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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Philadelphia:

Am

among Med

VR, eds. Modern nuLea & Febiger, 1988:

16.

Kaufmann

NA,

Poznanski

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and

opinions of teen-agers on nutrition and obesity. J Am Diet Assoc l975;66:264-8. 6. Kromhout D. Energy and macronutrient intake in lean and obese middle-aged men (the Zutphen study). Am J Clin Nutr 1983;37: 295-9. 7. 8.

W. Dietary intake JE. Caloric intake,

Kulesza Lincoln Nutr

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AJ, Waxman M. Accuracy of self-reports of food intake. l98l;79:547-51. 10. Myers Ri, Klesges RC, Eck LH, Hanson CL, Kiem ML. Accuracy ofself-reports offood intake in obese and normal weight individuals: effects of obesity on self-reports of dietary intake in adult females. Am J Gin Nutr l988;48:1248-5l. I 1 . Colditz GA, Willett WC, Stampfer Mi, London Si, Segal MR, Speizer FE. Patterns of weight change and their relation to diet in a cohort ofhealthy women. Am J Clin Nutr l990;5l:l 100-5. 9.

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1972;25:390-4.

AL

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physical

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in mortality

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By completing

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ofthe processes leading should be enhanced.

of

(36).

equations.

research.

16.

in-

women

prediction

in the present

equation

the

in white

of the population

important

balance and

of time,

because

than

sex-specific

included

our knowledge fat accumulation

women,

in black

generalizable

was

by following

periods

changes in body weight fluctuation. be stressed that only middle-class, Cauused in this research. Future research should

representative

lead

pro-

to detect

it should

subjects were for example,

obesity

longer

the weight-gain

El

Diet

1982;36:936-42.

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JAH, van Staveren WA, Burema J. Food consumption, habitual physical activity, and body fatness in young Dutch adults. Am J Gin Nuts 1983;37:278-86.

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