Explaining the Association between Early Adversity and Young Adults’ Diabetes Outcomes: Physiological, Psychological, and Behavioral Mechanisms
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Previous studies have documented that early adversity increases young adults’ risk for diabetes resulting in morbidity and comorbidity with adverse health conditions. However, less is known about how inter-related physiological (e.g., body mass index [BMI]), psychological (e.g., depressive symptoms), and behavioral mechanisms (e.g., unhealthy eating and sedentary behavior) link early adversity to young adults’ diabetes outcomes, although these mechanisms appear to stem from early stressful experiences. The current study tested the patterning of these longitudinal pathways leading to young adults’ diabetes using a nationally representative sample of 13,286 adolescents (54% female) over a period of 13 years. The findings indicated that early adversity contributed to elevated BMI, depressive symptoms, and stress-related health behaviors. The impact of these linking mechanisms on hierarchical diabetes outcomes (i.e., prediabetes and diabetes) remained significant after taking their associations with each other into account, showing that these mechanisms operate concurrently. The findings emphasize the importance of early detection for risk factors of young adults’ diabetes in order to minimize their detrimental health effects.
KeywordsYoung adults Diabetes Early adversity Health-risk mechanisms
This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis.
K.A.S.W. conceived of the study, conducted the preliminary analyses, and drafted the manuscript; D. B. participated in the design, analyses, and interpretation of the data; C.W.O. participated in manuscript preparation and revisions. All authors read and approved the final manuscript.
This study was not funded.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no competing interests.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- American Diabetes Association. (2014). Statistics about diabetes. http://www.diabetes.org/diabetes-basics/statistics/.
- American Heart Association. (2014). Prevention and treatment of metabolic syndrome. https://www.heart.org/HEARTORG/.
- Brownstein, N., Kalsbeek, W. D., Tabor, J., Entzel, P., Daza, E., & Harris, K. M. (2011). Non-response in wave IV of the National Longitudinal Study of Adolescent Health. Chapel Hill: Carolina Population Center, University of North Carolina.Google Scholar
- Cahill, L. E., Pan, A., Chiuve, S. E., Sun, Q., Willett, W. C., Hu, F. B., & Rimm, E. B. (2014). Fried-food consumption and risk of type 2 diabetes and coronary artery disease: A prospective study in 2 cohorts of US women and men. The American Journal of Clinical Nutrition. doi: 10.3945/ajcn.114.084129.PubMedPubMedCentralGoogle Scholar
- Festa, A., D’Agostino, Jr, R., Williams, K., Karter, A. J., Mayer-Davis, E. J., Tracy, R. P., & Haffner, S. M. (2001). The relation of body fat mass and distribution to markers of chronic inflammation. International Journal of Obesity & Related Metabolic Disorders, 25, 1407–1415.CrossRefGoogle Scholar
- Gillman, M. W. (2004). A life course approach to obesity. In D. Kuh, & Y. B. Shlomo (Eds.), A Life Course Approach to Chronic Disease Epidemiology (pp. 189–217). New York, NY: Oxford University Press.Google Scholar
- Muthén, B. O. (2011). Applications of causally defined direct and indirect effects in mediation analysis using SEM in Mplus. Unpublished manuscript. Retrieved from http://www.statmodel.com/download/causalmediation.pdf
- Muthén, L. K., & Muthén, B. O. (2012). Mplus: The comprehensive modeling program for applied researchers. Los Angeles, CA: Muthén and Muthén. User’s guide 5.Google Scholar
- Nabkasorn, C., Miyai, N., Sootmongkol, A., Junprasert, S., Yamamoto, H., Arita, M., & Miyashita, K. (2006). Effects of physical exercise on depression, neuroendocrine stress hormones and physiological fitness in adolescent females with depressive symptoms. The European Journal of Public Health, 16(2), 179–184.CrossRefPubMedGoogle Scholar
- Packard, C. J., Bezlyak, V., McLean, J. S., Batty, G. D., Ford, I., & Burns, H., et al. (2011). Early life socioeconomic adversity is associated in adult life with chronic inflammation, carotid atherosclerosis, poorer lung function and decreased cognitive performance: A cross-sectional, population-based study. BMC Public Health, 11(1), 42–57.CrossRefPubMedPubMedCentralGoogle Scholar
- Seeman, T., Gruenewald, T., Karlamangla, A., Sidney, S., Liu, K., McEwen, B., & Schwartz, J. (2010). Modeling multisystem biological risk in young adults: The coronary artery risk development in young adults study. American Journal of Human Biology, 22(4), 463–472.CrossRefPubMedPubMedCentralGoogle Scholar
- Stringhini, S., Batty, G. D., Bovet, P., Shipley, M. J., Marmot, M. G., & Kumari, M., et al. (2013). Association of life course socioeconomic status with chronic inflammation and type 2 diabetes risk: The Whitehall II prospective cohort study. PLoS Med, 10(7), e1001479.CrossRefPubMedPubMedCentralGoogle Scholar
- Wadsworth, M., Rienks, S. (2012), Stress as a mechanism of poverty’s ill effects on children: Making a case for family strengthening interventions that counteract poverty-related stress. http://www.apa.org/pi/families/resources/newsletter/2012/07/index.aspx.
- Wickrama, K. A. S., Conger, R. D., Lorenz, F. O., & Jung, T. (2008). Family antecedents and consequences of trajectories of depressive symptoms from adolescence to young adulthood: A life course investigation. Journal of Health and Social Behavior, 49(4), 468–483.CrossRefPubMedPubMedCentralGoogle Scholar