2010Chinese Journal of Public HealthRequires access

Predictive value of obesity indicators to diabetes risk

Yong Jia

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Abstract

Objective To evaluate the predictive values of body mass index(BMI),waist circumference(WC),waist/hip ratio(WHR),and waist-height ratio(WHtR) to diabetes risk.Methods Data came form the 2008 Chengdu Diabetes Survey,a population based cross-sectional study,and 5 205 residents aged 40-70 years were enrolled.Results WHtR showed positive correlation with WC(r=0.938 4 in male,r=0.952 6 in female,P0.05).WHR in male and WC in female showed low correlation with height(r=0.027 8 in male,r=0.029 4 in female,P0.05).WHR in male and WHtR in female were found to have the largest areas under the ROC curve relative to diabetes(c=0.641 5 in male,c=0.669 2 in female).Logistic regression analysis showed that WHR in male and WC in female were the best predictors related to obesity among the 4 deliberated indexes to diabetes risk(odds ratio=3.107 in male,OR=2.684 in female).After controling the interaction of 4 indexes,BMI combined with WC,WHR or WHtR could not improve the predictive value in the model.Conclusion The results suggest that WHR in male and WC in female are the best predictors related to obesity among the 4 evaluation indicators.The best cut-off points of WHR in male and WC in female are 0.90 and 83 centimeter,respectively,and the application of the predictors in defferent area or population needs to be researched.

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Objective To evaluate the predictive values of body mass index(BMI),waist circumference(WC),waist/hip ratio(WHR),and waist-height ratio(WHtR) to diabetes risk.Methods Data came form the 2008 Chengdu Diabetes Survey,a population based cross-sectional study,and 5 205 residents aged 40-70 years were enrolled.Results WHtR showed positive correlation with WC(r=0.938 4 in male,r=0.952 6 in female,P0.05).WHR in male and WC in female showed low correlation with height(r=0.027 8 in male,r=0.029 4 in female,P0.05).WHR in male and WHtR in female were found to have the largest areas under the ROC curve relative to diabetes(c=0.641 5 in male,c=0.669 2 in female).Logistic regression analysis showed that WHR in male and WC in female were the best predictors related to obesity among the 4 deliberated indexes to diabetes risk(odds ratio=3.107 in male,OR=2.684 in female).After controling the interaction of 4 indexes,BMI combined with WC,WHR or WHtR could not improve the predictive value in the model.Conclusion The results suggest that WHR in male and WC in female are the best predictors related to obesity among the 4 evaluation indicators.The best cut-off points of WHR in male and WC in female are 0.90 and 83 centimeter,respectively,and the application of the predictors in defferent area or population needs to be researched.

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Available abstract

Objective To evaluate the predictive values of body mass index(BMI),waist circumference(WC),waist/hip ratio(WHR),and waist-height ratio(WHtR) to diabetes risk.Methods Data came form the 2008 Chengdu Diabetes Survey,a population based cross-sectional study,and 5 205 residents aged 40-70 years were enrolled.Results WHtR showed positive correlation with WC(r=0.938 4 in male,r=0.952 6 in female,P0.05).WHR in male and WC in female showed low correlation with height(r=0.027 8 in male,r=0.029 4 in female,P0.05).WHR in male and WHtR in female were found to have the largest areas under the ROC curve relative to diabetes(c=0.641 5 in male,c=0.669 2 in female).Logistic regression analysis showed that WHR in male and WC in female were the best predictors related to obesity among the 4 deliberated indexes to diabetes risk(odds ratio=3.107 in male,OR=2.684 in female).After controling the interaction of 4 indexes,BMI combined with WC,WHR or WHtR could not improve the predictive value in the model.Conclusion The results suggest that WHR in male and WC in female are the best predictors related to obesity among the 4 evaluation indicators.The best cut-off points of WHR in male and WC in female are 0.90 and 83 centimeter,respectively,and the application of the predictors in defferent area or population needs to be researched.

Key concepts: Waist-to-height ratio, Demography, Waist, Body mass index, Medicine, Logistic regression, Odds ratio, Obesity

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