Uduakobong E Ntuk1, Jason M R Gill2, Daniel F Mackay1, Naveed Sattar2, Jill P Pell3. 1. Institute of Health and Wellbeing, University of Glasgow, Glasgow, U.K. 2. Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K. 3. Institute of Health and Wellbeing, University of Glasgow, Glasgow, U.K. jill.pell@glasgow.ac.uk.
Abstract
OBJECTIVE: To compare the relationship between adiposity and prevalent diabetes across ethnic groups in the UK Biobank cohort and to derive ethnic-specific obesity cutoffs that equate to those developed in white populations in terms of diabetes prevalence. RESEARCH DESIGN AND METHODS: UK Biobank recruited 502,682 U.K. residents aged 40-69 years. We used baseline data on the 490,288 participants from the four largest ethnic subgroups: 471,174 (96.1%) white, 9,631 (2.0%) South Asian, 7,949 (1.6%) black, and 1,534 (0.3%) Chinese. Regression models were developed for the association between anthropometric measures (BMI, waist circumference, percentage body fat, and waist-to-hip ratio) and prevalent diabetes, stratified by sex and adjusted for age, physical activity, socioeconomic status, and heart disease. RESULTS: Nonwhite participants were two- to fourfold more likely to have diabetes. For the equivalent prevalence of diabetes at 30 kg/m(2) in white participants, BMI equated to the following: South Asians, 22.0 kg/m(2); black, 26.0 kg/m(2); Chinese women, 24.0 kg/m(2); and Chinese men, 26.0 kg/m(2). Among women, a waist circumference of 88 cm in the white subgroup equated to the following: South Asians, 70 cm; black, 79 cm; and Chinese, 74 cm. Among men, a waist circumference of 102 cm equated to 79, 88, and 88 cm for South Asian, black, and Chinese participants, respectively. CONCLUSIONS: Obesity should be defined at lower thresholds in nonwhite populations to ensure that interventions are targeted equitably based on equivalent diabetes prevalence. Furthermore, within the Asian population, a substantially lower obesity threshold should be applied to South Asian compared with Chinese groups.
OBJECTIVE: To compare the relationship between adiposity and prevalent diabetes across ethnic groups in the UK Biobank cohort and to derive ethnic-specific obesity cutoffs that equate to those developed in white populations in terms of diabetes prevalence. RESEARCH DESIGN AND METHODS: UK Biobank recruited 502,682 U.K. residents aged 40-69 years. We used baseline data on the 490,288 participants from the four largest ethnic subgroups: 471,174 (96.1%) white, 9,631 (2.0%) South Asian, 7,949 (1.6%) black, and 1,534 (0.3%) Chinese. Regression models were developed for the association between anthropometric measures (BMI, waist circumference, percentage body fat, and waist-to-hip ratio) and prevalent diabetes, stratified by sex and adjusted for age, physical activity, socioeconomic status, and heart disease. RESULTS: Nonwhite participants were two- to fourfold more likely to have diabetes. For the equivalent prevalence of diabetes at 30 kg/m(2) in white participants, BMI equated to the following: South Asians, 22.0 kg/m(2); black, 26.0 kg/m(2); Chinese women, 24.0 kg/m(2); and Chinese men, 26.0 kg/m(2). Among women, a waist circumference of 88 cm in the white subgroup equated to the following: South Asians, 70 cm; black, 79 cm; and Chinese, 74 cm. Among men, a waist circumference of 102 cm equated to 79, 88, and 88 cm for South Asian, black, and Chinese participants, respectively. CONCLUSIONS: Obesity should be defined at lower thresholds in nonwhite populations to ensure that interventions are targeted equitably based on equivalent diabetes prevalence. Furthermore, within the Asian population, a substantially lower obesity threshold should be applied to South Asian compared with Chinese groups.
Authors: Eun Ji Kim; Taekyu Kim; Joseph Conigliaro; Jane M Liebschutz; Michael K Paasche-Orlow; Amresh D Hanchate Journal: J Gen Intern Med Date: 2018-05-07 Impact factor: 5.128
Authors: Maria Rosario G Araneta; Alka M Kanaya; William C Hsu; Healani K Chang; Andrew Grandinetti; Edward J Boyko; Tomoshige Hayashi; Steven E Kahn; Donna L Leonetti; Marguerite J McNeely; Yukiko Onishi; Kyoko K Sato; Wilfred Y Fujimoto Journal: Diabetes Care Date: 2015-02-09 Impact factor: 19.112
Authors: D J Cuthbertson; T Steele; J P Wilding; J C Halford; J A Harrold; M Hamer; F Karpe Journal: Int J Obes (Lond) Date: 2017-01-12 Impact factor: 5.095