Impact of race/ethnicity on insulin resistance and hypertriglyceridaemia. (March 2019)

• Record Type: Journal Article
• Authors: Raygor, Viraj; Abbasi, Fahim; Lazzeroni, Laura C; Kim, Sun; Ingelsson, Erik; Reaven, Gerald M; Knowles, Joshua W
• Is Part Of: Diabetes & vascular disease research. Volume 16:Number 2(2019:Mar.)
• Page Start: 153
• Page End: 159
• Publication Date: 2019-03
• Subjects: Insulin resistance -- race -- triglyceride -- modified insulin suppression test; Diabetic angiopathies -- Periodicals; 616.462005
• DOI: 10.1177/1479164118813890
• Languages: English
• ISSNs: 1479-1641

Abstract

Objective: Insulin sensitivity affects plasma triglyceride concentration and both differ by race/ethnicity. The purpose of this study was to provide a comprehensive assessment of the variation in insulin sensitivity and its relationship to hypertriglyceridaemia between five race/ethnic groups. Research design and methods: In this cross-sectional study, clinical data for 1025 healthy non-Hispanic White, Hispanic White, East Asian, South Asian and African American individuals were analysed. Insulin-mediated glucose disposal (a direct measure of peripheral insulin sensitivity) was measured using the modified insulin suppression test. Statistical analysis was performed using analysis of co-variance. Results: Of the study participants, 63% were non-Hispanic White, 9% were Hispanic White, 11% were East Asian, 11% were South Asian and 6% were African American. Overall, non-Hispanic Whites and African Americans displayed greater insulin sensitivity than East Asians and South Asians. Triglyceride concentration was positively associated with insulin resistance in all groups, including African Americans. Nevertheless, for any given level of insulin sensitivity, African Americans had the lowest triglyceride concentrations. Conclusion: Insulin sensitivity, as assessed by a direct measure of insulin-mediated glucose disposal, and its relationship to triglyceride concentration vary across five race/ethnic groups. Understanding these relationships is crucial for accurate cardiovascular risk stratification and prevention.