Association between metabolic score for insulin resistance and clinical outcomes: insights from the Tehran lipid and glucose study.

IF 3.9 2区 医学 Q2 NUTRITION & DIETETICS Nutrition & Metabolism Pub Date : 2024-06-12 DOI:10.1186/s12986-024-00808-w
Seyyed Saeed Tamehri Zadeh, Neda Cheraghloo, Soroush Masrouri, Farzad Esmaeili, Fereidoun Azizi, Farzad Hadaegh
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Abstract

Background: We aimed to assess the relationship between Metabolic Score for Insulin Resistance (METS-IR) and the incidence of coronary heart disease (CHD), stroke, mortality, diabetes, hypertension, and chronic kidney disease (CKD) in a population from the Middle East and North Africa (MENA) region.

Method: Individuals aged ≥ 20 years were enrolled. Cox proportional hazards regression models were applied to assess the association between METS-IR and incident CHD, stroke, all-cause mortality, diabetes, hypertension, and CKD.

Results: Over a median follow-up period of 9-18 years, 1080 (10.6%), 267 (2.6%), 1022 (9.6%), 1382 (16.4%), 2994 (58.5%), and 2002 (23.0%) CHD, stroke, all-cause mortality, diabetes, hypertension, and CKD events occurred, respectively. Compared to the lowest quartile (reference), the hazard ratios (HR) associated with the highest quartile of METS-IR were 1.527 (95% confidence interval [CI]: 1.208-1.930, P for trend 0.001), 1.393 (0.865-2.243, > 0.05), 0.841 (0.682-1.038, > 0.05), 3.277 (2.645-4.060, < 0.001), 1.969 (1.752-2.214, < 0.001), and 1.020 (0.874-1.191, > 0.05) for CHD, stroke, all-cause mortality, diabetes, hypertension, and CKD, respectively. METS-IR, as a continuous variable, was significantly associated with the risk of incident CHD [HR, 95% CI: 1.106, 1.034-1.184], diabetes [1.524, 1.438-1.616], and hypertension [1.321, 1.265-1.380]. These associations were also independent of metabolic syndrome (METS) and remained unchanged in a subgroup of individuals without METS and/or diabetes.

Conclusions: Increasing levels of METS-IR were significantly associated with a greater risk of incident CHD, diabetes, and hypertension; therefore, this index can be a useful tool for capturing the risk of these clinical outcomes.

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胰岛素抵抗代谢评分与临床结果之间的关系:德黑兰血脂和血糖研究的启示。
背景:我们旨在评估中东和北非地区人群中胰岛素抵抗代谢评分(METS-IR)与冠心病(CHD)、中风、死亡率、糖尿病、高血压和慢性肾病(CKD)发病率之间的关系:方法:对年龄≥ 20 岁的个体进行了登记。采用 Cox 比例危险回归模型评估 METS-IR 与冠心病、中风、全因死亡率、糖尿病、高血压和慢性肾脏病之间的关系:在 9-18 年的中位随访期内,分别发生了 1080 例(10.6%)、267 例(2.6%)、1022 例(9.6%)、1382 例(16.4%)、2994 例(58.5%)和 2002 例(23.0%)冠心病、中风、全因死亡、糖尿病、高血压和慢性肾脏病事件。与最低四分位数(参考值)相比,与 METS-IR 最高四分位数相关的危险比(HR)分别为 1.527(95% 置信区间 [CI]:1.208-1.930,P 为趋势 0.001)、1.393(0.865-2.243,> 0.05)、0.841(0.682-1.038,> 0.05)、3.277(2.645-4.060,0.05),分别与冠心病、中风、全因死亡率、糖尿病、高血压和慢性肾脏病有关。作为连续变量,METS-IR 与发生冠心病[HR,95% CI:1.106,1.034-1.184]、糖尿病[1.524,1.438-1.616]和高血压[1.321,1.265-1.380]的风险显著相关。这些关联也与代谢综合征(METS)无关,并且在没有代谢综合征和/或糖尿病的亚组中保持不变:结论:METS-IR水平的升高与冠心病、糖尿病和高血压的发病风险显著相关;因此,该指数可作为捕捉这些临床结果风险的有用工具。
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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
审稿时长
4-8 weeks
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.
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