Wen-Yan Xiong, Yu-Hong Liu, Yi-Bing Fan, Xiao-Lin Zhu, Kun Zhou, Hui Li
{"title":"累积代谢参数对 2 型糖尿病风险的共同影响:一项基于人群的队列研究。","authors":"Wen-Yan Xiong, Yu-Hong Liu, Yi-Bing Fan, Xiao-Lin Zhu, Kun Zhou, Hui Li","doi":"10.1186/s12986-024-00848-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and aims: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":19196,"journal":{"name":"Nutrition & Metabolism","volume":"21 1","pages":"78"},"PeriodicalIF":3.9000,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11448077/pdf/","citationCount":"0","resultStr":"{\"title\":\"The joint effect of cumulative metabolic parameters on the risk of type 2 diabetes: a population-based cohort study.\",\"authors\":\"Wen-Yan Xiong, Yu-Hong Liu, Yi-Bing Fan, Xiao-Lin Zhu, Kun Zhou, Hui Li\",\"doi\":\"10.1186/s12986-024-00848-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and aims: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>Participants with more numbers of high-cumulative metabolic parameters were associated with a higher risk of incident T2D and prediabetes progression. 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The joint effect of cumulative metabolic parameters on the risk of type 2 diabetes: a population-based cohort study.
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.
期刊介绍:
Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects.
The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases.
Key areas we wish to encourage submissions from include:
-how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes;
-the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components;
-how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved;
-how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.