2025
Exposure profiles, determinants, and health risks of chemicals in personal care products among healthy older adults from the China BAPE study
Guo X, Qian J, Ren H, Ding E, Ma X, Zhang J, Qiu T, Lu Y, Sun P, Li C, Li C, Xu Y, Cao K, Lin X, Mao C, Tong S, Tang S, Shi X. Exposure profiles, determinants, and health risks of chemicals in personal care products among healthy older adults from the China BAPE study. Journal Of Hazardous Materials 2025, 488: 137365. PMID: 39869979, DOI: 10.1016/j.jhazmat.2025.137365.Peer-Reviewed Original ResearchConceptsPersonal care productsHealthy older adultsHealth risksOlder adultsExposure to ambient PM<sub>2.5</sub>Benzophenone-2Ambient PM<sub>2.5</sub>Care productsHealth risks associated with exposureRisks associated with exposureAssociated health risksRisk of chemicalsHealth risks of chemicalsIncreased physical activityAssessment of older adultsMinimal health risksPhysical well-beingPredominant chemicalsMedian concentrationsPhysical activityExposure assessmentExposure profilesRisk assessmentExposure levelsMethyl paraben
2024
The need for a cancer exposome atlas: a scoping review
Young A, Mullins C, Sehgal N, Vermeulen R, Kolijn P, Vlaanderen J, Rahman M, Birmann B, Barupal D, Lan Q, Rothman N, Walker D. The need for a cancer exposome atlas: a scoping review. JNCI Cancer Spectrum 2024, 9: pkae122. PMID: 39700422, PMCID: PMC11729703, DOI: 10.1093/jncics/pkae122.Peer-Reviewed Original ResearchConceptsCancer riskGenetic susceptibility to cancerStudy design limitationsSusceptibility to cancerCancer heritabilitySocial determinantsCancer epidemiologyExposome approachProspective associationsExternal risk factorsCancer casesPrimary preventionUnmet opportunitiesCancer researchChemical exposure profilesEnvironmental exposuresRisk factorsExposomeEvaluate progressCancer typesCancerRiskExposure profilesEnvironmental influencesLifestyleContaminant Exposure Profiles Demonstrate Similar Physiological Effects Across Environments Despite Unique Profile Composition in Formosa, Argentina, and Connecticut, USA
Chaney C, Mansilla L, Kubica M, Pinto‐Pacheco B, Dunn K, Bertacchi V, Walker D, Valeggia C. Contaminant Exposure Profiles Demonstrate Similar Physiological Effects Across Environments Despite Unique Profile Composition in Formosa, Argentina, and Connecticut, USA. American Journal Of Human Biology 2024, 37: e24178. PMID: 39463098, DOI: 10.1002/ajhb.24178.Peer-Reviewed Original ResearchInfant urineChemical exposure profilesExposure profilesEnvironmental contaminationAssociated with alterationsExposure to environmental contaminantsCardiovascular disease riskExposed to contaminantsEnvironmental contaminant exposureUntargeted liquid chromatographyCombinations of contaminantsStatistically significant differenceMaternal urineMother-infant dyadsExposome-wide association studyHuman milk samplesEndogenous metabolitesInfant cognitive developmentContaminant exposureContamination profilesSignificant differenceInfant exposureStudy sitesHuman healthUrine
2021
Head, Shoulders, Knees, and Toes: Placement of Wearable Passive Samplers Alters Exposure Profiles Observed
Koelmel JP, Lin EZ, Nichols A, Guo P, Zhou Y, Pollitt K. Head, Shoulders, Knees, and Toes: Placement of Wearable Passive Samplers Alters Exposure Profiles Observed. Environmental Science And Technology 2021, 55: 3796-3806. PMID: 33625210, DOI: 10.1021/acs.est.0c05522.Peer-Reviewed Original ResearchConceptsSemivolatile organic compoundsOrganic compoundsGas chromatography-high resolution mass spectrometryPassive samplersHigh-resolution mass spectrometryVolatile organic compoundsPersonal exposure profilesChemicals of concernMass spectrometryChemicalsExposure dynamicsExposure profilesCompoundsMajor risk factorComprehensive characterizationPersonal exposureAirborne contaminantsContaminant exposureRisk factorsInhalation routeEpidemiological studiesChemical exposureSpectrometrySamplerParticipants' wrists
2016
Classification and Clustering Methods for Multiple Environmental Factors in Gene–Environment Interaction
Ko Y, Mukherjee B, Smith J, Kardia S, Allison M, Roux A. Classification and Clustering Methods for Multiple Environmental Factors in Gene–Environment Interaction. Epidemiology 2016, 27: 870-878. PMID: 27479650, PMCID: PMC5039086, DOI: 10.1097/ede.0000000000000548.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAtherosclerosisBayes TheoremCluster AnalysisData Interpretation, StatisticalEnvironmental ExposureEpidemiologic Research DesignFemaleFollow-Up StudiesGene-Environment InteractionGenetic Predisposition to DiseaseHumansMiddle AgedModels, StatisticalRegression AnalysisRisk FactorsConceptsMultiple environmental exposuresGene-environment interactionsG x EEnvironmental exposuresMultiethnic Study of AtherosclerosisStudy of atherosclerosisGene-environmentEffect modificationMultiethnic StudyEnvironmental factorsExposure subgroupsEnvironmental exposure profilesMain effectExposure profilesE studyEfficient analysis strategyE analysisMultiple environmental factorsSubgroupsAnalysis strategyFactorsExposureProduct terms
1994
Exposure to ambient light in patients with winter seasonal affective disorder
Oren D, Moul D, Schwartz P, Brown C, Yamada E, Rosenthal N. Exposure to ambient light in patients with winter seasonal affective disorder. American Journal Of Psychiatry 1994, 151: 591-593. PMID: 8147459, DOI: 10.1176/ajp.151.4.591.Peer-Reviewed Original ResearchConceptsWinter seasonal affective disorderSeasonal affective disorderAffective disordersSeverity of depressionNormal comparison subjectsMorning light exposureNormal subjectsComparison subjectsGreater severityPatientsDepressionDisordersExposure profilesSeverityExposureLight exposureSubjectsShort photoperiodOutpatientsLight monitorWeeks
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