Cited by 220Diabetes, Cardiovascular Risks, and LipoproteinsObesity, Physical Activity, DietAdipokines, Inflammation, and Metabolic Diseases

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Ethnic-Specific Obesity Cutoffs for Diabetes Risk: Cross-sectional Study of 490,288 UK Biobank Participants

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Ntuk, Uduakobong E., Gill, Jason M.R., Mackay, Daniel F., Sattar, Naveed, Pell, Jill P.·2014·Diabetes Care

DOI 10.2337/dc13-2966

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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/m2 in white participants, BMI equated to the following: South Asians, 22.0 kg/m2; black, 26.0 kg/m2; Chinese women, 24.0 kg/m2; and Chinese men, 26.0 kg/m2. 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.

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A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
International Diabetes Federation 2017
Carracher, A. M., Marathe, P. H., & Close, K. L. (2018) · Journal of Diabetes · doi:10.1111/1753-0407.12644 · Cited by 13,379
Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies
(2004) · The Lancet · doi:10.1016/s0140-6736(03)15268-3 · Cited by 12,717
Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians
McKeigue, P. M., Shah, B., & Marmot, M. G. (1991) · The Lancet · doi:10.1016/0140-6736(91)91164-p · Cited by 1,618
Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management.
Misra, A., Chowbey, P. K., Makkar, B. M., Vikram, N. K., Wasir, J. S., Chadha, D., Joshi, S., SADIKOT, S. M., Gupta, R., Gulati, S., et al. (2009) · PubMed · Cited by 1,165
Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis
Vazquez, G., Duval, S., Jacobs, D. R., & Silventoinen, K. (2007) · Epidemiologic Reviews · doi:10.1093/epirev/mxm008 · Cited by 976
WEIGHT AS A RISK FACTOR FOR CLINICAL DIABETES IN WOMEN
Colditz, G. A., Willett, W. C., Stampfer, M. J., Manson, J. E., Hennekens, C. H., Arky, R. A., & Speizer, F. E. (1990) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a115686 · Cited by 733
Defining Obesity Cut Points in a Multiethnic Population
Razak, F. A., Anand, S. S., Shannon, H. S., Vuksan, V. V. V., Davis, B. C., Jacobs, R., Teo, K. K., McQueen, M., & Yusuf, S. (2007) · Circulation · doi:10.1161/circulationaha.106.635011 · Cited by 558
UK Biobank: Current status and what it means for epidemiology
Allen, N., Sudlow, C., Downey, P., Peakman, T., Danesh, J., Elliott, P., Gallacher, J., Green, J., Matthews, P., Pell, J., et al. (2012) · Health Policy and Technology · doi:10.1016/j.hlpt.2012.07.003 · Cited by 521
Self-citation
EPIDEMIOLOGIC STUDIES OF CORONARY HEART DISEASE AND STROKE IN JAPANESE MEN LIVING IN JAPAN, HAWAII AND CALIFORNIA: PREVALENCE OF CORONARY AND HYPERTENSIVE HEART DISEASE AND ASSOCIATED RISK FACTORS1
Marmot, M. G., Syme, S. L., Kagan, A., Kato, H., Cohen, J. B., & Belsky, J. L. (1975) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a112189 · Cited by 406

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Authors: Ntuk, U. E., Gill, J. M. R., Mackay, D. F., Sattar, N., & Pell, J. P.
Affiliations: University of Glasgow (GB)
Corresponding author: Pell, Jill P.
ORCID: Gill, Jason M.R.
Mackay, Daniel F.
Sattar, Naveed
Pell, Jill P.
Venue: Diabetes Care
Publisher: American Diabetes Association
Published: 2014-08-07
Volume: 37
Issue: 9
Pages: 2500-2507
ISSN: 0149-5992 (ISSN-L)
1935-5548
DOI: 10.2337/dc13-2966
OpenAlex: W2157288306
Cited by: 220
References: 31
Citations by year: 2026: 12 · 2025: 26 · 2024: 14 · 2023: 14 · 2022: 18 · 2021: 21 · 2020: 17 · 2019: 12 · 2018: 21 · 2017: 23 · 2016: 17 · 2015: 20 · 2014: 5
FWCI: 17.44
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Diabetes Care (publishedVersion)
PubMed (publishedVersion)
ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
Funders: Wellcome Trust (093707)
British Heart Foundation
Topics: Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
Keywords: diabetes risk, ethnic differences, South Asian ethnicity, Black ethnicity, Chinese ethnicity, body mass index, waist circumference, waist-to-hip ratio, body fat percentage, diabetes prevalence, UK Biobank
MeSH terms: Adult, Aged, Cross-Sectional Studies, Diabetes Mellitus, Ethnicity, Female, United Kingdom, Humans, Male, Middle Aged, Obesity, Risk Factors, Body Mass Index, Prevalence, Biological Specimen Banks, Waist-Hip Ratio, Adiposity, Waist Circumference

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Ethnic-Specific Obesity Cutoffs for Diabetes Risk: Cross-sectional Study of 490,288 UK Biobank Participants

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