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J Adolesc Health. 2009 Nov;45(5):517-24. doi: 10.1016/j.jadohealth.2009.03.010. Epub 2009 May 28.

One size does not fit all: identifying risk profiles for overweight in adolescent population subsets.

Author information

  • 1Department of Health Policy and Administration, The Pennsylvania State University, University Park, Pennsylvania 16802, USA. rzb10@psu.edu

Abstract

PURPOSE:

The purpose of this study is to identify population subgroups of adolescents who are homogenous with respect to sociodemographic factors and potentially modifiable risk and protective factors related to overweight status in a nationally representative sample of adolescents ages 12-17.

METHODS:

The data used for this study are from the Centers for Disease Control and National Center for Health Statistics' National Survey of Children's Health, 2003 (NSCH). Classification and Regression Trees (CART) were used to identify population segments of adolescents based on risk and protective factors for obesity.

RESULTS:

In the final CART model, 12 variables remained, including: poverty level, race, gender, participation in sports, number of family meals, family educational attainment, child physical activity, participation in free lunch programs, neighborhood safety and connectedness, TV viewing time, and child age in years. Poverty level was determined to be the most variable related to weight status in this sample of adolescents. Adolescents living in households below approximately the 300% poverty level were subject to a different constellation of predictors than adolescents living in homes above the 300% poverty level.

CONCLUSIONS:

Our results demonstrate how risk and protective factors related to obesity emerge differently among sociodemographic subgroups and the relative importance of these risk and protective factors in relation to adolescent overweight status. Interventions that work for one population subgroup may not work for another.

PMID:
19837359
[PubMed - indexed for MEDLINE]
PMCID:
PMC3740573
Free PMC Article

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