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Diabetes Care 24:1377-1383, 2001
© 2001 by the American Diabetes Association, Inc.


Epidemiology/Health Services/Psychosocial Research
Original Article

High Prevalence of Type 2 Diabetes in All Ethnic Groups, Including Europeans, in a British Inner City

Relative poverty, history, inactivity, or 21st century Europe?

Lisa Riste, PHD, Farida Khan, MSC and Kennedy Cruickshank, MB, MD, FRCP

Clinical Epidemiology Group, University of Manchester Medical School, Manchester, M13 9PT, U.K. E-mail: clinep{at}man.ac.uk.

OBJECTIVE—To compare the prevalence of type 2 diabetes in white Europeans and individuals of African-Caribbean and Pakistani descent.

RESEARCH DESIGN AND METHODS—Random sampling of population-based registers in inner-city Manchester, Britain’s third most impoverished area. A total of 1,318 people (25–79 years of age) were screened (minimum response 67%); 533 individuals without known diabetes underwent 2-h glucose tolerance testing, classified by 1999 World Health Organization criteria.

RESULTS—More than 60% of individuals reported household annual income <£10,000 ($15,000) per year. Energetic physical activity was rare and obesity was common. Age-standardized (35–79 years) prevalence (mean 95% CI) of known and newly detected diabetes was 20% (17–24%) in Europeans, 22% (18–26%) in African-Caribbeans, and 33% (25–41%) in Pakistanis. Minimum prevalence (assuming all individuals not tested were normoglycemic) was 11% (8–14%), 19% (15–23%), and 32% (24–40%), respectively. Marked changes in prevalence represent only small shifts in glucose distributions. Regression models showed that greater waist girth, lower height, and older age were independently related to plasma glucose levels, as was physical activity. Substituting BMI and waist-to-hip ratio revealed their powerful contribution.

CONCLUSIONS—A surprisingly high prevalence of diabetes, despite expected increases with new lower criteria, was found in Europeans, as previously established in Caribbeans and Pakistanis. Lower height eliminated ethnic differences in regression models. History and relative poverty, which cosegregate with obesity and physical inactivity, are likely contributors. Whatever the causes, the implications for health services are alarming, although substantial preventive opportunities through small reversals of glucose distributions are the challenge.


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