{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T17:37:53Z","timestamp":1768239473100,"version":"3.49.0"},"reference-count":63,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"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>Volatile organic compounds (VOCs) are emerging environmental pollutants linked to various health problems. However, the relationship between exposure to urinary volatile organic compound metabolites (mVOCs) and sarcopenia remains unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used data from the National Health and Nutrition Examination Survey (NHANES 2011\u20132018) to assess the association between mVOCs and sarcopenia through multivariable logistic regression and restricted cubic spline (RCS) regression. We also employed Weighted Quantile Sum (WQS) regression model, a high-dimensional statistical approach used to evaluate the joint effects of multiple exposures, and Bayesian Kernel Machine regression (BKMR) model, a combination of Bayesian and statistical learning methods, to assess the mixture effects of mVOCs on sarcopenia risk. These methods account for non-linearity, collinearity, and dimensionality in exposure data. Mediation analysis was used to identify metabolic, endocrine, and inflammatory mediators in these associations. Subgroup analyses were conducted by gender and age. Network pharmacology analysis was performed to identify potential pathways and targets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 2,898 participants were included, with 145 (8%) diagnosed with sarcopenia. Logistic regression showed a positive correlation between mVOCs (3,4-MHA, ATCA, CEMA, CYMA, 2HPMA, 3HPMA, MHBMA3, and PGA) and sarcopenia. RCS results confirmed linear dose-response associations (\n                      <jats:italic>P<\/jats:italic>\n                      for overall &amp;lt; 0.05,\n                      <jats:italic>P<\/jats:italic>\n                      for non-linear \u22650.05). Subgroup analysis indicated stronger associations in older participants. The WQS and BKMR models consistently showed a positive link between VOC exposure and sarcopenia. Mediation analysis identified alkaline phosphatase (ALP), white blood cell count (WBC), systemic immune-inflammation index (SII), and vitamin D as mediators. Network analysis revealed significant enrichment in the endocrine resistance pathway.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our findings suggest that co-exposure to VOCs is associated with increased sarcopenia risk, potentially through disruption of endocrine and inflammatory pathways, as indicated by elevated alkaline phosphatase (ALP), white blood cell count (WBC), the systemic immune-inflammation index (SII), and reduced vitamin D levels, with enrichment observed in the endocrine resistance signaling pathway.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2025.1613435","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T05:25:22Z","timestamp":1752557122000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Volatile organic compounds exposure associated with sarcopenia in US adults from NHANES 2011\u20132018"],"prefix":"10.3389","volume":"13","author":[{"given":"Pangbo","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongwei","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liwei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,15]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e0169548","DOI":"10.1371\/journal.pone.0169548","article-title":"Health outcomes of sarcopenia: a systematic review and meta-analysis","volume":"12","author":"Beaudart","year":"2017","journal-title":"PLoS ONE."},{"key":"B2","doi-asserted-by":"publisher","first-page":"101617","DOI":"10.1016\/j.arr.2022.101617","article-title":"Sarcopenia definition: does it really matter? 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