Zhu Liang1, Qiao Yan Qiu2, Jia Hui Wu2, Jing Wen Zhou2, Tian Xu2, Ming Zhi Zhang3, Yong Hong Zhang3, Shao Yan Zhang3. 1. Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou 215123, Jiangsu, China; KunShan Center for Disease Control And Prevention, KunShan 215300, Jiangsu, China. 2. Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou 215123, Jiangsu, China. 3. Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou 215123, Jiangsu, China; Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou 215123, Jiangsu, China.
Abstract
OBJECTIVE: No previous studies have evaluated the association between dyslipidemia, alcohol drinking, and diabetes in an Inner Mongolian population. We aimed to evaluate the co-effects of drinking and dyslipidemia on diabetes incidence in this population. METHODS: The present study was based on 1880 participants from a population-based prospective cohort study among Inner Mongolians living in China. Participants were classified into four subgroups according to their drinking status and dyslipidemia. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curves were used to evaluate the association between alcohol drinking, dyslipidemia, and diabetes. RESULTS: During the follow-up period, 203 participants were found to have developed diabetes. The multivariable-adjusted odds ratios (95% confidence interval) for the incidence of non-dyslipidemia/drinkers, dyslipidemia/non-drinkers, and dyslipidemia/drinkers in diabetic patients were 1.40 (0.82-2.37), 1.73 (1.17-2.55), and 2.31 (1.38-3.87), respectively, when compared with non-dyslipidemia/non-drinkers. The area under the ROC curve for a model containing dyslipidemia and drinking status along with conventional factors (AUC=0.746) was significantly (P=0.003) larger than the one containing only conventional factors (AUC=0.711). CONCLUSION: The present study showed that dyslipidemia was an independent risk factor for diabetes, and that drinkers with dyslipidemia had the highest risk of diabetes in the Mongolian population. These findings suggest that dyslipidemia and drinking status may be valuable in predicting diabetes incidence.
OBJECTIVE: No previous studies have evaluated the association between dyslipidemia, alcohol drinking, and diabetes in an Inner Mongolian population. We aimed to evaluate the co-effects of drinking and dyslipidemia on diabetes incidence in this population. METHODS: The present study was based on 1880 participants from a population-based prospective cohort study among Inner Mongolians living in China. Participants were classified into four subgroups according to their drinking status and dyslipidemia. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curves were used to evaluate the association between alcohol drinking, dyslipidemia, and diabetes. RESULTS: During the follow-up period, 203 participants were found to have developed diabetes. The multivariable-adjusted odds ratios (95% confidence interval) for the incidence of non-dyslipidemia/drinkers, dyslipidemia/non-drinkers, and dyslipidemia/drinkers in diabeticpatients were 1.40 (0.82-2.37), 1.73 (1.17-2.55), and 2.31 (1.38-3.87), respectively, when compared with non-dyslipidemia/non-drinkers. The area under the ROC curve for a model containing dyslipidemia and drinking status along with conventional factors (AUC=0.746) was significantly (P=0.003) larger than the one containing only conventional factors (AUC=0.711). CONCLUSION: The present study showed that dyslipidemia was an independent risk factor for diabetes, and that drinkers with dyslipidemia had the highest risk of diabetes in the Mongolian population. These findings suggest that dyslipidemia and drinking status may be valuable in predicting diabetes incidence.