Regional variability of the impact of cardiometabolic diseases on incident dementia in United States Medicare beneficiaries

George K. Karway, Brittany Krzyzanowski, Jordan A. Killion, Irene M. Faust, Osvaldo J. Laurido-Soto, Marwan N. Sabbagh, Brad A. Racette

Research output: Contribution to journalArticlepeer-review

Abstract

INTRODUCTION: Understanding the impact of cardiometabolic diseases (CMDs) on dementia risk can inform primary preventative measures. METHODS: We leveraged a nationwide, population-based Medicare dataset of 20,789,037 beneficiaries (756,321 with incident dementia and 20,032,716 controls) from 2017 to compute the individual and combined population attributable fractions (PAFs) of dementia attributed to eight CMDs, adjusted for age, sex, and race. We mapped PAFs at the county level to investigate the geospatial patterns of CMD burden on dementia across the United States. RESULTS: The nationwide combined weighted PAF for the eight CMDs was 37% overall, with hypertension (9.6%), ischemic heart disease (6.7%), and chronic heart failure (5.7%) associated with the greatest attributable fractions of dementia cases. The greatest fraction of county-level dementia cases attributed to CMDs were in the Southeastern United States. DISCUSSION: A substantial proportion of incident dementia cases in the United States can be attributed to CMDs, especially in the Southeastern United States. Highlights: Investigated the combined effect of cardiometabolic diseases (CMDs) on dementia. Used novel geospatial techniques to map the burden of dementia attributed to CMDs. If eight CMDs are mitigated, 37% of incident dementia cases could be eliminated. Identified regions of the United States with high CMD burden on dementia.

Original languageEnglish
Article numbere70199
JournalAlzheimer's and Dementia
Volume21
Issue number5
DOIs
StatePublished - May 2025

Keywords

  • Alzheimer's disease
  • cardiometabolic diseases
  • dementia
  • geographic information systems
  • geospatial analysis
  • population attributable risk
  • potential impact fraction
  • risk factor analysis

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