Am J C/in Nuir 1992;55:943-9. Printed in USA. © 1992 American Society for Clinical Nutrition 943

Associations of body fat and its distribution with dietaryintake, physical activity, alcohol, and smokingin blacks and whites13

Martha L Slattery, Arline McDonald, Diane E Bud, Bette JDavid R Jacobs Jr, and Kiang Liu

ABSTRACf Cross-sectional associations between body fat

and its distribution and environmental factors influencing energybalance were examined in 5 1 1 5 young adults. Protein was di-

rectly associated with body mass index (BMI) in all race and sex

groups (P < 0.01) after age, education, cigarette-smoking status,alcohol intake, and physical activity were adjusted for. Carbo-hydrate intake was inversely associated with BMI in males (P

= 0.02). Total physical activity was inversely associated with

BMI in white women and with skinfold-thickness measures (P< 0.01) in all groups. Waist-to-hip-circumference ratio (WHCR)was positively associated with total kilojoules (kilocalories) inwomen, inversely associated with percent of kilojoules (kilocal-

ories) from carbohydrates in whites, grams of crude fiber/4 184

Id (1000 kcal)(except in black men), and physical activity (exceptin white women). WHCR was directly associated with cigarettesmoking except in black men, and with total alcohol intake in

men. Beer was consistently associated with WHCR in all race

and sex groups. Am J Clin Nutr l992;55:943-9.

KEY WORDS Alcohol, body fat, cigarette smoking, dietary

intake, physical activity

Introduction

The relation between total body fat and the development ofcardiovascular disease (CVD) as well as risk factors for developing

cardiovascular diseases is well established (1, 2). Limited datasuggest that the distribution of fat at various sites within thebody also may be related to the risk of developing CVD (3-6).

Both genetic and environmental factors contribute to body sizeand body-fat distribution (7, 8). Environmental factors such asenergy intake and energy expenditure are related to total body

size in older adults (9, 10), although their role in body-fat dis-tribution has not been thoroughly examined. Recent studiessuggested that smokers have more abdominal adiposity than dononsmokers, despite smaller body sizes (1 1, 12). This finding

supports the possibility that cigarette smoking influences body-fat distribution as well as overall body size.

The primary hypothesis of this study was that when energy

balance is not maintained, the distribution ofbody fat is affectedin addition to overall body size. Therefore, the relationships be-

tween body fat and its distribution, as reflected in the waist-to-hip circumference ratio (WHCR), with cigarette smoking and

with factors contributing to energy balance, total energy intake

Caan, Joan E Hilner,

[kilajoules (kilocalories)], and energy expenditure (physical ac-

tivity) were examined. It is hypothesized that energy-yielding

nutrients, including alcohol, are not only associated with body

fat but also with its distribution. Physical activity, a key deter-

minant of energy expenditure, was examined as a factor that

could impact on body fat and its distribution. To examine these

hypotheses, data from a biracial population ofyoung adult men

and women aged 18-30 y who are participants in the ongoingnational collaborative study on Coronary Artery Risk Devel-

oprnent in Young Adults (CARDIA) were used.

Methods

Data for these analyses were obtained during the baseline ex-

amination of the CARDIA study, which was conducted during

1985 and 1986. The study population consisted of black (52%)

and white (48%) individuals from Birmingham, AL; Chicago,

IL; Minneapolis, MN; and Oakland, CA. At the baseline ex-amination the study population consisted of46% men and 54%

women; 40% with a high school education or less and 60% with

more than a high school education; and 45% aged 18-24 y and

55% aged 25-30 y. At subsequent examinations it was discovered

that 62 people were slightly older or younger than 18-30 y at

baseline; these people are included in these analyses. The study

C From the Department of Family and Preventive Medicine, School

of Medicine, University of Utah, Salt Lake City; the Department ofNutrition and Medical Dietetics, University ofillinois, Chicago; National

Heart, Lung, and Blood Institute, Division ofEpidemiology and ClinicalApplications, Bethesda, MD; the Division of Research, Kaiser Perma-nente Medical Care Program (Northern California Region), Oakland,CA; the CARDIA Coordinating Center, University of Alabama atBirmingham; the Division of Epidemiology, University of Minnesota,Minneapolis; and the Department ofCommunity Health and PreventiveMedicine, Northwestern University Medical School, Chicago.

2 Supported by contracts N01-HC-48047, N0l-HC-48048, N01-HC-48049, NOl-HC-48050, and NOl-HC-95095 from the National Heart,Lung, and Blood Institute, National Institutes of Health, and a smallresearch award from the Department ofFamily and Preventive Medicine

at the University of Utah.3 Address reprint requests to ML Slattery, Department ofFamily and

Preventive Medicine, School ofMedicine, University ofUtah, Salt Lake

City, UT 84132.Received August 8, 1991.Accepted for publication October 16, 1991.

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944 SLATTERY ET AL

was designed so that methods of data collection were the same

for all centers; however, recruitment methods were center-spe-

cific. Study design and recruitment methods were reported in

detail elsewhere (13). Because ofthe study’s goals and recruitment

methods, results from this study pertain to black and white young

adults with a wide range ofyears ofeducation and income. The

methods used to obtain the data presented here are described

below. The study was conducted according to the ethical guide-

lines of the participating study centers.

Dietary intake

Dietary-intake data were obtained from a detailed diet-history

questionnaire developed for the CARDIA study (14). Study par-

ticipants were asked to recall their usual intake during the past

month by reporting amounts, frequency, and methods of prep-

aration of foods consumed. Quality-control methods concerningthe administration of the questionnaire and the results of the

study on comparative validity ofthe questionnaire were described

previously (1 5, 16). Food items were converted to nutrients by

using the University of Minnesota Nutrition Coding Center nu-

trient database tape 10(17). Alcohol intake was estimated from

the diet-history questionnaire and was expressed as grams of

alcohol consumed per day. A second estimate of alcohol intakewas obtained from a separate questionnaire, which defined al-

cohol intake in terms of the number of drinks of various typesof alcohol consumed per week. Both estimates of alcohol were

used in these analyses.

Physical activity

Individual physical activity was ascertained by using a phys-

ical-activity history questionnaire describing various types of ac-

tivities performed over the past year. This questionnaire was

developed for the CARDIA study (18) and was patterned after

the Leisure Time Physical Activity Questionnaire developed by

Taylor et al (19) to ascertain the type of activities engaged in

and the degree of intensity of performance. Activities weregrouped into moderate and intense categories, depending on the

predetermined energy expenditure associated with them. For

example, jogging was classified as intense activity whereas bowl-ing was considered an activity requiring a more moderate degree

ofenergy expenditure. Physical-activity units were calculated bymultiplying the number of months the activity was performedfor more than 1 h by the degree of intensity assigned to the

activity (20). Data from a test with a symptom-limited exercise

treadmill were used as an estimate of physical fitness. Scores for

total activity and for the subset of intense activities were signif-

icantly associated with performance during the exercise treadmill

test, as assessed by the duration sustained on the treadmill (20).

Anthropomeiric measures

Body weight was measured to the nearest 0.2 kg with a cali-

brated scale while subjects wore light clothing; height was mea-

sured to the nearest 0.5 cm with a vertical ruler while subjects

were not wearing shoes. Triceps, subscapular, and suprailiac

skinfold thicknesses were measured to the nearest millimeter

with calibrated Harpenden calipers. Each skinfold thickness was

measured twice at standard sites on the right side of the partic-ipant. Fifty millimeters was used as the value indicating that

skinfold thickness was too thick to measure, because this was

the maximum that could be measured with the calipers. Waist

circumference was measured in duplicate to the nearest 0.5 cm

at the minimum abdominal girth. Hip circumference also was

measured in duplicate to the nearest 0.5 cm at the maximum

protrusion of the hips at the level of the buttocks. The averages

of the duplicate measurements for skinfold thicknesses and for

WHCRs were used in the analyses.

Several indicators of total body fat and of location of body

fat were used in these analyses. The two measures of total body

fat or body size used were body mass index (BMI), calculatedas weight (kg)/height (m2), and the sum ofthe averages for skin-fold thicknesses from each ofthe three sites. Each skinfold mea-

surement site also was evaluated separately. The WHCR was

used as an indicator of central adiposity. Forty-five individuals

were excluded from the analyses of central adiposity because

their WHCR values were well outside the overall distribution

for this variable; the waist and hip circumference values were

considered errors in recording a WHCR > 1.05 for 1 3 black

men and for 10 white men; a WHCR > 1.0 for 15 black women

and for 7 white women).

Other variables

Demographic variables examined were educational level, race,

age, and sex. Smoking status was obtained from a self-reported

smoking history and subjects were classified as having never

smoked or as exsmokers or current smokers. The usual number

ofcigarettes smoked per day was used in some analyses to control

for smoking. Because cigarette smoking can alter basal metab-

olism and thus influence energy balance (2 1 ), smoking status is

presented.

Methods of analyses

Analyses of the selected variables were performed for each

sex and race stratum of the population. Regression techniques

were used to determine the associations of body fat and its dis-

tribution with dietary factors, physical activity, alcohol, and

smoking (22). Both linear and quadratic associations were cx-

amined. Dietary-intake variables were expressed as a percentage

of total calories from fat, protein, or carbohydrate and as theamount ofcrude fiber per 4184 kJ (1000 kcal). We used nutrient-

density measures to standardize for caloric consumption. Crude

fiber was examined along with the energy-yielding nutrients be-cause it could alter fat absorption. Alcohol was examined as the

number ofgrams consumed per day, grams consumed per 4184

kJ (1000 kcal), and drinks consumed per week. A 0.360-L beer,

a 0. l2-L glass ofwine, and 0.0045-L ofliquor were each defined

as one drink. To determine whether associations between skin-

fold-thickness measurements and WHCRs were independent of

overall body size, BMI was controlled in the analyses of those

anthropometric measures. Total physical activity, alcohol,

smoking status, and total caloric intake were assessed in the

same model to determine the independent effects of each of

these variables on body fat and its distribution. Dietary com-ponents were then substituted in the model for total caloric intake

to determine their independent associations with body fat andits distribution. Alcohol-intake variables and physical-activity

units were transformed by using a log transformation before

analyses because the distributions ofthese variables were skewed.

When it was necessary to categorize data, the race- and sex-

specific distributions for those variables were divided into ap-

proximate quartiles.

Results

The mean and the standard error of the study variables aregiven in Table 1 . Black men had smaller tricep and suprailiac

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BODY FAT AND ITS DISTRIBUTION 945

TABLE 1Values for selected variables, by race and sex*

Black men

(n= 1134-1157)

White men

(n= 1157-1171)

Black women

(n= 1393-1479)

White women

(n= 1286-1306)

AnthropometryBMIt 24.6 ± 0.13 24.3 ± 0.10 25.9 ± 0.17 23.1 ± 0.12�

Triceps (mm) 10.8 ± 0.19 12.3 ± 0.18f 22.2 ± 0.27 20.2 ± 0.22�

Subscapular (mm) 13.8 ± 0.21 13.6 ± 0.19 20.0 ± 0.29 15.2 ± 0.23�Suprailiac (mm) 16.3 ± 0.31 19.4 ± 0.30f 20.5 ± 0.31 17.8 ± 0.27�

Sum ofskinfold thicknesses (mm) 40.4 ± 0.66 45.1 ± 0.59� 61.5 ± 0.82 52.7 ± 0.65�

Waist-to-hip ratio 0.817 ± 0.001 0.839 ± 0.OOlf 0.742 ± 0.002 0.726 ± 0.00l�Dietary intake

Energy (kJ) 16 903 ± 298 13 774 ± l75� 10 837 ± 149 8 937 ± l03�

Fat (% Id) 38.2 ± 0.17 37.3 ± 0.l7t 37.7 ± 0.16 36.5 ± 0.l8�Protein (% Id) . 14.4 ± 0.07 15.3 ± 0.07f 14.2 ± 0.07 15.4 ± 0.08�Carbohydrate (% kJ) 45.0 ± 0.21 44.8 ± 0.20 47.7 ± 0.20 46.8 ± 0.2011

Crude fiber (g/4l84 Id) 1.7 ± 0.02 2.1 ± 0.02f 2.0 ± 0.02 2.6 ± 0.04�Starch(g/4l84kJ) 17.9±0.13 l8.7±0.l5� 17.4±0.12 18.3±0.14*

Alcohol (g)1J 17.5 ± 0.94 16.8 ± 0.70 5.5 ± 0.33 8.5 ± 0.32*

Physical activity (PA units)

Total activity 534.9 ± 10.1 509.7 ± 8.8 277.8 ± 5.9 399.5 ± 7.2*

Moderate activity 158.1 ± 3.6 168.1 ± 3.2cc 108.0 ± 2.4 143.9 ± 2.7*

Intense activity 376.7 ± 7.7 341.6 ± 6.9t 169.9 ± 4.4 255.7 ± 5.7�

Smoking status

Current smoker (%) 36.9 [423] 26.5 [307]j 31.3 [461] 27.3 [355]**Exsmoker (%) 9.3 [106] 15.7 [l82]t 8.6 [127] 20.1 [26lJtNever smoked (%) 53.8 [616] 57.8 [67l]** 60.1 [885] 52.7 [685]f

C �; � SE. n in brackets.

t In kg/m2.tee Significantly different from black men: �P < 0.001, **� < 0.05.

§11Significantly different from black women: P < 0.001, lIP < 0.01.#{182}No alcohol consumption was reported by 277 black men, 172 white men, 525 black women, and 231 white women.

skinfold measures and WHCR than did white men. White

women had smaller BMIs, smaller skinfold measurements for

each site measured, and smaller WHCRs than black women.

Blacks consumed diets higher in total kilojoules (kilocalories)and percentage of kilojoules (kilocalories) from fat and from

carbohydrate than their white-sex counterparts. Women con-

sumed more crude fiber per 4184 Id (1000 kcal) than did men;

white individuals consumed more crude fiber than did African

Americans. Men consumed more alcohol, both in volume and

as a percentage ofcalories, than did women. Men reported more

total physical activity as well as more activities of an intense

nature than did women, with black women reporting the smallest

amount ofphysical activity. The majority ofthe study population

(50-60%) reported never having smoked cigarettes; blacks as a

group had the greatest number of current smokers.

The mean BMI, WHCR, and sum of skinfold thicknesseswithin race- and sex-specific quartiles of total energy intake,

physical activity, alcohol intake, and cigarette-smoking status

are shown for blacks in Table 2 and for whites in Table 3. Energy

intake was inversely associated with BMI (P � 0.03) amongblacks and was directly associated with WHCR in women (P

< 0.001). Reported total physical activity was negatively asso-ciated with the sum of the skinfold measurements as well as

with each of the three individual skinfold measurements in all

race and sex strata (P � 0.002; data not shown). Men who con-sumed 13-26 g alcohol/d or one to two drinks per day had larger

WHCRs than did men who did not consume alcohol or who

consumed lower amounts of alcohol per day (P < 0.0 1). The

upper quartile of total alcohol intake in women was less than

one drink per day. Current smokers had larger WHCRs than

did exsmokers or individuals who never smoked. Although qua-

dratic associations were examined between these environmental

variables and the body-size variables, we did not observe any

statistically significant quadratic associations that were not also

significant linearly.

To further explore the associations of body fat and its distri-

bution with dietary intake and physical activity, energy-yielding

components of the diet and different intensities of energy ex-

penditure were examined in multivariate-regression analyses

(Table 4). Protein intake, as a percentage of kilojoules (kilocal-

ories) consumed, was directly associated with BMI in all race

and sex groups (all P values � 0.02). Total carbohydrate intake

was significantly inversely associated with BMI among men.Carbohydrate intake was inversely associated with WHCR in

whites and crude fiber intake was significantly inversely asso-

ciated with WHCR in all groups ofthe population except black

men (Table 4). No dietary factors were consistently associatedwith the skinfold measurements across race and sex groups (datanot shown).

Activities of both a moderate and intense degree were not

significantly associated with BMI. Activity of a more intense

nature was inversely associated with WHCR in all groups exceptfor white women. Similar patterns of association were notedwhen duration on the treadmill was used as an indicator of

physical activity rather than reported intense physical activity.

Activities ofa moderate nature were not associated with WHCR

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TABLE 2

Values for anthropometric variables within the categories energy

intake, physical activity, alcohol, and smokingstatus for blacks

Sum ofskinfold

BMI thicknesses WHCR

TABLE 3Values for anthropometric variable within the categories energy

intake, physical activity, alcohol, and smoking status for whites*

Sum ofskinfold

BMI thicknesses WHCR

Men MenEnergy intake (kJ)t Energy intake (kJ)t

�107l9 25.1 41.0 0.818[286] �9707 24.5 45.0 0.837 [286]

10720-14489 24.5 40.2 0.8l7[28l] 9708-12719 24.3 45.7 0.838 [285]

14 490-20 079 24.4 40.2 0.816 [282] 12 720-16 242 23.9 44.6 0.840 [292]>20 079 24.3 40.6 0.816 [278] > 16 242 24.3 44.6 0.835 [284]Linear trend P 0.03 0.77 0.53 Linear trend P 0.27 0.49 0.51

Physical activity (PA units) Physical activity (PA units)�270.5 24.6 42.9 0.817 [288] �288 24.3 48.1 0.838 [286]270.6-471.0 24.8 41.2 0.817 [279) 288.1-462.5 24.1 46.0 0.843 [286]471.1-723.0 24.2 39.7 0.817 [284] 462.6-672.0 24.0 44.6 0.838 [291]>723.0 24.6 38.1 0.816 [276] >672.0 24.6 41.2 0.835 [284]Linear trend P 0.7 1 <0.001 0.77 Linear trend P 0.43 <0.001 0.03

Alcohol intake (g/d) Alcohol intake (g/d)None 24.7 41.7 0.813 [271] None 24.4 47.2 0.837 [170]0.1-6.26 24.8 40.1 0.815 [295] 0.1-10.17 24.1 44.9 0.834 [408]

6.27-21.1 24.0 39.9 0.815 [280] 10.18-23.0 24.1 43.7 0.839 [288]

>21.1 24.7 40.4 0.823 [281] >23.0 24.6 45.0 0.845 [283]Linear trend P 0.62 0.28 0.01 Linear trend P 0.59 0.04 0.009

Smoking status Smoking status

Current smoker 24. 1 39.3 0.8 18 [409] Current smoker 24.0 44.4 0.847 [304]Exsmoker 24.8 40.9 0.817 [104] Exsmoker 24.0 45.0 0.836 [180]Never smoked 24.9 41.3 0.816 [604] Never smoked 24.5 45.2 0.835 [663]Overall P 0.02 0.08 0.7 1 Overall P 0.09 0.64 <0.001

Women WomenEnergy intake (Id) Energy intake (Id)

�6807 26.3 62.6 0.733 [365] �6594 23.3 52.6 0.722 [323]6808-9410 26.4 61.3 0.741 [357] 6595-8263 23.1 52.0 0.722 [323]9411-13443 25.9 59.9 0.744[362] 8264-10602 23.1 53.6 0.726 [324]

> 13 443 24.9 62.4 0.748 [363] > 10 602 22.7 52.8 0.735 [314]Linear trend P 0.003 0.61 <0.001 Linear trend P 0.10 0.51 <0.001

Physical activity (PA units) Physical activity (PA units)

� 103.0 25.8 63.2 0.749 [364] �208 23.6 54.7 0.729 [325]103.1-228.0 25.9 62.1 0.742 [365] 208.1-351.0 22.9 53.9 0.724 [319]228.1-396.0 26.0 62.6 0.739 [364] 351.1-543.0 23.1 52.1 0.725 [322]>396.0 25.8 59.4 0.736 [354] >543.0 22.7 50.2 0.728 [318]Linear trend P 0.89 0.002 <0.001 Linear trend P 0.02 <0.001 0.66

Alcohol intake (g/d) Alcohol intake (g/d)None 26.2 62.7 0.742 [516] None 24.1 53.3 0.729 [227]0.1-1.39 25.3 61.3 0.740 [212] 0.1-4.7 23.0 52.4 0.726 [418]1.40-5.58 25.5 61.0 0.740 [359] 4.8-12.0 22.7 52.1 0.725 [320]>5.58 26.1 60.6 0.742 [360] >12.0 22.8 53.6 0.727 [319]Linear trend P 0.91 0.07 0.95 Linear trend P 0.0004 0.87 0.54

Smoking status Smoking status

Current smoker 25.6 59.8 0.747 [45 1] Current smoker 23.4 50.7 0.732 [350]Exsmoker 25.3 62.2 0.742 [124] Exsmoker 23.2 53.9 0.725 [259]Never smoked 26. 1 62.3 0.738 [872] Never smoked 22.9 53.4 0.723 [675]Overall P 0.24 0.03 0.01 Overall P 0.24 0.004 0.008

946 SLATTERY ET AL

C Adjusted for age, education, alcohol, smoking, energy intake, and

physical activity; skinfold measurements and waist-to-hip ratio (WHCR)are also adjusted for BMI by linear-regression technique. n in brackets(n values for BMI are slightly higher than and n values for sum of skinfold

thicknesses are slightly lower than the n values given for WHCR).

t Categories divided into approximate quartiles on the basis of thesex-specific distribution of the study variable.

C Adjusted for age, education, alcohol, smoking, energy intake, and

physical activity; skinfold measurements and waist-to-hip ratio (WHCR)are also adjusted for BMI by linear-regression techniques. n in brackets(n values for BMI are slightly higher than and n values for sum of skinfoldthicknesses are slightly lower than the n values given for WHCR).

t Categories divided into approximate quartiles on the basis of thesex-specific distribution ofthe study variable.

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BODY FAT AND ITS DISTRIBUTION 947

except among black men. Both moderate and intense degrees

of physical activity were consistently inversely associated with

the sum ofthe skinfold-thickness measurements for all race and

sex groups (data not shown).The effect of the source of alcohol on the observed relations

between alcohol and WHCR was evaluated (Table 5). In all four

race and sex groups, higher beer consumption was associated

with a larger WHCR. Liquor consumption was positively as-

sociated with WHCR in every group but black women. Wine

consumption was inversely associated with WHCR in black

women and directly associated with WHCR in white men. White

women consumed the most wine per week; however, wine con-

sumption was not significantly associated with WHCR in this

group. When alcohol was used as a percent of total kilojoules

(kilocalories) consumed rather than as the number ofdrinks per

week when assessing associations, there were similar results ex-

cept for a slightly weaker association for beer consumption

among black men (P = 0.07) and for wine consumption among

white men (P = 0.07).

Because the degree of physical activity is an important deter-

minant ofenergy expenditure and thus body size, the associations

between WHCR and dietary intake, alcohol intake, and smoking

were examined separately for individuals above and below the

median degree of physical activity for their respective race and

sex group. BMI contributed to the majority ofthe variability inWHCR, thus these associations were assessed with and without

BMI in the model. Although the patterns ofobserved associations

were similar to those presented (Tables 2-4), the amount of

variability in WHCR explained by these energy-yielding nu-

trients, alcohol, activity, and smoking varied by the degree of

reported physical activity (Table 6). This was especially true

among blacks, in whom twice as much of the variability in

WHCR was accounted for by these variables if people were lessactive than if they were more active. The amount of variability

in WHCR accounted for by alcohol intake alone also varied by

TABLE 4

TABLE 5

Linear regression of type of alcohol on WHCR*

Meanservings/wk SD /3 SE P

Black menWine 0.74 2.47 0.003 0.002 0.15Beer 5.1 1 9.88 0.002 0.001 0.03Liquor 1.39 3.73 0.006 0.002 0.0001

White men

Wine 0.90 2.29 0.004 0.002 0.03Beer 5.24 8.12 0.003 0.001 0.009

Liquor 1.39 3.63 0.004 0.002 0.01

Black womenWine 0.56 1.59 -0.007 0.003 0.008

Beer 0.98 3.20 0.006 0.002 0.007Liquor 0.53 1.98 +0.003 0.003 0.93

White womenWine 1.23 2.41 -0.002 0.002 0.20

Beer 1.56 3.68 0.004 0.002 0.004

Liquor 0.84 2.68 0.005 0.002 0.02

C Model adjusted for age, education, BMI, caloric intake, and number

of cigarettes smoked per day; wine, beer, and liquor consumption was

transformed by using a log transformation before analyses.

degree of physical activity. Among black men whose reported

degree of physical activity was above the median, 3.7% of the

variability in WHCR was contributed by alcohol intake whereas

among white men, 2.2% of the variability in WHCR was ex-

plained by alcohol intake if their physical activity was of a high

degree.

Discussion

In this study, dietary intake, physical activity, alcohol, and

cigarette smoking were significantly associated with both total

Regression ofdietary-intake and physical-activity components on BMI and WHCR

Black men

(n = 1 127)

White men

(n = 1 147)

Bla

(nck women

= 1447)

W(

hite women

n = 1284)

SE P SE P $ SE P fi SE P

BMI

Dietary intake/d

Fat (% Id) 0.02 0.02 0.39 0.03 0.02 0.1 1 -0.03 0.03 0.25 -0.04 0.02 0.03

Protein (% LI) 0.12 0.05 0.01 0.22 0.04 <0.01 0.15 0.06 0.02 0.17 0.04 <0.01

Carbohydrate (% Id) -0.04 0.02 0.02 -0.08 0.02 <0.01 0.0004 0.02 1.00 -0.02 0.02 0.23

Crude fiber (g/4184 Id) -0.12 0.17 0.47 -0.30 0.13 0.01 0. 17 0. 19 0.39 -0.02 0. 10 0.86

Physical activity (PA units)ttIntense -0.09 0.12 0.44 -0.02 0.10 0.81 -0.008 0.10 0.93 -0.20 0.09 0.03

Moderate 0.03 0.1 1 0.76 -0.08 0. 1 1 0.47 0. 18 0. 12 0. 1 1 -0.20 +0. 12 0.09

WHCRDietary intake/d

Fat (% kJ) -0.0003 0.0002 0.09 0.0003 0.0002 0.1 1 0.00001 0.0002 0.96 0.0003 0.0002 0.09Protein (% U) 0.00006 0.0004 0.89 0.0008 0.0005 0.1 1 -0.001 0.0005 0.02 -0.00007 0.0004 0.86

Carbohydrate (% Id) 0.00008 0.0002 0.61 -0.0005 0.0002 <0.01 0.00007 0.0002 0.69 -0.0003 0.0002 0.05

Crude fiber (g/4184 Id) -0.001 0.002 0.51 -0.004 0.001 <0.01 -0.005 0.002 <0.01 -0.002 0.001 0.05

Physical activity (PA units)ff

Intense -0.002 0.001 0.03 -0.004 0.001 <0.01 -0.003 0.0008 <0.01 -0.00004 0.0009 0.97

Moderate 0.0007 0.0009 0.47 -0.001 0.001 0.23 -0.003 0.0009 <0.01 0.0002 0.001 0.85

* Adjusted for age, education, BMI, total activity, alcohol intake, and smoking status.

t Activity units transformed by using the natural log of the variables.� Adjusted for age, education, BMI, total energy intake, alcohol, and smoking status.

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948 SLATTERY ET AL

TABLE 6Variability (R2) in WHCR accounted for by study variables, by degree

of physical activity (PA)*

Model Model I Model 1 Model Model 2 Model 2- If (low PA) (high PA) 2� (low PA) (high PA)

%

Black men 27.4 35.7 18.2 11.7 14.1 9.9

White men 35.3 37.0 34.0 9.0 13.2 6.4

Black women 25.0 30.4 19.1 7.7 9.3 5.3

White women 25.7 27.3 24.2 8.2 8.2 8.3

S R2 obtained from linear-regression models.

t Includes age. education, BMI, total energy intake, total physical activity, cig-

arette-smoking status, and alcohol intake in the regression on WI-ICR. Analyses

for low and high degrees of physical activity are < median and � median.

t Includes age, education, total energy intake. total physical activity, cigarette-smoking status, and alcohol intake in the regression on WHCR. Analyses for low

and high degrees of physical activity are < median and � median degree of PA.

BMI is not included as a covariate in model 2.

body fat and its distribution. In this cross-sectional examination

of young adults, carbohydrates (in whites) and fiber (except in

black men) were inversely associated with WHCR, and protein

was directly associated with BMI in all race and sex groups after

the degree of physical activity was adjusted for. As a percentage

of kilojoules (kilocalories), fat was not associated with body fat

or its distribution. Physical activity, especially intense activity,

was inversely associated with WHCR (except among whitewomen) and with skinfold measurements in all groups although

it was not associated with BMI. Total alcohol consumed also

was positively associated with WHCR, primarily in men although

the amount of alcohol consumption among women was much

less than for men, which may have made associations difficult

to identify. Beer was the source ofalcohol associated with WHCR

in all race-sex groups. Wine and liquor consumption were not

as consistently associated with WHCR as was beer. Current cig-

arette smokers had larger WHCRs in most of the race and sex

groups than did nonsmokers or exsmokers.

In addition to WHCR, the distribution of body fat was ex-

amined by using the ratio of the triceps plus subscapular to the

suprailiac skinfold thicknesses, a measure of relative fat index

(23), and the ratio of the subscapular to the triceps skinfold

thicknesses (24). None ofthe associations between these skinfold

ratios and dietary intake, physical activity, alcohol, or smoking

were consistent across the race and sex groups. Selby et al (7)

also found stronger associations with WHCR than with skinfoldratios when examining associations between body-fat distribution

and both physical activity and cigarette smoking.It has been estimated that heredity accounts for 20-3 1% of

the variability in WHCRs (7, 25). In the present study �26-

28% of the variability in WHCR was explained by age, educa-

tional status, BMI, total activity, carbohydrate intake, smoking

status, and alcohol intake in all race-sex groups except white

men, for whom 36% of the variability was explained by these

variables. The largest proportion of the variability in WHCR

contributed by the variables examined in this study was explained

by BMI. Thus, although protein intake was not associated with

WHCR, it was consistently associated with BMI and could

therefore influence WHCR. Although the degree of physical ac-tivity did not change the significance ofassociations that existed

between environmental variables and WHCR, a much larger

percentage ofthe variability in WHCR was explained by dietary

intake, alcohol consumption, cigarette smoking, and physical

activity among individuals with low degrees of activity than

among individuals who reported high degrees ofphysical activity.We are not sure why these differences occurred, although it is

possible that as individuals become more physically active,

physical activity itself had less of an impact on WHCR.

The lack of consistency in findings across all race and sex

groups raises the possibility that statistical associations may be

from chance. However, the possibility that they may be explained

by real differences between race and sex groups exists. A previous

study ofblacks, in which skinfold-measurement data were used,

found them to have a higher proportion of trunk fat relative to

extremity fat than whites, but whites had more total body fat

than did blacks (26). Sex differences in fat distribution also have

been shown to exist (26). It has been suggested that differencesin body fat and its distribution in race and sex groups may be

explained by interactions between environmental factors or by

different exposures to these factors (26). Women and men also

differ in fat distribution, with men having more abdominal fat

than women (26, 27). Studies have shown that people with more

abdominal fat respond to exercise differently than do those

without this body-fat pattern. Individuals with an abdominal-

fat pattern tend to decrease body fat (as well as reduce blood

lipids and blood pressure) and increase lean body mass withexercise (27, 28), whereas individuals without this fat pattern

do not experience the same effects with an exercise training pro-

gram. Results of this study reveal that intense physical activity

was not associated with the WHCR in white women, the group

with the lowest mean WHCR. In other analyses, not shown

here, the influence ofphysical activity on WHCR was compared

between white women above and below the median WHCR,

but no differences in associations between physical activity and

WHCR were observed.

The associations of body-fat indicators with dietary intake

also differed between race and sex groups. Although the exam-ination of dietary intake in this study was more detailed than

what has generally been reported, the data presented can only

crudely describe individual dietary intake. Because individuals

eat foods and not nutrients in isolation, a composite value for

intake of fat or for any nutrient may be the same for individuals

(in grams consumed), but may be obtained from entirely different

sources. Different food sources contribute to differences in intakeofother nutrients, which may modify the effects ofthe primary

nutrient on the endpoint. A better understanding of dietary in-

take and its associations with anthropometric, physiological, and

disease endpoints can only be made by a description of dietary

patterns expressed as combinations of foods consumed.

In this population of young adults, both energy intake and

physical activity were related to body size, although it appears

that the energy-yielding components of diet and the degree of

physical activity differ in their effects on body fat and its distri-

bution. Several studies suggested that dietary composition may

affect adiposity independent ofcalories(29, 30). In healthy adult

men it has been shown that individuals who consume a high-

fat diet have a higher percentage ofbody fat than do individuals

who consume isocaloric diets containing less fat (3 1 ). However,

few population-based studies have examined both dietary com-

position and physical activity together in relation to body size.

Findings in this study are consistent with those recently reported

by Laws et al (32). In their study ofolder white adults in Rancho

Bernardo, the percentage of calories from carbohydrate was in-

versely associated with WHCR among men. In addition, grams

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BODY FAT AND ITS DISTRIBUTION 949

ofalcohol consumed per week and number ofcigarettes smoked

per day were significantly associated with WHCR in men and

women. Exercising less than three times a week was positively

associated with WHCRs in men in the Rancho Bernardo study

(32). A recent study by Seidell et al (33) also showed that physical

activity performed during sports was associated with WHCRs

in 38-y-old European men.

The finding that current smokers have larger WHCRs than

do nonsmokers in all race and sex groups (except for black men)is consistent with previous observations (1 1, 12, 34-36).

Previous studies of the association between alcohol and

WHCR yielded inconsistent findings (27, 34-36). Not all of these

studies examined relations with source ofalcohol consumed. A

study ofSwedish women (36), which did assess source of alcohol,

found that beer and wine consumption were not associated withWHCR whereas liquor consumption was. In the present study,

liquor consumption also was associated with WHCR in white

women.

In summary, the findings from this study suggest that dietary

composition, alcohol, physical activity, and smoking behavior

may be associated with the amount of total body fat as well as

the distribution of fat within the body. Additional studies are

needed to verify the associations identified in this research and

to provide a better understanding of the basis for race and sex

differences observed and of the physiological mechanisms in-

volved. 13

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