4.3 Article

Abdominal obesity and the prevalence of diabetes and intermediate hyperglycaemia in Chinese adults

期刊

PUBLIC HEALTH NUTRITION
卷 12, 期 8, 页码 1078-1084

出版社

CAMBRIDGE UNIV PRESS
DOI: 10.1017/S1368980008003856

关键词

Obesity; China; Body mass index; Waist circumference; Waist:height ratio; Type 2 diabetes; Abdominal adiposity; Intermediate hyperglycaemia; Glucose tolerance abnormalities

资金

  1. Ministry of Health and Ministry of Science and Technology, China [2001DEA30035, 2003DIA6N008]
  2. UNICEF
  3. WHO
  4. Unilever China
  5. Danone Nutrition Institute China

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Objective: To assess the association of indicators of general and abdominal obesity with the prevalence of type 2 diabetes (T2DM) and intermediate hyperglycaemia (IHG) in the Chinese population. Methods: We used data of 50905 adults aged 18-79 years in the 2002 China National Nutrition and Health Survey. Recommended Chinese cut-off values were used for BMI (24 kg/m(2)) and waist circumference (WC; 85 cm in men, 80 cm in women). Optimal cut-offs for waist:height ratio (WHtR) were determined from analyses of receiver-operating characteristic (ROC) curves. Results: The prevalence of T2DM and IHG was 2.6% and 1.9% respectively. ROC curve analyses indicated 0.5 as the optimal cut-off value for WHtR in both sexes. High BMI, WC and WHtR were all associated with the prevalence of glucose tolerance abnormalities, with the highest prevalence ratio (PR) for high WHtR (men: PR = 2.85, 95% CI 2.54, 3.21; women: PR = 3.10, 95% CI 2.74, 3.51). When combining BMI and WHtR, in men either a high BMI or a high WHtR alone was associated with increased risk. Among women, a high BMI without a concomitant high WHtR was not associated with increased glucose tolerance abnormalities risk, whereas a high WHtR was associated with risk irrespective of BMI. Conclusions: Among the Chinese adult population measures of central obesity are better predictors of glucose tolerance abnormalities prevalence than BMI. A WHtR cutoff point of 0.5 for both men and women can be considered as optimum for predicting (pre-) diabetes and may be a useful tool for screening and health education.

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