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Distinguishing Exposure to Secondhand and Thirdhand Tobacco Smoke among U.S. Children Using Machine Learning: NHANES 2013-2016.
Merianos, Ashley L; Mahabee-Gittens, E Melinda; Stone, Timothy M; Jandarov, Roman A; Wang, Lanqing; Bhandari, Deepak; Blount, Benjamin C; Matt, Georg E.
Afiliación
  • Merianos AL; School of Human Services, University of Cincinnati, P.O. Box 210068, Cincinnati, Ohio 45221, United States.
  • Mahabee-Gittens EM; Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Avenue, Cincinnati, Ohio 45229, United States.
  • Stone TM; Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Kettering Lab Building, 160 Panzeca Way, Cincinnati, Ohio 45267-0056, United States.
  • Jandarov RA; Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Kettering Lab Building, 160 Panzeca Way, Cincinnati, Ohio 45267-0056, United States.
  • Wang L; Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, Atlanta, Georgia 30341, United States.
  • Bhandari D; Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, Atlanta, Georgia 30341, United States.
  • Blount BC; Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, Atlanta, Georgia 30341, United States.
  • Matt GE; Department of Psychology, College of Sciences, San Diego State University, 9245 Sky Park Court, Suite 225, San Diego, California 92123, United States.
Environ Sci Technol ; 57(5): 2042-2053, 2023 02 07.
Article en En | MEDLINE | ID: mdl-36705578
While the thirdhand smoke (THS) residue from tobacco smoke has been recognized as a distinct public health hazard, there are currently no gold standard biomarkers to differentiate THS from secondhand smoke (SHS) exposure. This study used machine learning algorithms to assess which combinations of biomarkers and reported tobacco smoke exposure measures best differentiate children into three groups: no/minimal tobacco smoke exposure (NEG); predominant THS exposure (TEG); and mixed SHS and THS exposure (MEG). Participants were 4485 nonsmoking 3-17-year-olds from the National Health and Nutrition Examination Survey 2013-2016. We fitted and tested random forest models, and the majority (76%) of children were classified in NEG, 16% were classified in TEG, and 8% were classified in MEG. The final classification model based on reported exposure, biomarker, and biomarker ratio variables had a prediction accuracy of 95%. This final model had prediction accuracies of 100% for NEG, 88% for TEG, followed by 71% for MEG. The most important predictors were the reported number of household smokers, serum cotinine, serum hydroxycotinine, and urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). In the absence of validated biomarkers specific to THS, comprehensive biomarker and questionnaire data for tobacco smoke exposure can distinguish children exposed to SHS and THS with high accuracy.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminación por Humo de Tabaco Tipo de estudio: Prognostic_studies Límite: Child / Humans Idioma: En Revista: Environ Sci Technol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminación por Humo de Tabaco Tipo de estudio: Prognostic_studies Límite: Child / Humans Idioma: En Revista: Environ Sci Technol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos