Youth Substance Use and Body Composition: Does Risk in One Area Predict Risk in the Other?
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Both substance use and obesity are prevalent among youth. As youth age, substance use rates increase and over the past three decades, obesity rates among youth have tripled. While these two factors have both short- and long-term health impacts, little research has explored how substance use and obesity among youth may be related. This study explores the bi-directional longitudinal relationships between substance use and body composition. Participants (N = 704; 50.7% female) were mostly white (86.4%) with a baseline mean age of 14.7 years. Objectively measured body composition was used to calculate body mass index z-scores (BMI z-score) and percent body fat. Cross-lagged structural equation models, accounting for clustering at the school level, were run to determine the longitudinal association between body composition and self-reported substance use (alcohol, cigarette, and marijuana), adjusting for socio-demographic characteristics, pubertal status, and weight satisfaction. Baseline alcohol use predicted decreased BMI z-score at follow-up and a similar association with percent body fat approached significance. Baseline cigarette use predicted increased percent body fat. No longitudinal associations were seen between baseline body composition and future substance use. Our results suggest that substance use contributes to subsequent body composition; however, body composition does not contribute to subsequent substance use. Continued research that explores these relationships longitudinally is greatly needed.
KeywordsBody composition Adolescents Substance use Obesity
This research was funded through a grant from the National Cancer Institute as part of their Transdisciplinary Research in Energetics and Cancer (TREC) Initiative. Grant # 1U54CA116849 and through a grant supported by the Etiology of Childhood Obesity (ECHO) with funding from the National Heart, Lung and Blood Institute, Grant #R01HL085978. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, National Heart, Lung and Blood Institute, or the National Institutes of Health.
- Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equation perspective. Hoboken, NJ: Wiley-Interscience.Google Scholar
- United States Department of Agriculture. (2010). Report of the dietary guidelines advisory committee on the dietary guidelines for Americans. Washington, DC: U.S. Department of Agriculture, Agricultural Research Service.Google Scholar
- Eaton, D. K., Kann, L., Kinchen, S., Shanklin, S., Ross, J., Hawkins, J., et al. (2010). Youth risk behavior surveillance—United States, 2009. MMWR Surveillance Summaries: Morbidity and Mortality Weekly Report. Surveillance Summaries/CDC, 59(5), 1–142.Google Scholar
- Flegal, K. M., Ogden, C. L., Yanovski, J. A., Freedman, D. S., Shepherd, J. A., Graubard, B. I., et al. (2010). High adiposity and high body mass index-for-age in US children and adolescents overall and by race-ethnic group. The American Journal of Clinical Nutrition, 91(4), 1020–1026.PubMedCrossRefGoogle Scholar
- Goodman, E., & Huang, B. (2002). Socioeconomic status, depressive symptoms, and adolescent substance use. Archives of Pediatric & Adolescent Medicine, 156(5), 448–453.Google Scholar
- Jessor, R., & Jessor, S. L. (1977). Problem behavior and psychosocial development: A longitudinal study of youth. New York: Academic Press.Google Scholar
- Johnston, L. D., O’Malley, P. M., & Bachman, J. G. (1998). National survey results on drug use from the monitoring the future study, 1975–1997.Google Scholar
- Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2011). Monitoring the future national survey results on drug use, 1975–2010: Volume I, Secondary school students. Ann Arbor: Institute of Social Research, The University of Michigan.Google Scholar
- Koval, J. J., Pederson, L. L., Zhang, X., Mowery, P., & McKenna, M. (2008). Can young adult smoking status be predicted from concern about body weight and self-reported BMI among adolescents? Results from a ten-year cohort study. Nicotine Tobacco Research, 10(9), 1449–1455.PubMedCrossRefGoogle Scholar
- Kuczmarski, R. J., Ogden, C. L., Guo, S. S., et al. (2002). 2000 CDC growth charts for the United States: Methods and development. National Center for Health Statistics. Vital Health Statistics, 11(246), 1–203.Google Scholar
- Muthen, B. O., Du Toit, S. H. C., & Spisic, D. (1997). Robust inference using weighted least squares and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes.Google Scholar
- Muthen, L. K., & Muthen, B. O. (1998–2010). Mplus user’s guide (6th ed.). Los Angeles, CA: Muthen & Muthen.Google Scholar
- United States Department of Health and Human Services. (2000). Reducing tobacco use: A report of the surgeon general. Georgia: Atlanta.Google Scholar
- van den Berg, P. A., Mond, J., Eisenberg, M., Ackard, D., & Neumark-Sztainer, D. (2010). The link between body dissatisfaction and self-esteem in adolescents: Similarities across gender, age, weight status, race/ethnicity, and socioeconomic status. Journal of Adolescent Health, 47(3), 290–296.PubMedCrossRefGoogle Scholar