ArticleJournal of Alzheimer's disease : JAD2025
How much can biomarkers explain sociodemographic inequalities in cognitive dysfunction and cognitive impairment? Results from a machine learning model in the Health and Retirement Study.
Article in Journal of Alzheimer's disease : JAD, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Biomarkers help us understand how cellular and systemic aging contribute to mortality: a study utilizing a machine-learning approach in the Health and Retirement Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Screening mild cognitive impairment using aspects of personal, social, and functional lifestyle: Machine Learning Approaches.PloS one · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
BackgroundBiomarkers may be pathways by which social adversity affects cognitive aging and Alzheimer's disease and related dementias (ADRD) risk.ObjectiveHow much variance in cognitive dysfunction and cognitive impairment onset do blood-based and physiological biomarkers provide above and beyond easily attainable sociodemographic variables, and how much can biomarkers explain differences in cognitive functioning and ADRD by sociodemographic variables?MethodsWe utilize machine learning to generate measures of predicted cognitive dysfunction and cognitive impairment incidence based on 91 biomarkers, identify the relative importance of each biomarker, and examine how much these biomarkers mediate sociodemographic differences.ResultsMarkers related to cellular aging, neurodegeneration, diet and nutrition, immune functioning, and lung function were identified as important. Biomarkers mediated 47.2-77.3% of the variance associated with age, 22.7-35.2% of racial/ethnic differences in cognitive dysfunction, and 12.5-17.6% of educational differences.ConclusionsBiomarkers provide the potential to understand pathways linking sociodemographic characteristics to cognitive functioning and health. Future research should consider additional biomarkers and evaluate the specific systems that put people at risk for cognitive impairment.
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