Different Contributions of Dyslipidemia and Obesity to the Natural History of Type 2 Diabetes: 3-Year Cohort Study in China

糖尿病前期 医学 内科学 血脂异常 糖尿病 2型糖尿病 血糖性 体质指数 甘油三酯 队列 空腹血糖受损 队列研究 前瞻性队列研究 内分泌学 肥胖 糖耐量受损 胆固醇
作者
Lu Liu,Xiaoling Guan,Zhongshang Yuan,Meng Zhao,Qiu Li,Xu Zhang,Haiqing Zhang,Dongmei Zheng,Jin Xu,Ling Gao,Qingbo Guan,Jiajun Zhao,the REACTION Study Group
出处
期刊:Journal of diabetes research [Hindawi Publishing Corporation]
卷期号:2019: 1-10 被引量:12
标识
DOI:10.1155/2019/4328975
摘要

It is known that different stages of type 2 diabetes represent distinct pathophysiological changes, but how the spectrum of risk factors varies at different stages is not yet clarified. Hence, the aim of this study was to compare the effect of different metabolic variables on the natural history of type 2 diabetes.A total of 5,213 nondiabetic (normal glucose tolerance (NGT) and prediabetes) Chinese older than 40 years participated this prospective cohort study, and 4,577 completed the 3-year follow-up. Glycemic status was determined by standard oral glucose tolerance test both at enrollment and follow-up visit. Predictors for conversion in glycemic status were studied in a corresponding subcohort using the multiple logistic regression analysis.The incidence of prediabetes and diabetes of the cohort was 93.6 and 42.2 per 1,000 person-years, respectively. After a 3-year follow-up, 33.1% of prediabetes patients regressed to NGT. The predictive weight of body mass index (BMI), serum triglyceride, total cholesterol, and systolic blood pressure in different paths of conversions among diabetes, prediabetes, and NGT differed. Specifically, BMI was the strongest predictor for regression from prediabetes to NGT, while triglyceride was most prominent for onset of diabetes. One SD increase in serum triglyceride was associated with a 1.29- (95% CI 1.10-1.52; P = 0.002) or 1.12- (95% CI 1.01-1.27; P = 0.039) fold higher risk of diabetes for individuals with NGT or prediabetes, respectively.Risk factors for different stages of diabetes differed, suggesting personalized preventive strategies for individuals with different basal glycemic statuses.
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