IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v127y2015icp150-158.html
   My bibliography  Save this article

Genetic vulnerability to diabetes and obesity: Does education offset the risk?

Author

Listed:
  • Liu, S.Y.
  • Walter, S.
  • Marden, J.
  • Rehkopf, D.H.
  • Kubzansky, L.D.
  • Nguyen, T.
  • Glymour, M.M.

Abstract

The prevalence of type 2 diabetes (T2D) and obesity has recently increased dramatically. These common diseases are likely to arise from the interaction of multiple genetic, socio-demographic and environmental risk factors. While previous research has found genetic risk and education to be strong predictors of these diseases, few studies to date have examined their joint effects. This study investigates whether education modifies the association between genetic background and risk for type 2 diabetes (T2D) and obesity. Using data from non-Hispanic Whites in the Health and Retirement Study (HRS, n = 8398), we tested whether education modifies genetic risk for obesity and T2D, offsetting genetic effects; whether this effect is larger for individuals who have high risk for other (unobserved) reasons, i.e., at higher quantiles of HbA1c and BMI; and whether effects differ by gender. We measured T2D risk using Hemoglobin A1c (HbA1c) level, and obesity risk using body-mass index (BMI). We constructed separate genetic risk scores (GRS) for obesity and diabetes respectively based on the most current available information on the single nucleotide polymorphism (SNPs) confirmed as genome-wide significant predictors for BMI (29 SNPs) and diabetes risk (39 SNPs). Linear regression models with years of schooling indicate that the effect of genetic risk on HbA1c is smaller among people with more years of schooling and larger among those with less than a high school (HS) degree compared to HS degree-holders. Quantile regression models show that the GRS × education effect systematically increased along the HbA1c outcome distribution; for example the GRS × years of education interaction coefficient was −0.01 (95% CI = −0.03, 0.00) at the 10th percentile compared to −0.03 (95% CI = −0.07, 0.00) at the 90th percentile. These results suggest that education may be an important socioeconomic source of heterogeneity in responses to genetic vulnerability to T2D.

Suggested Citation

  • Liu, S.Y. & Walter, S. & Marden, J. & Rehkopf, D.H. & Kubzansky, L.D. & Nguyen, T. & Glymour, M.M., 2015. "Genetic vulnerability to diabetes and obesity: Does education offset the risk?," Social Science & Medicine, Elsevier, vol. 127(C), pages 150-158.
    • Handle: RePEc:eee:socmed:v:127:y:2015:i:c:p:150-158
    DOI: 10.1016/j.socscimed.2014.09.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953614005760
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2014.09.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Borrell, L.N. & Dallo, F.J. & White, K., 2006. "Education and diabetes in a racially and ethnically diverse population," American Journal of Public Health, American Public Health Association, vol. 96(9), pages 1637-1642.
    2. Reiss, D. & Leve, L.D. & Neiderhiser, J.M., 2013. "How genes and the social environment moderate each other," American Journal of Public Health, American Public Health Association, vol. 103(SUPPL.1), pages 111-121.
    3. Lois M. Verbrugge & Purvi Sevak, 2002. "Use, Type, and Efficacy of Assistance for Disability," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 57(6), pages 366-379.
    4. Ross, Catherine E. & Mirowsky, John, 2006. "Sex differences in the effect of education on depression: Resource multiplication or resource substitution?," Social Science & Medicine, Elsevier, vol. 63(5), pages 1400-1413, September.
    5. Cohen, Alison K. & Rehkopf, David H. & Deardorff, Julianna & Abrams, Barbara, 2013. "Education and obesity at age 40 among American adults," Social Science & Medicine, Elsevier, vol. 78(C), pages 34-41.
    6. Giorgio Brunello & Daniele Fabbri & Margherita Fort, 2013. "The Causal Effect of Education on Body Mass: Evidence from Europe," Journal of Labor Economics, University of Chicago Press, vol. 31(1), pages 195-223.
    7. Nick Colegrave & Graeme D. Ruxton, 2003. "Confidence intervals are a more useful complement to nonsignificant tests than are power calculations," Behavioral Ecology, International Society for Behavioral Ecology, vol. 14(3), pages 446-447, May.
    8. F. Thomas Juster & Richard Suzman, 1995. "An Overview of the Health and Retirement Study," Journal of Human Resources, University of Wisconsin Press, vol. 30, pages 7-56.
    9. Wendy Johnson & Kirsten Ohm Kyvik & Axel Skytthe & Ian J Deary & Thorkild I A Sørensen, 2011. "Education Modifies Genetic and Environmental Influences on BMI," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-11, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuwei Qi & Annemarie Koster & Martin van Boxtel & Sebastian Köhler & Miranda Schram & Nicolaas Schaper & Coen Stehouwer & Hans Bosma, 2019. "Adulthood Socioeconomic Position and Type 2 Diabetes Mellitus—A Comparison of Education, Occupation, Income, and Material Deprivation: The Maastricht Study," IJERPH, MDPI, vol. 16(8), pages 1-13, April.
    2. Amin, Vikesh & Böckerman, Petri & Viinikainen, Jutta & Smart, Melissa C. & Bao, Yanchun & Kumari, Meena & Pitkänen, Niina & Lehtimäki, Terho & Raitakari, Olli & Pehkonen, Jaakko, 2017. "Gene-environment interactions between education and body mass: Evidence from the UK and Finland," Social Science & Medicine, Elsevier, vol. 195(C), pages 12-16.
    3. Amin, Vikesh & Fletcher, Jason & Behrman, Jere & Flores, Carlos A & Flores, Carlos A & Flores-Lagunes, Alfonso & Kohler, Hans Peter, 2019. "Mental Health, Schooling Attainment and Polygenic Scores: Are There Significant Gene-Environment Associations?," SocArXiv wjp5v, Center for Open Science.
    4. Tamara Power & Ray Kelly & Kim Usher & Leah East & Jo Travaglia & Hamish Robertson & Ann Wong & Debra Jackson, 2020. "Living with diabetes and disadvantage: A qualitative, geographical case study," Journal of Clinical Nursing, John Wiley & Sons, vol. 29(13-14), pages 2710-2722, July.
    5. Amin, Vikesh & Dunn, Paul & Spector, Tim, 2018. "Does education attenuate the genetic risk of obesity? Evidence from U.K. Twins," Economics & Human Biology, Elsevier, vol. 31(C), pages 200-208.
    6. Bierut, Laura & Biroli, Pietro & Galama, Titus J. & Thom, Kevin, 2023. "Challenges in studying the interplay of genes and environment. A study of childhood financial distress moderating genetic predisposition for peak smoking," Journal of Economic Psychology, Elsevier, vol. 98(C).
    7. Vikesh Amin & Jere R. Behrman & Jason M. Fletcher & Carlos A. Flores & Alfonso Flores-Lagunes & Hans-Peter Kohler, 2020. "Mental Health, Schooling Attainment and Polygenic Scores: Are There Significant Genetic-Environmental Associations?," PIER Working Paper Archive 20-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Mirjam Frank & Nico Dragano & Marina Arendt & Andreas J Forstner & Markus M Nöthen & Susanne Moebus & Raimund Erbel & Karl-Heinz Jöckel & Börge Schmidt, 2019. "A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-14, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bahadır Dursun & Resul Cesur, 2016. "Transforming lives: the impact of compulsory schooling on hope and happiness," Journal of Population Economics, Springer;European Society for Population Economics, vol. 29(3), pages 911-956, July.
    2. Rashmita Basu, 2013. "Willingness-to-pay to prevent Alzheimer’s disease: a contingent valuation approach," International Journal of Health Economics and Management, Springer, vol. 13(3), pages 233-245, December.
    3. Elder, Harold W. & Rudolph, Patricia M., 2000. "Beliefs and actions: expectations and savings decisions by older Americans," Financial Services Review, Elsevier, vol. 9(1), pages 33-45, 00.
    4. Benson, Rebecca & von Hippel, Paul T. & Lynch, Jamie L., 2018. "Does more education cause lower BMI, or do lower-BMI individuals become more educated? Evidence from the National Longitudinal Survey of Youth 1979," Social Science & Medicine, Elsevier, vol. 211(C), pages 370-377.
    5. Pedro Albarran Pérez & Marisa Hidalgo Hidalgo & Iñigo Iturbe-Ormaetxe Kortajarene, 2017. "Schooling and adult health: Can education overcome bad early-life conditions?," Working Papers. Serie AD 2017-09, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. Hugo Benitez-Silva & Moshe Buchinsky & John Rust & Emine Boz & Joseph B. Nichols & Sharbani Roy & Ignez Tristao, 2005. "Health Status, Insurance, and Expenditures in the Transition from Work to Retirement," Department of Economics Working Papers 05-11, Stony Brook University, Department of Economics.
    7. Wändi Bruine de Bruin & Michael F. Bryan & Simon M. Potter & Giorgio Topa & Wilbert Van der Klaauw, 2008. "Rethinking the measurement of household inflation expectations: preliminary findings," Staff Reports 359, Federal Reserve Bank of New York.
    8. Tansel, Aysit & Karao?lan, Deniz, 2016. "The Causal Effect of Education on Health Behaviors: Evidence from Turkey," IZA Discussion Papers 10020, Institute of Labor Economics (IZA).
    9. Khwaja, Ahmed & Silverman, Dan & Sloan, Frank, 2007. "Time preference, time discounting, and smoking decisions," Journal of Health Economics, Elsevier, vol. 26(5), pages 927-949, September.
    10. Pamela Giustinelli & Charles F. Manski, 2018. "Survey Measures Of Family Decision Processes For Econometric Analysis Of Schooling Decisions," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 81-99, January.
    11. Steven F. Venti & David A. Wise, 2001. "Choice, Chance, and Wealth Dispersion at Retirement," NBER Chapters, in: Aging Issues in the United States and Japan, pages 25-64, National Bureau of Economic Research, Inc.
    12. Tansel, Aysit & Öztürk, Ceyhan & Erdil, Erkan, 2021. "The Impact of Body Mass Index on Growth, Schooling, Productivity, and Savings: A Cross-Country Study," GLO Discussion Paper Series 929, Global Labor Organization (GLO).
    13. Gabriel A. Picone & Frank Sloan & Justin G. Trogdon, 2004. "The effect of the tobacco settlement and smoking bans on alcohol consumption," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 1063-1080, October.
    14. Nicole Schneeweis & Vegard Skirbekk & Rudolf Winter-Ebmer, 2012. "Does schooling improve cognitive functioning at older ages?," Economics working papers 2012-11, Department of Economics, Johannes Kepler University Linz, Austria.
    15. Ke-wei Wang & Zhan-kun Shu & Le Cai & Jun-Qing Wu & Wei Wei, 2013. "Assessment of the Magnitude of Contextual and Individual Demographic Effects on Diabetes Mellitus and Glucose Intolerance in Rural Southwest China: A Multilevel Analysis," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
    16. Axel Börsch-Supan & Tabea Bucher-Koenen & Felizia Hanemann, 2018. "Early Determinants of Work Disability in an International Perspective," NBER Working Papers 25142, National Bureau of Economic Research, Inc.
    17. Cuypers, I.R.P., 2009. "Essays on equity joint ventures, uncertainty and experience," Other publications TiSEM 8dc79e86-c625-467f-a450-8, Tilburg University, School of Economics and Management.
    18. Rietveld, Cornelius A. & Webbink, Dinand, 2016. "On the genetic bias of the quarter of birth instrument," Economics & Human Biology, Elsevier, vol. 21(C), pages 137-146.
    19. Markus Frölich & Martin Huber, 2017. "Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1645-1666, November.
    20. Christopher House & John Laitner & Dmitriy Stolyarov, 2008. "Valuing Lost Home Production Of Dual Earner Couples," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 49(2), pages 701-736, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:127:y:2015:i:c:p:150-158. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.