Renyue Ji, Haisheng Wu, Hongli Lin, Yang Li, Yumeng Shi
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Logistic regression, weighted quantile sum (WQS), and Bayesian kernel machine learning (BKMR) models were employed to investigate the association between exposure to mixtures of five heavy metals and the odds of having CHF in individuals with diabetes and prediabetes.</p><p><strong>Result: </strong>Multivariate logistic regression analysis Shows that only blood Cd exhibited a significant linear positive correlation with CHF odds (OR: 1.26, 95%CI 1.07-1.47, p = 0.005), there was a significant 14% decrease in the odds rate of CHF for each additional standard deviation of log10 Se (OR: 0.86,95%CI 0.76-0.96, P = 0.009). The WQS index for the metal mixture only marginally increased the odds of CHF by 1% (OR = 1.01, 95% CI 1.00-1.02, P = 0.032). BKMR analysis demonstrated a positive association between Cd levels and the odds of CHF, an inverse relationship with Se levels in patients with diabetes and prediabetes. However, no significant association was observed between the metal mixture and CHF.</p><p><strong>Conclusion: </strong>This cross-sectional study demonstrates that increased Cd levels are associated with a higher odds of CHF in patients with diabetes and pre-diabetes, whereas elevated blood Se levels significantly mitigate this odds.</p>","PeriodicalId":11106,"journal":{"name":"Diabetology & Metabolic Syndrome","volume":"17 1","pages":"12"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11715992/pdf/","citationCount":"0","resultStr":"{\"title\":\"Cadmium and selenium blood levels in association with congestive heart failure in diabetic and prediabetic patients: a cross-sectional study from the national health and nutrition examination survey.\",\"authors\":\"Renyue Ji, Haisheng Wu, Hongli Lin, Yang Li, Yumeng Shi\",\"doi\":\"10.1186/s13098-024-01556-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Epidemiological research on the association between heavy metals and congestive heart failure (CHF) in individuals with abnormal glucose metabolism is scarce. 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Logistic regression, weighted quantile sum (WQS), and Bayesian kernel machine learning (BKMR) models were employed to investigate the association between exposure to mixtures of five heavy metals and the odds of having CHF in individuals with diabetes and prediabetes.</p><p><strong>Result: </strong>Multivariate logistic regression analysis Shows that only blood Cd exhibited a significant linear positive correlation with CHF odds (OR: 1.26, 95%CI 1.07-1.47, p = 0.005), there was a significant 14% decrease in the odds rate of CHF for each additional standard deviation of log10 Se (OR: 0.86,95%CI 0.76-0.96, P = 0.009). The WQS index for the metal mixture only marginally increased the odds of CHF by 1% (OR = 1.01, 95% CI 1.00-1.02, P = 0.032). BKMR analysis demonstrated a positive association between Cd levels and the odds of CHF, an inverse relationship with Se levels in patients with diabetes and prediabetes. 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引用次数: 0
摘要
背景:在糖代谢异常的人群中,关于重金属与充血性心力衰竭(CHF)之间关系的流行病学研究很少。该研究通过检查在葡萄糖代谢失调的人群中暴露于重金属与CHF几率之间的联系来解决这一研究空白。方法:对2011 - 2018年全国健康与营养检查调查中7326例糖尿病及前驱糖尿病患者进行横断面研究。暴露变量是五种环境重金属——镉(Cd)、铅(Pb)、汞(Hg)、硒(Se)和锰(Mn)——终点是CHF,通过面对面访谈确定。采用Logistic回归、加权分位数和(WQS)和贝叶斯核机器学习(BKMR)模型来研究糖尿病和前驱糖尿病患者暴露于五种重金属混合物与患CHF几率之间的关系。结果:多因素logistic回归分析显示,只有血Cd与CHF的比值呈显著的线性正相关(OR: 1.26, 95%CI 1.07 ~ 1.47, p = 0.005),每增加一个log10 Se的标准差,CHF的比值显著降低14% (OR: 0.86,95%CI 0.76 ~ 0.96, p = 0.009)。金属混合物的WQS指数仅使CHF的几率略微增加1% (OR = 1.01, 95% CI 1.00-1.02, P = 0.032)。BKMR分析显示Cd水平与CHF发病率呈正相关,而糖尿病和前驱糖尿病患者的Se水平与CHF发病率呈负相关。然而,没有观察到金属混合物与CHF之间的显著关联。结论:本横断面研究表明,在糖尿病和糖尿病前期患者中,Cd水平升高与CHF发生率升高相关,而血硒水平升高可显著降低这一发生率。
Cadmium and selenium blood levels in association with congestive heart failure in diabetic and prediabetic patients: a cross-sectional study from the national health and nutrition examination survey.
Background: Epidemiological research on the association between heavy metals and congestive heart failure (CHF) in individuals with abnormal glucose metabolism is scarce. The study addresses this research gap by examining the link between exposure to heavy metals and the odds of CHF in a population with dysregulated glucose metabolism.
Method: This cross-sectional study includes 7326 patients with diabetes and prediabetes from the National Health and Nutrition Examination Survey from 2011 to 2018. The exposure variables are five environmental heavy metals-cadmium (Cd), lead (Pb), mercury (Hg), selenium (Se), and manganese (Mn)-and the endpoint is CHF, determined via face-to-face interviews. Logistic regression, weighted quantile sum (WQS), and Bayesian kernel machine learning (BKMR) models were employed to investigate the association between exposure to mixtures of five heavy metals and the odds of having CHF in individuals with diabetes and prediabetes.
Result: Multivariate logistic regression analysis Shows that only blood Cd exhibited a significant linear positive correlation with CHF odds (OR: 1.26, 95%CI 1.07-1.47, p = 0.005), there was a significant 14% decrease in the odds rate of CHF for each additional standard deviation of log10 Se (OR: 0.86,95%CI 0.76-0.96, P = 0.009). The WQS index for the metal mixture only marginally increased the odds of CHF by 1% (OR = 1.01, 95% CI 1.00-1.02, P = 0.032). BKMR analysis demonstrated a positive association between Cd levels and the odds of CHF, an inverse relationship with Se levels in patients with diabetes and prediabetes. However, no significant association was observed between the metal mixture and CHF.
Conclusion: This cross-sectional study demonstrates that increased Cd levels are associated with a higher odds of CHF in patients with diabetes and pre-diabetes, whereas elevated blood Se levels significantly mitigate this odds.
期刊介绍:
Diabetology & Metabolic Syndrome publishes articles on all aspects of the pathophysiology of diabetes and metabolic syndrome.
By publishing original material exploring any area of laboratory, animal or clinical research into diabetes and metabolic syndrome, the journal offers a high-visibility forum for new insights and discussions into the issues of importance to the relevant community.