2024
A unified framework for assessing interaction effects among environmental exposures in epidemiologic studies: A case study on temperature, air pollution, and kidney-related conditions in New York state
Chu L, Chen K, Yang Z, Crowley S, Dubrow R. A unified framework for assessing interaction effects among environmental exposures in epidemiologic studies: A case study on temperature, air pollution, and kidney-related conditions in New York state. Environmental Research 2024, 248: 118324. PMID: 38301759, DOI: 10.1016/j.envres.2024.118324.Peer-Reviewed Original ResearchAir pollutionMultiplicative interaction effectsNew York StateEstimated health burdenCase-crossover designEvaluation of effect modificationBi-variate associationsAssess interaction effectsConditional logistic modelMeasures of exposureInteraction effectsEffect modificationPollutionExposure variablesHealth burdenEpidemiological studiesEnvironmental exposuresLog-linear modelLogistic modelInteraction termsQuantitative frameworkAirCase studyExposureAlert system
2018
Associations between maternal plasma measurements of inflammatory markers and urinary levels of phenols and parabens during pregnancy: A repeated measures study
Aung M, Ferguson K, Cantonwine D, Bakulski K, Mukherjee B, Loch-Caruso R, McElrath T, Meeker J. Associations between maternal plasma measurements of inflammatory markers and urinary levels of phenols and parabens during pregnancy: A repeated measures study. The Science Of The Total Environment 2018, 650: 1131-1140. PMID: 30308801, PMCID: PMC6236678, DOI: 10.1016/j.scitotenv.2018.08.356.Peer-Reviewed Original ResearchConceptsPlasma inflammatory markersInflammatory markersC-reactive proteinInterquartile range increaseFetal developmentImmunological biomarkersRange increaseTumor necrosis factor-aCase-control studyProspective birth cohortImmune system regulationHealthy pregnancyUrinary phenolSystemic inflammationImmunological mechanismsInterleukin-10Urinary levelsInterleukin-1bPregnancyStudy visitsMultivariate linear mixed modelReproductive outcomesMeasures of exposureInverse probability weightingUrine samplesEvaluating the Risk of Noise-Induced Hearing Loss Using Different Noise Measurement Criteria
Roberts B, Seixas N, Mukherjee B, Neitzel R. Evaluating the Risk of Noise-Induced Hearing Loss Using Different Noise Measurement Criteria. Annals Of Work Exposures And Health 2018, 62: 295-306. PMID: 29415217, DOI: 10.1093/annweh/wxy001.Peer-Reviewed Original ResearchConceptsHearing threshold levelsHearing outcomesHearing lossOccupational Safety and Health AdministrationRisk of noise-induced hearing lossHealth AdministrationNoise exposureOccupational Safety and HealthNoise-induced hearing lossInstitute of Occupational Safety and HealthSafety and HealthNational Institute of Occupational Safety and HealthCohort of construction workersMixed modelsDuration of participationAssessment of noise exposureMeasures of exposureHearing levelAkaike’s information criterion differencesConstruction workersAverage noise levelLinear mixed modelsLAVGContinuous averagingOSHA
2016
Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients
Han L, Pisani MA, Araujo KL, Allore HG. Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients. International Journal Of Statistics In Medical Research 2016, 5: 8-16. PMID: 27123153, PMCID: PMC4844076, DOI: 10.6000/1929-6029.2016.05.01.2.Peer-Reviewed Original ResearchDelirium severity scoresIntensive care unitSeverity scoreOld intensive care patientsIntensive care patientsOlder medical patientsDose of haloperidolStable patient characteristicsICU stayBaseline characteristicsAcute outcomesPatient characteristicsCare patientsCare unitMeasures of exposureMedical patientsAntipsychotic medicationFull cohortPatientsStable baselineAnalytic sampleTreatment effectsHaloperidolCohortScores
2015
Statistical methods for modeling repeated measures of maternal environmental exposure biomarkers during pregnancy in association with preterm birth
Chen Y, Ferguson K, Meeker J, McElrath T, Mukherjee B. Statistical methods for modeling repeated measures of maternal environmental exposure biomarkers during pregnancy in association with preterm birth. Environmental Health 2015, 14: 9. PMID: 25619201, PMCID: PMC4417225, DOI: 10.1186/1476-069x-14-9.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsBiomarkersBostonCase-Control StudiesCross-Sectional StudiesData Interpretation, StatisticalEnvironmental ExposureFemaleHazardous SubstancesHumansInfant, NewbornMaternal ExposureMiddle AgedModels, StatisticalPhthalic AcidsPregnancyPremature BirthSocioeconomic FactorsYoung AdultConceptsPreterm birthEnvironmental chemical exposuresMeasures of urinary phthalate metabolitesNested Case-Control StudyCross-sectional analysisAverage exposureMeasures of exposureCase-control studyUrinary phthalate metabolitesModel repeated measuresEpidemiological research projectsLongitudinal exposureRepeated measuresPremature birthPretermEnvironmental exposure biomarkersExposure measurementsUrinary metabolitesMaternal factorsPhthalate metabolitesPregnancyStudy of phthalatesLongitudinal predictorsChemical exposureBirth
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