Erschienen in:
01.07.2010 | Article
Anthropometric measures and glucose levels in a large multi-ethnic cohort of individuals at risk of developing type 2 diabetes
verfasst von:
L. de Koning, H. C. Gerstein, J. Bosch, R. Diaz, V. Mohan, G. Dagenais, S. Yusuf, S. S. Anand, for the EpiDREAM Investigators
Erschienen in:
Diabetologia
|
Ausgabe 7/2010
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Abstract
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.
Methods
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 (AUCOGTT) were determined using multiple regression. Explanatory power was assessed using the c-statistic and adjusted r
2.
Results
An increase in BMI, waist circumference or WHR had similar positive associations with type 2 diabetes, AUCOGTT 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.