grant

ACL-LIFE Life History Interview and Validation

Organization UNIVERSITY OF MICHIGAN AT ANN ARBORLocation ANN ARBOR, UNITED STATESPosted 15 Jan 2020Deadline 30 Nov 2026
NIHUS FederalResearch GrantFY202421+ years oldAddressAdultAdult HumanAgeAgingAmericanBehaviorBirthCalendarCare GiversCaregiversCharacteristicsChild RearingCirculatory CollapseCodeCoding SystemCohort StudiesCollectionCommunitiesComplexConcurrent StudiesDataDedicationsDimensionsDisparitiesDisparityDisparity populationEducationEducational aspectsEmploymentEnvironmentEnvironmental ExposureEthnic OriginEthnicityEuropeEventEvolutionFosteringFundingGenderGoalsHealthHealth Care UtilizationHealth SciencesHealth SurveysHealth and Retirement StudyHistoryIndividualInequalityInterviewInvestigatorsJobsLifeLife CycleLife Cycle StagesLife ExpectancyLongitudinal StudiesMeasurementMeasuresMediationMethodologyMorbidityMorbidity - disease rateNCMHDNIMHDNational Center on Minority Health and Health DisparitiesNational Institute of Minority Health and Health DisparitiesNational Institute on Minority Health and Health DisparitiesNegotiatingNegotiationOccupationsParentingParenting behaviorParentsParturitionPersonsPolicy MakerPrevalenceProcessProfessional PositionsProtocolProtocols documentationPublic Health ServiceRaceRacesRecommendationRecording of previous eventsReportingResearchResearch PersonnelResearch ResourcesResearchersResourcesRespondentRetrospective StudiesRiskRoleSchoolsSeveritiesShapesShockSocial NetworkSocial SciencesSocio-economic statusSocioeconomic StatusSubgroupSurvey InstrumentSurvey MethodSurvey MethodologySurveysSurvivorsTestingTimeTobacco ConsumptionTobacco useUSPHSUnited StatesUnited States Public Health ServiceValidationadulthoodagesaging associatedaging relatedchildrearingcirculatory shockcohortcostcost effectivedata qualitydisadvantaged groupdisadvantaged individualdisadvantaged peopledisadvantaged populationdisadvantaged subgroupdisparities across groupsdisparity across subgroupsdisparity among groupsdisparity among subgroupsdisparity between groupsdisparity between subgroupsdisparity eliminationdisparity in healtheliminate disparitieseliminating disparitiesexpectationexperiencegender disparitygroup disparitygroup inequalitygroup inequityhealth care service usehealth care service utilizationhealth disparityhealthcare service usehealthcare service utilizationhealthcare utilizationhealthy aginghealthy human aginghistoriesimprovedinequalities among populationsinequalities between populationsinequalities in populationsinequality across populationsinequality among groupsinequality between groupsinequality in groupsinequities among populationsinequities between populationsinequities in populationsinequity across groupsinequity across populationsinequity between groupsinequity in groupsinnovateinnovationinnovativeinstrumentintervention designinvestigator traininglate lifelife courselife historylife spanlifespanlong-term studylongitudinal outcome studieslongterm studymid lifemid-lifemiddle agemiddle agedmidlifemulti-racialmultiracialnovelparentpopulation inequalitypopulation inequityprospectivepsychosocialracialracial backgroundracial originshockssocialsocial disadvantagesocial disparitiessocial health determinantssocial inequalitysocial rolesocio-demographic predictorssocio-demographicssocio-economicsocio-economic positionsocio-economicallysociodemographic predictorssociodemographicssocioeconomic positionsocioeconomicallysocioeconomicssubgroup disparitytheoriestherapy designtobacco product usetreatment designunequal groupunequal populationvalidations
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Full Description

To understand the social determinants of health and address persistent disparities in healthy aging, researchers and policymakers have increasingly taken a life course view of social exposures. Conditions of early and midlife are implicated in empirical studies of later life health and health disparities by sex, race and ethnicity, and socioeconomic status. A better understanding of the long-term influences of complex and time-varying health, socioeconomic, psychosocial and environmental exposures is essential for evaluating theories of the life course, cumulative advantage and health disparities, and for designing interventions to foster healthy aging for all. Key methodological advances in the collection of retrospective life history (RLH) data have enabled major ongoing longitudinal studies of aging, including the English Longitudinal Study of Ageing (ELSA), the Survey of Health and Ageing in Europe (SHARE), and the Health and Retirement Study (HRS), to fill in life course gaps quickly and cost-effectively by collecting information using the event history calendar approach.

The data from RLH interviews can be used to generate measures of schooling, relationship, parenting, employment, financial and residential histories; life events like health shocks; presence and quality of social network relationships; and behaviors like tobacco use or health care utilization. However, the reliability of RLH interview data has not been comprehensively evaluated against the survey “gold standard” of prospectively-collected information. The few assessments of RLH data quality have focused on different domains of the life course, but each has revealed evidence of recall error (especially by duration since event and complexity of reporting task) and recall bias (especially by age, sex and sometimes race and education), though findings remain mixed and incomplete. We propose to build on the existing prospective Americans’ Changing Lives (ACL) study, a multi-racial, nationally-representative cohort study that has collected measures from across major life domains and of aging-related morbidities over the adult lifespan.

The ACL-6 wave is currently in the field, and will provide 33 years of exposure measures. We will field a RLH interview similar to the one used by SHARE (ACL-LIFE) and conduct an innovative, integrated set of analyses to more comprehensively examine the prevalence, dimensions, and sociodemographic determinants of mismatch between retrospectively- and prospectively-collected life history information than has been possible to date. We will also explore whether and how reliance on RLH data could influence conclusions about healthy aging or health disparities drawn from analyses using life course exposures as predictors. These novel assessments will inform research on survey methodology and enhance the value of major ongoing longitudinal studies of aging.

They will also provide critical findings for researchers and policy makers reliant on cost-effective and timely information about life course exposures that can be used to improve the lives of all adults, and to eliminate disparities in healthy aging.

Grant Number: 5R01AG065319-05
NIH Institute/Center: NIH

Principal Investigator: Sarah Burgard

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