Association between exposure to urinary metal and all-cause and cardiovascular mortality in US adults DOI Creative Commons
Ting Cheng, Dongdong Yu, Li Geng

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(12), P. e0316045 - e0316045

Published: Dec. 27, 2024

Background Further evidence is required regarding the influence of metal mixture exposure on mortality. Therefore, we employed diverse statistical models to evaluate associations between eight urinary metals and risks all-cause cardiovascular Methods We measured levels 8 in urine adults who participated National Health Nutrition Examination Survey (NHANES) from 1999 2018. Based follow-up data, determined whether they died reasons for their deaths. estimated association mortality using Cox regression, weighted quantile sum (WQS) Bayesian kernel machine regression (BKMR) models. Additionally, used a competing risk model estimate relationship Results Among 14,305 individuals included our final analysis, there were 2,066 deaths, with 1,429 being cardiovascular-related. analysis showed that cobalt (Co) (HR: 1.21; 95% CI: 1.13, 1.30) antimony (Sb) 1.26; 1.12, 1.40) positively associated (all P trend <0.001). In model, Co 1.29; 1.48), lead (Pb) 1.18; 1.03, 1.37), Sb 1.44; 1.18, 1.75) significantly an increased Sb, Pb, cadmium (Cd), molybdenum (Mo) had highest weight rankings WQS model. All complex non-linear mortality, high posterior inclusion probabilities (PIPs) BKMR Conclusions Combining all models, it possible may have more stable impact Meaningful effects individual still require careful attention.

Language: Английский

Association between exposure to urinary metal and all-cause and cardiovascular mortality in US adults DOI Creative Commons
Ting Cheng, Dongdong Yu, Li Geng

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(12), P. e0316045 - e0316045

Published: Dec. 27, 2024

Background Further evidence is required regarding the influence of metal mixture exposure on mortality. Therefore, we employed diverse statistical models to evaluate associations between eight urinary metals and risks all-cause cardiovascular Methods We measured levels 8 in urine adults who participated National Health Nutrition Examination Survey (NHANES) from 1999 2018. Based follow-up data, determined whether they died reasons for their deaths. estimated association mortality using Cox regression, weighted quantile sum (WQS) Bayesian kernel machine regression (BKMR) models. Additionally, used a competing risk model estimate relationship Results Among 14,305 individuals included our final analysis, there were 2,066 deaths, with 1,429 being cardiovascular-related. analysis showed that cobalt (Co) (HR: 1.21; 95% CI: 1.13, 1.30) antimony (Sb) 1.26; 1.12, 1.40) positively associated (all P trend <0.001). In model, Co 1.29; 1.48), lead (Pb) 1.18; 1.03, 1.37), Sb 1.44; 1.18, 1.75) significantly an increased Sb, Pb, cadmium (Cd), molybdenum (Mo) had highest weight rankings WQS model. All complex non-linear mortality, high posterior inclusion probabilities (PIPs) BKMR Conclusions Combining all models, it possible may have more stable impact Meaningful effects individual still require careful attention.

Language: Английский

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