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Race, community disadvantage, and cognitive decline: Findings from KHANDLE and STAR

  • Rachel L. Peterson
  • , Rebecca Pejak
  • , Kristen M. George
  • , Paola Gilsanz
  • , Michelle Ko
  • , Oanh L. Meyer
  • , Elizabeth Rose Mayeda
  • , Amy Kind
  • , Rachel A. Whitmer
  • University of Montana
  • University of California at Davis
  • Kaiser Permanente
  • University of California at Los Angeles
  • University of Wisconsin-Madison

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

INTRODUCTION: Community disadvantage is associated with late-life cognition. Few studies examine its contribution to racial disparities in cognition/cognitive change. METHODS: Inverse probability weighted models estimated expected mean differences in cognition/cognitive change attributed to residing in less advantaged communities, defined as cohort top quintile of Area Deprivation Indices (ADI): childhood 66–100; adulthood ADI 5-99). Interactions by race tested. RESULTS: More Black participants resided in less advantaged communities. Semantic memory would be lower if all participants had resided in less advantaged childhood (b = -0.16, 95% confidence interval [CI] = -0.30, -0.03) or adulthood (b = -0.14, 95% CI = -0.22, -0.04) communities. Race interactions indicated that, among Black participants, less advantaged childhood communities were associated with higher verbal episodic memory (interaction p-value = 0.007) and less advantaged adulthood communities were associated with lower semantic memory (interaction p-value = 0.002). DISCUSSION: Examining racial differences in levels of community advantage and late-life cognitive decline is a critical step toward unpacking community effects on cognitive disparities.

Original languageEnglish
Pages (from-to)904-913
Number of pages10
JournalAlzheimer's and Dementia
Volume20
Issue number2
Early online dateOct 10 2023
DOIs
StatePublished - 2023

Funding

The authors appreciate the detailed work provided by Kevin Zhou, KPNC Data Analyst, in geocoding the multiple historical addresses of STAR and KHANDLE cohort participants used in this analysis. Dr Peterson and Ms Pejak are supported by NIH/NIA 4R00AG073457‐02. Dr George is supported by NIH/NIA R01AG052132, R01AG056519, and RF1AG050782 and California Department of Public Health RFA 20‐10079. Dr Gilsanz is supported by NIH/NIA R01AG052132. Dr Ko is supported by NIH/NIA R01AG067525‐03. Dr Mayeda is supported by NIH/NIA R01AG052132 and R01AG074359. Dr Kind is supported by NIH/NIA RF1AG057784; R01AG070883 and 1R01MD010243. Dr Whitmer is supported by NIH/NIA R01AG052132 and 7RF1AG050782‐02. The authors appreciate the detailed work provided by Kevin Zhou, KPNC Data Analyst, in geocoding the multiple historical addresses of STAR and KHANDLE cohort participants used in this analysis. Dr Peterson and Ms Pejak are supported by NIH/NIA 4R00AG073457-02. Dr George is supported by NIH/NIA R01AG052132, R01AG056519, and RF1AG050782 and California Department of Public Health RFA 20-10079. Dr Gilsanz is supported by NIH/NIA R01AG052132. Dr Ko is supported by NIH/NIA R01AG067525-03. Dr Mayeda is supported by NIH/NIA R01AG052132 and R01AG074359. Dr Kind is supported by NIH/NIA RF1AG057784; R01AG070883 and 1R01MD010243. Dr Whitmer is supported by NIH/NIA R01AG052132 and 7RF1AG050782-02. Rachel L. Peterson, Funding: NIH/NIA 4R00AG073457-02 (PI: Peterson). Rebecca Pejak, Funding: NIH/NIA 4R00AG073457-02 (PI: Peterson). Kristen M. George, Funding: NIH/NIA R01AG052132 (Whitmer, Glymour, Gilsanz, Mayeda); R01AG056519 (Whitmer, Gilsanz, Corrada); RF1AG050782 (Whitmer); California Department of Public Health RFA 20-10079 (Nosheny, Mayeda, George). Paola Gilsanz, Funding: NIH/NIA R01AG052132 (PI: Whitmer, Gilsanz, Glymour, Mayeda). Michelle Ko, Funding: NIH/NIA R01AG067525-03 (PI: Ko). Oanh L. Meyer, Funding: NIH/NIA R01AG067541 (PI: Meyer). Elizabeth Rose Mayeda, Funding: NIH/NIA R01AG052132 (PI: Whitmer, Gilsanz, Glymour, Mayeda), R01AG074359 (PI: Casey, Mayeda). Amy Kind, Funding: NIH/NIA RF1AG057784 (Kind, Bendlin); 1R01MD010243 (PI: Kind); R01AG070883 (Kind, Bendlin). Rachel A. Whitmer, Funding: NIH/NIA R01AG052132 (PI: Whitmer, Gilsanz, Glymour, Mayeda); 7RF1AG050782-02 (PI: Whitmer).

Funder number
R01AG056519, RF1AG050782, R01AG052132, 4R00AG073457-02
RF1AG057784, RFA 20‐10079, R01AG067525‐03, R01AG074359, 1R01MD010243, 7RF1AG050782‐02, R01AG070883

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • health disparities
    • social determinants
    • social epidemiology
    • structural racism

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