Testing and Validating Semi-automated Approaches to the Occupational Exposure Assessment of Polycyclic Aromatic Hydrocarbons.

Santiago-Colón, Albeliz; Rocheleau, Carissa M; Bertke, Stephen; Christianson, Annette; Collins, Devon T; Trester-Wilson, Emma; Sanderson, Wayne; Waters, Martha A; Reefhuis, Jennita

Santiago-Colón, Albeliz; Rocheleau, Carissa M; Bertke, Stephen; Christianson, Annette; Collins, Devon T; Trester-Wilson, Emma; Sanderson, Wayne; Waters, Martha A; Reefhuis, Jennita.

Afiliación

Santiago-Colón A; Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Cincinnati, OH, USA.
Rocheleau CM; Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Cincinnati, OH, USA.
Bertke S; Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Cincinnati, OH, USA.
Christianson A; Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Cincinnati, OH, USA.
Collins DT; Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, USA.
Trester-Wilson E; Department of Epidemiology, University of Kentucky, College of Public Health, Lexington, KY, USA.
Sanderson W; Inova Fairfax Medical Campus, Falls Church, VA, USA.
Waters MA; Department of Epidemiology, University of Kentucky, College of Public Health, Lexington, KY, USA.
Reefhuis J; Department of Epidemiology, University of Kentucky, College of Public Health, Lexington, KY, USA.

Ann Work Expo Health ; 65(6): 682-693, 2021 07 03.

Article en En | MEDLINE | ID: mdl-33889928

Asunto(s)

Exposición Profesional; Hidrocarburos Policíclicos Aromáticos; Estudios de Casos y Controles; Femenino; Humanos; Exposición Profesional/análisis; Ocupaciones; Estudios Retrospectivos

Palabras clave

National Birth Defects Prevention Study; exposure assessment; female worker; jobs; machine-learning algorithm; occupation; polycyclic aromatic hydrocarbons; population-based; prediction model; regularized logistic regression

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Texto completo: 1 Colección: 01-internacional Asunto principal: Hidrocarburos Policíclicos Aromáticos / Exposición Profesional Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Ann Work Expo Health Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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