The relationship between dietary vitamin B1 and stroke: a machine learning analysis of NHANES data DOI Creative Commons

Shihan Guo,

Jiao Xu,

Mingfei Li

и другие.

Frontiers in Nutrition, Год журнала: 2025, Номер 12

Опубликована: Май 6, 2025

Vitamin B1 deficiency is closely linked to damage in the cardiovascular system. However, relationship between dietary intake and risk of stroke remains ambiguous requires further investigation. This study analyzed data from participants National Health Nutrition Examination Survey (NHANES: 2005-2018) investigate vitamin ischemic stroke. Weighted multivariable logistic regression models restricted cubic spline (RCS) were employed explore potential nonlinear relationships, subgroup analyses conducted assess robustness results. Additionally, Least Absolute Shrinkage Selection Operator (LASSO) was utilized for feature selection. Eight machine learning methods construct predictive evaluate their performance. Based on best-performing model, we examined variable importance model accuracy, employing Shapley Additive Explanations (SHAP) analysis interpret model. Finally, a nomogram created enhance readability After controlling various variables, exhibited significant linear negative correlation with risk. In comparison lowest quartile, adjusted odds ratio (OR) fourth quartile notably reduced 0.66 (95% CI: 0.46, 0.94). Restricted confirmed inverse levels Moreover, Gradient Boosting Machine (GBM) demonstrated robust efficacy, achieving an area under curve (AUC) 91.9%. A large-scale based NHANES indicates that as increases, shows gradual decline. Therefore, appropriately increasing may reduce occurrence.

Язык: Английский

Legacy and alternative per- and polyfluoroalkyl substances spatiotemporal distribution in China: human exposure, environmental media, and risk assessment DOI
Jing Li,

Wenjing Duan,

Ziwen An

и другие.

Journal of Hazardous Materials, Год журнала: 2024, Номер 480, С. 135795 - 135795

Опубликована: Сен. 12, 2024

Язык: Английский

Процитировано

14
Association Between Serum Levels of Perfluoroalkyl and Polyfluoroalkyl Substances and Dental Floss Use: The Double‐Edged Sword of Dental Floss Use—A Cross‐Sectional Study DOI Creative Commons

Yan Jiao,

Fu Zhuo,

Xiaochen Ni

и другие.

Journal Of Clinical Periodontology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 11, 2025

ABSTRACT Background Although evidence suggests that dental floss contains perfluoroalkyl and polyfluoroalkyl substances (PFASs), it is still uncertain whether the use of contributes to an increased risk PFAS exposure. Methods We analysed data on serum concentrations usage in a cohort 6750 adults who participated National Health Nutrition Examination Survey (NHANES) from 2009 2020. In our study, we used logistic regression, survey‐weighted linear model, item response theory (IRT) scores, inverse probability weights (IPWs) sensitivity analysis assess potential impact human levels. Results The six PFASs revealed users had higher perfluorooctanoic acid (PFOA) compared with non‐users, while other were lower. Dental recorded lower level overall burden score non‐users. Sensitivity showed statistically significant increase PFOA concentration among users. Conclusion Our findings suggest may be associated differently specific PFASs. Among large representative sample U.S. adults, individuals reporting levels overall, exception PFOA, which was slightly elevated. important oral hygiene tool, further research needed clarify its role

Язык: Английский

Процитировано

1
Drosophila melanogaster as a tractable eco-environmental model to unravel the toxicity of micro- and nanoplastics DOI Creative Commons
Yán Wāng, Yang Jiang

Environment International, Год журнала: 2024, Номер 192, С. 109012 - 109012

Опубликована: Сен. 17, 2024

Язык: Английский

Процитировано

8
Machine learning prediction of glaucoma by heavy metal exposure: results from the National Health and Nutrition Examination Survey 2005 to 2008 DOI Creative Commons
Xinchen Wang, Gang Chen, Rui He

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 10, 2025

Using follow-up data from the National Health and Nutrition Examination Survey (NHANES) database, we have collected information on 2572 subjects used generalized linear model to investigate association between urinary heavy metal levels glaucoma risk. In addition, developed an individualized risk prediction using machine learning algorithms further interpreted results through feature importance analysis, local cumulative interaction effects. this study, found significant logarithmically calculated arsenic (As) metabolites, especially arsenochlorine (AC), after adjusting for a series of confounders, including creatinine (β = 1.090, 95% CI: 0.313–1.835). The Shapley Additive Explanations (SHAP) analysis clinical scores also indicated that As metabolites promoted more severely than other variables. This study applied first time explore relationship metals while analyzing effects multiple exposures disease, improving predictive power compared conventional models. Our provided important insights into potential role in pathogenesis glaucoma, facilitated discovery new biomarkers early diagnosis, assessment, timely treatment guided public health measures reduce exposure.

Язык: Английский

Процитировано

0
The relationship between dietary vitamin B1 and stroke: a machine learning analysis of NHANES data DOI Creative Commons

Shihan Guo,

Jiao Xu,

Mingfei Li

и другие.

Frontiers in Nutrition, Год журнала: 2025, Номер 12

Опубликована: Май 6, 2025

Vitamin B1 deficiency is closely linked to damage in the cardiovascular system. However, relationship between dietary intake and risk of stroke remains ambiguous requires further investigation. This study analyzed data from participants National Health Nutrition Examination Survey (NHANES: 2005-2018) investigate vitamin ischemic stroke. Weighted multivariable logistic regression models restricted cubic spline (RCS) were employed explore potential nonlinear relationships, subgroup analyses conducted assess robustness results. Additionally, Least Absolute Shrinkage Selection Operator (LASSO) was utilized for feature selection. Eight machine learning methods construct predictive evaluate their performance. Based on best-performing model, we examined variable importance model accuracy, employing Shapley Additive Explanations (SHAP) analysis interpret model. Finally, a nomogram created enhance readability After controlling various variables, exhibited significant linear negative correlation with risk. In comparison lowest quartile, adjusted odds ratio (OR) fourth quartile notably reduced 0.66 (95% CI: 0.46, 0.94). Restricted confirmed inverse levels Moreover, Gradient Boosting Machine (GBM) demonstrated robust efficacy, achieving an area under curve (AUC) 91.9%. A large-scale based NHANES indicates that as increases, shows gradual decline. Therefore, appropriately increasing may reduce occurrence.

Язык: Английский

Процитировано

0