2017
Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES
Park S, Zhao Z, Mukherjee B. Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES. Environmental Health 2017, 16: 102. PMID: 28950902, PMCID: PMC5615812, DOI: 10.1186/s12940-017-0310-9.Peer-Reviewed Original ResearchConceptsEnvironmental risk scoreBayesian kernel machine regressionNational Health and Nutrition Examination SurveyHealth and Nutrition Examination SurveyRisk scoreAssociated with odds ratiosNutrition Examination SurveyAssociated with systolicExamination SurveyMulti-pollutant approachKernel machine regressionPollutant mixturesSD increaseEpidemiological researchDiastolic blood pressureMortality outcomesOdds ratioBayesian additive regression treesDisease endpointsHealth endpointsCumulative riskPositive associationEnvironmental exposuresIntermediate markersCardiovascular disease
2005
The avoidable health effects of air pollution in three Latin American cities: Santiago, São Paulo, and Mexico City
Bell ML, Davis DL, Gouveia N, Borja-Aburto VH, Cifuentes LA. The avoidable health effects of air pollution in three Latin American cities: Santiago, São Paulo, and Mexico City. Environmental Research 2005, 100: 431-440. PMID: 16181621, DOI: 10.1016/j.envres.2005.08.002.Peer-Reviewed Original ResearchConceptsMedical visitsHealth outcomesConcentration-response functionsNumerous adverse health outcomesHealth benefitsAdverse health outcomesChild's medical visitsChronic bronchitisAsthma attacksEpidemiological studiesEconomic burdenHealth consequencesHealth endpointsHealth effectsSignificant healthHealth impactsAir pollutionHealth
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