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The risks due to multiple workplace chemical exposures and those occupations most susceptible to the resulting health effects remain poorly characterized. The aim of this study is to identify occupations with elevated toxicant biomarker concentrations and increased health risk associated with toxicant exposures in a diverse working US population. For this observational study of 51\u00a0008 participants, we used data from the 1999\u20132014 National Health and Nutrition Examination Survey. We characterized differences in chemical exposures by occupational group for 131 chemicals by applying a series of generalized linear models with the outcome as biomarker concentrations and the main predictor as the occupational groups, adjusting for age, sex, race\/ethnicity, poverty income ratio, study period, and biomarker of tobacco use. For each occupational group, we calculated percentages of participants with chemical biomarker levels exceeding acceptable health-based guidelines. Blue-collar workers from \u201cConstruction,\u201d \u201cProfessional, Scientific, Technical Services,\u201d \u201cReal Estate, Rental, Leasing,\u201d \u201cManufacturing,\u201d and \u201cWholesale Trade\u201d have higher biomarker levels of toxicants such as several heavy metals, acrylamide, glycideamide, and several volatile organic compounds (VOCs) compared with their white-collar counterparts. Moreover, blue-collar workers from these industries have toxicant concentrations exceeding acceptable levels: arsenic (16%\u201358%), lead (1%\u20133%), cadmium (1%\u201311%), glycideamide (3%\u20136%), and VOCs (1%\u201333%). Blue-collar workers have higher toxicant levels relative to their white-collar counterparts, often exceeding acceptable levels associated with noncancer effects. Our findings identify multiple occupations to prioritize for targeted interventions and health policies to monitor and reduce toxicant exposures.<\/jats:p>","DOI":"10.1093\/exposome\/osac004","type":"journal-article","created":{"date-parts":[[2022,6,25]],"date-time":"2022-06-25T08:55:07Z","timestamp":1656147307000},"source":"Crossref","is-referenced-by-count":19,"title":["Identification of occupations susceptible to high exposure and risk associated with multiple toxicants in an observational study: National Health and Nutrition Examination Survey 1999\u20132014"],"prefix":"10.1093","volume":"2","author":[{"given":"Vy Kim","family":"Nguyen","sequence":"first","affiliation":[{"name":"Department of Environmental Health Sciences, School of Public Health, University of Michigan , Ann Arbor, MI, USA"},{"name":"Department of Biomedical Informatics, Medical School, Harvard University , Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justin","family":"Colacino","sequence":"additional","affiliation":[{"name":"Department of Environmental Health Sciences, School of Public Health, University of Michigan , Ann Arbor, MI, USA"},{"name":"Department of Nutritional Sciences, School of Public Health, University of Michigan , Ann Arbor, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8756-8525","authenticated-orcid":false,"given":"Chirag J","family":"Patel","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Medical School, Harvard University , Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maureen","family":"Sartor","sequence":"additional","affiliation":[{"name":"Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan , Ann Arbor, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olivier","family":"Jolliet","sequence":"additional","affiliation":[{"name":"Department of Environmental Health Sciences, School of Public Health, University of Michigan , Ann Arbor, MI, USA"},{"name":"Quantitative Sustainability Assessment, Department of Environmental and Resource Engineering, Technical University of Denmark , Kgs. 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