Urinary metal levels and their association with Parkinson’s disease risk
Insights from NHANES 2013–2020
Bibliographic Data
| ID | 22077258 |
|---|---|
| Authors | Jia-Jie Lv (Tongji University), Xinyu Li (0000-0002-3828-0971, Tongji University), Xin-Yu Li, Chenghao Yang (0000-0003-4793-7864, Tongji University, corresponding author), Cheng-hao Yang (0009-0002-1134-8734) |
| Year | 2025 |
| Volume | 13 |
| Pages | 1439325-1439325 |
| Publication date | 2025-03-26 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2025.1439325 |
| PMID | 40206165 |
| OpenAlex | W4408840271 |
| Language | EN |
| References cited | 35 |
Background: Parkinson's disease (PD) poses a significant public health challenge worldwide, with both genetic predispositions and behavioral factors contributing to its onset and progression. While the precise mechanisms underlying PD remain uncertain, environmental influences are increasingly acknowledged as critical risk factors. This research focused on investigating the relationship between urinary metal levels and the likelihood of developing PD. Methods: Using data from the National Health and Nutrition Examination Survey (NHANES), urinary levels of nine metals-barium (Ba), cadmium (Cd), cobalt (Co), cesium (Cs), molybdenum (Mo), lead (Pb), antimony (Sb), thallium (Tl), and uranium (Tu)-were measured in a cohort of 3,148 US adults. To examine their association with Parkinson's disease (PD) risk, multivariate logistic regression, weighted quantile sum (WQS) regression, and quantile regression were employed to evaluate both single and combined metal exposures. Additionally, Bayesian kernel machine regression (BKMR) was utilized to explore the joint effects of these metals, allowing for the assessment of potential nonlinear and non-additive interactions (using the "BKMR" package). Smooth curve fitting was further applied to visualize the nonlinear relationships between urinary metal concentrations and PD risk. Results: < 0.05). Mixed-exposure analyses showed a consistent association (OR 1.48, 95% CI 1.06 to 2.06). The metals with the highest weight in the WQS model were Mo (56.79%), Co (34.20%), Ba (3.33%), and Tu (3.27%). In addition, BKMR model analysis showed that most single and mixed metals were positively associated with PD risk. Taken together, the results suggest that metal concentrations can increase the prevalence of PD. Conclusion: In conclusion, this cross-sectional analysis of NHANES data indicates that higher urinary concentrations of metals including Mo, Cd, and Tu are associated with increased odds of PD among US adults. Mixed exposures to several metals may jointly elevate PD risk in a dose-dependent manner
Cohort · Environmental health · Logistic regression · National Health and Nutrition Examination Survey · Odds ratio · Population · Urinary system · Heavy Metal Exposure and Toxicity · Medicine · Parkinson's Disease Mechanisms and Treatments · Trace Elements in Health · Internal Medicine
| Citation velocity | historical |
|---|---|
| Highly cited | No |