The Population Health Research Institute, McMaster University, Hamilton, ON, Canada.
Diabetologia. 2010 Jul;53(7):1322-30. doi: 10.1007/s00125-010-1710-3. Epub 2010 Apr 7.
AIMS/HYPOTHESES: We determined: (1) which of BMI, waist circumference, hip circumference and WHR has the strongest association and explanatory power for newly diagnosed type 2 diabetes and glucose status; and (2) the impact of considering two measures simultaneously. We also explored variation in anthropometric associations by sex and ethnicity.
We performed cross-sectional analysis of 22,293 men and women who were from five ethnic groups and 21 countries, and at risk of developing type 2 diabetes. Standardised anthropometric associations with type 2 diabetes and AUC of glucose status from OGTT (AUC(OGTT)) were determined using multiple regression. Explanatory power was assessed using the c-statistic and adjusted r (2).
An increase in BMI, waist circumference or WHR had similar positive associations with type 2 diabetes, AUC(OGTT) and explanatory power after adjustment for age, sex, smoking and ethnicity (p < 0.01). However, using BMI and WHR together resulted in greater explanatory power than with other models (p < 0.01). Associations were strongest when waist circumference and hip circumference were used together, a combination that had greater explanatory power than other models except for BMI and WHR together (p < 0.01). Results were directionally similar according to sex and ethnicity; however, significant variations in associations were observed among these subgroups.
CONCLUSIONS/INTERPRETATION: The combination of BMI and WHR, or of waist circumference and hip circumference has the best explanatory power for type 2 diabetes and glucose status compared with a single anthropometric measure. Measurement of waist circumference and hip circumference is required to optimally identify people at risk of type 2 diabetes and people with elevated glucose levels.
目的/假设:我们确定:(1)BMI、腰围、臀围和腰臀比(WHR)中哪一个与新诊断的 2 型糖尿病和血糖状态的关联最强,解释能力最强;(2)同时考虑两个指标的影响。我们还探讨了性别和种族对人体测量指标相关性的影响。
我们对来自五个种族和 21 个国家、有患 2 型糖尿病风险的 22293 名男性和女性进行了横断面分析。使用多元回归确定 2 型糖尿病和 OGTT 葡萄糖状态 AUC(AUC(OGTT))的标准人体测量关联,并使用 c 统计量和调整后的 r(2)评估解释能力。
BMI、腰围或 WHR 的增加与 2 型糖尿病、AUC(OGTT)和调整年龄、性别、吸烟和种族后的解释能力呈正相关(p<0.01)。然而,与其他模型相比,使用 BMI 和 WHR 一起可以获得更大的解释能力(p<0.01)。当使用腰围和臀围一起时,关联最强,这种组合比其他模型(除了 BMI 和 WHR 一起)具有更大的解释能力(p<0.01)。结果在性别和种族方面方向相似;然而,在这些亚组中观察到了关联的显著差异。
结论/解释:与单一人体测量指标相比,BMI 和 WHR 的组合,或腰围和臀围的组合对 2 型糖尿病和血糖状态具有最佳的解释能力。需要测量腰围和臀围,以最佳地识别有患 2 型糖尿病风险的人和血糖水平升高的人。