Journal of Clinical & Translational Endocrinology (Jun 2016)

Ethnic variations in diabetes and prediabetes prevalence and the roles of insulin resistance and β-cell function: The CARRS and NHANES studies

  • U.P. Gujral,
  • V. Mohan,
  • R. Pradeepa,
  • M. Deepa,
  • R.M. Anjana,
  • N.K. Mehta,
  • E.W. Gregg,
  • K.M. Narayan

DOI
https://doi.org/10.1016/j.jcte.2016.02.004
Journal volume & issue
Vol. 4, no. C
pp. 19 – 27

Abstract

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Aims: It is unclear how the prevalence of diabetes in Asian Indians in urban India compares to that of race/ethnic groups in the US that may have different underlying susceptibilities. Therefore, we examined ethnic variations in the prevalence of type 2 diabetes, iIFG, iIGT, IFG + IGT, and the associated risk factors in Asian Indians in Chennai, India, and Whites, Blacks, and Hispanics in the United States. Methods: Cross-sectional analyses, using representative samples of 4867 Asian Indians aged 20–74 years from Chennai, India, in the Centre for Cardiometabolic Risk Reduction in South-Asia study (CARRS) (2010–2011) and 6512 US Whites, Blacks, and Hispanics aged 20–74 years from the National Health and Nutrition Examination Survey (NHANES) (2007–2012). Results: The age-adjusted prevalence of type 2 diabetes was highest in Asian Indians (men: 28.4, 95% CI: 25.9, 31.0; women: 30.6, 95% CI, 27.5, 33.9) and lowest in Caucasians (men: 12.2, 95% CI, 10.3, 14.4, women: 9.5, 95% CI, 7.9, 11.5). Asian Indians had the lowest prediabetes prevalence (men: 19.0, 95% CI, 17.2, 20.8; women: 27.2, 95% CI, 22.8, 32.1) and Caucasians had the highest (men; 46.5, 95% CI, 43.5, 49.6, women: 34.4, 95% CI, 31.7, 37.3). However, there were differences in prediabetes prevalence by gender and prediabetes state. The inclusion of HOMA-β in standardized polytomous logistic regression models resulted in a greater odds of diabetes in Blacks and Hispanics compared to Asian Indians. Conclusions: The high prevalence of diabetes in Asian Indians may be due to innate susceptibilities for β-cell dysfunction in this high risk population.

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