The joint effect of cumulative metabolic parameters on the risk of type 2 diabetes: a population-based cohort study

累积代谢参数对2型糖尿病风险的联合影响:一项基于人群的队列研究

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Abstract

BACKGROUND AND AIMS: This study aimed to examine the cumulative effects of body mass index (BMI), body roundness index (BRI), pulse pressure (PP), triglycerides (TG), high-density lipoprotein cholesterol (HDL) and fasting plasma glucose (FPG) on Type 2 diabetes (T2D) morbidity. METHODS: A total of 78,456 participants aged older than 45 years were extracted from basic public health services in China. During the 2-year follow-up, 6,942 individuals had developed T2D. The binary logistic regression models and multinomial logistic regression models were conducted to investigate the effects of cumulative metabolic parameters on incident T2D, prediabetes regression and progression. RESULTS: We found statistically deleterious impacts of exposure to high cumulative BMI, BRI, PP, TG and low cumulative HDL on T2D morbidity and prediabetes progression. Compared to the group with low cumulative of all five parameters, the adjusted ORs for new-onset T2D for participants presenting with 1-2, 3, and 4-5 elevated metabolic parameters were 1.41(1.31,1.52), 1.93(1.74,2.13) and 2.21(1.94,2.51), respectively. There was additive interaction between FPG level and cumulative metabolic parameters with T2D. Compared with participants with the lowest quartile of FPG and low cumulative of all 5 parameters, those with the highest quartile of FPG and high cumulative of 4-5 parameters had a 14.63 [95% CI (12.27, 17.42)] higher risk of incident T2D. CONCLUSIONS: Participants with more numbers of high-cumulative metabolic parameters were associated with a higher risk of incident T2D and prediabetes progression. A high level of normal FPG could enhance these risks.

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