{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:29:07Z","timestamp":1787027347622,"version":"build-2736575974"},"reference-count":61,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T00:00:00Z","timestamp":1748995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Increasing evidence has demonstrated that exposure to environmental heavy metals harms human health. However, information regarding the impact of co-exposure to metal mixtures on the risk of overactive bladder (OAB) was limited. Our study aimed to explore the joint effects of blood heavy metal mixtures on OAB risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data for this study were obtained from four National Health and Nutrition Examination Survey cycles (2011\u20132018). The effects of single metals on OAB risk were explored using multivariate logistic regression. Additionally, we used weighted quantile sum (WQS), quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR) models to explore the combined effect of metal mixtures on OAB risk. Age-stratified subgroup analyses were conducted, and restricted cubic splines (RCS) were utilized to investigate the non-linear relationship between metals and OAB.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 4,183 individuals aged 20\u201380\u202fyears were included for further study. Among them, 866 (20.7%) participants had OAB. OAB patients had significantly higher blood concentrations of cadmium (Cd) and lead and lower blood concentrations of selenium and manganese than those without OAB (all\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.05). In the single-metal analyses, Cd significantly increased OAB risk. In the mixed-exposure analyses, the WQS and BKMR models consistently revealed a significant positive association between co-exposure to heavy metal mixtures and OAB risk, identifying Cd as the main positive driver. The young\/middle-aged group exhibited similar significant associations. In the metal mixtures, Cd was the top-weighted metal for the entire population and young\/middle-aged individuals, whereas mercury (Hg) held the highest weight among older adult individuals. Furthermore, we observed an underlying interaction between Cd and Hg in the BKMR model. In the sensitivity analyses, the findings from the qgcomp model validated the toxic effect of blood metal mixtures on OAB. According to the RCS regression, we identified a positive linear dose\u2013response relationship between Cd and OAB risk.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our study identified that co-exposure to heavy metal mixtures was significantly related to OAB risk. Further research prioritizing low-dose, real-world exposure to metal mixtures in vulnerable populations (e.g., older adult, high-risk occupations) is essential to translate our findings into preventive strategies and regulatory policies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2025.1597321","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T01:37:26Z","timestamp":1749001046000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Association between exposure to blood heavy metal mixtures and overactive bladder risk among U.S. adults: a cross-sectional study"],"prefix":"10.3389","volume":"13","author":[{"given":"Yanlin","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yameng","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meisheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hengxing","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoke","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,4]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1097\/JU.0000000000003985","article-title":"The aua\/sufu guideline on the diagnosis and treatment of idiopathic overactive bladder","volume":"212","author":"Cameron","year":"2024","journal-title":"J Urol"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.eururo.2022.01.045","article-title":"European association of urology guidelines on the diagnosis and management of female non-neurogenic lower urinary tract symptoms. 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