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Prevalence of diabetes and predictions of its risks using anthropometric measures in southwest rural areas of China

BACKGROUND: To examine the prevalence of diabetes and prediabetes in Songming county, Yunnan province, South-west China and examine influences of anthropometric indicators on diabetic risk. METHODS: This study was a population based cross-sectional study of 1031 subjects in Songming County aged 30 y...

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Detalles Bibliográficos
Autores principales: Zhao, Xiaolong, Zhu, Xiaoming, Zhang, Hengsheng, Zhao, Weiwei, Li, Jinhui, Shu, Yonghui, Li, Songwu, Yang, Minghui, Cai, Linghu, Zhou, Jiping, Li, Yiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3549931/
https://www.ncbi.nlm.nih.gov/pubmed/22998969
http://dx.doi.org/10.1186/1471-2458-12-821
Descripción
Sumario:BACKGROUND: To examine the prevalence of diabetes and prediabetes in Songming county, Yunnan province, South-west China and examine influences of anthropometric indicators on diabetic risk. METHODS: This study was a population based cross-sectional study of 1031 subjects in Songming County aged 30 years and older. Age-standardization was performed by using the 2010 Songming population as the standard population. After an overnight fasting, participants underwent an oral glucose tolerance test (OGTT), and venous blood glucose levels were measured to identify diabetes and prediabetes. Physicians completed questionnaires and blood pressure measurements; trained nurses measured anthropometric variables. Age-adjusted logistic regression models were used to assess the association between anthropometric variables and diabetes. RESULTS: Total prevalences of diabetes and prediabetes were 10.0% and 11.6%, respectively. In women, prevalence of diabetes and prediabetes significantly increased with body mass index (BMI),waist hip ratio (WHR), and waist-to-height ratio (WHtR). But in men, prevalence of diabetes and prediabetes only significantly increased with WHR and WHtR. Compared to 1(st) WHR tertile in women, there was a nearly tenfold increase in the risk of diabetes with 3(rd) WHR tertile (OR 10.50, 95% CI 3.95-27.86). Men with 3(rd) BMI tertile had 4.8-fold risk of getting diabetes compared to men with 1(st) WHtR tertile (OR 4.79, 95% CI 1.88-12.26). Only WHtR had significantly higher receiver operating characteristic (ROC) area than BMI in total men (0.668 vs. 0.561, p < 0.05). And in total women, only WHR had significantly higher ROC area than BMI (0.723 vs. 0.628, p < 0.05). In the partial correlation analysis controlling for waist circumference, only WHR had significant correlation with fasting plasma glucose (r = 0.132, p = 0.002) and 2-h plasma glucose (r = 0.162, p = 0.000) in women, and WHtR had a much stronger association with both fasting plasma glucose (r = 0.305, P = 0.000) and 2 h plasma glucose (r = 0.303, P = 0.000) than WHR in men. CONCLUSION: High prevalence of diabetes and prediabetes were found in this underdeveloped region. About half of total subjects with diabetes were undiagnosed. The association of obesity indices and diabetic risk factors varied with gender. The strongest predictors of diabetes were WHR for the female subgroup and WHtR for the male subgroup.