Risk factors for obesity in young adults: Hispanics, African Americans and whites in the transition years, age 16–28 years

Bionrrd & Pharn~aco~hrr fc? Elsevicr. Paris

( 1994) 48. I42- I56

143

Dossier “Obesity”

Risk factors for obesity in young adults: Hispanics, African Americans and Whites in the transition years, age 16-28 years A Must’, SL Gortmaker*, WH Dietz’ ‘TuJis lJni\~rsiry. Depnrment o/‘ Contnwtirv ‘Deparmwnt qf’ Healrh and Social Behm~ior:

Healrh. Harvard

136 Harrison Atvenue, Bosron. MA 02111; School of’ Public Health. Bosron. MA USA

Summary - Previous studies have suggested that late adolescence may represent a critical period in the development of lifelong obesity. but representative prospective studies in this age group are lacking. The analytic cohort consisted of a representative sample from the United States of I I.591 Hispanic. African American, and white youths interviewed as part of the National Longitudinal Survey of Youth. Significant differences in obesity measures were observed among the six race-sex groups. Compared to whites of the same sex. the prevalence of obesity in 1981 was significantly higher among Hispanic males (12.0 vs 8.6%. P < 0.05) and African American females (14.2% vs 7.3%. P r 0.001) and lower among African American males (6.4% vs 8.6%. P > 0.005). Five-year cumulative incidence of obesity (1981-1986) was highest in Hispanic males. Hispanic females and African American females. Among those ages studied both in I981 and in 1986. a secular trend towards increased prevalence of obesity was observed over the five-year period (10.6% in 1981, 13.6% in 1986. P > 0.0001). Multivariate analyses failed to identify behavioral or sociodemographic factors that operated similarly in all race-sex groups. adolescence

/ epidemiology

I overweight

/ obesity

Introduction Young adulthood represents an understudied but potentially critical period in the natural history of obesity. Important correlates of obesity in adolescence include elevated cholesterol, hypertension, and abnormal glucose tolerance [l-4]. In a 5S-year follow-up study, adolescent obesity was associated with increased mortality in males and increased morbidity for several important diseases among males and females (51. During the transitional period from late adolescence through the early adult years, youth may establish lifelong eating and exercise habits that may influence the development or persistence of obesity [6]. Graduation from secondary school often terminates involvement in sports and may thereby decrease physical activity significantly. Pastimes that replace school-based activities may appreciably increase inactivity. For example, television viewing increases with age [7]. Marriage and childbearing may influence incidence or remission of obesity 18, 91.

The rapidity of the recent rise in the prevalence of childhood, adolescent, and adult obesity [IO- 131 and the presence of temporal trends in weight among genetically similar persons [ 14) suggests that environmental rather than genetic factors have caused the increase in prevalence. Increases in prevalence may arise from increased incidence, decreased remission or both. Identification of demographic, lifestyle and behavioral factors that influence prevalence, incidence, and remission and that operate similarly in all racial groups would facilitate prevention and treatment initiatives. We have analyzed data collected from 198 1 in the United States as part of the National Longitudinal Survey of Youth (NLSY). This large nationally representative survey was used to estimate prevalence, incidence and remission of obesity and to explore associated demographic and lifestyle characteristics of Hispanic, African American and white youths aged 16 to 28 years.

144 resulted baseline

Methods Population The National Longitudinal Survey of Youth (NLSY) was initiated in 1979 by the United States Department of Labor to study youth training and employment [ 151. This longitudinal data set contains over 24,000 pieces of information on each of 12,686 subjects. The Center for Human Resource Research at Ohio State University and NORC (formerly the National Opinion Research Center) at the University of Chicago have shared responsibility for all aspects of the project. Survey design and methods have been detailed elsewhere [ 1.51. Briefly, the sample of 12,686 was designed to represent the noninstitutionalized segment of American young people aged 14 to 21 years as of January 1979. The population was oversampled for Hispanic, African American, and economically disadvantaged white youth. Sample selection was accomplished through a multi-stage stratified area probability sample of dwelling units. Ninety percent (n = 12,686) of the civilian youth selected were interviewed in 1979. As of 1988. the overall retention rate was 90.2%. The NLSY defined three racial cohorts: Hispanic, non-Hispanic blacks, and non-Hispanic non-blacks. Here, we use the terms Hispanic, American and white to reflect contemporary terminology and improve readability. The analyses presented below are based on survey years 198 I-1986. For our obesity studies, the sole exclusion criterion was pregnancy. In 1982 and 1986 females were asked if they were pregnant. Pregnancy in 198 I was established by calculations based on the birth record obtained in 1984. Attrition as of the 1981 survey (n = 491) and exclusion for pregnancy (n = 604)

Table I. Sample Survey

of

Youth

characteristics, (198 I - 1986)*.

National

Longitudinal

#I (%) Sex male female

6076 5408

(52.9) (47.1)

1779 2870 6835

(15.5) (25.0) (59.5)

Race Hispanic African White

American

Mean

Age (Y) Parental Television

education viewing

(y) (hrslwk)

* Numbers reflect unweighred ticipants missing values for females pregnant in 1981.

(standard 19.8 10.9 13.9

deviation) (2.3) (3.9) (14.2)

sample in 1981 excluding parweight, height, sex, or race and

in a sample of I I.591 year for these analyses

persons in (table 1).

1981.

the

The sample weight associated with each subject weights the respondent’s data inversely to his/her probability of selection. Application of weights to the entire sample downweights oversampled groups, adjusts for some aspects of the sample design and non-response, and produces estimates that are representative of youth aged 14-2 I years in 1979. For race-specific analyses, we normalized the sample weights to the total number of persons sampled in each race. We applied population-based or race-specific sample weights as appropriate for all estimates of prevalence, incidence, and remission. We were unable to adjust standard errors, confidence intervals, or P-values for the design effects that arose from the clustered sampling scheme because the information was unavailable. Design effects for BMI estimated in the National Health and Examination Survey I (NHANES II) averaged only 1.4 for the racesex groups studied [ 161, suggesting only minor attenuation of the variance.

Obesity

measures

In 1981. 1982, 1985 and 1986, survey participants were asked for their current weight. Self-reported height was collected in 1981 and 1982, but not in 1985 and 1986 because the cohort was presumed to have attained adult height by 1982 when all subjects were I7 or older. In a comparison of reported and measured height and weight in NHANES 11, misclassification averaged 1% for males and 3% for females aged 20-24 and did not vary by race or education [ 171, similar to findings in earlier non-representative studies [ 18-201. We defined obesity as body mass index (BMI) greater than the sexspecific 85th percentile of persons aged 20-29 years in the National Health and Nutrition Evaluation Survey I (NHANES I, 197 I-1975, 27.8 kg/m2 for males, 26.6 kg/m2 for females) [2 I]. A statistical definition of obesity requires the choice of an arbitrary percentile cut-off point. The bias introduced by the self-report of weight and height slightly raises the cut-off point used to define obesity operationally. Despite theoretical limitations of BMI as an indicator of obesity, BMI correlates as well as skinfolds with densitometry-based measures of fatness [22] and prcdiets disease outcomes 123, 341. However, the possibility that the associations observed reflect increases in other body compartments besides fat (muscle or bone) [25] or altered fat distribution [26, 271 must also be considered. Prevalence was calculated from cross-sectional data as the number of persons obese divided by the total population. Pregnant women were excluded only for the survey round at which they were pregnant. Cumulative incidence was calculated as the percentage of persons obese at follow-up who were non-obese at baseline. Females who were pregnant in 198 I or I986 were excluded from incidence calculations. Cumulative remission was calculated in a similar manner: among those

145 obese at baseline, cumulative remission was the number of persons non-obese at follow-up. These measures are subject to random misclassification because the baseline measure may not represent usual BMI and because cumulative incidence and remission measures capture only those subjects who have undergone a transition at the end of the follow-up period: intervening transitions are missed. Measurement error of this kind decreases the apparent differences between groups. To correct for the tendency of extreme values to move towards the mean upon remeasurement (regression to the mean), we used the mean BMI calculated from I98 I and I982 for the baseline measure. For estimates of remission, women who were pregnant in 1981, 1982, or 1986 were excluded. The five-year trend in prevalence of obesity was assessed for persons 21-23 years of age, the ages surveyed in both I98 I and 1986. Differences in the prevalence of obesity were assessed by the x2 test for homogeneity of proportions.

Multivariate

analysis

We evaluated variables that were potentially important in relation to prevalence, incidence, and remission of obesity. These included race, sex, age, parental education (measured by father’s education or if missing, mother’s education), net family income, marital status, poverty status, region and population density of residence (asscsscd in 1979). living arrangements (parental home, own home or group living situation), weekly television viewing (in quintiles), and daily hours of sleep (the mean of seven consecutive days’ reports). Daily hours of sleep were included because it was the only other time-use variable available and was an important covariate in some racc-sex groups. Living arrangements, television viewing and sleep measures were assessed only in I98 I, the baseline year for calculation of incidence and remission estimates. Reliability of a single measurement is uncertain and use of a baseline measure may decrease validity because status may change over the follow-up period. Both will tend to decrease the size of the effect observed [ZS]. Regression models were tested for the presence of interactions between independent variables and stratified where effect modification was present. Stratification necessarily reduced power to detect relationships due to smaller sample sizes. Odds ratios were estimated from weighted logistic regression analysis by using the LOGISTIC procedure in SAS, Version 6.06 1291. We assessed the significance of linear trends for parental education and television viewing in separate analyses that included these variables as continuous. Sample sizes varied slightly due to missing data. The decreased variability that results from the clustered sampling scheme could be addressed by significance testing at a more conservative level. However, due to the exploratory nature of this study, we chose to report all potentially meaningful associations. Statistical sig-

nificance indicated.

therefore

denotes

P < 0.05

unless

otherwise

Results Obesity

measures

Sex-specific prevalence, incidence and remission of obesity for the population and by race are shown in table II. Although prevalence, incidence and remission were similar for males and females in the population, the greater number of whites obscure significant differences in the other two racial groups. The highest prevalence of obesity occurred among Hispanic males and African American females. African American males were significantly less obese than males of the other two racial cohorts. Whereas prevalence for all groups was two-fold greater in 1986 than 1981, patterns by sex and race were similar at the two interviews. Five-year cumulative incidence was significantly higher for Hispanic males, Hispanic females, and African American females compared to the other race-sex groups. Remission was lowest among Hispanic males and African American females, the two groups with greatest prevalence. These differences in cumulative remission were weakly significant (P = 0.08) for African American females. The five-year trend in prevalence of obesity can be assessed only for persons 21-23 years of age, the ages interviewed in both 1981 and 1986 (table III). Prevalence of obesity for the whole population changed significantly from 10.6% to 13.6% which represents a 34% increase. When we analyzed each race-sex group separately, we found that prevalence increased significantly from 1981 to 1986 for Hispanic males, Hispanic females, and white females. For every race-sex group except for African American males, the prevalence of obesity in 1986 exceeded the prevalence in 1981, although not all differences reached

Multivariate

statistical

significance.

analyses

In our multivariate analysis of obesity, prevalence and incidence, we noted significant interactions between race and sex. Therefore, we analyzed each race-sex group separately (tables IVa, IVb, tables Va,Vb). The bivariate “rates” reflect the crude effect of a single independent variable on obesity. Because the sociodemographic and be-

146

Table II. Survey

of

Obesity Youth

measures (1981-1986).

(prevalence,

incidence

and

remission

8

[SE])

by

race

and

Males Obesity

Males

measure

Females

Prevalence 1981 n

8.5 (0.5) 6074

8.3 (0.5) 5408

12.0

Prevalence 1986 n

16.1 (0.7) 4978

17.2 (0.7) 4818

Cumulative incidence n

9.1 (0.5) 4951

9.9 (0.6) 4310

Cumulative remission n

14.0

(2.1) 426

II.7

(I .2)* 939

6.4

23.2

(l.6)** 825

13.0

(2.0) 410

National

Longitudinal

Females

African American

Hispanic

sex,

African American

Hispanic

White

(0.7)* 1550

8.6 (0.6) 3585

8.9

14.5

(1.1) I328

15.8 (0.8) 2825

21.9

(1.6)** 755

27.6

(1.3)*** 1257

15.0 (0.8) 2806

(l.3)** 817

9.2

(0.9) 1321

8.7 (0.6) 2813

14.4

(1.5)** 661

15.0

(l.l)*** 1090

8.7 (0.6) 2559

(3.0) 99

14.5

(4.4) 78

(5.0) 63

7.2

(2.2)+ 148

9.3

14.4

(1.1)

14.2

White

(2.5) 249

16.9

7.3 (0.5) 3249

( I .O)***

839

I320

12.6

(2.7) 199

Prevalence (%): percent of population above 85th percentile NHANES I. Cumulative incidence (8): percent of population below 85th percentile (1981) and above 85th percentile in 1986. Cumulative remission (%): percentage of population above 85th percentile (mean 198111982) and below 85th percentile (1986). * different from whites P-zO.05. ** PC 0.01. *** PC 0.001. + different from whites P c 0.10.

Table III. sex.

National

Five-year trends Longitudinal

in prevalence of obesity and Survey of Youth (1981-1986).

superobesity

for

Prevalence Obesity

21-23

year-olds

American

and

Females

1986

1981

1986

15.4 10.5 10.6 10.8

2 I .4* 10.2 12.3 12.6

I I.0 17.3 9.1 10.3

l8.2* 20.6 13.9** 15.0**

Males

American

* Significantly

race

(%)

1981

Superobesity

Hispanic African White Total

by

. Males

Hispanic African White Total

(n = 7773)

different

from

1981

Females

1981

1986

1981

1986

4.1 3.1 2.7 2.9

6.0 2.0 3.5 3.5

1.4 4.7 2.7 2.9

4.9* 7.6 3.0 3.8

P < 0.05.

**

P < 0.001.

havioral variables considered are inter-related, multivariate adjustment was necessary to evaluate the independent effect of a given variable after statistical control for all the other variables. These effects are presented as adjusted relative odds.

Risk

factors

for

obesity

Among males, variables ity prevalence differ (table IVa). For Hispanic risk of obesity increases

related to risk of substantially by and white males, significantly with

obesrace the tele-

147

vision viewing. The gradient was especially steep among white males where obesity risk was more than four-fold greater for those who watched 21 hours or more per week compared to those who watched less than 3 hours of television per week. None of the other behavioral and demographic variables considered were associated with risk of obesity prevalence for Hispanic or African American males. For white males, group living arrangement and urban domicile were associated with significantly decreased risk of obesity. Obesity risk also varied with geographic region for white males: obesity risk was significantly elevated in the North Central and Southern regions of the United States compared to the West. Predictors of obesity prevalence showed more concordance by race for females than for males (table IVb). Television viewing was associated with increased risk for Hispanic and African American females, but not for white females. Living in one’s own home was associated with lower risk of obesity compared to living in one’s parental home for African American females. However, married black females were at significantly increased risk of obesity compared to unmarried black females. For females of all three racial cohorts, risk of obesity prevalence decreased with increasing parental education. Fiveyear cumulative incidence of obesity among males was associated with few of the variables considered. The risk of incident obesity was increased two- and three-fold for married Hispanic and African American males respectively when compared to their non-married counterparts. Poverty status reduced incident obesity among Hispanic males. Significant predictors of five-year cumulative incidence in females were noted only for whites. Increased television viewing predicted incident obesity. Incidence decreased with increasing parental education. None of the behavioral or sociodemographic predictors were significantly related to the incidcncc of obesity in Hispanic or African American females. After adjustment for other covariates. television viewing and parental education were the only variables considered which intlucnced prevalence or incidence of obesity over more than two race-sex groups, after adjustment for other covariates. Remission of obesity was explored among males and females; the sample size precluded stratification by racial cohort (table VI). In a multivariate analysis, five-year remission was lower (P = 0.09) among Hispanic males than

white males. Remission increased directly with parental education in a dose-dependent manner for males. Among obese males, remission of obesity was lower in each quintile of television viewing compared to the lowest, but no dose-response relationship was apparent. The probability of remission was two times greater for males living in an urban area than for males in a rural setting. For obese females, television viewing and poverty status lowered the likelihood of remission.

Discussion Our data emphasize important race and sex differences in the prevalence, incidence, and remission of obesity in American youth. The demographic, behavioral, and lifestyle variables examined exhibit distinct effects on obesity in each group. Prevalence.

incidence,

and

remission

Hispanic males and African American females had higher prevalence, higher incidence and lower remission of obesity than other groups. The magnitude of the prevalences in the present study arc lower than those estimated in NHANES I, probably because we used self-reported BMI measures that tend to underestimate weight and overestimate height and because the criteria we used were based on persons who were aged 20-29 years. The differences in prevalence that we observed between African Americans and whites are consistent with other findings in adults from national surveys [ 16, 21, 30, 3 I]. The elevated prevalence of obesity we observed in Hispanic males is also consistent with higher mean triceps and subscapular skinfold thickness noted among older adolescent Mexican American males [32]. However, because American Hispanics are heterogeneous [33], a comparison of the NLSY (60% Mexican American) with an unmixed Mexican American population may not be valid. Results from adult females examined in the National Health Interview Survey paralleled our own. The prevalence of obesity was highest for African Americans, followed by Hispanics, and whites [34]. Prior studies have not identified important differences by age in cumulative incidence of obesity in children or adults [35, 361. Interest in racial differences in the incidence of obesity

813 137

463 I31 196 103

642 222

182 63 238 447

56 846

Marital status Not married Married

Parental education < 8th grade Some high school High school graduate > High school

Poveriy status Non-poverty Poverty

Region West Northeast North Central South

Urban/rural Rural Urban

for

14.2 12.1

IO.0 16.4 I I.3 I I.8

12.3 12.6

12.2 Il.5 14.5 8.4

I I.9 12.7

14.2 10.8 IO.0

9.1 Il.3 12.0 IO. I 17.1

% Obese

according

” Weighted different

I .o 0.8 (0.3,

I .o 0.8 (0.4, I.5 (0.7, 0.8 (0.5,

I .o 1.2 (0.6,

I .o 1.4 (0.7, I .5 (0.9, 0.7 (0.3,

I .o I .o (0.5,

I .o 0.6 (0.3, I.4 (0.7,

I o*** I:2 (0.5, 1.6 (0.7, I .I (0.5, 2.4 ( I .2,

25 I II57

275 280 838 140

931 496

364 388 517 175

I460 100

726 263 571

8.1 6.2

5.2 6.0 7.6 2.6

8.6 3.5

6.3 5.9 6.9 7.8

6.2 9.8

6.8 8.2 5.2

7.8 4.5 5.2 6.4 8.6

% Obese

risk

(0.2, (0.4, (0.3, (0.6,

I .o 0.8 (0.4,

I .o I.6 (0.4, 2.0 (0.6, 2.7 (0.8,

I .o 0.6 (0.3,

I .o I.2 (0.6. I.2 (0.7, I.1 (0.5,

I .o 0.9 (0.3,

I .o 0.9 (0.4, I.5 (0.8,

I .o 0.5 0.7 0.6 I.1

1.5)

5.7) 7.0) 8.9)

1.2)

2.4) 2.3) 2.7)

2.4)

1.8) 2.8)

1.0) 1.5) I .4) 2.3)

Adjusted relative odds

Americans

sociodemographic

African

and

factors,

estimates adjusted for all variables listed and age, family from referent at P < 0.05. ++ P < 0.01. +” P < 0.001.

1.8)

1.5) 3.3) I .4)

2.4)

2.8) 2.7) 1.5)

2. I )

1.1) 2.7)

305 322 317 256 344

. ’

to behavioral

2.8) 3.4) 2.6) 5. I )+

Adjusted relative odds’

by race,

Hispnics

males

v Numbers in parentheses are 95% confidence limits. ** P < 0.01. *** P < 0.001. + Category is significantly

417 236 297

Living situation Parental home Own home Group living

n

obesity

186 188 196 173 I98

of

viewing < 3 hrslweek 3-6 hrs/week 7- I2 hrs/week 13-20 hrs/week 1 2 I hrsl week

TV

Prevalence

Characteristics

( 198 I - I 986)w.

Table IVa.

income,

881 2205

758 I IO1 1078 607

2944 459

608 635 1252 1046

2999 609

1236 II67 I205

666 780 787 656 684

n

* Trend

12.3 7.5

7.5 9.9 9.7 5.7

8.5 9.5

IO.9 Il.4 IO.2 4.6

7.5 15.3

I I.0 10.4 4.5

4.2 6.8 8.4 8.6 15.9

70 Obese

Whites

Longitudinal

and sleep.

National

of

Youth

significant

I .o 0.7 (0.5,

I.0 1.4 (0.9, I .8 (I .2. I.7 (1.0,

I .o 0.9 (0.6,

I .o I .2 (0.8, 1.2 (0.8, 0.6 (0.4,

I .o I .4 (0.9,

I .o 0.7 (0.5, 0.5 (0.3,

I .o*** 1.7 (1.0, 2.1 (1.2, 2.0 (1.2, 4.4 (2.6,

P < 0.05.

l.o)+

2.4) 2.9)++ 2.7)+

1.5)

I .9) 1.8) 0.9)

2. I )

1.1) 0.7)+++

3.0)+ 3.6)++ 3.5)++ 7.5)+++

Adjusted relative odds

Survey

E

658 196

417 142 177 91

Marital status Not married Married

Parental I 8th Some High > High

63 769

Urban/rural Rural Urban

for

8.7 9.0

12.1 8.3 8.8 7.1

6.2 14. I

I I.0 I I.6 2.9 3.3

8.4 10.7

9.8 9.7 6.6

8.2 9.8 5.8 7.7 Il.7

70 Obese

Adjusred

(0.3,

# Weighted different

I.0 I.0

I .o I.4 (0.6, 1.6 (0.6, 1.2 (0.6,

I .o 3.5 (1.6.

I .o* 0.9 (0.4, 0.3 (0.1, 0.2 (0.0.

I .o 2.2 (0.9,

1 .o 0.4 (0.2, 1.3 (0.5,

227 1034

226 235 762 84

736 490

344 342 406 163

II73 I56

559 372 398

168 249 245 212 438

n

to behavioral

20.8 13.0

II.8 14.3 15.3 I I.5

13.5 16.6

19.2 14. I 10.2 12.3

13.2 23.0

16.3 14.7 IO.9

9.1 I I.1 Il.9 12.8 19.8

70 Obese

Adjusred

0.7)++ 1.4)

1.9) 1.9) 2.1) 3.4)

odds

risk

I.0 0.6

(0.4,

1.0 I.5 (0.6, I .6 (0.7, 1.2 (0.5.

I .o 1.2 (0.7,

I .o** 0.6 (0.4, 0.4 (0.2, 0.9 (0.5,

I .O)

3.7) 4.0) 2.9)

2.0)

827 2 197

707 961 999 525

2588 473

576 535 1193 918

247 I 802

976 1414 883

528 659 705 567 783

n

* Trend

10.2 6.4

4. I 7.0 IO.0 6.9

6.8 I I.5

14.1 13.5 5.8 3.0

6.6 9.7

8.6 8.7 4. I

3.8 4.5 8.6 7.4 Il.2

70 Obese

Whiles

Longitudinal

and sleep.

National

income,

factors.

I.O)+ 0.6)++’ 1.8)

I .o I .9 ( I .O, 3.6)+

I .o 0.4 (0.3, 0.8 (0.5,

I .o** 0.9 (0.4, 0.9 (0.5. I.0 (0.5, 1.8 (I .O,

relative

Americans

sociodemographic

African

and

estimates adjusted for all variables listed.and age, family from referent at P < 0.05. ++ P < 0.01. +++ P < 0.001.

3.2)

3.2) 4.3) 2.4)

7.6)++

1.9) 0.8)+ 1.2)

5.5)

1.0) 3.8)

I .o*** 0.9 (0.3, 2.7) 0.4 (0. I, I .4) 0.9 (0.3, 2.7) 1.3 (0.5, 3.3)+

odds’

according

relative

by race,

Hispanics

females

V Numbers in parentheses are 95% confidence limits. ** P c 0.01. +** P c 0.001: +. Category is significantly

74 238 375

I>5

Region West Northeast North Central South

Poverty status Non-poverty Poverty

569 208

340 304 210

Living situation Parental home Own home Group living

education grade high school school graduate school

128 162 167 I59 233

n

of obesity

viewing c 3 hrs/week 3-6 hrs/week 7- 12 hrs/week 13-20 hrslweek 1 2 I hrs/week

TV

Prevalence

Characrerisrics

(1981-1986)w.

Table IVb. of

(0.4. (0.9, (0.6, (0.9,

(0.6, significant

I.0 0.8

I .o 0.6 (0.3, 0.9 (0.6, 1.2 (0.8,

I .o 1.2 (0.8,

I .o*** I.1 (0.7, 0.5 (0.3, 0.3 (0.2,

I .o 1.0 (0.7,

I .o 0.7 (0.5, 0.6 (0.3,

I .o 0.8 I.5 I.0 1.6

Youth

P < 0.05.

1.1)

I .O)+ I .4) 1.8)

1.9)

1.7) o.,j+++ 0.5)+++

1.5)

1.0) I.O)+

1.4) 2.6) 1.9) 2.7)

Adjusted relatilse odds

Survey

L \o

642 222

I82 62 238 447

56 846

Poverty status Non-poverty Poverty

Region West Northeast North Central South

Urban/rural Rural Urban

**

P-cO.01.

***

P
of

13.3 13.1

15.3 3.4 12.3 13.8

14.5 8.2

14.8 I I.2 I I.4 9.1

I I.7 21.1

Il.3 17.2 12.1

15.8 10.6 10.7 12.3 15.9

according

(0.5, (0.5, (0.4, (0.6,

(1.0,

I.0 0.9 (0.4,

I .o I.5 (0.8, 0.2 (0.0, 0.9 (0.5,

I .o 0.4 (0.2,

I .o* 0.7 (0.3, 0.7 (0.4, 0.5 (0.2.

I.0 2.9

I .o I.1 (0.5, 1.6 (0.8,

I .o I.2 I.0 0.9 1.3

25 I I I57

27.5 280 838 I40

931 496

364 388 517 I75

1460 100

726 263 571

305 322 317 256 344

.”

and

8.9 9.3

14.5 IO.0 7.6 5.9

10.9 6.9

9.7 10.0 8.3 12.7

8.9 14.4

9. I 10.7 8.6

9.5 9.4 7.8 9.0 9.5

% Obese

African

to behavioral

(0.3, (0.6.

l

1.8)

9.5)+ 4.7) 4.6)

1.3)

2.6) 1.3) 3.7)

8.3)+

1.6) 2.0)

2.2) 1.4) 2.2) 2.8)

and age, family +’ P < 0.001.

I .o 0.9 (0.5,

I .o 3.1 (1.0, 1.5 (0.5, 1.6 (0.5.

I .o 0.7 (0.4,

I .o I.4 (0.7, 0.7 (0.4, I.8 (0.8,

I .o 3.2 (1.2,

I.0 0.7 I.1

(0.5, (0.3, (0.5, (0.7,

Adjusted rela/i\ve odds

I .o I.1 0.6 I.0 I.4

Americans

sociodemographic

estimates adjusted for all variables listed from referent at P -z 0.05. ++ P < 0.01.

2.3)

2.9) 1.4) 1.5)

0.8)++

1.6) 1.3) 1.3)

4.0)+

2.1) 3.2)

2.6) 2.3) 2.1) 2.7)

Adjusred relafive odds’

by race,

” Weighted different

males

Hispanics

for

% Obese

obesity

are 95% confidence limits. + Category is significantly

463 I31 196 103

Parental education S 8th grade Some high school High school graduate > High school

in parentheses

813 I37

Marital status Not married Married

W Numbers

417 236 297

n

Living situation Parental home Own home Group living

incidence

186 I88 196 173 I98

Characrerisrics

(1981-1986)v.

viewing c 3 hrslweek 3-6 hrs/week 7- I2 hrs/week 13-20 hrslweek > 2 1 hrs/week

TV

Youth

Table Va. Five-year risk

income,

881 2205

758 II01 1078 607

2944 459

608 635 1252 1046

2999 609

1236 II67 1205

666 780 787 656 684

n

factors,

and sleep.

* Trend

8.8 8.7

9.3 8.8 9.4 7.0

8.9 9. I

8.9 IO.5 8.5 8.5

8.3 I I.8

8.4 10.5 7.6

8.4 8.7 7.6 8.7 I I.1

Survey

(0.8, (0.7,

(0.7, (0.5, (0.6, (0.9,

(0.5,

significant

I .o I.1 (0.8,

I.0 I.4 (0.9, 1.2 (0.8, I.4 (0.9,

I.0 0.8

I .o I.4 (0.9, I.1 (0.7, I.1 (0.7,

I .o 1.2 (0.8,

1.0 1.2 0.9

I .o I.0 0.8 0.9 I .4

of

P < 0.05.

1.5)

2.1) 1.8) 2.2)

I .4)

2.3) 1.8) 1.8)

1.9)

1.8) l.4)+

1.6) 1.3) 1.4) 2. I )

Adjusted relarive odds

Longitudinal

Whiles % Obese

National

o

Five-year incidence (I 98 I - 1986)w.

520 197

147 67 221 340

60 705

Poverty status Non-poverty Poverty

Region West Northeast North Central South

Urban/rural Rural Urban

of

21.8 13.8

13.9 Il.4 18.1 13.0

12.6 18.5

15.2 13.1 10.8 21.8

13.8 16.7

14.9 15.9 Il.7

14.2 II.5 12.9 I I.5 18.8

race,

(0.4, (0.4, (0.4, (0.5,

3.0)

3.2) 2.0) 2.9)

3.5)

207 973

215 216 718 79

692 457

324 326 377 I54

II02 146

532 354 362

I57 235 230 202 409

n

I I.5 15.6

18.0 18.4 13.4 12.3

14.3 14.5

14.8 15.5 14.8 16.1

14.4 19.9

14.7 15.9 14.5

14.2 17.6 16.2 12.7 13.9

70 Obese

African

g to behavioral

(0.4, (0.4. (0.3, (3.3,

I .o I.1 (0.6,

I .o 1.6 (0.6. 1.8 (0.7, I.2 (0.5.

I .o 1.2 (0.7,

I.0 I.1 (0.7, 1.3 (0.8, I.2 (0.6,

I.0 1.8 (0.9,

I .o I.1 (0.6. 0.7 (0.4,

I .o 0.9 0.8 0.6 0.6

relative

Adjusted

1.9)

3.9) 4.4) 2.9)

2.0)

1.9) 2.2) 2.3)

3.4)

1.8) 1.3)

1.7) 1.6) 1.2) 1.1)

odds

sociodemographic

Americans

and

estimates adjusted for all variables listed and age, family from referent at P c 0.05. +* P < 0.01. +++ P c 0.001.

I .o 0.4 (0. I, 0.9)’

I .o I.5 (0.7, 0.6 (0.2, I.5 (0.8,

I .o t.7 (0.8,

accordin

I .8) 1.5)

2.7) 2.9) 3.4) 3.5)

I .o 0.9 (0.4, 2.0) 0.9 (0.4, 1.9) 2.4 (I .O, 5.9)

I .o 1.4 (0.6,

I .o I .2 (0.6, 0.6 (0.2,

I .o I.0 I. I 1.2 1.4

Adjusted relative odds’

by

x Weighted different

males

Hispanics

for

70 Obese

obesity

are 95% confidence limits. + Category is significantly

380 I31 164 85

Parental education < 8th grade Some high school High school graduate > High school

in parentheses *** P<0.001.

610 177

Marital status Not married Married

V Numbers ** PcO.01.

314 279 194

Living situation Parental home Own home Group living

II

II8 149 160 137 209

Characterisrics

Youth

viewing c 3 h&week 3-6 hrs/week 7-12 h&week 13-20 hrslweek 2 2 I hrs/week

TV

of

Table Vb.

773 2063

673 901 939 491

2430 451

544 503 II20 871

2348 737

913 1324 848

492 613 670 538 742

-

* Trend

9.5 8.5

6.8 IO.9 6.9 IO.9

8.6 9.2

12.6 Il.6 6.9 8.2

8.4 10.2

8.4 9.2 8.6

5.6 IO.0 7.8 7.7 12.1

70 Obese

Whites

National

and sleep.

factors,

n

income.

risk

Survey

(I .O, (0.8, (0.6, (1.2.

(0.7.

(0.6, significant

I.0 0.9

I .o 0.9 (0.5, 1.4 (0.9, 0.8 (0.5,

I .o 0.8 (0.5,

I .o* 0.9 (0.5, 0.5 (0.4, 0.7 (0.5,

I.0 I.1

I .o I.1 (0.7, I.1 (0.7,

I .8 1.4 I.1 2.1

1 .o**

P < 0.05.

I .3)

1.4) 2.2) I .3)

1.4)

1.4) 0.8)++ I. I )

1.7)

1.7) 1.7)

3.0)+ 2.4) 2.0) 3.6)++

Adjured relative odds

Longitudinal

WI

403 81

87 129 I84 92 II4 336

Poverty status Non-poverty Poverty

Region West Northeast North Central South

Urban/rural Rural Urban

are 95% confidence limits. + Category is significantly

I28 IO1 174 79

Parental education 5 8th grade Some high school High school graduate > High school

in parentheses *** 1’<0.001.

391 I08

Marital status Not married Married

V Numbers ** P
227 I55 II7

300 107 92

n

for

Living situation Parental home Own home Group living

of obesity

72 84 99 80 162

incidence

viewing < 3 hrs/week 3-6 hrsiweek 7- I2 hrsiweek 13-20 hrsiweek Z 2 I hrs/week

TV

Characteristics

Five-year (1981-1986)v.

Race White Hispanic Black

Youth

Table VI.

12.7 14.6

15.2 12.0 16.7 I I.9

13.9 I X.8

14.6 12.4 12.7 18.9

14.3 12.6

14.9 II.2 16.2

34.5 6.1 15.1 13.3 I I.6

14.4 9.3 14.5

% Obese

by race,

” Weighted different

males

(0.3, (0.3.

(0.0. (0.1, (0.0. (0. I,

I .o 2.0 (0.9,

I .o 0.8 (0.2, 0.7 (0.3, 1.7 (0.6,

I .o 1.5 (0.5,

I .o* I. I (0.4, I.2 (0.5. 2.0 (0.7.

I .o I.4 (0.6,

0.8 0.7

I .o

I.0 0.1 0.3 0.1 0.2

I .o 0.3 (0.1. 0.5 (0.2,

4.2)’

2.3) 2.0) 4.7)

4.2)

3.0) 2.8) 5.5)

3.5)

1.9) 1.8)

0.3)+++ 0.8)+ 0.5)+++ 0.6)+++

1.2)’ 1.5)

Adjured relative odds’

to behavioral

and

n

120 330

72 I08 210 66

297 I 45

I56 II8 II5 56

363 102

206 I 65 94

45 70 92 71 I81

236 69 160

sociodemographic

estimates adjusted for all variables listed and age. family from referent at P c 0.10. ++ P < 0.01. +++ P < 0.

Males

according

risk

income,

8.9 12.7

20.3 12.8 8.6 10.8

14.0 5.6

10.7 16.9 10.8 4.0

10.3 16.3

10.2 13.9 10.6

19.9 7.6 8.0 12.5 13.4

12.6 16.9 7.2

Females

National

and sleep.

% Obese

factors,

(0.6, (0.3, (0.1,

* Trend

2.8)

lo.o)+ 5.4) 3.6)

I .o)+

3.6) 2.0) 1.8)

4. I )

3.6) 2.5)

I .4) 1.4) 1.7) 1.8)

10.7) 2.6)

significant

I.0 1.2 (0.5,

I .o 3.0 (0.9, I.8 (0.6, 1.2 (0.4,

I .o 0.3 (0. I,

I.0 I.5 0.8 0.4

I .o I .5 (0.5,

I .o 1.4 (0.5, 0.7 (0.2,

(0. I, (0.1, (0.1, (0.3,

I .o 2.9 (0.8, 0.9 (0.3, I .o** 0.4 0.5 0.5 0.7

of

P < 0.05

Survey

Adjusted relative odds

Longitudinal

_ VI h)

153 among females has generated several studies with inconsistent results. An almost two-fold greater IO-year incidence of being overweight was noted in the NHANES I follow-up of African American and white females aged 35-44. However, in the same study, the opposite pattern was observed among females aged 25-34. The IO-year incidence among white females was slightly higher than among African American females [37]. In a subsequent report which employed a more restrictive criterion for obesity, the IO-year incidence of obesity in African American females aged 3055 was twice that of white females [38]. The twofold greater incidence of obesity that we observed among African American females compared to white females is consistent with these later findings. The cumulative incidence values of 8.7% for whites and 15.0% for African American females are also comparable. To our knowledge, ours is the first prospective study to include Hispanics in sufficient numbers to estimate racespecific incidence. Five-year remission varied by sex and race. Overall, obesity remission was approximately 13%. Both frequencies of remission were lower in African American females and Hispanic males. Because obese individuals represent only a small percentage of the total population, earlier studies that relied on clinic population where remission rates were generally low [39, 401 may not generalize to the whole population. Remission estimates of obesity in community samples are higher in adults [4l, 421 and children [43], but appear to be lower in African American females than white females even after adjustment for socioeconomic status [43]. Secular trends Our observations suggest that young adults reflect the upward trend in prevalence seen in other populations. Comparisons of skinfolds indicated marked increases in the prevalence of obesity in children and adolescents that ranged from 17% to 306% between 1963 and 1980 [IO]. Using BMI criteria, a second analysis found a trend towards increased prevalence of obesity over the same period in adult African Americans and white females, but not adult males or younger adolescents of either sex [ I I]. Upward trends in the prevalence of obesity over the last several decades have also been noted in geographically defined bi-racial childhood populations [ 131, Navajo Indian schoolchildren [44], young men in

Denmark [45], and middle-aged men but not women aged 30-59 in Finland [46]. In contrast to the decline observed in other cardiovascular risk factors, a secular trend towards increased prevalence of obesity in all adult age groups was apparent in the Minnesota Heart Study [47]. Upward trends observed in the 1960’s and 1970’s appear to have continued into the 1980’s for this age group. Because the recent increase in prevalence has occurred over a relatively short time and because the increase was greatest at the upper percentiles of the distribution, environmental causes are likely to be involved. Increased prevalence can arise through increased incidence, decreased remission, or both. The increased prevalence of obesity which we observed among Hispanic males and African American females appears due to both increased incidence and decreased remission. The greater secular increase among Hispanic females appears to be due to increased incidence. Mirltivuriate

analysis

Although stratification by race and sex limited our power to detect significant relationships, several important associations emerged in the NLSY sample. Effect of socioeconomic

status

We used parental education to reflect socioeconomic status (SES) because subject’s income may not reflect SES and respondent’s education is often still ongoing during this transitional period. We observed complex relationships between obesity measures and parental education by race and sex. The inverse relationship between prevalence of obesity and SES observed by us in females is in accordance with previous investigations of adult females [48-501. Among Hispanic females, poverty status after multivariate adjustment was associated with a significant three-fold increased risk of prevalent obesity. In a comprehensive review, the lack of consistency for SES effects among 32 US studies of children was ascribed to measurement differences, secular changes, and different distributions of confounding covariates in the different samples [51]. Prior work has indicated that the obesity/SES relationship reverses from direct to inverse among females as they mature [52]. We observed a strong inverse relationship of obesity and SES in female children by late adolescence that appears

154 to intensify for white females during this period. The absence of an effect of poverty status on prevalence or incidence of obesity among the African American females we studied implies that this reversal either occurs later or is due to other factors. In contrast to increased risk of major weight loss observed among low-income women in the NHANES I follow-up [53], the younger females living in poverty in our study experienced a lowered risk of remission. Effect of television

viewing

As in children [53], adolescents [53] and adults [54-561, television viewing was directly related to-the prevalence and incidence of obesity among older white. youth. However, the quintile dat.a suggest a threshold effect: viewing more than 21 hours per week confers excess risk. Although non-whites watch more television than whites [57], associations between obesity and television viewing among Hispanics and African Americans in the present study were weak or absent. Daily television viewing in excess of three hours was associated with a two- to four-fold risk of obesity in samples of all white or predominantly white adults [58], comparable to the magnitude of risk we observed for white males. Although inactivity, represented by television viewing, contributes to increased incidence of obesity [58], we could only relate, television viewing to the incidence of obesity among ‘white females. The lack of a stror&f predictive relationship between televisign-viewing and the 5-year incidence of obesity may be due to crudeness of the television measure, duration of follow-up, unsettled lifestyles, or the fact that for this age group television viewing does not influence inactivity. Displacement of other activities as well as overt and veiled promotion of high fat and low nutrient dense foods are additional mechanisms that explain how television viewing could increase incidence or decrease remission of obesity.

imens. Dynamics in obese families may foster dependence and impede autonomy [59. 601. In addition, later marriage and economic considerations that delay autonomy [61] may influence prevalence, incidence, or remission. The effect of living situation on obesity has not been examined previously and may be especially important for this transitional age group.

Conclusions Our findings suggest important differences in the prevalence, incidence and remission of obesity in this representative sample of older youth. Secular trends indicate increasing obesity in this age group with likely long-term health consequences [62-651. The lower likelihood of obesity remission associated with poverty status and African American race, coupled with elevated incidence among African American females, emphasizes the need for specially targeted prevention and treatment initiatives for low-income African American females. Future studies must clarify the relationship of obesity to living arrangement and assess the impact of childbearing in young adults. These data emphasize the complex relationships between behavioral/sociodemographic variables and obesity outcome measures for this transitional age group. Other unmeasured variables may exert more homogeneous effects across race-sex groups or at other more stable periods in the life-cycle. Our inability to identify common behavioral and sociodemographic characteristics among the six race-sex groups suggests that prevention and intervention efforts undertaken in late adolescence may need to be carefully targeted.

Acknowledgments Preparation of this manuscript was supported in part by the Weight Watchers Foundation.

Effect of living arrangement Autonomy appeared to affect prevalence of obesity: in several race-sex groups prevalence was lower for youth living in their own homes or in group living situations than among youth living with their parents. The lower prevalence of obesity for whites in group living situations may reflec,t,military.entrance requirements, the influence of congregate feeding, or enforced exercise reg-

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