Abstract
Increasing obesity among Americans is a serious issue in the US, especially in the pediatric and young adult population. We use a longitudinal design to examine the relationship between childhood poverty/welfare receipt and obesity onset and continuity from adolescence into young adulthood using three waves of the National Longitudinal Study of Adolescent Health. We include multiple measures of disadvantage that co-occur with poverty and model potential mediating mechanisms within a life course framework. We find a significant effect of poverty/welfare receipt in childhood on obesity outcomes for females, but not for males. However, other measures of socioeconomic disadvantage such as neighborhood poverty, and low parental education are related to obesity in both males and females. Poverty may impact female obesity through the mediating effects of physical activity, inadequate sleep, skipping breakfast and certain forms of parental monitoring, while race is an important confounder of poverty’s influence. This paper highlights the important influence of poverty and other aspects of social disadvantage on obesity outcomes during this critical transition to adulthood. Implications of this research include physical activity and parenting interventions for low-income youth. In addition, governmental efforts should be made to increase physical activity opportunities in poor neighborhoods.
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Notes
Selected special oversamples (including ethnic, disabled, and sibling over-samples) were also included in the in-home sample.
The questions for moderate to vigorous physical activity are: (1) During the past week, how many times did you go roller-blading, roller-skating, skate-boarding, or bicycling?; (2) During the past week, how many times did you play an active sport, such as baseball, softball, basketball, soccer, swimming, or football?; and (3) During the past week, how many times did you do exercise, such as jogging, walking, karate, jumping rope, gymnastics or dancing?
We also ran models including welfare/poverty status and our intervening mechanisms (excluding additional socioeconomic measures). Welfare/poverty was mediated by similar intervening factors as reported in Model 3, but remained significant.
We also ran models for females controlling for parity given weight gains associated with fertility. The results did not substantively change.
Our analysis is limited to adolescents who participated in all three waves of the study and have complete measured height and weight data. We exclude seriously disabled respondents, pregnant females, and individuals missing sampling weights or had missing data on covariates, which generally came from missing data on the parent questionnaire. We ran basic descriptive statistics (including, race/ethnicity, sex, age, family structure and immigrant generation) of those individuals with missing data and who were excluded for the reasons stated above. Although we do not include immigrant generation in our analysis, our missing sample has a much larger percentage of first generation immigrants (10%) than our non-missing sample (5%). This is due to the fact that a larger proportion of parents of first and second generation immigrant respondents did not complete the parent questionnaire. In addition, a larger proportion of blacks (24%), Hispanics (18%) and Asians (6%) were represented among those with missing data compared to our sample without missing data. This means that the missing sample is overrepresented by racial/ethnic minorities. The overrepresentation among Hispanics and Asians may be due to a higher proportion of first and second generation immigrants in the missing sample. The sample is also slightly overrepresented by non-two biological parent households. Mean age for the missing data sample is about a year older than our sample without missing data. In general, descriptive statistics indicate that individuals with missing data come from slightly more vulnerable disadvantaged minority groups. Thus, the effect sizes in this analysis may be somewhat underestimated, assuming that the addition of disadvantaged sample members would strengthen our results. Nevertheless, we do not suspect that missingness biases the parameter estimates based on Add Health analysis of attrition bias which shows little to no bias (Chantala et al. 2004).
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Acknowledgement
This paper was presented previously at the 100th Annual Meeting of the American Sociological Association, Philadelphia, PA, August, 2005. We gratefully acknowledge research support from the Carolina Population Center to Lee through an NICHD pre-doctoral fellowship and from the National Institute of Child Health and Human Development to Harris through grant P01 HD31921 as part of the Add Health program project and grant U01 HD37558 as part of the NICHD Family and Child Well-being Research Network, and to Penny Gordon-Larsen through grant K01 HD044263-01 from the NICHD. This research uses data from Add Health, a program project designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris, and funded by a grant P01-HD31921 from the National Institute of Child Health and Human Development, with cooperative funding from 17 other agencies. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Persons interested in obtaining data files from Add Health should contact Add Health, Carolina Population Center, 123W. Franklin Street, Chapel Hill, NC 27516-2524 (www.cpc.unc.edu/addhealth/contract.html).
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Lee, H., Harris, K.M. & Gordon-Larsen, P. Life Course Perspectives on the Links Between Poverty and Obesity During the Transition to Young Adulthood. Popul Res Policy Rev 28, 505–532 (2009). https://doi.org/10.1007/s11113-008-9115-4
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DOI: https://doi.org/10.1007/s11113-008-9115-4