Limited evidence was found to support a positive
relationship between occupational sitting and health risks. The heterogeneity of study
designs, measures, and findings makes it difficult to draw definitive conclusions at this
time” (537). The concept of intermittency
of lack of weight bearing by sitting is supported by older basic science research. In rats
cycling 4 times/day through periods of weight bearing and non-weight bearing (hindlimb
suspension), soleus muscle atrophy was prevented by 4 × 15-min periods of ground
support during 12 hrs of the day (118).

5.9 Animal wheel lock studies (2000’s)

In order to optimize primary prevention by physical activity, mechanisms by
which physical inactivity initiates risk factors for chronic diseases must be elucidated
for the optimal science-based physical activity prescription. One animal model used young
male rats that underwent 3 weeks of voluntary running and then had their wheels locked
(WL) for 5 hrs (WL5), 29 hrs (WL29), or 53 hrs (WL53). Within 53 hrs two major changes in
functional capacities were observed, decreased submaximal insulin sensitivity and enhanced
storage of TG in visceral adipose tissue. (For the purposes of this article, visceral and
intra-abdominal adipose tissues are considered similar and the term visceral is used).
Specifically, submaximal insulin-stimulated 2-deoxyglucose uptake, insulin binding,
insulin receptor ß-subunit (IRß) protein level, submaximal
insulin-stimulated IRß tyrosine phosphorylation, glucose transporter-4 protein
level, and Akt/protein kinase B Ser473 phosphorylation (an index of proximal insulin
signaling) in the epitrochlearis muscle, returned to sedentary levels at WL53 (293). Further, the epididymal adipose tissue mass at
WL53 weighed 25% more than at WL5 in the same rats as studied for insulin sensitivity

5.10 Translation studies – Reduced stepping studies in humans (2000’s)

While continuous bed rest is a model examining the absence of physical activity,
a novel human reduced-activity model was designed to test the effects of reduced, rather
than lack of, physical activity on metabolic health. Step numbers were reduced by taking
elevators instead of stairs and riding in cars instead of walking or bicycling within a
free-living environment by young, healthy male adults who were not undertaking >2
hrs/wk exercise at the start of the study. After reducing daily step number form 6203 to
1394 for 3 weeks, areas under the curve (AUC) for plasma insulin during an oral glucose
tolerance test (OGTT) progressively increased 53%, 61%, and 79% after 1, 2, and 3 weeks,
respectively (389).

In a second study, subjects reduced daily steps from 10,501 to 1,344 (where
there are ~2000 steps in a mile). After 2 weeks, VO2max decreased 7%,
peripheral insulin sensitivity decreased by 17% with concurrent decreases in
insulin-stimulated ratio of pAkt-Thr308/total Akt in skeletal muscle. Body
composition was also significantly altered by 2 weeks of reduced stepping with visceral
adipose tissue mass increased 7%, total fat-free mass decreased by 1.2 kg, 0.5 kg of it in
the legs, while total-body fat mass and BMI were unchanged (286, 389). Thus, an inverse
relationship existed between gain of visceral adipose tissue and loss of lean mass,
indicative of body composition repartitioning. Similar observations have been made in a
rat WL model. In a different WL experiment visceral adipose tissue mass, but not lean mass
increased independent of food intake after 173 hours of WL followed 6 weeks of voluntary
running (310). Thus, both human and rat models of
reduced daily steps increased visceral adipose tissue while diminishing lean mass,
independent of caloric increases.

5.11 Clinical significance

Short-term reductions in daily step number (producing less daily physical
activity) cause decreased CRF, loss of insulin sensitivity, reduced lean mass and
increased visceral adipose tissue. These functional decrements help explain the link
between reduced physical activity and the risks that have been associated with the
progression of chronic disorders and premature mortality (389). Using physical activity prescriptions to prevent physical inactivity would
help maintain functional capacities.

5.12 Summary: Inactivity causes loss of functional capacities

Taken together, the historical work provides overwhelming evidence that physical
inactivity cause decreases in capacities of functional systems, leading to premature
deterioration of health in humans. The Copenhagen study of reduced stepping, while low in
subject number, is particularly relevant to everyday living because the reduced physical
activity level is similar to the step numbers performed in a free-living environment by
billions of humans worldwide in both developed and developing countries.

6. Cause vs. treatment

A sedentary lifestyle over several years is associated with increased risk for
type 2 diabetes, cardiovascular disease, and premature mortality. What is much less
appreciated is the high cost of physical inactivity even in the short term. Booth
et al. have been drawing attention for years to the societal and
individual burden of inactivity-related chronic diseases. They remind us that while
exercise is a treatment to prevent many chronic diseases, it is the lack of regular
exercise or physical inactivity that is one of the actual causes of many of these
diseases” (481).

Convincing proof that physical inactivity causes primary deterioration of function
is provided from extensive historical and scientific evidence. Thus, physical activity can
prevent physical inactivity-induced chronic diseases (left panel of ). In contrast (right panel of ), physical activity can treat against lung cancer-induced dyspnea, a common side
effect 1 to 6 years after lung cancer resection (179) (Right panel ). Thus, in the left
panel physical activity addresses the cause of the disease, while in the right panel
physical activity only acts as a treatment against a disease in which it cannot prevent. We
will focus on the disease processes of the left panel in this article.

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0001.jpg

Physical activity produces primary and tertiary preventive health benefits for chronic
diseases. Left panel. Physical inactivity is an actual initiating cause
of a chronic disease/condition. Restoration of physical activity (primary prevention)
removes the actual cause (physical inactivity) that produced the health deficiency.
Right panel. Physical inactivity is not the
cause of lung cancer. Smoking is an actual cause of lung cancer. Addition of aerobic
exercise training compensates (tertiary prevention) for loss of lung function after
surgical removal of a portion of lung by strengthening respiratory skeletal muscles for
remaining lung (179). Exercise does not cure lung

7. Mechanisms of physical inactivity and activity differ

Mechanisms of physical inactivity are considered anti-parallel, rather than in
series (continuum) to physical activity (210, 570). Physical activity and inactivity reside in
different mechanistic planes, and are not merely mirror images of each other as is commonly
considered (discussed below). Optimal therapies and preventive strategies require knowledge
of causal mechanisms. Thus, it is important to understand that some of the mechanisms by
which inactivity causes chronic diseases differ from mechanisms by which exercise acts as
primary prevention of same diseases.

One example is that inactivity and exercise differ with regards to time courses of
structural changes in conduit arteries and changes in endothelial function. This difference
is summarized nicely in a review where Thijssen et al. state: “However, the nature
and impact of inactivity and exercise on vascular structure and function suggest that
inactivity and exercise are not simply the opposite ends of a linear spectrum of
physiological adaptation” (506). In our , distinct mechanisms by which inactivity and/or
exercise alter conduit size and endothelial function are outlined. For instance inactivity
results in immediate negative remodeling of the vessel, while activity requires 4–6
weeks to positively remodel the vessel.

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0002.jpg

Changes in artery function and structure (remodeling) show differential time courses in
response to increasing or decreasing human physical activity as hypothesized by Thijssen
et al. (506). Exercise training (right side)
produces early, rapid increases of arterial function (blue line), which is followed weeks
later by arterial remodeling (red line and larger diameter vessel) that returns arterial
function to pre-exercise training levels. Physical inactivity (left side) is associated
with immediate, rapid decreases in arterial diameter after spinal cord injury (decreased
size in top far left blood vessels and red line). Function immediately decreases and then
returns to pre-injury value. [Reproduced with permission from Figure 2 in ref. (506)].

A second example that inactivity and exercise are not mirror images of one another
is found from global analysis of skeletal muscle gene expression, before bed rest,
immediately after bed rest, and after 4 weeks of post-bed rest training. Compared to pre-bed
rest levels, 9 days of bed rest altered 4500 mRNAs. If physical activity were merely the
reverse of inactivity then all 4500 would be hypothesized to return to pre-bed rest levels
following 4 weeks of training. However, a normalization of expression failed to occur in 20%
of the 4500 genes that changed with bed rest. This observation led Vaag and co-workers
(8) to speculate that rather severe and long lasting
adverse alterations in mRNA levels may develop in important biological pathways relevant to
their general health after 9 days of bed rest.

A third example is by Stein and Bolster (491) who compared muscle atrophy (311) to
skeletal muscle regrowth from atrophy (184), and
reiterated by Greenhaff and Hargreaves (210). Again,
if physical activity were the opposite of physical inactivity, then the expected result
would be many of the same genes changes would be similar for atrophy and regrowth. However,
comparison of these two gene lists showed virtually no common gene names on both lists.
These examples illustrate a fundamental principle of biochemistry, which Stein and Bolster
concisely state, “This is a common finding in biochemistry. Anabolic and catabolic
pathways are usually separate” (491)”,
or put another way, opposite processes work through entirely different mechanisms rather
than altering the level of one pathway. Further biochemical examples include; irreversible
steps in glycolysis and glycogen synthesis, protein synthesis and degradation, lipolysis and
lipogenesis, and mitochondrial biogenesis and mitophagy, all of which support the idea that
exercise and inactivity are not merely opposites of each other. Thus, a single molecular
paradigm to explain adaptations to exercise and inactivity does not exist.

8. Gene-Exercise/physical inactivity interactions

Physical fitness and physical activity/inactivity interact with genes. While many
fitness examples of gene-environment could be chosen, VO2max will be used because
it is well studied and integrates the function of multiple organs at multiple levels (i.e.
tissue, cell, protein, and gene). (Cross-reference: Genetics: environment and their

8.1 Genetic Component Alone

Phenotype responsiveness variability to aerobic training

Using untrained pairs of monozygotic twins, dizygotic twins, and brothers
approximately 40–50% of VO2max was estimated to be due to genetics
(57). Similarly, pairs of identical twins had
significantly more similar increases in VO2max than unrelated twin pairs after
aerobic training in three papers in the mid-1980s (217, 421, 474). The papers led to the milestone paper reporting that some
individuals experiencing little or no gain in VO2max, whereas others gained
>1.0 L/min in 481 sedentary subjects (55). A
2.5-times greater variance existed between families than within families in the
VO2max response variance.

8.2 Higher VO2max associates with better health

The 1996 US Surgeon General’s Report (531) concluded that high CRF decreases the risk of cardiovascular disease (CVD)
mortality. High VO2max is associated with “positive health”; low
VO2max is associated with “negative health.” Remarkably, low
CRF was a stronger predictor of death than clinical variables or established risk factors,
such as hypertension, smoking, and diabetes, as well as other exercise-test variables,
including ST-segment depression, the peak heart rate, or the development of arrhythmias
during exercise in both healthy subjects and those with CVD (363). Specifically, subjects aged 60 and older with low CRF had
notably higher mortality risk from all causes than those with high CRF (499). Maintaining the highest possible
VO2max is a primary preventer of morbidity and mortality from low
VO2max (discussed later). Further information on the role of genes, physical
activity, VO2max (CRF), and health is presented next.

8.3 Using VO2max to identify “health” genes

Theoretic selection of specific genes to optimize functional capacities

In 1979, Bennett and Ruben elegantly described a basis for natural selection
of genes by physical activity to maximize inherited potential VO2max,

“We believe that this increased stamina and sustainable activity
were important selective factors from the outset… The selective advantages of
increased activity capacity are not subtle but rather are central to survival and
reproduction. An animal with greater stamina has an advantage that is readily
comprehensible in selective terms. It can sustain greater levels of pursuit or
flight in gathering food or avoiding becoming food. It will be superior in
territorial defense or invasion. It will be more successful in courtship and
mating” (34).

The quotation hints that some genes were selected during evolution to support
high levels of physical activity and the ability to adapt to physical activity. However,
recent observations that a small portion of the population is low responders for
VO2max suggest a greater biological complexity than known in 1979.

Genes associated with plasticity of VO2max

In 1998, Bouchard and co-investigators published, “Maximal heritability
estimates were at least 50%, a value inflated to an undetermined degree by inclusion of
nongenetic shared factors” (56). Timmons
employed a novel approach to improve the examination of complex physiological variables
in human models. To identify genes responsible for variance of VO2max
plasticity, Timmons et al. (517) used a novel
approach by first conducting mRNA expression microarray profiling, which were then used
to produce molecular predictors to locate or rank a discrete number of genes that
correlate with the change in VO2max following endurance training. Follow up
studies allowed for subsequent targeted genotyping and, hence, discovery of key genetic
variants responsible for the variance of VO2max plasticity. A signature of 29
mRNAs and of 11 single nucleotide polymorphisms (SNPs) were identified that predicted
~50% and ~23%, respectively, of the estimated variance for
VO2max plasticity following aerobic training in humans (517). Timmons et al. (517)
noted two remarkable characteristics in their identified 29 predictor mRNAs: 1)
pretraining levels were greater in high than low responders for VO2max; and
2) >90% of the 29 mRNAs did not change with aerobic training. They suggested that
individuals with a low responder predictor gene profile would require alternative
exercise intervention paradigms or more intensive pharmacological and dietary protocols
to help compensate for their genomic profile. Timmons and co-authors further examined
the same subjects after 6 weeks of endurance training at 70% of maximal
VO2max (517). They observed that
low-responders did not switch on their proangiogenic network genes effectively (269). (Cross-references: Molecular mechanisms and
muscle plasticity with acute and chronic exercise; Muscle plasticity: energy demand and
supply processes; Regulation of gene expression in skeletal muscle by contractile

Timmons et al.’s (517) development and
validation of mRNA predictors to hunt for genetic markers have many advantages over
existing approaches of SNP. Each SNP seems to contribute only weakly for chronic complex
human diseases. For example, after genome-wide association analysis in type 2 diabetes
(T2D) patients, 18 robust SNPs explain <7% of the total disease variance (484). As to generalization of a low responder to all
of tens of health benefits from exercise training from VO2max alone, Timmons
cautions, “No systematic analysis allows us to be certain that a `nonresponder’
for one trait does not cluster with a poor response for another” (516). Thus, additional research is needed to
determine whether low responders for gain in VO2max with endurance training
respond to other “positive health” benefits of physical activity, such as
improved cognitive function, bone density, skeletal muscle strength, visceral adipose
tissue quantity and quality, and the tens of other “positive health”
benefits detailed later in this article (52).
Blair, Church, and co-workers (478) reported
that non-responders to for increase in VO2max comprised a total of 44.9%,
23.8%, and 19.3% of the 4-, the 8-, and the 12-kcal/kg/wk treatment groups,
respectively. They concluded that greater volumes of exercise were associated with a
lower probability of being a nonresponder. In summary then, additional research is
needed to determine if low responders to aerobic exercise are low or high responders to
high-intensity interval training, to resistance training, balance, or flexibility

Proof due to experimental selection of physical aerobic-fitness genes in

Britton and Koch’s experimental selection, based upon a single
volitional/behavioral forced running test to exhaustion, provided experimental evidence
that natural selection for high aerobic capacity during evolution is a feasible concept
(569). Selection of rats on the basis of the
longest or shortest running distances during a single exercise test resulted in
selection of a 58% higher aerobic capacity in the high-distance line than the
short-distance line over 11 generations. Rats with high VO2max had healthier
cardiovascular systems (12% lower mean 24-hr blood pressures and 48% better
acetylcholine-induced vasorelaxation), and healthier metabolic risk factors (16% less
fasting plasma glucose, 39% less visceral adipose tissue, 63% lower plasma triglyceride
levels, and greater mitochondrial protein concentrations). These data provides evidence
of a genetic role in inter-animal variation in VO2max that is correlated with
better health outcomes.

8.4 Phenotype responsiveness variability to resistance training (RT)

In addition to VO2max variance among subjects in response to aerobic
training, RT also has a tremendous amount of variability in adaptive responsiveness. In
585 subjects undergoing 12 weeks of RT, changes from 2 to +59%, 0 to +250%, and −32
to +149% occurred in cross sectional area, one repetition max, and maximal isometric
contraction, respectively (250). The variability
in muscle mass may, in part, be related (but not limited) to inter-individual differences
in genome code (as with IGF2 in the aforementioned porcine model) (377), the individual’s ability to activate intramuscular mTORC1
signaling within skeletal muscle in response to exercise (333), and/or different responses of microRNA (miRNA) to RT(120). Successful RT-induced hypertrophy in human skeletal muscle was
associated with specific differences in miRNA expression to RT in high- and low-
responders, respectively, which Davidsen et al. (120) suggest means that miRNAs may play a role in regulating the translation of
key gene networks responsible for human skeletal muscle growth. One possible pathway is
the PI3K/Akt/mTOR pathway, which is up-regulated during skeletal muscle hypertrophy in
humans, and related to the ability for satellite cells to proliferate and/or differentiate

8.5 Pharmacogenetics interactions with exercise

The efficacy of drugs is affected by physical fitness/activity status (104, 328) in
addition to genetic disposition. For instance, in patients with abnormal left ventricular
(LV) relaxation and preserved LV ejection fraction, exercise and weight loss plus drug
reduced the LV relaxation dysfunction that was not reduced by the drug alone (104). Martin et al. (328) speculate that drugs with good efficacy in sedentary overfed (overweight)
animal models may be less effective in active normal weight animals.

8.6 The future of personalized human medicine

The findings of the previous sections have led Timmons et al. (517) to predict that they could apply gene data for
changes in VO2max in personalized medicine to tailor exercise prescription.
Medicine will continue to become more personalized with the looming question of how to
optimize how it is applied to ensure the greatest patient benefit. Carl Sagan wrote,
“It is the tension between creativity and skepticism that has produced the stunning
and unexpected findings of science” (452).
It is the spirit of Sagan’s quotation that we now raise issues about which we are
skeptical. We are skeptical that exercise experts will be used to inform health care
professionals on how to make personalized exercise prescriptions based on science. The
fear is that a patient will be informed that they have low-responder genes for
VO2max, which may lead to failure of the patient to exercise or lack of
compliance to alternative exercise prescriptions. We hope that solutions, such as
encouraging low responders to aerobic exercise or to engage in resistance exercise, can
lead to striking improvements in personalized health.

8.7 Clinical significance

In a statement in Science, NIH Director Francis Collins wrote,

However, the best opportunity to reduce risk in genetically susceptible
people for the foreseeable future will not be to re-engineer their genes, but to
modify their environment. We need to understand how genetic factors and environmental
exposures interact in individuals to alter normal biological function and to affect
the risk of disease development (464).

The clinical significance of low- and high-responders for a given dosage and
type of exercise, implies that individualized medicine, if exclusively restricted to
viewing genetic background in vacuum, will result in less than optimal prescriptive
therapy. Rather, individualized medicine for primary prevention of disease and premature
death must also be based on individualized variation of inherited genes for: a) disease
susceptibility, b) responsiveness to exercise training and type of exercise, and c)
drug-exercise interactions, if appropriate. Thus, fully capturing personalized
gene-environment interactions.

Kujala et al. (289) wrote, “When
tailoring clinical physical activity interventions, we must remember that not all
individuals are suited to the same guidelines for exercise intensity, because the ability
to exercise seems to vary not only by training background but also by genetic

9. Twin studies – Modulation of twin phenotype by physical activity

Claude Bouchard has extensively used the experimental approach of MZ twins to
minimize genetic variability for estimating the percentage contribution of environmental
(physical activity) interventions since the mid-1980s. In addition to studies where twins
were subjected to exquisitely controlled exercise protocols, a number of studies used
overfeeding protocols to look at the effect of excess calories (not included in the
following tables). The twin approaches have been critical to our ability to separate genetic
from environmental effects related to health and chronic disease in humans. Future,
twin-activity studies will contribute to prescription of exercise types and of dose-response
thresholds for primary prevention of chronic diseases.

9.1 Comprehensive presentation of twin-activity (gene-environment) studies

In this section, we take the approach of searching the literature for all
articles (that we could find) that have examined a variety of health outcomes in
monozygotic twins (MZ) to attempt to control for genetic variation.

9.2 MZ twin-activity comparisons show high mortality component

To summarize the most important health outcome, mortality, is presented to show the mortality outcome in
MZ twins discordant for physical activity in a large cohort of Swedish twins (77). The higher physically active MZ had a
36%–66% lower mortality than their inactive MZ pair.

Table 2

Tendency for dose-response between higher physical activity level and lower mortality in
Swedish monozygotic twins [modified from (77)].

Sex Physical activity level All-cause mortality Cardiovascular mortality
Hazard ratio 95% confidence intervals Hazard ratio 95% confidence intervals
Men Low 1 1
Moderate 0.84 0.72, 0.98 0.86 0.68, 1.08
High 0.64 0.50, 0.83 0.55 0.36, 085
Women Low 1 1
Moderate 0.82 0.70, 0.96 0.85 0.64, 1.13
High 0.75 0.50, 1.14 0.34 0.1,0.95

9.3 MZ twin activity comparisons show variable chronic disease component

These studies have taken the approach of either a priori
separating pairs of MZ that are discordant for physical activity (), looking at exercise responses in MZ twins relative to
dizygotic twins (), correlating health
parameters with physical activity or fitness levels in MZ twins (), and looking at the genetic component of physical fitness and
activity parameters (). By evaluating this
approach, we can obtain an idea about which factors are controlled mainly by genetics and
which are most modifiable for physical activity levels. However, it should be noted that
many of these studies have methodological limitations including a wide range of physical
activity levels and outcomes that differ from classical exercise physiology

Table 3

Studies with Twin Discordant for Physical Activity Levels.

Outcomes Physical Inactivity Effect MZ (n) Other (n) Sex PA Measurement Comments Ref
MRI Visceral Fat ↑ 50% in inactive Twin 16 B Questionnaire Age 50–74 years and Followed for
over 32 years. Subset for Finnish twin study.
MRI Liver Fat Score ↑ 170% in inactive Twin
MRI Intramuscular Fat ↑ 54% in Inactive Twin
BW changes from 1975 to 2005 ↑ 5.4 kg for the inactive twin 42 twins MZ to DZ proportions
B Phone Interview Unclear about proportion of MZ vs. DZ,
but states no differences between MZ and DZ. Subset of Finnish twin study. Twins not
discordant for PA had no difference in BW.
WC changes from 1975 to 2005 ↑ 8.4 cm in inactive twin
BMI ↑ 0.33 BMI in non-vigorously active twin 614 M Self Reported Vigorous Activity All males (mean age 41.1) that fought in Vietnam war.
When looking at all twins modeling predicted no genetic effect on the relationship
between vigorous activity and BMI.
Weight Gain ↑ 5.4 kg inactive twin 42 B Questionnaire showing Discordant PA in
1975, 1981, and 2005
Finnish twin study (545)
Waist Circumference ↑ 8.4 cm in inactive twin
Total Body fat in women with similar weight ↑ 1.0 kg& 1.4 kg fat for 1-hr or 2-hr less
156 W Questionnaire Home, sport, sweating
Discordant for physical activity. Age of 55.5
Total and regional Body fat in women with discordant
↑ 3.96 kg lower BF & 0.53kg central Also showed increased physical activity increased
muscle mass and strength (not analyzed in discordant twins)
BMI ↑ 2.12 in inactive twin (p<0.001) 35 Healthy Runners Survey – high PA =
40km/wk > than low PA (male), 32km/wk (female)
Subjects recruited from the National
Healthy Runners Survey. No active twins with overweight twin were themselves
HDL ↓0.14 in inactive (p=0.004)
HDL2 ↑ 2.71 in inactive (p=0.001)
Apo A-1 ↑ 0.10 in inactive (p=0.004)
Lipid profile before and after 40% fat or 20% fat
diet (cross over study): LDL and sybfractions, apolipoprotein A-1
N.S. 28 M Survey. One twin running >50km/wk than other
Subjects recruited from the National Healthy Runners
study. A diet low in fat independent of high amounts of exercise modifies circulating
Adiposity ↑ Sig lower in inactive twin 21 F 9 months of 3xwk high intensity weight bearing
Girls were prepubertal aged 8.7. Did not tell the
control group that they could no longer participate in sports.
BMD N.S. 12 Lifetime leisure high-impact sports Subgroup from the original group.
aBMC ↓ Sig in inactive twin
Femoral neck and lumbar BMD E = 1%&G = 73% of lumbar variance 105 M Questionnaire for endurance and balls sports Finnish men (35–69yr/old)Calcium supplements
also explained 1% of difference in BMD.
Spinal MRI N.S. disk degeneration 22 M Questionnaire between 1975 and 1981 showing
discordant endurance PA (3.9 v 1.1 time/wk)
Finnish Twin Cohort aged
↓T6-T12disk degeneration in low strength PA
12 Questionnaire between 1975 and 1981 showing
discordant strength PA (2300 v 200 hrs)
Psychomotor reaction times ↓ Sig slower choice reaction for hand &
contra foot in inactive
38 Lifetime exercise histories Finnish twin cohort. Average age of discordant PA
twins is 50. PA data collected in 1972, 81, 92
Psychological functioning (mood, optimism,
↓ Sig in inactive twin 63 B Questionnaire for discordant vigorous activity From US National Survey of Midlife Development (258)
Survey based Anxiety and Depression symptoms N.S. ? ? B Leisure time PA only Article is unclear how many MZ twins were discordant
for PA in their models. Only current levels of PA and not PA history used. Used Dutch
population, but excluded cycling to work as PA (non-leisure)
Dementia ↑ P = 0.07 for inactive PA twin 90 B Twin registry reported 31 years before follow-up Swedish twin registry. Data on all twins showed
significant correlation of increased PA and decreased dementia
Life satisfaction N.S. 161 172 2842 Survey Data in MZ and related family members
showed an OR>1.0for active pair of an unrelated paired of people.
Life Happiness N.S.
Lactate threshold E is 25–30% & G is 50–60% 9 M 6 months of anaerobic threshold
Aged 11–14. Change in VO2max was
more due to the less weight gain in trained twin. Used analysis of variance to
estimate the genetic and training effects.
VO2max E is 35% & G is 45%
Total Body Fat E is 20% & G is 70%
Myocardial infusion at rest, during adenosine, and
cold-presser test
N.S. 9 M Separated by VO2max and physical activity
Young males with a 18% difference
inVO2max (ml/kg/min) of (43.7 vs 50.7)
Endothelial function via ultrasound of brachial and
LAD coronary artery
Oxygen extraction fraction ↑ in low fit (p=0.06)
Hepatic FFA uptake at rest ↑Sig in less fit group Same subjects as above. (222)
Myocardial FFA uptake at rest and during
Skeletal muscle perfusion and free fatty acid
N.S. Same subjects as previous study. (223)
Cornell voltage (electrical measurement of LV
↓Sig in inactive (36)
Right-side hypertrophy index
LV mass index
Type 2 Diabetes 18 inactive v 2 active twins acquired T2DM 5 15 DZ B Leisure time PA Twins discordant for PA and discordant for Type 2
diabetes. For MZs it was the inactive twin that developed type 2 diabetes.
Mortality from 1975–1981 ↑Sig in inactive DZ twins, but not inactive MZ
157 517 B Questionnaires for vigorous PA and estimates of
>2MET wk/day/wk
Finnish twin cohort aged 24–60. Low level of
leisure physical activity in early life was associated with increased risks of death
in dizygotic twin pairs, but monozygotic co-twins.
(289, 546)

Table 4

Studies with Twin Response to Exercise

PA Intervention Outcomes H-effect MZ (n) DZ (n) Sex Comments Ref
Submaximal supine bicycle at HR of
End-diastolic mean wall thickness (rest) H = 53% 21 12 M Similar results when adjusted for body
fat. Non-genetic component is made up of both shared and non-shared environmental
LV diameter (rest) N.S
Fractional shortening (rest) H = 13% (N.S)
Change in End-diastolic mean wall thickness
H = 0% (N.S.)
Change LV diameter w/exercise H = 24%
Change in Fractional shortening w/exercise H = 47%
Cycling Power output H = 53%
Cycling VO2max H = 46%
20-wk endurance training LV wall, posterior wall, septal wall, LV mass, Minimal H effect 20 20 (not related) M Training effect in all subjects. (303)
Supine bicycle at 60W (submaximal) SBP (rest) Sig H 32 21 M Less effect on heritability during
exercise than at rest (conclusions based only on abstract; unable to obtain full
DBP (rest)
Change in SBP w/exercise
Change in DBP w/exercise
Graded Cycle test to
Peak VO2 H = 77%, 66% when PA and skinfolds adjusted 29 19 M Testing was done on a max test and also
collected with HR was at 150bpm.
O2 uptake at HR of 150bpm H = 61%, 16% when PA and skinfolds adjusted
Mechanical Efficiency N.S. H Correlation
Anaerobic energy generation H = 78%, 58% when PA and skinfolds adjusted
Respiratory exchange ratio H = 6% only
30 minutes of treadmill at anaerobic
GH and PRL response to exercise and cortisol at
Sig H Correlation 9 M Athletes (135)
ACTH and cortisol response to exercise and
beta-endorphin at rest
N.S. H Correlation
93 days of negative energy balance (diet
and exercise)
euglycemic-hyperinsuliemic clamp before and after
N.S. H Correlation 7 M (390)
Fasting and postprandial insulin
dehydroepiandrosterone sulfate & androsterone
Sig. H effect 7 M Healthy Young Males. (419)
Cortisol levels
Wingate test, max progressive test Max 5 s Wingate power H = 74% 8 8 Not correlated were measures in the
ergojump test. Had different heritability’s with different tests measuring same
performance measure. Homogenous subject group.
Max Lactate Wingate H = 82%
Delta Lactate during maximal test H = 84%
10-wk isokinetic strength training
HK, MDH, B-HAD N.S. H 5 5 (unrelated) M (505)
oxoglutarate dehydrogenase activity (OGDH) Sig H
Maximal and submaximal treadmill
running economy N.S. H Correlation 8 8 No significant differences in references
to MZ v DZ twins.
VO2 max N.S. H Correlation
Maximal lactate H = 75%
15 weeks of endurance training Skeleteal Muslce HKII, (31%), PFK (37%), LDH (21%),
MDH (31%), &B-HAD (60%)
Sig H 12 M (217)
fiber-type, CK activitiy, N.S. H
15 weeks of high intensity supramaximal
exercise (4–5 times/wk)
ALC, CK, HK, LDH, MDH, OGDH activitiy & PFK:OGDH
activity ratio
Sig H 28 Exercise bouts of 15–90s all
fiber type & anaerobic capacity
A single 90 minute bout of exercise Rest v Ex Adipose LPL activity following
Sig difference btw MZ and DZ 11 10 M Aged 18–27 (458)
Cycle exercise Rest v Ex metabolic rate(VO2) H = 46% at low power. N.S. H at > 6xRMR 37 21 + 31 parent child B (60)
Cycle exercise to max Absolute and BW adjust VO2max Sig H 12 12 M 18–31 years old (177)
Rest v Ex LV internal diameter N.S. H
Rest v Ex Fractional Shortening N.S. H
LV Mass N.S. H when adjusted for BW
165 min submax treadmill test before & after 22
days of 1000 kcal/day overfeeding
Pre v Post change in VO2max Sig H 12 M (524)
93 days of supervised 60min/d
Loss in B.W., fat mass, skinfold, visceral fat Sig H 7 M Healthy young males (59)
Change in fasting TAGs and Cholesterol
Change in VO2max, RER during exercise
1000 kcal of vigorous exercise per day
for 22 days
Pre v Post fasting insulin Sig H 12 M Healthy young males. (522)
Pre v Post delta insulin during OGTT N.S. H
93 days of supervised 60min/d exercise Pre v post fasting insulin and glucose disposal N.S. H, but Sig improvement 7 (390)
116min/day of cycle ergometer for 22days
at 58% max
Pre v Post fat mass N.S. H 12 M Healthy males aged 19.1 yr old. (414)
basal lipogenesis Sig H
Pre v Post insulin stimulated lipogenesis N.S. H
Pre v Post epinephrine and basal lipolysis N.S. H
Pre v Post LPL activity N.S. H
Fat Free Mass Sig H
20-wk cycle ergometer endurance
Pre vs. Post epinephrine lipolysis Sig H. 8 B 4 male and 4 female. (133)
Basal lipolysis N.S. H
Single 90 min bout of exercise LPL activity More Sig in MZ than DZ 11 10 M (458)
116 min/day of cycle ergometer for 22days
at 58% max
Total Cholesterol Sig H 12 M (134)
LDL Cholesterol
HDL Cholesterol
93 days of supervised 60min/d
Total cholesterol Sig H 7 M Male, young and healthy. ~93000
total calorie deficit. Significant within twin effects.
LDL Cholesterol
Cholesterol to HDL ratio
116min/day of cycle ergometer for 22days
at 58% max
Baseline RMR Sig H 12 M (415)
Baseline thermic effect of food
Pre v Post plasma T3, T4, and FT4 Sig H (except for T3)
93 days of supervised 60min/d
Pre v post RMR, Thermic effect of food, Sig H 7 M Healthy young males (523)
Thyroid hormones
14 weeks of exercise training Cardiac Size N.S. H 28 10 + 12 siblings B No genetic effect on heart size pre or post exercise

Table 5

Studies with Twin Correlations that are corrected for PA levels or Unique Environmental
Effects (twins may not be discordant for PA).

Outcomes H-effect PA Effect MZ (n) DZ(n) Sex PA Measurement Comments Ref
Weight gain ↓ correlation in inactive 1571 3029 B Questionnaire of Physical activity levels at
Finnish twin study. At all activity levels MZ twins
had greater hereditability than DZ twins.
Waist Circumference ↑ 2.5 cm in low PA twin 287 189 Questionnaire in 1998 and 2002. Only
looking at leisure and occupational PA
No analysis for discordant PA. If twins
had large genetic susceptibility then low PA resulted in larger increase in WC
Waist Circumference 76(M)–77(F)% 21(M)–22(F)% 71 75 B Questionnaire African Americans aged 22–88 from
Carolina African American Twin Study of Aging. All effects are unique environemental
not just PA levels.
Waist-Hip Ratio 59(M)–56(F)% 36(M)–38(F)%
BMI 89(M)–73(F)% 11(M)–27(F)%
Discordant for BMI by at least 3. N.S. 23 B Interviews and Questionnaire for PA No significant effects of PA on the discordance of
overweight prevalence.
Discordant for obesity ↓ fitness (8%) and activity (15%) in Obese
14 M VO2max and Baecke leisure time PA From FinnTwin study – obese also had lower
adipose mitochondrial gene expression
Subscapulantrice ps BF ratio 24% 265 M “crude” measure of PA PA was inversely related to adjusted
waist c i re umf ranee
waist circumference 46%
Diastolic BP 35% 5% 71 104 B Interview: Lifetime exercise divided into
power, aerobic, or other
Aerobic exercise in adolescence lifetime
high intensity aerobic associated with low diastolic BP throughout life (mean age of
50 at study time).
Aerobic exercise amount 44% N.S.
“Augmentation index”, or systemic
arterial stiffness
↑ Sig in high genetic risk group when
53 262 + 54 singlet ons F Questionnaires (209)
MZ subjects that are discordant for hypertension Hypertensive twin ↑being inactive (after
military service)
281 M Survey from the National Heart, Lung, and Blood
Institute (NIH)
Twins whom are veterans of WWII aged 55–66.
Surveyed at time of entry to military and time of study.
HDL cholesterol Correctin g for genetics prevent correlatio n ↑correlation btw exercise and HDL 179 255 F Questionnaire (one question about PA) Kaiser Twin Registry in Oakland, CA. aged
Lumbar spine disk degeneration 74% N.S. 172 154 B Interviewed about weight bearing
No effect of adjustment for exercise on
lumbar or cervical disk degeneration
Lumbar spine disk degeneration 73% N.S.
total body BMC (DEXA) 1.2% less in inactive twin/hour of less exercise 30 26 Questionnaire for weight bearing
Associated was not present in
pre-pubescent twins
leg BMC ↓ 1.4% in inactive
Spine BMC ↓ Sig in inactive
BMD N.S. 122 93 F 12 month recall questionnaire for sport activity 10–26 yr old from Australian twin
Smoking Likelihood at follow up (about 4 yrs) ↑ 3.36x for inactive twin to be regular
97 339 B Survey for twins discordant for PA (3 categories
used) at baseline
Adolescents from a Finnish Twin Registry. Did not
analyze by zygosity.
Discordant Prevalence of non-Alzheimer dementias ↑Risk Correlated with Physical inactivity 106 Questionnaire administered 30 years before Swedish twin registry average age of first
questionnaire was 48
Twins discordant for chronic fatigue syndrome
– cognitive functioning tests pre-post max test
Cognitive tests did were N.S. No relationship to chronic PA was made 21 B (19 M, 2F) Acute Cycle ergometerto max Exercise caused no change in cognitive functioning
Various Cognitive Functions >15% <80% 1,432 1,715 + 268,496 siblings M Cycle W max/kg PA effect for all non-shared environmental

Table 6

Genetic Influence on Physical Activity, Exercise Levels, and Exercise Capacity. B = both;
DZ= dizygotic; F = female; H = heredity effect; M = male; monozygotic; N.D. = not
determined; n = number of subjects; Y = young

PA Measurement H-effect Unique Environmental Effect (unless noted) MZ (n) DZ (n) Sex Comments Ref
Isometric knee extensor strength 56% 42% 206 228 F PA effect is non-shared environmental
effects. All older women subjects (63–76 yr/old). New non-shared environmental
effects responsible for differences at follow up.
leg extensor power 67% 33%
isometric knee extensor strength (at 3 years follow
58% 15% 149 164
leg extensor power (at 3 years follow up) 48% 11%
Elbow flexor muscle cross sectional area 43% 6% 25 16 M Subjects were young (22.4 yr old)
Caucasians from Belgium. Remaining variation accounted for by MCSA and environmental
Elbow flexor eccentric strength 47% 20%
Elbow flexor isometric strength 32% 1%
Leg extensor power 32% 4% 101 116 F Finnish Twin Study on Aging. Subjects
63–73 yr old.
Leg extensor strength 48% 52%
Isokinetic lifting 60% 35% 122 131 M Finnish twin study. (446)
Psychophysical lifting 33% 49%
Isometric trunk extensor endurance 5% 61%
Questionnaires based on country. >60min of 4
MET activity = exerciser
26.5–70.5% 29.2–51.9% 13676 23375 B Twins from 7 different countries. Australia had
lowest genetic – highest unique environmental. UK females had highest
SportsMET (>4MET activity in last 3
79% in Y, 41% Mid 21% in Y 57% Mid 69Y, 93M 88Y, 105M B Young and middle age subjects (122)
Questionnaire Physical activity amount =
60–150 minutes a week
MZ = 45% DZ = 30% MZ = 55% 1003 386 B Twins from the Washington State twin
registry. The more PA you undergo the less the genetic influence there is.
Questionnaire Physical activity amount > 150
minutes a week (current guidelines)
MZH=31% DZ= 25% MZ = 69%
Baecke and exercise Questionnaire 40–65% 60–35% 359 232 M Nationwide Swedish twins. No shared environmental
Sport participation between ages of 13–16 0% 16–22% 1095 1533 B Dutch population. Does not include common
Sport participation between ages of 17–18 36% 17%
Sport participation after age of 18 85% 15%
Adulthood exercise 43% 26% from competitive sports 121 M Finnish twin study. Also found that sports from ages
12–18 was a predictor of adulthood exercise.
Respiration chamber (doubly labeled H2O)
activity-induced energy expenditure
8% 30% 12 8 B Aged 17–39 yr old. Univariate
analysis using the additive genetic, but excluding the common environmental
Respiration chamber physical activity by
0% 59%
Doubly labeled H2OFree living activity
induced energy expenditure
72% 29%
Free living PA by accelerometer 78% 22%
RMR 3% 38% 62 38 B Aged 4–10. Correlations are
corrected for body weight and do not include common environmental
Total EE by Doubly labeled H2O 19% 23%
Physical Activity energy expenditure 0% 31%
VO2max, Vmax, HRmax 40, 50, 60% N.D. 106 66 B Also 42 brothers included in the study (57)
Fiber Type N.S. N.D. 35 26 B 32 brothers also included MZ twins had
inter-pair correlation, but DZ and brothers suggested strong (but not quantified)
environmental component.
Skeletal muscle mitochondrial activities N.S.
Oxidative to glycolytic ratio 25–50%

As expected many of the tested health parameters had both genetic and
environmental components. In many studies, questionnaires were used to evaluate physical
activity levels, a less than optimal method to collect such data. Thus, while the design
of the studies analyzed was not optimized for elucidating the effects of physical activity
independent of genotype, some cautious conclusions may be made from –, presented

9.4 Important physical activity component to activity adaptation

The data indicate that inactivity increases both visceral and total fat masses
independent of genetic disposition. Additionally, Alzheimer’s and dementia both have a
large physical inactivity component. However, changes in muscle morphology (length,
shortening velocity, of ventricular diameter) do not exhibit compelling genetic
components. Genotype is apparently not a major determinant of the changes in insulin
levels and sensitivity brought about by negative energy balance with exercise (390) (see insulin resistance later in article).

9.5 Important gene component to activity adaptation

In these studies, while physical activity levels themselves exhibit a large
genetic component; it varies tremendously between countries and cultures. In addition to
activity levels, a major genetic component is found for both measures of strength fitness
(muscle strength and power) and in endurance fitness as well as responses (lactate levels,
blood pressure) to exercise. More surprisingly is the minor effect of physical activity on
overall “well-being”, which is in contrast to a number of cross-sectional
studies suggesting that physical activity is strongly negatively correlated with
depression and anxiety. Another surprisingly result is that twins discordant for physical
activity do not differ in generalized bone mass or spinal cord bone mass (542), despite the well-known effects of bed rest and
inactivity on increasing bone loss. These contradictory results may simply be due to the
lack of specific measures of bone mass in the active limbs, or to the variation in types
of load-bearing physical activity, and thus bone health, in the physically active

9.6 Clinical significance

Taken together, data in – provide conclusive evidence
that physical inactivity alone is sufficient to increase chronic diseases and death.
“Together, the 80 monozygotic publications unequivocally show that co-twins with
lower physical activity levels exhibit increased risks for chronic diseases regardless of
genotype. Such data, therefore, empowers physicians and other health care providers to
prescribe physical activity as primary preventative medicine”

10. Variety of training types to primarily prevent disease

Specificity of training (i.e., adaptation to training is specific to the class of
exercise (aerobic vs. resistance) is dogma. For example in 1976, one of us wrote that the
nature of the exercise stimulus determines the type of adaptation (243). One type of adaptation involves hypertrophy of the muscle cells
with an increase in strength; it is exemplified in its most extreme form by the muscles of
weight lifters and body builders. The second type of adaptation involves an increase in the
capacity of muscle for aerobic metabolism with an increase in endurance and is found in its
most highly developed form in the muscles of competitive middle- and long-distance runners,
long-distance cross-country skiers, bicyclists, and swimmers. Further, hypertrophied muscles
of weight lifters did not have the increased mitochondria of aerobic training and that
prolonged daily run training increases mitochondria, but does not hypertrophy the muscles.
Application of the information to elderly individuals is that they must perform both types
of exercise to prevent physical (endurance and strength) frailty.

Recent information expands and emphasizes the specificity dogma. High-intensity
interval training (HIT) (near peak performance for short bursts alternating with longer
periods of low-intensity aerobic activity) has been said to “prove more benefit than
traditional continuous exercise programs in several metabolic, muscular, and cardiovascular
parameters” (278). For example, HIT-walking
resulted in greater increases in VO2peak and thigh muscle strength and a greater
reduction in SBP than moderate-intensity continuous walking in older men and women (375). In contrast, one HIT report indicates that HIT by
untrained men produced greater (VO2max), the same (improvements in oral glucose
tolerance), and less (resting bradycardia, total-body fat percentage, and reducing ratio
between total and HDL plasma cholesterol.) adaptations than in a second group performing
continuous training (384).

11. Diseasome of physical inactivity (35 diseases/conditions)

The term “diseasome of physical inactivity” was presented by
Pedersen (403) to describe a clustering of diseases.
Our article enlarges Pedersen’s cluster to include over 35 diseases/conditions and death,
which constitute most of the remaining article (). (Cross-reference: Muscle as an endocrine organ) Joyner and Pedersen (260) contend that it is a failure of regulation at
multiple levels that causes many common diseases. They further argue that a lack of fluency
to use key physiological concepts (like homeostasis, regulated systems and redundancy) as
major intellectual tools to understand at multiple levels how whole animals adapt to
exercise and maladapt to physical inactivity.

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0003.jpg

Health deficiencies accelerated by decreasing physical activity from higher to lower
levels. Gheorghe Constantinescu generously made original drawing. [Reproduced with
permission from (53)].

12. Inactivity accelerates loss of functional capacities with years of life

12.1 Definitions

Primary aging

Inevitable deterioration of cellular structure and function, independent of
disease (241)

Maximal lifespan

Maximum amount of time one member of a species has been observed to survive
between birth and death

Secondary aging

Aging processes which result from disease, bodily abuse, and/or disuse and
which are often preventable

Life expectancy

Average lifespan of a population

Functional capacity

Absolute maximal value of a function

Relative functional capacity Relative age of functional capacity of an organ
system, an organ, or cell to its lifetime highest value at a given calendar age

12.2 Etiology

Primary prevention

The next quotation is impactful because of its source, a report from top
exercise scientists that was accepted by the top official of the U.S. Department of
Health and Human Services.

The data very strongly support an inverse association between physical
activity and all-cause mortality. Active individuals — both men and women
— have approximately a 30% lower risk of dying during follow-up, compared
with inactive individuals. This inverse association has been observed among persons
residing in the United States, as well as in other countries, older persons (aged 65
years and older), and persons of different race/ethnic groups. In one study of
persons with impaired mobility (unable to walk 2 km and climb 1 flight with no
difficulty), physical activity also appeared to be associated with lower all-cause
mortality rates. (412)

Less physical activity shortens years of life relative to average lifespan

Healthy behavioral choices in Californian Adventists extend life expectancy by
several years, even as much as a decade, (190).
Various reports estimate that higher physical activity levels may extend life expectancy
relative to average lifespan by 2.1 (405), 2.5
(395), 5.1 (men)(181), and 5.7 (women)(181)
yrs for the physically active population.

Another example of lifetime physical activity shortening years lived is the
increased risk of chronic diseases such as type 2 diabetes (See type 2 diabetes later in
article). Diagnosis of type 2 diabetes at the age of 20 yrs is associated with 17.2 and
17.9 yrs of life lost in males and females, respectively (366).

Less physical activity increases percentage of population that is disabled

At the same age for death, the high physical activity group spent less time
disabled than the overall population of men (2.5 vs. 3.0 years), while the low physical
activity group actually spends more time disabled than all men (2.6 vs. 1.4 years)(181). Thus, less lifetime physical activity shortens
years of life. (Cross-reference: Implications of aging and athletics)

12.3 Dose-response relationship between sitting time and prediction of premature

Longitudinal studies

Katzmarzyk et al. (268) reported a
dose-response association existed between sitting time and mortality from all causes and
CVD, but not for cancer, independent of leisure time physical activity in 17,000
Canadians, such that hazard ratio was 1.54 for the greatest sitting time. Dunstan et al.
(151) found that each 1-hour increase in TV
viewing time was associated with 11% and 18% increased risks of all-cause and CVD
mortality, respectively, in 20,000 Australian men and women. Further, all-cause and CVD
mortalities increased 46% and 80%, respectively for TV viewing time >4hr/day as
compared to <2 hrs/day, which were independent of smoking, blood pressure,
cholesterol, diet, waist circumference, and leisure-time exercise.


While light physical activity is associated with rather low-intensity muscle
contractions, it still has favorable improvements on plasma glucose in glucose tolerance
tests (228), and differs substantially from the
absence of muscle activity while sitting The detrimental effects of sitting have been
hypothesized by Stamatakis et al. (489) to occur
in the following sequence of events: excessive sitting lowers skeletal muscle blood
flow, lowering shear stress on vascular endothelial cells,,and decreasing endothelial
nitric oxide synthase (NOS) expression. They also noted that the low-grade inflammatory
marker, CRP was approximately 2 times greater in subjects with >4 hr/day in
screen time, compared to those <2 hr/day. However, two weeks of reduced daily
stepping (286) and 5 days of bed rest (216) do not increase inflammatory markers so CRP is
unlikely to be the first initiating mechanism. Rapid biochemical changes in a rodent
models of sitting, hindlimb unloading, have demonstrated decreases in rat skeletal
muscle protein synthesis rates within the first 6 hrs (54, 357, 507, 529, 550) and loss of insulin-stimulated glucose uptake
into the mouse soleus muscle after 1 day (466).

12.4 Biomarkers of premature death

Low values of functional capacities for maximal aerobic capacity
(VO2max) and for maximal skeletal muscle mass/strength, each alone, are
biomarkers for death as they are associated with shorter life expectancies.

Sedentary lifestyle speeds secondary aging of VO2max by 30 yrs
(illustrated by shifting of age-VO2max relationship leftward in shown example)

As previously discussed, VO2max is a measure of CRF. CRF is a
health-related component of physical fitness defined as the ability of the circulatory,
respiratory, and muscular systems to supply oxygen during sustained physical activity.
While physically active and inactive individuals lose a
VO2max at a similar rate (slope of the curve) due to
primary aging, the inactive individuals have a leftward shift of the curve. For
instance, 80-yr-old, physically active women had VO2max’s that were
equivalent to 50-yr-old physically inactive women. () (503).

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0004.jpg

Best-fit linear lines are shown for aerobic capacities of two cross-sectional groups
(aerobic trained and sedentary) as a function of their increasing chronological age. At
the chronological age of 80 yrs, a horizontal line is extended from the endurance trained
line to the left where it intersects the sedentary line at age 50 yrs. Subjects were women
who had been aerobically trained for at least 2 yrs with road-racing competition (closed
circles) vs. women who were sedentary (open squares) who performed no regular exercise and
had BMI’s <35 kg/m2 (aerobic-trained women were matched across the
entire age range for age-adjusted world-best 10-km running times to ensure homogeneity
relative competitiveness). [Reproduced with permission from (503)].

Low VO2max increases prevalence of death

Convincing evidence exists that lower CRF is associated with increased
mortality in both men and women, independently of other risk factors (79, 96, 277, 312,

An inverse relationship between CRF and death was present with a
cross-sectional comparison between lesser fit men and women with greater fit men and
women showed. When CRF in the second lowest CRF quintile is compared to the lowest
quantile, the risk of all-cause death in the lowest CRF quantile is increased by 39% and
67% in a prospective study of 40,451 men and 12,831 women, respectively (312) ().
Likewise comparing the highest CRF quintile) to the second lowest increased all-cause
death risk by 26% and 28% in men and women, respectively. Thus, comparing the top
quintile to the lowest quintile increased all-cause death risk by 75% and 113% in men
and women, respectively.

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0005.jpg

Relative risk of death as a function of cardiorespiratory fitness (CRF) or change in CRF.
Relative risks of all-cause mortality by (CRF) quintiles for 12,831 women aged
20–100 years without cardiovascular disease (CVD) or cancer in the Aerobics Center
Longitudinal Study. Relative risks were adjusted for age, year of examination, body mass
index, smoking status, abnormal electrocardiogram, hypertension, diabetes,
hypercholesterolemia, and family history of CVD. [Reproduced with permission from (312)].

Changes in CRF level result in a similar change in mortality risk. Men (n =
9777; aged 20–82 at baseline) had two CRF assessments with an average period of
4.9 years between first and second examinations (44, 312). The men were then followed
an average of 5.1 years for mortality after the second CRF test. Men who were unfit at
both visits had the highest death risk while men who were fit at both visits had the
lowest death risk. Remarkably, men who changed fitness status between the two CRF
assessments had intermediate risk of death between the fit-that-stayed-fit group and
unfit-who-stayed-unfit group. Fit-who-became-unfit between assessments had an increased
risk of death. Unfit-men who-became-fit between CRF assessments decreased their risk of
death. Erikssen et al. (165) found similar trend
and concluded that even small improvements in physical fitness are associated with a
significantly lowered risk of death.

Sedentary lifestyle speeds secondary aging of skeletal muscle power by 24 yrs
(illustrated by shifting of age-power relationship leftward in shown example)

Low muscle strength has been inversely associated with all-cause-mortality in
thirteen studies using subjects > 65 yrs of age (see (451) for refs). While, aging causes a similar rate of loss in power
between 40 and 90 yrs of age, untrained, healthy men generate 35% less average power
than male competitors at a World Masters Weight-Lifting Championships (402) ().
Recreational resistance training results in strength gains ranging from 10%–257%
after 9–52 weeks of 2–3 days/week resistance training in subjects mainly
aged between 60–80 years of age (252),
however a cross-sectional study spanning 20–80 yrs of age in recreational
weight-lifters is not available to our knowledge. (Cross-references: Influence of
exercise on protein and amino acid metabolism; Physical activity and skeletal muscle

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0006.jpg

Best-fit linear lines are shown for power of two cross-sectional groups (strength trained
and sedentary) as a function of their increasing chronological age. At the chronological
age of 80 yrs, a horizontal line is extended from the power-trained line to the left where
it intersects the sedentary line at age 56 yrs. The cross-sectional strength-trained
subjects are shown in closed circles and sedentary in open circles. [Reproduced with
permission from (402)].

12.5 Mechanisms

Cardiovascular system

According to Blair and co-authors (313), several possible biological mechanisms exist for the risk reduction of
all-cause mortality in individuals with higher CRF. Higher CRF is associated healthier
values for risk factors including insulin sensitivity, blood lipid and lipoprotein
profile, body composition, systemic inflammation, blood pressure and the autonomic
nervous system functioning.

Evolutionary origin

Maximal functional capacity defines the upper limit of a cell, tissue,
system, or whole body to maintain homeostasis to stress. Hayflick (226) and others argue that greater functional capacity in vital
organs ensures survival, reproductive success, and thus is favored by natural selection.
Hayflick lists some stresses that higher capacities in organ systems would be more
likely to favor natural selection as

…more efficient healing process, faster sensory responses, or
greater strength or speed to avoid predation or natural disasters, finding food, and
surviving disease, accidents, and environmental extremes. The favored animals will
have developed redundant capacity, or greater physiological reserve, thus increasing
chances for survival to reproductive success. (226)

In an extreme stress, such as needing maximal caloric expenditure (reflected
in VO2max) or skeletal muscle strength, animals whose vital systems have the
largest redundant functional-capacity would be better able to survive the stress. Thus,
the ability to adapt to and develop greater physiological capacity in response to
repeated stressors (i.e. physical activity) was likely a consequence of natural

12.6 Clinical significance

Low CRF (VO2max) and handgrip strength predict the risk of impending
death. To minimize the all-cause death risk, lifelong efforts, starting in youth, are
needed to develop high CRF and skeletal muscle strength within the limitations of one’s
inherited genes. Slowing of secondary aging of CRF and strength functional capacities can
delay the age for inevitable threshold of frailty due to primary aging. A more detailed
coverage of inactivity and aging is given in our review (50).

13. Prevention of death by primary prevention of physical inactivity

13.1 Etiology

Blair et al. (45) first showed in 1989
that an asymptote exists between metabolic equivalents (METs) and age-adjusted mortality
rates. Mortality was independent of MET values > ~9 METs in women and
>~10 METs in men, but increased when lower than these values.

Kokkinos and Myers found an identical trend in 15,000 older veterans () (278). An
age-related threshold for mortality risk reduction at 4 to 6 METs and an asymptote
occurred at ~9 METs for women and ~10 METs for men (MET values are multiples
of resting metabolic rate).

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0007.jpg

Mortality risk at different exercise capacities. Significant reductions in mortality do
not occur <4 metabolic equivalents of resting metabolism (METs), become less at
~4 to 6 METs and an asymptote occurring at ~10 METs in 15,000 U.S. veterans
of wars. [Reproduced with permission from (278,

, shows 20% increase in mortality
exists for an individual when maximal exercise MET values grouped between 4.1–6.0
METs fall into 2.1–4.0 MET group, with no further increase between groupings of MET
values <2.0 METs and 2.1– 4.0 METs (278). This suggests that a threshold at around 4.0 METs below which, no further
increase in mortality exists. Further, an asymptote around 9.0–10.0 METs indicates
that no differences in mortality risk were reported in comparisons among the higher MET
ranges of 10.1–12.0, 12.1–14.0, and >14.0.

Cautionary statements are necessary though. Maximal MET values decrease
~10%/decade with aging, in part due to decreased physical activity levels. Thus,
physical activity levels need to be maintained or increased to remain in or near to the
asymptotic region (>9 METs) as long as possible with aging..

13.2 Clinical significance

Primary prevention of death (shortening of life expectancy) is possible by
increasing CRF.

14. Metabolic syndrome (MS)

All risk factors for MS are exasperated by sedentary lifestyle (). In other words, physical inactivity is a primary
cause of MS risk factors by virtue of its being upstream to the common MS risk factors.
Alternatively, risk factors for MS are secondary to sedentary lifestyle. Consequently,
increased physical activity is primary prevention of MS. (Cross-reference: Metabolic
syndrome: Impact of lifestyle)

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0008.jpg

Physical inactivity is an actual cause of premature death by interacting with other
environmental factors to increase risk factors for metabolic syndrome, which, in turn
produces two “leading causes” of “premature death” (type 2
diabetes and atherosclerosis). Primary prevention of physical inactivity is shown by
physical activity inhibiting physical inactivity.

14.1 Disease definition

MS is currently defined as a cluster of three of five risk factors for CVD and
type 2 diabetes, which tend to cluster together in the same individual () (6). Four
of the five factors have drug treatments in attempts to normalize them, and include
elevated triglycerides, reduced HDL-cholesterol, elevated blood pressure, and elevated
fasting glucose. The fifth factor, elevated waist circumference (as a marker of elevated
visceral obesity) does not have as an effective drug treatment. Three abnormal findings
out of the five risk factors indicate that an individual has MS. In addition, MS is
associated with increased risk of certain forms of cancer, polycystic ovarian disease,
nonalcoholic fatty liver disease, and neurodegeneration (39).

14.2 Etiology

The total number of U.S. adults who have MS ranges from 77–86 million
(34.3%–38.5% of total age-group) (187). A
Joint Scientific Statement indicates that patients with MS have twice the risk of
developing CVD and type 2 diabetes, respectively, over the next 5 to 10 years, as compared
to individuals without MS (6). Physical inactivity
has been shown to be an important risk factor of MS (38, 186, 296, 560). The proportion of
sedentary time, determined by accelerometry was strongly related to metabolic risk,
independent of physical activity (22).

14.3 Mechanisms

A 2009 Joint Scientific Statement from the American Heart Association states,
“Most persons with the metabolic syndrome have abdominal obesity and insulin
resistance. Both of the latter conditions appear to contribute to the development of
metabolic risk factors, although the mechanisms underlying these contributions are not
fully understood (6).” However, it is
understood that physical inactivity is a primary causal mechanism of every MS risk factor
– dyslipidemia, hypertension, hyperglycemia, visceral obesity, prothrombsis, and
pro-inflammatory events ().

Several risk factors for MS are associated with physical inactivity, including
low-grade inflammation and impaired metabolism (403, 404). Conversely, prevention of
physical inactivity through physical activity improves inflammatory markers by reducing
resting CRP, interleukin-6 (IL-6), and tumour necrosis factor-α concentration
(403). On potential mechanism is highlighted by
Pedersen (404) who has put forth the hypothesis
that the muscle secretome (termed myokines) is involved in mediating some of the health
effects of regular exercise, in particular chronic diseases associated with low-grade
inflammation and impaired metabolism, as well as the brain. For example, contracting
skeletal muscle during exercise produces interleukin-6, which has anti-inflammatory
properties (490). Cross-reference: Muscle as an
endocrine organ)

14.4 Clinical significance of primary prevention of MS

Physical activity is primary prevention for every major MS risk factor. In
addition, Bankoski et al. (22) have results that
led them to suggest that individuals >60 yrs of age may benefit from reducing total
sedentary time and avoiding prolonged periods of sedentary time by increasing the number
of light physical activity bouts during sedentary time.

15. Presentation strategy for diseases composing MS

Each risk factor for MS and chronic diseases resulting from MS will be
individually considered next.

16. Obesity

16.1 Disease definition

The CDC defines overweight for adults as BMIs of 25.0–29.9; obese class
I as 30.0–34.9 BMI; obese class II of 35.0–39.9 BMI; and obese class III
>40.0 BMI. A future auxiliary definition will likely include waist circumference as
a proxy for intra-abdominal adipose tissue since all fat is not equally unhealthy.

Etiology 45% of the U.S. adult population was estimated to be
overweight or obese in 1960–1962. Overweight and obesity began a continual rise in
U.S. adults, aged 20–74 yrs, in the 1980’s. The percentage of overweight and obese
were 45%, 47%, 56%, 65% and 66% in survey years 1960–62, 1976–80,
1988–94, 1999–2000, and 2003–04, respectively, with men ~10%
higher than women (87, 387); (). A recent
publication establishes that 68% of U.S. adults in 2007–2008 are overweight and
obese (182).

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0009.jpg

Overweight and obese, by age from 1960–2006. Modified from CDC website (87).

16.2 Misconception that obesity is independent of physical inactivity

The next sections document historical declines in physical activity, putatively
reflecting increases physical inactivity.

16.3 Caloric expenditure from physical activity has decreased historically

Caloric expenditure of modern day hunter-gatherers and U.S. Amish vs.

The modern hunter-gatherers’ daily estimated energy expenditures for physical
activity are at least 600 kcal more than the average U.S. sedentary adult of today, as
documented in column labeled “EE PA” () (385). The authors of the
data in commented, “The systematic
displacement from a very physically active lifestyle in our natural outdoor environment
to a sedentary, indoor lifestyle is at the root of many of the ubiquitous chronic
diseases that are endemic in our culture” (60). Astrand and Rodahl have made a similar comment,

Close to 100 percent of the biologic existence of our species has been
dominated by outdoor activity. Hunting and foraging for food and other necessities
in the wilds have been a condition of human life for millions of years…there
is obviously no way to revert to our natural way of life…but with insight
into our biological heritage we may yet be able to modify our current life,
Knowledge of the function of the body at rest, as well as during exercise under
various conditions is important as a basis for an optimization of our
existence” (17).

Table 7

Calories expended by physical activity: Hunter-gatherer vs. Moderns

Species Sex Weight (kg) RMR (kcal) TEE (kcal) Ratio (TEE/RMR) EE PA (kcal) Day range (km)
Fossil hominids
Homo habitus 48.0 1404 2387 1.70 983
Homo erectus 53.0 1517 2731 1.80 1214
Homo sapiens 57.0 1605 2880 1.80 1284
Modern hunter-gatherers
Kung M 46.0 1275 2178 1.71 903 10
F 41.0 1170 1770 1.51 600 8
Ache M 59.6 1549 3327 2.15 1778 16
Acculturated modern humans
Homo sapiens (sedentary M 70.0 1694 2000 1.18 306 2.4
office worker F 55.0 1448 1679 1.16 231 2.4
Homo sapiens (runner) 70.0 1694 2888 1.70 1194 11

shows that agrarian Amish men
and women undertake 900 and 700 calories worth of daily physical activity, (439). They eat a typical American dieting terms of
macronutrients consisting of meat, potatoes, gravy, cakes, pies, and eggs (439). Nonetheless, only 25% and 27% of these Amish
men and women, respectively, are overweight; and 0% and 9%, respectively, are obese
(439). Several simple observations give rise
to conclusions that the lower physical activity levels of modern inactive humans
contributes to the obesity epidemic more so than an increase in caloric intake. Agrarian
Amish physical activity expenditures exceed modern sedentary by at least 600 kcal/day
(). If modern caloric intake remained
unchanged then on average each individual would have a positive energy resulting in 73
pounds of fat/year. Clearly this is untrue and therfore caloric intake must have
dropped. However, if the modern population had a decrease in caloric intake of more than
600 kcal/day then obesity rates between Amish and the general population would be
similar, which is also untrue. Thus, while caloric intake has dropped between 0 and 600
kcal/day in the general population it is the lack of 600 kcal/day of physical activity
has led to a large discrepancy in the obesity rates between the modern general
population and Amish societies.

Modern human caloric expenditure is less than free-ranging mammals

Compared to other free-ranging mammals, Hayes et al. (225) calculate that sedentary humans have a significantly lower
level of relative physical activity-induced energy expenditure. However, highly active
humans have relative physical activity-induced energy expenditure that nears that of
other free-ranging mammals ().

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0010.jpg

Human caloric expenditure for physical activity in non-athletes is much lower than
physically active populations. The y axis is the ratio of Activity Energy Expenditure
(AEE) /Resting Energy Expenditure (REE). AEE = free-living energy expenditure –
(diet-induced energy expenditure + REE). Data are presented for various human groups
(non-athletes living in developed nations, military trainees, individuals from rural areas
engaged in high levels of physical activity, and athletes in training) on the x axis. Each
bar is a single subject. Non-athletes in developed nations have AEE/REE ratio of =
~0.5, which is equivalent to PAL of ~1.67). [Reproduced with permission from

Decreases by physical activity type in past few decades: U.S.

A misconception is that leisure time physical activity reflects directional
trends of all types of daily physical activity. Brownson et al. (67) reported the following trends in U.S. (up to 50 years when
possible) according to physical activity type: relatively stable or slightly increasing
levels of leisure-time physical activity. However, declines occurred in work-related
activity, transportation activity, and home-related activity as well as an increase in
sedentary activity. Therefore, overall trends for all physical activity types were for
declining caloric expenditure by physical activity in recent decade(s).

Decreases by physical activity type in past few decades: China

James (256) shows that transfer from
working in the field in China to city work would drop caloric expenditure by ~315
kcal/day (men) and ~375 kcal/day (women). James comments,

…these calculations are set out to illustrate how foolish it is to
focus on only one of the two parts of the energy balance equation. The calculations
also illustrate the magnitude of the required drop in intake, given the
transformation in our working conditions” (256).

Further, instead of walking to fields, motorized transportation is taken,
reducing caloric expenditure by an additional ~200 kcal/day. James concludes,

“Thus, intakes may need to fall by 400–800 kcal/day for
each Chinese adult as their working and living conditions change, and the physical
revolution transforms working conditions and transport, with city living and home
entertainment with television and cinema viewing taking over from the major
sustained demands of an agricultural life” (256).

The misconception of “overnutrition” is due to a widening
positive caloric balance due to food intake not falling calorie with calorie to the
decline in caloric expenditure (PubMed cites >100,000 papers with the term

Caloric cost of engineering physical activity out of lifestyle

Energy expenditure was significantly greater when daily domestic tasks were
performed without the aid of machines or equipment. An estimated 110 kcal/d was
estimated to be expended by the combined impact of domestic mechanization (304) (). The annualization of 110 kcal/day is the caloric equivalent of 11.5 pounds of
fat/yr. Levine and co-authors concluded, “the magnitude of the energetic impact
of the mechanized tasks we studied was sufficiently great to contribute to the positive
energy balance associated with weight gain” (304).

Table 8

Estimation of caloric cost of mechanization of daily living

Active activity Calories used Sedentary activity Calories used
Hand clothes washing 45 Machine clothes washing 27
Hand dish washing 80 Machine dish washing 54
Walk to work 83 Drive to work 25
Stair climbing 11 Elevator 3
Total for active 219 Total for sedentary 109

We followed Levine’s model and calculated an annualized loss of 64,349
calories (caloric equivalent of 18.4 pounds of fat in one year) would not be expended
when walking/standing is selected out of lifestyle in our hypothetical model ().

Table 9

Estimation of caloric cost of removing walking/standing from daily living

Active activity Calories used Sedentary activity Calories used
Walk up one flight of stairs 4 Take escalator up one flight 0.1
Park and walk into fast food restaurant 23 Sit in car for 10 min in a drive-through lane at
Walk dog for 30 min 125 Let the dog out the back door 2
Stand for 30 min of phone calls 20 Recline for 30 min of phone calls 4
Walk into gas station to pay 5 Pay at pump 0.6
Walk 1 min to colleague & stand to talk to them for 4
6 Send e-mail to colleague 2
Walk length of two football fields parking away from
10 Drive around until a parking space opens near store’s
Total for active 193 Total for sedentary 16.7

Alternative interpretation that physical activity has not declined

Westerterp concluded,

“Physical activity energy expenditure, as measured with doubly
labeled water (DLW), has not declined since the start of the obesity epidemic in the
1980s (554)… it is unlikely that
decreased expenditure has fuelled the obesity epidemic.”

Our view of the above quotation follows. Indeed, DLW estimates of energy
expenditure determined between 1988 (555) and
2006 (554) did not significantly differ.
However, from ~1980 to 1988 the increased prevalence of obesity was already
occurring and the slope of the increase remained unchanged through 2006 (). The unchanged slope suggests that whatever was
responsible for the increasing prevalence of obesity was maintained, not increased or
decreased through 2006. Thus, physical activity levels may have been altered downward
prior to 1988 and maintained from 1988–2006 at their low levels, which could be
one possible explanation for the inconsistency between the DLW results and lack of
change in physical activity levels

16.4 Primary prevention of total-body fat gain by physical activity

It is preferable to avoid, in the first place, the excess weight gain that
leads to overweight and then obesity…A major emphasis on obesity prevention is
needed in the population at large to prevent the development of obesity in those adults
who are still in the normal weight range and in successive generations of children and
adolescents during development. Treatment will continue to be of critical importance,
but treatment alone cannot curb the epidemic…prevention has not been the primary
focus (292).

Mimimal research exists on preventing weight gain.

Primary prevention is demonstrated by one human study. A threshold of
~60 minutes a day of moderate-intensity activity throughout a 13-yr study was
needed to gain <2.3 kg in 34,079 healthy US women consuming a usual diet. In a 3-yr
sub-study, the only group having significantly less weight gain than other groups was
women whom fit all 3 of the next criteria: BMI < 25, moderate-intensity exercise
>60 min/day, and < 64 yrs of age (314).

Primary prevention of further weight gain in already overweight to obese
individuals was accomplished with 8 months of low volume-moderate intensity activity
(caloric equivalent of walking 12 miles/wk at 40–55% of VO2max), while
high-volume (caloric equivalent of jogging 20 miles/wk at 65–80% of
VO2max) decreased total fat mass by 4.8 kg (480)

Primary prevention of weight regain was calculated retrospectively, after 12
months in previously obese female, to be 80 min/day of moderate activity, 35 min/day of
vigorous activity, or 0.011 kcal physical expenditure/kg body weight/day (461). Maintenance of a 10% reduced body weight in
humans with BMIs >30 is associated with a significant decrease in total energy
expenditure of ~300–500 kcal/day greater than that predicted by changes in
body mass and composition, which is due predominantly to increased work efficiency of
skeletal muscle at low work intensities (203).

Joyner and Pedersen (260) present
another example. Low prevalence of obesity has been related to poor economic conditions.
Collapse of the Soviet empire in at the end of the 1980s led to decreased food
availability, increased physical activity and ~50% decrease in adult obesity
prevalence in Cuba (441). Upon economic recovery,
obesity rose 50% from 1993 to 1996.

16.5 Preferential decrease in visceral adipose tissue (VAT) by exercise

Primary prevention of VAT obesity by physical activity has been demonstrated in
numerous human studies. Physical training of T2D patients produced a greater loss in VAT
(48%) than subcutaneous adipose tissue (SAT) (18%), did not significantly affect body
weight (360). Ross et al. (447) reported that exercise without weight change in
obese men reduced VAT more than SAT. Likewise, a greater percentage loss in VAT percentage
than in body weight occurred after 12 months in a moderate-intensity exercise intervention
study of sedentary, overweight, postmenopausal women. VAT loss was exercise dose-dependent

A 6-month study examined the dose-response relationship for exercise volume-VAT
mass in men and women whose BMI’s ranged from 25–35 (479). Low volume-moderate intensity (caloric equivalent of walking 12
miles/wk at 40–55% of VO2max) was sufficient to prevent any further
gains in VAT mass, while high-volume, high-intensity activity decreased VAT by 6.9% ().

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0011.jpg

Gain by visceral and abdominal fat depots in non-exercising group while 6 months of
exercise training produced loss in these fat depots. Data are presented as change in A)
visceral abdominal fat, B) subcutaneous abdominal fat, and C) total abdominal fat on the y
axis. Four exercise levels are given on the x axis; they are 1) Control (no exercise); 2)
Low-amount, moderate-intensity exercise (caloric equivalent of walking ~12 miles/wk
at 40–55% of peak oxygen consumption); 3) low-amount, vigorous-intensity exercise
(same amount of exercise as group 2, but at 65–80% of peak oxygen consumption); and
4) high-amount, vigorous-intensity exercise (caloric equivalent of jogging ~20
miles/wk at 65–80% of oxygen consumption). [Reproduced with permission from (479)].

Remarkably, the non-treatment group (no exercise) had an 8.6% increase in VAT.
Extrapolated to 10 years, this would have been a 172% increase in VAT. Kraus et al. (482) later wrote about the non-exercise group,
“current levels of physical activity may be so low that significant metabolic
deterioration occurs in numerous health-related parameters in as little as 6 months of
continued inactivity.” The study provides the evidence that a primary cause of VAT
obesity is lack of exercise and that primary prevention for the expansion of VAT is
physical activity ().

16.6 Primary prevention of inactivity prevents obesity with predisposed obesity

Sedentary lifestyle reveals an obesity phenotype that is primarily prevented by
enhanced physical activity.


The 16% of sedentary adults who are homozygous for the risk allele of AA in
rs9939609 in the fat mass and obesity-associated (FTO) gene weighed
~3 kg more and had 1.67-fold increased odds of obesity when compared with those
not inheriting a risk allele (191). Physically
inactive homozygous risk A-allele in rs9939609 carriers had a 2 kg/m2 greater
BMI compared with homozygous T-allele carriers in a cross-sectional study of 17,000
Danes (14). A second study replicated the primary
preventative effect of physical activity. Adolescents meeting the daily physical
activity recommendations overcame the effect of the FTO rs9939609 AA
polymorphism on obesity-related BMI, body fat, and waist circumference traits seen in
sedentary subjects (450). High physical activity
levels in additional studies were associated with attenuated BMI and waist-circumference
obesity traits for two additional FTO polymorphisms [rs1861868 (422) and rs1121980 (543)]. Women with the FTO allele rs8050136 only have obesity
risk if they are less active (5). In summary then,
physical inactivity is required to elicit the phenotype of obesity with polymorphisms
predisposing to obesity for the human FTO gene.


Obesity is primarily prevented in at least two genetically modified, obese
rodent models by allowing natural, instinctive voluntary running. Voluntary running
prevented obesity and its comorbidities [T2D and non-alcoholic fatty liver disease] with
no significant reductions of food intake in cholecytokinin-1 receptor (OLETF) rats
having a mutant cholecystokinin gene (37, 355, 429,
470). Mice lacking expression of the
melanocortin-4 receptor (MC4-R) exhibit maturity-onset obesity with hyperphagia,
hyperinsulinemia, and hyperglycemia, that is prevented by providing access to wheels for
voluntary running (224). Lack of voluntary wheel
running reveals the obesity phenotypes.

16.7 Mechanisms

Physical inactivity, as one of the two components in the caloric balance
equation, is an actual cause of positive caloric balance, i.e., obesity. The most
effective control of obesity is primary prevention of physical inactivity by moderate
levels of physical activity, rather than secondary or tertiary prevention of obesity
associated co-morbidities.

16.8 Clinical significance

Physical inactivity is a primary cause to VAT and whole-body obesities. Primary
prevention of obesity is possible today for almost all able-bodied individuals able to
exercise. According to the CDC primary prevention of overweight/obesity would reduce risks
for coronary heart disease, T2D, hypertension, dyslipidemia, stroke, non-alcoholic fatty
liver disease, gallbladder diseases, sleep apnea and respiratory problems, osteoarthritis,
gynecological problems (abnormal menses, infertility), endometrial, postmenopausal,
breast, prostate, and other cancers, and premature death (89).

17. Inactivity fosters obese co-morbidities

17.1 Obesity co-morbidities

Risks for the following conditions increase with physical inactivity: Coronary
heart disease, T2D, cancers (endometrial, breast, and colon), hypertension, dyslipidemia
(for example, high total cholesterol or high levels of triglycerides), stroke, liver and
gallbladder disease, sleep apnea and respiratory problems, osteoarthritis, and
gynecological problems (abnormal menses, infertility).


A recent systemic review by Fogelholm (185) of 36 papers made the next conclusions for the lowering of disease risk
with physical activity in obese individuals (conclusions may not apply to BMI
>35). Poor fitness or low PA in physically unfit individuals is a greater
all-cause and cardiovascular mortality risk than obesity in physically fit individual
(185).” A study published since the
above review essentially concurs with the review by its conclusion made from veterans
population that overweight and obese men with moderate CRF fitness had mortality rates
similar to those of the highly fit normal-weight reference group (334).

17.2 Clinical significance

Physical inactivity is a cause of some obesity co-morbidities. Thus, even if
primary prevention for the loss in body fat fails, primary prevention of some, but not
all, of obesity’s co-morbidities is possible with physical activity.

18. Insulin sensitivity/resistance

18.1 Etiology

A summary of the medical literature describing U.S. population-based data on
the incidence of 54 endocrine and metabolic disorders in the United States found that the
prevalence of impaired fasting glucose and impaired glucose tolerance was 26% and 17%,
respectively (202). Both of these conditions
increase risk for the development of type 2 diabetes.

18.2 Insulin sensitivity

How successful blood glucose is lowered by blood insulin

18.3 Insulin resistance

Diminished ability of skeletal muscle and liver cells to respond to the action
of a given dose of insulin by transporting glucose from the bloodstream into these
tissues, or by reducing glucose production, respectively (B to D in )

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0012.jpg

Insulin secretion is presented as a function of insulin sensitivity. Insulin secretion
rises as insulin sensitivity falls when physically active individual (point A) becomes
sedentary (point B). A failure of insulin secretion to compensate for fall in insulin
sensitivity is noted when both insulin secretion and insulin sensitivity decline from
point B to point C, indicating prediabetes. The upper axis for increased and decreased
levels of physical activity implies bidirectionality of the two arrows for glucose
intolerance and insulin resistance. The leftward enlarging two arrows illustrate
increasing glucose intolerance and insulin resistance with 2–3 days of decreased
physical activity. The clinical significant is that low levels of physical activity
produce a permissive environment for prediabetes. In opposite direction, high levels of
daily physical activity markedly diminish the permission state to develop prediabetes. The
distinction between the two arrows is based upon variability in Masters athlete’s
responses to stopping training as shown in
of ref (443) in which 4 subjects had lesser
increases in blood insulin (insulin resistance arrow) at 30 min into an oral glucose
tolerance test as compared to 10 other subjects (glucose intolerance arrow). A continued
decline in both insulin secretion and insulin sensitivity at point D is where overt type 2
diabetes is present. Reproduced with permission from Bergman’s original figure (ref 36).

A hyperbolic relationship between insulin sensitivity and insulin secretion has
been defined as by Bergman (36). illustrates the progression from normal glucose
tolerance (Point A) to overt clinical T2D (Point D), as described in Harrison’s textbook,

glucose tolerance remains to near-normal (NGT), despite insulin resistance,
because the pancreatic beta cells compensate by increasing insulin output (Points A to
B). As insulin resistance and compensatory hyperinsulinemia progress, the pancreatic
islets in certain individuals are unable to sustain the hyperinsulinemic state.
Impaired glucose tolerance, characterized by elevations in postprandial glucose, then
develops (Points B to C). A further decline in insulin secretion and an increase in
hepatic glucose production lead to overt diabetes with fasting hyperglycemia (Point
D). Ultimately, beta cell failure may ensue (418).

We have further modified Harrisons’ redrawing of Bergman’s original figure to
indicate that Point A is representative of a daily physically active human and point B is
an occasionally active human. Based on a number of studies we propose that increases and
decreases in daily physical activity over a time frame of hours to a few days places
subjects between Points A and B. Thus, daily physical activity prevents the progression to
Point B, making it impossible to continue from Point B, to Point C and Point D, overt
diabetes. Therefore, only if continual physical inactivity is present can the progression
to Point C, impaired glucose tolerance, and eventually into Point D, overt diabetes,
occur. As Zimmet astutely and succinctly wrote, “A large proportion of cases of
type 2 diabetes is preventable” (579).

18.4 Impaired glucose tolerance (IGT) may increase cardiovascular disease (CVD)

After adjusting for age and sex, an increased risk of CVD mortality was
observed in those with postchallenge hyperglycemia (PCH) and fasting glucose ≥7.0
mmol/l, with 2-h glucose ≥7.8 and <11.1 mmol/l and fasting glucose
<7.0 mmol/l, or with PCH and fasting glucose <7.0 mmol/l (459).

18.5 T2D was preventable 35–70 years ago

Diabetes prevalence has risen from 1.4% in 1950 to 7.8% in the U.S. (367) and from 1% in 1975 to 9.7% in 2007–2008
in China (576). Zimmet commented, “In
conjunction with genetic susceptibility, particularly in certain ethnic groups, type 2
diabetes is brought on by environmental and behavioral factors such as a sedentary
lifestyle, overly rich nutrition and obesity” (579). We will propose the notion that proper volumes of physical activity would
essentially primarily prevent most of T2D, as illustrated by maintaining at point A in

18.6 Inactivity/exercise rapidly change insulin sensitivity

Reduced activity

LaMonte. Blair, and Church (300)
hypothesized that the most proximal behavioral cause of insulin resistance is physical
inactivity. Highly endurance trained men’s high insulin sensitivity returns to sedentary
levels after cessation of training for 38 hrs (391) or 60 hrs (72) as measured by
euglycemic-hyperinsulimic clamp. Measured 12, 60, and 168 hrs after the last exercise
bout, peripheral tissue glucose disposal dropped from 15.6 to 10.1 to 8.5 ml/kg/min,
respectively, compared to 7.8 ml/kg/min in sedentary subjects (72). Similarly, 14, 38, 86, and 144 hr after the last exercise bout
by endurance trained athletes glucose disposal declined from 9.40 to 7.78 to 6.82 to
7.11 mg/kg/min compared to 6.80 in sedentary subjects (391). Therefore, only days after ceasing exercise training, endurance athletes
the same insulin sensitivity as long-term sedentary subjects. Like humans, rats who
cease 3 weeks of voluntary wheel running drop their submaximal insulin-stimulated
glucose uptake to sedentary values on the 2nd day of no running in skeletal
muscle normally recruited during wheel running (293). Less extreme reductions in physical activity, such as humans decreasing
daily step numbers from 6203 to 1394 for 1 week lead to a 53% increase in the area under
the curve for plasma insulin following an oral glucose tolerance test, a response that
occurs due to reduced peripheral insulin sensitivity (389). Conversely, more extreme physical inactivity such as strict bed rest for
24-hr/day lasting 5 days (216), 7 days (46, 342,
495), and 9 days (7) is also associated with substantial increases in insulin
resistance. Two days of bed rest did not affect insulin resistance (152).

Increasing activity improves insulin sensitivity in muscle

A single bout of muscle contraction increases insulin sensitivity in perfused
hindquarters of healthy animals (242, 255, 434)
and in the whole body of healthy humans (230,
343). Seven days of aerobic training increases
whole body insulin sensitivity in 22- and 58-yr-old men and women (244), 66-yr-old men and women (BMI = 33) (486); 60- to 80-yr old men and women (112), and T2D patients (274,
444). Resistance training also enhances
insulin sensitivity and improves glucose tolerance in a wide range of human subjects
(526). A systemic review of 20 studies found
that supervised resistance training improved glycemic control and insulin sensitivity in
adults with T2D (206).

18.7 Biochemical mechanisms

Exercise-induced glucose uptake into skeletal muscle

A 2009 review wrote, “Within the past 25 years, characterizing the
beneficial interaction between acute exercise and subsequent insulin action has been an
area of much focus; although progress has been made recently, the underlying mechanisms
are still poorly understood” (193).


Independent of insulin action, exercise acts to prevent hyperglycemia by
improving glucose uptake in animal skeletal muscle primarily by independently activating
the translocation of glucose transporter, GLUT4, from intracellular locations to the
plasma membrane of rats (145, 205), and also by increasing transcription in mice
(528) and translation in rats (294) of GLUT4 leading to greater GLUT4 protein


In human subjects, a positive correlation exists between GLUT4 protein
content in the vastus lateralis muscle with insulin sensitivity in both sexes (247). The relationship remained in men after
adjustment for overall adiposity, regional adiposity, and CRF (247). Endurance-trained healthy individuals have higher GLUT4 mRNA
and protein content than do sedentary (245,
467). Physical training also increases muscle
GLUT4 protein and mRNA in patients with T2D (128). GLUT4 transcription is controlled in part by calcium signaling and the
energy sensor 5′-AMP-activated protein kinase (AMPK) during exercise (435, 567,

Skeletal muscle insulin sensitivity with contraction and inactivity

Conversely, much less effort has gone into investigating the mechanisms
through which lack of physical activity decreases insulin sensitivity. Although
low-grade inflammation can worsen insulin resistance in a variety of models circulating
inflammatory markers were unchanged, while insulin resistance increased during 5 days of
bed rest, implying that systemic inflammation is not a mechanism for initial insulin
resistance (216). Reduced mitochondrial content
or dysfunction has also been postulated to cause insulin resistance by leading to an
increased accumulation of lipid intermediates in skeletal muscle (457). The lipid intermediates putatively activate serine kinases
that reduce insulin signaling ultimately leading to reduced insulin stimulated GLUT4
translocation to the plasma membrane. However, the links between insulin resistance and
an accumulation of lipid intermediates are associative at this time, and an increasing
number of reports have found that the relationship does not always hold true (460). Another possibility is oxidative stress.
Anderson et al. (13) report that both acute and
chronic high-dietary fat intake lead to a dramatic increase in the
H2O2-emitting potential of rat or human mitochondria in the
absence of any change in respiratory function, consequently generating a shift to a more
oxidized cellular redox environment that, if persistent, precedes the development of
insulin resistance in skeletal muscle.

Insulin sensitivity in rat epitrochlearis muscle declines at a time (2 days
after stopping 3 weeks of voluntary wheel running) when the mitochondrial marker,
citrate synthase activity, remains unchanged and elevated from the wheel running (293). No differences in skeletal muscle mitochondria
and insulin sensitivity existed between non-obese sedentary controls and hyperphagic,
voluntary running in OLETF rats. Rector et al. (430) suggest a constant caloric overload and expanding adiposity may be the
primary driver to insulin resistance in the OLETF sedentary animal model. Thyfault
(511) suggested “It may be that a
hypercaloric/lipidomic environment plus low energy flux (physical inactivity) is
required to induce skeletal muscle insulin resistance in obesity” (511). Inactive skeletal muscles in physically
inactive rats have insufficient electron transport flux to completely oxidize
mitochondrial intermediates of ß-oxidation, producing lipid toxicity (281, 512).
However, acute exercise prior to insulin stimulation can restore insulin stimulated
glucose transport in muscle from obese Zucker rats (513), without improving signaling through the insulin-signaling pathway. Thus
it appears that contraction induces a robust mitochondrial energy flux increasing in a
coordinated fashion with both β-oxidation and the TCA cycle, that can override
existing perturbations of the insulin-signaling pathway to enhanced insulin-stimulated
glucose uptake in insulin resistant muscle in obese Zucker rats (512). The links between the contraction-induced energy flux and
insulin action are at this time unknown, however according to a comprehensive review of
the topic, the molecule Akt substrate 160 may play an integral role as it is activated
by both insulin and muscle contraction and plays a major role in activation of GLUT4
translocation to the plasma membrane (82).

18.8 mRNA mechanisms

Global mRNA analysis of human vastus lateralis muscle identified 4500
transcripts changing after development of insulin resistance following 9 days of
continuous bed rest in 20 healthy young men (8).
They found that 54% of 162 transcripts in the oxidative phosphorylation pathway decreased.
Vaag and coauthors (8) emphasized that they could
not exclude the possibility that down-regulation of oxidation phosphorylation as well as
other genes may have occurred as a result of – not as a causal factor for –
skeletal muscle insulin resistance during bed rest. Two potential physiological mechanisms
may be decreased capillarization (not determined), as suggested by decreases in both
VEGFα mRNA and PGC1α mRNA, or increased fat accumulation due to decreased
CPT1B mRNA and thus decreased fatty acid oxidation (8). Furthermore, increased reactive-oxygen species generation and endoplasmic
reticulum stress were also identified as potential mechanisms of inactivity induced
insulin resistance (8).

18.9 Clinical significance

Physical inactivity is a primary cause of loss of insulin sensitivity in
skeletal muscle, and thus whole-body. Primary prevention of almost all of insulin
resistance by high levels of daily physical activity is possible for almost all humans up
their seventh decade of life (305). Continued
long-term reductions in physical activity are a primary cause of insulin resistance.

The clinical consequences of insulin resistance, alone, have been delineated by
Reaven (425): Some degree of glucose
intolerance/impaired fasting glucose/impaired glucose tolerance, dylipidemia (↑
triglycerides, ↓ HDL-C, ↓ LDL partical size, ↑ postprandial
accumulation of triglyceride-rich lipoproteins), endothelial dysfunction (↑
nonnuclear cell adhesion, ↑ plasma cellular adhesion molecules, ↑ plasma
asymmetric dimethylarginine, ↓ endothelial-dependent vasodilation), Procoagulant
factors (↑ plasminogen activator inhibitor-1, ↑ fibrinogen), hemodynamic
factors (↑ sympathetic nervous system activity, ↑ renal sodium retention),
markers of inflammation (↑ C-reactive protein, ↑ white blood cell count)
abnormal uric acid metabolism (↑ plasma uric acid concentration, ↓ uric
renal acid concentration), ↑ testosterone (ovary), and sleep-disordered breathing.
By a direct cause of insulin resistance, physical inactivity indirectly, directly, or both
in some cases (endothelial dysfunction) causes all of the aforementioned.

19. Prediabetes

Condition’s definition A person with prediabetes has a fasting blood
glucose level between 100 and 125 mg/dl and/or 2-hour blood glucose between 140 and 199
mg/dl during an oral glucose tolerance test.

19.1 Etiology

It is estimated that 57 million people have prediabetes in the U.S (88). Prediabetes is a condition in which blood glucose
levels are higher than normal, but not high enough to be classified as T2D. Prediabetics
have an increased risk of developing T2D, and T2D’s-associated comorbidities of heart
disease, and stroke.

19.2 Clinical significance

We speculate that physical inactivity is an actual cause of much of prediabetes
cases in those <60 yrs of age. The speculation is based upon the Finnish DPS and
DPP RCTs in prediabetics. However, to our knowledge, no large RCTs have been performed to
test whether a physically active lifestyle over time primarily prevents prediabetes in
healthy individuals as compared to healthy inactive individuals.

20. Type 2 diabetes (T2D)

20.1 Physical activity can reverse prediabetes

While early prediabetes, late prediabetes, and diabetes are in a continuum,
they differ in success of primary prevention by physical activity. For instance, daily
physical can reverse insulin resistance in healthy individuals (points B to A in the
modified Bergman ), and prediabetes (to point
A). However, microvascular (retinopathy, neuropathy, nephropathy) damage in T2D seems to
be non-repairable by physical activity (418).” Thus, the risk of chronic complications that are unable to be
reversed by daily physical activity increases as a function of the duration of
hyperglycemia, many of which maybe present in individuals when finally diagnosed with T2D

20.2 Etiology

Nearly 24 million people in the U.S. are diagnosed with T2D in 2007 (11). Today the number is likely even higher. By 2020
> 50% of Americans could have diabetes or prediabetes, at a cost of $3.35 trillion
based according to new projections by UnitedHealth Group’s Center for Health Reform and
Modernization (533). The estimated lifetime risk
of developing diabetes for babies born in 2000 is 32.8% for males and 38.5% for females,
with Hispanics having the highest estimated lifetime risk (males, 45.4% and females,
52.5%) among ethic groups (366), Remarkably, some
adolescents have been reported to have T2D in the past 5 years, a disease once called
adult-onset diabetes because of its time of onset.

20.3 Primary prevention of T2D – overview

The CDC Website states that progression to diabetes among those with
prediabetes is not inevitable (88). The National
Physical Activity Guidelines Advisory Committee Report (NPAGCR1) (412) states that usage of
physical activity questionnaires in large prospective cohort and cross-sectional
observational studies all show that increased physical activity levels show associations
with reduced risk for developing T2D. A systemic review of follow-up, case–control
or cross-sectional studies by Fogelholm (185)
concludes for individuals with BMI of 25–35 having high BMI even with high physical
activity were at a greater risk for the incidence of T2D and the prevalence of
cardiovascular and diabetes risk factors, compared with normal BMI with low physical
activity. Nonetheless, in men with a BMI of 25 or more, a history of hypertension, a
positive parental history of diabetes, or any combination of these factors, the incidence
of T2D declined by 41% from the lowest to the highest levels of energy expenditure (234) ().

Table 10

Prospective studies implicating physical inactivity as a risk factor in the development
of T2D

Comments Sample size Country of study Reference
↓ Age-adjusted risk of 6% every 500 kcal of leisure
time physical activity
5990 men US (234)
↓ Relative risk of 60% between moderately active
men and inactive men
7735 men UK (248)
↓ Relative risk of 26% between upper and lower
quintile of physical activity
70102 women US (406)
↓ Adjusted relative risk of 59% between upper and
lower quintile of physical activity
2924 men Japan (365)
↓ Adjusted relative risk of 15 and 57% between
moderate and high compared to low physical activity
2017 men
2352 women
Finland (249)
↓ Adjusted relative risk of 13, 30 and 76% between
low, moderate and high compared to no physical activity
4069 men
4034 women
Germany (338)

20.5 Primary prevention of T2D – Exercise clinical trial

Prescribed exercise was associated with a 46% reduction in risk of developing
T2D in 110,000 men and women with impaired glucose tolerance in Da Qing China over a 6-yr
intervention period (398).

20.6 Primary prevention of T2D- Lifestyle clinical trial

Prediabetic individuals who incorporate lifestyle modification including
increases in their physical activity prevent or delay the onset of T2D by returning their
elevated blood glucose levels to normal. During the Finnish Diabetes Prevention Study
(Finnish DPS), T2D risk was reduced in prediabetics by 58% (530). In the U.S. Diabetes Prevention Program (DPP), T2D incidence was
11.0, 7.8, and 4.8 cases per 100 person-years in the placebo, metformin, and diet-exercise
groups, respectively, with reductions, compared to placebo, of 31% and 58% in metformin,
and diet-exercise groups, respectively (276). The
result led Knowler et al. (276) to conclude that
the lifestyle intervention was significantly more effective than metformin. However, the
58% reduction in the diet-exercise group and 31% reduction with metformin in the Finnish
DPS and DPP were both intent-to-treat values. Intent-to-treat values in both studies are
the sum of behavioral and biological mechanisms for 100% of the subjects, providing data
for physicians on effectiveness of prescription. However, intent-to-treat does not
separate behavioral from biological mechanisms. Thus, the biological effectiveness of diet
and exercise, independent of behavior, is underestimated due to lower compliance rates in
the lifestyle versus metformin groups.

20.7 Physical activity can prevent T2D without weight loss

Primary prevention of T2D without weight loss has major public health
importance due to media and medical emphasis on weight loss.

Randomized clinical trials (RCT)

Subjects were 80% less likely to develop T2D when they did not reach the
percentage goal of weight loss, but achieved the goal with respect to exercise volume
(more than four hours per week) as compared to the reference group, in the Finnish DPS

Prediabetes independent of changes in body weight

To determine the effect of leisure-time physical activity on the occurrence
of T2D in prediabetics of the Finnish DPS, subjects filled out a 1-yr questionnaire for
leisure-time activity and then were followed for an additional 4.1 yrs after the
original 3.2-yr DPS. Subjects within the upper third of total leisure-time physical
activity had ~70% lower risk of T2D than those in the lowest third, in
overweight, prediabetic men and women in the Finnish DPS (297, 299), despite similar
baseline physical activity, age, baseline BMI and dietary variables and their changes
during the study. In the U.S. DPP, a follow-up analysis was made for those subjects who
made one goal, but not a second goal. Subjects who met the activity goal (>150
min/wk in the U.S. DPP, but did not meet the weight loss goal (>7%), had a 44%
reduction in diabetes incidence, independent of the small weight loss (−2.9 kg)
that occurred in the DPP (219).

20.8 Mechanisms

A recent review describes available evidence suggesting that exercise primarily
acts to lower hyperglycemia by improving glucose sensitivity and mechanisms that interfere
directly with endothelial metabolism (4). Another
review indicates that it is likely that one of the mechanisms by which physical fitness
and activity reduce health risk associated with high BMI is by decreasing fat-to-lean mass
ratio and also by decreasing visceral-to-subcutaneous fat ratio. The review indicates that
decreasing VAT is particularly important for BMIs between 25 and 30 (185). Physical activity also improves glucose-induced insulin
secretion in pancreatic beta cells, likely through enhanced gastric inhibitory protein
(GIP) secretion (483).

20.9 T2D predisposing genes-environmental interactions

A complex disease such as T2D has, at present, 18 multiple candidate loci that
account for only a small percentage (< 7%) of the total identifiable genetic load.
Snyder at al. wrote,

“Thus, the interpretable genetic contributions that can be
identified are quite minor… Presumably, either many low-frequency alleles at
different loci contribute to the genetic load or perhaps the many phenotypes are
because of other phenomena such as synergistic effects between variants at more than
one locus or between different loci and factors in the environment, recurrent
spontaneous mutations, or epigenetic defects.” (484).

Contemporary hypotheses are that many individual rare gene variants play a much
larger role in the genetic predisposition to T2D (436), but currently there is little data to support this speculation.

20.10 Clinical significance

Physical inactivity is an actual cause of insulin resistance and of
prediabetes, and therefore, according to disease progression of T2D, itself. T2D is
primarily prevented by primary prevention of insulin resistance (prevents movement from
point A to B in the modified Bergman figure (), and of decreased beta-cell insulin secretion and of prediabetes (prevents
movement from point B to C in Bergman’s ).

T2D is estimated to cost men 11.6 life-years and 18.6 quality-adjusted
life-years and women 14.3 life-years and 22.0 quality-adjusted life-years when at the age
40 years (366). Complications given at the
American Diabetes Website (11) are: heart disease
and stroke (death rate is 2–4 times greater than non-diabetics); hypertension (75%
of diabetes); blindness (12,000–24,000 new cases/yr); kidney failure
(~47,000 new cases/yr); neuropathy (60–70% of diabetics); and lower limb
amputation (~71,000 cases/yr).

21. Non-alcoholic fatty liver disease (NAFLD)

21.1 Definition

NAFLD is a liver disease in females and males who drink less than 10 and 20
grams of alcohol/day, respectively. NAFLD is a progressive disease first apparent by
benign fatty liver (steatosis), which can evolve to non-alcoholic steatohepatitis (NASH)
that adds inflammation to steatosis. Later progression leads to steatosis with
inflammation and mild to advanced fibrosis, to steatosis with fibrosis alone, to cirrhosis
and finally to end-stage liver disease. Histologic findings of pediatric NAFLD may or may
not differ from adult NAFLD (69). Serious outcomes
of NAFLD include cirrhosis, hepatocellular carcinoma, coronary heart disease, and diabetes

21.2 Etiology

NAFLD is recognized as the leading cause of chronic liver disease in adults and
children (518). Prevalence estimates are
~20% of adult Americans have benign fatty liver without inflammation or damage and
2–5% have NASH (164). Prevalence of NAFLD
in a subpopulation of morbidly obese population ranges from 75–92%. The prevalence
of NAFLD in American children is estimated at 13% (472) and has emerged as the leading cause of chronic liver disease in children
and adolescents in the United States (322).

NAFLD independent of changes in body weight

St. Gorge et al. (488) concluded that
“maintaining or increasing physical activity provides health benefits for
patients with fatty liver, independent of changes in weight.” Caldwell and Lazo
(74) contend that increased physical
conditioning appears to be closely linked to improved hepatic metabolism independent of
changes in body weight.


Church found lower CRF directly associated with higher NAFLD prevalence in
healthy, nonsmoking, nonalcoholic 33–73-yr-old men (101). A second study reported a low level of habitual physical
activity was associated with higher intrahepatic fat content in healthy, nonalcoholic
males and females ages 19–62 (407).

21.4 Interventions/animals

OLETF rats have a spontaneous mutation that inactivates cholecystokinin
receptor 1 protein to signal satiety. Without the satiety signal, hyperphagia leads to
concurrent obesity and NAFLD between the ages of 5 and 8 wks old, which progress to T2D
(429). Sixteen weeks of voluntary running of
4-wk-old OLETF rats totally prevented the development of NAFLD. Morphologically, livers of
runners had both fewer and smaller lipid droplets compared non-runners.

21.5 Cross-sectional

Habitual leisure-time physical activity, especially anaerobic, may play a
protective role in NAFLD by a reduced rate of abdominal obesity in 24–70-yr old
human subjects (578). Further, only the
association with resistance physical activity remained significant with further adjustment
for BMI. Lower VO2peak was associated with increasing NAFLD activity and with
disease severity by NASH diagnosis (283).

21.6 Intervention

Maintaining or increasing physical activity provides health benefits for
patients with fatty liver, independent of changes in weight (488). An intensive lifestyle intervention program can successfully
produce a 7%–10% weight reduction and significant improvements in liver chemistry
and histological activity in patients with NASH (420). Targeting weight loss by energy restriction alone or in combination with
exercise training has been shown to reduce NAFLD pathology. In patients with and without
NAFLD, nine months of diet and exercise intervention led to three important outcomes: 1)
reduction in liver fat was approximately twice reduction of VAT; 2) subjects who resolved
NAFLD tended to have higher CRF at prior to the intervention; and 3) VO2max at
baseline was a predictor of change in liver fat, independently of total- and VAT mass
(264). The study indicated that CRF fitness and
liver fat are related to each other.

21.7 Clinical trials

Long-term RCTs examining the effects of exercise, independent of weight loss,
on NAFLD are lacking.

21.8 Mechanisms

Two approaches were tested. The first approach compared OLETF rats with and
without 16 weeks of voluntary running. OLETF rats that underwent the voluntary running had
3-fold higher rates of hepatic fatty acid oxidation (complete palmitate oxidization to
CO2); lower TG synthesis [70% and 35% lower protein concentrations of fatty
acid synthase and acetyl-coenzyme A carboxylase (ACC), respectively], and higher oxidative
capacity (35% and 30% higher ACC phosphorylation and cytochrome c concentrations,
respectively), as compared to sedentary OLETF rats (429). The second approach was to suddenly cease 16 wks of daily voluntary
running by OLETF rats. The times for hepatic metabolic adaptations to occur with stoppage
of running were: 2 days (malonyl-CoA protein increased while phospho-acetyl-CoA
carboxylase (ACC) decreased) and 7 days (fatty acid synthase increased and cytochrome
oxidase activity and fatty acid oxidation decreased). Thus, reduced physical activity for
less than 7 days initiates biochemical sequences that leads to NAFLD in OLETF rats (428).

21.9 Clinical significance

A recent title on PubMed was “Some experts suggest that fatty liver
disease will be the next big metabolic disorder associated with obesity and
inactivity” (15). Physical inactivity is an
actual cause of NAFLD. Most cases of NAFLD can be primarily prevented by sufficient
physical activity. Reversal of NAFLD with sufficient physical activity can also occur
before hepatofibrosis occurs.

22. Cardiovascular diseases (CVD): All types

22.1 Definition

CVD includes all diseases that affect heart and blood vessels. The American
Heart Association (321) lists major CVDs as: of
subclinical atherosclerosis, coronary heart disease, acute coronary syndrome (myocardial
ischemia), angina pectoris, stroke (cerebrovascular disease), high blood pressure,
congenital cardiovascular defects, cardiomyopathy and heart failure, and other less
prevalent CVDs. Physical inactivity increases the prevalence of all major CVDs.

22.2 Known and unidentified risk factors

Of the identified CVD risk factors, modest percentage changes occur with
habitual physical activity. Mora and Lee (349)
indicate that changes in individual risk factors with physical activity are on the order
of 5% for blood lipids, 3 to 5 mm Hg for blood pressure, and 1% for hemoglobin A1c, in
contrast to the large (30% to 50%) reductions seen in CVD risk with physical activity.

Mora and Lee (349) presented an
analysis that showed that almost one-half of risk factors by which physical activity
lowers CVDs are not identified. Subjects were 27,000 women compared by >1500
kcal/wk vs. <200 kcal/wk. Differences in “known” risk factors
explained 59.0% of CVD and 36% of coronary heart disease (CHD) of the inverse association
between higher physical activity levels and fewer CVD events (349). Respective contributions of “known” risk factors
for CVD and CHD were inflammatory/hemostatic (33% and 21%), blood pressure/hypertension
(27% and 15%), traditional lipids (19% and 13%), BMI (10% and 7%), HbA1c/diabetes (9% and
5%), and homocysteine (0.7% and 0.3%) (349). Mora
and Lee (349) caution that some or all of the
aforementioned risk factors have interactions, or are acting in concert, since they add up
to more than 59% for CVD and 36% for CHD. The deduction then is 41% and 64% of mechanisms
by which physical activity primary prevents CVD and CHD, respectively remained to be
identified in 2007.

CVD independent of changes in body weight

Physical activity predicts lower CVD risk independent of obesity (552). BMI’s >25 contributed only 10% and 7%
of physical activity’s protection from CVD and CHD, respectively (349). Public health ramifications are that BMI is a minor
contributor as to how physical activity prevents CVD and CHD. Increased physical
activity levels in women with elevated BMI considerably reduce the risk of coronary
heart disease (553). However, the risk is not
completely eliminated, reinforcing the importance of being lean and physically active

22.3 Unknown pathophysiological mechanisms

Joyner and Green (261) proposed a
global hypothesis that might include some, or all, the unknown ~40% and ~60%
of unidentified risk factors by which physical activity reduces CVD and CHD, respectively.
Their suggestions for additional risk factor candidates that are improved by habitual
physical activity include:

  • Enhanced vagal tone via improved peripheral baroreflex function and
    central nervous system cardiovascular regulation. In populations, this will be
    protective and be seen as improved or maintained heart rate variability.

  • Enhanced or maintained endothelial function that will both favor
    vasodilatation and contribute to enhanced peripheral baroreflex function by limiting
    age- or risk factor-associated increases in vascular stiffness.

  • Positive interactions between enhanced endothelial function and
    sympathetic outflow that limit the effects of high levels of baseline sympathetic
    outflow on blood pressure (261).

22.4 Coronary vascular disease (CVD) gene-environmental interaction

CVD is a complex disease. Physical inactivity adaptations in gene expression
are very complex, varying by tissue type and time. Thus CVD x physical inactivity
interaction promises to be highly individualized, depending on the degree of accuracy of
the desired prediction.

23. Presentation of individual cardiovascular diseases

The strategy for the presentation of individual cardiovascular diseases follows.
The order of cardiovascular diseases presented will be coronary heart disease, peripheral
artery disease, hypertension, stroke, and congestive heart failure. (Cross-references:
Chronic cardiac disease)

24. Coronary heart disease (CHD)

24.1 Definition

CHD is a disease of the heart and the coronary arteries that is characterized
by atherosclerotic arterial deposits that block blood flow to the heart, causing
myocardial infarction.

24.2 Etiology

CHD caused ~1 of every 6 deaths (~425,000) in the U.S. in 2006.
In 2010, an estimated 785,000 Americans will have a myocardial infarction, and
approximately 470,000 will have a recurrent attack. The American Heart Association
recognized physical inactivity as a risk factor for CHD and CVD in 1992 (183) and the Surgeon General concluded in 1996 that
“regular physical activity or cardiorespiratory fitness (CRF) decreases the risk of
CVD … and CHD” (531).

24.3 Primary prevention of CHD

Each 1-MET decrease in maximal aerobic exercise capacity increases the adjusted
hazard ratio for death by 12% (279). Using those
individuals with 4 MET maximal aerobic exercise capacity as a reference value of 1.0, the
mortality risk was 38% lower for those who achieved 5.1 to 6.0 METs, mortality risk
declining progressively to 61% for those who achieved >9 METs, regardless of age.
Unfit individuals who improved their fitness status with serial testing had a 35% lower
mortality risk compared with those who remained unfit (279). The NPAGCR reports the literature shows a strong inverse relation between
the amount of habitual physical activity performed and CHD morbidity and mortality (412). Sedentary behavior is a major independent risk
factor for CHD as middle aged or older individuals of both genders who have moderate or
higher amounts of physical activity lower their CHD risk 20% and 30%, respectively,
compared to sedentary (412).

24.4 Mechanisms

Positive effects of chronic exercise on primary prevention of CHD could be
explained by several mechanisms including: increased nitric oxide and antioxidants,
decreased pro-inflammatory cytokine levels in blood by decreasing production from multiple
tissues, and increased regenerative capacity of endothelium expressed by an increased
number of circulating endothelial precursor cells, according to a recent comprehensive
review of the topic (433). However, these
mechanisms do not totally explain the primary prevention of CHD.

24.5 Clinical significance

Physical inactivity is a cause of at least 1 of 3 deaths from CHD. Sufficient
physical activity primarily prevents CHD.

25. Peripheral arterial disease (PAD)

25.1 Definition

Narrowed arteries reduce blood flow to limbs, sometimes causing leg pain,
generally referred to as claudication when walking. (Cross-reference: Exercise and
peripheral arterial insufficiency: Control of blood flow to cardiac and skeletal muscle
during exercise)

25.2 Etiology

PAD affects affects 8–12 million people million in the U.S.
(12%–20% > 65 yrs old have PAD). The NPAGCR concludes that a lack of RCT
exercise studies exists to evaluate the effect of exercise training on preventing PAD
(412). However, the Report does find support
that physical inactivity contributes to accelerated disease progression in those who have
PAD. A recent review concludes that the magnitude of effect from a supervised exercise
program exceeds that achieved with any of the pharmacologic agents available to treat PAD

25.3 Mechanisms

Mechanisms by which physical activity is primary prevention of PAD are
potentially similar to those given for coronary artery disease.

25.4 Clinical significance

Physical inactivity may be a factor increasing the risk of PAD. PAD is a strong
predictor of myocardial infraction, stroke, and death due to vascular causes. As
atherosclerosis is by far the most common etiology of PAD, and as physical activity
primarily prevents coronary artery disease, speculation could be made that physical
activity could also primarily prevent PAD. However, insufficient large RCT studies have
been performed. Some tertiary preventive evidence exists in PAD patients that walking
performed 3 times or more weekly have less functional decline during the next year (336) and that greater than light physical activity
reduces mortality (194). (Cross-reference:
Peripheral Circulation)

26. Hypertension

26.1 Definition

With prehypertension, systolic blood pressure (SBP) is 120–139 mgHg and
diastolic blood pressure (DBP) is 80–89 mmHg. Hypertension is defined as SBP
≥140 mmHg or DBP ≥90 mmHg, or taking antihypertensive medicine.

26.2 Etiology

In the United States, >62% of adults have blood pressures above optimal
levels. The NPAGCR concluded that both aerobic and progressive resistance exercise cause
reduced SBP and DBP in adult humans, although aerobic exercise evidence is stronger (412). The influence of exercise intensity on
post-exercise hypotension occurred in dose-response fashion such that for each 10%
increase in relative VO2peak, SBP decreased 1.5 mmHg and DBP 0.6 mmHg, thus
showing a dose-response relationship for physical activity intensity and lowering of blood
pressure post exercise (post-exercise hypotension) (156).

26.3 Mechanisms

Eicher et al. (157) suggest potential
mechanistic clues for post-exercise hypotension involve the renin-angiotensin system and
sympathetic nervous systems and include modulation by cardiometabolic, inflammatory, and
hemostatic factors.

26.4 Clinical significance

With decreased daily physical activity, increases in SBP and DBP were 2.4 mmHg
and 1.6 mmHg, respectively, in normotensive; 3.1 mmHg and 1.7 mmHg in prehypertensive; and
6.9 mmHg and 4.9 mmHg in hypertensive subjects, respectively (412). A 3.0 mmHg higher systolic and a 2.3 mmHg higher DBP translates
into an estimated 12% increased risk for CHD and 24% increased risk for stroke (416). Physical activity is one of a number of primary
preventive measures against hypertension.

27. Stroke

27.1 Definition

Stroke is a sudden diminution or loss of consciousness, sensation, and
voluntary motion caused by rupture or obstruction (as by a clot) of a blood vessel of the

27.2 Etiology

Each year ~800,000 individuals experience a new (~610,000) or
recurrent (~185,000) stroke with ~185,000 deaths in the U.S. The most
physically active men and women have a 25% to 30% lower risk for stroke incidence and
mortality. Data on ischemic and hemorrhagic stroke subtypes is quite limited according the
NPAGCR (412). Thirteen of 992 articles satisfied
all eligibility criteria to be included in a meta-analysis. Compared with low physical
activity, moderate physical activity caused an 11% reduction in risk of stroke outcome and
high physical activity a 19% reduction. No significant risk reduction associated with
moderate physical activity in women (137). A
meta-analysis of 33 prospective cohort studies and 10 case-control studies found that
physical activity reduces the relative risk of 0.75 for fatal or non-fatal cerebral
infarction, while the corresponding relative risks for cerebral hemorrhage and stroke of
unspecified type are 0.67 and 0.71, respectively. The reduction of risk was only
statistically significant for men (432).

27.3 Mechanisms

Reimers et al. (432) suggest potential
mechanisms of risk reduction by physical activity on stroke. They include:
antihypertensive effect, beneficial effect on lipid metabolism, and improved endothelial
function (increased endothelial NOS activity and extracellular superoxide dismutase
expression). Other mechanisms that may play a role include a lowered blood viscosity, a
tendency toward platelet aggregation, increased fibrinolysis, reduced plasma fibrinogen,
increased activity of plasma tissue plasminogen activator activity, and higher of

27.4 Clinical significance

Physical inactivity causes deteriorations in multiple mechanisms that cause
stroke, as mentioned above. Physical activity could be primary prevention of 10–30%
of stroke, depending on the volume of activity.

28. Congestive heart failure (CHF)

28.1 Definition

The heart fails to pump adequate amounts of blood through arteries to tissues,
which causes blood to back up and accumulate in other parts of the body, such as lungs and
feet. CHF is often accompanied by distension of the ventricles, peripheral and pulmonary
(causing shortness of breath) edema.

28.2 Etiology

After 65 yrs of age, ~10 per 1000 individuals have CHF. Hypertension
precedes 75% of CHF cases. RCTs for prevention of congestive heart failure are not
available. Observational data supports the notion that habitual endurance training is
primary prevention against development of CHF.

28.3 Mechanisms

Levine and co-authors (16) have
concluded that prolonged, sustained endurance training preserves ventricular compliance
with aging and may be an important approach to reduce the probability of heart failure
with aging. Preservation of ventricular compliance with endurance training probably
includes preservation of viscoelastic myocardial properties (absence of increased
ventricular stiffening) and eccentric ventricular hypertrophy (a balanced enlargement of
ventricular mass and dimensions) (16). These
adaptations lead to profoundly improved cardiac performance without apparent change in
contractility, which thus is largely explained by enhanced diastolic filling due to low
stiffness (16). Together these are coupled with
endurance training prevention of arterial stiffening with aging result in preserving
ventricular-vascular coupling of compliance, lowering afterload on the left ventricle

28.4 Clinical significance

Physical inactivity contributes development of CHF. Physical activity can
primarily prevent some CHF.

29. Known mechanisms for CVD risk factors

29.1 Endothelial dysfunction


Endothelial dysfunction is characterized by vascular endothelium exhibiting
reduced vasodilation along with greater proinflammatory and prothrombic markers (161).

Conditions associated with endothelial dysfunction

Félétou and Vanhoutte’s review states that endothelial
dysfunction has been associated not only with hypertension or atherosclerosis, but also
with the following long list of conditions:

Since then the term “endothelial dysfunction” has been
referred to in the scientific literature more than 20,000 times (PubMed search,
November 2005) and has been associated not only with hypertension or
atherosclerosis, but also with physiological and pathophysiological processes,
including aging, heart and renal failure, coronary syndrome, microalbuminuria,
dialysis, thrombosis, intravascular coagulation, preeclampsia, Type I and Type II
diabetes, impaired glucose tolerance, insulin resistance, hyperglycemia, obesity,
postprandial lipemia, hypercholesterolemia, hyperhomocysteinemia, elevated
asymmetric dimethylarginine plasma levels, inflammation, vasculitis, infections,
sepsis, rheumatoid arthritis, periodontitis, trauma, transplantation, low birth
weight, postmenopause in women, mental stress, sleep apnea syndrome, smoking,
nitrate tolerance, glucocorticoids, and so on” (180).

The list of associations would now have to include physical inactivity since
the 2005 list is out-of-date.


Sedentary men at ages of 50–76 years of age have impaired
endothelium-dependent dilation in response to both acetylcholine and increased shear
stress in humans (465). In contrast,
50–76 yr-old, long-term, exercise-trained men do not show age impairment as they
have similar endothelium-dependent dilation to acetylcholine-mediated vasodilation as
healthy, 22–35-yr old men have (132,
167). Regular aerobic exercise can restore the
loss of endothelium-dependent vasodilation in previously sedentary 50–76 yr-old
men, implying that physical inactivity is responsible for nearly 100% of endothelial
dysfunction in this group of men (132) Seven
days of dry immersion, a human model of extreme physical inactivity diminished
endothelium-dependent vasodilation by 59% (371).

Clinical outcomes

Davigon and Ganz (121) contend that
endothelial dysfunction is an early marker for atherosclerosis and can be detected
before structural changes to the vessel wall are evident. If, as claimed by Davigon and
Ganz (121), endothelial dysfunction is an early
marker for atherosclerosis and can be detected before structural changes to the vessel
wall are evident, then a prevention of endothelial dysfunction by a lifetime of physical
activity would therefore also prevent most of atherosclerosis reaching a clinical level
at the age of 50–76 yrs in men (132,
167) or even initiation of aerobic physical
activity within lifestyle (132).

Biochemical adaptations to inactivity

Singularly caged, healthy, young male mice had ~30% less
endothelium-dependent vasodilation to acetylcholine and ~50% less eNOS protein
than did five mice in large cages, where the multiple housed mice ran, climbed, and
fought during their active cycle (501). With
other data, they suggest that an impaired nitric oxide/cGMP-pathway signaling is most
likely not involved in endothelial dysfunction induced by a sedentary lifestyle in mice.
In a second report, mice in cages without wheels for voluntary running had 148% higher
vascular lipid peroxidation, 176–188% higher superoxide release, 154% greater
NADPH oxidase, and 161% higher rac1 protein than mice voluntarily running in wheels for
6 weeks (307). Expression levels for subunits
nox1, p47phox and p67phox were increased, which suggests increased oxidative stress. A
tissue that is not involved in limb movement of running or cycling is the penis.
Treadmill training of diabetic rats restored impaired endothelial-dependent and
neurogenic nitrergic relaxation in corpus cavernosum (102). The exercise training increased depressed plasma superoxide dismutase
(SOD) levels of sedentary diabetic rats. The paper hypothesized that nitric oxide
bioavailability to corporal smooth muscle was increased by plasma’s SOD’s antioxidant

Mechanisms of inactivity

Lack of shear stress from transient bouts of exercise initiates a cascade of
unhealthy events that can be inferred if the sedentary group in exercise studies is
considered (308). Extreme 7-day physical
inactivity in humans causes microvascular impairment with 32% and 59% decreases in basal
flow and endothelium-dependent vasodilation, respectively that was associated with a
selective increase in circulating endothelial microparticles (371), that have pro-coagulant and pro-inflammatory properties (99).

Clinical significance

Physical inactivity is a cause of endothelial dysfunction by lack of
increased blood flow by exercise in sedentary condition. Exercise signals a beneficial
endothelial cell phenotype, at least in part through changes in shear stress and wall
stretch in the arteries.

29.2 Atherogenic Dyslipidemia


Atherogenic dyslipidemia is defined as the presence of abnormally low serum
concentrations of high-density lipoprotein cholesterol (HDL-C) and elevated
concentrations of high triglycerides and small, dense low-density lipoprotein
cholesterol (LDL-C).


The NPAGCR concludes that habitual physical activity increases serum HDL-C
and decreases serum TG. Threshold volumes are from 7 to 15 miles per week of regular
aerobic exercise (equating to an approximate 600 to 800 MET-minutes), with no sex
differences (412). The NPAGCR also concludes
that evidence is inconsistent as to whether and if LDL-C responds favorably to exercise
training. A meta-analysis of 29 RCTs of progressive resistance training found
statistically significant improvements of −2.7% for total cholesterol,
−11.6% for ratio of total cholesterol /HDL-C, −5.6% for non-HDL-C,
−4.6% for LDL-C, and −6.4% for TG (−8.1 mg/dl, −14.5 to
−1.8) (270). The change for HDL-C was not
significant. The clinical importance of reductions in LDL-C by resistance training is
that for every 1% reduction in LDL-C levels, a 1% reduction occurs in relative risk for
major CHD events.

Clinical significance

Physical inactivity contributes to worsening of atherogenic dyslipidemia.
Exercise improves blood lipid values. Lakka and Laaksonen (299) caution not to underestimate the clinical significance of small
changes in plasma LDL-C, HDL-C, and TG concentrations with aerobic exercise training
because they occur concurrently with benefits on other cardiovascular and metabolic risk
factors. Traditional lipids contribute to 19% and 13% of physical activity’s
contributions of “known” risk factors to reduce CVD and CHD, respectively,
according to Mora et al. (349). Another report
found that traditional lipid risk factors account for only 20% of total risk of CVD risk
events in 27,000 women (349).

29.3 Hemostasis


Hemostasis is the arrest of bleeding either by physiological properties of
vasoconstriction and coagulation or by surgical means.


In a 1990 review, physical inactivity had been associated with the following:
low plasma volume, high hematocrit, high plasma fibrinogen, elevated blood viscosity,
increased platelet aggregation, and diminished fibrinolysis (158). Low physical fitness and self-reported sedentary lifestyle
have been associated with a pro-thrombotic blood profile in middle-aged women with CHD
(364). Plasma levels of the hemostatic factors
such as fibrinogen, FVIIag, FVIIa, vWFag showed an inverse relation to self-reported
physical activity. Regular physical exercise has beneficial long-term effects on
hemostasis in studies including male subjects (See (364) for refs.).

Clinical significance

Numerous reviews suggest that physical activity has long-term healthy
benefits on hemostasis (2, 28, 158, 320).

30. Deep vein thrombosis (DVT)

DVT is the formation of a blood clot (“thrombus”) in a deep vein.
its prevalence is ~12,000/yr with 6% dying within 1 month. DVT is caused by physical
inactivity. The lack of shear stress along with low blood flow likely may account for deep
vein thrombosis (“economy-class syndrome”) at the back of vein valves where
white cells adhere to fibrin strains (48). The
clinical significance of DVT results when a clot breaks off as an embolus and flows to the
lung where it blocks a portion of pulmonary blood flow, causing lack of gas exchange in
pulmonary capillaries. Primary prevention is muscle pumping from muscle contraction that
“squeezes” venous blood to return blood past venous valves back to the right

31. Cognitive Function

31.1 Disease definitions

Cognitive function is a broad term defined as the “an intellectual
process by which one becomes aware of, perceives, or comprehends ideas. It involves all
aspects of perception, thinking, reasoning, and remembering” (358). Cognitive decline is considered an aging disease with two of the
most severe forms being Alzheimer’s and dementia. Thus, cognitive function can arbitrarily
be divided into studies of developing cognition and of primary prevention of the decline
in cognition. (Cross-reference: Dementia and Alzheimer’s disease; Effects of exercise on
brain function and cognitive development)

31.2 Epidemiology of developing better cognition

Research in exercise and prevention of cognitive decline is relatively new and
moving rapidly. Recent reviews exist (239, 341).


Aerobic exercise and physical activity improve cognitive health across the
lifespan (239). Dutch men, but not women, who
were physically active at a young age (15–25 yrs old), had less of a decline in
informational processing capabilities versus individuals physically inactivity early in
life (138). Women who reported being physically
active at any point in life had a lower likelihood of cognitive impairment in late life
(341). Women who began physical activity later
in life after inactive teenage years also had lower rates of cognitive impairment in
late life. Of the four ages examined, teenage physical activity appeared to be most
strongly related to better cognitive function and lower prevalence of cognitive
impairment in old age (341).


A 2003 meta-analysis in children (aged 4–18 yrs) demonstrated a
significant positive relationship between physical activity levels and perceptual
skills, intelligence quotient, achievement, verbal tests, mathematic tests,
developmental level/academic readiness, with only an effect on memory not found (172). Chaddock et al. (91) found improvements in relational, but not item memory in
children. Children who have low physical activity levels have poorer academic
achievement scores and inferior cognitive performance as compared to physically fit
children (70, 84, 91, 92, 100, 144, 172, 174, 237,
238, 273, 417, 565). A 2008 review concluded that exercise facilitates children’s
executive function, (i.e., organize thoughts and activities, prioritize tasks, manage
time efficiently, and make decisions) similar to improvements reported for other age
groups (520).


A cohort study of Swedish men born in 1950 through 1976 who were enlisted for
military service at age 18 (N = 1,221,727) (1)
reported that cardiovascular fitness, as measured by ergometer cycling, was positively
associated with global intelligence scores with aerobic capacity most strongly
associated with logic and verbal intelligence. The longitudinal arm of the Swedish study
showed that between the ages of 15 and 18 yrs of age those with the top 10% of
improvement in cardiovascular fitness scores had highest enhancement of global
intelligence, logical, verbal, visuospatial, and technical scores while those subjects
with declines in cardiovascular fitness had less than mean intelligence scores. Further,
an association between better cardiovascular fitness at age 18 yrs, a higher
socioeconomic status, and educational attainment later in life existed.

Older adults

18 RCTs (published prior to 2001) focused on aerobic physical activity
interventions in older adults. Aerobic exercise had an overall effect size of 0.48 was
found with the largest effect on executive functioning, followed by attention,
visuospatial, and speed dependent processes (108). In a prospective study of 18,000 women aged 71–80 yrs old, higher
levels of long-term regular physical activity were strongly associated with higher
levels of cognitive function and a 20% lower risk of cognitive impairment (556). Physical inactivity (less than 3 bouts of
exercise/week) increased the risk of dementia from 13.0 per 1000 person-years to 19.7
per 1000 person-years (306). Each 10 blocks that
were walked/day in women >65 years old resulted in 13% less impairment in
cognitive function (574). Moderate and high
levels of physical activity were associated with significantly lower risks for Alzheimer
disease and for dementia of any type (309). An
inverse relationship between physical activity levels and dementia was found in men and
women aged 65 years and older (413). Higher
VO2peak was associated positively with preservation of cognitive function
over a 6-year period in 349 subjects over the age of 55 (24).

Increased aerobic fitness can be neuroprotective and can enhance cognitive
function (108, 110, 282). Kramer et al. reported in
1999 that those who received aerobic training (walking) showed substantial improvements
in performance on tasks requiring executive control compared with stretching- and
toning-trained subjects aged 60–75 yrs (282). Resistance exercise also had a positive impact on cognitive function in
65–75-yr-old males (83).

Physical activity, not fitness, improves cognitive function

A meta-analysis was performed on 571 fitness effect sizes from 1306 subjects
from 37 studies prior to 2005. Etnier et al. (172) concluded that the empirical literature did not support a relationship
between aerobic fitness and cognitive performance. Rather across the same 37 studies
designed to test the effects of fitness on cognition, the summary statistic indicated
that a positive association existed between physical activity and cognitive performance
(172), confirming the findings of three
previous meta-analytic reviews of this literature (108, 173, 473).

Dementia: Primary prevention

The NPAGCR (see (412) for refs)]
found that physical activity delayed the onset of cognitive decline or dementia in most
studies with sample sizes >1,000 individuals, but with inconsistent findings for
underpowered studies containing low subject numbers. Nine of 16 prospective studies had
odds ratios (OR = 0.63) showing protection by physical activity from dementia or
Alzheimer’s Disease [Figure G8.8 in NPAGCR (412)]. To date, no RCT has been performed to show that regular physical activity
prevents dementia (445).

31.3 Mechanisms

As a new frontier in inactivity disease, we chose to provide a more extensive
presentation on the inactivity/exercise mechanisms for cognitive function.



Highly cardiorespiratory-fit or aerobically-trained individuals had reduced
activation of the anterior cingulated cortex concomitantly with lower indecision that
arises when multiple conflicting responses are elicited in response to a stimulus
during a task that required variable amounts of executive control, relative to
untrained individuals (110). Fit and trained
subjects also had greater task-related activity in regions of the prefrontal and
parietal cortices that are involved in spatial selection and inhibitory functioning

Reductions in hippocampus volume are associated with a decline in memory
performance, specifically acquisition and recall measures (410) hippocampal volume is positively correlated with physical
fitness in adults (163) and children 10-yr
olds (91), and can be increased by aerobic
training of both schizophrenic and healthy subjects’ (397). Likewise, a 6-month aerobic exercise intervention increased grey
matter volume in the frontal and superior temporal lobes(109). Further, results suggest that aerobic fitness does not have
a general impact on the volume of all structures in the brain in children (92). Electrical function is increased in
“high” hit older (50–62 year old) adults (154) in potentially due to increased synaptic plasticity and
long-term-potentiation (544).


Exercise increases neurogenesis in the dentrate gyrus, a hippocampal region
that is important for spatial recognition. Van Praag et al. (535) showed increased voluntary exercise is sufficient for
enhanced survival of newborn cells in 3-month-old adult mouse dentate gyrus. Another
study found that improved spatial pattern separation in 3-month-old mice was tightly
correlated with increased neurogenesis and vasculature in the dentate gryus after 10
weeks of voluntary wheel running (117). Rat
voluntary runners have longer-lasting LTP following tetanic stimulation (due to lower
threshold of LTP induction) in dentate gyrus, which is dependent upon the activation
of N-methyl-D-aspartate (NMDA) receptors (538). Another anatomical change associated with improved cognitive is
improvements is brain blood flow. Voluntary wheel running can increase blood vessel
density, blood flow, and capillary perfusion of the motor cortex in rats (42, 502).
Potential mechanisms include the increased density of microvessels (141), angiopoietin 1 (141), VEGF protein (141),
or endothelial proliferation (141, 160). Angiogenesis in the brain is associated with
enhanced improvement in a functional outcome like water maze time (536), but not the ability to activate the motor
limbs (275).

Biochemical adaptations


The human brain is responsible for ~70–80% of circulating
BDNF at rest (423). BDNF mRNA and protein
expression were increased in human skeletal muscle after exercise, but muscle-derived
BDNF appeared not to be released into the circulation (332).


Physical activity can induce local and systemic expression of many growth
factors that protect the brain from physical inactivity-related declines in function.
Brain-derived neurotrophic factor (BDNF) plays an important role in the growth,
development, maintenance, and function of several neuronal systems (372). BDNF mRNA was upregulated in a dose-response
manner following 2, 4, and 7 days of voluntary distance run by rats (372). Three days of voluntary wheel running had as
much effect as 28 days in increasing mRNAs for growth factors (BDNF, neural growth
factor, fibroblast growth factor-2), synapse related proteins (synapsin, syntaxin,
synaptoginamin), neurotransmitter systems (reduced γ-aminobutyric acid (GABA)
neurogenic signaling, which is associated with increased recover), and intracellular
kinases (Ca2+/Calmodulin-Dependent Protein Kinase II, MAPK/ERK kinase 1/2,
mitogen-activated protein kinase 1/2) (346).
Whether 1 day would have the same effects is unknown. Conversely, cessation of
voluntary wheel running in spontaneously hypertensive rats can decrease the BDNF and
BDNF/NT-3 growth factor receptor (TrkB) system mRNA in hippocampus for a duration
lasting at least 10 days (559).

Another critical growth factor for neuroprotection and brain health is
IGF-1. A number of studies show that IGF-1 increases in the brain following exercise.
Infusion of IGF-1 mimicked the effects of exercise. while infusion of an anti-IGF-1
antibody blocked the effects (80). Blocking
hippocampal IGF-I receptors, but abolished the effect of exercise on augmenting recall
in rats during 5 days of wheel running (140).
Anti-IGF-I antibody can also abrogate the protective effects of exercise in many types
of brain lesions (81). Like BDNF, the levels of
IGF-1 increase in the circulation in response to physical activity (521) and both exercise and systemic infusion of
IGF-1 increases new and survivability of BrdU+ cells in the hippocampus (323, 521),
likely signaling through IGF-receptors located on the luminal side of the brain (323). In culture, IGF stimulates VEGF via a HIF
mechanism (323). Blockage of peripheral VEGF
prevents the increase in BrdU-positive cells and mitosis in immature neurons of
exercising animals only (175).



Polymorphisms in the APOE4 genotype have been examined in relationship to
physical activity, with mixed results (399).
For instance in cross-sectional studies examining physical activity by questionnaire,
two studies suggest that carriers of APOE4 benefit from physical activity (127, 462),
while one does not (413). However, higher
aerobic fitness levels in older women having the APOE4 genotype had better cognitive
function in another cross-sectional study (171), suggesting that physical activity levels that are capable of increasing
aerobic fitness are needed to improve cognitive function in those with APOE4


Animal studies support this. Mice with the APOE4 genotype that voluntarily
ran in wheels for 6 months rescued cognitive function and BDNF levels within the
hippocampus by returned them to that found in APOE3 (control) mice (379).

31.4 Clinical Significance

Epidemiological, interventions, and mechanistic insights from human and rodent
studies all suggest that physical inactivity can accelerate declines in cognitive
function; a decline that be attenuated or potentially reversed by physical activity.
However, questions remain regarding the best-practice for mode, duration, intensity, the
long lasting effects, potential gender specific effects, and the interaction with genetic

32. Depression and anxiety

32.1 Definitions


A mood disorder marked especially by sadness, inactivity, difficulty with
thinking and concentration, a significant increase or decrease in appetite and time
spent sleeping, feelings of dejection and hopelessness, and sometimes with suicidal
thoughts or an attempt to commit suicide. (Cross-reference: Depression)


An abnormal and overwhelming sense of apprehension and fear often marked by
physiological signs (as sweating, tension, and increased pulse), by doubt concerning the
reality and nature of the threat, and by self-doubt about one’s capacity to cope with

32.2 Etiology

Depression is relatively common affecting 8% of women and 4% of men, having a
lifetime prevalence of 16%, and an annual cost of $83 billion dollars in the United States
(208). Anxiety is prevalent in 10% of the
general public, has many similar symptoms and treatments to depression, but can also
include a wide range of phobias. Both depression and anxiety are associated with increased
risks of many other diseases. Genetic, biological, chemical, hormonal, environmental,
psychological, and social factors all likely intersect to contribute to depression in
women (see (369) or details). Some of these same
factors play a role in men. For anxiety, disorders last at least 6 months and commonly
occur along with other mental or physical illnesses, including alcohol or substance

Since 1995, more than 100 population-based observational studies have been
completed. Looking at these studies, the 2008 NPAGCR (412) concluded that active people were nearly 45% less likely to have depressive
symptoms than inactive people. Looking at the 28 prospective cohorts allows for
examination of physical activity levels before depression symptoms occur. Nearly 4 years
of physical inactivity increased risk for depression by about 49% without adjustment for
depression risk factors and by 22% after adjusting for known risk factors such as age,
sex, race, education, income, smoking, alcohol use, and chronic health conditions. In 66
of 67 cohort studies, physical inactivity increased the risk of depression. While many of
the studies relied on self-questionnaires, 8 cohort studies contained clinical diagnosis
of depression symptoms, which reported an increase of 40% in the inactive group. Physical
working capacity was found in depressed male patients but not female patients (350). Morgan et al, who noted that both grip strength
inversely related to hospital length stay and lower in depressed patients (351). In Britain, children under the age of 15 had an
8% reduction in depression symptoms for every hour of exercise completed/week (448). Likewise, lower fitness was found in depressed
male patients but not female patients (350).

Treatment of depression with exercise has also been shown to be effective. In
1979, Greist et al (211) found that running and
time-limited/unlimited psychotherapy reduced depression symptoms similarly. Depressed
patients that participated in exercise had less of a need for medication and less relapse
(18), and adhere to exercise (66%) greater than
medication (40%). An exercise dose consistent with public health recommendations in
1998–2001 (about 12 miles/week of walking for 12 weeks) reduced depressive symptoms
47% from baseline while a lower dose exercise (5 miles/week) group did not respond any
better than the exercise placebo control group (150). Other studies have found a relatively quick effect of exercise involving
10 days of walking for 30 min/day resulted in a decrease in the Hamilton Rating Scale for
Depression and self-assessed intensity of symptoms (139).

The NPAGCR (412, 532) concluded that after examining 4 population-based cross-sectional
studies of over 121,000 Americans that regular physical activity decreases the odds of an
anxiety disorder. Specifically, the national Co-Morbidity study found physical inactivity
increased anxiety disorder by 1.75 times in raw odds and 1.38 times once adjusted for
sociodemographic and illness (204). Australians
reporting no activity were 2.1 times more likely to develop anxiety disorders than those
conducting more than 3 hours of vigorous activity a week (30); similar results were found in inactive young Germans (493). In summary of all random controls trials the Committee Report
concluded a strong effect of a moderate (>25minutes/day) amount of physical
activity (both resistance and aerobic) in reducing anxiety symptoms.

32.3 Mechanisms


A decline in cognitive function may be a cause of depression. For instance,
in over 5,000 elderly women (mostly white), increasing symptoms of depression were
associated with reduced cognitive function in each of 3 tests, showing a negative
correlation (575). Those with 6
cognitive-impairment symptoms had a relative risk of 2.3 times to be depressed than
those with 0–2 impairments. While it is unknown whether the mechanisms of
increased depression and decreased cognitive function are similar in different
populations (for example young vs. old), reduced brain tissue, blood flow, or otherwise
are found in both suggesting a similar cause if not similar mechanism.

Biochemical adaptations


Potential roles of elevated gluccocorticoids due to a failure to suppress
the hypothalamic-pituitary-adrenal (HPA) axis have also been studied in healthy
humans. Physically active individuals have less stress response to the same absolute
exercise in terms of cortisol release (324).
Furthermore, the most fit group had a diminished release of cortisol in response to
intravenous ovine corticotropin-releasing hormone (324).


In rats, physical inactivity increases the ACTH levels rather than cortisol
in response to a stressor (143, 178). However, questions remain about the level of
physical activity necessary for beneficial HPA adaptations with some studies
suggesting intense physical activity can have a detrimental effect (97).

Changes in monamines and other circulating markers may also be involved in
inactivity-induced increases in depression and anxiety, similar to changes in
cognitive function. Catecholamines, specifically norepinephrine (NE) signaling and
production, is increased with physical activity in the pons medulla, which is where
the only NE-producing nerves are found that serve the frontal cortex, hippocampus,
thalamus, and cerebellum; a major source of NE-serving nerves to the hypothalamus,
amygdala, and spinal cord [reviewed in (142)].. A decrease in NE levels in response to repeated stress is prevented by
chronic VWR in rats (142), with a threshold of
as little as 30 min/day of VWR (149). In
addition to increased NE levels at the site of production, microdialysis showed
increased levels and turnover of NE where the neurons terminate in the spinal cord is
found after just 1 hour of treadmill running in rats (396).

Levels of 5-hydroxytryptamine (serotonin), an important neurotransmitter
for mood, and its receptor are potentially increased by acute treadmill running due to
the increased lipolysis and FFA binding to albumin. By reducing albumin, tryptophan
levels are higher in circulation and have an increased entry into the brain, leading
to increased synthesis of serotonin (95).



In a large twin-population based in the Netherlands, data about
leisure-time exercise and anxiety and depression symptoms were measured.
Interestingly, in genetically identical twin-pairs, the lack of leisure-time exercise
did not increase anxiety or depression symptoms (126). However, this study took a very narrow approach at looking at exercise
level, whereby physical activity, such as walking or cycling work, or vocational
related physical activity were not considered (571). Lastly, adolescent girls with an allele for high BDNF received no
protective effects against depression and anxiety symptoms by avoiding physical
inactivity, while those with the allele causing lower BDNF level were protected (330).


Exercise stress response has been looked at using rats selected for either
high endurance (high capacity runners; HCR) or low endurance (low capacity runners;
LCR) based on a run to volitional/behavioral exhaustion. Counter to the hypothesis,
the HCR had more anxiety-like behavior on a maze test and higher levels of cortisol in
response to a restraint test (547). The
surprising result may be in part due to the fact that the HCR selection is based on
avoiding the electrical shock and, thus, avoiding stress in addition to their
volitional/behavioral endurance capacity.

32.4 Clinical significance

Physical inactivity causes up to 1/3rd of depression. Physical
activity can primarily prevent 20–30% of depression.

33. Bone (Osteoporosis)

33.1 Definition

Decrease in bone mass with decreased density and enlargement of bone spaces
producing porosity and brittleness.

33.2 Etiology

Among males >50 yrs old, prevalence of osteoporosis and osteopenia was
6% and 47%, respectively; and in females >50 yrs of age, prevalence was 7% and 40%,
respectively (202).

Etiology – Lack of gravity and physical inactivity

Four cosmonauts who spent up to 7 months on the Russian space station Mir
lost ~1–1.6% of bone mineral density mainly from the spine, femoral neck,
trochanter and pelvis (540). The spaceflight
data shows that loading bone (gravity) is a powerful stimulus to maintenance of bone
mass. In spinal cord injury to one monozygotic twin, as compared to their non-injured
monozygotic twin, bone mineral content and bone mineral density were reduced 42% and 35%
in the legs, respectively, and 50% and 29% in the pelvis, respectively (29). Non-weight-bearing athletes (bicycling) had
lower bone mineral mass of whole-body and spine than weight-bearing athletes in males
(426, 427). The spinal cord injury and cycling data demonstrate that absence of
gravitational loading is a powerful stimulus for loss of bone mass.

An actual cause: lack of exercise

Bone is lost from the lumbar spine and femoral neck at the rate of ~1%
per year in sedentary pre-and postmenopausal women (). Inactivity, i.e., reduced gravitational loading and muscle contraction
forces on the skeleton, might contribute to aging-associated bone loss as suggested by
the studies described below. (Exercise: the key to bone health through the life

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0014.jpg

Peak value for bone mineral density (BMD) in third decade of life contributes to the age
in later life at which threshold for osteoporosis is passed. The higher the peak value for
BMD, the later age in life delays age at which BMD reaches the osteoporosis threshold,
below which osteoporosis is diagnosed. The upper line reflects a population that had high
bone-loading physical activities throughout lifespan with genes predisposing to high bone
strength in contrast to the lower line reflecting low lifetime bone loading with genes
predisposing to low bone strength. Adapted from Rizzoli et al. (438) who modified original figure of Hernandez et al. (235). [Reproduced with permission from (438)].

33.3. Primary prevention

Exercise-training programs prevent or reverse almost 1% of bone loss per year
in the lumbar spine and femoral neck in both pre-and postmenopausal women, who were
presumably sedentary, in a meta-analysis (572).
Mixed loading exercise programs combining jogging with other low-impact loading activity
and programs mixing impact activity with high-magnitude resistance exercise were effective
in reducing postmenopausal bone loss at the hip and spine (329). In a first study, a 3-yr program of combined low-volume,
high-resistance strength training, and high-impact aerobics maintained bone mineral
density at the spine, hip, and calcaneus, but not at the forearm (which lost 3%), in early
post-menopausal women (162). Importantly, the
non-trained group bone mineral density decreased 2–8% over the same 3-yr period.
These findings emphasize the clinical importance of avoiding inactivity in the early
post-menopausal period and the specificity of the lack of impact on critical bones with
high fracture rates in later life (162). In a
second study, site-specific increases in bone density by resistance training happened in
50–70 year-old postmenopausal women and men who exercised ~3–4 days
each week for 1 yr (212). As in the first study,
inactive “control” subjects lost bone mass.

Finally, it is important to emphasize the site-specificity of exercise on bone.
Only bones subject to loading will become stronger as adaptations are site-specific.
Further, not all “weight-bearing” exercise is equivalent when it comes to
increasing bone mass/strength, e.g., comparisons of walking (which does relatively little)
< jogging < jumping.

33.4 Physiological mechanisms

Physical inactivity results in reduced mechanical, both gravitational and
muscle contraction, forces which in turn induces catabolism (resorption) by promoting
osteoclastogenesis with concurrent suppression of both bone formation and
osteoblastogenesis. Dynamic exercise alters the balance between bone formation and
resorption to favor anabolism through osteoblast recruitment and activity.

Mechanical loading of bone occurs in response to compressive forces from
gravity during walking or running, or to in response to muscular forces at the bone
attachments during contractions. Physical activity, alone, only increases strain on bone
by ~0.1%. However, strains of 1–10% are needed to activate bone cells. The
implication, then, is that a mechanism must therefore exist to amplify strains from
physical activity (compressive impact forces from striking surfaces and tensile forces
from contracting skeletal muscle at attachment sites to bone) to exceed the threshold
needed to activate bone cells. Ozcivici et al. (394) conclude that mechanical targeting of the bone marrow stem-cell pool might,
therefore, represent a novel, drug-free means of slowing the age-related decline of the
musculoskeletal system.

33.5 Cellular mechanisms

Current thought for how a bone strain of ~0.1% can be amplified to a
1–10% has been suggested based upon 25 years of publications by Riddle and Donahue
(437). Deformation of skeletal tissues induces
pressurization of interstitial fluid, producing a positive pressure gradient from the
matrix to the haversian cannels, allowing bone cells perceive changes in their mechanical
environment (an amplification mechanism) (437). It
is not completely settled whether the conversion of the physical force of fluid flow to a
biochemical signal is by means of integrin/cytoskeletal transduction of forces or
chemotransport ion channels, or both.

33.6 Clinical consequences

Physical inactivity is a primary cause of bone loss in weight-bearing bones.
Physical activity results in both gravitational and muscle-contraction loading of the
skeleton and, therefore, is primary prevention of osteoporosis.

34. Osteoarthritis (OA)

34.1 Definition

Degeneration of cartilage and its underlying bone within a joint
(Cross-reference: Osteoarthritis and exercise: cause and effects)

34 2 Etiology

The type and duration of physical activity is a key factor determining whether
exercise is beneficial to joint health or not. Buckwalter wrote,

Participation in sports that cause minimal joint impact and torsional
loading by people with normal joints and neuromuscular function may cause osteophyte
(bony projections that form along joints) formation, but it has minimal, if any,
effect on the risk of osteoarthritis. In contrast, participation in sports that
subject joints to high levels of impact and torsional loading increases the risk of
injury-induced joint degeneration. People with abnormal joint anatomy or alignment,
previous joint injury or surgery, osteoarthritis, joint instability, articular surface
incongruity or dysplasia, disturbances of joint or muscle innervation, or inadequate
muscle strength have increased risk of joint damage during participation in
athletics” (71).

The NPAGCR(412) lists sports/activities
associated with an increased prevalence of incident osteoarthritis as being ballet/modern
dance, orienteering, running, track and field, football (American and Australian rules),
team sports (basketball, soccer, and ice hockey), boxing, weight lifting, wrestling,
tennis, and handball. Confirming the specificity of sport/activity is a longitudinal study
that followed 45 long-distance runners and 53 control subjects from age 58 in 1984 until
2002 with a series of knee radiographs to examine the progression of OA (93). In 2002 20% of runners and 32% of controls had
prevalent OA, with 2.2% and 9.4% being severe. The small size of this study prevented this
difference from reaching statistical significance. The NPAGCR(412) concluded that no evidence presently exists to indicate that
regular moderate to vigorous physical activity of 30–60 minutes for general health
benefits increases the risk of developing osteoarthritis in those without pre-existing
major joint injury.

34.3 Clinical significance

Primary prevention would be to avoid those sports predisposing to later life
development of osteoarthritis.

35. Balance

Balance is defined as the ability to maintain the center of gravity
for the body within the base of support that produces minimal postural sway. Its etiology
can be related to lack of usage of nervous system controlling skeletal muscle movement
against gravity. For example, living in space for as little as 9 days accelerates problems
of equilibrium on standing, walking and coordination on return to Earth (caused by
inappropriate neurovestibular responses) (540). With
eyes closed on this platform astronauts complain of having no sensation of falling. Similar
balance dysfunctions occur with aging. It is likely that improper balance upon return to
Earth from spaceflight and with aging have a common denominator of insufficient exercise
against gravity. Lack of appropriate balance occurs in later life. The NPAGCR (412) concluded that the strong evidence exists in old
Americans that the risk of falls is reduced from physical activity programs that emphasize
both balance training and muscle-strengthening activity with some aerobic activity,
especially walking. The NPAGCR (412) further
indicates that no evidence indicates that planned physical activity reduces falls in adults
and older adults who are not at risk for falls. The clinical significance for primary
prevention requires exercises that retain normal balance to reduce falls in individuals at
risk for falls (124).

Bone fracture/falls

Bone fracture is defined as a break, rupture, or crack in bone or cartilage.
Physical inactivity, specifically lack of loading bones against gravity, will cause loss
in bone density, which increases the risk of bone fracture. Physical inactivity is
directly associated with fracture risk, particularly for fractures of the proximal femur
(i.e., increased physical inactivity increases fracture risk), according to NPAGCR (412). Based on epidemiologic studies that evaluated
present dose-response associations, the minimal levels of physical activity that were
significantly associated with reduced fracture risk were at least 9 to 14.9 MET-hours per
week of physical activity. The METs translate to >4 hours per week of walking
(types of exercise that mechanically load the proximal femur as opposed to cycling (426) or other activities that do not load the femur).
Primary prevention with exercises that load bones can reduce falls in those with balance
irregularities, fall-related fractures, and several risk factors for falls in individuals
with low bone density (124).

37. Rheumatoid Arthritis (RA)

RA is a chronic autoimmune disease characterized by inflammation of
the joints, frequently accompanied by marked deformities, and ordinarily associated with
manifestations of a general, or systemic, affliction. While no preventive measures are
currently known, physical activity is critical to not allowing RA to progress. Studies show
no harmful effects of physical activity, and some even show a positive effect in the
reduction of symptoms (73). High-intensity physical
activity is better than low at preventing the worsening of symptoms. The mechanism by which
physical activity has a beneficial effect on RA might be its countering the global increase
in inflammation that normally occurs during the progression of RA.

38. Cancer

38.1 Definition

A malignant tumor of potentially unlimited growth that expands locally by
invasion and systemically by metastasis.

38.2 Comments on cancer types

Majority of cancer prevalence has environmental component

Inherited genetic factors make a minor contribution to susceptibility to most
types of neoplasms, implying that the environment has the principal role in causing
sporadic cancer (319). A review on targets and
pathways for cancer prevention exists (442).

Risks of only some cancers rise with physical inactivity

Physical inactivity increases the prevalence of some site-specific (colon,
breast, and endometrial cancers), but, to date, not all cancer types. The specificity of
cancer types enhanced by physical inactivity supports a notion that mechanisms of
inactivity-induced cancers are specific to each site-specific cancer. Stated in an
opposite manner, some cancer types are not caused by physical inactivity.
(Cross-reference: Cancer)

Those cancers whose risk is enhanced by inactivity will be considered

39. Colon cancer

39.1 Cross-sectional and longitudinal studies

A literature review through March 1997 found 23 case-control (cross-sectional)
studies and 17 cohort (longitudinal) studies. In both types of studies, those in the
highest physical activity category had ~40%–50% reduction in risk of colon
cancer compared with the least active category (111). A decade later, the NPAGCR(412)
concluded physical activity produced a medium reduction of 30% in colon cancer from 8 case
-control and 12 cohort studies, respectively.

39.2 Randomized control trials

The NPAGCR (412) states that RCTs have
demonstrated effects of physical activity interventions on cancer risk factors, which
further support a role of physical activity in reducing risk for cancer.

39.3 Mechanisms


Suggestions by others how physical inactivity might increase prevalence of
colon cancer are: 1) lengthening the transit time of feces, thus prolonging exposure
to fecal carcinogens (114); 2) causing higher
levels of blood insulin, thus producing insulin resistance, which is a risk factor for
cancer (198, 207); 3) causing higher levels of blood free IGF-I (198), exposing the rapidly turning over colon epithelium to higher
levels of anabolic hormone that is associated with greater colon cancer incidence
(198); 4) preventing synthesis and release
of exercise-derived, anti-inflammatory myokines, thus removing their systemic effect
(62); and/or 5) producing positive energy
expenditure, increasing body fat (9).


ApcMin/+ mice have a nonsense mutation at codon
850 in the Apc (Adenomatous polyposis coli) gene
that predisposes them to both small and large intestinal adenomas, thus these mice
have been used as a model of colon cancer (359). Colbert et al. reported two exercise studies using
ApcMin/+ male mice. In their first study, 3 weeks of
voluntary running followed by 5 weeks of treadmill running did not alter polyp
development or serum IGF-I (106). In their
second study of ApcMin/+ mice, 10 weeks of voluntary
running decreased polyp number and increased serum IGF-I in male
ApcMin/+, with IGF-I not being related to polyp number
(107). Carson and co-authors observed that
treadmill exercise reduced polyp number and size in male, but not female
ApcMin/+ mice, while voluntary wheel running did not
elicit a change in polyp number or size (337).
Carson and co-authors reported that treadmill training caused intestinal polyps of
ApcMin/+ mice to have 35%, 73%, and 43% decreases in
macrophages, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling
(TUNEL)-positive cells (index of apoptosis), and Bax protein 43% (proapoptotic
protein), respectively (21). β-Catenin
phosphorylation was elevated 3.3-fold in polyps from these exercised mice. Ju et al.
(262) found that colon tumorigenesis was
~40% greater in sedentary than voluntary running mice
ApcMin/+ mice. The sedentary mice had higher
IGF-1/IGFBP-3 ratios and aberrant β-catenin signaling, as compared to the
voluntarily running mice (262).

39.4 Clinical significance

The lowest activity group has ~40% increased prevalence of colon cancer
compared to the highest activity group. Physical activity is a primary preventer of colon

40. Breast cancer

40.1 Cross-sectional and longitudinal studies

The NPAGCR (412) concludes from 63
published studies that physical activity was associated with a medium reduction of 20%
across all studies. However, the NPAGCR reports the range of reductions in breast cancer
for all population-based case-control studies to be 20%–70% and for cohort studies
to be 20%–80%.

The effect of physical activity on breast cancer reduction differs between pre-
and post-menopausal conditions. A 2007 systemic review of 19 cohort and 29 case-control
studies found a strong evidence for risk reductions ranging from 20% to 80% by physical
activity for postmenopausal breast cancer (347).
However, much weaker evidence is available for physical activities reduction on risk of
premenopausal breast cancer, so no effect existed. Combining pre- and postmenopausal
breast cancer resulted in a 15–20% decreased risk by physical activity. A trend
analysis indicated a ~6% decrease in breast cancer risk for each additional hour of
physical activity per week assuming that the level of activity would be sustained.

40.2 Mechanisms

Neilsen (373) suggests that physical
inactivity might increase breast cancer prevalence by any or the following: higher than
normal BMI, androgens, estrogens, lifetime exposure to estrogen, leptin, insulin, insulin
resistance, TNF-α, IL-6, CRP, and inflammation. Lower levels of steroid hormone
binding protein by physical inactivity have been suggested to increase breast cancer risk.
The mechanisms by which long-term physical activity lowers postmenopausal breast cancer
risk, however, remain unclear (373).

Thompson et al.’s comprehensive review provides extensive literature to support
three hypotheses by which physical inactivity could enhance breast cancer’s prevalence
(509). Hypothesis 1 proposes that
inactivity-induced changes in circulating growth factors and hormones activate the
mTOR-signaling network to increase proliferation and decrease apoptosis in breast cells
while stimulating new blood vessel formation. Hypothesis 2 states that inactivity
increases breast cells responsiveness to physiological stresses, potentially through FoxO,
Sirtuin, and/or adipokine/myokine signaling. Hypothesis 3 says that inactivity increases
glucose and glutamine availability in mammary carcinomas, thereby attenuating breast cell
apoptosis and, thus, increasing the accumulation of breast tumor masses.

40.3 Clinical significance

The lowest activity group has ~25% increased prevalence of breast cancer
compared to the highest activity group. Physical activity is a primary preventer of breast

41. Endometrial cancer

The NPAGCR (412) found growing evidence
to support reduced risk of endometrial cancers in physically active versus sedentary
persons. A meta-analysis of prospective studies published through to December 2009 found
that physical activity was clearly associated with a 30% lower risk of endometrial cancer

42. Activity prevention of female reproductive disorders

42.1 Pregnancy

Multiple methodological pitfalls exist in the studies published (196), so conclusions made about benefits of physical
activity on female reproductive health remain for further testing. Nonetheless, the
consensus is that exercise can serve as primary prevention during pregnancy (196, 339).
Maternal outcomes to be briefly discussed are gestational diabetes mellitus (GDM),
preeclampsia, and weight gain [Summaries below are taken from an extensive review (196)].

42.2 Gestational diabetes mellitus (GDM)


Any degree of glucose intolerance with onset, or first recognition, during
pregnancy. Women in the high-risk category not found to have GDM at initial screening
should be retested between 24 and 28 wks of gestation.


Overall prevalence of gestational diabetes is 4%-8%, depending on U.S. locale
(202). The American Diabetes Association has
stated, “Women with clinical characteristics consistent with a high risk of GDM
(marked obesity, personal history of GDM, glycosuria, or a strong family history of
diabetes) should undergo glucose testing… as soon as feasible” (10). Note the statement does not include physical
inactivity as a risk factor.

Exercise outcomes

Gavard and Artal’s have a lengthy review (196). They conclude that the balance of evidence is that exercise is
protective against GDM. The protective effect seems to be particularly strong for
vigorous or intense exercise, particularly for women reporting physical activity both
before and during pregnancy. Studied in their review mentioned no deleterious exercise
effects. Obviously, exceptions may occur and obstetricians should be consulted.

Clinical significance

GDM occurs during pregnancy and having GDM increases the risk of T2D later in
life in both mothers and their offspring carried during GMD. Physical inactivity would
increase chances of GDM. Physical activity is primary prevention.

42.3 Preeclampsia


A condition developing in late pregnancy that is characterized by a sudden
rise in blood pressure, excessive weight gain, generalized edema, proteinuria, severe
headache, and visual disturbances and that may result in eclampsia if untreated.

Exercise outcomes

Gavard and Artal (196) concluded that
the balance of evidence still supports that exercise is the primary prevention against
preeclampsia, with the effects being particularly strong for vigorous or intense
exercise. No deleterious effects of exercise on preeclampsia were found, but Gavard and
Artal caution that purposes of the investigations cited by them may not have been to
report deleterious effects (196).

Clinical outcomes

Physical activity seems to be helpful in preventing preeclampsia from the
limited numbers of studies on the topic.

42.4 Excessive weight gain during pregnancy

Gavard and Artal (196) conclude that
prospective clinical trials are needed to establish exercise’s effectiveness for lowering
risk of maternal and fetal comorbidities during pregnancies with excessive weight-gain.
Likewise, Shirazian and Raghavan (471) call for
prospective interventional studies to demonstrate the benefits of weight limitation on
pregnancy outcomes.

42.5 Polycystic ovarian syndrome (PCOS)


Accumulation of numerous cysts on the ovaries associated with high male
hormone levels, chronic anovulation, and other metabolic disturbances. Classic symptoms
include excess facial and body hair, acne, obesity, irregular menstrual cycles, and

Exercise outcomes

Limited information is available for the primary prevention of PCOS by
physical activity. Exercise appears to provide secondary/tertiary prevention, so studies
of primary prevention seem justified. Thomson et al.’s review on treatment and
management of PCOS conclude, “…few well-controlled randomized studies have
been conducted evaluating the benefits of exercise training…Future research with
rigorous study designs is needed to determine specific exercise
guidelines…” (510).

42.6 Female athlete triad (Triad)


A combination of disorders frequently found in female athletes that includes
disordered eating, osteoporosis, and oligo- or amenorrhea.

The Triad is discussed in detail by an American College of Sports Medicine
position stand (370). The position stand places
emphasis on optimizing energy availability for primary prevention. The stand also
states, “No pharmacological agent adequately restores bone loss or corrects
metabolic abnormalities that impair health and performance in athletes with functional
hypothalamic amenorrhea” (370). Eating
disorders warrant psychotherapy.

42.7 Dysmenorrhea


Painful cramps during menstruation.

Exercise outcomes

Physical exercise has been suggested as a non-medical approach to manage
these symptoms, but Cochrane review (66) cautions
their conclusion is limited to a single RCT with a small sample size of limited quality.
Primary prevention by physical activity may be plausible but is not sufficiently

43. Activity prevention of male reproductive disorders

43.1 Erectile Dysfunction (ED)


Impotence, or erectile dysfunction (ED), is defined by the as the inability
for a male to maintain erection of the penis sufficient for sexual performance.


It is estimated that ED affects 30 million males in the United States. ED
prevalence increases steadily with age, from 6.5% in men aged 20 to 29 years to 77.5% in
those 75 years and older (453). In addition to
physical inactivity, other risk factors are age, CVD, T2D, high cholesterol, smoking,
recreational drug use, and depression are all risk factors. Erections are established
through a set of well known evens whereby neural stimulation (of various types) results
in a release of nitric oxide, increased cGMP, and ultimately vasodilation of the smooth
muscle in the arteries supplying the penis, which expands penile volume by increased
blood flow into the corpora cavernosa. This process is reversed by phosphodiesterase
type 5 (PDE5) breaking down cGMP; thus, pharmaceutical treatments of ED inhibit PDE5

Cross-sectional evidence

Several large cross sectional studies exist to suggest that physical
inactivity is a cause of ED. In a cohort of over 31,000 men over the age of 50 one third
of men had ED (19). Men engaged in at least 32.6
MET equivalent hours of exercise per week had a significantly lower relative risk (0.7)
than those undergoing less than 2.7 MET activity hours/week, a similar reduction in risk
as obesity increased risk (19). For instance in
the Boston Area Community Health (BACH) Survey of 2031 males aged 30–79 lifestyle
contributed to 12.2% of the total subject with clinically validated ED (295). However, when all covariates were considered,
lifestyle alone could only explain 0.9% of the ED. In a prospective study from the same
population those went from no physical activity to some physical activity had a similar
relative risk (OR of 0.5) as those that maintained high levels of physical activity (OR
of 0.3) (131).

Interventional evidence

Utilizing a randomized-single bind design 110 obese men with ED, as defined
by a International Index of Erectile Function (IIEF) less than 21, were either placed
into an intervention group with the goal of 10% weight loss by walking 4 hours a week
and reducing caloric intake or a control group. After 2 years, using an intent-to-treat
analysis, the intervention group spent 195 min/wk doing physical activity and had a
significant improvement in IIEF scores from 13.9 to 17, with no change in the control
group. Furthermore, physical inactivity levels were independently associated with ED
(170). In a follow up study using twice as
many subjects this same group demonstrated that lifestyle intervention for two years
reduced the prevalence of ED from 66% to 44% (169). Those within the lifestyle group that exercised more than 4 hours/wk
were 1.9 times more likely to reverse ED than those in the lifestyle group that remained
sedentary, correcting for changes in diet and other lifestyle habits. Using a higher
intensity exercise of 75–80% VO2max for 60 minutes, 3 times a week,
previously sedentary, but otherwise healthy men, had significant improvements in
subjective sexual experiences. The improved sexual experiences correlated with the
improvement in fitness (557).

Potential Mechanisms

Since the underlying pathology of physical inactivity-induced impotence is
similar to that of physical inactivity-induced endothelial function, many of the
mechanisms though which exercise can be preventable are likely similar. However, the
penile vasculature does not exhibit increased blood flow during treadmill running by
Yucatan pigs (361). A few potential mediators of
this are secreted factors from skeletal muscle (myokines), adipose tissue (adipokines),
liver (hepatokines) or other changes in circulating factors, such as the physical
activity-induced increased in testosterone in young, healthy men and adolescent boys
(130, 326), an important regulator of vasculature health [reviewed in (344)]. Nevertheless, considerable evidence now
suggests that chronic exercise training produces beneficial endothelial adaptations in
vasculatures not recruited/active during exercise bouts. (Cross-reference: Effects of
exercise on distribution of cardiac output in the peripheral circulation)

Clinical significance of primary prevention Physical inactivity
is one cause of ED. Physical activity can be a primary preventer of ED.

43.2 Prostate Cancer (PCa)

The overalle effects of physical activity on primary prevention of PCa are
unclear. The NPAGCR concluded no association exists between physical activity and prostate
cancer (412). On the other hand, the NPAGCR states
a statistically significant trend towards decreasing prostate cancer risk was observed
with increasing physical activity in several studies. Tertiary prevention may exist as
Kenfield et al. (271) provided evidence that
physical activity was associated with lower mortality and PCa mortality in men previously
diagnosed with PCa. Barnard et al. (23) noted that
serum from subjects performing regular aerobic exercise led to reduced growth and
increased apoptosis of lymph node cancer of the prostate tumor cells in

44. Pain

44.1 Definition

A basic bodily sensation that is induced by a noxious stimulus, received by
free nerve endings, and characterized by physical discomfort.

44.2 Occurrence of low-back pain (LBP)

One-quarter of adults have at least 1 day of low back pain in a 3-month period
and most adults suffer low back pain at some point during their lives (192). Well-trained individuals seem to exhibit higher
pain tolerance to skeletal muscle biopsies and to skin suturing, but to our knowledge
clinical trials testing the hypothesis are not available.

44.3 Clinical trials

Limited evidence exists according to a systemic review of 10 RCTs and 5
non-randomized clinical trials for the overall effectiveness of exercise to prevent LBP in
humans (31).

44.4 Mechanisms

Moderate-intensity aerobic exercise reduced cutaneous and deep tissue
hyperalgesia induced by acidic saline and stimulated neurotrophic factor-3 synthesis in
gastrocnemius but not the soleus muscle (469).
Sharma et al. (469) caution that their results are
limited to animal models and cannot be generalized to chronic pain syndromes in

44.5 Clinical significance

Exercise training has been long suggested to reduce pain, but not to be a cure
to the source of the pain [see (469) for refs.],
but sufficient publications to verify the claim do not exist. Bell and Burnett’s review
(31) concludes that future research is needed to
clarify which exercises are effective and the dose-response relationships regarding
exercise and low-back-pain outcomes.

45. Digestive tract diseases

45.1 Definition

The digestive tract begins in the mouth, ends in the anus, and includes
accessory organs of digestion. Scores of digestive tract clinical conditions exist (368). Inactivity increases digestive system disorders.
Some (cancers, non-alcoholic liver disease, and diabetic pancreas) are considered in
elsewhere in the article.

45.2 Diverticulitis


Diverticulitis is an inflammatory swelling of an abnormal pouch
(diverticulum) in the intestinal wall, usually in the large intestine (colon).

Physical activity is a primary preventer

Physical activity lowered the risk of diverticulitis and diverticular
bleeding during an 18-yr of follow-up of 47,228 US males in the Health Professionals
Study (492). Vigorous-intensity activity
subjects largely explained the association, a conclusion verified by Williams (562).

45.3 Gallbladder disease


Gallbladder disease includes inflammation, infection, stones, or blockage
(obstruction) of the gallbladder.

Physical activity is a primary preventer

Physical activity levels are inversely related to prevalence of gallbladder
disease in an American Indian population (285).


Treadmill running promoted changes in hepatic gene expression that increased
cholesterol uptake by the liver while simultaneously increasing the catabolism of
cholesterol to bile acids, thus effectively reducing cholesterol saturation in the bile.
Wilund et al. (566) suggest their results
describe a potential mechanism by which exercise improves cholesterol clearance from the
circulation while simultaneously inhibiting gallstone formation.

45.4 Clinical significance

Observational studies suggest that diverticulitis, constipation, and
gallbladder disease can be caused by physical inactivity and primarily prevented by
increased activity. Physical activity may reduce the risk of gastrointestinal hemorrhage
and inflammatory bowel disease although this cannot be substantiated firmly (409).

46. Chronic respiratory diseases

46.1 Definition

Chronic diseases of the airways and other structures of the lung constitute
chronic respiratory diseases. Some of the most common are asthma, chronic obstructive
pulmonary disease (COPD), respiratory allergies, sleep apnea, occupational lung diseases
and pulmonary hypertension. (Cross-reference: Chronic lung disease)

46.2 Etiology

Causes of these respiratory diseases are varied and include behavioral
(smoking), environmental (air pollution and occupational hazards), and suppression of the
immune system.

46.3 Physical inactivity

There are no studies to our knowledge showing that physical inactivity is
associated with an increase in most chronic obstructive pulmonary diseases. With sleep
apnea it is difficult to determine whether physical inactivity is a cause or a result of
the sleep apnea resulting in a viscous cycle of less sleep coupled with less activity
(549). With asthma, an interaction of an
increased environmental pollution with physical activity may be the factor for more recent
studies finding higher asthma in athletes. In two cross-sectional studies, asthma was more
prevalent in swimmers [Odds ratio (OR) = 10], long distance runners (OR = 6), and power
athletes (OR = 3–4), than in less active individuals (232, 233). However, in
contrast, an older study of Finnish athletes that died between 1936 and 1985 showed that
they were no more likely to have asthma and about 50% less likely to die of any pulmonary
disease than non-athletes (291). Our suggestion is
that increased environmental pollution interacting with physical inactivity, rather than
physical activity per se, is a major cause for increased asthma rates in
athletes. The conclusion is consistent with an increase in asthma in the general
population as well in the last several decades.

The sum of data suggests that a “J-shaped” curve exists where
physical inactivity and extreme physical activity increase the risk the greatest for
acquiring upper respiratory tract infections (URTI). While some prospective studies
suggest a greater risk for URTI after a competitive event (381, 382), with increasing
amount of training (229, 408), and higher in faster finishers (487) others show no difference after an event (159) and lower UTRI with 6–7 METs/day of any activity (331). A decreased prevalence of UTI existed in two
intervention studies utilizing lower levels of physical activity [one involving elderly
women (380) and the other mildly obese females
(383)] However, many of these studies contain
methodological problems including, failure to report bouts of physical activity, UTRI are
only reported never verified by virus analysis, higher medical awareness during high
intensity training, contact with other infections (large marathon), stress, nutrition,
supplements, and all the studies are focused on exercise not physical inactivity.

46.4 Mechanisms

There are several excellent reviews that the reader is directed to on
immunosuppression following high levels of physical activity (64, 199, 401). The changes in immune function include low levels of lymphocytes
and lymphocyte function (301), impaired
phagocytosis, impaired neutrophilic function with prolonged exercise (401), neutrophil degranulation (400), reduced monocyte function (302), reduced oxidative burst activity, and potentially lower mucosal
immunoglobulin levels (201).

46.5 Clinical significance

While regular moderate exercise reduces susceptibility to infection compared to
sedentary, prolonged bouts of strenuous exercise cause a temporary depression of various
aspects of immune function (e.g., neutrophil respiratory burst, lymphocyte proliferation,
monocyte antigen presentation) for ~3–24 hr, e.g., after prolonged
(>1.5 h), of moderate to high intensity (55–75% maximum O2
uptake) without food intake (199, 200). Periods of intensified training (overreaching)
lasting 1 wk or more may result in longer lasting immune dysfunction (199, 200)

47. Chronic kidney disease (CKD)

CKDs damage the kidneys so that they are no longer capable of adequately removing
fluids and wastes from the body or of maintaining the proper level of certain
kidney-regulated chemicals in the bloodstream. (Cross-reference: Chronic renal failure). CKD
is a secondary consequence of physical inactivity’s increasing hypertension and T2D
prevalence. Albumin to creatine ratio (ACR) is a marker of kidney function. The U.S. DPP
found no change in ACR despite reductions in diabetes development with lifestyle reduction
of T2D (136). In contrast, the Australian Diabetes,
Obesity, and Lifestyle Study found that increased television watching or low self-reported
leisure-time physical activity were associated with increased odds ratio of albuminuria and
low estimated glomerular filtration rate in 6,000 subjects (325, 558). Physical inactivity was one of
multiple covariants accounting for early decline in renal function in 1400 U.S. diabetic
blacks (287). Norwegians (n = 65,000) undergoing no
or little physical activity were twice as likely to have a low estimated glomerular
filtration rate (215). In summary, physical
inactivity contributes to development of CKD.

48. Clinical significance of physical inactivity as one cause of 35 chronic

48.1 Volume of evidence

Much of the article has presented evidence to prove that physical inactivity is
a primary, upstream event that causes substantial increases in risk factors for 30 chronic
diseases/conditions (; ). The volume of evidence in itself is
overwhelming. The clinical significance of physical activity itself is underappreciated as
specific disease risk factors, themselves are often the prime objective of research and
clinical care, rather than emphasis being placed on one major cause (physical inactivity)
that is upstream of these risk factors.

Table 11

Estimations of the incubation durations to overt clinical conditions for
diseases/conditions caused by physical inactivity and of the percentage reductions in
diseases primarily prevented by physical activity (where sufficient information exists in
healthy humans aged 20–65 yrs of age).

Disease/condition Inactivity causes (Longer-term most days of the week
implies years or decades while short-term is weeks to months)
Exercise primarily preventsdelays
* Just meet
guidelines for moderate activity (30 min/day), not intent-treat.
** Our
speculated asymptote for maximum in dose-response
~ Indicates our
speculated percentage
Premature death Long-term increase Yes, 30% reduction
VO2max (CRF) 30-yr acceleration in loss Yes, **Aerobic activity delays 30 yrs
Sarcopenia 24-yr acceleration to reach Yes, **Resistance activity delays 24 yrs
Metabolic syndrome Long-term increase Yes, *20–30%; **80%
Obesity Long-term increase Yes, *20–30%; **~80%
Insulin resistance Increase in 2–3 days Yes, * ~80%; **~95%
Prediabetes Intermediate-term increase Yes, * ~80%; **~95%
Type 2 diabetes mellitus Long-term increase Yes, * ~80%; **~95% (<60 yrs
Non-alcoholic fatty liver disease Long-term increase Yes, * ~80%; **~95%
Coronary heart disease Long-term increase Yes, *20%; **50%
Peripheral artery disease Long-term increase Yes, *20%; **50%
Hypertension Long-term increase Yes, 2.3-mm Hg lower diastolic blood pressure in
hypertension translates into an estimated 12% and 24% increased risks for CHD and
stroke, respectively
Stroke Long-term increase Yes, *25%; **35%
Congestive heart failure Long-term increase Yes, ~Should be major percentage
Endothelial dysfunction Increase in hours Yes, Asymptote should approach 90%
Atherogenic dysfunction Long-term increase Yes, ~Should be major percentage
Hemostasis Shorter-term increase Yes, ~Should be minor percentage
Deep vein thrombosis Increase in hours Yes, close to 100%
Dementia Long-term increase Yes, *35%
Depression and anxiety Shorter-term increase Yes, *20–30% (depression); *30% (anxiety)
Osteoporosis Long-term maintenance Yes, ~Should be major percentage
Balance Shorter-term loss Yes, ~Should be major percentage
Bone fracture/falls Long-term increase in old Yes, *35–60% (hip fractures) *30% (falls)
Colon cancer Long-term increase Yes, *40%
Breast cancer Long-term increase Yes, *25%
Endometrial cancer Long-term increase Yes, *30%
Gestational diabetes Increase in weeks Yes, ~ occurrence strengthens with predisposing
Preeclampsia Increase in weeks Yes, insufficient information
Erectile dysfunction Long-term increase Yes, Asymptote should approach 90%
Diverticulitis Long-term increase Yes. Insufficient information
Constipation Increase in days Yes, Asymptote should approach 100%
Gallbladder diseases Long-term increase Yes, insufficient information

48.2 Levels of evidence

Levels of evidence-based medicine vary in strength among the 30 chronic
conditions caused by physical inactivity. Pressure toward evidence-based medicine has come
from public and private health insurance providers, which refuse coverage of practices
lacking in systematic evidence of usefulness. Levels of evidence are ranked for policy
decision-making for health care distribution. The highest level of evidence is that there
is a systemic review of RCT trials (Level 1) (94).
The lowest level is based on mechanisms. However, models of extreme physical inactivity
are so dramatic in the magnitude of health detriment that Human Institutional Research
Boards IRB), for ethical reasons if side effects were to be muscle atrophy, for example,
the IRB would consider the risk and then review what arrangements have been made to
mitigate this risk. Our speculation is that IRBs would likely be hesitant, for ethical
reasons, to approve RCTs lasting years if irreversible overt chronic disease were to occur
because of physical inactivity. Therefore, RCTs to prove long-term physical inactivity
causes a chronic disease are unlikely to occur.

In 2008 the DPP Research Group commented,

“Debate prevails about whether resources (human and financial) would
be better spent on T2DM prevention or on its early detection and treatment. Early
detection is feasible through use of the same simple tests used in prevention
programs, and could be done much more economically than attempting to prevent diabetes
at the population level. Allocation of resources to intensive management of patients
with newly diagnosed diabetes could be preferable to prevention. A major drawback of
this approach, however, is that many people will have already developed macrovascular
disease (and, rarely, microvascular disease) before diagnosis. Nonetheless, no data
from clinical trials that have specifically compared prevention with early detection
and intensive treatment have yet been reported” (116).

Narayan et al. already predicted in 2003 that 50% of U.S. births in 2000 would
have diabetes in their lifetime (366). Seven years
later, the CDC has made a similar statement that diabetes prevalence could increase to 33%
of the population in 2050 in the worse case scenario (61). Boyle et al. (61) predict that
focusing on high-risk subgroups of the population the widespread implementation of
reasonably effective preventive interventions could considerably reduce, but not
eliminate, future increases in diabetes prevalence. Nonetheless, physical activity as
primary prevention remains largely not reimbursable and mostly absent from evidence-based
medical discussions.

Clinical significance

The primary prevention of physical inactivity is underappreciated.

49. Effectiveness of drug therapy for simultaneous primary prevention of 35 physical
inactivity conditions

49.1 Inability to mimic adaptive health benefits of physical activity

The natural adaptations to exercise provide a higher therapeutic index
(benefits/side effects) than any drug therapy could exceed (). The high therapeutic index of exercise is in part due to its systemic
complexity. It requires the integration of almost every physiological system (brain,
neural, vascular, liver, adipose, muscle, etc.) to accomplish several basic physiological
tasks such as movement and energy utilization. Since physical activity results in the
whole body disruption of homeostasis in multiple organ systems, a drug therapy alone
cannot replicate the entire ensemble its effects, without actually increasing physical
activity. The complexity of physical activity is highlighted by comparison to other traits
such as obesity. For instance, Reed et al. (431)
estimate that 31% (extrapolated to 6000 genes) of all viable knockout mice have altered
body weights. Such physiological complexity has been difficult to pharmacologically
address with no FDA approved obesity drugs since 1999. Since the relative contribution of
BMI for CVD and CHD has been estimated to be 10% and 7%, respectively (349), more than obesity is responsible for these
diseases, making an “exercise pill” even less likely than obesity pill. We
have published scientific criteria that must be met to legitimately use the terms
`exercise pill’ and `exercise mimetic’ (53).

49.2 Clinical significance

Drugs will not substitute for all health benefits from physical activity in
individuals medically capable of exercise.

50. Risk factors worsen over 6–12 months in RCTs

50.1 RCTs

The definition of chronic diseases contains the word “ongoing”.
Slentz, Houmard, and Kraus (481) cite evidence to
support the notion, “continued sedentary lifestyle in overweight or obese
individuals—particularly those who already have some metabolic
abnormalities—comes at a high metabolic cost, as numerous health-related variables
worsen over relatively short time periods” (51, 123, 218, 257). Examples from their
own studies are given. Twelve markers that increase the risk of chronic diseases became
worse in the 6-month inactive “control group”, including increases in body
weight, waist circumference, waist-to-hip ratio, VAT, total abdominal fat, fasting
insulin, LDL particle number, small dense LDL and LDL-cholesterol; and decreases in
insulin sensitivity, and fitness (35, 153, 246,
257, 284, 481).

Hunter et al. (251) have published
similar decrements for inactive “control” groups. Aerobic- and
resistance-exercise adherence for 1 yr prevented regain of VAT in healthy, overweight,
premenopausal women following a weight loss of 12 kg (251). Specifically, aerobic or resistance exercise adherers did not change in
visceral adipose tissue mass (1.6% and 0%, respectively) (80 min/wk), contrary to a 38%
increased VAT in the non-exercise adherers. While aerobic and resistance exercise adherers
still regained 3.1 and 3.9 kg of body weight, respectively, it was significantly less than
the 6.2 kg regain in exercise non-adherers, which was similar to the 6.4 kg gained in the
group that did not exercise (251). Thus, sedentary
“controls” became less healthy by increasing risk factors for chronic
diseases, compared to exercising groups in both the Slentz et al. (481) and the Hunter et al. (251) studies. Together the two studies illustrate contemporary inactive
“control” groups have a progressive worsening for risk factors of chronic
diseases that physical activity can be a primary prevention against. A similar theme was
apparent for osteoporosis, presented earlier in this article, i.e., bones in non-bone
loading group lose mass and density over a period of months. Importantly, the above
studies fit the definition of “slow in its progress and of long continuance”
for chronic diseases (551). The pathological
events from sedentary lifestyle are slow in progress.

51. Primary prevention of physical inactivity: childhood developing adult

51.1 Prevalence of physical inactivity in youth

58% and 92% of American children aged 6–11 and 12–19 yrs-old,
respectively, do not meet the recommended 60 min of daily physical activity (527). 73%–91% of Canadian children do not
accomplish sufficient daily step numbers (76). A
study was performed to compare lifestyle of children reminiscent of 100 yrs ago vs. modern
children. 11-yr old accelerometer values were found the following progressive declines in
physical activity in weekday minutes of activity/day: Old-Order-Amish (90 min) >
Old-Order-Mennonite (69 min) > rural Saskatchewan (58 min) > urban
Saskatchewan (49 min) (168). Tremblay et al. have
commented, “Groups that preserve a traditional lifestyle, with significant
incidental, lifestyle-embedded, physical activities, appear to achieve high levels of
daily physical activity and fitness and resist obesity (525).

51.2 Obesity in children and adolescents

Between the mid-1960’s and mid-1980’s, childhood and adolescent obesity ranged
between 4%–6% (). About 25 yrs later
(mid-1980’s to 2008), obesity (>95% BMI percentile for children in the 1960’s) in
children (6–11 yrs) had risen 5-fold from ~4% in 1963–1974 to 20% in
2007–2008, and in adolescents (12–19 yrs) rose 3-fold from
~5%–6% in between 1966–1980 to 18% in 2007–2008 () (386,
387). Even with a more liberal cutoff for
overweight and obesity, 36% of children and 34% of adolescents, rather than 15% were above
the 85th percentile of the 1960’s (386). Higher BMI during childhood is associated with an increased risk of CHD in
adulthood (20).

An external file that holds a picture, illustration, etc.
Object name is nihms-603913-f0013.jpg

Rise in childhood and adolescent obesity in U.S. From 1980’s to 2007–2008 obesity
in 2–5, 6–11, and 12–19-yr-old U.S. females increased
3–5-fold. [Tabular data is converted from graphic from (386, 387)]

51.3 Fasting blood glucose

The number of youth with elevated fasting blood sugar increased 87% from
1999–2000 to 2005–2006 (318). The
children with high fasting blood glucose have 49% lower glucose deposition index (504). More importantly, children with elevated fasting
blood glucose were 3.4 and 2.1 times more likely to develop prediabetes and diabetes,
respectively, as adults (378).

51.4 Prediabetes in children and adolescents

The number of US adolescents with elevated fasting glucose reached
~2,769,000 in 1999–2002 (147).
Within this population, adolescents of Mexican Americans decent are overrepresented (15.3%
of all Mexican American adolescents) relative to non-Hispanic whites (11.3%) and
non-Hispanic black adolescents (7.4%).

51.5 Adult-onset diabetes in our adolescents

Once considered a disease of adults, T2D is becoming increasingly common among
adolescents (376) with ~39,005 U.S.
adolescents having T2D in 1999–2002, and now almost as common as T1D in some
pediatric populations (147). Children in whom T2D
develops are at earlier risks for complications as adults from the disease, including
retinopathy, neuropathy, and cardiovascular and renal disease that may require decades of
treatment (188). Primary prevention of T2D is
essential in children and adolescents (327).

The estimated lifetime risk of developing diabetes for children born in 2000 is
32.8% for males and 38.5% for females, about 10–15% higher than current prevalence
(366). This risk is higher for Hispanics, at
45.4% for males and 52.5% for females. In addition to developing complications,
adolescents diagnosed as having diabetes have large reductions in life expectancy. For
example, Narayan et al. (366) estimated that if
diagnosed with T2D at age 20 yrs, males and females would die 17 and 18 years before
normal, with a reduction of 27 and 30 quality-life adjusted years.

51.6 Metabolic syndrome in adolescents

A major problem with identifying the metabolic syndrome in children and
adolescents is that there are no established criteria in this population (315). According to Cook et al., “In obese
adolescents only, the prevalence rates were 44.2% using the definition of Cook/Ford (113), 26.2% using the adult criteria, 14.1% using the
definition of Caprio, and 12.4% using the definition of Cruz” [As different
modifications of adult criteria for the metabolic syndrome were applied, the specific
criteria can be located in of and of (315)]. Children with BMI and waist circumference values greater than normal values
are at increased risk for the adult metabolic syndrome (500). Morrison et al. (356) contend that
evaluating 5- to 19-year-old children for metabolic syndrome and family history of
diabetes could identify children at increased risk of adult metabolic syndrome and T2D,
allowing prospective primary prevention of these outcomes.

51.7 Atherosclerosis

Atherosclerosis is a consequence of lifetime accumulation of vascular lesions
and plaques. Expectedly, Gillman indicates that the extent of coronary lesions in
adolescents is associated with risk factors including lipids, smoking, blood pressure,
obesity, and hyperglycemia (we add inactivity as a risk factor). Reversibility of
childhood metabolic syndrome is rare, thus leading to high risk of adulthood
cardiovascular disease” (197, 548).

51.8 Non-alcoholic fatty liver disease (NAFLD) in children

The prevalence of NAFLD among normal-weight children is 3–10%, rising up
to 40–70% among obese children (32, 33).

51.9 Cognitive function

Children and adolescents who are physically inactive will develop less
cognitive skills than more active cohorts, as discussed in Cognitive Function section.

51.10 Peak lifetime value determines years to reach clinical disease

Increases in bone mineral mass, skeletal muscle mass, and CRF occur throughout
childhood and adolescence peaking and have their greatest lifetime values in the third
decade of life. Thereafter with aging, their respective values progressively decline to
lower values, at some age reaching a threshold past which an overt clinical condition has
an increased probability of existing (osteoporosis, sarcopenia, and endurance

Bone: less weight-bearing activity by children/adolescents results in earlier

After the age of ~25 yrs, bone mineral density (BMD) is progressively
lost. As some age, BMD passes a threshold of an overt clinical event (osteoporosis). For
example, a 25-yr old individual with a BMD that is 90% of the mean peak BMD be
osteoporotic ~30 yrs earlier than if they had a BMD 110% of the mean peak BMD

The positive effect of mechanical loading on bone growth is greatest pre- and
early-puberty in girls (25) and pre-puberty in
boys (146). Thus, less load-bearing activity by
children during skeletal growth is associated with smaller bone mass than in
load-bearing children (438, 463). For example, girls starting at ages
9–15 had substantially greater increases in bone mineral content at lumbar spine
and femoral neck if they had the highest physical activity levels during the 7-year
follow-up as compared with those having the lowest physical activity levels (424). Thus, Rizzoli et al. (438) assert that childhood and adolescence is a key determinant of
bone health and future fracture risk during adulthood.

Skeletal muscle: less weight-bearing activity by children/adolescents results in
earlier sarcopenia

In an earlier section (Inactivity accelerates loss of functional capacities
with chronological aging leading to premature death), Skeletal muscle power peaks about
the third decade of life, and then declines thereafter (). However, physically inactive individuals reached skeletal muscle
frailty 24 yrs younger in age than masters’ weight lifters.

CRF: less endurance-type play in children/adolescents increases risk of earlier
death at old age

in the earlier section
(Inactivity accelerates loss of functional capacities with chronological aging leading
to premature death), showed that VO2max peaks at the third decade of life,
and thereafter declines. However, physically inactive individuals passed below the
threshold of aerobic frailty 30 yrs earlier in age than masters’ aerobically trained

51.11 Summary

Physical inactivity is a cause of chronic disease in children and adolescents.
Documented health benefits by prevention of physical inactivity in children and
adolescents (412, 494) include increased physical fitness (both CRF and muscular strength),
reduced body fatness, favorable cardiovascular and metabolic disease risk profiles,
enhanced bone health, and reduced symptoms of depression and anxiety.

52. Public policy

52.1 Underappreciated cost

The NPAGCR (412) indicates that
physical activity diminishes mortality by 30% in the U.S. Stated alternatively, physical
inactivity increases mortality by 30%, or by 720,000 annual deaths (one death every 44
seconds). Our estimations are that U.S. health care costs of inactivity will range from
$2.2–3.8 trillion in the first decade of the 21st century, or $700
yearly ($7000 for the next decade) from each U.S. resident. Our estimate of physical
inactivity’s cost is in line with a) the Society of Actuaries estimate that overweight and
obesity cost the U.S. $270 billion/year (cost includes increased need for medical care,
and loss of economic productivity resulting from excess mortality and disability) (485) and b) the estimated nationwide cost of for
physical inactivity and obesity of $507 billion with projected costs exceeding $708
billion in 2008 (98). We estimate that if every
U.S. individual had 30 min of moderate physical activity/day obesity, annual U.S. health
costs would be reduced ~4% ($100 billion out of $2.4 trillion), and additionally we
speculate that if all U.S. individuals would approach the physical activity levels of U.S.
Amish, obesity would be reduced ~8% ($200 billion out of $2.4 trillion). Further,
physical activity reduces prevalence of many conditions that are not obesity
co-morbidities, so we contend our estimates of physical inactivity are conservative and

52.2 Role of exercise scientists in public policy

According to Kersh and Morone, “Public health crusades are typically
built on a scientific base…In any event, medical knowledge in itself is rarely
enough to stimulate a political response. Rather, the key to its impact lies in the policy
entrepreneurs who spread the medical findings” (272). Scientists enable the enablers. Exercise and chronic diseases are complex
polygenic conditions. The scientific and technical expertise to appreciate the complexity
of exercise/inactivity and chronic diseases is limited within the scientific community.
Thus, policy entrepreneurs must be careful in their selection of scientists to enable
their public policy. The information in this article was presented both to enable both
scientists and policy entrepreneurs to reduce physical inactivity-caused diseases.

53. Conclusion

Physical activity, food, and reproduction are some of the minimal requirements
for life. They evolved not as choices, but as requirements for individual and species
survival. Modern humans have been able to engineer most physical activity out of daily life.
Humans now have a choice not to be physically active. Conclusive and overwhelming scientific
evidence, largely ignored and prioritized as low, exists for physical inactivity as a
primary and actual cause of most chronic diseases. Thus, longer-term health was also
engineered out with the successful removal of physical activity as a necessity for immediate
survival. The comprehensive evidence herein clearly establishes that lack of physical
activity affects almost every cell, organ, and system in the body causing sedentary
dysfunction and accelerated death. The massive multifactorial nature of dysfunction caused
by sedentarism means that just as food and reproduction remain as requirements for long-term
continued human existence, physical activity is also a requirement to maximize health span
and lifespan. The only valid scientific therapeutic approach to completely counter sedentary
dysfunction is primary prevention with physical activity itself.


Jacob Brown, Marybeth Brown, Pam Hinton, Arthur Kramer, Thomas Meek, Scott Rector, Mike
Roberts, Ron Terjung, John Thyfault, and Ryan Toedebusch for reviewing comments on specific
sections of the article. Howard Wilson for constructing figures. Supported by anonymous
gifts to FB. The article is dedicated to the continuing legacy of Charles M. Tipton and John
O. Holloszy, who directly or indirectly touched the training of the authors.


1Major source for disease frequency data in chapter is US government report on
physical activity by National Physical Activity Guidelines Advisory Committee, which will
be referred to as NPAGCR.


1. Aberg MA, Pedersen NL, Toren K, Svartengren M, Backstrand B, Johnsson T, Cooper-Kuhn CM, Aberg ND, Nilsson M, Kuhn HG. Cardiovascular fitness is associated with cognition in young
adulthood. Proc Natl Acad Sci U S A. 2009;106:20906–20911. [PMC free article] [PubMed] [Google Scholar]
2. Adams M, Fell J, Williams A. Exercise causing thrombosis. Phys Sportsmed. 2009;37:124–130. [PubMed] [Google Scholar]
3. Adams TD, Yanowitz FG, Fisher AG, Ridges JD, Nelson AG, Hagan AD, Williams RR, Hunt SC. Heritability of cardiac size: an echocardiographic and electrocardiographic
study of monozygotic and dizygotic twins. Circulation. 1985;71:39–44. [PubMed] [Google Scholar]
4. Agosti V, Graziano S, Artiaco L, Sorrentino G. Biological mechanisms of stroke prevention by physical activity in type 2
diabetes. Acta Neurol Scand. 2009;119:213–223. [PubMed] [Google Scholar]
5. Ahmad T, Chasman DI, Mora S, Pare G, Cook NR, Buring JE, Ridker PM, Lee IM. The fat-mass and obesity-associated (FTO) gene, physical activity, and risk
of incident cardiovascular events in white women. Am Heart J. 2010;160:1163–1169. [PMC free article] [PubMed] [Google Scholar]
6. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC., Jr. Harmonizing the metabolic syndrome: a joint interim statement of the
International Diabetes Federation Task Force on Epidemiology and Prevention; National
Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation;
International Atherosclerosis Society; and International Association for the Study of
Obesity. Circulation. 2009;120:1640–1645. [PubMed] [Google Scholar]
7. Alibegovic AC, Hojbjerre L, Sonne MP, van Hall G, Stallknecht B, Dela F, Vaag A. Impact of 9 days of bed rest on hepatic and peripheral insulin action,
insulin secretion, and whole-body lipolysis in healthy young male offspring of patients
with type 2 diabetes. Diabetes. 2009;58:2749–2756. [PMC free article] [PubMed] [Google Scholar]
8. Alibegovic AC, Sonne MP, Hojbjerre L, Bork-Jensen J, Jacobsen S, Nilsson E, Faerch K, Hiscock NJ, Mortensen B, Friedrichsen M, Stallknecht B, Dela F, Vaag A. Insulin resistance induced by physical inactivity is associated with
multiple transcriptional changes in skeletal muscle in young men. Am J Physiol Endocrinol Metab [PubMed] [Google Scholar]
10. American Diabetes Association Gestational diabetes mellitus. Diabetes Care. 2004;27(Suppl 1):S88–90. [PubMed] [Google Scholar]
12. Andel R, Crowe M, Pedersen NL, Fratiglioni L, Johansson B, Gatz M. Physical exercise at midlife and risk of dementia three decades later: a
population-based study of Swedish twins. J Gerontol A Biol Sci Med Sci. 2008;63:62–66. [PubMed] [Google Scholar]
13. Anderson EJ, Lustig ME, Boyle KE, Woodlief TL, Kane DA, Lin CT, Price JW, 3rd, Kang L, Rabinovitch PS, Szeto HH, Houmard JA, Cortright RN, Wasserman DH, Neufer PD. Mitochondrial H2O2 emission and cellular redox state link excess fat intake
to insulin resistance in both rodents and humans. J Clin Invest. 2009;119:573–581. [PMC free article] [PubMed] [Google Scholar]
14. Andreasen CH, Stender-Petersen KL, Mogensen MS, Torekov SS, Wegner L, Andersen G, Nielsen AL, Albrechtsen A, Borch-Johnsen K, Rasmussen SS, Clausen JO, Sandbaek A, Lauritzen T, Hansen L, Jorgensen T, Pedersen O, Hansen T. Low physical activity accentuates the effect of the FTO rs9939609
polymorphism on body fat accumulation. Diabetes. 2008;57:95–101. [PubMed] [Google Scholar]
15. Treat fatty liver disease to reduce heart risk. Some experts suggest that
fatty liver disease will be the next big metabolic disorder associated with obesity and
inactivity. Heart Advis. 2010;13:5. Anonymous. [PubMed] [Google Scholar]
16. Arbab-Zadeh A, Dijk E, Prasad A, Fu Q, Torres P, Zhang R, Thomas JD, Palmer D, Levine BD. Effect of aging and physical activity on left ventricular
compliance. Circulation. 2004;110:1799–1805. [PubMed] [Google Scholar]
17. Astrand PO, Rodahl K. Textbook of Work Physiology. 3rd ed McGraw-Hill; New York: 1986. [Google Scholar]
18. Babyak M, Blumenthal JA, Herman S, Khatri P, Doraiswamy M, Moore K, Craighead WE, Baldewicz TT, Krishnan KR. Exercise treatment for major depression: maintenance of therapeutic benefit
at 10 months. Psychosom Med. 2000;62:633–638. [PubMed] [Google Scholar]
19. Bacon CG, Mittleman MA, Kawachi I, Giovannucci E, Glasser DB, Rimm EB. Sexual function in men older than 50 years of age: results from the health
professionals follow-up study. Ann Intern Med. 2003;139:161–168. [PubMed] [Google Scholar]
20. Baker JL, Olsen LW, Sorensen TI. Childhood body-mass index and the risk of coronary heart disease in
adulthood. N Engl J Med. 2007;357:2329–2337. [PMC free article] [PubMed] [Google Scholar]
21. Baltgalvis KA, Berger FG, Pena MM, Davis JM, Carson JA. Effect of exercise on biological pathways in ApcMin/+ mouse intestinal
polyps. J Appl Physiol. 2008;104:1137–1143. [PubMed] [Google Scholar]
22. Bankoski A, Harris TB, McClain JJ, Brychta RJ, Caserotti P, Chen KY, Berrigan D, Troiano RP, Koster A. Sedentary activity associated with metabolic syndrome independent of
physical activity. Diabetes Care. 2011;34:497–503. [PMC free article] [PubMed] [Google Scholar]
23. Barnard RJ, Leung PS, Aronson WJ, Cohen P, Golding LA. A mechanism to explain how regular exercise might reduce the risk for
clinical prostate cancer. Eur J Cancer Prev. 2007;16:415–421. [PubMed] [Google Scholar]
24. Barnes DE, Yaffe K, Satariano WA, Tager IB. A longitudinal study of cardiorespiratory fitness and cognitive function in
healthy older adults. J Am Geriatr Soc. 2003;51:459–465. [PubMed] [Google Scholar]
25. Bass SL. The prepubertal years: a uniquely opportune stage of growth when the
skeleton is most responsive to exercise? Sports Med. 2000;30:73–78. [PubMed] [Google Scholar]
26. Bassett DR, Jr., Wyatt HR, Thompson H, Peters JC, Hill JO. Pedometer-measured physical activity and health behaviors in U.S.
adults. Med Sci Sports Exerc. 2010;42:1819–1825. [PMC free article] [PubMed] [Google Scholar]
27. Bassett DR, Schneider PL, Huntington GE. Physical activity in an Old Order Amish community. Med Sci Sports Exerc. 2004;36:79–85. [PubMed] [Google Scholar]
28. Bassuk SS, Manson JE. Physical activity and cardiovascular disease prevention in women: a review
of the epidemiologic evidence. Nutr Metab Cardiovasc Dis. 2010;20:467–473. [PubMed] [Google Scholar]
29. Bauman WA, Spungen AM, Wang J, Pierson RN, Jr., Schwartz E. Continuous loss of bone during chronic immobilization: a monozygotic twin
study. Osteoporos Int. 1999;10:123–127. [PubMed] [Google Scholar]
30. Beard JR, Heathcote K, Brooks R, Earnest A, Kelly B. Predictors of mental disorders and their outcome in a community based
cohort. Soc Psychiatry Psychiatr Epidemiol. 2007;42:623–630. [PubMed] [Google Scholar]
31. Bell JA, Burnett A. Exercise for the primary, secondary and tertiary prevention of low back
pain in the workplace: a systematic review. J Occup Rehabil. 2009;19:8–24. [PubMed] [Google Scholar]
32. Bellentani S, Marino M. Epidemiology and natural history of non-alcoholic fatty liver disease
(NAFLD) Ann Hepatol. 2009;8(Suppl 1):S4–8. [PubMed] [Google Scholar]
33. Bellentani S, Scaglioni F, Marino M, Bedogni G. Epidemiology of non-alcoholic fatty liver disease. Dig Dis. 2010;28:155–161. [PubMed] [Google Scholar]
34. Bennett AF, Ruben JA. Endothermy and activity in vertebrates. Science. 1979;206:649–654. [PubMed] [Google Scholar]
35. Berggren JR, Hulver MW, Dohm GL, Houmard JA. Weight loss and exercise: implications for muscle lipid metabolism and
insulin action. Med Sci Sports Exerc. 2004;36:1191–1195. [PubMed] [Google Scholar]
36. Bergman RN, Ader M. Free fatty acids and pathogenesis of type 2 diabetes
mellitus. Trends Endocrinol Metab. 2000;11:351–356. [PubMed] [Google Scholar]
37. Bi S, Scott KA, Hyun J, Ladenheim EE, Moran TH. Running wheel activity prevents hyperphagia and obesity in Otsuka
long-evans Tokushima Fatty rats: role of hypothalamic signaling. Endocrinology. 2005;146:1676–1685. [PubMed] [Google Scholar]
38. Bianchi G, Rossi V, Muscari A, Magalotti D, Zoli M. Physical activity is negatively associated with the metabolic syndrome in
the elderly. QJM. 2008;101:713–721. [PubMed] [Google Scholar]
39. Biddinger SB, Kahn CR. From mice to men: insights into the insulin resistance
syndromes. Annu Rev Physiol. 2006;68:123–158. [PubMed] [Google Scholar]
40. Bielen EC, Fagard RH, Amery AK. Inheritance of acute cardiac changes during bicycle exercise: an
echocardiographic study in twins. Med Sci Sports Exerc. 1991;23:1254–1259. [PubMed] [Google Scholar]
41. Bielen EC, Fagard RH, Amery AK. Inheritance of blood pressure and haemodynamic phenotypes measured at rest
and during supine dynamic exercise. J Hypertens. 1991;9:655–663. [PubMed] [Google Scholar]
42. Black JE, Isaacs KR, Anderson BJ, Alcantara AA, Greenough WT. Learning causes synaptogenesis, whereas motor activity causes angiogenesis,
in cerebellar cortex of adult rats. Proc Natl Acad Sci U S A. 1990;87:5568–5572. [PMC free article] [PubMed] [Google Scholar]
43. Blair SN, Davey Smith G, Lee IM, Fox K, Hillsdon M, McKeown RE, Haskell WL, Marmot M. A tribute to professor Jeremiah Morris: the man who invented the field of
physical activity epidemiology. Ann Epidemiol. 2010;20:651–660. [PubMed] [Google Scholar]
44. Blair SN, Kohl HW, 3rd, Barlow CE, Paffenbarger RS, Jr., Gibbons LW, Macera CA. Changes in physical fitness and all-cause mortality. A prospective study of
healthy and unhealthy men. JAMA. 1995;273:1093–1098. [PubMed] [Google Scholar]
45. Blair SN, Kohl HW, 3rd, Paffenbarger RS, Jr., Clark DG, Cooper KH, Gibbons LW. Physical fitness and all-cause mortality. A prospective study of healthy
men and women. JAMA. 1989;262:2395–2401. [PubMed] [Google Scholar]
46. Blanc S, Normand S, Pachiaudi C, Fortrat JO, Laville M, Gharib C. Fuel homeostasis during physical inactivity induced by bed
rest. J Clin Endocrinol Metab. 2000;85:2223–2233. [PubMed] [Google Scholar]
47. Blotner H. Effect of prolonged physical inactivity on tolerance of
sugar. Arch Int Med. 1945;75:39–44. [Google Scholar]
48. Boisseau MR. Roles of mechanical blood forces in vascular diseases. A clinical
overview. Clin Hemorheol Microcirc. 2005;33:201–207. [PubMed] [Google Scholar]
49. Booth FW. Effect of limb immobilization on skeletal muscle. J Appl Physiol. 1982;52:1113–1118. [PubMed] [Google Scholar]
50. Booth FW, Laye MJ, Roberts MD. Lifetime sedentary living accelerates some aspects of secondary
aging. J Appl Physiol. In Review. [PubMed] [Google Scholar]
51. Booth FW, Gordon SE, Carlson CJ, Hamilton MT. Waging war on modern chronic diseases: primary prevention through exercise
biology. J Appl Physiol. 2000;88:774–787. [PubMed] [Google Scholar]
52. Booth FW, Laye MJ. The future: genes, physical activity and health. Acta Physiol (Oxf) 2010;199:549–556. [PubMed] [Google Scholar]
53. Booth FW, Laye MJ. Lack of adequate appreciation of physical exercise’s complexities can
pre-empt appropriate design and interpretation in scientific discovery. J Physiol. 2009;587:5527–5539. [PMC free article] [PubMed] [Google Scholar]
54. Booth FW, Seider MJ. Early change in skeletal muscle protein synthesis after limb immobilization
of rats. J Appl Physiol. 1979;47:974–977. [PubMed] [Google Scholar]
55. Bouchard C, An P, Rice T, Skinner JS, Wilmore JH, Gagnon J, Perusse L, Leon AS, Rao DC. Familial aggregation of VO(2max) response to exercise training: results
from the HERITAGE Family Study. J Appl Physiol. 1999;87:1003–1008. [PubMed] [Google Scholar]
56. Bouchard C, Daw EW, Rice T, Perusse L, Gagnon J, Province MA, Leon AS, Rao DC, Skinner JS, Wilmore JH. Familial resemblance for VO2max in the sedentary state: the HERITAGE family
study. Med Sci Sports Exerc. 1998;30:252–258. [PubMed] [Google Scholar]
57. Bouchard C, Lesage R, Lortie G, Simoneau JA, Hamel P, Boulay MR, Perusse L, Theriault G, Leblanc C. Aerobic performance in brothers, dizygotic and monozygotic
twins. Med Sci Sports Exerc. 1986;18:639–646. [PubMed] [Google Scholar]
58. Bouchard C, Simoneau JA, Lortie G, Boulay MR, Marcotte M, Thibault MC. Genetic effects in human skeletal muscle fiber type distribution and enzyme
activities. Can J Physiol Pharmacol. 1986;64:1245–1251. [PubMed] [Google Scholar]
59. Bouchard C, Tremblay A, Despres JP, Theriault G, Nadeau A, Lupien PJ, Moorjani S, Prudhomme D, Fournier G. The response to exercise with constant energy intake in identical
twins. Obes Res. 1994;2:400–410. [PubMed] [Google Scholar]
60. Bouchard C, Tremblay A, Nadeau A, Despres JP, Theriault G, Boulay MR, Lortie G, Leblanc C, Fournier G. Genetic effect in resting and exercise metabolic rates. Metabolism. 1989;38:364–370. [PubMed] [Google Scholar]
61. Boyle JP, Thompson TJ, Gregg EW, Barker LE, Williamson DF. Projection of the year 2050 burden of diabetes in the US adult population:
dynamic modeling of incidence, mortality, and prediabetes prevalence. Popul Health Metr. 2010;8:29. [PMC free article] [PubMed] [Google Scholar]
62. Brandt C, Pedersen BK. The role of exercise-induced myokines in muscle homeostasis and the defense
against chronic diseases. J Biomed Biotechnol. 2010;2010:520258. [PMC free article] [PubMed] [Google Scholar]
63. Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R, Stave CD, Olkin I, Sirard JR. Using pedometers to increase physical activity and improve health: a
systematic review. JAMA. 2007;298:2296–2304. [PubMed] [Google Scholar]
64. Brolinson PG, Elliott D. Exercise and the immune system. Clin Sports Med. 2007;26:311–319. [PubMed] [Google Scholar]
65. Brooks GA FT, Baldwin KM. Exercise Physiology. McGraw-Hill; New York: 2005. [Google Scholar]
66. Brown J, Brown S. Exercise for dysmenorrhoea. Cochrane Database Syst Rev. 2010;2:CD004142. [PubMed] [Google Scholar]
67. Brownson RC, Boehmer TK, Luke DA. Declining rates of physical activity in the United States: what are the
contributors. Annu Rev Public Health. 2005;26:421–443. [PubMed] [Google Scholar]
68. Browse NL. The physiology and pathology of bed rest. Charles C Thomas Publisher; Springlield, IL: 1965. p. V. [Google Scholar]
69. Brunt EM. Pathology of nonalcoholic fatty liver disease. Nat Rev Gastroenterol Hepatol. 7:195–203. [PubMed] [Google Scholar]
70. Buck SM, Hillman CH, Castelli DM. The relation of aerobic fitness to stroop task performance in preadolescent
children. Med Sci Sports Exerc. 2008;40:166–172. [PubMed] [Google Scholar]
71. Buckwalter JA, Martin JA. Sports and osteoarthritis. Curr Opin Rheumatol. 2004;16:634–639. [PubMed] [Google Scholar]
72. Burstein R, Polychronakos C, Toews CJ, MacDougall JD, Guyda HJ, Posner BI. Acute reversal of the enhanced insulin action in trained athletes.
Association with insulin receptor changes. Diabetes. 1985;34:756–760. [PubMed] [Google Scholar]
73. Cairns AP, McVeigh JG. A systematic review of the effects of dynamic exercise in rheumatoid
arthritis. Rheumatol Int. 2009;30:147–158. [PubMed] [Google Scholar]
74. Caldwell S, Lazo M. Is exercise an effective treatment for NASH? Knowns and
unknowns. Ann Hepatol. 2009;8(Suppl 1):S60–66. [PubMed] [Google Scholar]
75. Calvo M, Rodas G, Vallejo M, Estruch A, Arcas A, Javierre C, Viscor G, Ventura JL. Heritability of explosive power and anaerobic capacity in
humans. Eur J Appl Physiol. 2002;86:218–225. [PubMed] [Google Scholar]
76. Cameron C WR, Craig CL. Physical Activity and Sport: Encouraging Children to be Active. Canadian Fitness and Lifestyle Research Institute; Ottawa (ON): 2007. p. 14. [Google Scholar]
77. Carlsson S, Andersson T, Lichtenstein P, Michaelsson K, Ahlbom A. Physical activity and mortality: is the association explained by genetic
selection? Am J Epidemiol. 2007;166:255–259. [PubMed] [Google Scholar]
78. Carmelli D, Robinette D, Fabsitz R. Concordance, discordance and prevalence of hypertension in World War II
male veteran twins. J Hypertens. 1994;12:323–328. [PubMed] [Google Scholar]
79. Carnethon MR, Gidding SS, Nehgme R, Sidney S, Jacobs DR, Jr., Liu K. Cardiorespiratory fitness in young adulthood and the development of
cardiovascular disease risk factors. JAMA. 2003;290:3092–3100. [PubMed] [Google Scholar]
80. Carro E, Nunez A, Busiguina S, Torres-Aleman I. Circulating insulin-like growth factor I mediates effects of exercise on
the brain. J Neurosci. 2000;20:2926–2933. [PMC free article] [PubMed] [Google Scholar]
81. Carro E, Trejo JL, Busiguina S, Torres-Aleman I. Circulating insulin-like growth factor I mediates the protective effects of
physical exercise against brain insults of different etiology and
anatomy. J Neurosci. 2001;21:5678–5684. [PMC free article] [PubMed] [Google Scholar]
83. Cassilhas RC, Viana VA, Grassmann V, Santos RT, Santos RF, Tufik S, Mello MT. The impact of resistance exercise on the cognitive function of the
elderly. Med Sci Sports Exerc. 2007;39:1401–1407. [PubMed] [Google Scholar]
84. Castelli DM, Hillman CH, Buck SM, Erwin HE. Physical fitness and academic achievement in third- and fifth-grade
students. J Sport Exerc Psychol. 2007;29:239–252. [PubMed] [Google Scholar]
91. Chaddock L, Erickson KI, Prakash RS, Kim JS, Voss MW, Vanpatter M, Pontifex MB, Raine LB, Konkel A, Hillman CH, Cohen NJ, Kramer AF. A neuroimaging investigation of the association between aerobic fitness,
hippocampal volume, and memory performance in preadolescent children. Brain Res. 2010;1358:172–183. [PMC free article] [PubMed] [Google Scholar]
92. Chaddock L, Erickson KI, Prakash RS, VanPatter M, Voss MW, Pontifex MB, Raine LB, Hillman CH, Kramer AF. Basal ganglia volume is associated with aerobic fitness in preadolescent
children. Dev Neurosci. 2010;32:249–256. [PMC free article] [PubMed] [Google Scholar]
93. Chakravarty EF, Hubert HB, Lingala VB, Zatarain E, Fries JF. Long distance running and knee osteoarthritis. A prospective
study. Am J Prev Med. 2008;35:133–138. [PMC free article] [PubMed] [Google Scholar]
95. Chaouloff F. Effects of acute physical exercise on central serotonergic
systems. Med Sci Sports Exerc. 1997;29:58–62. [PubMed] [Google Scholar]
96. Chase NL, Sui X, Lee DC, Blair SN. The association of cardiorespiratory fitness and physical activity with
incidence of hypertension in men. Am J Hypertens. 2009;22:417–424. [PubMed] [Google Scholar]
97. Chennaoui M, Gomez Merino D, Lesage J, Drogou C, Guezennec CY. Effects of moderate and intensive training on the
hypothalamo-pituitary-adrenal axis in rats. Acta Physiol Scand. 2002;175:113–121. [PubMed] [Google Scholar]
98. Chenoweth DLJ. The Economic Cost of Physical Inactivity and Excess Weight in American
Adults. J Phys Act Health. 2008:148–163. [PubMed] [Google Scholar]
99. Chironi GN, Boulanger CM, Simon A, Dignat-George F, Freyssinet JM, Tedgui A. Endothelial microparticles in diseases. Cell Tissue Res. 2009;335:143–151. [PubMed] [Google Scholar]
100. Chomitz VR, Slining MM, McGowan RJ, Mitchell SE, Dawson GF, Hacker KA. Is there a relationship between physical fitness and academic achievement?
Positive results from public school children in the northeastern United
States. J Sch Health. 2009;79:30–37. [PubMed] [Google Scholar]
101. Church TS, Kuk JL, Ross R, Priest EL, Biltoft E, Blair SN. Association of cardiorespiratory fitness, body mass index, and waist
circumference to nonalcoholic fatty liver disease. Gastroenterology. 2006;130:2023–2030. [PubMed] [Google Scholar]
102. Claudino MA, Delbin MA, Franco-Penteado CF, Priviero FB, De Nucci G, Antunes E, Zanesco A. Exercise training ameliorates the impairment of endothelial and nitrergic
corpus cavernosum responses in diabetic rats. Life Sci. 2010;88:272–277. [PubMed] [Google Scholar]
103. Claypoole K, Mahurin R, Fischer ME, Goldberg J, Schmaling KB, Schoene RB, Ashton S, Buchwald D. Cognitive compromise following exercise in monozygotic twins discordant for
chronic fatigue syndrome: fact or artifact? Appl Neuropsychol. 2001;8:31–40. [PubMed] [Google Scholar]
104. Cocco G, Pandolfi S. Physical exercise with weight reduction lowers blood pressure and improves
abnormal left ventricular relaxation in pharmacologically treated hypertensive
patients. J Clin Hypertens (Greenwich) 2011;13:23–29. [PMC free article] [PubMed] [Google Scholar]
105. Cohn BA, Brand RJ, Hulley SB. Correlates of high density lipoprotein cholesterol in women studied by the
method of co-twin control. Am J Epidemiol. 1989;129:988–999. [PubMed] [Google Scholar]
106. Colbert LH, Mai V, Perkins SN, Berrigan D, Lavigne JA, Wimbrow HH, Alvord WG, Haines DC, Srinivas P, Hursting SD. Exercise and intestinal polyp development in APCMin mice. Med Sci Sports Exerc. 2003;35:1662–1669. [PubMed] [Google Scholar]
107. Colbert LH, Mai V, Tooze JA, Perkins SN, Berrigan D, Hursting SD. Negative energy balance induced by voluntary wheel running inhibits polyp
development in APCMin mice. Carcinogenesis. 2006;27:2103–2107. [PubMed] [Google Scholar]
108. Colcombe S, Kramer AF. Fitness effects on the cognitive function of older adults: a meta-analytic
study. Psychol Sci. 2003;14:125–130. [PubMed] [Google Scholar]
109. Colcombe SJ, Erickson KI, Scalf PE, Kim JS, Prakash R, McAuley E, Elavsky S, Marquez DX, Hu L, Kramer AF. Aerobic exercise training increases brain volume in aging
humans. J Gerontol A Biol Sci Med Sci. 2006;61:1166–1170. [PubMed] [Google Scholar]
110. Colcombe SJ, Kramer AF, Erickson KI, Scalf P, McAuley E, Cohen NJ, Webb A, Jerome GJ, Marquez DX, Elavsky S. Cardiovascular fitness, cortical plasticity, and aging. Proc Natl Acad Sci U S A. 2004;101:3316–3321. [PMC free article] [PubMed] [Google Scholar]
111. Colditz GA, Cannuscio CC, Frazier AL. Physical activity and reduced risk of colon cancer: implications for
prevention. Cancer Causes Control. 1997;8:649–667. [PubMed] [Google Scholar]
112. Cononie CC, Goldberg AP, Rogus E, Hagberg JM. Seven consecutive days of exercise lowers plasma insulin responses to an
oral glucose challenge in sedentary elderly. J Am Geriatr Soc. 1994;42:394–398. [PubMed] [Google Scholar]
113. Cook S, Auinger P, Li C, Ford ES. Metabolic syndrome rates in United States adolescents, from the National
Health and Nutrition Examination Survey, 1999–2002. J Pediatr. 2008;152:165–170. [PubMed] [Google Scholar]
114. Cordain L, Latin RW, Behnke JJ. The effects of an aerobic running program on bowel transit
time. J Sports Med Phys Fitness. 1986;26:101–104. [PubMed] [Google Scholar]
115. Cordain LFJ. The paleo diet for athletes: a nutritional formula for peak athletic
Rodale Books; New York: 2005. [Google Scholar]
116. Crandall JP, Knowler WC, Kahn SE, Marrero D, Florez JC, Bray GA, Haffner SM, Hoskin M, Nathan DM. The prevention of type 2 diabetes. Nat Clin Pract Endocrinol Metab. 2008;4:382–393. [PMC free article] [PubMed] [Google Scholar]
117. Creer DJ, Romberg C, Saksida LM, van Praag H, Bussey TJ. Running enhances spatial pattern separation in mice. Proc Natl Acad Sci U S A. 2010;107:2367–2372. [PMC free article] [PubMed] [Google Scholar]
118. D’Aunno DS, Robinson RR, Smith GS, Thomason DB, Booth FW. Intermittent acceleration as a countermeasure to soleus muscle
atrophy. J Appl Physiol. 1992;72:428–433. [PubMed] [Google Scholar]
119. Danis A, Kyriazis Y, Klissouras V. The effect of training in male prepubertal and pubertal monozygotic
twins. Eur J Appl Physiol. 2003;89:309–318. [PubMed] [Google Scholar]
120. Davidsen PK, Gallagher IJ, Hartman JW, Tarnopolsky MA, Dela F, Helge JW, Timmons JA, Phillips SM. High responders to resistance exercise training demonstrate differential
regulation of skeletal muscle microRNA expression. J Appl Physiol. 2011;110:309–317. [PubMed] [Google Scholar]
121. Davignon J, Ganz P. Role of endothelial dysfunction in atherosclerosis. Circulation. 2004;109:III27–32. [PubMed] [Google Scholar]
122. De Geus EJ, Boomsma DI, Snieder H. Genetic correlation of exercise with heart rate and respiratory sinus
arrhythmia. Med Sci Sports Exerc. 2003;35:1287–1295. [PubMed] [Google Scholar]
123. de Groot PC, Bleeker MW, Hopman MT. Magnitude and time course of arterial vascular adaptations to inactivity in
humans. Exerc Sport Sci Rev. 2006;34:65–71. [PubMed] [Google Scholar]
124. de Kam D, Smulders E, Weerdesteyn V, Smits-Engelsman BC. Exercise interventions to reduce fall-related fractures and their risk
factors in individuals with low bone density: a systematic review of randomized
controlled trials. Osteoporos Int. 2009;20:2111–2125. [PubMed] [Google Scholar]
125. De Mars G, Thomis MA, Windelinckx A, Van Leemputte M, Maes HH, Blimkie CJ, Claessens AL, Vlietinck R, Beunen G. Covariance of isometric and dynamic arm contractions: multivariate genetic
analysis. Twin Res Hum Genet. 2007;10:180–190. [PubMed] [Google Scholar]
126. De Moor MH, Boomsma DI, Stubbe JH, Willemsen G, de Geus EJ. Testing causality in the association between regular exercise and symptoms
of anxiety and depression. Arch Gen Psychiatry. 2008;65:897–905. [PubMed] [Google Scholar]
127. Deeny SP, Poeppel D, Zimmerman JB, Roth SM, Brandauer J, Witkowski S, Hearn JW, Ludlow AT, Contreras-Vidal JL, Brandt J, Hatfield BD. Exercise, APOE, and working memory: MEG and behavioral evidence for benefit
of exercise in epsilon4 carriers. Biol Psychol. 2008;78:179–187. [PMC free article] [PubMed] [Google Scholar]
128. Dela F, Ploug T, Handberg A, Petersen LN, Larsen JJ, Mikines KJ, Galbo H. Physical training increases muscle GLUT4 protein and mRNA in patients with
NIDDM. Diabetes. 1994;43:862–865. [PubMed] [Google Scholar]
129. Denissenko MF, Pao A, Tang M, Pfeifer GP. Preferential formation of benzo[a]pyrene adducts at lung cancer mutational
hotspots in P53. Science. 1996;274:430–432. [PubMed] [Google Scholar]
130. Derbre F, Vincent S, Maitel B, Jacob C, Delamarche P, Delamarche A, Zouhal H. Androgen responses to sprint exercise in young men. Int J Sports Med. 31:291–297. [PubMed] [Google Scholar]
131. Derby CA, Mohr BA, Goldstein I, Feldman HA, Johannes CB, McKinlay JB. Modifiable risk factors and erectile dysfunction: can lifestyle changes
modify risk? Urology. 2000;56:302–306. [PubMed] [Google Scholar]
132. DeSouza CA, Shapiro LF, Clevenger CM, Dinenno FA, Monahan KD, Tanaka H, Seals DR. Regular aerobic exercise prevents and restores age-related declines in
endothelium-dependent vasodilation in healthy men. Circulation. 2000;102:1351–1357. [PubMed] [Google Scholar]
133. Despres JP, Bouchard C, Savard R, Prud’homme D, Bukowiecki L, Theriault G. Adaptive changes to training in adipose tissue lipolysis are genotype
dependent. Int J Obes. 1984;8:87–95. [PubMed] [Google Scholar]
134. Despres JP, Moorjani S, Tremblay A, Poehlman ET, Lupien PJ, Nadeau A, Bouchard C. Heredity and changes in plasma lipids and lipoproteins after short-term
exercise training in men. Arteriosclerosis. 1988;8:402–409. [PubMed] [Google Scholar]
135. Di Luigi L, Guidetti L, Baldari C, Romanelli F. Heredity and pituitary response to exercise-related stress in trained
men. Int J Sports Med. 2003;24:551–558. [PubMed] [Google Scholar]
136. Diabetes Prevention Program Research Group Changes in albumin excretion in the diabetes prevention
program. Diabetes Care. 2009;32:720–725. [PMC free article] [PubMed] [Google Scholar]
137. Diep L, Kwagyan J, Kurantsin-Mills J, Weir R, Jayam-Trouth A. Association of physical activity level and stroke outcomes in men and
women: a meta-analysis. J Womens Health (Larchmt) 2010;19:1815–1822. [PMC free article] [PubMed] [Google Scholar]
138. Dik M, Deeg DJ, Visser M, Jonker C. Early life physical activity and cognition at old age. J Clin Exp Neuropsychol. 2003;25:643–653. [PubMed] [Google Scholar]
139. Dimeo F, Bauer M, Varahram I, Proest G, Halter U. Benefits from aerobic exercise in patients with major depression: a pilot
study. Br J Sports Med. 2001;35:114–117. [PMC free article] [PubMed] [Google Scholar]
140. Ding Q, Vaynman S, Akhavan M, Ying Z, Gomez-Pinilla F. Insulin-like growth factor I interfaces with brain-derived neurotrophic
factor-mediated synaptic plasticity to modulate aspects of exercise-induced cognitive
function. Neuroscience. 2006;140:823–833. [PubMed] [Google Scholar]
141. Ding YH, Li J, Zhou Y, Rafols JA, Clark JC, Ding Y. Cerebral angiogenesis and expression of angiogenic factors in aging rats
after exercise. Curr Neurovasc Res. 2006;3:15–23. [PubMed] [Google Scholar]
142. Dishman RK. Brain monoamines, exercise, and behavioral stress: animal
models. Med Sci Sports Exerc. 1997;29:63–74. [PubMed] [Google Scholar]
143. Dishman RK, Bunnell BN, Youngstedt SD, Yoo HS, Mougey EH, Meyerhoff JL. Activity wheel running blunts increased plasma adrenocorticotrophin (ACTH)
after footshock and cage-switch stress. Physiol Behav. 1998;63:911–917. [PubMed] [Google Scholar]
144. Donnelly JE, Greene JL, Gibson CA, Smith BK, Washburn RA, Sullivan DK, DuBose K, Mayo MS, Schmelzle KH, Ryan JJ, Jacobsen DJ, Williams SL. Physical Activity Across the Curriculum (PAAC): a randomized controlled
trial to promote physical activity and diminish overweight and obesity in elementary
school children. Prev Med. 2009;49:336–341. [PMC free article] [PubMed] [Google Scholar]
145. Douen AG, Ramlal T, Rastogi S, Bilan PJ, Cartee GD, Vranic M, Holloszy JO, Klip A. Exercise induces recruitment of the “insulin-responsive glucose
transporter”. Evidence for distinct intracellular insulin- and
exercise-recruitable transporter pools in skeletal muscle. J Biol Chem. 1990;265:13427–13430. [PubMed] [Google Scholar]
146. Ducher G, Daly RM, Bass SL. Effects of repetitive loading on bone mass and geometry in young male
tennis players: a quantitative study using MRI. J Bone Miner Res. 2009;24:1686–1692. [PubMed] [Google Scholar]
147. Duncan GE. Prevalence of diabetes and impaired fasting glucose levels among US
adolescents: National Health and Nutrition Examination Survey,
1999–2002. Arch Pediatr Adolesc Med. 2006;160:523–528. [PubMed] [Google Scholar]
148. Duncan GE, Goldberg J, Noonan C, Moudon AV, Hurvitz P, Buchwald D. Unique environmental effects on physical activity participation: a twin
study. PLoS ONE. 2008;3:e2019. [PMC free article] [PubMed] [Google Scholar]
149. Dunn AL, Reigle TG, Youngstedt SD, Armstrong RB, Dishman RK. Brain norepinephrine and metabolites after treadmill training and wheel
running in rats. Med Sci Sports Exerc. 1996;28:204–209. [PubMed] [Google Scholar]
150. Dunn AL, Trivedi MH, Kampert JB, Clark CG, Chambliss HO. Exercise treatment for depression: efficacy and dose
response. Am J Prev Med. 2005;28:1–8. [PubMed] [Google Scholar]
151. Dunstan DW, Barr EL, Healy GN, Salmon J, Shaw JE, Balkau B, Magliano DJ, Cameron AJ, Zimmet PZ, Owen N. Television viewing time and mortality: the Australian Diabetes, Obesity and
Lifestyle Study (AusDiab) Circulation. 2010;121:384–391. [PubMed] [Google Scholar]
152. Duran-Valdez E, de Serna DG, Schneider S, Amorim F, Burge M, Schade DS. Metabolic effects of 2 days of strict bed rest. Endocr Pract. 2008;14:564–569. [PubMed] [Google Scholar]
153. Duscha BD, Slentz CA, Johnson JL, Houmard JA, Bensimhon DR, Knetzger KJ, Kraus WE. Effects of exercise training amount and intensity on peak oxygen
consumption in middle-age men and women at risk for cardiovascular
disease. Chest. 2005;128:2788–2793. [PubMed] [Google Scholar]
154. Dustman RE, Emmerson RY, Ruhling RO, Shearer DE, Steinhaus LA, Johnson SC, Bonekat HW, Shigeoka JW. Age and fitness effects on EEG, ERPs, visual sensitivity, and
cognition. Neurobiol Aging. 1990;11:193–200. [PubMed] [Google Scholar]
155. Eagle KA, Berger PB, Calkins H, Chaitman BR, Ewy GA, Fleischmann KE, Fleisher LA, Froehlich JB, Gusberg RJ, Leppo JA, Ryan T, Schlant RC, Winters WL, Jr., Gibbons RJ, Antman EM, Alpert JS, Faxon DP, Fuster V, Gregoratos G, Jacobs AK, Hiratzka LF, Russell RO, Smith SC., Jr ACC/AHA guideline update for perioperative cardiovascular evaluation for
noncardiac surgery—executive summary a report of the American College of
Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to
Update the 1996 Guidelines on Perioperative Cardiovascular Evaluation for Noncardiac
Surgery) Circulation. 2002;105:1257–1267. [PubMed] [Google Scholar]
156. Eicher JD, Maresh CM, Tsongalis GJ, Thompson PD, Pescatello LS. The additive blood pressure lowering effects of exercise intensity on
post-exercise hypotension. Am Heart J. 160:513–520. [PubMed] [Google Scholar]
157. Eicher JD, Maresh CM, Tsongalis GJ, Thompson PD, Pescatello LS. The additive blood pressure lowering effects of exercise intensity on
post-exercise hypotension. Am Heart J. 2010;160:513–520. [PubMed] [Google Scholar]
158. Eichner ER. Exercise and arthritis. The hematology of inactivity. Rheum Dis Clin North Am. 1990;16:815–825. [PubMed] [Google Scholar]
159. Ekblom B, Ekblom O, Malm C. Infectious episodes before and after a marathon race. Scand J Med Sci Sports. 2006;16:287–293. [PubMed] [Google Scholar]
160. Ekstrand J, Hellsten J, Tingstrom A. Environmental enrichment, exercise and corticosterone affect endothelial
cell proliferation in adult rat hippocampus and prefrontal cortex. Neurosci Lett. 2008;442:203–207. [PubMed] [Google Scholar]
161. Endemann DH, Schiffrin EL. Endothelial dysfunction. J Am Soc Nephrol. 2004;15:1983–1992. [PubMed] [Google Scholar]
162. Engelke K, Kemmler W, Lauber D, Beeskow C, Pintag R, Kalender WA. Exercise maintains bone density at spine and hip EFOPS: a 3-year
longitudinal study in early postmenopausal women. Osteoporos Int. 2006;17:133–142. [PubMed] [Google Scholar]
163. Erickson KI, Prakash RS, Voss MW, Chaddock L, Hu L, Morris KS, White SM, Wojcicki TR, McAuley E, Kramer AF. Aerobic fitness is associated with hippocampal volume in elderly
humans. Hippocampus. 2009;19:1030–1039. [PMC free article] [PubMed] [Google Scholar]
165. Erikssen G, Liestol K, Bjornholt J, Thaulow E, Sandvik L, Erikssen J. Changes in physical fitness and changes in mortality. Lancet. 1998;352:759–762. [PubMed] [Google Scholar]
166. Eriksson M, Rasmussen F, Tynelius P. Genetic factors in physical activity and the equal environment assumption–
the Swedish young male twins study. Behav Genet. 2006;36:238–247. [PubMed] [Google Scholar]
167. Eskurza I, Monahan KD, Robinson JA, Seals DR. Effect of acute and chronic ascorbic acid on flow-mediated dilatation with
sedentary and physically active human ageing. J Physiol. 2004;556:315–324. [PMC free article] [PubMed] [Google Scholar]
168. Esliger DW, Tremblay MS, Copeland JL, Barnes JD, Huntington GE, Bassett DR., Jr Physical activity profile of Old Order Amish, Mennonite, and contemporary
children. Med Sci Sports Exerc. 2010;42:296–303. [PubMed] [Google Scholar]
169. Esposito K, Ciotola M, Giugliano F, Maiorino MI, Autorino R, De Sio M, Giugliano G, Nicoletti G, D’Andrea F, Giugliano D. Effects of intensive lifestyle changes on erectile dysfunction in
men. J Sex Med. 2009;6:243–250. [PubMed] [Google Scholar]
170. Esposito K, Giugliano F, Di Palo C, Giugliano G, Marfella R, D’Andrea F, D’Armiento M, Giugliano D. Effect of lifestyle changes on erectile dysfunction in obese men: a
randomized controlled trial. JAMA. 2004;291:2978–2984. [PubMed] [Google Scholar]
171. Etnier JL, Caselli RJ, Reiman EM, Alexander GE, Sibley BA, Tessier D, McLemore EC. Cognitive performance in older women relative to ApoE-epsilon4 genotype and
aerobic fitness. Med Sci Sports Exerc. 2007;39:199–207. [PubMed] [Google Scholar]
172. Etnier JL, Nowell PM, Landers DM, Sibley BA. A meta-regression to examine the relationship between aerobic fitness and
cognitive performance. Brain Res Rev. 2006;52:119–130. [PubMed] [Google Scholar]
173. Etnier JL. SW, Landers DM., Petruzello M., Han M. and Nowell P.,. The influence of
physical fitness and exercise upon cognitive functioning: a
meta-analysis. J Sport Exerc Psychol. 1997;19:249–277. [Google Scholar]
174. Eveland-Sayers BM, Farley RS, Fuller DK, Morgan DW, Caputo JL. Physical fitness and academic achievement in elementary school
children. J Phys Act Health. 2009;6:99–104. [PubMed] [Google Scholar]
175. Fabel K, Tam B, Kaufer D, Baiker A, Simmons N, Kuo CJ, Palmer TD. VEGF is necessary for exercise-induced adult hippocampal
neurogenesis. Eur J Neurosci. 2003;18:2803–2812. [PubMed] [Google Scholar]
176. Fagard R, Bielen E, Amery A. Heritability of aerobic power and anaerobic energy generation during
exercise. J Appl Physiol. 1991;70:357–362. [PubMed] [Google Scholar]
177. Fagard R, Van Den Broeke C, Bielen E, Amery A. Maximum oxygen uptake and cardiac size and function in
twins. Am J Cardiol. 1987;60:1362–1367. [PubMed] [Google Scholar]
178. Fediuc S, Campbell JE, Riddell MC. Effect of voluntary wheel running on circadian corticosterone release and
on HPA axis responsiveness to restraint stress in Sprague-Dawley rats. J Appl Physiol. 2006;100:1867–1875. [PubMed] [Google Scholar]
179. Feinstein MB, Krebs P, Coups EJ, Park BJ, Steingart RM, Burkhalter J, Logue A, Ostroff JS. Current dyspnea among long-term survivors of early-stage non-small cell
lung cancer. J Thorac Oncol. 5:1221–1226. [PMC free article] [PubMed] [Google Scholar]
180. Feletou M, Vanhoutte PM. Endothelial dysfunction: a multifaceted disorder (The Wiggers Award
Lecture) Am J Physiol Heart Circ Physiol. 2006;291:H985–1002. [PubMed] [Google Scholar]
181. Ferrucci L, Izmirlian G, Leveille S, Phillips CL, Corti MC, Brock DB, Guralnik JM. Smoking, physical activity, and active life expectancy. Am J Epidemiol. 1999;149:645–653. [PubMed] [Google Scholar]
182. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults,
1999–2008. JAMA. 2010;303:235–241. [PubMed] [Google Scholar]
183. Fletcher GF, Blair SN, Blumenthal J, Caspersen C, Chaitman B, Epstein S, Falls H, Froelicher ES, Froelicher VF, Pina IL. Statement on exercise. Benefits and recommendations for physical activity
programs for all Americans. A statement for health professionals by the Committee on
Exercise and Cardiac Rehabilitation of the Council on Clinical Cardiology, American
Heart association. Circulation. 1992;86:340–344. [PubMed] [Google Scholar]
184. Fluck M, Schmutz S, Wittwer M, Hoppeler H, Desplanches D. Transcriptional reprogramming during reloading of atrophied rat soleus
muscle. Am J Physiol Regul Integr Comp Physiol. 2005;289:R4–14. [PubMed] [Google Scholar]
185. Fogelholm M. Physical activity, fitness and fatness: relations to mortality, morbidity
and disease risk factors. A systematic review. Obes Rev. 2010;11:202–221. [PubMed] [Google Scholar]
186. Ford ES, Kohl HW, 3rd, Mokdad AH, Ajani UA. Sedentary behavior, physical activity, and the metabolic syndrome among
U.S. adults. Obes Res. 2005;13:608–614. [PubMed] [Google Scholar]
187. Ford ES, Li C, Zhao G. Prevalence and correlates of metabolic syndrome based on a harmonious
definition among adults in the US. J Diabetes. 2010;2:180–193. [PubMed] [Google Scholar]
188. Foster GD, Linder B, Baranowski T, Cooper DM, Goldberg L, Harrell JS, Kaufman F, Marcus MD, Trevino RP, Hirst K. A school-based intervention for diabetes risk reduction. N Engl J Med. 2010;363:443–453. [PMC free article] [PubMed] [Google Scholar]
189. Franks PW, Ravussin E, Hanson RL, Harper IT, Allison DB, Knowler WC, Tataranni PA, Salbe AD. Habitual physical activity in children: the role of genes and the
environment. Am J Clin Nutr. 2005;82:901–908. [PubMed] [Google Scholar]
190. Fraser GE, Shavlik DJ. Ten years of life: Is it a matter of choice? Arch Intern Med. 2001;161:1645–1652. [PubMed] [Google Scholar]
191. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, Perry JR, Elliott KS, Lango H, Rayner NW, Shields B, Harries LW, Barrett JC, Ellard S, Groves CJ, Knight B, Patch AM, Ness AR, Ebrahim S, Lawlor DA, Ring SM, Ben-Shlomo Y, Jarvelin MR, Sovio U, Bennett AJ, Melzer D, Ferrucci L, Loos RJ, Barroso I, Wareham NJ, Karpe F, Owen KR, Cardon LR, Walker M, Hitman GA, Palmer CN, Doney AS, Morris AD, Smith GD, Hattersley AT, McCarthy MI. A common variant in the FTO gene is associated with body mass index and
predisposes to childhood and adult obesity. Science. 2007;316:889–894. [PMC free article] [PubMed] [Google Scholar]
192. Friedman BW, Chilstrom M, Bijur PE, Gallagher EJ. Diagnostic testing and treatment of low back pain in United States
emergency departments: a national perspective. Spine (Phila Pa 1976) 2010;35:E1406–1411. [PMC free article] [PubMed] [Google Scholar]
193. Frosig C, Richter EA. Improved insulin sensitivity after exercise: focus on insulin
signaling. Obesity (Silver Spring) 2009;17 Suppl 3:S15–20. [PubMed] [Google Scholar]
194. Gardner AW, Montgomery PS, Parker DE. Physical activity is a predictor of all-cause mortality in patients with
intermittent claudication. J Vasc Surg. 2008;47:117–122. [PMC free article] [PubMed] [Google Scholar]
195. Gatz M, Mortimer JA, Fratiglioni L, Johansson B, Berg S, Reynolds CA, Pedersen NL. Potentially modifiable risk factors for dementia in identical
twins. Alzheimers Dement. 2006;2:110–117. [PubMed] [Google Scholar]
196. Gavard JA, Artal R. Effect of exercise on pregnancy outcome. Clin Obstet Gynecol. 2008;51:467–480. [PubMed] [Google Scholar]
198. Giovannucci E. Insulin, insulin-like growth factors and colon cancer: a review of the
evidence. J Nutr. 2001;131:3109S–3120S. [PubMed] [Google Scholar]
199. Gleeson M. Immune function in sport and exercise. J Appl Physiol. 2007;103:693–699. [PubMed] [Google Scholar]
200. Gleeson M, Nieman DC, Pedersen BK. Exercise, nutrition and immune function. J Sports Sci. 2004;22:115–125. [PubMed] [Google Scholar]
201. Gleeson M, Pyne DB, Austin JP, Lynn Francis J, Clancy RL, McDonald WA, Fricker PA. Epstein-Barr virus reactivation and upper-respiratory illness in elite
swimmers. Med Sci Sports Exerc. 2002;34:411–417. [PubMed] [Google Scholar]
202. Golden SH, Robinson KA, Saldanha I, Anton B, Ladenson PW. Clinical review: Prevalence and incidence of endocrine and metabolic
disorders in the United States: a comprehensive review. J Clin Endocrinol Metab. 2009;94:1853–1878. [PMC free article] [PubMed] [Google Scholar]
203. Goldsmith R, Joanisse DR, Gallagher D, Pavlovich K, Shamoon E, Leibel RL, Rosenbaum M. Effects of experimental weight perturbation on skeletal muscle work
efficiency, fuel utilization, and biochemistry in human subjects. Am J Physiol Regul Integr Comp Physiol. 2010;298:R79–88. [PMC free article] [PubMed] [Google Scholar]
204. Goodwin RD. Association between physical activity and mental disorders among adults in
the United States. Prev Med. 2003;36:698–703. [PubMed] [Google Scholar]
205. Goodyear LJ, Hirshman MF, King PA, Horton ED, Thompson CM, Horton ES. Skeletal muscle plasma membrane glucose transport and glucose transporters
after exercise. J Appl Physiol. 1990;68:193–198. [PubMed] [Google Scholar]
206. Gordon BA, Benson AC, Bird SR, Fraser SF. Resistance training improves metabolic health in type 2 diabetes: a
systematic review. Diabetes Res Clin Pract. 2009;83:157–175. [PubMed] [Google Scholar]
207. Grant WB. Comments on E. Giovannucci, “Insulin, insulin-like growth factors and colon
cancer: a review of the evidence”. J Nutr. 2002;132 2324; author reply 2325. [PubMed] [Google Scholar]
208. Greenberg PE, Kessler RC, Birnbaum HG, Leong SA, Lowe SW, Berglund PA, Corey-Lisle PK. The economic burden of depression in the United States: how did it change
between 1990 and 2000? J Clin Psychiatry. 2003;64:1465–1475. [PubMed] [Google Scholar]
209. Greenfield JR, Samaras K, Campbell LV, Jenkins AB, Kelly PJ, Spector TD, Hayward CS. Physical activity reduces genetic susceptibility to increased central
systolic pressure augmentation: a study of female twins. J Am Coll Cardiol. 2003;42:264–270. [PubMed] [Google Scholar]
210. Greenhaff PL, Hargreaves M. “Systems Biology” in Human Exercise Physiology: is it
something different from Integrative Physiology? J Physiol. 2011 [PMC free article] [PubMed] [Google Scholar]
211. Greist JH, Klein MH, Eischens RR, Faris J, Gurman AS, Morgan WP. Running as treatment for depression. Compr Psychiatry. 1979;20:41–54. [PubMed] [Google Scholar]
212. Guadalupe-Grau A, Fuentes T, Guerra B, Calbet JA. Exercise and bone mass in adults. Sports Med. 2009;39:439–468. [PubMed] [Google Scholar]
213. Hahn RA, Teutsch SM, Rothenberg RB, Marks JS. Excess deaths from nine chronic diseases in the United States,
1986. JAMA. 1990;264:2654–2659. [PubMed] [Google Scholar]
214. Hakala P, Rissanen A, Koskenvuo M, Kaprio J, Ronnemaa T. Environmental factors in the development of obesity in identical
twins. Int J Obes Relat Metab Disord. 1999;23:746–753. [PubMed] [Google Scholar]
215. Hallan S, de Mutsert R, Carlsen S, Dekker FW, Aasarod K, Holmen J. Obesity, smoking, and physical inactivity as risk factors for CKD: are men
more vulnerable? Am J Kidney Dis. 2006;47:396–405. [PubMed] [Google Scholar]
216. Hamburg NM, McMackin CJ, Huang AL, Shenouda SM, Widlansky ME, Schulz E, Gokce N, Ruderman NB, Keaney JF, Jr, Vita JA. Physical inactivity rapidly induces insulin resistance and microvascular
dysfunction in healthy volunteers. Arterioscler Thromb Vasc Biol. 2007;27:2650–2656. [PMC free article] [PubMed] [Google Scholar]
217. Hamel P, Simoneau JA, Lortie G, Boulay MR, Bouchard C. Heredity and muscle adaptation to endurance training. Med Sci Sports Exerc. 1986;18:690–696. [PubMed] [Google Scholar]
218. Hamilton MT, Hamilton DG, Zderic TW. Role of low energy expenditure and sitting in obesity, metabolic syndrome,
type 2 diabetes, and cardiovascular disease. Diabetes. 2007;56:2655–2667. [PubMed] [Google Scholar]
219. Hamman RF, Wing RR, Edelstein SL, Lachin JM, Bray GA, Delahanty L, Hoskin M, Kriska AM, Mayer-Davis EJ, Pi-Sunyer X, Regensteiner J, Venditti B, Wylie-Rosett J. Effect of weight loss with lifestyle intervention on risk of
diabetes. Diabetes Care. 2006;29:2102–2107. [PMC free article] [PubMed] [Google Scholar]
220. Hammermeister J, Page RM, Dolny D, Burnham T. Occupational physical activity as an indicator of health and
fitness. Percept Mot Skills. 2001;92:121–127. [PubMed] [Google Scholar]
221. Hannukainen JC, Janatuinen T, Toikka JO, Jarvisalo MJ, Heinonen OJ, Kapanen J, Nagren K, Nuutila P, Kujala UM, Kaprio J, Knuuti J, Kalliokoski KK. Myocardial and peripheral vascular functional adaptation to exercise
training. Scand J Med Sci Sports. 2007;17:139–147. [PubMed] [Google Scholar]
222. Hannukainen JC, Nuutila P, Borra R, Kaprio J, Kujala UM, Janatuinen T, Heinonen OJ, Kapanen J, Viljanen T, Haaparanta M, Ronnemaa T, Parkkola R, Knuuti J, Kalliokoski KK. Increased physical activity decreases hepatic free fatty acid uptake: a
study in human monozygotic twins. J Physiol. 2007;578:347–358. [PMC free article] [PubMed] [Google Scholar]
223. Hannukainen JC, Nuutila P, Kaprio J, Heinonen OJ, Kujala UM, Janatuinen T, Ronnemaa T, Kapanen J, Haaparanta-Solin M, Viljanen T, Knuuti J, Kalliokoski KK. Relationship between local perfusion and FFA uptake in human skeletal
muscle-no effect of increased physical activity and aerobic fitness. J Appl Physiol. 2006;101:1303–1311. [PubMed] [Google Scholar]
224. Haskell-Luevano C, Schaub JW, Andreasen A, Haskell KR, Moore MC, Koerper LM, Rouzaud F, Baker HV, Millard WJ, Walter G, Litherland SA, Xiang Z. Voluntary exercise prevents the obese and diabetic metabolic syndrome of
the melanocortin-4 receptor knockout mouse. FASEB J. 2009;23:642–655. [PMC free article] [PubMed] [Google Scholar]
225. Hayes M, Chustek M, Heshka S, Wang Z, Pietrobelli A, Heymsfield SB. Low physical activity levels of modern Homo sapiens among free-ranging
mammals. Int J Obes (Lond) 2005;29:151–156. [PubMed] [Google Scholar]
226. Hayflick L. The not-so-close relationship between biological aging and age-associated
pathologies in humans. J Gerontol A Biol Sci Med Sci. 2004;59:B547–550. discussion 551–543. [PubMed] [Google Scholar]
227. Haykowsky M, Scott J, Esch B, Schopflocher D, Myers J, Paterson I, Warburton D, Jones L, Clark AM. A Meta-analysis of the effects of Exercise Training on Left Ventricular
Remodeling Following Myocardial Infarction: Start early and go longer for greatest
exercise benefits on remodeling. Trials. 2011;12:92. [PMC free article] [PubMed] [Google Scholar]
228. Healy GN, Dunstan DW, Salmon J, Cerin E, Shaw JE, Zimmet PZ, Owen N. Objectively measured light-intensity physical activity is independently
associated with 2-h plasma glucose. Diabetes Care. 2007;30:1384–1389. [PubMed] [Google Scholar]
229. Heath GW, Ford ES, Craven TE, Macera CA, Jackson KL, Pate RR. Exercise and the incidence of upper respiratory tract
infections. Med Sci Sports Exerc. 1991;23:152–157. [PubMed] [Google Scholar]
230. Heath GW, Gavin JR, 3rd, Hinderliter JM, Hagberg JM, Bloomfield SA, Holloszy JO. Effects of exercise and lack of exercise on glucose tolerance and insulin
sensitivity. J Appl Physiol. 1983;55:512–517. [PubMed] [Google Scholar]
231. Heitmann BL, Kaprio J, Harris JR, Rissanen A, Korkeila M, Koskenvuo M. Are genetic determinants of weight gain modified by leisure-time physical
activity? A prospective study of Finnish twins. Am J Clin Nutr. 1997;66:672–678. [PubMed] [Google Scholar]
232. Helenius IJ, Tikkanen HO, Haahtela T. Association between type of training and risk of asthma in elite
athletes. Thorax. 1997;52:157–160. [PMC free article] [PubMed] [Google Scholar]
233. Helenius IJ, Tikkanen HO, Sarna S, Haahtela T. Asthma and increased bronchial responsiveness in elite athletes: atopy and
sport event as risk factors. J Allergy Clin Immunol. 1998;101:646–652. [PubMed] [Google Scholar]
234. Helmrich SP, Ragland DR, Leung RW, Paffenbarger RS., Jr Physical activity and reduced occurrence of non-insulin-dependent diabetes
mellitus. N Engl J Med. 1991;325:147–152. [PubMed] [Google Scholar]
235. Hernandez CJ, Beaupre GS, Carter DR. A theoretical analysis of the relative influences of peak BMD, age-related
bone loss and menopause on the development of osteoporosis. Osteoporos Int. 2003;14:843–847. [PubMed] [Google Scholar]
236. Hernelahti M, Levalahti E, Simonen RL, Kaprio J, Kujala UM, Uusitalo-Koskinen AL, Battie MC, Videman T. Relative roles of heredity and physical activity in adolescence and
adulthood on blood pressure. J Appl Physiol. 2004;97:1046–1052. [PubMed] [Google Scholar]
237. Hillman CH, Buck SM, Themanson JR, Pontifex MB, Castelli DM. Aerobic fitness and cognitive development: Event-related brain potential
and task performance indices of executive control in preadolescent
children. Dev Psychol. 2009;45:114–129. [PubMed] [Google Scholar]
238. Hillman CH, Castelli DM, Buck SM. Aerobic fitness and neurocognitive function in healthy preadolescent
children. Med Sci Sports Exerc. 2005;37:1967–1974. [PubMed] [Google Scholar]
239. Hillman CH, Erickson KI, Kramer AF. Be smart, exercise your heart: exercise effects on brain and
cognition. Nat Rev Neurosci. 2008;9:58–65. [PubMed] [Google Scholar]
241. Holloszy JO. The biology of aging. Mayo Clin Proc. 2000;75 Suppl:S3–8. discussion S8–9. [PubMed] [Google Scholar]
242. Holloszy JO. Exercise-induced increase in muscle insulin sensitivity. J Appl Physiol. 2005;99:338–343. [PubMed] [Google Scholar]
243. Holloszy JO, Booth FW. Biochemical adaptations to endurance exercise in muscle. Annu Rev Physiol. 1976;38:273–291. [PubMed] [Google Scholar]
244. Houmard JA, Cox JH, MacLean PS, Barakat HA. Effect of short-term exercise training on leptin and insulin
action. Metabolism. 2000;49:858–861. [PubMed] [Google Scholar]
245. Houmard JA, Egan PC, Neufer PD, Friedman JE, Wheeler WS, Israel RG, Dohm GL. Elevated skeletal muscle glucose transporter levels in exercise-trained
middle-aged men. Am J Physiol. 1991;261:E437–443. [PubMed] [Google Scholar]
246. Houmard JA, Tanner CJ, Slentz CA, Duscha BD, McCartney JS, Kraus WE. Effect of the volume and intensity of exercise training on insulin
sensitivity. J Appl Physiol. 2004;96:101–106. [PubMed] [Google Scholar]
247. Houmard JA, Weidner MD, Dolan PL, Leggett-Frazier N, Gavigan KE, Hickey MS, Tyndall GL, Zheng D, Alshami A, Dohm GL. Skeletal muscle GLUT4 protein concentration and aging in
humans. Diabetes. 1995;44:555–560. [PubMed] [Google Scholar]
248. Hu FB, Sigal RJ, Rich-Edwards JW, Colditz GA, Solomon CG, Willett WC, Speizer FE, Manson JE. Walking compared with vigorous physical activity and risk of type 2
diabetes in women: a prospective study. JAMA. 1999;282:1433–1439. [PubMed] [Google Scholar]
249. Hu G, Lindstrom J, Valle TT, Eriksson JG, Jousilahti P, Silventoinen K, Qiao Q, Tuomilehto J. Physical activity, body mass index, and risk of type 2 diabetes in patients
with normal or impaired glucose regulation. Arch Intern Med. 2004;164:892–896. [PubMed] [Google Scholar]
250. Hubal MJ, Gordish-Dressman H, Thompson PD, Price TB, Hoffman EP, Angelopoulos TJ, Gordon PM, Moyna NM, Pescatello LS, Visich PS, Zoeller RF, Seip RL, Clarkson PM. Variability in muscle size and strength gain after unilateral resistance
training. Med Sci Sports Exerc. 2005;37:964–972. [PubMed] [Google Scholar]
251. Hunter GR, Brock DW, Byrne NM, Chandler-Laney PC, Del Corral P, Gower BA. Exercise training prevents regain of visceral fat for 1 year following
weight loss. Obesity (Silver Spring) 2010;18:690–695. [PMC free article] [PubMed] [Google Scholar]
252. Hunter GR, McCarthy JP, Bamman MM. Effects of resistance training on older adults. Sports Med. 2004;34:329–348. [PubMed] [Google Scholar]
253. Irwin ML, Yasui Y, Ulrich CM, Bowen D, Rudolph RE, Schwartz RS, Yukawa M, Aiello E, Potter JD, McTiernan A. Effect of exercise on total and intra-abdominal body fat in postmenopausal
women: a randomized controlled trial. JAMA. 2003;289:323–330. [PubMed] [Google Scholar]
254. Iuliano-Burns S, Stone J, Hopper JL, Seeman E. Diet and exercise during growth have site-specific skeletal effects: a
co-twin control study. Osteoporos Int. 2005;16:1225–1232. [PubMed] [Google Scholar]
255. Ivy JL, Holloszy JO. Persistent increase in glucose uptake by rat skeletal muscle following
exercise. Am J Physiol. 1981;241:C200–203. [PubMed] [Google Scholar]
256. James WP. The fundamental drivers of the obesity epidemic. Obes Rev. 2008;9 Suppl 1:6–13. [PubMed] [Google Scholar]
257. Johnson JL, Slentz CA, Houmard JA, Samsa GP, Duscha BD, Aiken LB, McCartney JS, Tanner CJ, Kraus WE. Exercise training amount and intensity effects on metabolic syndrome (from
Studies of a Targeted Risk Reduction Intervention through Defined
Exercise) Am J Cardiol. 2007;100:1759–1766. [PMC free article] [PubMed] [Google Scholar]
258. Johnson W, Krueger RF. The psychological benefits of vigorous exercise: a study of discordant MZ
twin pairs. Twin Res Hum Genet. 2007;10:275–283. [PubMed] [Google Scholar]
259. Joosen AM, Gielen M, Vlietinck R, Westerterp KR. Genetic analysis of physical activity in twins. Am J Clin Nutr. 2005;82:1253–1259. [PubMed] [Google Scholar]
261. Joyner MJ, Green DJ. Exercise protects the cardiovascular system: effects beyond traditional
risk factors. J Physiol. 2009;587:5551–5558. [PMC free article] [PubMed] [Google Scholar]
262. Ju J, Nolan B, Cheh M, Bose M, Lin Y, Wagner GC, Yang CS. Voluntary exercise inhibits intestinal tumorigenesis in Apc(Min/+) mice and
azoxymethane/dextran sulfate sodium-treated mice. BMC Cancer. 2008;8:316. [PMC free article] [PubMed] [Google Scholar]
263. Kaminsky LA. ACSM’s Health-related physical fitness assessment manual. 3rd ed Wolters Kluwer; Philadelphia: 2010. p. 151. [Google Scholar]
264. Kantartzis K, Thamer C, Peter A, Machann J, Schick F, Schraml C, Konigsrainer A, Konigsrainer I, Krober S, Niess A, Fritsche A, Haring HU, Stefan N. High cardiorespiratory fitness is an independent predictor of the reduction
in liver fat during a lifestyle intervention in non-alcoholic fatty liver
disease. Gut. 2009;58:1281–1288. [PubMed] [Google Scholar]
266. Karnehed N, Tynelius P, Heitmann BL, Rasmussen F. Physical activity, diet and gene-environment interactions in relation to
body mass index and waist circumference: the Swedish young male twins
study. Public Health Nutr. 2006;9:851–858. [PubMed] [Google Scholar]
267. Katz DL. Preventive medicine, integrative medicine & the health of the public. 2009. AA. [Google Scholar]
268. Katzmarzyk PT, Church TS, Craig CL, Bouchard C. Sitting time and mortality from all causes, cardiovascular disease, and
cancer. Med Sci Sports Exerc. 2009;41:998–1005. [PubMed] [Google Scholar]
269. Keller P, Vollaard NB, Gustafsson T, Gallagher IJ, Sundberg CJ, Rankinen T, Britton SL, Bouchard C, Koch LG, Timmons JA. A transcriptional map of the impact of endurance exercise training on
skeletal muscle phenotype. J Appl Physiol. 2011;110:46–59. [PMC free article] [PubMed] [Google Scholar]
270. Kelley GA, Kelley KS. Impact of progressive resistance training on lipids and lipoproteins in
adults: a meta-analysis of randomized controlled trials. Prev Med. 2009;48:9–19. [PubMed] [Google Scholar]
271. Kenfield SA, Stampfer MJ, Giovannucci E, Chan JM. Physical Activity and Survival After Prostate Cancer Diagnosis in the
Health Professionals Follow-Up Study. J Clin Oncol. 2011;29:72–732. [PMC free article] [PubMed] [Google Scholar]
272. Kersh R, Morone J. The politics of obesity: seven steps to government action. Health Aff (Millwood) 2002;21:142–153. [PubMed] [Google Scholar]
273. Kim HY, Frongillo EA, Han SS, Oh SY, Kim WK, Jang YA, Won HS, Lee HS, Kim SH. Academic performance of Korean children is associated with dietary
behaviours and physical status. Asia Pac J Clin Nutr. 2003;12:186–192. [PubMed] [Google Scholar]
274. Kirwan JP, Solomon TP, Wojta DM, Staten MA, Holloszy JO. Effects of 7 days of exercise training on insulin sensitivity and
responsiveness in type 2 diabetes mellitus. Am J Physiol Endocrinol Metab. 2009;297:E151–156. [PMC free article] [PubMed] [Google Scholar]
275. Kleim JA, Cooper NR, VandenBerg PM. Exercise induces angiogenesis but does not alter movement representations
within rat motor cortex. Brain Res. 2002;934:1–6. [PubMed] [Google Scholar]
276. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM. Reduction in the incidence of type 2 diabetes with lifestyle intervention
or metformin. N Engl J Med. 2002;346:393–403. [PMC free article] [PubMed] [Google Scholar]
277. Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, Sugawara A, Totsuka K, Shimano H, Ohashi Y, Yamada N, Sone H. Cardiorespiratory fitness as a quantitative predictor of all-cause
mortality and cardiovascular events in healthy men and women: a
meta-analysis. JAMA. 2009;301:2024–2035. [PubMed] [Google Scholar]
278. Kokkinos P, Myers J. Exercise and physical activity: clinical outcomes and
applications. Circulation. 2010;122:1637–1648. [PubMed] [Google Scholar]
279. Kokkinos P, Myers J, Faselis C, Panagiotakos DB, Doumas M, Pittaras A, Manolis A, Kokkinos JP, Karasik P, Greenberg M, Papademetriou V, Fletcher R. Exercise capacity and mortality in older men: a 20-year follow-up
study. Circulation. 2010;122:790–797. [PubMed] [Google Scholar]
280. Kokkinos P, Myers J, Kokkinos JP, Pittaras A, Narayan P, Manolis A, Karasik P, Greenberg M, Papademetriou V, Singh S. Exercise capacity and mortality in black and white men. Circulation. 2008;117:614–622. [PubMed] [Google Scholar]
281. Koves TR, Ussher JR, Noland RC, Slentz D, Mosedale M, Ilkayeva O, Bain J, Stevens R, Dyck JR, Newgard CB, Lopaschuk GD, Muoio DM. Mitochondrial overload and incomplete fatty acid oxidation contribute to
skeletal muscle insulin resistance. Cell Metab. 2008;7:45–56. [PubMed] [Google Scholar]
282. Kramer AF, Hahn S, Cohen NJ, Banich MT, McAuley E, Harrison CR, Chason J, Vakil E, Bardell L, Boileau RA, Colcombe A. Ageing, fitness and neurocognitive function. Nature. 1999;400:418–419. [PubMed] [Google Scholar]
283. Krasnoff JB, Painter PL, Wallace JP, Bass NM, Merriman RB. Health-related fitness and physical activity in patients with nonalcoholic
fatty liver disease. Hepatology. 2008;47:1158–1166. [PMC free article] [PubMed] [Google Scholar]
284. Kraus WE, Houmard JA, Duscha BD, Knetzger KJ, Wharton MB, McCartney JS, Bales CW, Henes S, Samsa GP, Otvos JD, Kulkarni KR, Slentz CA. Effects of the amount and intensity of exercise on plasma
lipoproteins. N Engl J Med. 2002;347:1483–1492. [PubMed] [Google Scholar]
285. Kriska AM, Brach JS, Jarvis BJ, Everhart JE, Fabio A, Richardson CR, Howard BV. Physical activity and gallbladder disease determined by
ultrasonography. Med Sci Sports Exerc. 2007;39:1927–1932. [PubMed] [Google Scholar]
286. Krogh-Madsen R, Thyfault JP, Broholm C, Mortensen OH, Olsen RH, Mounier R, Plomgaard P, van Hall G, Booth FW, Pedersen BK. A 2-wk reduction of ambulatory activity attenuates peripheral insulin
sensitivity. J Appl Physiol. 2010;108:1034–1040. [PubMed] [Google Scholar]
287. Krop JS, Coresh J, Chambless LE, Shahar E, Watson RL, Szklo M, Brancati FL. A community-based study of explanatory factors for the excess risk for
early renal function decline in blacks vs whites with diabetes: the Atherosclerosis Risk
in Communities study. Arch Intern Med. 1999;159:1777–1783. [PubMed] [Google Scholar]
288. Kujala UM, Kaprio J, Koskenvuo M. Diabetes in a population-based series of twin pairs discordant for leisure
sedentariness. Diabetologia. 2000;43:259. [PubMed] [Google Scholar]
289. Kujala UM, Kaprio J, Koskenvuo M. Modifiable risk factors as predictors of all-cause mortality: the roles of
genetics and childhood environment. Am J Epidemiol. 2002;156:985–993. [PubMed] [Google Scholar]
290. Kujala UM, Kaprio J, Rose RJ. Physical activity in adolescence and smoking in young adulthood: a
prospective twin cohort study. Addiction. 2007;102:1151–1157. [PMC free article] [PubMed] [Google Scholar]
291. Kujala UM, Sarna S, Kaprio J, Koskenvuo M. Asthma and other pulmonary diseases in former elite
athletes. Thorax. 1996;51:288–292. [PMC free article] [PubMed] [Google Scholar]
292. Kumanyika SK, Obarzanek E, Stettler N, Bell R, Field AE, Fortmann SP, Franklin BA, Gillman MW, Lewis CE, Poston WC, 2nd, Stevens J, Hong Y. Population-based prevention of obesity: the need for comprehensive
promotion of healthful eating, physical activity, and energy balance: a scientific
statement from American Heart Association Council on Epidemiology and Prevention,
Interdisciplinary Committee for Prevention (formerly the expert panel on population and
prevention science) Circulation. 2008;118:428–464. [PubMed] [Google Scholar]
293. Kump DS, Booth FW. Alterations in insulin receptor signalling in the rat epitrochlearis muscle
upon cessation of voluntary exercise. J Physiol. 2005;562:829–838. [PMC free article] [PubMed] [Google Scholar]
294. Kuo CH, Browning KS, Ivy JL. Regulation of GLUT4 protein expression and glycogen storage after prolonged
exercise. Acta Physiol Scand. 1999;165:193–201. [PubMed] [Google Scholar]
295. Kupelian V, Araujo AB, Chiu GR, Rosen RC, McKinlay JB. Relative contributions of modifiable risk factors to erectile dysfunction:
results from the Boston Area Community Health (BACH) Survey. Prev Med. 2010;50:19–25. [PMC free article] [PubMed] [Google Scholar]
296. Laaksonen DE, Lakka HM, Salonen JT, Niskanen LK, Rauramaa R, Lakka TA. Low levels of leisure-time physical activity and cardiorespiratory fitness
predict development of the metabolic syndrome. Diabetes Care. 2002;25:1612–1618. [PubMed] [Google Scholar]
297. Laaksonen DE, Lindstrom J, Lakka TA, Eriksson JG, Niskanen L, Wikstrom K, Aunola S, Keinanen-Kiukaanniemi S, Laakso M, Valle TT, Ilanne-Parikka P, Louheranta A, Hamalainen H, Rastas M, Salminen V, Cepaitis Z, Hakumaki M, Kaikkonen H, Harkonen P, Sundvall J, Tuomilehto J, Uusitupa M. Physical activity in the prevention of type 2 diabetes: the Finnish
diabetes prevention study. Diabetes. 2005;54:158–165. [PubMed] [Google Scholar]
298. Lakka HM, Tremblay A, Despres JP, Bouchard C. Effects of long-term negative energy balance with exercise on plasma lipid
and lipoprotein levels in identical twins. Atherosclerosis. 2004;172:127–133. [PubMed] [Google Scholar]
299. Lakka TA, Laaksonen DE. Physical activity in prevention and treatment of the metabolic
syndrome. Appl Physiol Nutr Metab. 2007;32:76–88. [PubMed] [Google Scholar]
300. LaMonte MJ, Blair SN, Church TS. Physical activity and diabetes prevention. J Appl Physiol. 2005;99:1205–1213. [PubMed] [Google Scholar]
301. Lancaster GI, Halson SL, Khan Q, Drysdale P, Wallace F, Jeukendrup AE, Drayson MT, Gleeson M. Effects of acute exhaustive exercise and chronic exercise training on type
1 and type 2 T lymphocytes. Exerc Immunol Rev. 2004;10:91–106. [PubMed] [Google Scholar]
302. Lancaster GI, Khan Q, Drysdale P, Wallace F, Jeukendrup AE, Drayson MT, Gleeson M. The physiological regulation of toll-like receptor expression and function
in humans. J Physiol. 2005;563:945–955. [PMC free article] [PubMed] [Google Scholar]
303. Landry F, Bouchard C, Dumesnil J. Cardiac dimension changes with endurance training. Indications of a
genotype dependency. JAMA. 1985;254:77–80. [PubMed] [Google Scholar]
304. Lanningham-Foster L, Nysse LJ, Levine JA. Labor saved, calories lost: the energetic impact of domestic labor-saving
devices. Obes Res. 2003;11:1178–1181. [PubMed] [Google Scholar]
305. Lanza IR, Short DK, Short KR, Raghavakaimal S, Basu R, Joyner MJ, McConnell JP, Nair KS. Endurance exercise as a countermeasure for aging. Diabetes. 2008;57:2933–2942. [PMC free article] [PubMed] [Google Scholar]
306. Larson EB, Wang L, Bowen JD, McCormick WC, Teri L, Crane P, Kukull W. Exercise is associated with reduced risk for incident dementia among
persons 65 years of age and older. Ann Intern Med. 2006;144:73–81. [PubMed] [Google Scholar]
307. Laufs U, Wassmann S, Czech T, Munzel T, Eisenhauer M, Bohm M, Nickenig G. Physical inactivity increases oxidative stress, endothelial dysfunction,
and atherosclerosis. Arterioscler Thromb Vasc Biol. 2005;25:809–814. [PubMed] [Google Scholar]
308. Laughlin MH, Newcomer SC, Bender SB. Importance of hemodynamic forces as signals for exercise-induced changes in
endothelial cell phenotype. J Appl Physiol. 2008;104:588–600. [PMC free article] [PubMed] [Google Scholar]
309. Laurin D, Verreault R, Lindsay J, MacPherson K, Rockwood K. Physical activity and risk of cognitive impairment and dementia in elderly
persons. Arch Neurol. 2001;58:498–504. [PubMed] [Google Scholar]
310. Laye MJ, Rector RS, Borengasser SJ, Naples SP, Uptergrove GM, Ibdah JA, Booth FW, Thyfault JP. Cessation of daily wheel running differentially alters fat oxidation
capacity in liver, muscle, and adipose tissue. J Appl Physiol. 2009;106:161–168. [PMC free article] [PubMed] [Google Scholar]
311. Lecker SH, Jagoe RT, Gilbert A, Gomes M, Baracos V, Bailey J, Price SR, Mitch WE, Goldberg AL. Multiple types of skeletal muscle atrophy involve a common program of
changes in gene expression. FASEB J. 2004;18:39–51. [PubMed] [Google Scholar]
312. Lee DC, Artero EG, Sui X, Blair SN. Mortality trends in the general population: the importance of
cardiorespiratory fitness. J Psychopharmacol. 2010;24:27–35. [PMC free article] [PubMed] [Google Scholar]
313. Lee DC, Sui X, Church TS, Lee IM, Blair SN. Associations of cardiorespiratory fitness and obesity with risks of
impaired fasting glucose and type 2 diabetes in men. Diabetes Care. 2009;32:257–262. [PMC free article] [PubMed] [Google Scholar]
315. Lee S, Bacha F, Gungor N, Arslanian S. Comparison of different definitions of pediatric metabolic syndrome:
relation to abdominal adiposity, insulin resistance, adiponectin, and inflammatory
biomarkers. J Pediatr. 2008;152:177–184. [PubMed] [Google Scholar]
316. Leskinen T, Sipila S, Alen M, Cheng S, Pietilainen KH, Usenius JP, Suominen H, Kovanen V, Kainulainen H, Kaprio J, Kujala UM. Leisure-time physical activity and high-risk fat: a longitudinal
population-based twin study. Int J Obes (Lond) 2009;33:1211–1218. [PubMed] [Google Scholar]
317. Levine JA, Schleusner SJ, Jensen MD. Energy expenditure of nonexercise activity. Am J Clin Nutr. 2000;72:1451–1454. [PubMed] [Google Scholar]
318. Li C, Ford ES, Zhao G, Mokdad AH. Prevalence of pre-diabetes and its association with clustering of
cardiometabolic risk factors and hyperinsulinemia among U.S. adolescents: National
Health and Nutrition Examination Survey 2005–2006. Diabetes Care. 2009;32:342–347. [PMC free article] [PubMed] [Google Scholar]
319. Lichtenstein P, Holm NV, Verkasalo PK, Iliadou A, Kaprio J, Koskenvuo M, Pukkala E, Skytthe A, Hemminki K. Environmental and heritable factors in the causation of cancer–analyses of
cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med. 2000;343:78–85. [PubMed] [Google Scholar]
320. Lippi G, Maffulli N. Biological influence of physical exercise on hemostasis. Semin Thromb Hemost. 2009;35:269–276. [PubMed] [Google Scholar]
321. Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, Ferguson TB, Ford E, Furie K, Gillespie C, Go A, Greenlund K, Haase N, Hailpern S, Ho PM, Howard V, Kissela B, Kittner S, Lackland D, Lisabeth L, Marelli A, McDermott MM, Meigs J, Mozaffarian D, Mussolino M, Nichol G, Roger VL, Rosamond W, Sacco R, Sorlie P, Thom T, Wasserthiel-Smoller S, Wong ND, Wylie-Rosett J. Heart disease and stroke statistics–2010 update: a report from the
American Heart Association. Circulation. 2010;121:e46–e215. [PubMed] [Google Scholar]
322. Loomba R, Sirlin CB, Schwimmer JB, Lavine JE. Advances in pediatric nonalcoholic fatty liver disease. Hepatology. 2009;50:1282–1293. [PMC free article] [PubMed] [Google Scholar]
323. Lopez-Lopez C, LeRoith D, Torres-Aleman I. Insulin-like growth factor I is required for vessel remodeling in the adult
brain. Proc Natl Acad Sci U S A. 2004;101:9833–9838. [PMC free article] [PubMed] [Google Scholar]
324. Luger A, Deuster PA, Kyle SB, Gallucci WT, Montgomery LC, Gold PW, Loriaux DL, Chrousos GP. Acute hypothalamic-pituitary-adrenal responses to the stress of treadmill
exercise. Physiologic adaptations to physical training. N Engl J Med. 1987;316:1309–1315. [PubMed] [Google Scholar]
325. Lynch BM, White SL, Owen N, Healy GN, Chadban SJ, Atkins RC, Dunstan DW. Television viewing time and risk of chronic kidney disease in adults: the
AusDiab Study. Ann Behav Med. 2010;40:265–274. [PubMed] [Google Scholar]
326. Mantzoros CS, Georgiadis EI. Body mass and physical activity are important predictors of serum androgen
concentrations in young healthy men. Epidemiology. 1995;6:432–435. [PubMed] [Google Scholar]
327. Marcovecchio M, Mohn A, Chiarelli F. Type 2 diabetes mellitus in children and adolescents. J Endocrinol Invest. 2005;28:853–863. [PubMed] [Google Scholar]
328. Martin B, Ji S, Maudsley S, Mattson MP. “Control” laboratory rodents are metabolically morbid: why it
matters. Proc Natl Acad Sci U S A. 2010;107:6127–6133. [PMC free article] [PubMed] [Google Scholar]
329. Martyn-St James M, Carroll S. A meta-analysis of impact exercise on postmenopausal bone loss: the case
for mixed loading exercise programmes. Br J Sports Med. 2009;43:898–908. [PubMed] [Google Scholar]
330. Mata J, Thompson RJ, Gotlib IH. BDNF genotype moderates the relation between physical activity and
depressive symptoms. Health Psychol. 2010;29:130–133. [PMC free article] [PubMed] [Google Scholar]
331. Matthews CE, Ockene IS, Freedson PS, Rosal MC, Merriam PA, Hebert JR. Moderate to vigorous physical activity and risk of upper-respiratory tract
infection. Med Sci Sports Exerc. 2002;34:1242–1248. [PubMed] [Google Scholar]
332. Matthews VB, Astrom MB, Chan MH, Bruce CR, Krabbe KS, Prelovsek O, Akerstrom T, Yfanti C, Broholm C, Mortensen OH, Penkowa M, Hojman P, Zankari A, Watt MJ, Bruunsgaard H, Pedersen BK, Febbraio MA. Brain-derived neurotrophic factor is produced by skeletal muscle cells in
response to contraction and enhances fat oxidation via activation of AMP-activated
protein kinase. Diabetologia. 2009;52:1409–1418. [PubMed] [Google Scholar]
333. Mayhew DLKJ, Kosek D, Petrella, Cross J, Bamman M. The PI3K/Akt/mTOR pathway is up-regulated during skeletal muscle
hypertrophy in humans. FASEB J. 2007;21:895. [Google Scholar]
334. McAuley PA, Kokkinos PF, Oliveira RB, Emerson BT, Myers JN. Obesity paradox and cardiorespiratory fitness in 12,417 male veterans aged
40 to 70 years. Mayo Clin Proc. 2010;85:115–121. [PMC free article] [PubMed] [Google Scholar]
335. McCaffery JM, Papandonatos GD, Bond DS, Lyons MJ, Wing RR. Gene X environment interaction of vigorous exercise and body mass index
among male Vietnam-era twins. Am J Clin Nutr. 2009;89:1011–1018. [PMC free article] [PubMed] [Google Scholar]
336. McDermott MM, Liu K, Ferrucci L, Criqui MH, Greenland P, Guralnik JM, Tian L, Schneider JR, Pearce WH, Tan J, Martin GJ. Physical performance in peripheral arterial disease: a slower rate of
decline in patients who walk more. Ann Intern Med. 2006;144:10–20. [PubMed] [Google Scholar]
337. Mehl KA, Davis JM, Clements JM, Berger FG, Pena MM, Carson JA. Decreased intestinal polyp multiplicity is related to exercise mode and
gender in ApcMin/+ mice. J Appl Physiol. 2005;98:2219–2225. [PubMed] [Google Scholar]
338. Meisinger C, Lowel H, Thorand B, Doring A. Leisure time physical activity and the risk of type 2 diabetes in men and
women from the general population. The MONICA/KORA Augsburg Cohort Study. Diabetologia. 2005;48:27–34. [PubMed] [Google Scholar]
339. Melzer K, Schutz Y, Boulvain M, Kayser B. Physical activity and pregnancy: cardiovascular adaptations,
recommendations and pregnancy outcomes. Sports Med. 2010;40:493–507. [PubMed] [Google Scholar]
340. Messerli FH, Messerli AW, Luscher TF. Eisenhower’s billion-dollar heart attack–50 years later. N Engl J Med. 2005;353:1205–1207. [PubMed] [Google Scholar]
341. Middleton LE, Barnes DE, Lui LY, Yaffe K. Physical activity over the life course and its association with cognitive
performance and impairment in old age. J Am Geriatr Soc. 2010;58:1322–1326. [PMC free article] [PubMed] [Google Scholar]
342. Mikines KJ, Dela F, Tronier B, Galbo H. Effect of 7 days of bed rest on dose-response relation between plasma
glucose and insulin secretion. Am J Physiol. 1989;257:E43–48. [PubMed] [Google Scholar]
343. Mikines KJ, Sonne B, Farrell PA, Tronier B, Galbo H. Effect of physical exercise on sensitivity and responsiveness to insulin in
humans. Am J Physiol. 1988;254:E248–259. [PubMed] [Google Scholar]
344. Mirone V, Imbimbo C, Fusco F, Verze P, Creta M, Tajana G. Androgens and morphologic remodeling at penile and cardiovascular levels: a
common piece in complicated puzzles? Eur Urol. 2009;56:309–316. [PubMed] [Google Scholar]
345. Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States, 2000. JAMA. 2004;291:1238–1245. [PubMed] [Google Scholar]
346. Molteni R, Ying Z, Gomez-Pinilla F. Differential effects of acute and chronic exercise on plasticity-related
genes in the rat hippocampus revealed by microarray. Eur J Neurosci. 2002;16:1107–1116. [PubMed] [Google Scholar]
347. Monninkhof EM, Elias SG, Vlems FA, van der Tweel I, Schuit AJ, Voskuil DW, van Leeuwen FE. Physical activity and breast cancer: a systematic review. Epidemiology. 2007;18:137–157. [PubMed] [Google Scholar]
348. Moore SC, Gierach GL, Schatzkin A, Matthews CE. Physical activity, sedentary behaviours, and the prevention of endometrial
cancer. Br J Cancer. 2010;103:933–938. [PMC free article] [PubMed] [Google Scholar]
349. Mora S, Cook N, Buring JE, Ridker PM, Lee IM. Physical activity and reduced risk of cardiovascular events: potential
mediating mechanisms. Circulation. 2007;116:2110–2118. [PMC free article] [PubMed] [Google Scholar]
350. Morgan WP. Physical working capacity in depressed and non-depressed psychiatric
females: a preliminary study. Am Correct Ther J. 1970;24:14–16. [PubMed] [Google Scholar]
351. Morgan WP. Selected physiological and psychomotor correlates of depression in
psychiatric patients. Res Q. 1968;39:1037–1043. [PubMed] [Google Scholar]
352. Morris CK, Ueshima K, Kawaguchi T, Hideg A, Froelicher VF. The prognostic value of exercise capacity: a review of the
literature. Am Heart J. 1991;122:1423–1431. [PubMed] [Google Scholar]
353. Morris JN, Heady JA, Raffle PA, Roberts CG, Parks JW. Coronary heart-disease and physical activity of work. Lancet. 1953;265:1053–1057. [PubMed] [Google Scholar]
354. Morris JN. Foreward. In: Lee I-MBS, Manson JE, editors. Epidemiologic methods in physical activity studies. Oxford Press; New York: 2009. pp. 3–12. [Google Scholar]
355. Morris RT, Laye MJ, Lees SJ, Rector RS, Thyfault JP, Booth FW. Exerciseinduced attenuation of obesity, hyperinsulinemia, and skeletal
muscle lipid peroxidation in the OLETF rat. J Appl Physiol. 2008;104:708–715. [PubMed] [Google Scholar]
356. Morrison JA, Friedman LA, Wang P, Glueck CJ. Metabolic syndrome in childhood predicts adult metabolic syndrome and type
2 diabetes mellitus 25 to 30 years later. J Pediatr. 2008;152:201–206. [PubMed] [Google Scholar]
357. Morrison PR, Montgomery JA, Wong TS, Booth FW. Cytochrome c proteinsynthesis rates and mRNA contents during atrophy and
recovery in skeletal muscle. Biochem J. 1987;241:257–263. [PMC free article] [PubMed] [Google Scholar]
358. Mosby’s . Mosby’s Medical Dictionary. Elsevier: 2009. [Google Scholar]
359. Moser AR, Pitot HC, Dove WF. A dominant mutation that predisposes to multiple intestinal neoplasia in
the mouse. Science. 1990;247:322–324. [PubMed] [Google Scholar]
360. Mourier A, Gautier JF, De Kerviler E, Bigard AX, Villette JM, Garnier JP, Duvallet A, Guezennec CY, Cathelineau G. Mobilization of visceral adipose tissue related to the improvement in
insulin sensitivity in response to physical training in NIDDM. Effects of branchedchain
amino acid supplements. Diabetes Care. 1997;20:385–391. [PubMed] [Google Scholar]
361. Musicki B, Liu T, Strong T, Jin L, Laughlin MH, Turk JR, Burnett AL. Low-fat diet and exercise preserve eNOS regulation and endothelial function
in the penis of early atherosclerotic pigs: a molecular analysis. J Sex Med. 2008;5:552–561. [PMC free article] [PubMed] [Google Scholar]
362. Mustelin L, Pietilainen KH, Rissanen A, Sovijarvi AR, Piirila P, Naukkarinen J, Peltonen L, Kaprio J, Yki-Jarvinen H. Acquired obesity and poor physical fitness impair expression of genes of
mitochondrial oxidative phosphorylation in monozygotic twins discordant for
obesity. Am J Physiol Endocrinol Metab. 2008;295:E148–154. [PMC free article] [PubMed] [Google Scholar]
363. Myers J, Prakash M, Froelicher V, Do D, Partington S, Atwood JE. Exercise capacity and mortality among men referred for exercise
testing. N Engl J Med. 2002;346:793–801. [PubMed] [Google Scholar]
364. Nagy E, Janszky I, Eriksson-Berg M, Al-Khalili F, Schenck-Gustafsson K. The effects of exercise capacity and sedentary lifestyle on haemostasis
among middle-aged women with coronary heart disease. Thromb Haemost. 2008;100:899–904. [PubMed] [Google Scholar]
365. Nakanishi N, Takatorige T, Suzuki K. Daily life activity and risk of developing impaired fasting glucose or type
2 diabetes in middle-aged Japanese men. Diabetologia. 2004;47:1768–1775. [PubMed] [Google Scholar]
366. Narayan KM, Boyle JP, Thompson TJ, Sorensen SW, Williamson DF. Lifetime risk for diabetes mellitus in the United States. JAMA. 2003;290:1884–1890. [PubMed] [Google Scholar]
370. Nattiv A, Loucks AB, Manore MM, Sanborn CF, Sundgot-Borgen J, Warren MP. American College of Sports Medicine position stand. The female athlete
triad. Med Sci Sports Exerc. 2007;39:1867–1882. [PubMed] [Google Scholar]
371. Navasiolava NM, Dignat-George F, Sabatier F, Larina IM, Demiot C, Fortrat JO, Gauquelin-Koch G, Kozlovskaya IB, Custaud MA. Enforced physical inactivity increases endothelial microparticle levels in
healthy volunteers. Am J Physiol Heart Circ Physiol. 2010;299:H248–256. [PubMed] [Google Scholar]
372. Neeper SA, Gomez-Pinilla F, Choi J, Cotman C. Exercise and brain neurotrophins. Nature. 373:109–1995. [PubMed] [Google Scholar]
373. Neilson HK, Friedenreich CM, Brockton NT, Millikan RC. Physical activity and postmenopausal breast cancer: proposed biologic
mechanisms and areas for future research. Cancer Epidemiol Biomarkers Prev. 2009;18:11–27. [PubMed] [Google Scholar]
374. Nelson TL, Brandon DT, Wiggins SA, Whitfield KE. Genetic and environmental influences on body-fat measures among
African-American twins. Obes Res. 2002;10:733–739. [PubMed] [Google Scholar]
375. Nemoto K, Gen-no H, Masuki S, Okazaki K, Nose H. Effects of high-intensity interval walking training on physical fitness and
blood pressure in middle-aged and older people. Mayo Clin Proc. 2007;82:803–811. [PubMed] [Google Scholar]
376. Nesmith JD. Type 2 diabetes mellitus in children and adolescents. Pediatr Rev. 2001;22:147–152. [PubMed] [Google Scholar]
377. Nezer C, Collette C, Moreau L, Brouwers B, Kim JJ, Giuffra E, Buys N, Andersson L, Georges M. Haplotype sharing refines the location of an imprinted quantitative trait
locus with major effect on muscle mass to a 250-kb chromosome segment containing the
porcine IGF2 gene. Genetics. 2003;165:277–285. [PMC free article] [PubMed] [Google Scholar]
378. Nguyen QM, Srinivasan SR, Xu JH, Chen W, Berenson GS. Fasting plasma glucose levels within the normoglycemic range in childhood
as a predictor of prediabetes and type 2 diabetes in adulthood: the Bogalusa Heart
Study. Arch Pediatr Adolesc Med. 2010;164:124–128. [PubMed] [Google Scholar]
379. Nichol K, Deeny SP, Seif J, Camaclang K, Cotman CW. Exercise improves cognition and hippocampal plasticity in APOE epsilon4
mice. Alzheimers Dement. 2009;5:287–294. [PMC free article] [PubMed] [Google Scholar]
380. Nieman DC, Henson DA, Gusewitch G, Warren BJ, Dotson RC, Butterworth DE, Nehlsen-Cannarella SL. Physical activity and immune function in elderly women. Med Sci Sports Exerc. 1993;25:823–831. [PubMed] [Google Scholar]
381. Nieman DC, Johanssen LM, Lee JW. Infectious episodes in runners before and after a roadrace. J Sports Med Phys Fitness. 1989;29:289–296. [PubMed] [Google Scholar]
382. Nieman DC, Johanssen LM, Lee JW, Arabatzis K. Infectious episodes in runners before and after the Los Angeles
Marathon. J Sports Med Phys Fitness. 1990;30:316–328. [PubMed] [Google Scholar]
383. Nieman DC, Nehlsen-Cannarella SL, Markoff PA, Balk-Lamberton AJ, Yang H, Chritton DB, Lee JW, Arabatzis K. The effects of moderate exercise training on natural killer cells and acute
upper respiratory tract infections. Int J Sports Med. 1990;11:467–473. [PubMed] [Google Scholar]
384. Nybo L, Sundstrup E, Jakobsen MD, Mohr M, Hornstrup T, Simonsen L, Bulow J, Randers MB, Nielsen JJ, Aagaard P, Krustrup P. High-intensity training versus traditional exercise interventions for
promoting health. Med Sci Sports Exerc. 2010;42:1951–1958. [PubMed] [Google Scholar]
385. O’Keefe JH, Vogel R, Lavie CJ, Cordain L. Achieving Hunter-gatherer Fitness in the 21(st) Century: Back to the
Future. Am J Med. 2010;123:1082–1086. [PubMed] [Google Scholar]
386. Ogden CL, Carroll MD, Curtin LR, Lamb MM, Flegal KM. Prevalence of high body mass index in US children and adolescents,
2007–2008. JAMA. 2010;303:242–249. [PubMed] [Google Scholar]
387. Ogden CL, Yanovski SZ, Carroll MD, Flegal KM. The epidemiology of obesity. Gastroenterology. 2007;132:2087–2102. [PubMed] [Google Scholar]
388. Olin JW, Sealove BA. Peripheral artery disease: current insight into the disease and its
diagnosis and management. Mayo Clin Proc. 2010;85:678–692. [PMC free article] [PubMed] [Google Scholar]
389. Olsen RH, Krogh-Madsen R, Thomsen C, Booth FW, Pedersen BK. Metabolic responses to reduced daily steps in healthy nonexercising
men. JAMA. 2008;299:1261–1263. [PubMed] [Google Scholar]
390. Oppert JM, Nadeau A, Tremblay A, Despres JP, Theriault G, Bouchard C. Negative energy balance with exercise in identical twins: plasma glucose
and insulin responses. Am J Physiol. 1997;272:E248–254. [PubMed] [Google Scholar]
391. Oshida Y, Yamanouchi K, Hayamizu S, Nagasawa J, Ohsawa I, Sato Y. Effects of training and training cessation on insulin
action. Int J Sports Med. 1991;12:484–486. [PubMed] [Google Scholar]
392. Owen N, Healy GN, Matthews CE, Dunstan DW. Too much sitting: the population health science of sedentary
behavior. Exerc Sport Sci Rev. 2010;38:105–113. [PMC free article] [PubMed] [Google Scholar]
393. Owen N, Leslie E, Salmon J, Fotheringham MJ. Environmental determinants of physical activity and sedentary
behavior. Exerc Sport Sci Rev. 2000;28:153–158. [PubMed] [Google Scholar]
394. Ozcivici E, Luu YK, Adler B, Qin YX, Rubin J, Judex S, Rubin CT. Mechanical signals as anabolic agents in bone. Nat Rev Rheumatol. 2010;6:50–59. [PMC free article] [PubMed] [Google Scholar]
395. Paffenbarger RS, Jr., Hyde RT, Wing AL, Hsieh CC. Physical activity, all-cause mortality, and longevity of college
alumni. N Engl J Med. 1986;314:605–613. [PubMed] [Google Scholar]
396. Pagliari R, Peyrin L. Norepinephrine release in the rat frontal cortex under treadmill exercise:
a study with microdialysis. J Appl Physiol. 1995;78:2121–2130. [PubMed] [Google Scholar]
397. Pajonk FG, Wobrock T, Gruber O, Scherk H, Berner D, Kaizl I, Kierer A, Muller S, Oest M, Meyer T, Backens M, Schneider-Axmann T, Thornton AE, Honer WG, Falkai P. Hippocampal plasticity in response to exercise in
schizophrenia. Arch Gen Psychiatry. 67:133–143. [PubMed] [Google Scholar]
398. Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, Hu ZX, Lin J, Xiao JZ, Cao HB, Liu PA, Jiang XG, Jiang YY, Wang JP, Zheng H, Zhang H, Bennett PH, Howard BV. Effects of diet and exercise in preventing NIDDM in people with impaired
glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care. 1997;20:537–544. [PubMed] [Google Scholar]
399. Payton A. The impact of genetic research on our understanding of normal cognitive
ageing: 1995 to 2009. Neuropsychol Rev. 2009;19:451–477. [PubMed] [Google Scholar]
400. Peake J, Wilson G, Hordern M, Suzuki K, Yamaya K, Nosaka K, Mackinnon L, Coombes JS. Changes in neutrophil surface receptor expression, degranulation, and
respiratory burst activity after moderate- and high-intensity exercise. J Appl Physiol. 2004;97:612–618. [PubMed] [Google Scholar]
401. Peake JM. Exercise-induced alterations in neutrophil degranulation and respiratory
burst activity: possible mechanisms of action. Exerc Immunol Rev. 2002;8:49–100. [PubMed] [Google Scholar]
402. Pearson SJ, Young A, Macaluso A, Devito G, Nimmo MA, Cobbold M, Harridge SD. Muscle function in elite master weightlifters. Med Sci Sports Exerc. 2002;34:1199–1206. [PubMed] [Google Scholar]
403. Pedersen BK. The diseasome of physical inactivity–and the role of myokines in muscle–
fat cross talk. J Physiol. 2009;587:5559–5568. [PMC free article] [PubMed] [Google Scholar]
404. Pedersen BK. Muscles and their myokines. J Exp Biol. 2011;214:337–346. [PubMed] [Google Scholar]
405. Pekkanen J, Marti B, Nissinen A, Tuomilehto J, Punsar S, Karvonen MJ. Reduction of premature mortality by high physical activity: a 20-year
follow-up of middle-aged Finnish men. Lancet. 1987;1:1473–1477. [PubMed] [Google Scholar]
406. Perry IJ, Wannamethee SG, Walker MK, Thomson AG, Whincup PH, Shaper AG. Prospective study of risk factors for development of non-insulin dependent
diabetes in middle aged British men. BMJ. 1995;310:560–564. [PMC free article] [PubMed] [Google Scholar]
407. Perseghin G, Lattuada G, De Cobelli F, Ragogna F, Ntali G, Esposito A, Belloni E, Canu T, Terruzzi I, Scifo P, Del Maschio A, Luzi L. Habitual physical activity is associated with intrahepatic fat content in
humans. Diabetes Care. 2007;30:683–688. [PubMed] [Google Scholar]
408. Peters EM, Goetzsche JM, Grobbelaar B, Noakes TD. Vitamin C supplementation reduces the incidence of postrace symptoms of
upper-respiratory-tract infection in ultramarathon runners. Am J Clin Nutr. 1993;57:170–174. [PubMed] [Google Scholar]
409. Peters HP, De Vries WR, Vanberge-Henegouwen GP, Akkermans LM. Potential benefits and hazards of physical activity and exercise on the
gastrointestinal tract. Gut. 2001;48:435–439. [PMC free article] [PubMed] [Google Scholar]
410. Petersen RC, Jack CR, Jr., Xu YC, Waring SC, O’Brien PC, Smith GE, Ivnik RJ, Tangalos EG, Boeve BF, Kokmen E. Memory and MRI-based hippocampal volumes in aging and AD. Neurology. 2000;54:581–587. [PubMed] [Google Scholar]
411. Petrella JK, Kim JS, Mayhew DL, Cross JM, Bamman MM. Potent myofiber hypertrophy during resistance training in humans is
associated with satellite cell-mediated myonuclear addition: a cluster
analysis. J Appl Physiol. 2008;104:1736–1742. [PubMed] [Google Scholar]
413. Podewils LJ, Guallar E, Kuller LH, Fried LP, Lopez OL, Carlson M, Lyketsos CG. Physical activity, APOE genotype, and dementia risk: findings from the
Cardiovascular Health Cognition Study. Am J Epidemiol. 2005;161:639–651. [PubMed] [Google Scholar]
414. Poehlman ET, Tremblay A, Marcotte M, Perusse L, Theriault G, Bouchard C. Heredity and changes in body composition and adipose tissue metabolism
after short-term exercise-training. Eur J Appl Physiol Occup Physiol. 1987;56:398–402. [PubMed] [Google Scholar]
415. Poehlman ET, Tremblay A, Nadeau A, Dussault J, Theriault G, Bouchard C. Heredity and changes in hormones and metabolic rates with short-term
training. Am J Physiol. 1986;250:E711–717. [PubMed] [Google Scholar]
416. Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX, Eckel RH. Obesity and cardiovascular disease: pathophysiology, evaluation, and effect
of weight loss: an update of the 1997 American Heart Association Scientific Statement on
Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition,
Physical Activity, and Metabolism. Circulation. 2006;113:898–918. [PubMed] [Google Scholar]
417. Pontifex MB, Raine LB, Johnson CR, Chaddock L, Voss MW, Cohen NJ, Kramer AF, Hillman CH. Cardiorespiratory Fitness and the Flexible Modulation of Cognitive Control
in Preadolescent Children. J Cogn Neurosci. 2010;23:1332–1345. [PubMed] [Google Scholar]
418. Powers A. Diabetes Mellitus. In: Fauci AS KD, Braunwald E, Hauser SL, Longo DL, Losalzo J, editors. Harrison’s Principles of Internal Medicine. McGraw-Hill; New York: 2008. p. 2281. [Google Scholar]
419. Pritchard J, Despres JP, Gagnon J, Tchernof A, Nadeau A, Tremblay A, Bouchard C. Plasma adrenal, gonadal, and conjugated steroids following long-term
exercise-induced negative energy balance in identical twins. Metabolism. 1999;48:1120–1127. [PubMed] [Google Scholar]
420. Promrat K, Kleiner DE, Niemeier HM, Jackvony E, Kearns M, Wands JR, Fava JL, Wing RR. Randomized controlled trial testing the effects of weight loss on
nonalcoholic steatohepatitis. Hepatology. 2010;51:121–129. [PMC free article] [PubMed] [Google Scholar]
421. Prud’homme D, Bouchard C, Leblanc C, Landry F, Fontaine E. Sensitivity of maximal aerobic power to training is
genotype-dependent. Med Sci Sports Exerc. 1984;16:489–493. [PubMed] [Google Scholar]
422. Rampersaud E, Mitchell BD, Pollin TI, Fu M, Shen H, O’Connell JR, Ducharme JL, Hines S, Sack P, Naglieri R, Shuldiner AR, Snitker S. Physical activity and the association of common FTO gene variants with body
mass index and obesity. Arch Intern Med. 2008;168:1791–1797. [PMC free article] [PubMed] [Google Scholar]
423. Rasmussen P, Brassard P, Adser H, Pedersen MV, Leick L, Hart E, Secher NH, Pedersen BK, Pilegaard H. Evidence for a release of brain-derived neurotrophic factor from the brain
during exercise. Exp Physiol. 2009;94:1062–1069. [PubMed] [Google Scholar]
424. Rautava E, Lehtonen-Veromaa M, Kautiainen H, Kajander S, Heinonen OJ, Viikari J, Mottonen T. The reduction of physical activity reflects on the bone mass among young
females: a follow-up study of 142 adolescent girls. Osteoporos Int. 2007;18:915–922. [PubMed] [Google Scholar]
425. Reaven GM. The insulin resistance syndrome: definition and dietary approaches to
treatment. Annu Rev Nutr. 2005;25:391–406. [PubMed] [Google Scholar]
426. Rector RS, Rogers R, Ruebel M, Hinton PS. Participation in road cycling vs running is associated with lower bone
mineral density in men. Metabolism. 2008;57:226–232. [PubMed] [Google Scholar]
427. Rector RS, Rogers R, Ruebel M, Widzer MO, Hinton PS. Lean body mass and weight-bearing activity in the prediction of bone
mineral density in physically active men. J Strength Cond Res. 2009;23:427–435. [PubMed] [Google Scholar]
428. Rector RS, Thyfault JP, Laye MJ, Morris RT, Borengasser SJ, Uptergrove GM, Chakravarthy MV, Booth FW, Ibdah JA. Cessation of daily exercise dramatically alters precursors of hepatic
steatosis in Otsuka Long-Evans Tokushima Fatty (OLETF) rats. J Physiol. 2008;586:4241–4249. [PMC free article] [PubMed] [Google Scholar]
429. Rector RS, Thyfault JP, Morris RT, Laye MJ, Borengasser SJ, Booth FW, Ibdah JA. Daily exercise increases hepatic fatty acid oxidation and prevents
steatosis in Otsuka Long-Evans Tokushima Fatty rats. Am J Physiol Gastrointest Liver Physiol. 2008;294:G619–626. [PubMed] [Google Scholar]
430. Rector RS, Uptergrove GM, Borengasser SJ, Mikus CR, Morris EM, Naples SP, Laye MJ, Laughlin MH, Booth FW, Ibdah JA, Thyfault JP. Changes in skeletal muscle mitochondria in response to the development of
type 2 diabetes or prevention by daily wheel running in hyperphagic OLETF
rats. Am J Physiol Endocrinol Metab. 2010;298:E1179–1187. [PMC free article] [PubMed] [Google Scholar]
433. Ribeiro F, Alves AJ, Duarte JA, Oliveira J. Is exercise training an effective therapy targeting endothelial dysfunction
and vascular wall inflammation? Int J Cardiol. 2010;141:214–221. [PubMed] [Google Scholar]
434. Richter EA, Garetto LP, Goodman MN, Ruderman NB. Muscle glucose metabolism following exercise in the rat: increased
sensitivity to insulin. J Clin Invest. 1982;69:785–793. [PMC free article] [PubMed] [Google Scholar]
435. Richter EA, Ruderman NB. AMPK and the biochemistry of exercise: implications for human health and
disease. Biochem J. 2009;418:261–275. [PMC free article] [PubMed] [Google Scholar]
436. Ridderstrale M, Groop L. Genetic dissection of type 2 diabetes. Mol Cell Endocrinol. 2009;297:10–17. [PubMed] [Google Scholar]
437. Riddle RC, Donahue HJ. From streaming-potentials to shear stress: 25 years of bone cell
mechanotransduction. J Orthop Res. 2009;27:143–149. [PubMed] [Google Scholar]
438. Rizzoli R, Bianchi ML, Garabedian M, McKay HA, Moreno LA. Maximizing bone mineral mass gain during growth for the prevention of
fractures in the adolescents and the elderly. Bone. 2010;46:294–305. [PubMed] [Google Scholar]
439. Roberts WC. The Amish, body weight, and exercise. Am J Cardiol. 2004;94:1221. [PubMed] [Google Scholar]
440. Rodas G, Calvo M, Estruch A, Garrido E, Ercilla G, Arcas A, Segura R, Ventura JL. Heritability of running economy: a study made on twin
brothers. Eur J Appl Physiol Occup Physiol. 1998;77:511–516. [PubMed] [Google Scholar]
441. Rodriguez-Ojea A, Jimenez S, Berdasco A, Esquivel M. The nutrition transition in Cuba in the nineties: an
overview. Public Health Nutr. 2002;5:129–133. [PubMed] [Google Scholar]
442. Rogers CJ, Colbert LH, Greiner JW, Perkins SN, Hursting SD. Physical activity and cancer prevention : pathways and targets for
intervention. Sports Med. 2008;38:271–296. [PubMed] [Google Scholar]
443. Rogers MA, King DS, Hagberg JM, Ehsani AA, Holloszy JO. Effect of 10 days of physical inactivity on glucose tolerance in master
athletes. J Appl Physiol. 1990;68:1833–1837. [PubMed] [Google Scholar]
444. Rogers MA, Yamamoto C, King DS, Hagberg JM, Ehsani AA, Holloszy JO. Improvement in glucose tolerance after 1 wk of exercise in patients with
mild NIDDM. Diabetes Care. 1988;11:613–618. [PubMed] [Google Scholar]
445. Rolland Y, Abellan van Kan G, Vellas B. Healthy brain aging: role of exercise and physical activity. Clin Geriatr Med. 2010;26:75–87. [PubMed] [Google Scholar]
446. Ropponen A, Levalahti E, Videman T, Kaprio J, Battie MC. The role of genetics and environment in lifting force and isometric trunk
extensor endurance. Phys Ther. 2004;84:608–621. [PubMed] [Google Scholar]
447. Ross R, Dagnone D, Jones PJ, Smith H, Paddags A, Hudson R, Janssen I. Reduction in obesity and related comorbid conditions after diet-induced
weight loss or exerciseinduced weight loss in men. A randomized, controlled
trial. Ann Intern Med. 2000;133:92–103. [PubMed] [Google Scholar]
448. Rothon C, Edwards P, Bhui K, Viner RM, Taylor S, Stansfeld SA. Physical activity and depressive symptoms in adolescents: a prospective
study. BMC Med. 2010;8:32. [PMC free article] [PubMed] [Google Scholar]
449. Rubinstein E, Lavine JE, Schwimmer JB. Hepatic, cardiovascular, and endocrine outcomes of the histological
subphenotypes of nonalcoholic fatty liver disease. Semin Liver Dis. 2008;28:380–385. [PubMed] [Google Scholar]
450. Ruiz JR, Labayen I, Ortega FB, Legry V, Moreno LA, Dallongeville J, Martinez-Gomez D, Bokor S, Manios Y, Ciarapica D, Gottrand F, De Henauw S, Molnar D, Sjostrom M, Meirhaeghe A. Attenuation of the effect of the FTO rs9939609 polymorphism on total and
central body fat by physical activity in adolescents: the HELENA study. Arch Pediatr Adolesc Med. 164:328–333. [PubMed] [Google Scholar]
451. Ruiz JR, Sui X, Lobelo F, Morrow JR, Jr., Jackson AW, Sjostrom M, Blair SN. Association between muscular strength and mortality in men: prospective
cohort study. BMJ. 2008;337:a439. [PMC free article] [PubMed] [Google Scholar]
453. Saigal CS, Wessells H, Pace J, Schonlau M, Wilt TJ. Predictors and prevalence of erectile dysfunction in a racially diverse
population. Arch Intern Med. 2006;166:207–212. [PubMed] [Google Scholar]
454. Saltin B, Blomqvist G, Mitchell JH, Johnson RL, Jr., Wildenthal K, Chapman CB. Response to exercise after bed rest and after training. Circulation. 1968;38:VII1–78. [PubMed] [Google Scholar]
455. Samaras K, Kelly PJ, Chiano MN, Spector TD, Campbell LV. Genetic and environmental influences on total-body and central abdominal
fat: the effect of physical activity in female twins. Ann Intern Med. 1999;130:873–882. [PubMed] [Google Scholar]
456. Sambrook PN, MacGregor AJ, Spector TD. Genetic influences on cervical and lumbar disc degeneration: a magnetic
resonance imaging study in twins. Arthritis Rheum. 1999;42:366–372. [PubMed] [Google Scholar]
458. Savard R, Bouchard C. Genetic effects in the response of adipose tissue lipoprotein lipase
activity to prolonged exercise. A twin study. Int J Obes. 1990;14:771–777. [PubMed] [Google Scholar]
459. Saydah SH, Miret M, Sung J, Varas C, Gause D, Brancati FL. Postchallenge hyperglycemia and mortality in a national sample of U.S.
adults. Diabetes Care. 2001;24:1397–1402. [PubMed] [Google Scholar]
460. Schenk S, Horowitz JF. Acute exercise increases triglyceride synthesis in skeletal muscle and
prevents fatty acid-induced insulin resistance. J Clin Invest. 2007;117:1690–1698. [PMC free article] [PubMed] [Google Scholar]
461. Schoeller DA, Shay K, Kushner RF. How much physical activity is needed to minimize weight gain in previously
obese women? Am J Clin Nutr. 1997;66:551–556. [PubMed] [Google Scholar]
462. Schuit AJ, Feskens EJ, Launer LJ, Kromhout D. Physical activity and cognitive decline, the role of the apolipoprotein e4
allele. Med Sci Sports Exerc. 2001;33:772–777. [PubMed] [Google Scholar]
463. Schwab P, Klein RF. Nonpharmacological approaches to improve bone health and reduce
osteoporosis. Curr Opin Rheumatol. 2008;20:213–217. [PubMed] [Google Scholar]
464. Schwartz D, Collins F. Medicine. Environmental biology and human disease. Science. 2007;316:695–696. [PubMed] [Google Scholar]
466. Seider MJ, Nicholson WF, Booth FW. Insulin resistance for glucose metabolism in disused soleus muscle of
mice. Am J Physiol. 1982;242:E12–18. [PubMed] [Google Scholar]
467. Seki Y, Berggren JR, Houmard JA, Charron MJ. Glucose transporter expression in skeletal muscle of endurance-trained
individuals. Med Sci Sports Exerc. 2006;38:1088–1092. [PubMed] [Google Scholar]
468. Selby JV, Newman B, Quesenberry CP, Jr., Fabsitz RR, Carmelli D, Meaney FJ, Slemenda C. Genetic and behavioral influences on body fat distribution. Int J Obes. 1990;14:593–602. [PubMed] [Google Scholar]
469. Sharma NK, Ryals JM, Gajewski BJ, Wright DE. Aerobic exercise alters analgesia and neurotrophin-3 synthesis in an animal
model of chronic widespread pain. Phys Ther. 2010;90:714–725. [PMC free article] [PubMed] [Google Scholar]
470. Shima K, Shi K, Sano T, Iwami T, Mizuno A, Noma Y. Is exercise training effective in preventing diabetes mellitus in the
Otsuka-Long-Evans-Tokushima fatty rat, a model of spontaneous non-insulin-dependent
diabetes mellitus? Metabolism. 1993;42:971–977. [PubMed] [Google Scholar]
471. Shirazian T, Raghavan S. Obesity and pregnancy: implications and management strategies for
providers. Mt Sinai J Med. 2009;76:539–545. [PubMed] [Google Scholar]
472. Shneider BL, Gonzalez-Peralta R, Roberts EA. Controversies in the management of pediatric liver disease: Hepatitis B, C
and NAFLD: Summary of a single topic conference. Hepatology. 2006;44:1344–1354. [PubMed] [Google Scholar]
473. Sibley BA EJ. The relationship between physical activity and cognition in children: a
meta-analysis. Pediatr Exerc Sci. 2003;15:243–256. [Google Scholar]
474. Simoneau JA, Lortie G, Boulay MR, Marcotte M, Thibault MC, Bouchard C. Inheritance of human skeletal muscle and anaerobic capacity adaptation to
high-intensity intermittent training. Int J Sports Med. 1986;7:167–171. [PubMed] [Google Scholar]
475. Simonen RL, Videman T, Battie MC, Gibbons LE. The effect of lifelong exercise on psychomotor reaction time: a study of 38
pairs of male monozygotic twins. Med Sci Sports Exerc. 1998;30:1445–1450. [PubMed] [Google Scholar]
476. Simonen RL, Videman T, Kaprio J, Levalahti E, Battie MC. Factors associated with exercise lifestyle–a study of monozygotic
twins. Int J Sports Med. 2003;24:499–505. [PubMed] [Google Scholar]
477. Simopoulos AP. The Hippocratic concept of positive health in the 5th century BC and in the
new millennium. World Rev Nutr Diet. 2001;89:1–4. [PubMed] [Google Scholar]
478. Sisson SB, Katzmarzyk PT, Earnest CP, Bouchard C, Blair SN, Church TS. Volume of exercise and fitness nonresponse in sedentary, postmenopausal
women. Med Sci Sports Exerc. 2009;41:539–545. [PMC free article] [PubMed] [Google Scholar]
479. Slentz CA, Aiken LB, Houmard JA, Bales CW, Johnson JL, Tanner CJ, Duscha BD, Kraus WE. Inactivity, exercise, and visceral fat. STRRIDE: a randomized, controlled
study of exercise intensity and amount. J Appl Physiol. 2005;99:1613–1618. [PubMed] [Google Scholar]
480. Slentz CA, Duscha BD, Johnson JL, Ketchum K, Aiken LB, Samsa GP, Houmard JA, Bales CW, Kraus WE. Effects of the amount of exercise on body weight, body composition, and
measures of central obesity: STRRIDE–a randomized controlled study. Arch Intern Med. 2004;164:31–39. [PubMed] [Google Scholar]
481. Slentz CA, Houmard JA, Kraus WE. Exercise, abdominal obesity, skeletal muscle, and metabolic risk: evidence
for a dose response. Obesity (Silver Spring) 2009;17(Suppl 3):S27–33. [PMC free article] [PubMed] [Google Scholar]
482. Slentz CA, Houmard JA, Kraus WE. Modest exercise prevents the progressive disease associated with physical
inactivity. Exerc Sport Sci Rev. 2007;35:18–23. [PubMed] [Google Scholar]
483. Slentz CA, Tanner CJ, Bateman LA, Durheim MT, Huffman KM, Houmard JA, Kraus WE. Effects of exercise training intensity on pancreatic beta-cell
function. Diabetes Care. 2009;32:1807–1811. [PMC free article] [PubMed] [Google Scholar]
485. Obesity and its Relation to Mortality and Morbidity Costs. 2010. Society of Actuaries. [Google Scholar]
486. Solomon TP, Haus JM, Kelly KR, Cook MD, Riccardi M, Rocco M, Kashyap SR, Barkoukis H, Kirwan JP. Randomized trial on the effects of a 7-d low-glycemic diet and exercise
intervention on insulin resistance in older obese humans. Am J Clin Nutr. 2009;90:1222–1229. [PMC free article] [PubMed] [Google Scholar]
487. Spence L, Brown WJ, Pyne DB, Nissen MD, Sloots TP, McCormack JG, Locke AS, Fricker PA. Incidence, etiology, and symptomatology of upper respiratory illness in
elite athletes. Med Sci Sports Exerc. 2007;39:577–586. [PubMed] [Google Scholar]
488. St George A, Bauman A, Johnston A, Farrell G, Chey T, George J. Independent effects of physical activity in patients with nonalcoholic
fatty liver disease. Hepatology. 2009;50:68–76. [PubMed] [Google Scholar]
489. Stamatakis E, Hamer M, Dunstan DW. Screen-based entertainment time, all-cause mortality, and cardiovascular
events population-based study with ongoing mortality and hospital events
follow-up. J Am Coll Cardiol. 2011;57:292–299. [PubMed] [Google Scholar]
490. Steensberg A, Keller C, Starkie RL, Osada T, Febbraio MA, Pedersen BK. IL-6 and TNF-alpha expression in, and release from, contracting human
skeletal muscle. Am J Physiol Endocrinol Metab. 2002;283:E1272–1278. [PubMed] [Google Scholar]
491. Stein TP, Bolster DR. Insights into muscle atrophy and recovery pathway based on genetic
models. Curr Opin Clin Nutr Metab Care. 2006;9:395–402. [PubMed] [Google Scholar]
492. Strate LL, Liu YL, Aldoori WH, Giovannucci EL. Physical activity decreases diverticular complications. Am J Gastroenterol. 2009;104:1221–1230. [PMC free article] [PubMed] [Google Scholar]
493. Strohle A, Hofler M, Pfister H, Muller AG, Hoyer J, Wittchen HU, Lieb R. Physical activity and prevalence and incidence of mental disorders in
adolescents and young adults. Psychol Med. 2007;37:1657–1666. [PubMed] [Google Scholar]
494. Strong WB, Malina RM, Blimkie CJ, Daniels SR, Dishman RK, Gutin B, Hergenroeder AC, Must A, Nixon PA, Pivarnik JM, Rowland T, Trost S, Trudeau F. Evidence based physical activity for school-age youth. J Pediatr. 2005;146:732–737. [PubMed] [Google Scholar]
495. Stuart CA, Shangraw RE, Prince MJ, Peters EJ, Wolfe RR. Bed-rest-induced insulin resistance occurs primarily in
muscle. Metabolism. 1988;37:802–806. [PubMed] [Google Scholar]
496. Stubbe JH, Boomsma DI, De Geus EJ. Sports participation during adolescence: a shift from environmental to
genetic factors. Med Sci Sports Exerc. 2005;37:563–570. [PubMed] [Google Scholar]
497. Stubbe JH, Boomsma DI, Vink JM, Cornes BK, Martin NG, Skytthe A, Kyvik KO, Rose RJ, Kujala UM, Kaprio J, Harris JR, Pedersen NL, Hunkin J, Spector TD, de Geus EJ. Genetic influences on exercise participation in 37,051 twin pairs from
seven countries. PLoS ONE. 2006;1:e22. [PMC free article] [PubMed] [Google Scholar]
498. Stubbe JH, de Moor MH, Boomsma DI, de Geus EJ. The association between exercise participation and well-being: a co-twin
study. Prev Med. 2007;44:148–152. [PubMed] [Google Scholar]
499. Sui X, Laditka JN, Hardin JW, Blair SN. Estimated functional capacity predicts mortality in older
adults. J Am Geriatr Soc. 2007;55:1940–1947. [PMC free article] [PubMed] [Google Scholar]
500. Sun SS, Liang R, Huang TT, Daniels SR, Arslanian S, Liu K, Grave GD, Siervogel RM. Childhood obesity predicts adult metabolic syndrome: the Fels Longitudinal
Study. J Pediatr. 2008;152:191–200. [PMC free article] [PubMed] [Google Scholar]
501. Suvorava T, Lauer N, Kojda G. Physical inactivity causes endothelial dysfunction in healthy young
mice. J Am Coll Cardiol. 2004;44:1320–1327. [PubMed] [Google Scholar]
502. Swain RA, Harris AB, Wiener EC, Dutka MV, Morris HD, Theien BE, Konda S, Engberg K, Lauterbur PC, Greenough WT. Prolonged exercise induces angiogenesis and increases cerebral blood volume
in primary motor cortex of the rat. Neuroscience. 2003;117:1037–1046. [PubMed] [Google Scholar]
503. Tanaka H, Seals DR. Invited Review: Dynamic exercise performance in Masters athletes: insight
into the effects of primary human aging on physiological functional
capacity. J Appl Physiol. 2003;95:2152–2162. [PubMed] [Google Scholar]
504. Tfayli H, Lee S, Arslanian S. Declining beta-cell function relative to insulin sensitivity with
increasing fasting glucose levels in the nondiabetic range in children. Diabetes Care. 2010;33:2024–2030. [PMC free article] [PubMed] [Google Scholar]
505. Thibault MC, Simoneau JA, Cote C, Boulay MR, Lagasse P, Marcotte M, Bouchard C. Inheritance of human muscle enzyme adaptation to isokinetic strength
training. Hum Hered. 1986;36:341–347. [PubMed] [Google Scholar]
506. Thijssen DH, Maiorana AJ, O’Driscoll G, Cable NT, Hopman MT, Green DJ. Impact of inactivity and exercise on the vasculature in
humans. Eur J Appl Physiol. 2010;108:845–875. [PMC free article] [PubMed] [Google Scholar]
507. Thomason DB, Biggs RB, Booth FW. Protein metabolism and beta-myosin heavy-chain mRNA in unweighted soleus
muscle. Am J Physiol. 1989;257:R300–305. [PubMed] [Google Scholar]
508. Thomason DB, Booth FW. Atrophy of the soleus muscle by hindlimb unweighting. J Appl Physiol. 1990;68:1–12. [PubMed] [Google Scholar]
509. Thompson HJ, Jiang W, Zhu Z. Candidate mechanisms accounting for effects of physical activity on breast
carcinogenesis. IUBMB Life. 2009;61:895–901. [PMC free article] [PubMed] [Google Scholar]
510. Thomson RL, Buckley JD, Brinkworth GD. Obes Rev Epub ahead of print. 2011. Exercise for the treatment and management of overweight women with
polycystic ovary syndrome: a review of the literature. [PubMed] [Google Scholar]
511. Thyfault JP. Setting the stage: possible mechanisms by which acute contraction restores
insulin sensitivity in muscle. Am J Physiol Regul Integr Comp Physiol. 2008;294:R1103–1110. [PubMed] [Google Scholar]
512. Thyfault JP, Cree MG, Tapscott EB, Bell JA, Koves TR, Ilkayeva O, Wolfe RR, Dohm GL, Muoio DM. Metabolic profiling of muscle contraction in lean compared with obese
rodents. Am J Physiol Regul Integr Comp Physiol. 2010;299:R926–934. [PMC free article] [PubMed] [Google Scholar]
513. Thyfault JP, Cree MG, Zheng D, Zwetsloot JJ, Tapscott EB, Koves TR, Ilkayeva O, Wolfe RR, Muoio DM, Dohm GL. Contraction of insulin-resistant muscle normalizes insulin action in
association with increased mitochondrial activity and fatty acid
catabolism. Am J Physiol Cell Physiol. 2007;292:C729–739. [PubMed] [Google Scholar]
514. Tiainen K, Sipila S, Alen M, Heikkinen E, Kaprio J, Koskenvuo M, Tolvanen A, Pajala S, Rantanen T. Shared genetic and environmental effects on strength and power in older
female twins. Med Sci Sports Exerc. 2005;37:72–78. [PubMed] [Google Scholar]
515. Tiainen K, Sipila S, Kauppinen M, Kaprio J, Rantanen T. Genetic and environmental effects on isometric muscle strength and leg
extensor power followed up for three years among older female twins. J Appl Physiol. 2009;106:1604–1610. [PubMed] [Google Scholar]
516. Timmons JA. Commentary on viewpoint: Perspective on the future use of genomics in
exercise prescription. J Appl Physiol. 2008;104:1250. [PubMed] [Google Scholar]
517. Timmons JA, Knudsen S, Rankinen T, Koch LG, Sarzynski M, Jensen T, Keller P, Scheele C, Vollaard NB, Nielsen S, Akerstrom T, MacDougald OA, Jansson E, Greenhaff PL, Tarnopolsky MA, van Loon LJ, Pedersen BK, Sundberg CJ, Wahlestedt C, Britton SL, Bouchard C. Using molecular classification to predict gains in maximal aerobic capacity
following endurance exercise training in humans. J Appl Physiol. 108:1487–1496. [PMC free article] [PubMed] [Google Scholar]
518. Tiniakos DG, Vos MB, Brunt EM. Nonalcoholic fatty liver disease: pathology and
pathogenesis. Annu Rev Pathol. 2010;5:145–171. [PubMed] [Google Scholar]
519. Tipton CM. Susruta of India, an unrecognized contributor to the history of exercise
physiology. J Appl Physiol. 2008;104:1553–1556. [PubMed] [Google Scholar]
520. Tomporowski PD, Davis CL, Miller PH, Naglieri JA. Exercise and Children’s Intelligence, Cognition, and Academic
Achievement. Educ Psychol Rev. 2008;20:111–131. [PMC free article] [PubMed] [Google Scholar]
521. Trejo JL, Carro E, Torres-Aleman I. Circulating insulin-like growth factor I mediates exercise-induced
increases in the number of new neurons in the adult hippocampus. J Neurosci. 2001;21:1628–1634. [PMC free article] [PubMed] [Google Scholar]
522. Tremblay A, Poehlman E, Nadeau A, Perusse L, Bouchard C. Is the response of plasma glucose and insulin to short-term
exercise-training genetically determined? Horm Metab Res. 1987;19:65–67. [PubMed] [Google Scholar]
523. Tremblay A, Poehlman ET, Despres JP, Theriault G, Danforth E, Bouchard C. Endurance training with constant energy intake in identical twins: changes
over time in energy expenditure and related hormones. Metabolism. 1997;46:499–503. [PubMed] [Google Scholar]
524. Tremblay A, Poehlman ET, Nadeau A, Dussault J, Bouchard C. Heredity and overfeeding-induced changes in submaximal exercise
VO2. J Appl Physiol. 1987;62:539–544. [PubMed] [Google Scholar]
525. Tremblay MS, Esliger DW, Copeland JL, Barnes JD, Bassett DR. Moving forward by looking back: lessons learned from long-lost
lifestyles. Appl Physiol Nutr Metab. 2008;33:836–842. [PubMed] [Google Scholar]
526. Tresierras MA, Balady GJ. Resistance training in the treatment of diabetes and obesity: mechanisms
and outcomes. J Cardiopulm Rehabil Prev. 2009;29:67–75. [PubMed] [Google Scholar]
527. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by
accelerometer. Med Sci Sports Exerc. 2008;40:181–188. [PubMed] [Google Scholar]
528. Tsunoda N, Maruyama K, Cooke DW, Lane DM, Ezaki O. Localization of exerciseand denervation-responsive elements in the mouse
GLUT4 gene. Biochem Biophys Res Commun. 2000;267:744–751. [PubMed] [Google Scholar]
529. Tucker KR, Seider MJ, Booth FW. Protein synthesis rates in atrophied gastrocnemius muscles after limb
immobilization. J Appl Physiol. 1981;51:73–77. [PubMed] [Google Scholar]
530. Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ilanne-Parikka P, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M, Salminen V, Uusitupa M. Prevention of type 2 diabetes mellitus by changes in lifestyle among
subjects with impaired glucose tolerance. N Engl J Med. 2001;344:1343–1350. [PubMed] [Google Scholar]
534. Van Langendonck L, Claessens AL, Vlietinck R, Derom C, Beunen G. Influence of weight-bearing exercises on bone acquisition in prepubertal
monozygotic female twins: a randomized controlled prospective study. Calcif Tissue Int. 2003;72:666–674. [PubMed] [Google Scholar]
535. van Praag H, Kempermann G, Gage FH. Running increases cell proliferation and neurogenesis in the adult mouse
dentate gyrus. Nat Neurosci. 1999;2:266–270. [PubMed] [Google Scholar]
536. van Praag H, Lucero MJ, Yeo GW, Stecker K, Heivand N, Zhao C, Yip E, Afanador M, Schroeter H, Hammerstone J, Gage FH. Plant-derived flavanol (−)epicatechin enhances angiogenesis and
retention of spatial memory in mice. J Neurosci. 2007;27:5869–5878. [PMC free article] [PubMed] [Google Scholar]
537. van Uffelen JG, Wong J, Chau JY, van der Ploeg HP, Riphagen I, Gilson ND, Burton NW, Healy GN, Thorp AA, Clark BK, Gardiner PA, Dunstan DW, Bauman A, Owen N, Brown WJ. Occupational sitting and health risks: a systematic review. Am J Prev Med. 2010;39:379–388. [PubMed] [Google Scholar]
538. Vasuta C, Caunt C, James R, Samadi S, Schibuk E, Kannangara T, Titterness AK, Christie BR. Effects of exercise on NMDA receptor subunit contributions to bidirectional
synaptic plasticity in the mouse dentate gyrus. Hippocampus. 2007;17:1201–1208. [PubMed] [Google Scholar]
539. Venables MC, Jeukendrup AE. Physical inactivity and obesity: links with insulin resistance and type 2
diabetes mellitus. Diabetes Metab Res Rev. 2009;25(Suppl 1):S18–23. [PubMed] [Google Scholar]
540. Vernikos J, Schneider VS. Space, gravity and the physiology of aging: parallel or convergent
disciplines? A mini-review. Gerontology. 2010;56:157–166. [PubMed] [Google Scholar]
541. Videman T, Batti MC, Gibbons LE, Vanninen E, Kaprio J, Koskenvuo M. The roles of adulthood behavioural factors and familial influences in bone
density among men. Ann Med. 2002;34:434–443. [PubMed] [Google Scholar]
542. Videman T, Battie MC, Gibbons LE, Manninen H, Gill K, Fisher LD, Koskenvuo M. Lifetime exercise and disk degeneration: an MRI study of monozygotic
twins. Med Sci Sports Exerc. 1997;29:1350–1356. [PubMed] [Google Scholar]
543. Vimaleswaran KS, Li S, Zhao JH, Luan J, Bingham SA, Khaw KT, Ekelund U, Wareham NJ, Loos RJ. Physical activity attenuates the body mass index-increasing influence of
genetic variation in the FTO gene. Am J Clin Nutr. 2009;90:425–428. [PubMed] [Google Scholar]
544. Voss MW, Prakash RS, Erickson KI, Basak C, Chaddock L, Kim JS, Alves H, Heo S, Szabo AN, White SM, Wojcicki TR, Mailey EL, Gothe N, Olson EA, McAuley E, Kramer AF. Plasticity of brain networks in a randomized intervention trial of exercise
training in older adults. Front Aging Neurosci. 2010;2 [PMC free article] [PubMed] [Google Scholar]
545. Waller K, Kaprio J, Kujala UM. Associations between long-term physical activity, waist circumference and
weight gain: a 30-year longitudinal twin study. Int J Obes (Lond) 2008;32:353–361. [PubMed] [Google Scholar]
546. Waller K, Kujala UM, Rantanen T, Kauppinen M, Silventoinen K, Koskenvuo M, Kaprio J. Physical activity, morbidity and mortality in twins: a 24-year prospective
follow-up. Eur J Epidemiol. 2010;25:731–739. [PubMed] [Google Scholar]
547. Walters WR, Renner KJ, Summers CH, Watt ML, Forster GL, Koch LG, Britton SL, Swallow JG. Selection for intrinsic endurance modifies endocrine stress
responsiveness. Brain Res. 2010;1357:53–61. [PMC free article] [PubMed] [Google Scholar]
548. Washington RL. Metabolic syndrome—no longer an adult only disease. Journal of Pediatrics. 2008;152 [Google Scholar]
549. Watenpaugh DE. The role of sleep dysfunction in physical inactivity and its relationship
to obesity. Curr Sports Med Rep. 2009;8:331–338. [PubMed] [Google Scholar]
550. Watson PA, Stein JP, Booth FW. Changes in actin synthesis and alpha-actin-mRNA content in rat muscle
during immobilization. Am J Physiol. 1984;247:C39–44. [PubMed] [Google Scholar]
551. Saunders WB. Dorland’s Illustrated Medical Dictionary. Philadelphia: 1974. [Google Scholar]
552. Weinstein AR, Sesso HD. Joint effects of physical activity and body weight on diabetes and
cardiovascular disease. Exerc Sport Sci Rev. 2006;34:10–15. [PubMed] [Google Scholar]
553. Weinstein AR, Sesso HD, Lee IM, Rexrode KM, Cook NR, Manson JE, Buring JE, Gaziano JM. The joint effects of physical activity and body mass index on coronary
heart disease risk in women. Arch Intern Med. 2008;168:884–890. [PubMed] [Google Scholar]
554. Westerterp KR. Physical activity, food intake, and body weight regulation: insights from
doubly labeled water studies. Nutr Rev. 2010;68:148–154. [PubMed] [Google Scholar]
555. Westerterp KR, Speakman JR. Physical activity energy expenditure has not declined since the 1980s and
matches energy expenditures of wild mammals. Int J Obes (Lond) 2008;32:1256–1263. [PubMed] [Google Scholar]
556. Weuve J, Kang JH, Manson JE, Breteler MM, Ware JH, Grodstein F. Physical activity, including walking, and cognitive function in older
women. JAMA. 2004;292:1454–1461. [PubMed] [Google Scholar]
557. White JR, Case DA, McWhirter D, Mattison AM. Enhanced sexual behavior in exercising men. Arch Sex Behav. 1990;19:193–209. [PubMed] [Google Scholar]
558. White SL, Dunstan DW, Polkinghorne KR, Atkins RC, Cass A, Chadban SJ. Physical inactivity and chronic kidney disease in Australian adults: The
AusDiab study. Nutr Metab Cardiovasc Dis. 2010;21:104–112. [PubMed] [Google Scholar]
559. Widenfalk J, Olson L, Thoren P. Deprived of habitual running, rats downregulate BDNF and TrkB messages in
the brain. Neurosci Res. 1999;34:125–132. [PubMed] [Google Scholar]
560. Wijndaele K, Duvigneaud N, Matton L, Duquet W, Delecluse C, Thomis M, Beunen G, Lefevre J, Philippaerts RM. Sedentary behaviour, physical activity and a continuous metabolic syndrome
risk score in adults. Eur J Clin Nutr. 2009;63:421–429. [PubMed] [Google Scholar]
561. Williams D, Kuipers A, Mukai C, Thirsk R. Acclimation during space flight: effects on human
physiology. CMAJ. 2009;180:1317–1323. [PMC free article] [PubMed] [Google Scholar]
562. Williams PT. Incident diverticular disease is inversely related to vigorous physical
activity. Med Sci Sports Exerc. 2009;41:1042–1047. [PMC free article] [PubMed] [Google Scholar]
563. Williams PT, Blanche PJ, Krauss RM. Behavioral versus genetic correlates of lipoproteins and adiposity in
identical twins discordant for exercise. Circulation. 2005;112:350–356. [PubMed] [Google Scholar]
564. Williams PT, Blanche PJ, Rawlings R, Krauss RM. Concordant lipoprotein and weight responses to dietary fat change in
identical twins with divergent exercise levels 1. Am J Clin Nutr. 2005;82:181–187. [PubMed] [Google Scholar]
565. Wilson NC, Mumpower JL. Automated evaluation of goal-attainment ratings. Hosp Community Psychiatry. 1975;26:163–164. [PubMed] [Google Scholar]
566. Wilund KR, Feeney LA, Tomayko EJ, Chung HR, Kim K. Endurance exercise training reduces gallstone development in
mice. J Appl Physiol. 2008;104:761–765. [PubMed] [Google Scholar]
567. Winder WW, Hardie DG. Inactivation of acetyl-CoA carboxylase and activation of AMP-activated
protein kinase in muscle during exercise. Am J Physiol. 1996;270:E299–304. [PubMed] [Google Scholar]
568. Winder WW, Thomson DM. Cellular energy sensing and signaling by AMP-activated protein
kinase. Cell Biochem Biophys. 2007;47:332–347. [PubMed] [Google Scholar]
569. Wisloff U, Najjar SM, Ellingsen O, Haram PM, Swoap S, Al-Share Q, Fernstrom M, Rezaei K, Lee SJ, Koch LG, Britton SL. Cardiovascular risk factors emerge after artificial selection for low
aerobic capacity. Science. 2005;307:418–420. [PubMed] [Google Scholar]
570. Witkowski S, Spangenburg EE. Reduced physical activity and the retired athlete: a dangerous
combination? Br J Sports Med. 2008;42:952–953. [PubMed] [Google Scholar]
571. Wolff E, Strohle A. Causal associations of physical activity/exercise and symptoms of
depression and anxiety. Arch Gen Psychiatry. 2010;67:540–541. [PubMed] [Google Scholar]
572. Wolff I, van Croonenborg JJ, Kemper HC, Kostense PJ, Twisk JW. The effect of exercise training programs on bone mass: a meta-analysis of
published controlled trials in pre- and postmenopausal women. Osteoporos Int. 1999;9:1–12. [PubMed] [Google Scholar]
573. Wyatt HR, Peters JC, Reed GW, Barry M, Hill JO. A Colorado statewide survey of walking and its relation to excessive
weight. Med Sci Sports Exerc. 2005;37:724–730. [PubMed] [Google Scholar]
574. Yaffe K, Barnes D, Nevitt M, Lui LY, Covinsky K. A prospective study of physical activity and cognitive decline in elderly
women: women who walk. Arch Intern Med. 2001;161:1703–1708. [PubMed] [Google Scholar]
575. Yaffe K, Blackwell T, Gore R, Sands L, Reus V, Browner WS. Depressive symptoms and cognitive decline in nondemented elderly women: a
prospective study. Arch Gen Psychiatry. 1999;56:425–430. [PubMed] [Google Scholar]
576. Yang W, Lu J, Weng J, Jia W, Ji L, Xiao J, Shan Z, Liu J, Tian H, Ji Q, Zhu D, Ge J, Lin L, Chen L, Guo X, Zhao Z, Li Q, Zhou Z, Shan G, He J. Prevalence of diabetes among men and women in China. N Engl J Med. 2010;362:1090–1101. [PubMed] [Google Scholar]
577. Young D, Hopper JL, Nowson CA, Green RM, Sherwin AJ, Kaymakci B, Smid M, Guest CS, Larkins RG, Wark JD. Determinants of bone mass in 10- to 26-year-old females: a twin
study. J Bone Miner Res. 1995;10:558–567. [PubMed] [Google Scholar]
578. Zelber-Sagi S, Nitzan-Kaluski D, Goldsmith R, Webb M, Zvibel I, Goldiner I, Blendis L, Halpern Z, Oren R. Role of leisure-time physical activity in nonalcoholic fatty liver disease:
a population-based study. Hepatology. 2008;48:1791–1798. [PubMed] [Google Scholar]
579. Zimmet P, Alberti KG, Shaw J. Global and societal implications of the diabetes epidemic. Nature. 2001;414:782–787. [PubMed] [Google Scholar]

Source link

Leave a Comment