A longitudinal analysis of the impact of dietary physical activity on weight change in adults13 Robert
C Klesges,
Lisa
ABSTRACT analysis tivity,
and =
weight
investigation
change
Measures
and
alcohol
indicated
C Keith
between
1 52).
cigarette
Results
current
relationship
body
(n
women and
The of the
M Kiesges,
intake,
in adult
Linda
ac-
142)
=
were
pattern
physical
(n physical
men
intake,
consumption
a different
and
is a longitudinal
dietary
ofdietary
Haddock,
and
activity,
obtained
for
of predictors
3 y.
of weight
change for men vs women. For women a high dietary energy and fat intake as well as increases in total energy intake were related to higher weight gain and increases in work activity levels were
related
to decreased
weight
gain.
For
predicted
by increases
in dietary
fat intake.
discussed
as a possible
moderator
variable
AmfClinNutr
equation.
KEY WORDS energy
men
weight
Sex
gain
was
differences
in the energy
are balance
1992;55:818-22.
Body mass,
weight
change,
physical
activity,
intake
Despite
decades
be a common miologic 043),
above
the
85th
that
percentile alarming
overweight
tudinal
study
remains
tribute
because
of336
that individuals mortality from
Moreover,
and
419
it has long
figures suggested
risk for several
000
a 12-y
women
impact
polongi-
(2) indicated
of obesity
identifying
accumulation excess energy
assumed
have
overweight suffer increased heart disease, and cancer.
(3), research
been
to
y were
These
example,
that
treatment
factors
is needed. stores when
balance between energy intake and energy the sources of this imbalance are not fully ample,
(1).
studies
For
the long-term
weight develop
States aged 20-29
are at increased men
continues
epideto date (n
index
numerous
who are > 40% diabetes, coronary
because to body
mass
problems.
000
disappointing
Individuals
of body
medical
obesity
In one of the largest
in the United 30% of women
individuals
serious
research,
disorder.
of obesity of men and
23%
are especially tentially
of ambitious
nutritional
studies
28
=
there
that
often
documented
that
sume
the same
or less energy
viduals
Obese
individuals
are in their
because the studies largely cross-sectional nonobese subjects, 818
assess the impact of overall energy intake on estimated body weight accumulation. In the only prospective investigation of dietary intake and body weight to date, Colditz et al (1 1) found that recent prior weight weight
change was the strongest prospective predictor in a cohort of women. Levels of dietary intake
(4), but For ex-
intake
reports
obese
individuals than
appear
report
do their
of energy
intake
they
normal-weight
to be as accurate
of dietary
that
(10).
of body were not
related to body weight gain. Unfortunately, this study was not able to control levels ofphysical activity and included only selfreports of body weight. Whereas a clear relationship between excess energy intake and increased weight has not emerged in cross-sectional research, many recent investigations have examined whether obese and nonobese individuals differ in the composition of their diet. Generally, these studies investigated whether the percentage of the diet derived from carbohydrate and fat differ between obese and nonobese individuals. This literature indicated that both children (12) and adults (13, 14) having a dietary composition in carbohydrate
and
higher
in
fat
showed
higher
body
weight, regardless of the overall level of energy intake. Thus, examining dietary composition variables such as fat intake may be more important than total energy intake in predicting body fat accumulation. Given these promising initial findings, Iongitudinal investigations ofthe relative importance oftotal energy intake vs dietary composition are needed. Another common explanation for the accumulation of excess weight
is decreased
activity ation
energy
expenditure
(15).
Several
studies
between
less
physical
due
demonstrated activity
to reduced
a significant and
increasing large body ofstudies
physical
associrelative failed
weights (16-20). However, an equally to find a relationship between physical activity and body weight (21-25). As is true with the research on dietary intake and obesity, studies examining body weight have
the relationship
used cross-sectional
between data.
physical As such,
activity and longitudinal
is an im-
expenditure understood.
an excess
con-
leads to weight gain. This assumption has not been consistently supported in the literature. Cross-sectional investigations have
(5-9).
H Eck
lower
Introduction
intake and
conpeers
as lean
mdi-
Nevertheless,
concerning obesity and dietary intake are comparisons of the intake of obese and longitudinal research is needed to adequately Am J C/in Nuir
1992;55:818-22.
Downloaded from https://academic.oup.com/ajcn/article-abstract/55/4/818/4694368 by Washington University School of Medicine Library user on 08 April 2018
From the Center for Applied Psychological Research, Department of Psychology, Memphis State University, and the Department of Biostatistics and Epidemiology, University of Tennessee, Memphis. 2 Supported by National Heart, Lung, and Blood Institute grants HL39332 and HL-36553 (to RCK) and a Tennessee Centers of Excellence grant awarded to the Department of Psychology, Memphis State University. 3
Address
chological
versity,
requests to RC Klesges, Center For Applied PsyDepartment of Psychology, Memphis State UrnTN 38152.
all reprint Research,
Memphis,
Received
February
Accepted
for publication
Printed
in USA.
22,
1991. November
© 1992
American
21,
1991.
Society
for Clinical
Nutrition
WEIGHT models
may
with
help
changes
The
purpose
tudinal
impact
ious
physical ofadult
diet
physical
were
used
of the present
study intake,
energy factors,
cigarette
risk
of obesity
family males
and
data
to examine
were
and
physical
activity
their
was to examine dietary and
females.
activity
ditionally, because weight pact ofchanges in energy gain
intake
of total
and
a cohort
energy
weight.
activity
pregnancy, and
associate
in body
GAIN
alcohol
This
change
in repeated
relationship
to weight
in
because
assessments change.
294
men,
healthy,
largely
1 52 women)
who
middle-class
participants
24-42
y) whereas
(range
25-52
Review
at entry the
average
y). This
Board
into
study
was
age of male was
at Memphis
the study
subjects
approved
State
33.07
by the
y (range
was
Subjects
were
recruited
34.78
y
Institutional
physicians’
offices,
dition
to response
ments
placed
day
forms,
in local
by recommendations
them
forms
centers,
and
were
recruited radio
already
participating
subjects
project
were
collected
and
an initial briefing, subjects dietary intake and physical
and in the
Subjects
filled
were them out
for 3 y. mailed
examined
for omissions.
After
the yearly
for participating.
The
measures
obtained
to longitudinally
for visit
where their height, were recorded by a
On completing
physical-activity
the
once a year visit, their
completed additional measures activity. During the laboratory
trained exercise physiologist. visit, subjects were paid $60 periods
stations,
laboratory laboratory
were escorted to a private room and triceps skinfold measurements
assessment
In ad-
in the study, subjects and asked to complete laboratory.
to
by advertise-
on local
to the
and
churches.
newspapers,
questionnaires
diet
distributed
from
and came to the arrived at each
subjects weight,
response
care
On agreeing to participate a packet of questionnaires bring
laboratory
present
study
during
the
predict
weight
gain
taken
on both
men
a 2-y period.
Measurements Measurements
of height
and women (dressed research assistants. using
Sports
activity
34.78
± 4.73
2.63
± 0.75
2.28
± 0.60
a metal
0. 1 kg using was assessed
height
and
weight
were
in light clothing, without shoes) by trained Height was recorded to the nearest 1 cm rod.
a hospital-grade via self-reported
Weight
was
recorded
digital scale. Cigarette status and number
to the
± 4.15
7920.1 ± 2386.0 1892.94 ± 570.25 36.80 ± 6.12 2.74 ± 0.50 2.53
± 0.60
0.61 1. 18 ± 5.20 63.5
2.62 ± 0.74 4.30 ± 10.64
2.08
67.5 26.0
±
23.2 5.3
-
take
Subjects
completed
to
laboratory
over
the
previous
questionnaires
as
nearest
consumption smoked
per
self-reports
nutritionists
were
Downloaded from https://academic.oup.com/ajcn/article-abstract/55/4/818/4694368 by Washington University School of Medicine Library user on 08 April 2018
27). prior
available
each
assesses
in the laboratory
and to check for measures ofdietary
intheir visit.
to answer
the completeness intake were used
of the in this
high in fat has been found to relate to higher body fat in crosssectional studies (13, 14), the percent ofenergy intake consumed as fat was also used. Diet was evaluated at each of the yearly assessment
periods.
Physical activity
activity
was
assessed
(28).
The
Baecke
scale
by using
the
assessment
Baecke
physical-
is a factor-analyzed
scale comprising 16 items that represent physical activity at work, sport, and nonsport leisure time. Fifteen of the questions are
on a five-point
Likert-type scale (I = highly sedentary to ask how often one participates in various work, sport, or leisure activities. One question related to sport participation is open-ended and is given a value from 0.5 to 4.5 depending on the intensity and direction of the activity. The work factor asks questions concerning how much one stands, walks, and lifts heavy loads while at work. The sport factor asks based 5
=
highly
about
active)
and
participation
in sports,
including
activities
which
make
one sweat (ie, aerobic activity). Finally, the leisure factor asks how much time is spent in such nonsport, low-intensity activities as walking while at leisure. Low scores indicate low activity. The Baecke scale has been used extensively in recent years and has demonstrated a highly acceptable degree of reliability (3-mo test-retest for the scales averages 0.8 1) and construct validity (28-30). As with the diet variables, an average ofthe Baecke factors collected over the three assessment periods was used in the analysis. Statisticalanalyses Analyses
status
obese.
1-y (26,
Frequency
that
study. First, the average daily caloric intake of the subjects was used as a measure of total energy intake. Also, because a diet
their
were
33.07
Food
at each
parents
± 4.96 ± 13.74
Dietary intake was assessed with the WilIest’s Questionnaire (FFQ), a well-validated measure
day while alcohol intake was coded as whether or not subjects regularly ingested alcoholic beverages. Familial risk for obesity was assessed by subjects reporting whether zero, one, or two of biologic
24.83
65.98
SD.
subjects’ questions questionnaire. Iwo
subjects
questionnaires When subjects
over
activity
Trained
University.
through
15.69
ex-
Procedure
three
Leisure
S
in a study
cardiovascular risk in adults and their young children. there were 21 1 females and 206 males, but this number was reduced by attrition. As seen in Table 1, average age of the
used
±
8717.3±2911.8
Fat intake (%) Work activity
Caucasian
participated
± 4.32
2083.49 ± 695.94 35.97 ± 5.40
(kcal)
amining Initially
and
27.8
Family risk (% one or more obese) Pregnancy status (% pregnant)
were
Women (n = 152)
86.48
Cigarettes smoked (n/d) Alcohol consumption (% yes)
(142
study. mailed
models
(Id)
investigated.
Subjects
local
for longitudinal
Body mass (kgJm2) Body weight (kg) Age (y) Energy intake
Ad-
process, the imactivity on weight
Subjects
female
variables
Men (n = 142)
Methods
adults
1
Baseline
var-
is unique
obtained
change is a dynamic intake and physical
TABLE
consumption,
weight
study
819
the longi-
composition,
on body
IN ADULTS
mass
initially
(in kg/m2)
identified
at each
year were gender (0
=
no,
1
=
yes),
cross-sectional
year.
(0
Potential =
male,
cigarette
predictors
predictors
1 and
=
female), alcohol
of body
for body
mass
age, pregnancy consumption
(0
KLESGES
820 TABLE 2 Cross-sectional
of body
mass
Coefficient
SE
2.005 -0.993 -0.924
0.752 1.885 0.538
2.465 0.637 0. 15 1 1.276 -0.8 1 1
0.895 2.477 0.070 0.804 0.533
2.028 0.160 0.173
0.980 1.870 0.081
Year I (n = 211) Family risk Pregnancy Sports activity Year2(n 169)
Significance
I
Pregnancy
Percent energy as fat Work activity Leisure activity Year3(n= 153) Family risk Pregnancy Percent energy as fat = 206) intake energy as fat 155)
no,
0.202 1.164
yes),
=
family
2.665 -0.527 -1.719 2.755 0.257 2. 150 1.588
0.0065 0.7976 0.0330 0.1143
I .52 I
0.1303
2.069 0.086 2.144
0.0402 0.9318 0.0337
-2.499 4.091
0.0123 0.0001
-
x i0 0.049
0.0083 0.5988 0.0871
1 . 139
0.756 0.065 0.522
1.540 3.687 2. 182
0.1256 0.0003 0.0307
0.147
0.062
2.385
0.0184
0.241
138) energy as fat
1
4.22
-0.001
Alcohol Percent energy as fat Work activity
=
risk
of obesity
(no
parents
obese
vs one
or two parents obese), energy intake, percent of energy intake as fat, sports activity, work activity, and leisure activity. Twoway interactions between gender and other predictors were also considered. Longitudinal analyses of weight change over 2 y included all baseline predictors as described above. In addition, scores of change from baseline to year 3 for these variables were eligible for model inclusion: energy intake, percent of energy intake as fat, work activity, leisure activity, sports activity, and cigarettes smoked per day. Change in alcohol consumption was coded as two contrasts; the first compared those who began to consume alcohol with those with no change in consumption and the seeond compared those who stopped consuming alcohol with no change in consumption. Additionally, pregnancy status for women was coded as two contrasts: women who became pregnant (n 8) vs no change in status (n 1 38) and women who were pregnant at baseline and not at year 3 (n 6) vs those without change in pregnancy status. =
Initial
variables for both separate gitudinal other
=
models
including
two-way
variables
were
by using
a stepwise
regression
women,
pregnancy
status
were
interactions
with
predictor
and gender indicated several significant interactions cross-sectional and longitudinal models. Subsequently, models for males and females were analyzed. For lonmodels, initial body weight was forced to enter while
predictor
forced
to enter
the
eligible
for inclusion
in the model
(P to enter as well as initial
algorithm
contrasts
=
0. 15). For weight
body
model.
Results Cross-sectional
analyses
Cross-sectional in Table
=
body
Family risk
Year3(n= Percent
of body mass. Women with one or two obese parents had higher body mass (adjusted mean 26.34) compared with those with no parent obese (adjusted mean 24. 19). Percent of energy intake as fat was also predictive ofbody mass for females at years 2 and 3. Higher fat intake was associated with increased =
Women
Energy Percent Year2(n=
AL
predictor
predictors
Predictor
Men Year I (n
El
2. Family
predictors risk
for women of obesity
at each year can be seen
is a strong
and
consistent
Downloaded from https://academic.oup.com/ajcn/article-abstract/55/4/818/4694368 by Washington University School of Medicine Library user on 08 April 2018
mass.
A 5%
increase
in fat
intake
was
associated
with
a
of 0.75 kg/m2. Table 2 also presents cross-sectional predictors of body mass for men. Percent of energy intake as fat was consistently predictive ofbody mass. Similarly to that found for women, higher fat intake was associated with higher body mass at each year. A 5% increase in fat intake was associated with a body mass increase of 1 kgJm2. Family risk of obesity was not predictive of body mass for men. body
mass
increase
Longitudinal
analyses
Weight gain The longitudinal
for women over 2 y was 1.37 ± 5.89 kg (i ± SD). regression model explained 32.4% ofthe total variability ofthis weight change (F13 6.101, P < 0.0001). As seen in Table 3, women with higher baseline body weights had less weight gain over 2 y. Not surprisingly, women who became pregnant gained weight and those initially pregnant lost weight at the follow-up compared with those with no change in pregnancy status. Higher baseline energy intake and percent of energy intake as fat was found to be related to increased weight gain. An inverse relationship was found between weight gain and work and leisure activity at baseline. Specifically, higher work and leisure activity was associated with lower weight gain. Three change variables were associated with weight gain in women. As energy intake increased from baseline, weight gain increased. For increases of836.8 Id (200 kcal) in energy intake, resultant weight gain over 2 y was 2.206 kg. In addition, as =
cigarette
were
consumption
seen.
crease
decreases Weight gain
in work
activity
over
for men over 2 y tended women (F112921 = 3.22, P
kg) than
reductions
in weight
gain
2 y.
to be less (0.265 =
0.07).
The
±
4.546
longitudinal
3
Predictors
ofweight
change
Predictor
Women
large
of five cigarettes resulted in a 1.586 kg deover 2 y. Higher weight gain was also associated
in weight
with
TABLE
increased,
Increases
(n
=
Coefficient
SE
t
Significance
152)
0.617 -0.036
Intercept Baseline
weight Became pregnant Bore a child
10.002 -9.657
Energy intake Percentenergyasfat Work activity Leisure activity Sportsactivity Change in energy Changeinworkactivity
Change in cigarette consumption Men(n= 142) Intercept Baseline weight Energy intake Sports activity Changeinenergyintake
Change in fat intake
-
0.057 1.141 2.919
0.9550 0.2557 0.0041
0.527
3.137 0.002 0.157
-3.538 -6.181 3.020
2.098 1.646 1.581
0.005 -5.868
0.002 2.536
2.207 -2.314
0.0289 0.0221
-0.707
0. 179
-3.946
0.0001
0.004
intake
10.909 0.032 3.426
-3.078 2.065 3.353
0.0025 0.0407 0.0010
1.687 -3.756 1.910
0.0939 0.0003 0.0582
-
12.95
6. 179
2.096
-0.053
0.024
-2.229
-0.003
0.001 1.094 0.001
-2.290
1.856 -0.002
0.383
0.165
1.697 -1.573 2.324
0.0379
0.0274 0.0235 0.0920
0.1181 0.0216
WEIGHT regression
model
oftheir
weight
Table gain.
3, higher Additionally,
increased
related
fat intake
explained
(F15,1361
12.0% 3.720,
=
ofthe
gain
over
total
activity
2 y. Higher
As seen
baseline
in
less weight
was
related
energy
IN
to
intake
atic
reports
family
risk
to increased
weight
was
weight
increased,
weight
gain.
Positive
in weight
changes
of 0.86
gain
of 5% in
kg.
current
weight that
investigation
dietary change
higher ergy intake energy
the relationships
body mass, The results
design. predictors
ofbody
and body
would
indicated
sure
mass
were
an
risk
baseline energy from fat, lower
intake,
decreases
arette
consumption.
itively
associated
a higher of sport
in work
intake from fat, were inconsistent
and
percent increases
decreases
not surprisingly,
weight
predictor
baseline activity,
activity,
Pregnancy, with
cross-sectional
intake, levels
gain.
ofbody
For
men
the only
enin
in cigconsistent
although total energy intake and work activity predictors (ie, one year and not another). In-
one
striking
in the
pattern
ofbody
the diet from fat predicted women’s men’s body mass for 3 of 3 y. More
body mass importantly,
to weight weight
2 of
3 y and fat intake (or
by the energy
was
gain gain
in men;
significantly
balance
gain in women. In men the only predictor was a positive relationship
significant between
at year
weight
2. This
pattern
(P
men
women
0.09)
=
respond
and
(P
women
to weight
gain
interest
was the finding
much
longitudinal
lower
analyses).
than
This
that
the explained
in women
may
indicate
variability
activity Future
increases research
little
sport,
leisure,
focus
of future
Finally, sumption
is known
and
about
work
cigarette
consumption
in weight
gain.
0.06).
=
for women. for total
An illustration energy
a relationship
intake between
pothesized direction dietary intake over
is the very as a predictor energy
intake
results gain.
weight
gain
in the hy-
termine more
predicted if other predictive
decreased factors,
weight such
of weight
gain.
Future
as resting gain
in men
underscores
weight is much This could also
studies
should
energy
expenditure,
than
in women
deare or
Downloaded from https://academic.oup.com/ajcn/article-abstract/55/4/818/4694368 by Washington University School of Medicine Library user on 08 April 2018
men
if
costs
with
muscle Ad-
of various
should
be the
a marked
cigarettes
reported
more indicate
decrease
smoked
in weight
the
over
was
a 2-y
relationship
as-
period.
between
findings impact
are consisof smoking
powerful in women a different metabolic
energy
predictors
possible
and women
weight
than men response
are differentially
balance gain
of weight
implication
equation.
is a highly
The complex
gain
were
of current
affected findings
highly
findings
is
by components seem to suggest
phenomenon
and
lends
support to contentions that a single cause for obesity is not likely to be found ( 1 5). Moreover, gender may represent only one potential moderating factor associated with weight gain. It is possible that race, socioeconomic status, age, and other demographic and behavioral factors may all moderate predictors of weight gain.
Information
our knowledge in adults.
contrast, in men energy intake was inversely related to weight gain: higher baseline intake and dietary intake increases over time
finding
of the that
obtained
partici-
to smoking in men than in women (33, 34). To summarize, dietary fat consistently predicted body mass and weight gain in both men and women. Beyond this one con-
that
In women
men
their
metabolic
of five
kg decrease
One
disparate and
a 1.586
however,
as women increased their body weight increased. In
was observed: time, subsequent
with
specific.
of weight
Perhaps
(3 1, 32) and
associated
increase
finding,
measured predictors (eg, metabolic rate) that are more operative than ingested energy intake and physical activity for men than
that gain
to counteract this change increased participation in
the
activities
was
Every
sistent
men’s self-reports less reliable than are different, un-
to be
there was a strong relationship between cigarette conand weight gain in women but not in men. Increased
gender
the independent variables in men (for example, of dietary intake might be unreliable or women’s). Another possibility is that there
and
credence
research.
greater
among
adds
weight in the form of increased should investigate these hypotheses.
( 12% vs 32% on the error
lei-
to weight
physical-activity work activity
by increasing
pation in sports activity in an effort in weight. Another possibility is that
on body (34, 35).
in both
Greater
differently from women. However, it was also observed greater sports activity tended to be related to greater weight
This
and be-
men and women, there were also a number ofdifferences in the pattern ofbody mass and weight gain between men and women. was
activity
the speculation that males’ reports of physical activity may less reliable than females or that men answer the questionnaires
smoking and body weight (33). The current tent with recent reports indicating that the
in men
physical
of results
that fat intake is critically important to weight-loss efforts confirms previous cross-sectional studies on the relationship
Of most
In women,
longitudinally.
related
sociated
predictor
cross-
was not baseline
as baseline
equation.
changes in fat intake) predicted changes in body weight in both men and women. The current results lend credence to the notion
tween fat intake and body weight (12-14). Although intake from fat was a consistent
mass
decreased.
negatively
ditionally,
mass
The most consistent change in both men of the diet from fat. The percent of
was the percent
related subsequent
be predicted
sports mass.
in both men and women. mass and body weight
and weight change predictor of body
and women
similarity
to body
family risk Similarly,
and
and
in body weight over time were related to a lower baseline weight, a lower baseline energy intake, and an increase in dietary fat intake over time. was
inversely
related
In contrast, for any year.
was not related to weight gain were also curious relationships between
in both
of energy
creases
There
was positively
for 3 y in women. men’s body mass
activity
body
was also pos-
was the percent
mass
or system-
and weight change in both men and women. In general, womens’ physical activity was related to body weight in a direction that
for obesity and a higher percent of energy fat. Increases in body weight over time were related
from
to a
activity,
cross-sectional
family
intake
to evaluate
physical
in a longitudinal
for women
increased
sought
intake,
to random
weight
There
Discussion
are subject
of other differences in the predictors of gain in men vs women. For example,
for obesity
sectionally related to
2 y resulted
intake
There were a number body mass and weight
baseline
The
ofdietary
bias.
in energy intake were associated with decreased Increases in the percentage of energy intake as fat over
between
821
ADULTS
men’s
variability
P 0.0035). associated with
baseline weight was higher baseline sports
weight
and increases weight gain. were
for men change
GAIN
about
such
concerning
In addition,
treatments
on the wrong energy balance moderators such as gender. models to diet and gain, should include
activity potential
moderator
the causes
variables
may
ofaccelerated
for obesity
could
weight place
refine
gain
emphasis
components ifthey do not consider Future research, rather than limiting variables moderator
when predicting weight variables in their mod-
822
KLESGES
els, thus possibly more correctly specifying cess. Future research would also be enhanced cohorts
of individuals
creasing
our
ability
In addition, casian focus,
over
is much
more
to more
nally,
one
diture,
on black
greater
the energy activity,
sample
potentially not
larger
thereby
resting
variable,
resting
(ie, including
energy
incidence
at large
should
expenditure)
energy
in subsequent gain
750 3.
000
men
Brownell Pi-Sunyer
trition
L. Variations
20.
studies,
and body 0
FX.
Obesity.
and
In: Shils
disease.
NE,
by weight
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in-
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the
in white
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important
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than
sex-specific
included
our knowledge fat accumulation
women,
in black
generalizable
was
by following
periods
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to detect
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