Elsevier

Annals of Epidemiology

Volume 6, Issue 4, July 1996, Pages 266-275
Annals of Epidemiology

Original report
Race, socioeconomic status, and obesity in 9- to 10-year-old girls: The NHLBI growth and health study

https://doi.org/10.1016/S1047-2797(96)00056-7Get rights and content

Abstract

The purpose of this investigation was to determine whether measures of socioeconomic status (SES) are inversely associated with obesity in 9- to 10-year-old black and white girls and their parents. Subjects were participants in the Growth and Health Study (NGHS) of the National Heart, Lung, and Blood Institute. Extensive SES, anthropometric, and dietary data were collected at baseline on 2379 NGHS participants. The prevalence of obesity was examined in the NGHS girls and parents in relation to SES and selected environmental factors. Less obesity was observed at higher levels of household income and parental education in white girls but not in black girls. Among the mothers of the NGHS participants who were seen, lower prevalence of obesity was observed with higher levels of income and education for white mothers, but no consistent patterns were seen in black mothers. Univariate logistic models indicated that the prevalence of obesity was significantly and inversely associated with parental income and education and number of parents in the household in white girls whereas caloric intake and TV viewing were significantly and positively associated with obesity. Among black girls, only TV viewing was significantly and positively associated with the prevalence of obesity. Multivariate logistic regression models revealed that lower parental educational attainment, one-parent household, and increased caloric intake were significantly associated with the prevalence of obesity in white girls; for black girls, only increased hours of TV viewing were significant in these models. It is concluded that socioeconomic status, as measured by education and income, was related to the prevalence of obesity in girls, with racial variation in these associations. A lower prevalence of obesity was seen at higher levels of socioeconomic status in white girls, whereas no clear relationship was detected in black girls. These findings raise new questions regarding the correlates of obesity in black girls.

References (44)

  • SM Garn

    Family-line and socioeconomic factors in fatness and obesity

    Nutr Rev

    (1986)
  • TA Sorensen

    Genetic aspects of obesity

    Int J Obesity

    (1992)
  • C Bouchard et al.

    Genetic aspects of obesity

    Ann NY Acad Sci

    (1993)
  • J Sobal et al.

    Socioeconomic status and obesity: a review of the literature

    Psychol Bull

    (1989)
  • National Center for Health Statistics

    Health promotion and disease prevention, United States, 1985

  • JP Leigh et al.

    Gender and race differences in the correlation between body mass and education in the 1971–1975 NHANES I

    J Epidemiol Community Health

    (1992)
  • MF Najjar et al.

    Anthropometric reference data and prevalence of overweight, United States, 1976–1980

  • S Kumanyika

    Obesity in black women

    Epidemiol Rev

    (1987)
  • VR Fuchs et al.

    America's children: Economic perspectives and policy options

    Science

    (1992)
  • MP Golden et al.

    Obesity and socioeconomic class in children and their mothers

    JDBP

    (1983)
  • AJ Stunkard et al.

    The influence of social class on obesity and thinness in children

    JAMA

    (1972)
  • PB Goldblatt et al.

    Social factors in obesity

    JAMA

    (1965)
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    This research was performed under contracts NO-HC-55023-26 of the National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.

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