Jiang-Feng Ke1, Jun-Wei Wang2, Jun-Xi Lu3, Zhi-Hui Zhang4, Yun Liu5, Lian-Xi Li6. 1. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, 600 Yishan Road, 200233 Shanghai, China. Electronic address: kjf168168@sjtu.edu.cn. 2. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, 600 Yishan Road, 200233 Shanghai, China. Electronic address: wangjunwei0611@163.com. 3. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, 600 Yishan Road, 200233 Shanghai, China. Electronic address: cissyludai@163.com. 4. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, 600 Yishan Road, 200233 Shanghai, China. Electronic address: zhihui@sjtu.edu.cn. 5. Department of Information, the First Affiliated Hospital of Nanjing Medical University, Department of Medical Information, School of Biomedical Engineering and Informatics, Nanjing Medical University, Jiangsu, China. Electronic address: liuyun@njmu.edu.cn. 6. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, 600 Yishan Road, 200233 Shanghai, China. Electronic address: lilx@sjtu.edu.cn.
Abstract
AIMS: To compare the associations between four anthropometric indices including waist-to-height ratio (WHtR), waist circumference (WC), waist-hip-ratio (WHR) and body mass index (BMI) and cardio-cerebrovascular events (CCBVEs) in Chinese T2DM patients. METHODS: The associations of four anthropometric measures with CCBVEs and metabolic syndrome (MetS) were compared by multiple regression model in 3108 T2DM patients. CCBVEs was defined as a history of myocardial infarction, angina, angioplasty, coronary artery bypass surgery, transient ischemic attack, ischemic or hemorrhagic stroke. RESULTS: After controlling for age, sex and diabetes duration, the prevalence of CCBVEs and MetS significantly increased across the WHtR, WC, WHR and BMI quartiles in T2DM patients, respectively. However, when controlling for these four anthropometric measurements together, although four anthropometric measures were closely associated with MetS prevalence, only WHtR quartile was significantly associated with CCBVEs prevalence (6.5%, 13.8%, 16.9% and 21.3%, p < 0.001 for trend). After adjusting for multiple confounders including four anthropometric parameters, a regression analysis revealed that only WHtR was independently and positively associated with the presence of CCBVEs (p = 0.029). CONCLUSIONS: Compared with WC, WHR and BMI, WHtR have a stronger association with CCBVEs in T2DM subjects. WHtR maybe a better indicator than other anthropometric measurements for evaluating cardiovascular risks in T2DM.
AIMS: To compare the associations between four anthropometric indices including waist-to-height ratio (WHtR), waist circumference (WC), waist-hip-ratio (WHR) and body mass index (BMI) and cardio-cerebrovascular events (CCBVEs) in Chinese T2DM patients. METHODS: The associations of four anthropometric measures with CCBVEs and metabolic syndrome (MetS) were compared by multiple regression model in 3108 T2DM patients. CCBVEs was defined as a history of myocardial infarction, angina, angioplasty, coronary artery bypass surgery, transient ischemic attack, ischemic or hemorrhagic stroke. RESULTS: After controlling for age, sex and diabetes duration, the prevalence of CCBVEs and MetS significantly increased across the WHtR, WC, WHR and BMI quartiles in T2DM patients, respectively. However, when controlling for these four anthropometric measurements together, although four anthropometric measures were closely associated with MetS prevalence, only WHtR quartile was significantly associated with CCBVEs prevalence (6.5%, 13.8%, 16.9% and 21.3%, p < 0.001 for trend). After adjusting for multiple confounders including four anthropometric parameters, a regression analysis revealed that only WHtR was independently and positively associated with the presence of CCBVEs (p = 0.029). CONCLUSIONS: Compared with WC, WHR and BMI, WHtR have a stronger association with CCBVEs in T2DM subjects. WHtR maybe a better indicator than other anthropometric measurements for evaluating cardiovascular risks in T2DM.