2024
Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention
Golbus J, Shi J, Gupta K, Stevens R, Jeganathan V, Luff E, Boyden T, Mukherjee B, Kohnstamm S, Taralunga V, Kheterpal V, Kheterpal S, Resnicow K, Murphy S, Dempsey W, Klasnja P, Nallamothu B. Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention. Circulation Cardiovascular Quality And Outcomes 2024, 17: e010731. PMID: 38887953, PMCID: PMC11251861, DOI: 10.1161/circoutcomes.123.010731.Peer-Reviewed Original ResearchIncreased step countsCardiac rehabilitationPhysical activityMicro-randomized trialStep countsText messagesLow-level physical activityEffects of text messagingPromote physical activityPhysical activity levelsTailored text messagesIncreased physical activityJust-in-time adaptive interventionsCardiovascular diseaseSignificant 6% increaseEstimate causal effectsActivity levelsRehabilitationPrimary outcomeApple WatchContextual factorsAdaptive interventionsParticipantsCausal effectsLong-term effects
2019
Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction?
Wang X, Mukherjee B, Park S. Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction? Journal Of The American Heart Association 2019, 8: e013571. PMID: 31631727, PMCID: PMC6898859, DOI: 10.1161/jaha.119.013571.Peer-Reviewed Original ResearchConceptsCardiovascular diseaseNational Health and Nutrition Examination SurveyHealth and Nutrition Examination SurveyRisk factorsStudy sampleCardiovascular disease risk factorsCardiovascular disease mortalityCardiovascular disease risk assessmentImprove CVD risk predictionC-statisticNutrition Examination SurveyCardiovascular mortality predictionCVD risk predictionCox modelBlood markersExamination SurveyPrecision healthRisk scorePairwise interaction termsBlood metalsIntegrated discrimination improvementRisk predictionReclassification improvementMortality predictionInteraction terms
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
2013
The effect of acute exposure to coarse particulate matter air pollution in a rural location on circulating endothelial progenitor cells: results from a randomized controlled study
Brook R, Bard R, Kaplan M, Yalavarthi S, Morishita M, Dvonch J, Wang L, Yang H, Spino C, Mukherjee B, Oral E, Sun Q, Brook J, Harkema J, Rajagopalan S. The effect of acute exposure to coarse particulate matter air pollution in a rural location on circulating endothelial progenitor cells: results from a randomized controlled study. Inhalation Toxicology 2013, 25: 587-592. PMID: 23919441, PMCID: PMC4364610, DOI: 10.3109/08958378.2013.814733.Peer-Reviewed Original ResearchConceptsCirculating endothelial progenitor cellsRural locationsVascular endothelial growth factorEndothelial progenitor cellsCirculating EPC levelsCoarse PMWhite blood cellsParticulate matterConcentrated ambient particlesParticulate matter air pollutionAir pollutionFine particulate matterEPC levelsProgenitor cellsWilcoxon signed-rank testRandomized double-blind crossover studyDouble-blind crossover studyFiltered airSigned-rank testBlood cellsPeripheral venous bloodSympathetic nervous system activityEndothelial growth factorAssociated with alterationsCardiovascular disease
2010
HFE H63D Polymorphism as a Modifier of the Effect of Cumulative Lead Exposure on Pulse Pressure: The Normative Aging Study
Zhang A, Park S, Wright R, Weisskopf M, Mukherjee B, Nie H, Sparrow D, Hu H. HFE H63D Polymorphism as a Modifier of the Effect of Cumulative Lead Exposure on Pulse Pressure: The Normative Aging Study. Environmental Health Perspectives 2010, 118: 1261-1266. PMID: 20478760, PMCID: PMC2944087, DOI: 10.1289/ehp.1002251.Peer-Reviewed Original ResearchConceptsCumulative lead exposureHFE H63D polymorphismC282Y variantBone lead levelsAssociated with steeper increasesLinear mixed-effects regression modelsFamily history of hypertensionMixed-effects regression modelsDaily intake of calciumNormative Aging StudyPredictor of cardiovascular diseaseWaist circumferenceIntake of calciumHistory of hypertensionLead exposureH63D polymorphismAlcohol intakeRandom interceptFamily historyMarker of arterial stiffnessTotal caloriesAging StudySteeper increasesLead levelsCardiovascular disease