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Socioeconomic status and type 2 diabetes in African American and non-Hispanic White women and men: Evidence from the Third National Health and Nutrition Examination Survey


  • Robbins, J.M.
  • Vaccarino, V.
  • Zhang, H.
  • Kasl, S.V.


Objectives. This study examined the associations of poverty income ratio (PIR), education, and occupational status with type 2 diabetes prevalence among African American and non-Hispanic White (White) women and men aged 40 to 74 years. Methods. We analyzed cross-sectional data from the Third National Health and Nutrition Examination Survey, controlling for age and examination-related variables. Results. Among African American women, there was a strong, graded association between PIR and diabetes, which remained significant after other risk factors were adjusted for. All 3 variables were significantly associated with diabetes among White women. Among White men, only PIR was significantly associated with diabetes. Controlling for risk factors substantially attenuated these associations among White women. There were no significant associations for African American men. Conclusions. Socioeconomic status is associated with type 2 diabetes prevalence among women, but not consistently among men. Diabetes prevalence is more strongly associated with PIR than with education or occupational status. These associations are largely independent of other risk factors, especially among African American women. Economic resources should be addressed in efforts to explain and reverse the increasing prevalence of diabetes in the United States.

Suggested Citation

  • Robbins, J.M. & Vaccarino, V. & Zhang, H. & Kasl, S.V., 2001. "Socioeconomic status and type 2 diabetes in African American and non-Hispanic White women and men: Evidence from the Third National Health and Nutrition Examination Survey," American Journal of Public Health, American Public Health Association, vol. 91(1), pages 76-83.
  • Handle: RePEc:aph:ajpbhl:2001:91:1:76-83_6

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    Cited by:

    1. Elena DRUICĂ & Zizi GOSCHIN & Cristian BĂICUȘ, 2018. "Regional socio-economic factors influencing diabetes incidence: the case of Romania," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 9, pages 87-109, June.
    2. So-Ra Kim & Kyungdo Han & Jin-Young Choi & Jennifer Ersek & Junxiu Liu & Sun-Jin Jo & Kang-Sook Lee & Hyeon Woo Yim & Won-Chul Lee & Yong Gyu Park & Seung-Hwan Lee & Yong-Moon Park, 2015. "Age- and Sex-Specific Relationships between Household Income, Education, and Diabetes Mellitus in Korean Adults: The Korea National Health and Nutrition Examination Survey, 2008-2010," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-15, January.
    3. Ramya Chari & Thomas A. Burke & Ronald H. White & Mary A. Fox, 2012. "Integrating Susceptibility into Environmental Policy: An Analysis of the National Ambient Air Quality Standard for Lead," IJERPH, MDPI, vol. 9(4), pages 1-20, March.
    4. Karoline Kragelund Nielsen & Peter Damm & Anil Kapur & Vijayam Balaji & Madhuri S Balaji & Veerasamy Seshiah & Ib C Bygbjerg, 2016. "Risk Factors for Hyperglycaemia in Pregnancy in Tamil Nadu, India," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-18, March.
    5. Shoham, David A. & Vupputuri, Suma & Kaufman, Jay S. & Kshirsagar, Abhijit V. & Diez Roux, Ana V. & Coresh, Josef & Heiss, Gerardo, 2008. "Kidney disease and the cumulative burden of life course socioeconomic conditions: The Atherosclerosis Risk in Communities (ARIC) Study," Social Science & Medicine, Elsevier, vol. 67(8), pages 1311-1320, October.
    6. Jiaoling Huang & Qin Zhu & Jing Guo, 2020. "Can Health Disparity Be Eliminated? The Role of Family Doctor Played in Shanghai, China," IJERPH, MDPI, vol. 17(15), pages 1-15, July.
    7. Gebreab, Samson Y. & Diez-Roux, Ana V. & Hickson, DeMarc A. & Boykin, Shawn & Sims, Mario & Sarpong, Daniel F. & Taylor, Herman A. & Wyatt, Sharon B., 2012. "The contribution of stress to the social patterning of clinical and subclinical CVD risk factors in African Americans: The Jackson Heart Study," Social Science & Medicine, Elsevier, vol. 75(9), pages 1697-1707.
    8. Reiko Ishihara & Akira Babazono & Ning Liu & Reiko Yamao, 2022. "Impact of Income and Industry on New-Onset Diabetes among Employees: A Retrospective Cohort Study," IJERPH, MDPI, vol. 19(3), pages 1-14, January.
    9. Nordström, Jonas & Thunström, Linda, 2011. "Can targeted food taxes and subsidies improve the diet? Distributional effects among income groups," Food Policy, Elsevier, vol. 36(2), pages 259-271, April.
    10. Lily O’Hara & Jane Taylor, 2018. "What’s Wrong With the ‘War on Obesity?’ A Narrative Review of the Weight-Centered Health Paradigm and Development of the 3C Framework to Build Critical Competency for a Paradigm Shift," SAGE Open, , vol. 8(2), pages 21582440187, May.
    11. Hadewijch Vandenheede & Patrick Deboosere & Albert Espelt & Matthias Bopp & Carme Borrell & Giuseppe Costa & Terje Eikemo & Roberto Gnavi & Rasmus Hoffmann & Ivana Kulhanova & Margarete Kulik & Mall L, 2015. "Educational inequalities in diabetes mortality across Europe in the 2000s: the interaction with gender," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 60(4), pages 401-410, May.
    12. D. Sittig & H. Friedel & J. Wasem, 2015. "Prevalence and treatment costs of type 2 diabetes in Germany and the effects of social and demographical differences," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(3), pages 305-311, April.
    13. Dinca-Panaitescu, Serban & Dinca-Panaitescu, Mihaela & Bryant, Toba & Daiski, Isolde & Pilkington, Beryl & Raphael, Dennis, 2011. "Diabetes prevalence and income: Results of the Canadian Community Health Survey," Health Policy, Elsevier, vol. 99(2), pages 116-123, February.
    14. Alberto Palloni & Jason Thomas, 2013. "Estimation of Covariate Effects With Current Status Data and Differential Mortality," Demography, Springer;Population Association of America (PAA), vol. 50(2), pages 521-544, April.

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