2022
Per- and polyfluoroalkyl substances and incident diabetes in midlife women: the Study of Women’s Health Across the Nation (SWAN)
Park S, Wang X, Ding N, Karvonen-Gutierrez C, Calafat A, Herman W, Mukherjee B, Harlow S. Per- and polyfluoroalkyl substances and incident diabetes in midlife women: the Study of Women’s Health Across the Nation (SWAN). Diabetologia 2022, 65: 1157-1168. PMID: 35399113, PMCID: PMC9177697, DOI: 10.1007/s00125-022-05695-5.Peer-Reviewed Original ResearchConceptsStudy of Women's HealthIncident diabetesWomen's HealthPolyfluoroalkyl substancesDiabetes riskMidlife womenSelf-reported diabetesTotal energy intakeProspective cohort studyIncreased diabetes riskCox proportional hazards modelsPhysical activityGlucose-lowering medicationsProportional hazards modelResultsAfter adjustmentNation Multi-Pollutant StudyBottom tertileSmoking statusHighest tertileAlcohol consumptionDiabetes-free womenFollow-up visitG-computationQuantile-based g-computationCohort study
2021
Urinary concentrations of phenols and parabens and incident diabetes in midlife women
Lee S, Karvonen-Gutierrez C, Mukherjee B, Herman W, Harlow S, Park S. Urinary concentrations of phenols and parabens and incident diabetes in midlife women. Environmental Epidemiology 2021, 5: e171. PMID: 34934892, PMCID: PMC8683147, DOI: 10.1097/ee9.0000000000000171.Peer-Reviewed Original ResearchIncident diabetesHazard ratioAssociated with incident diabetesStudy of Women's HealthMid-life womenAdjusted hazard ratiosAssociation of incident diabetesProspective cohort studyWomen's HealthNo significant associationWomen's backgroundConcentration of phenolJoint effectsExposure variablesG-computationQuantile-based g-computationWithin-person variabilityBenzophenone-3Cohort studyDiabetes-freeBisphenol ANonlinear associationSignificant associationJoint effect of mixturesConcentrations of bisphenol AChanges in COVID-19-related outcomes, potential risk factors and disparities over time
Yu Y, Gu T, Valley T, Mukherjee B, Fritsche L. Changes in COVID-19-related outcomes, potential risk factors and disparities over time. Epidemiology And Infection 2021, 149: e192. PMCID: PMC8376857, DOI: 10.1017/s0950268821001898.Peer-Reviewed Original ResearchIntensive care unit admission ratePotential risk factorsHospitalisation ratesAdmission ratesIntensive care unitCOVID-19-positive cohortCOVID-19-related hospitalisationMichigan MedicineResidential-level socioeconomic characteristicsOdds ratioRisk factorsTime-stratified analysisT1 to T3Impact of potential risk factorsInvestigate temporal trendsCOVID-19-related outcomesRetrospective cohort studySocioeconomic statusRacial disparitiesCalendar timeCohort studySocioeconomic characteristicsHospitalisationBlack patientsComorbid conditionsPsychosocial status modifies the effect of maternal blood metal and metalloid concentrations on birth outcomes
Ashrap P, Aker A, Watkins D, Mukherjee B, Rosario-Pabón Z, Vélez-Vega C, Alshawabkeh A, Cordero J, Meeker J. Psychosocial status modifies the effect of maternal blood metal and metalloid concentrations on birth outcomes. Environment International 2021, 149: 106418. PMID: 33548848, PMCID: PMC7897320, DOI: 10.1016/j.envint.2021.106418.Peer-Reviewed Original ResearchConceptsAdverse birth outcomesPsychosocial statusBirth outcomesBody mass indexPsychosocial stressPreterm birthOdds ratioAssociated with adverse birth outcomesPre-pregnancy body mass indexSecond-hand smoke exposurePrenatal psychosocial stressPregnant womenBlood metalsClusters of womenEffects of psychosocial stressPuerto Rico TestsiteIncreased odds ratioSocial supportPerceived stressMaternal educationAdverse associationOverall preterm birthLow birth weightSpontaneous preterm birthCohort study
2020
Comprehensive public health evaluation of lockdown as a non-pharmaceutical intervention on COVID-19 spread in India: national trends masking state-level variations
Salvatore M, Basu D, Ray D, Kleinsasser M, Purkayastha S, Bhattacharyya R, Mukherjee B. Comprehensive public health evaluation of lockdown as a non-pharmaceutical intervention on COVID-19 spread in India: national trends masking state-level variations. BMJ Open 2020, 10: e041778. PMID: 33303462, PMCID: PMC7733201, DOI: 10.1136/bmjopen-2020-041778.Peer-Reviewed Original ResearchConceptsEffective public health interventionsPublic health interventionsPublic health evaluationPublic health metricsAverage daily numberHealth interventionsState-level trendsHealth metricsTest positivity rateCohort studyCase fatality rateHealth evaluationNational trendsCOVID-19Holistic assessmentDaily numberConfirmed COVID-19 casesCOVID-19 pandemicNational patternsNational lockdownInterventionCOVID-19 outbreakFatality rateCase countsState-wise variations
2019
Interactions between chemicals and non-chemical stressors: The modifying effect of life events on the association between triclocarban, phenols and parabens with gestational length in a Puerto Rican cohort
Aker A, McConnell R, Loch-Caruso R, Park S, Mukherjee B, Rosario Z, Vélez-Vega C, Huerta-Montanez G, Alshawabkeh A, Cordero J, Meeker J. Interactions between chemicals and non-chemical stressors: The modifying effect of life events on the association between triclocarban, phenols and parabens with gestational length in a Puerto Rican cohort. The Science Of The Total Environment 2019, 708: 134719. PMID: 31785910, PMCID: PMC6957748, DOI: 10.1016/j.scitotenv.2019.134719.Peer-Reviewed Original ResearchConceptsLife eventsLinear regression modelsMultiple linear regression modelNegative life eventsPresence of negative life eventsPsychosocial stress measuresAdverse birth outcomesPregnancy cohort studyRegression modelsEffects of psychosocial stressPsychosocial factorsNon-chemical stressorsBirth outcomesEffects of life eventsCohort studyPsychosocial stressPositive LEsPositive life eventsExposure biomarkersSignificant modifiersPrenatal exposureSignificant interactionWomenAssociationRate of eventsEstimating Outcome-Exposure Associations when Exposure Biomarker Detection Limits vary Across Batches.
Boss J, Mukherjee B, Ferguson K, Aker A, Alshawabkeh A, Cordero J, Meeker J, Kim S. Estimating Outcome-Exposure Associations when Exposure Biomarker Detection Limits vary Across Batches. Epidemiology 2019, 30: 746-755. PMID: 31299670, PMCID: PMC6677587, DOI: 10.1097/ede.0000000000001052.Peer-Reviewed Original ResearchConceptsBinary outcome dataLikelihood-based methodsComplete-case analysisDistributional assumptionsAssignment of samplesSuperior estimation propertiesSimulation studyComplete-caseMultiple imputation strategyExposure dataMultiple batchesBatch assignmentEstimated propertiesLimit-variablesSingle imputationMultiple imputationCohort studyFactors Associated With Use of Sipuleucel-T to Treat Patients With Advanced Prostate Cancer
Caram M, Ross R, Lin P, Mukherjee B. Factors Associated With Use of Sipuleucel-T to Treat Patients With Advanced Prostate Cancer. JAMA Network Open 2019, 2: e192589. PMID: 31002323, PMCID: PMC6481456, DOI: 10.1001/jamanetworkopen.2019.2589.Peer-Reviewed Original ResearchConceptsMinimally symptomatic metastatic castration-resistant prostate cancerSipuleucel-TProstate cancerSymptomatic metastatic castration-resistant prostate cancerDatabase of commercially insured patientsMetastatic castration-resistant prostate cancerCastration-resistant prostate cancerAge of patientsRetrospective cohort studyFactors associated with useAssociated with patientsCommercially insured patientsPatterns of treatmentConcurrent therapyTreated patientsCohort studyMultivariate analysisCancer therapyTherapyPatientsPhysician factorsCancerBarriers to treatmentBinomial logistic regressionLogistic regressionMulticenter Prospective Cohort Study of the Diagnostic Yield and Patient Experience of Multiplex Gene Panel Testing For Hereditary Cancer Risk
Idos G, Kurian A, Ricker C, Sturgeon D, Culver J, Kingham K, Koff R, Chun N, Rowe-Teeter C, Lebensohn A, Levonian P, Lowstuter K, Partynski K, Hong C, Mills M, Petrovchich I, S. C, Hartman A, Allen B, Wenstrup R, Lancaster J, Brown K, Kidd J, Evans B, Mukherjee B, McDonnell K, Ladabaum U, Ford J, Gruber S. Multicenter Prospective Cohort Study of the Diagnostic Yield and Patient Experience of Multiplex Gene Panel Testing For Hereditary Cancer Risk. JCO Precision Oncology 2019, 3: po.18.00217. PMID: 34322651, PMCID: PMC8260917, DOI: 10.1200/po.18.00217.Peer-Reviewed Original ResearchMultiplex gene panel testProspective cohort studyGene panel testingPatient experiencePathogenic variantsDiagnostic yieldCohort studyNorris Comprehensive Cancer CenterHereditary cancer riskSocioeconomically diverse cohortComprehensive cancer centerPost-test surveysPanel testingCancer susceptibility genesMulticenter prospective cohort studyLos Angeles CountyUniversity of Southern California Medical CenterIdentified pathogenic variantsCancer riskSouthern California Medical CenterLess educationPatient regretProphylactic surgeryExpert clinical assessmentCalifornia Medical Center
2018
Associations between repeated ultrasound measures of fetal growth and biomarkers of maternal oxidative stress and inflammation in pregnancy
Ferguson K, Kamai E, Cantonwine D, Mukherjee B, Meeker J, McElrath T. Associations between repeated ultrasound measures of fetal growth and biomarkers of maternal oxidative stress and inflammation in pregnancy. American Journal Of Reproductive Immunology 2018, 80: e13017. PMID: 29984454, PMCID: PMC6160349, DOI: 10.1111/aji.13017.Peer-Reviewed Original ResearchConceptsAssociated with reduced fetal growthFetal growthAssociated with poorer childAdult health outcomesOxidative stress markersBirth cohort studyInterquartile rangeAssociated with head circumferenceRepeated-measures modelFetal weight z-scoreAssociated with fetal weightOxidative stressHealth outcomesStandard deviation decreaseWeight z-scoreStress markersSecondary analysisMaternal oxidative stressCohort studyZ-scoreFetal weightMaternal inflammationDeviation decreasePreterm birthHead circumferenceAssociations between maternal phenol and paraben urinary biomarkers and maternal hormones during pregnancy: A repeated measures study
Aker A, Johns L, McElrath T, Cantonwine D, Mukherjee B, Meeker J. Associations between maternal phenol and paraben urinary biomarkers and maternal hormones during pregnancy: A repeated measures study. Environment International 2018, 113: 341-349. PMID: 29366524, PMCID: PMC5866216, DOI: 10.1016/j.envint.2018.01.006.Peer-Reviewed Original ResearchConceptsThyroid hormonesAssociated with altered thyroid hormone levelsFetal health outcomesThyroid hormone levelsIQR increaseMultivariate regression analysisGestational ageMultivariate linear regression modelFetal neurodevelopmentPregnant womenFree thyroxinePotential biological mechanismsTime of exposureUrinary biomarkersCohort studyHormone levelsParaben biomarkersTotal triiodothyronineCase-control samplePregnancyBlood samplesTotal thyroxineHormone concentrationsHealth outcomesHormone
2017
Exposure enriched outcome dependent designs for longitudinal studies of gene–environment interaction
Sun Z, Mukherjee B, Estes J, Vokonas P, Park S. Exposure enriched outcome dependent designs for longitudinal studies of gene–environment interaction. Statistics In Medicine 2017, 36: 2947-2960. PMID: 28497531, PMCID: PMC5523112, DOI: 10.1002/sim.7332.Peer-Reviewed Original ResearchConceptsLongitudinal cohort studyCohort studyCase-only designLongitudinal studyG x E interactionNormative Aging StudyComplete-case analysisGene-environmentSampling designCase-controlVeterans AdministrationComplex human diseasesE interactionExposure informationAging StudyOutcome trajectoriesStratified samplingRetrospective genotypingIndividual exposureCovariate dataExposure effectsJoint effectsOutcomesTime-varying outcomeEnvironmental factors
2014
Latent variable models for gene–environment interactions in longitudinal studies with multiple correlated exposures
Tao Y, Sánchez B, Mukherjee B. Latent variable models for gene–environment interactions in longitudinal studies with multiple correlated exposures. Statistics In Medicine 2014, 34: 1227-1241. PMID: 25545894, PMCID: PMC4355187, DOI: 10.1002/sim.6401.Peer-Reviewed Original ResearchMeSH KeywordsBiostatisticsChild, PreschoolComputer SimulationEnvironmental ExposureFemaleGene-Environment InteractionHemochromatosis ProteinHistocompatibility Antigens Class IHumansInfantInfant, NewbornLead PoisoningLongitudinal StudiesMembrane ProteinsMexicoModels, GeneticModels, StatisticalPolymorphism, Single NucleotidePregnancyPrenatal Exposure Delayed EffectsConceptsGene-environment interactionsOutcome measuresCohort studyHealth effects of environmental exposuresEnvironmental exposuresInvestigate health effectsGene-environment associationsEffects of environmental exposuresEarly life exposuresLV frameworkG x E effectsMultivariate exposuresGenotyped single nucleotide polymorphismsEffect modificationShrinkage estimatorsLife exposureExposure measurementsSingle nucleotide polymorphismsData-adaptive wayMultiple testingOutcome dataLongitudinal studyLongitudinal natureGenetic factorsNucleotide polymorphisms
2013
Propensity score‐based diagnostics for categorical response regression models
Boonstra P, Bondarenko I, Park S, Vokonas P, Mukherjee B. Propensity score‐based diagnostics for categorical response regression models. Statistics In Medicine 2013, 33: 455-469. PMID: 23934948, PMCID: PMC3911784, DOI: 10.1002/sim.5940.Peer-Reviewed Original ResearchConceptsRetrospective sampling designsChi-square distributionCategorical response modelsGoodness-of-fit statisticsPredicted response probabilitiesResponse regression modelsConditional distributionProportional odds modelAssess model adequacyData examplesSimulation studyVA Normative Aging StudyNormative Aging StudyPropensity scoreCumulative lead exposureOdds modelModel diagnosticsCase-control studyAssociated with diabetesBalance scoresResponse probabilityModel adequacyCohort studyAging StudyNumerical summariesNovel Likelihood Ratio Tests for Screening Gene‐Gene and Gene‐Environment Interactions With Unbalanced Repeated‐Measures Data
Ko Y, Saha‐Chaudhuri P, Park S, Vokonas P, Mukherjee B. Novel Likelihood Ratio Tests for Screening Gene‐Gene and Gene‐Environment Interactions With Unbalanced Repeated‐Measures Data. Genetic Epidemiology 2013, 37: 581-591. PMID: 23798480, PMCID: PMC4009698, DOI: 10.1002/gepi.21744.Peer-Reviewed Original ResearchConceptsGene-environment interactionsGene-gene interactionsTesting gene-gene interactionsModel gene-gene interactionsRepeated-measures studyLongitudinal cohort studyNormative Aging StudyCumulative lead exposureCase-control studyGene-environmentGene-geneType I error rateCohort studyScreening toolAging StudyLikelihood ratio testMain effectEpistasis patternsRatio testLead exposureHemochromatosis genePower propertiesPulse pressureRegression-based approachRestrictive assumptions
2012
Air-Pollution and Cardiometabolic Diseases (AIRCMD): A prospective study investigating the impact of air pollution exposure and propensity for type II diabetes
Sun Z, Mukherjee B, Brook R, Gatts G, Yang F, Sun Q, Brook J, Fan Z, Rajagopalan S. Air-Pollution and Cardiometabolic Diseases (AIRCMD): A prospective study investigating the impact of air pollution exposure and propensity for type II diabetes. The Science Of The Total Environment 2012, 448: 72-78. PMID: 23182147, PMCID: PMC4548977, DOI: 10.1016/j.scitotenv.2012.10.087.Peer-Reviewed Original ResearchConceptsAir pollution exposureAir pollutionAmbient fine particulate matterMeasures of air pollution exposureImpact of air pollution exposureFine particulate matterExposure to PM2.5Air pollution measurementsPersonal exposure measurementsCreation of novel methodologiesSub-acute exposurePolluted urban environmentsImpact of environmental factorsParticulate matterPollution exposureStudy visitsPollution measurementsType II diabetesProspective cohort studyEnvironmental risk factorsAmbient measurementsII diabetesCohort studyUrban environmentScreening visitA Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies
Bhadra D, Daniels M, Kim S, Ghosh M, Mukherjee B. A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies. Biometrics 2012, 68: 361-370. PMID: 22313248, PMCID: PMC3935236, DOI: 10.1111/j.1541-0420.2011.01686.x.Peer-Reviewed Original ResearchConceptsBayesian semiparametric approachSemiparametric approachCase-control studyReversible jump Markov chain Monte Carlo algorithmMarkov chain Monte Carlo algorithmMeasures of cumulative exposureLongitudinal biomarker informationMonte Carlo algorithmClinically meaningful estimatesSmooth functionsCase-control study of prostate cancerWeighted integralsCumulative exposureInfluence functionJoint likelihoodLikelihood formulationExposure historyStudy of prostate cancerDisease risk modelsHierarchical Bayesian frameworkDisease statusBayesian frameworkCase-controlRisk modelCohort study
2011
A Latent Variable Approach to Study Gene–Environment Interactions in the Presence of Multiple Correlated Exposures
Sánchez B, Kang S, Mukherjee B. A Latent Variable Approach to Study Gene–Environment Interactions in the Presence of Multiple Correlated Exposures. Biometrics 2011, 68: 466-476. PMID: 21955029, PMCID: PMC4405908, DOI: 10.1111/j.1541-0420.2011.01677.x.Peer-Reviewed Original ResearchMeSH KeywordsAnalysis of VarianceBiasBiometryBirth WeightCase-Control StudiesComputer SimulationEnvironmental ExposureEpidemiologic FactorsFemaleGene-Environment InteractionHumansInfant, NewbornIronLead PoisoningModels, StatisticalPregnancyPrenatal Exposure Delayed EffectsPrincipal Component AnalysisConceptsGene-environment interactionsGene-environmentEnvironmental epidemiologyCohort studyGene-environment dependenceBurden of multiple testingStudy gene-environment interactionsEnvironmental exposuresExposure dataEarly life exposuresLV frameworkG x E effectsHealth StudyCorrelated exposuresG x EDisease riskLife exposureMultiple testingFunction of environmental exposureE studyGenotype categoriesStudy of lead exposureBirth weightIron metabolism genesAdaptive trade-off