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Hindawi Publishing Corporation
Evidence-Based Complementary and Alternative Medicine
Volume 2012, Article ID 983258, 10 pages
doi:10.1155/2012/983258
Research Article
Frequency of Yoga Practice Predicts Health: Results of
a National Survey of Yoga Practitioners
Alyson Ross,1Erika Friedmann,1Margaret Bevans,2and Sue Thomas1
1University of Maryland School of Nursing, 655 West Lombard Street, Baltimore, MD 21201, USA
2National Institutes of Health Clinical Center, 10 Center Drive, Room 2B13, MSC 1151, Bethesda, MD 20892, USA
Correspondence should be addressed to Alyson Ross, alyross1@verizon.net
Received 22 April 2012; Accepted 20 June 2012
Academic Editor: Sat Bir S. Khalsa
Copyright © 2012 Alyson Ross et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background. Yoga shows promise as a therapeutic intervention, but relationships between yoga practice and health are
underexplored. Purpose. To examine the relationship between yoga practice and health (subjective well-being, diet, BMI, smoking,
alcohol/caffeine consumption, sleep, fatigue, social support, mindfulness, and physical activity). Methods. Cross-sectional,
anonymous internet surveys distributed to 4307 randomly selected from 18,160 individuals at 15 US Iyengar yoga studios; 1045
(24.3%) surveys completed. Results. Mean age 51.7 (±11.7) years; 84.2% female. Frequency of home practice favorably predicted
(P<.001): mindfulness, subjective well-being, BMI, fruit and vegetable consumption, vegetarian status, sleep, and fatigue. Each
componentofyogapractice(different categories of physical poses, breath work, meditation, philosophy study) predicted at least
1 health outcome (P<.05). Conclusions. Home practice of yoga predicted health better than years of practice or class frequency.
Different physical poses and yoga techniques may have unique health benefits.
1. Introduction
Three out of every four dollars in health care are spent
on treatment of chronic, lifestyle-related health conditions
including obesity, type 2 diabetes, cardiovascular disease
(CVD), and cancer [1]. These conditions are associated
with a number of modifiable health behaviors including
diet [2,3], physical activity [4–6], cigarette smoking [7,8],
and excessive alcohol consumption [9,10]. Poor mental
health [11], low social support [12,13], and poor sleep
[14] are also factors that contribute to morbidity and
mortality.
Making even small, positive changes in health behaviors
significantly improves mortality rates [15], and simultane-
ously changing multiple health behaviors results in further
reductions in morbidity and mortality [16,17]. While the
answer to America’s health crisis appears clear, permanently
improving health behaviors has proven to be elusive.
Yoga, an ancient discipline that uses a combination
of practices including physical poses, breath work, and
meditation, is defined by Patanjali in the second yoga sutra
as “the stilling of the changing states of the mind [18].” It
has recently shown promise as an intervention targeting a
number of outcomes associated with lifestyle-related health
conditions including cardiovascular disease [19], metabolic
syndrome [20], diabetes [21], and cancer [22]. While aerobic
exercise long has been a valuable tool in combating these
health conditions, a review of clinical trials comparing
exercise to yoga found yoga to be equal or superior to aerobic
exercise in improving a number of outcomes associated with
chronic health conditions [23].
One mechanism that would explain the effectiveness
of yoga interventions compared with exercise interventions
is that, in addition to the benefits of increased physical
activity associated with the physical practice of yoga poses,
yoga appears to downregulate the Hypothalamic-Pituitary-
Adrenal (HPA) axis and the Sympathetic Nervous System
(SNS) response to stress, possibly via direct vagal stimulation
[20]. Repeated firing of the HPA axis and SNS can lead to
dysregulation of the system and ultimately diseases such as
2 Evidence-Based Complementary and Alternative Medicine
obesity, diabetes, autoimmune disorders, depression, sub-
stance abuse, and cardiovascular disease [24,25]. Numerous
studies have shown yoga to have an immediate download
effect on both the SNS/HPA axis response to stress by
decreasing cortisol [26,27] and blood glucose [28,29], as
well as norepinephrine and epinephrine levels [30]. Yoga
significantly decreases heart rate, systolic and diastolic blood
pressure [30–32], and inflammation [33], and yoga increases
levels of Immunoglobulin A [34] and Natural Killer Cells
[35]. In addition to the immediate SNS and HPA-axis effects,
yoga improves outcomes associated with chronic SNS/HPA-
axis activation: blood cholesterol [36–38]; body composition
including: BMI [39], body weight [36,37,40], and waist
circumference [29]; fatigue [41,42]; and sleep in healthy and
diseased populations [43].
While this evidence is promising, the relationship be-
tween yoga practice and positive changes in health behaviors
remains unclear. Only three studies were found examining
relationships between yoga practice and aspects of health
in individuals who practice yoga [40,44,45]. These studies
contributed valuable evidence that there may be a favorable
relationship between regular yoga practice and BMI [44,45],
diet [45], and weight maintenance [40]. However, these
studies looked only at yoga practice in general and did not
examine the relative contributions of the different aspects of
yoga practice.
This also appears to be the case in many clinical trials
involving yoga, as studies frequently focus either exclusively
on interventions using only physical poses or breath work,
or they utilize a combination of different aspects of yoga
practice (including vigorous physical poses, gentle restorative
poses, breath work, and meditation) without examining the
relative contributions of the individual aspects. This creates
two problems when interpreting the results. First, when yoga
is taught according to classical texts such as the Yoga Sutras
[18], it consists of eight components; only one of the eight
components focuses on the physical practice of poses. The
remaining components consist of breath work, control of
the mind and senses, meditation, and ethical practices that
guide one’s behaviors such as how to interact with others and
howtotreatoneself[18]. A second reason for examining the
relative contributions of the different aspects of yoga practice
is that the different physical poses (standing poses, vigorous
poses such as arm balances and back bends, inversions such
as head stand and should stand) and yoga practices such as
breath work and meditation are believed to have different
physiological and psychological effects [46]. No studies were
found in peer-reviewed journals that examine the relative
contributions of the various aspects of yoga. Therefore,
the clinical value of the individual components remains
unclear.
The objective of this study is to better understand
the interrelationship between yoga practice and health.
Specifically, the study addressed the contributions of yoga
practice in general (years of practice, classes per month,
and/or days per month of home practice) and practice of
specific components of yoga practice (physical poses, breath
work, meditation, and/or philosophy study) to these aspects
of health. It is important to study the unique contributions
of the individual components of yoga practice because some
aspects of yoga practice may be more effective than others
in improving specific health outcomes such as body weight,
sleep, and mental health.
2. Methods
The study utilized a cross-sectional design with an anony-
mous online survey to examine yoga practice and its
relationship to aspects of health including physical activity,
fruit and vegetable consumption, sleep disturbance, fatigue,
social support, mindfulness, and subjective well-being.
2.1. Participants and Randomization. Approval for the study
was obtained from the Institutional Review Board at the
University of Maryland, Baltimore. Individuals included (1)
were at least 18 years of age, (2) practiced yoga (either taking
classes or practicing at home) at least weekly for a minimum
of two months within the past 6 months, and (3) had Internet
access and ability to complete an online survey. The length
and amount of yoga practice required to be included in the
study was chosen based upon the expert opinion of Senior
Iyengar yoga instructors as to the minimum required to be
considered an individual who practices yoga.
The researchers worked with the Iyengar Yoga National
Association U.S. (IYNAUS) in selecting study participants.
Iyengar yoga studios were chosen because they have (1) a
large national organization (representing over 900 teachers
and 100+ studios) and (2) strict standardization of teaching
that would likely contribute to consistent instruction.
There are over 900 certified Iyengar Yoga Teachers
within IYNAUS, representing over 100 yoga studios. The
investigators worked with IYNAUS to target studios in the
major geographic regions (Northeast, Southeast, Midwest,
Southwest, and West), taking steps to ensure all the regions
were represented in proportion to the number and size of
studios in their region. Based on an a priori power analysis,
15 studios with e-mail list serves of 18,160 were selected
to participate in the survey. Random sampling software
(SPSS version 19) was used to draw a random sample
(approximately 25%) of e-mail addresses from each studio.
Using this sampling strategy, 4307 potential subjects were
randomly selected from the 15 yoga studios to receive a
secure link to the survey, which was sent by the studio
owners. Of the 1164 individuals (27%) who responded to
the survey, 1045 (89.8%) completed the survey in its entirety
and met inclusion criteria. Data were collected from June to
September of 2011.
2.2. Measurement. Following strategies suggested by Dill-
man et al. [47] to develop and implement the survey,
the researchers used SurveyMonkey to create a 65-item
questionnaire that asked detailed questions about yoga
practice and health. Health outcomes were aspects of health
that are associated with increased risk of morbidity and
mortality. The survey utilized preexisting measures except
for demographic characteristics, descriptors of yoga practice,
Evidence-Based Complementary and Alternative Medicine 3
and a few individual health items including smoking, alcohol
consumption, and vegetarian status.
2.2.1. Yoga Practice. Questions regarding yoga practice were
divided into questions about general yoga practice (years of
practice and frequency of home practice and yoga classes)
and specific components of yoga practice (physical poses,
breath work, meditation, and philosophy study). Physical
poses were divided into four categories: standing poses;
vigorous poses such as sun salutations, backbends, and arm
balances; inversions such as head and shoulder stands; gentle
and/or restorative poses. Frequency of physical poses was
defined as days per month of practice at home and in
class, with the exception of gentle poses, which was defined
as ≤30 or >30 minutes per week. Frequency of breath
work and meditation were defined as ≤or >once per
week. The study of yogic philosophical texts, primarily the
Yoga Sutras of Patanjali, is considered one of the ethical
requirements of yoga study [18]. The amount of time
spent on the study of yoga philosophy (yoga sutras) was
defined as the frequency with which one attends classes or
lectures (including recordings or webcasts) or reads classical
yoga texts such as the Yoga Sutras, Bagavad Gita, or the
Upanishads.
2.2.2. Demographics. Demographic data were collected from
each subject including information regarding: age, gender,
race, height, weight, education, marital status, and job status.
Body mass index (BMI) was calculated using the following
formula: [Weight (pounds)/height (inches) 2] ×703 [48].
2.2.3. Sleep Disturbance, Fatigue, and Social Support. Sleep
disturbance (4-items), fatigue (4-items), and social sup-
port (8-items) were measured using short forms from
the Patient-Reported Outcomes Measurement Information
System (PROMIS) (sleep disturbance and fatigue) and
the National Institutes of Health (NIH) Toolbox (social
support). PROMIS and the NIH Toolbox are initiatives of
the NIH designed to provide the public with a free national
item bank of valid and reliable measures of commonly used
patient-reported outcomes measures [49,50]. All item banks
have high reliability [51] and compare favorably with legacy
measures [52]. Each item is assessed on a 5-point Likert scale,
ranging from 1 (“not at all”) to 5 (“very much”) to measure
perceptions of the amounts of social support (during past
month), as well as sleep disturbance and fatigue (during past
7 days), with higher scores indicating of higher levels of the
concepts. In the present study, Cronbach’s alpha was .83 for
sleep disturbance, .90 for fatigue, and .96 for social support.
2.2.4. Subjective Well-Being (Happiness). Subjective well-
being is a multidimensional construct of mental health
involving emotional, psychological, and social well-being,
often referred to as “happiness [53].” Subjective well-being
was measured using the 14-item Mental Health Continuum-
short form (MHC-SF) that asked subjects to report how
frequently they experienced symptoms of positive mental
health in the past month. Answers range from “never” to
“every day” and scores range from 14 to 70, with higher
scores indicating higher levels of subjective well-being.
Cronbach’s alpha for the total scale was .91 in the present
study.
2.2.5. Fruit and Vegetable Consumption. The number of
servings per day of fruits and vegetables was obtained using
7 items from the National Cancer Institute’s Multifactor
Screener, a self-report, food frequency questionnaire. The
Multifactor Screener asked subjects how often they ate fruits
and vegetables during the past month. Responses ranged
from never to several times per day, from which pyramid
servings of fruits and vegetables per day were calculated.
This questionnaire was validated in a number of large studies
including NCI’s Observing Protein and Energy (OPEN)
study and Eating at America’s Table Study (EATS), with
correlations with true consumption ranging from 0.5 to 0.8
[54].
2.2.6. Physical Activity. Information regarding physical activ-
ity was gathered using the 7-item International Physical
Activity Questionnaire (Short form) (IPAQ). Subjects were
instructed to report average number of days per week and
minutes per day of physical activity, not including yoga
classes or practice, during the past month. Results were
used to calculate the total number of metabolic-equivalent
minutes (MET-min) of exercise per week and levels of
physical activity [55]. The IPAQ was extensively studied in
12 countries and was found to be valid and reliable in 18 to
65-year-old adults in a variety of settings [56,57].
2.2.7. Freiberg Mindfulness Inventory—Short Form. Mind-
fulness was measured using the Freiberg Mindfulness
Inventory—Short Form (FMI-SF), an 8-item version of the
original 30-item Freiberg Mindfulness Inventory [58,59]
that uses a 4-point Likert scale to assess how frequently
subjects experience certain situations or mind states. Scores
range from 8 to 32, with higher scores indicating higher
levels of mindfulness. Cronbach’s alpha was .87 in the present
study.
2.2.8. Other Health Information. Single items were used to
assess current smoking status (yes/no), vegetarian status
(defined as no consumption of meat, fish, or poultry), and
alcohol consumption (alcoholic drinks per week).
2.3. Statistical Analysis. Data cleaning techniques using SPSS
19.0 were used to identify miscoded data, outliers, and miss-
ing data. Because the survey required participants to answer
every question, less than 5% of the data were missing. Incom-
plete cases were excluded from future analyses. Independent
ttests were used to examine differences between those cases
with and without missing data as well as incomplete versus
complete cases; no significant differences were noted. Three
variables (gentle poses, meditation, and breath work) were
badly skewed and could not be normalized. These three
variables were dichotomized using the median as a cut point.
Descriptive statistics (frequencies, percentages, measures of
4 Evidence-Based Complementary and Alternative Medicine
central tendency, and standard deviations) were obtained
to describe the demographic data, yoga practice habits,
and aspects of health. According to Gellman and Hill [60],
analysis adjustment for multiple analyses is not necessary in
an exploratory model building context. Thus, the researchers
used a .05 level of significance for all analyses.
Research questions examining relationships of predic-
tors with outcomes were analyzed using linear or logistic
regression, depending upon the level of measurement of
the outcome. Regression analyses were conducted using the
following steps. First, bivariate relationships of yoga practice
and demographic variables with aspects of health were inves-
tigated by computing Pearson rcorrelations. Next, any yoga
practice variable or demographic variable that had at least
asmall(r=.10) and significant relationship to the health
variable of interest was included in appropriate regression
analyses (linear or logistic) to examine the independent
effects of all correlated variables [61]. Variables that were
significant at P=.05 were placed into subsequent regressions
to examine interaction effects. Interactions that were not
significant at P=.05 were removed, one at a time, until the
final model was determined.
Research questions examining differences in means
between those with high and low practice frequency were
analyzed using independent ttests. Cut offpoints for
determining high and low yoga practice groups were selected
using the highest and lowest quartiles. A priori power
analyses showed the 1045 cases were sufficient to achieve
80% power with alpha .05 with a medium effect size for all
analyses.
3. Results
Demographic characteristics of the study sample are
included in Table 1. The age of participants ranged from
19 to 87 years (M=51.7±11.7). The large majority
of subjects was female (84.2%) and white (89.2%). Most
of the subjects were married (61.3%) and employed full
time (50.9%). They were highly educated, with almost 90%
having either an undergraduate (36.9%), master’s (37%), or
a doctoral (13.5%) degree. Subjects reported practicing yoga
for less than one to more than 25 years (M=11.4±7.5).
They reported taking between zero and 28 classes per month
(M=6.1±5.1) and practicing yoga outside of class up to 28
days per month (M=12.2±9.7).
In the final models examining general yoga practice,
frequency of home practice was the practice variable that
most often predicted aspects of health (Table 2). Specifically
practice frequency (β=.106, P<.001) and years of
practice (β=.039, P<.05) were independent predictors
of mindfulness. For every extra day per week of yoga home
practice, mindfulness scores increased .42 of a point (.10 of a
SD). After controlling for gender and age, practice frequency
was a significant independent predictor of subjective well-
being (β=.183, P<.001) and BMI (β=−.043, P<
.001). Every additional day per week of home practice was
associatedwithadecreaseof.17ofapoint(.04ofSD)in
BMI. After controlling for gender and age, practice frequency
Tab l e 1: Demographic characteristics of study sample (N=1045).
Var i a b l es M(SD) Range
Age (n=1043) 51.7 (11.7) 19–87
Frequency Percent
Gender
Female 880 84.2
Race
White 932 89.2
Othera113 10.8
Marital status
Married/lives with partner 730 69.8
Singleb/widowed/separated/divorced 308 29.5
Other 70.7
Employment
Full time 532 50.9
Part time 277 26.5
Not employed 236 22.6
Education
High school/GED/trade/vocational
school/Other 31 3.0
Some college 100 9.6
College graduate 386 36.9
Master’s degree 387 37.0
Doctoral degree 141 13.5
aMultiracial (n=38; 3.6%), Asian (n=28; 2.7%), African American (n=
18; 1.7%), American Indian/Alaskan/Hawaiian/Pacific Islander (6; 0.6%),
other (n=23; 2.2%).
bNever married.
predicted fruit and vegetable servings per day (β=.031,
P<.001). Practice frequency was the only variable negatively
related to sleep disturbance (β=−.052, P<.001), and
individuals who practiced more frequently had higher odds
of being a vegetarian than those who practiced less often
(OR =1.057, P<.001). For every additional day per week
of yoga practice, sleep improved by .21 of a point (.07 of
an SD) and the odds of being vegetarian increased 22.8%.
After controlling for the effects of practice frequency (β=
−.171, P<.01) and age (β=−.072, P<.01), there was
a significant interaction effect between practice frequency
and age on fatigue (β=.002, P<.01). Older individuals
had lower levels of fatigue regardless of practice frequency,
but younger individuals with a higher frequency of home
practice exhibited lower levels of fatigue than those who
practiced less often (see Figure 1). At the highest levels of
practice, older and younger individuals experienced similar
fatigue levels.
Because practice frequency was such an important pre-
dictor of health, the authors explored differences in yoga
practice between intense practitioners (those who practice at
home ≥5 days per week) and less intense practitioners (those
with a home practice of ≤1 day/week). Intense practitioners
reported significantly more years of yoga practice (M=
15.1±6.7 years versus 8.6±7.2 years) than those who were
Evidence-Based Complementary and Alternative Medicine 5
Tab l e 2: Summary of results of final linear and logistic regression models predicting health outcomes from general patterns of yoga practice
in combination with influential demographic predictors (N=1045).
Health outcome Parameter statistics
Final predictorsaBSE t
Mindfulness Practice frequencyb.106 .014 7.53∗∗
Years of practice .039 .018 2.17∗
Subjective well-being Practice frequencyb.183 .034 5.31∗∗
Genderc3.39 .915 3.72∗∗
BMI (n=1034) Practice frequencyb−.043 .012 −3.26∗∗
Genderc−2.013 .321 −6.28∗∗
Fruit and vegetables/Day (n=1043)
Practice frequencyb.031 .006 5.59∗∗
Age .013 .005 2.92∗∗
Genderc−.583 .147 −3.97∗∗
Sleep disturbance Practice frequencyb−.052 .009 −5.58∗∗
Fatigue
Practice frequencyb−.171 .042 −4.02∗∗
Age −.072 .011 −6.36∗∗
Practice frequencybx Age .002 .001 2.91∗∗
Wald/O R
Vegetarian status Practice frequencyb.056 .011 25.78∗/1.057∗
aEach final model includes all predictors included in the final model. Demographic covariates were included if they had at least a small (r=.1) and significant
(P<.05) correlation with the health variable. No demographic covariate met these criteria that was not included in the final model. bDays per month of
home yoga practice. cGender coded males “0,” females “1.” Abbreviations—B: unstandardized beta weight. SE: standard error. t:tscore for linear regressions.
x: interaction effect. Wald: Wald statistic for logistic regressions. OR: odds ratio. BMI: body mass index. Note: for all measures, higher scores indicate more of
the concept measured. ∗P<0.05 level (2-tailed). ∗∗P<0.01 (2-tailed).
Amount of practice
Least 25th %ile 50th %ile 75th %ile Most
Fatigue
7
8
9
Age at the 25th %ile (43 years)
Age at 50th %ile (53 years)
Age at the 75th %ile (60 years)
Figure 1: Interaction effect between frequency of home yoga practice and age (n=1043). Note: Percentiles for frequency of home yoga
practice: least =0 days/month, 25th =4 days/month, 50th =12 days/month, 75th =20 days/month, most =28 days/month.
less experienced (t=−12.038, df =480; P<.001). Intense
practitioners practiced more standing poses (M=17.8±7.6
days per month versus M=7.2±5.4 days per month;
t=−21.587, df =700; P<.001), more vigorous poses
(M=14.6±8.5dayspermonthversusM=4.3±4.6
days per month; t=−19.755, df =482.31; P<.001), and
more inversions (M=18.04 ±9.0 days per month versus
M=4.51 ±4.6 days per month; t=−24.508, df =468.71;
P<.001) than less intense practitioners. Those with high
practice frequency report studying philosophy about once
per month, compared to those with low practice frequency
who study yoga philosophy only about 3 or 4 times per
year (P<.001). Intense practitioners had nine times the
odds of regularly practicing gentle poses, twice the odds of
6 Evidence-Based Complementary and Alternative Medicine
Tab l e 3: Results of final linear and logistic regression models predicting health outcomes from specific types of yoga practiceain combination
with influential demographic predictors (N=1045).
Health outcome Final predictorsbBS.E. t
Mindfulness
Breath workc1.60 .29 5.51∗
Meditationc1.05 .28 3.71∗
Philosophy study .31 .08 4.09∗
Subjective well-being
Meditationc2.80 .71 3.95∗
Philosophy study .76 .20 3.87∗
Genderd3.40 .91 3.73∗
BMI (n=1034)
Vigorous posese−.05 .02 −3.27∗
Philosophy study −.16 .07 −2.22∗∗
Genderd−2.03 .32 −6.34∗
Fruit and vegetables/day (n=1043)
Standing posese.024 .01 3.31∗
Gentle posesf.36 .11 3.16∗
Genderd−.59 .15 −4.03∗
Age .01 .01 3.17∗
Sleep disturbance Vigorous posese−.07 .14 −5.50∗
Fatigue
Inversionse−.05 .01 −4.62∗
Meditationc−.52 .18 −2.83∗
Age −.05 .01 –6.53∗
Wald/O R
Vegetarian statusgGentle posesf.73 .24 9.05∗/2.07∗
Philosophy study .24 .06 15.84∗/1.27∗
Alcohol consumptionhGentle posesf−.48 .13 14.37∗/.621∗
Racei.92 .22 17.56∗/.53∗
aSpecific yoga practices: physical poses (standing, vigorous, inversions, and gentle), breath work, meditation, and yoga philosophy study. bEach final model
includes all predictors included in the final model. Demographic covariates were included if they had at least a small (r=.1) and significant (P<.05)
correlation with the health variable. No demographic variable met these criteria that was not included in the final model. c≤or >once per week. dGender
coded “0” =male “1” =female. eDays per month. f≤or ≥30 minutes per week. gVegetarian status coded no =“0”, yes =“1”. hAlcohol consumption
(number of drinks one consumes on a typical day when one drinks) coded ≤2 drinks per day =“0”, >2 drinks per day. iRace coded “0” =other, “1” =white.
Abbreviations—B: unstandardized beta weight. SE: standard error. t:tscore for linear regressions. Wald: Wald statistic for logistic regressions. OR: odds ratio.
BMI: body mass index. Note: For all measures, higher scores indicate more of the concept measured. ∗P<0.05 level (2-tailed). ∗∗P<0.01 (2-tailed).
meditating at least weekly, and nearly three times the odds
of practicing breath work at least weekly than those who
reported low practice frequency (P<.001).
In the final models examining specific components of
yoga practice, all of the specific components predicted at
least one aspect of health (Table 3). Notably, frequency of
philosophy study was the yoga practice variable that most
often predicted health. Frequency of philosophy study (β=
.310, P<.001), along with breath work (β=.290, P<.001)
and meditation (β=.282, P<.001), positively predicted
mindfulness. Frequency of philosophy study (β=.756, P<
.001), in addition to meditation (β=2.80, P<.001) and
female gender (β=3.39, P<.001), also positively predicted
subjective well-being. More frequent philosophy study also
contributed to a lower BMI (β=−.158, P<.05) and higher
odds of being a vegetarian (β=.242, P<.001).
After controlling for gender, vigorous poses remained
an independent predictor of BMI (β=−.053, P<.05).
Vigorous poses also predicted sleep disturbance (β=−.065,
P<.05). For every additional day per week of vigorous
pose practice, BMI decreased .21 of a point (.05 of a SD)
and sleep disturbance improved .26 of a point (.087 of an
SD). Frequency of gentle poses (β=.360, P<.001),
along with standing poses (β=.024, P<.01), remained
positive predictors of fruit and vegetables consumption, even
when controlling for the effects of age and gender. Those
individuals who practiced gentle poses 30 minutes or more
per week had 7% higher odds of being vegetarian (OR =
2.073, P<.01) and about 50% lower odds of consuming
alcohol (OR =.621, P<.001) than those who practiced
gentle poses for 30 minutes or less per week.
4. Discussion
In general, frequency of yoga practice outside of class, as
opposed to years of yoga practice or class participation,
was repeatedly a predictor of aspects of health including
mindfulness, subjective well-being, BMI, fruit and vegetable
consumption, and sleep disturbance. It did not appear to
Evidence-Based Complementary and Alternative Medicine 7
matter how long an individual had practiced yoga. Rather,
it appeared to matter how often they practiced. While class
participation may be important in learning to do yoga, it did
not predict any aspects of health. Perhaps time spent in class
counts as additional practice time, and it is not unique unto
itself.
While the individual effects of frequency of home prac-
tice are small, accounting for less than 7% of the variance
in the health variables, they are cumulative. For instance, for
an individual who did not previously have a home practice
of yoga, practicing one day per week is associated with
consuming an extra tenth of a serving of fruits and vegetables
per day or almost one extra serving per week. If that same
individual were to practice five days per week, that would be
associated with an increase of over one half a serving of fruits
and vegetables per day or nearly four and a half extra servings
per week.
Individuals who were intense practitioners (5+ days per
week of home practice) tended to practice all aspects of yoga
including all of the physical poses, breath work, meditation,
and philosophy study more often than those who did not
practice as often. Intense practitioners attended class at
the same rate as less intense practitioners. This possibly
explains why class frequency did not predict any aspects of
health. Because frequency of home practice was an important
predictor of many aspects of health, and intense practitioners
tended to practice all aspects of yoga, it is logical to assume
that a practice that includes all aspects of yoga may be more
beneficial to health than practice that includes only one or
two aspects of yoga (such as only breath work or vigorous
poses).
The interaction effectofpracticefrequencywithageon
fatigue showed that older individuals, regardless of their
practice frequency, had significantly lower levels of fatigue
than younger yoga practitioners; younger individuals who
had a more frequent home practice had less fatigue than
younger practitioners who did not practice as often. Perhaps
older individuals experience benefits from just a little bit
of yoga practice, while younger individuals need more to
experience benefits on fatigue. This finding is encouraging
for older individuals beginning the practice of yoga, as
problems with sleep and fatigue are common in the elderly
[62,63].
While no single category of physical pose (standing
poses, vigorous poses, inversions, and/or gentle poses) was
related to all aspects of health, each category of physical
pose was related significantly to at least one aspect of health.
The physical poses, often referred to as the “external” or
physical practice in yoga texts [64], were most commonly
related to the physical aspects of health (sleep, diet, BMI).
In contrast, the higher level practices of breath work
and meditation, typically defined in yoga texts as tools
for controlling a distracted, fluctuating mind [64], were
associated with mindfulness and subjective well-being. It is
possible that physical poses, particularly active poses (such as
standing poses) and vigorous poses (such as sun salutations,
backbends, and arm balances), have effects similar to those
of exercise. These findings support previous evidence that
exercise is related to diet [65], energy levels [65], and BMI
[66]. Levels of physical activity in this population predicted
fruit and vegetable consumption and levels of fatigue,
although the effects (standardized betas) of physical activity
were smaller than those of yoga home practice. Likewise,
because breath work and meditation appear to influence
mindfulness and well-being, they may be particularly useful
in treating conditions such as depression and anxiety.
More frequent practice of gentle poses, including supine
restorative poses and relaxation pose (Savasana), were
associated with three aspects of health that deal with
feeding behaviors or cravings: higher fruit and vegetable
consumption, higher rates of vegetarianism, and lower
alcohol consumption. It has been postulated that yoga
impacts the Hypothalamic-Pituitary-Adrenal (HPA) axis and
the Sympathetic Nervous System (SNS) response to stress
[23], possibly via direct vagal stimulation [20]. Evidence
suggests that stress is associated with unhealthy changes in
food seeking behavior including increased consumption of
foods high in sugar and fat [67,68], as well as increased
alcohol consumption [69,70]. Of all types of physical poses,
gentle poses would likely exert the most profound relaxation
response. Perhaps an effective weight loss intervention would
include a combination of active physical poses for their
exercise benefits, as well as gentle poses for their possible
effects on the HPA axis response to stress, particularly as
it relates to self-medicating with food and alcohol. While
combination approaches have resulted in weight loss in past
studies [36–38], none looked specifically at the combination
of active and gentle poses.
Compared to other components of yoga practice, fre-
quency of philosophy study most often predicted aspects
of health. It is doubtful that reading yoga philosophy texts
will lead to lower BMI or more happiness. Rather, because
individuals who were intense practitioners (≥5daysperweek
of yoga practice) studied philosophy significantly more often
than those who practiced less than once per week, it is
likely that frequency of philosophy study served as a “proxy
variable” for intense practice. In addition, these same intense
practitioners tended to practice all aspects of yoga, with
more days of practice per month of all of the physical poses,
breath work, and meditation. Thus, any relationship between
philosophy study and health may reflect the relationship
of frequency and intensity of yoga practice to health. This
provides more evidence that an intense practice involving all
aspects of yoga practice may be more beneficial to health than
a less intense practice that includes only one or two aspects
of yoga practice, such as just practicing the physical poses or
breath work.
A number of limitations existed in this study. The
findings of this study are generalizable only to Iyengar yoga
practitioners in the USA. Second, anonymous online surveys
have the potential for denial, deception, and recall and/or
response bias. Thus, answers for measures such as height and
weight might not be accurate. The response rate of 27% was
low, which could potentially result in bias. Because subjects
were predominantly white, female, and highly educated, it
is not known if a lack of diversity may have limited the
ability to control for these demographics in the models.
Finally, the cross-sectional nature of the study allows one
8 Evidence-Based Complementary and Alternative Medicine
to draw inferences, but do not allow one to conclude that
yoga actually impacts health. It should be noted that the use
of the word “predicted” when describing the relationship
between yoga practice and health is the appropriate term
when interpreting linear regressions, but it does not imply
causality. Despite these limitations, this study makes an
important contribution to understanding of the practice of
yoga and its potential contribution to practitioners’ health.
5. Conclusion
In conclusion, yoga may be a useful intervention for improv-
ing health behaviors or life-style-related health conditions.
Frequency of home practice appears to be very important—
more important than how long an individual has been
practicing or how many classes one takes. This emphasizes a
simple fact: it is not enough simply to learn how to do healthy
behaviors. Rather, healthy behaviors must be incorporated
into one’s daily life. While these findings suggest that
individuals will only glean benefits from yoga practice that
are proportional to the energy they are willing to invest in
making it a part of their lives, the findings also suggest that
they do not have to practice for years in order to reap the
rewards.
Whatonepractices,beitthedifferent types of physical
poses, breath work, or meditation, is important because the
different aspects of yoga practice may well have different
health benefits. Randomized clinical trials are needed to
examine causal relationships between the different aspects
of yoga practice and aspects of health. For instance, does an
intervention focusing on gentle poses positively affect feeding
behaviors? Does an intervention focusing on vigorous poses
effect sleep better than an intervention focusing on gentle
poses?
While this study focused exclusively on Iyengar yoga,
it is important to note that styles of yoga differ in what
components of yoga practice are emphasized. Thus, some
styles of yoga may be better suited for certain individuals,
depending upon the aspects of health they are seeking
to improve, as well as their temperament and physical
condition. For this reason, future research should examine
the comparative effectiveness of different styles of yoga on a
variety of health outcomes.
Acknowledgment
The authors wish to thank the Iyengar Yoga National
Association U.S. and all the participating yoga studios for
their assistance in this research study. The authors extend
a special note of appreciation to Kathleen Pringle and John
Schumacher for their expert guidance in developing and
implementing the survey.
References
[1] S. J. Wu and A. Green, A Projection of Chronic Illness Prevalence
and Cost Inflation, RAND Health, Santa Monica, Calif, USA,
2000.
[2]B.D.Cox,M.J.Whichelow,andA.T.Prevost,“Seasonal
consumption of salad vegetables and fresh fruit in relation to
the development of cardiovascular disease and cancer,” Public
Health Nutrition, vol. 3, no. 1, pp. 19–29, 2000.
[3] C. Heidemann, M. B. Schulze, O. H. Franco, R. M. Van Dam,
C. S. Mantzoros, and F. B. Hu, “Dietary patterns and risk of
mortality from cardiovascular disease, cancer, and all causes
in a prospective cohort of women,” Circulation, vol. 118, no. 3,
pp. 230–237, 2008.
[4] G. D. Smith, M. J. Shipley, G. D. Batty, J. N. Morris, and M.
Marmot, “Physical activity and cause-specific mortality in the
Whitehall study,” Public Health, vol. 114, no. 5, pp. 308–315,
2000.
[5] E. Teixeira-Lemos, S. Nunes, F. Teixeira, and F. Reis, “Regular
physical exercise training assists in preventing type 2 diabetes
development: focus on its antioxidant and anti-inflammatory
properties,” Cardiovascular Diabetology, vol. 10, article 12,
2011.
[6] C. M. Friedenreich, “Physical activity and breast cancer:
review of the epidemiologic evidence and biologic mecha-
nisms,” Recent Results in Cancer Research, vol. 188, pp. 125–
139, 2011.
[7]G.D.Batty,M.Kivimaki,L.Gray,G.D.Smith,M.G.
Marmot, and M. J. Shipley, “Cigarette smoking and site-
specific cancer mortality: testing uncertain associations using
extended follow-up of the original Whitehall study,” Annals of
Oncology, vol. 19, no. 5, pp. 996–1002, 2008.
[8] K. K. Teo, S. Ounpuu, S. Hawken et al., “Tobacco use and risk
of myocardial infarction in 52 countries in the INTERHEART
study: a case-control study,” The Lancet, vol. 368, no. 9536, pp.
647–658, 2006.
[9] T. Laatikainen, L. Manninen, K. Poikolainen, and E. Varti-
ainen, “Increased mortality related to heavy alcohol intake
pattern,” Journal of Epidemiology and Community Health, vol.
57, no. 5, pp. 379–384, 2003.
[10]K.J.Mukamal,C.M.Chen,S.R.Rao,andR.A.Breslow,
“Alcohol consumption and cardiovascular mortality among
U.S. adults, 1987 to 2002,” Journal of the American College of
Cardiology, vol. 55, no. 13, pp. 1328–1335, 2010.
[11] J. Barth, M. Schumacher, and C. Herrmann-Lingen, “Depres-
sion as a risk factor for mortality in patients with coronary
heart disease: a meta-analysis,” Psychosomatic Medicine, vol.
66, no. 6, pp. 802–813, 2004.
[12] F. Mookadam and H. M. Arthur, “Social support and its
relationship to morbidity and mortality after acute myocardial
infarction: systematic overview,” Archives of Internal Medicine,
vol. 164, no. 14, pp. 1514–1518, 2004.
[13] T. E. Seeman, “Health promoting effects of friends and family
on health outcomes in older adults,” American Journal of
Health Promotion, vol. 14, no. 6, pp. 362–370, 2000.
[14] M. A. Wallander, S. Johansson, A. Ruig ´
omez, L. A. Garc´
ıa
Rodr´
ıguez, and R. Jones, “Morbidity associated with sleep
disorders in primary care: a longitudinal cohort study,” Journal
of Clinical Psychiatry, vol. 9, no. 5, pp. 338–345, 2007.
[15] Kvaavik, “Influence of individual and combined health behav-
iors on total and cause-specific mortality in men and women:
the United Kingdom health and lifestyle survey (Archives
of Internal Medicine (2010) 170, 8, (711–718)),” Archives of
Internal Medicine, vol. 170, no. 11, p. 998, 2010.
[16] D. Scrutinio, “The potential of lifestyle changes for improving
the clinical outcome of patients with coronary heart disease:
mechanisms of benefit and clinical results,” Reviews on Recent
Clinical Trials, vol. 5, no. 1, pp. 1–13, 2010.
Evidence-Based Complementary and Alternative Medicine 9
[17] R. M. Van Dam, T. Li, D. Spiegelman, O. H. Franco, and F.
B. Hu, “Combined impact of lifestyle factors on mortality:
prospective cohort study in US women,” BMJ, vol. 337, no.
7672, pp. 742–745, 2008.
[18] E. F. Bryant, The Yoga Sutras of Patanjali, North Point Press,
New York, NY, USA, 1st edition, 2009.
[19] J. A. Raub, “Psychophysiologic effects of Hatha Yoga on
musculoskeletal and cardiopulmonary function: a literature
review,” Journal of Alternative and Complementary Medicine,
vol. 8, no. 6, pp. 797–812, 2002.
[20] K. E. Innes, C. Bourguignon, and A. G. Taylor, “Risk indices
associated with the insulin resistance syndrome, cardiovascu-
lar disease, and possible protection with yoga: a systematic
review,” Journal of the American Board of Family Practice, vol.
18, no. 6, pp. 491–519, 2005.
[21] K. E. Innes and H. K. Vincent, “The influence of yoga-
based programs on risk profiles in adults with type 2 diabetes
mellitus: a systematic review,” Evidence-Based Complementary
and Alternative Medicine, vol. 4, no. 4, pp. 469–486, 2007.
[22] J.E.Bower,A.Woolery,B.Sternlieb,andD.Garet,“Yogafor
cancer patients and survivors,” Cancer Control, vol. 12, no. 3,
pp. 165–171, 2005.
[23] A. Ross and S. Thomas, “The health benefits of yoga and
exercise: a review of comparison studies,” Journal of Alternative
and Complementary Medicine, vol. 16, no. 1, pp. 3–12, 2010.
[24] P. Sterling, “Principles of allostasis: optimal design, predictive
regulation, pthophysiology, and rational therapeutics,” in
Allostasis, Homeostasis, and the Costs of Physiological Adapta-
tion, J. Schulkin, Ed., Cambridge University Press, Cambridge,
Mass, USA, 2004.
[25] B. S. McEwen, “Allostasis and allostatic load: implications for
neuropsychopharmacology,” Neuropsychopharmacology, vol.
22, no. 2, pp. 108–124, 2000.
[26] A. Michalsen, P. Grossman, A. Acil et al., “Rapid stress reduc-
tion and anxiolysis among distressed women as a consequence
of a three-month intensive yoga program,” Medical Science
Monitor, vol. 11, no. 12, pp. CR555–CR561, 2005.
[27] J. West, C. Otte, K. Geher, J. Johnson, and D. C. Mohr, “Effects
of Hatha yoga and African dance on perceived stress, affect,
and salivary cortisol,” Annals of Behavioral Medicine, vol. 28,
no. 2, pp. 114–118, 2004.
[28] R. Gokal, L. Shillito, and S. R. Maharaj, “Positive impact of
yoga and pranayam on obesity, hypertension, blood sugar,
and cholesterol: a pilot assessment,” Journal of Alternative and
Complementary Medicine, vol. 13, no. 10, pp. 1056–1057, 2007.
[29] D. Khatri, K. C. Mathur, S. Gahlot, S. Jain, and R. P. Agrawal,
“Effects of yoga and meditation on clinical and biochemical
parameters of metabolic syndrome,” Diabetes Research and
Clinical Practice, vol. 78, no. 3, pp. e9–e10, 2007.
[30] W. Selvamurthy, K. Sridharan, U. S. Ray et al., “A new
physiological approach to control essential hypertension,”
Indian Journal of Physiology and Pharmacology, vol. 42, no. 4,
pp. 205–213, 1998.
[31] A. Damodaran, A. Malathi, N. Patil, N. Shah, Suryavanshi,
and S. Marathe, “Therapeutic potential of yoga practices in
modifying cardiovascular risk profile in middle aged men and
women,” Journal of Association of Physicians of India, vol. 50,
no. 5, pp. 633–639, 2002.
[32] R. McCaffrey, P. Ruknui, U. Hatthakit, and P. Kasetsomboon,
“The effects of yoga on hypertensive persons in Thailand,”
Holistic Nursing Practice, vol. 19, no. 4, pp. 173–180, 2005.
[33] P. R. Pullen, S. H. Nagamia, P. K. Mehta et al., “Effects of
yoga on inflammation and exercise capacity in patients with
chronic heart failure,” Journal of Cardiac Failure,vol.14,no.5,
pp. 407–413, 2008.
[34] M. Stuck, K. Meyer, T. Rigotti, K. Bauer, and U. Sack,
“Evaluation of a yoga-based stress management training
for teachers: effects on immunoglobuline a secretion and
subjective relaxation,” Journal for Meditation and Meditation
Research, pp. 1–8, 2003.
[35] R. M. Rao, S. Telles, H. R. Nagendra et al., “Effects of yoga on
natural killer cell counts in early breast cancer patients under-
going conventional treatment. Comment to: recreational
music-making modulates natural killer cell activity, cytokines,
and mood states in corporate employees Masatada Wachi,
Masahiro Koyama, Masanori Utsuyama, Barry B. Bittman,
Masanobu Kitagawa, Katsuiku Hirokawa Med Sci Monit,
2007; 13(2): CR57–70,” Medical Science Monitor, vol. 14, no.
2, pp. LE3–LE4, 2008.
[36] A. S. Mahajan, K. S. Reddy, and U. Sachdeva, “Lipid profile of
coronary risk subjects following yogic lifestyle intervention,”
Indian Heart Journal, vol. 51, no. 1, pp. 37–40, 1999.
[37] R. Gokal, L. Shillito, and S. R. Maharaj, “Positive impact of
yoga and pranayam on obesity, hypertension, blood sugar,
and cholesterol: a pilot assessment,” Journal of Alternative and
Complementary Medicine, vol. 13, no. 10, pp. 1056–1057, 2007.
[38]L.Gordon,E.Y.Morrison,D.McGrowderetal.,“Effect
of yoga and traditional physical exercise on hormones and
percentage insulin binding receptor in patients with type 2
diabetes,” American Journal of Biochemistry and Biotechnology,
vol. 4, no. 1, pp. 35–42, 2008.
[39] S. Sivasankaran, S. Pollard-Quintner, R. Sachdeva, J. Pugeda,
S. M. Hoq, and S. W. Zarich, “The effectofasix-week
program of yoga and meditation on brachial artery reactivity:
do psychosocial interventions affect vascular tone?” Clinical
Cardiology, vol. 29, no. 9, pp. 393–398, 2006.
[40] A. R. Kristal, A. J. Littman, D. Benitez, and E. White, “Yoga
practice is associated with attenuated weight gain in healthy,
middle-aged men and women,” Alternative Therapies in Health
and Medicine, vol. 11, no. 4, pp. 28–33, 2005.
[41]B.S.Oken,S.Kishiyama,D.Zajdeletal.,“Randomized
controlled trial of yoga and exercise in multiple sclerosis,”
Neurology, vol. 62, no. 11, pp. 2058–2064, 2004.
[42] B. S. Oken, D. Zajdel, S. Kishiyama et al., “Randomized,
controlled, six-month trial of yoga in healthy seniors: effects
on cognition and quality of life,” Alternative Therapies in
Health and Medicine, vol. 12, no. 1, pp. 40–47, 2006.
[43] M. Yurtkuran, A. Alp, M. Yurtkuran, and K. Dilek, “A mod-
ified yoga-based exercise program in hemodialysis patients:
a randomized controlled study,” Complementary Therapies in
Medicine, vol. 15, no. 3, pp. 164–171, 2007.
[44] N. Moliver et al., “Increased Hatha yoga experience predicts
lower body mass index and reduced medication use in women
over 45 years,” International Journal of Yoga, vol. 4, pp. 77–86,
2011.
[45] A. Palasuwan, I. Margaritis, S. Soogarun, and A. S. Rousseau,
“Dietary intakes and antioxidant status in mind-body exercis-
ing pre- and postmenopausal women,” Journal of Nutrition,
Health and Aging, vol. 15, no. 7, pp. 577–584, 2011.
[46] B. K. S. Iyengar and B. K. S. I. Yoga, The Path to Holistic Health,
vol. 1, Dorling Kindersley, London, UK, 2001.
[47] D. Dillman, J. Smyth, and L. Christian, Internet, Mail, and
Mixed-Mode Surveys: The Tailored Design Method,JohnWiley
& Sons, Hoboken, NJ, USA, 2009.
[48] NHLBI, “Clinical guidelines on the identification, evaluation,
and treatment of overweight and obesity in adults: the
10 Evidence-Based Complementary and Alternative Medicine
evidence report 1993,” 2011, http://www.nhlbi.nih.gov/guide-
lines/obesity/ob gdlns.pdf.
[49] PROMIS, “Patient-reported outcomes measurement informa-
tion system: dynamic tools to measure health outcomes from
the patient perspective,” 2011, http://www.nihpromis.org/
default.aspx.
[50] R. C. Gershon, D. Cella, N. A. Fox, R. J. Havlik, H. C.
Hendrie, and M. V. Wagster, “Assessment of neurological
and behavioural function: the NIH Toolbox,” The Lancet
Neurology, vol. 9, no. 2, pp. 138–139, 2010.
[51] D. Cella, W. Riley, A. Stone et al., “The patient-reported
outcomes measurement information system (PROMIS) devel-
oped and tested its first wave of adult self-reported health
outcome item banks: 2005–2008,” Journal of Clinical Epidemi-
ology, vol. 63, no. 11, pp. 1179–1194, 2010.
[52] W.T.Riley,N.Rothrock,B.Bruceetal.,“Patient-reportedout-
comes measurement information system (PROMIS) domain
names and definitions revisions: further evaluation of content
validity in IRT-derived item banks,” Quality of Life Research,
vol. 19, no. 9, pp. 1311–1321, 2010.
[53] C. Robitschek and C. L. M. Keyes, “Keyes’s model of mental
health with personal growth initiative as a parsimonious
predictor,” Journal of Counseling Psychology,vol.56,no.2,pp.
321–329, 2009.
[54] F. E. Thompson, D. Midthune, A. F. Subar, L. L. Kahle, A.
Schatzkin, and V. Kipnis, “Performance of a short tool to assess
dietary intakes of fruits and vegetables, percentage energy
from fat and fibre,” Public Health Nutrition,vol.7,no.8,pp.
1097–1105, 2004.
[55] C. L. Craig, A. L. Marshall, M. Sj¨
ostr¨
om et al., “International
physical activity questionnaire: 12-Country reliability and
validity,” Medicine and Science in Sports and Exercise, vol. 35,
no. 8, pp. 1381–1395, 2003.
[56] U. M¨
ader, B. W. Martin, Y. Schutz, and B. Marti, “Validity
of four short physical activity questionnaires in middle-aged
persons,” Medicine and Science in Sports and Exercise, vol. 38,
no. 7, pp. 1255–1266, 2006.
[57] A. P. Gauthier, M. Lariviere, and N. Young, “Psychometric
properties of the IPAQ: a validation study in a sample of
northern Franco-Ontarians,” JournalofPhysicalActivity&
Health, vol. 6, supplement 1, pp. S54–S60, 2009.
[58] H. Walach, N. Buchheld, V. Buttenm¨
uller, N. Kleinknecht, and
S. Schmidt, “Measuring mindfulness-the Freiburg Mindful-
ness Inventory (FMI),” Personality and Individual Differences,
vol. 40, no. 8, pp. 1543–1555, 2006.
[59] N. Kohls, S. Sauer, and H. Walach, “Facets of mindfulness—
results of an online study investigating the Freiburg mindful-
ness inventory,” Personality and Individual Differences, vol. 46,
no. 2, pp. 224–230, 2009.
[60] A. Gellman and J. Hill, Data Analysis Using Regression and
Multilevel/Hierarchical Models, Cambridge University Press,
New York, NY, USA, 2007.
[61] G. G. Tabachnik and L. S. Fidell, Using Multivariate Statistics,
Allyn and Bacon, Boston, Mass, USA, 5th edition, 2007.
[62] V. Morelli, “Fatigue and chronic fatigue in the elderly: def-
initions, diagnoses, and treatments,” Clinics in Geriatric
Medicine, vol. 27, no. 4, pp. 673–686, 2011.
[63] S. Surani and A. Khan, “Sleep related disorders in the elderly:
an overview,” Current Respiratory Medicine Reviews, vol. 3, no.
4, pp. 286–291, 2007.
[64] B. K. S. Iyengar, Light on Yoga: Yoga Dipika, Schocken Books,
New York, NY, USA, 2nd edition, 1979.
[65] J. Goss and L. Grubbs, “Comparative analysis of body mass
index, consumption of fruits and vegetables, smoking, and
physical activity among Florida residents,” Journal of Commu-
nity Health Nursing, vol. 22, no. 1, pp. 37–46, 2005.
[66] J. Kruger, H. R. Bowles, D. A. Jones, B. E. Ainsworth, and H. W.
Kohl, “Health-related quality of life, BMI and physical activity
among US adults (≥18 years): national physical activity and
weight loss survey, 2002,” International Journal of Obesity, vol.
31, no. 2, pp. 321–327, 2007.
[67] S. S. Schiffman, B. G. Graham, E. A. Sattely-Miller, and M.
Peterson-Dancy, “Elevated and sustained desire for sweet taste
in African-Americans: a potential factor in the development of
obesity,” Nutrition, vol. 16, no. 10, pp. 886–893, 2000.
[68] G. Oliver, J. Wardle, and E. L. Gibson, “Stress and food choice:
a laboratory study,” Psychosomatic Medicine,vol.62,no.6,pp.
853–865, 2000.
[69] J. R. Volpicelli, “Uncontrollable events and alcohol drinking,”
British Journal of Addiction, vol. 82, no. 4, pp. 381–392, 1987.
[70] L. A. Pohorecky, “Stress and alcohol interaction: an update of
human research,” Alcoholism, vol. 15, no. 3, pp. 438–459, 1991.
