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Childhood adversity is linked to adult health among African Americans via adolescent weight gain and effects are genetically moderated

Published online by Cambridge University Press:  06 May 2020

Steven R. H. Beach Open the ORCID record for Steven R. H. Beach [Opens in a new window] ,
Mei Ling Ong ,
Man-Kit Lei ,
Eric Klopack ,
Sierra E. Carter ,
Ronald L. Simons ,
Frederick X. Gibbons ,
Justin A. Lavner ,
Robert A. Philibert  and
Kaixiong Ye
Steven R. H. Beach*
Affiliation:
Department of Psychology, University of Georgia, Athens, GA, USA Center for Family Research, University of Georgia, Athens, GA, USA
Mei Ling Ong
Affiliation:
Center for Family Research, University of Georgia, Athens, GA, USA
Man-Kit Lei
Affiliation:
Department of Sociology, University of Georgia, Athens, GA, USA
Eric Klopack
Affiliation:
Department of Sociology, University of Georgia, Athens, GA, USA
Sierra E. Carter
Affiliation:
Department of Psychology, Georgia State University, Atlanta, GA, USA
Ronald L. Simons
Affiliation:
Department of Sociology, University of Georgia, Athens, GA, USA
Frederick X. Gibbons
Affiliation:
Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
Justin A. Lavner
Affiliation:
Department of Psychology, University of Georgia, Athens, GA, USA Center for Family Research, University of Georgia, Athens, GA, USA
Robert A. Philibert
Affiliation:
Department of Psychiatry, University of Iowa, Iowa City, IA, USA Behavioral Diagnostics, Coralville, IA, USA
Kaixiong Ye
Affiliation:
Department of Genetics and Institute of Bioinformatics, University of Georgia, Athens, GA, USA
*
Author for correspondence: Steven R. H. Beach, Center for Family Research, University of Georgia, 1095 College Station Road, Athens, GA 30602-4527; E-mail: [email protected].
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Abstract

Identifying the mechanisms linking early experiences, genetic risk factors, and their interaction with later health consequences is central to the development of preventive interventions and identifying potential boundary conditions for their efficacy. In the current investigation of 412 African American adolescents followed across a 20-year period, we examined change in body mass index (BMI) across adolescence as one possible mechanism linking childhood adversity and adult health. We found associations of childhood adversity with objective indicators of young adult health, including a cardiometabolic risk index, a methylomic aging index, and a count of chronic health conditions. Childhood adversities were associated with objective indicators indirectly through their association with gains in BMI across adolescence and early adulthood. We also found evidence of an association of genetic risk with weight gain across adolescence and young adult health, as well as genetic moderation of childhood adversity's effect on gains in BMI, resulting in moderated mediation. These patterns indicated that genetic risk moderated the indirect pathways from childhood adversity to young adult health outcomes and childhood adversity moderated the indirect pathways from genetic risk to young adult health outcomes through effects on weight gain during adolescence and early adulthood.

Keywords

African Americanchildhood adversitygenetic riskhealth disparitiesobesity
Type
Regular Articles
Information
Development and Psychopathology , Volume 33 , Issue 3 , August 2021 , pp. 803 - 820
Copyright
Copyright © Cambridge University Press 2020

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References

Baldwin, J. R., Arseneault, L., Odgers, C., Belsky, D. W., Mathews, T., Ambler, A., … Danese, A. (2016). Childhood bullying victimization and overweight in young adulthood: A cohort study. Psychosomatic Medicine, 78, 1094–1103.CrossRefGoogle ScholarPubMed
Baldwin, J. R., Reuben, A., Newbury, J. B., & Danese, A. (2019). Agreement between prospective and retrospective measures of childhood maltreatment: A systematic review and meta-analysis. JAMA Psychiatry, 76, 584–593. doi:10.1001/jamapsychiatry.2019.0097CrossRefGoogle ScholarPubMed
Basu, A., McLaughlin, K. A., Misra, S., & Koenen, K. C. (2017). Childhood maltreatment and health impact: The examples of cardiovascular disease and type 2 diabetes mellitus in adults. Clinical Psychology: Science and Practice, 24, 125–139. doi:10.1111/cpsp.12191Google ScholarPubMed
Beach, S. R. H., Dogan, M. V., Lei, M. K., Cutrona, C. E., Gerrard, M., Gibbons, F. X., … Philibert, R.A. (2015). Methylomic aging as a window on lifestyle impact: Tobacco and alcohol use alter rate of biological aging. Journal of the American Geriatrics Society, 63, 2519–2525. doi:10.1111/jgs.13830CrossRefGoogle ScholarPubMed
Beach, S. R. H., Lei, M. K., Simons, R. L., Barr, A. B., Simons, L. G., Ehrlich, K., … Philibert, R. A. (2017). When inflammation and depression go together: The longitudinal effects of parent–child relationships. Development and Psychopathology, 29, 1969–1986. doi:10.1017/S0954579417001523CrossRefGoogle ScholarPubMed
Bellatorre, A., Finch, B., Do, D. P., Bird, C., & Beck, A. (2011). Contextual predictors of cumulative biological risk: Segregation and allostatic load. Social Science Quarterly, 92, 1338–1362. doi:10.1111/j.1540-6237.2011.00821.xGoogle Scholar
Belsky, D. W., Moffitt, T. E., & Caspi, A. (2013). Genetics in population health science: Strategies and opportunities. American Journal of Public Health, 103(Suppl. 1), S73–S83. doi:10.2105/AJPH.2012.301139CrossRefGoogle ScholarPubMed
Belsky, D. W., Moffitt, T. E., Houts, R., Bennett, G. G., Biddle, A. K., Blumenthal, J. A., … Caspi, A. (2012). Polygenic risk, rapid childhood growth, and the development of obesity: Evidence from a 4-decade longitudinal study. Archives of Pediatric and Adolescent Medicine, 166, 515–521.CrossRefGoogle ScholarPubMed
Belsky, D. W., Moffitt, T. E., Sugden, K., Williams, B., Houts, R., McCarthy, J., & Caspi, A. (2013). Development and evaluation of a genetic risk score for obesity. Biodemography and Social Biology, 59, 85–100. doi:10.1080/19485565.2013.774628CrossRefGoogle ScholarPubMed
Björntorp, P. (2001). Do stress reactions cause abdominal obesity and comorbidities? Obesity Review, 2, 73–86.CrossRefGoogle ScholarPubMed
Brewin, C. R., Andrews, B., & Gotlib, I. H. (1993). Psychopathology and early experience: A reappraisal of retrospective reports. Psychological Bulletin, 113, 82–98.CrossRefGoogle ScholarPubMed
Brody, G. H., Beach, S. R. H., Hill, K. G., Howe, G. W., Prado, G., & Fullerton, S. M. (2013). Using genetically informed, randomized prevention trials to test etiological hypotheses about child and adolescent drug use and psychopathology. American Journal of Public Health, 103(Suppl. 1), S19–S24. doi:10.2105/AJPH.2012.301080CrossRefGoogle ScholarPubMed
Brody, G. H., Yu, T., & Beach, S. R. H. (2016). Resilience to adversity and the early origins of disease. Development and Psychopathology, 28, 1347–1365. doi:10.1017/S0954579416000894CrossRefGoogle ScholarPubMed
Brody, G. H., Yu, T., Chen, E., Miller, G. E., Kogan, S. M., & Beach, S. R. (2013). Is resilience only skin deep? Rural African Americans' socioeconomic status-related risk and competence in preadolescence and psychological adjustment and allostatic load at age 19. Psychological Science, 24, 1285–1293.CrossRefGoogle ScholarPubMed
Carey, V. J., Walters, E. E., Colditz, G. A., Solomon, C. G., Willett, W. C., Rosner, B. A., … Manson, J. E. (1997). Body fat distribution and risk of non-insulin-dependent diabetes mellitus in women: The Nurses' Health Study. American Journal of Epidemiology, 145, 614–619.CrossRefGoogle ScholarPubMed
Carnethon, M. R., Pu, J., Howard, G., Albert, M. A., Anderson, C. A. M., Bertoni, A. G., … Yancy, C. W. (2017). Cardiovascular health in African Americans: A scientific statement from the American Heart Association. Circulation, 136, e393–e423. doi:10.1161/CIR.0000000000000534CrossRefGoogle ScholarPubMed
Chan, J. M., Rimm, E. B., Colditz, G. A., Stampfer, M. J., & Willett, W. C. (1994). Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care, 179, 61–69.Google Scholar
Chen, E., Yu, T., Miller, G. E., & Brody, G. H. (2018). Substance use and obesity trajectories in African Americans entering adulthood. American Journal of Preventive Medicine, 55, 856–863.CrossRefGoogle ScholarPubMed
Cockerham, W., Hamby, B. W., & Oates, G. R. (2017). The social determinants of chronic disease. American Journal of Preventative Medicine, 52, S5–S12.CrossRefGoogle ScholarPubMed
Cohen, S., Janicki-Deverts, D., Chen, E., & Matthews, K. A. (2010). Childhood socioeconomic status and adult health. Annals of the New York Academy of Science, 1186, e37–e55.CrossRefGoogle ScholarPubMed
Danese, A., & Tan, M. (2014). Childhood maltreatment and obesity: Systematic review and meta-analysis. Molecular Psychiatry, 19, 544–554. doi:10.1038/mp.2013.54CrossRefGoogle ScholarPubMed
Deightona, S., Nevillea, A., Puschb, D., & Dobson, K. (2018). Biomarkers of adverse childhood experiences: A scoping review. Psychiatry Research, 269, 719–732. doi:10.1016/j.psychres.2018.08.097CrossRefGoogle Scholar
Dietz, W. H. (1994). Critical periods in childhood for the development of obesity. American Journal of Clinical Nutrition, 59, 955–959.CrossRefGoogle ScholarPubMed
Domingue, B. W., Belsky, D. W., Harris, K. M., Smolen, A., McQueen, M. B., & Boardman, J. D. (2014) Polygenic risk predicts obesity in both White and Black young adults. PLOS ONE, 9, e101596. doi:10.1371/journal.pone.0101596CrossRefGoogle ScholarPubMed
Dong, M., Anda, R. F., Felitti, V. J., Dube, S. R., Williamson, D. F., Thompson, T. J., … Giles, W. H. (2004). The interrelatedness of multiple forms of childhood abuse, neglect, and household dysfunction. Child Abuse & Neglect, 28, 771–784.CrossRefGoogle ScholarPubMed
Dudbridge, F. (2013). Power and predictive accuracy of polygenic risk scores. PLOS Genetics, 9, e1003348.CrossRefGoogle ScholarPubMed
Duru, O. K., Harawa, N. T., Kermah, D., & Norris, K. C. (2012). Allostatic load burden and racial disparities in mortality. Journal of the National Medical Association, 104, 89–95.CrossRefGoogle ScholarPubMed
Eckel, R. H., Kahn, R., Robertson, R. M., & Rizza, R. A. (2006). Preventing cardiovascular disease and diabetes: A call to action from the American Diabetes Association and the American Heart Association. Circulation, 113, 2943–2946.CrossRefGoogle Scholar
El-Sayed, M. J. S., & Froguel, P. (2013). From obesity genetics to the future of personalized obesity therapy. National Review of Endocrinology, 9, 402–413.CrossRefGoogle Scholar
Elgar, F. J., Xie, A., Pfortner, T. K., White, J., & Pickett, K. E. (2016). Relative deprivation and risk factors for obesity in Canadian adolescents. Social Science and Medicine, 152, e111–e118.CrossRefGoogle ScholarPubMed
Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., … Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The adverse childhood experiences (ACE) study. American Journal of Preventive Medicine, 14, 245–258.CrossRefGoogle ScholarPubMed
Felson, D. T., Zhang, Y., Hannan, M. T., Nalmark, A., Weissman, B., Allabadi, P., & Levy, D. (1997). Risk factors for incident radiographic knee osteoarthritis in the elderly: The Framingham Study. Arthritis and Rheumatism, 40, 728–733.CrossRefGoogle ScholarPubMed
Gaillard, T. R., & Ose, K. (2010). Ethnic differences in lipids/lipoproteins/apo lipoproteins and proinflammatory markers in non-diabetic African American and White postmenopausal women. Diabetes, 59, A607.Google Scholar
Garasky, S., Stewart, S., Gundersen, C., Lohman, B., & Eisenmann, J. (2009). Family stressors and child obesity. Social Science Research, 38, 755–766.CrossRefGoogle ScholarPubMed
Gee, D. G., & Casey, B. J. (2015). The impact of developmental timing for stress and recovery. Neurobiology of Stress, 1, 184–194. doi:10.1016/j. ynstr.2015.02.001CrossRefGoogle ScholarPubMed
Geronimus, A. T. (1992). The weathering hypothesis and the health of African-American women and infants: Evidence and speculations. Ethnicity and Disease, 2, 207–221.Google ScholarPubMed
Geronimus, A. T., Bound, J., Keene, D., & Hicken, M. (2006). Black-white differences in age trajectories of hypertension prevalence among adult women and men, 1999–2002. Ethnicity & Disease, 16, 40–48.Google Scholar
Geronimus, A. T., Hicken, M., Keene, D., & Bound, J. (2006). “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States. American Journal of Public Health, 96, 826–833. doi:10.2105/ajph.2004.060749CrossRefGoogle ScholarPubMed
Gini, G., & Pozzoli, T. (2009). Association between bullying and psychosomatic problems: A meta-analysis. Pediatrics, 123, 1059–1065.CrossRefGoogle ScholarPubMed
Gouin, J. P., Glaser, R., Malarkey, W. B., Beversdorf, D., & Kiecolt-Glaser, J. (2012). Chronic stress, daily stressors, and circulating inflammatory markers. Health Psychology, 31, 264–268.CrossRefGoogle ScholarPubMed
Hannum, G., Guinney, J., Zhao, L., Zhang, L, Hughes, G., Sadda, S., … Zhang, K. (2013). Genome-wide methylation profiles reveal quantitative views of human aging rates. Molecular Cell, 49, 359–367. doi:10.1016/j.molcel.2012.10.016CrossRefGoogle ScholarPubMed
Hardt, J., & Rutter, M. (2004). Validity of adult retrospective reports of adverse childhood experiences: Review of the evidence. Journal of Child Psychology and Psychiatry, 45, 260–273. doi:10.1111/j.1469-7610.2004.00218.xCrossRefGoogle Scholar
Hayes, A. F. (2015). An index and test of linear moderated mediation. Multivariate Behavioral Research, 50, 1–22.CrossRefGoogle ScholarPubMed
Hitchcock, C., Nixon, R. D. V., & Weber, N. (2014). A review of over general memory in child psychopathology. British Journal of Clinical Psychology, 53, 170–193. doi:10.1111/bjc.12034CrossRefGoogle Scholar
Hitchcock, C., Rees, C., & Dalgleish, T. (2017). The devil's in the detail: Accessibility of specific personal memories supports rose-tinted self-generalizations in mental health and toxic self-generalizations in clinical depression. Journal of Experimental Psychology: General, 146, 1286–1295. doi:10.1037/xge0000343CrossRefGoogle ScholarPubMed
Hitchcock, C., Rodrigues, E., Rees, C., Gormley, S., Dritschel, B., & Dalgleish, T. (2019). Misremembrance of things past: Depression is associated with difficulties in the recollection of both specific and categoric autobiographical memories. Clinical Psychological Science, 7, 693–700. doi:10.1177/2167702619826967CrossRefGoogle ScholarPubMed
Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome Biology, 14, R115. doi:10.1186/gb-2013-14-10-r115CrossRefGoogle ScholarPubMed
Horvath, S., & Raj, K. (2018). DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nature Reviews: Genetics, 19, 371–384. doi:10.1038/s415/6-018-0004-3CrossRefGoogle ScholarPubMed
Hostinar, C. E., Lachman, M. E., Mroczek, D. K., Seeman, T. E., & Miller, G. E. (2015). Additive contributions of childhood adversity and recent stressors to inflammation at midlife: Findings from the MIDUS study. Developmental Psychology, 51, 1630–1644. doi:10.1037/dev0000049CrossRefGoogle ScholarPubMed
Howe, G., Beach, S R. H., Brody, G. H., & Wyman, P. A. (2016). Translating genetic research into prevention and treatment: The baseline target moderated mediator design. Frontiers in Psychology, 6, 1911. doi:10.3389/fpsyg.2015.01911CrossRefGoogle ScholarPubMed
Hoyert, D. L., & Xu, J. (2012). Deaths: Preliminary data for 2011. National Vital Statistics Report, 61, 1–51.Google ScholarPubMed
Hozawa, A., Folsom, A. R., Sharrett, A. R., & Chambless, L. E. (2007). Absolute and attributable risks of cardiovascular disease incidence in relation to optimal and borderline risk factors: Comparison of African American with white subjects: Atherosclerosis Risk in Communities Study. Archives of Internal Medicine, 167, 573–579. doi:10.1001/archinte.167.6.573CrossRefGoogle ScholarPubMed
Justice, A. E., Chittoor, G., Blanco, E., Graff, M., Wang, Y., Albala, C., … Gahagan, S. (2019). Genetic determinants of BMI from early childhood to adolescence: The Santiago Longitudinal Study. Pediatric Obesity, 14, e12479. doi:10.1111/ijpo.12479CrossRefGoogle ScholarPubMed
Jyhava, J., Pedersen, N., & Hagg, S. (2017). Biological age predictors. EBioMedicine, 21, 29–36. doi:10.1186/1753-2000-4-17PMID:20569490CrossRefGoogle Scholar
Katzmarzyk, P. T., Pérusse, L., Malina, R. M., & Bouchard, C. (1999). Seven-year stability of indicators of obesity and adipose tissue distribution in the Canadian population. American Journal of Clinical Nutrition, 69, 1123–1129. doi:10.1093/ajcn/69.6.1123CrossRefGoogle ScholarPubMed
Kessler, R. C., McGonagle, K. A., Zhao, S., Nelson, C. B., Hughes, M., Eshleman, S., … Kendler, K. S. (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: Results from the National Comorbidity Survey. Archives of General Psychiatry, 51, 8–19.CrossRefGoogle ScholarPubMed
Kessler, R. C., McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., … Williams, D. R. (2010). Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. British Journal of Psychiatry, 197, 378–385. doi:10.1192/bjp.bp.110.080499PMID:21037215CrossRefGoogle ScholarPubMed
Khoury, M. J., Gwinn, M., Bowen, M. S., & Dotson, W. D. (2012). Beyond base pairs to bedside: A population perspective on how genomics can improve health. American Journal of Public Health, 102, 34–37.CrossRefGoogle ScholarPubMed
Kimm, S. Y., Barton, B. A., Obarzanek, E., Mcmahon, R. P., Kronsberg, S. S., Waclawiw, M. A., … Daniels, S. R. (2002). Obesity development during adolescence in a biracial cohort: The NHLBI growth and health study. Pediatrics, 110, e54.CrossRefGoogle Scholar
Kittleson, M. M., Meoni, L. A., Wang, N.-Y., Chu, A. Y., Ford, D. E., & Klag, M. J. (2006). Association of childhood socioeconomic status with subsequent coronary heart disease in physicians. Archives of Internal Medicine, 166, e2356–e2361.CrossRefGoogle ScholarPubMed
Konen, J. C., Summerson, J. H., Bell, R. A., & Curtis, L. G. (1999). Racial differences in symptoms and complications in adults with type 2 diabetes mellitus. Ethnicity and Health, 4, 39–49.CrossRefGoogle ScholarPubMed
Lean, M. E. J., Han, T. S., & Seidell, J. C. (1998). Impairment of health and quality of life in people with large waist circumference. Lancet, 351, 853–856.CrossRefGoogle ScholarPubMed
Lei, M. K., Beach, S. R. H., & Simons, R. L. (2018). Childhood trauma, pubertal timing, and cardiovascular risk in adulthood. Health Psychology, 37, 613–617. doi:10.1037/hea0000609CrossRefGoogle ScholarPubMed
Levine, M. E., Lu, A. T., Quach, A., Chen, B. H., Assimes, T. L., Bandinelli, S., … Horvath, S. (2018). An epigenetic biomarker of aging for lifespan and healthspan. Aging, 10, 573–591. doi:10.18632/aging.101414CrossRefGoogle ScholarPubMed
Li, T. Y., Rana, J. S., Manson, J. E., Willett, W. C., Stampfer, M. J., Colditz, G. A., … Hu, F. B. (2006). Obesity as compared with physical activity in predicting risk of coronary heart disease in women. Circulation, 113, 499–506.CrossRefGoogle ScholarPubMed
Li, S., Zhao, J. H., Luan, J., Ekelund, U., Luben, R. N., Khaw, K. T., … Loos, R. J. (2010). Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women from EPIC-Norfolk prospective population study. PLOS Medicine, 7, 1–9.CrossRefGoogle ScholarPubMed
Lu, A. T., Quach, A., Wilson, J. G., Reiner, A. P., Aviv, A., Raj, K., … Horvath, S. (2019). DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging, 11, 303–327. doi:10.18632/aging.101684CrossRefGoogle ScholarPubMed
Lutz, W., Sanderson, W., & Scherbov, S. (2008). The coming acceleration of global population ageing. Nature, 451, 716–719.CrossRefGoogle ScholarPubMed
Manson, J. E., Colditz, G. A., Stampfer, M. J., Willett, W. C., Rosner, B., Monson, R. R., … Hennekens, C. H. (1990). A prospective study of obesity and risk of coronary heart disease in women. New England Journal of Medicine, 322, 882–889.CrossRefGoogle ScholarPubMed
Miller, G. E., Chen, E., & Parker, K. J. (2011). Psychological stress in childhood and susceptibility to the chronic diseases of aging: Moving toward a model of behavioral and biological mechanisms. Psychological Bulletin, 137, 959–997.CrossRefGoogle Scholar
Miller, G. E., & Cole, S. W. (2012). Clustering of depression and inflammation in adolescents previously exposed to childhood adversity. Biological Psychiatry, 72, 34–40. doi:10.1016/j.biopsych.2012.02.034CrossRefGoogle ScholarPubMed
Mills, J., Beach, S. R. H., Dogan, M., Simons, R. A., Gibbons, F. X., Long, J., & Philibert, R. A. (2019). A direct comparison of the relationship of epigenetic aging and epigenetic substance consumption markers to mortality in the Framingham Heart Study. Genes, 10, 30650672.CrossRefGoogle ScholarPubMed
Minkler, M., Fuller-Thompson, E., & Guralnik, J. M. (2006). Gradient 36 biological consequences of socioeconomic inequalities of disability across the socioeconomic spectrum in the United States. New England Journal of Medicine, 355, 695–703.CrossRefGoogle Scholar
Monda, K. L., Chen, G. K., Taylor, K. C., Palmer, C., Edwards, T. L., Lange, L. A., … Haiman, C. A. (2013). A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. Nature Genetics, 45, 690–698. doi:10.1038/ng.2608CrossRefGoogle ScholarPubMed
Mozaffarian, D., Benjamin, E. J., Go, A. S., Arnett, D. K., Blaha, M. J., Cushman, M., … American Heart Association Statistics Committee, Stroke Statistics Subcommittee. (2016). Executive summary: Heart disease and stroke statistics-2016 update: A report from the American Heart Association. Circulation, 133, 447–454.CrossRefGoogle Scholar
Muthén, L. K., & Muthén, B. O. (2017). Mplus: Statistical analysis with latent variables: User's guide (Version 8). Los Angeles: Author.Google Scholar
North, K. E., Graff, M., Adair, L. S., Lange, E. M., Lange, L. A., Guo, G., & Gzordon-Larsen, P. (2010). Genetic epidemiology of BMI and body mass change from adolescence to young adulthood. Obesity, 18, 1474–1476.CrossRefGoogle ScholarPubMed
Nuru-Jeter, A. M., Thorpe, R. J., & Fuller-Thompson, E. (2011). Black-White differences in self-reported disability outcomes in the U.S.: Early childhood to older adulthood. Public Health Reports, 126, 834–843.CrossRefGoogle ScholarPubMed
Nusslock, R., & Miller, G. E. (2016). Early-life adversity and physical and emotional health across the lifespan: A neuroimmune network hypothesis. Biological Psychiatry, 80, 23–32. doi:10.1016/j.biopsych.2015.05.017CrossRefGoogle ScholarPubMed
Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2014). Prevalence of childhood and adult obesity in the United States, 2011–2012. Journal of the American Medical Association, 311, 806–814.CrossRefGoogle ScholarPubMed
Olshansky, S. J., Passaro, D. J., Hershow, R. C., Layden, J., Carnes, B. A., Brody, J., … Ludwig, D. S. (2005). A potential decline in life expectancy in the United States in the 21st century. New England Journal of Medicine, 352, 1138–1145.CrossRefGoogle ScholarPubMed
Osborn, M., & Widom, C. S. (2019). Do documented records and retrospective reports of childhood maltreatment similarly predict chronic inflammation? Psychological Medicine. Advance online publication. doi:10.1017/S0033291719002575Google ScholarPubMed
Phelan, J. C., & Link, B. G. (2005). Controlling disease and creating disparities: A fundamental cause perspective. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60, 27–33.CrossRefGoogle ScholarPubMed
Plomin, R., Haworth, C. M., & Davis, O. S. P. (2009). Common disorders are quantitative traits. Nature Review Genetics, 10, 872–878.CrossRefGoogle ScholarPubMed
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics, 38, 904–909.CrossRefGoogle ScholarPubMed
Radford, L., Corral, S., Bradley, C., & Fisher, H. L. (2013). The prevalence and impact of child maltreatment and other types of victimization in the UK: Findings from a population survey of caregivers, children and young people and young adults. Child Abuse & Neglect, 37, 801–813.CrossRefGoogle Scholar
Reuben, A., Moffitt, T. E., Caspi, A., Belsky, D. W., Harrington, H., Schroeder, F., … Danese, A. (2016). Lest we forget: Comparing retrospective and prospective assessments of adverse childhood experiences in the prediction of adult health. Journal of Child Psychology and Psychiatry, 57, 1103–1112.CrossRefGoogle ScholarPubMed
Rezende, L. F., Rodrigues Lopes, M., Rey-López, J. P., Matsudo, V. K. R., & Luiz, O. (2014). Sedentary behavior and health outcomes: An overview of systematic reviews. PLOS ONE, 9, e105620. doi:10.1371/journal.pone.0105620CrossRefGoogle Scholar
Rimm, E. B., Stampfer, M. J., Giovannucci, E., Ascherio, A., Spiegelman, D., Colditz, G. A., & Willett, W. C. (1995). Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men. American Journal of Epidemiology, 141, 1117–1127.CrossRefGoogle ScholarPubMed
Rissanen, A., Heliövaara, M., Knekt, P., Reunanen, A., Aromaa, A., & Maatela, J. (1990). Risk of disability and mortality due to overweight in a Finnish population. BMJ, 301, 835–837.CrossRefGoogle Scholar
Sanders-Phillips, K. (2009). Racial discrimination: A continuum of violence exposure for children of color. Clinical Child and Family Psychology Review, 12, 174–195.CrossRefGoogle Scholar
Sankar, P., Cho, M. K., Condit, C. M., Hunt, L. M., Koenig, B., Marshall, P., … Spicer, P. (2004). Genetic research and health disparities. Journal of the American Medical Association, 291, 2985–2989. doi:10.1001/jama.291.24.2985CrossRefGoogle ScholarPubMed
Schwingshackl, L., & Hoffmann, G. (2015). Diet quality as assessed by the Healthy Eating Index, the Alternate Healthy Eating Index, the Dietary Approaches to Stop Hypertension Score, and health outcomes: A systematic review and meta-analysis of cohort studies. Journal of the Academy of Nutrition and Dietetics, 115, 780–800.CrossRefGoogle ScholarPubMed
Shonkoff, J. P., & Bales, S. N. (2011). Science does not speak for itself: Translating child development research for the public and its policymakers. Child Development, 82, 17–32.CrossRefGoogle Scholar
Shonkoff, J., Boyce, T., & McEwen, B. (2009). Neuroscience, molecular biology, and the childhood roots of health disparities. Journal of the American Medical Association, 301, 2252–2259.CrossRefGoogle ScholarPubMed
Shonkoff, J. P., Garner, A. S., Siegel, B. S., Dobbins, M. I., Earls, M. F., McGuinn, L., … Wood, D. L. (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129, 232–246.CrossRefGoogle ScholarPubMed
Silventoinen, K., Jelenkovic, A., Sund, R., Yokoyama, Y., Hur, Y-M., Cozen, W., … Kaprio, J. (2017). Differences in genetic and environmental variation in adult BMI by sex, age, time period, and region: An individual-based pooled analyses of 40 twin cohorts. American Journal of Clinical Nutrition, 106, 457–466. doi:10.3945/ajcn.117.153643CrossRefGoogle Scholar
Simons, R. L., Lei, M. K., Beach, S. R., Barr, A. B., Cutrona, C. E., Gibbons, F. X., & Philibert, R. A. (2017). An index of the ratio of inflammatory to antiviral cell types mediates the effects of social adversity and age on chronic illness. Social Science & Medicine, 185, 158–165.CrossRefGoogle ScholarPubMed
Simons, R. L., Lei, M. K., Beach, S. R. H., Barr, A. B., Simons, L. G., Gibbons, F. X., & Philibert, R. A. (2018). Discrimination, segregation, and chronic inflammation: Testing the weathering explanation for the poor health of Black Americans. Developmental Psychology, 54, 1993–2006. doi:10.1037/dev0000511CrossRefGoogle ScholarPubMed
Slopen, N., Williams, D. R., Seedat, S., Moomal, H., Herman, A., & Stein, D. J. (2010). Adversities in childhood and adult psychopathology in the South Africa Stress and Health Study: Associations with first-onset DSM-IV disorders. Social Science & Medicine, 71, 1847–1854.CrossRefGoogle ScholarPubMed
Solís, C. B., Kelly-Irving, M., Fantin, R., Darnaudéry, M., Torrisani, J., Lang, T., & Delpierre, C. (2015). Adverse childhood experiences and physiological wear-and-tear in midlife: Findings from the 1958 British birth cohort. PNAS, 112, E738–E746. doi:10.1073/pnas.1417325112CrossRefGoogle Scholar
Sovio, U., Mook-Kanamori, D. O., Warrington, N. M., Lawrence, R., Briollais, L., Palmer, C. N., … Timpson, N. J. (2011). Association between common variation at the FTO locus and changes in body mass index from infancy to late childhood: The complex nature of genetic association through growth and development. PLOS Genetics, 7, e1001307. doi:10.1371/journal.pgen.1001307CrossRefGoogle Scholar
Speliotes, E. K., Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., … Loos, R. J. (2010). Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nature Genetics, 42, 937–948.CrossRefGoogle ScholarPubMed
Stepanikova, I., Baker, E. H., Simoni, Z. R., Zhu, A., Rutland, S. B., Sims, M., & Wilkinson, L. L. (2017). The role of perceived discrimination in obesity among African Americans. American Journal of Preventive Medicine, 52(Suppl. 1), S77–S85. doi:10.1016/j.amepre.2016.07.034CrossRefGoogle ScholarPubMed
Suglia, S. F., Koenen, K. C., Boyton-Jarrett, R., Chan, P. S., Clark, C. J., Danese, A., … Zachariah, J. P. (2018). Childhood and adolescent adversity and cardiometabolic outcomes: A scientific statement from the American Heart Association. Circulation, 137, e15–e28. doi:10.1161/CIR.0000000000000536CirculationCrossRefGoogle ScholarPubMed
Sumner, J. A., Griffith, J. W., & Mineka, S. (2010). Over general autobiographical memory as a predictor of the course of depression: A meta-analysis. Behaviour Research and Therapy, 48, 614–625. doi:10.1016/j.brat.2010.03.013CrossRefGoogle Scholar
Tamayo, T., Chrinstian, H., & Rathmann, W. (2010). Impact of early psychosocial factors (Childhood socioeconomic factors and adversities) on future risk of type 2 diabetes, metabolic disturbances, and obesity: A systematic review. BMC Public Health, 10, 525–539.CrossRefGoogle ScholarPubMed
Thompson, D., Edelsberg, J., Colditz, G. A., Bird, A. P., & Oster, G. (1999). Lifetime health and economic consequences of obesity. Archives of Internal Medicine, 159, 2177–2183.CrossRefGoogle ScholarPubMed
Turner, R. J., Thomas, C. S., & Brown, T. H. (2016). Childhood adversity and adult health: Evaluating intervening mechanisms. Social Science and Medicine, 156, e114–e124.CrossRefGoogle ScholarPubMed
van Vreeswijk, M. F., & de Wilde, E. J. (2004). Autobiographical memory specificity, psychopathology, depressed mood and the use of the Autobiographical Memory Test: A meta-analysis. Behaviour Research and Therapy, 42, 731–743. doi:10.1016/S0005-7967(03)00194-3CrossRefGoogle ScholarPubMed
Visscher, T. L. S., & Seidell, J. C. (2001). The public health impact of obesity. Annual Review of Public Health, 22, 355–375.CrossRefGoogle ScholarPubMed
Wall, M. M., Mason, S. M., Liu, J., Olfson, M., Neumark-Sztainer, D., & Blanco, C. (2019). Childhood psychosocial challenges and risk for obesity in U.S. men and women. Translational Psychiatry, 9, 16–28. doi:10.1038/s41398-018-0341-1CrossRefGoogle ScholarPubMed
Wickrama, K. A., Lee, T. K., & O'Neal, C. W. (2015). Stressful life experiences in adolescence and cardiometabolic risk factors in young adulthood. Journal of Adolescent Health, 56, 456–463.CrossRefGoogle ScholarPubMed
Williams, D. R. (2012). Miles to go before we sleep: Racial inequities in health. Journal of Health and Social Behavior, 53, 279–295.CrossRefGoogle ScholarPubMed
Williams, J. M. G., Barnhofer, T., Crane, C., Herman, D., Raes, F., Watkins, E., & Dalgleish, T. (2007). Autobiographical memory specificity and emotional disorder. Psychological Bulletin, 133, 122–148.CrossRefGoogle ScholarPubMed
Wojcik, G. L., Graff, M., Nishimura, K. K., Tao, R., Haessler, J., Gignoux, C. R., … Carlson, C. S. (2019). Genetic analyses of diverse populations improves discovery for complex traits. Nature, 570, 514–518. doi:10.1038/s41586-019-1310-4CrossRefGoogle ScholarPubMed
Zhang, T., Whelton, P. K., Xi, B., Krousel-Wood, M., Bazzano, L., He, J., … Li, S. (2019). Rate of change in body mass index at different ages during childhood and adult obesity risk. Pediatric Obesity, 14, e12513. doi:10.1111/ijpo.12513CrossRefGoogle ScholarPubMed
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