南京市成年人体重指数、腰围、腰臀比、腰高比与高血糖关系的随访研究

目的 探讨南京市成年人BMI、腰围(WC)、腰臀比(WHR)和腰高比(WHtR)与高血糖发病危险的关系.方法 2004年7月对南京市3个城区和1个郊县的35岁以上居民开展横断面调查,对无高血糖的人群于2007年7月进行随访.采用多因素logistic回归和受试者工作特征曲线(ROC)评估基线4个肥胖指标对高血糖发生的预测作用.结果 基线调查时无高血糖者共3727名,3年后共随访3031名,随访率为81.3%.高血糖3年累计发病率为6.7%;男女性发病率差异无统计学意义(6.3%vs.7.0%).经多元线性回归分析,BMI、WC、WHR、WHtR平均增加一个单位,随访时空腹血糖值分别增加0.015 mmol/L、0.023 mmol/L、1.923 mmol/L、2.382 mmol/L.随着基线肥胖程度的增加,高血糖的发病危险增加.WHtR≥0.5者发生高血糖的风险,男性(OR=1.998,95%C1:1.231～3.212)和女性(OR=1.832,95%CI:1.157～2.902)均高于其他肥胖指标.4个肥胖指标中,ROC曲线下面积WHtR最大.结论 BMI、WC、WHR和WHtR值的上升均能增加高血糖发病的风险;而WHtR会成为预测高血糖的重要指标.

The relationship between body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio and hyperglycemia: a three-year follow-up study in Nanjing

Objective To explore whether the increase of body mass index (BMI) , waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) can predict a higher risk of developing hyperglycemia. Methods A population-based cross-sectional study was conducted on local residents above 35 years of age in three urban districts and one rural county in July 2004. The subjects who were non-hyperglycemia in the baseline survey were selected to follow the survey in July 2007. Multivariable logistic regression analysis and area under curve (AUC) of receivcr-operating characteristics (ROC) were used to evaluate the predictive value of BMI, WC, WHR and WHtR. Results Of 3727 subjects without hyperglycemia who had completed in the baseline survey, 3031 of them participated in the follow-up survey, with a follow-up rate of 81.3%. The Three-year cumulative incidence of hyperglycemia was 6.7%,with male 6.3% and female 7.0%. By multiple linear regression, on average, an increase in BMI, WC, WHR, WHtR of 1 unit was associated with a 0.015 mmol/L, 0.023 mmol/L, 1.923 mmol/L, 2.382 mmol/L increase in fasting plasma glucose, respectively. The risk of developing hyperglycemia increased along with the increase of all the four indexes. When compared with other three indexes, the group which WHtR was more than 0.5, had the highest risk (male OR= 1.998, 95%CI:1.231-3.212, female OR= 1.832,95%CI: 1.157-2.902) of developing hyperglycemia. Data from ROC curve analysis showed that the AUC of WHtR was the highest in both males and females. Conclusion The increase of BMI, WC, WHR and WHtR could predict the higher risk causing the development of hyperglycemia. WHtR might serve as a simple but most effective index of hyperglycemia.