grant

Susceptibility and adverse health outcomes related to weather-sensitive events among older Medicare beneficiaries with Alzheimer and Dementia

Organization YALE UNIVERSITYLocation NEW HAVEN, UNITED STATESPosted 15 Dec 2022Deadline 30 Nov 2027
NIHUS FederalResearch GrantFY2026AD and related dementiaAD dementiaAD related dementiaAD riskAD risk factorADRDAddressAgeAgingAir PollutantsAir PollutionAlzheimer Type DementiaAlzheimer disease dementiaAlzheimer risk factorAlzheimer sclerosisAlzheimer syndromeAlzheimer'sAlzheimer's DiseaseAlzheimer's Disease and its related dementiasAlzheimer's and related dementiasAlzheimer's dementia and related dementiaAlzheimer's dementia or related dementiaAlzheimer's disease and related dementiaAlzheimer's disease and related disordersAlzheimer's disease and related forms of dementiaAlzheimer's disease or a related dementiaAlzheimer's disease or a related disorderAlzheimer's disease or related dementiaAlzheimer's disease related dementiaAlzheimer's disease riskAlzheimers DementiaAmentiaAreaBurn injuryBurnsChargeChronicCodeCoding SystemComputer softwareDataDementiaDependenceDevelopmentEcological impactElderlyEmergenciesEmergency SituationEnvironmental ExposureEnvironmental HealthEnvironmental Health ScienceEnvironmental ImpactEventExposure toFutureGoalsHealthHealth Insurance for Aged and Disabled, Title 18Health Insurance for Disabled Title 18Heat WavesHomeHospital AdmissionHospitalizationHospitalsImageryIndividualKnowledgeLinkLiteratureMachine LearningMedicareMethodologyMethodsModelingMonitorNO2Nitrogen DioxideNitrogen PeroxideNursing HomesO3Older PopulationOutcomeOzonePM2.5Patient outcomePatient-Centered OutcomesPatient-Focused OutcomesPersonsPhysiologicPhysiologicalPopulationPredispositionPreparednessPrimary Senile Degenerative DementiaPublic HealthReadinessRecoveryRegulationReportingResearchRisk EstimateScienceSeriesSmokeSoftwareStatistical Data AnalysesStatistical Data AnalysisStatistical Data InterpretationSubgroupSusceptibilitySymptomsTimeTitle 18Vulnerable PopulationsWeatherWildfireWorkWorld Health Organizationadvanced ageagesalzheimer riskbeneficiarybrain healthburnedco-exposuresco-occurring exposurecohortcombined exposurecommunity factorcommunity-level factorcomplex exposureconcurrent exposuredeath riskdesigndesigningdevelopmentaleffective interventionexposure mixtureexposure to environmental agentsexposure to environmental factorsexposure to environmental stimuliexposure to environmental substancesextreme heatextreme temperaturefine particlesfine particulate matterfrailtygeriatrichealth assessmenthealth care managementhealth insurance for disabledhealth managementheatwavehomeshospital re-admissionhospital readmissionland useloved onesmachine based learningmachine learned algorithmmachine learning algorithmmachine learning based algorithmmeteorological datamixed exposuremortalitymortality riskmultimorbiditymultiple chronic conditionsnovelnursing homeolder adultolder adulthoodolder groupsolder individualsolder personpatient oriented outcomesprimary degenerative dementiare-admissionre-hospitalizationreadmissionrehospitalizationresponserisk factor for developing Alzheimer'srisk factor in Alzheimer'srisk of developing Alzheimer'ssenile dementia of the Alzheimer typesenior citizensexsimultaneous exposuresspatial and temporalspatial temporalspatiotemporalstatistical analysisstructural determinantsstructural factorsvulnerable groupvulnerable individualvulnerable peopleweather datawild firewildland fire
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Full Description

The WHO listed air pollution as one of the top ten threats in 2019, and earlier research indicates links between weather exposures and brain health. Further, the burden of older persons with Alzheimer’s disease (AD) and related dementias (ADRD) is expected to double by 2060. Simultaneously, wildfires are a substantial contributor to extremely high levels of air pollution . To date, little is known regarding impacts of heat or air pollution, including wildfire smoke, on the elderly with AD/ADRD.

Most studies on environmental exposures and related vulnerabilities investigated a single factor at a time rather than the real-world settings characterized by multiple factors (co-occurring air pollution and heat, frailty, chronic conditions). Further, previous studies have not leveraged recent developments in satellite imagery, machine learning, and causal inference methods, which can increase the rigor and validity of statistical analysis. We propose to address these scientific gaps using a large, validated cohort of US Medicare beneficiaries (>65y) with AD/ADRD (approx. 10 million for the period 2000-2019) and spatially resolved weather data combined with state-of-the-science machine learning for estimates of air pollution exposure, which leverages satellite imagery, land use data, and monitors. Our long-term goals are to characterize the vulnerability and health impacts of weather-related exposures within a large cohort of older adults with AD/ADRD.

First, we will estimate the impacts of short-term exposure to heat and heatwaves on cause-specific hospital admissions, readmissions, mortality, and a novel patient-centered outcomes of days-at-home, and develop machine learning algorithms to identify which subpopulations with AD/ADRD are most vulnerable with respect to several individual- and community-level factors (e.g., sex, chronic conditions, frailty). Next, we will estimate vulnerability of older persons with AD/ADRD to air pollution including wildfire smoke using our state-of-the-science approach to estimate air pollution and wildfire smoke exposure. We then estimate the impacts and vulnerabilities from co-occurring heat and air pollution (including heat waves and wildfire smoke) by developing Bayesian hierarchical spatio-temporal models to quantify synergistic effects. Finally, we will disseminate all methods, exposure data, and statistical software, making them publicly available free of charge.

Characterizing the factors that increase vulnerability for older persons with AD/ADRD will allow decisionmakers to design effective interventions. Findings will inform impact assessments of the health burden of environmental exposures, specifically heat and air pollution including wildfires, and for understanding environmental health. Our results will have implications for management of health during co-occurring heat and air pollution events, including wildfires, and increase knowledge on weather and air pollution preparedness, response, and recovery.

Grant Number: 4R01AG080948-02
NIH Institute/Center: NIH

Principal Investigator: Michelle Bell

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