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Updated: Jun 7, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Social determinants of health and mild cognitive impairment in a diverse community sample
Mary Ganguli1,2,3, Erin Jacobsen1, Ruopu Song1
1Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Background:
The associations between community-wide social determinants of health and mild cognitive impairment (MCI) among individuals warrant investigation.
Methods:
Among 2830 dementia-free individuals aged 65+ years in a community-based US study, we examined cross-sectional associations of MCI (Clinical Dementia Rating = 0.5) with the following potential social determinants of health: at the census tract or block group level obtained from public sources: neighborhood disadvantage (Area Deprivation Index, ADI), air pollution with fine particulate matter (PM2.5), greenspace, Walkability Index, ambulatory healthcare availability per square mile, homicide rate; and at the individual participant level, birth/schooling in a southern US state.
Results:
Unadjusted logistic regression models found higher odds ratios (OR, 95% CI) for MCI with higher ADI (1.01, 1.003-1.02), higher PM2.5 (1.16, 1.07-1.26), higher homicide rate (1.007, 1.001-1.012), lesser greenspace (0.99, 0.90-0.99), and southern schooling (2.06, 1.6-3.54). Adjusting for age, race, sex, and educational level, ADI remained statistically significant (1.04, 1.01-1.06), while PM2.5 and Southern state schooling interacted significantly with race and were more strongly affected in Black participants than in White participants.
Conclusions:
In this cohort, several community-wide social/environmental factors were associated with MCI. While clinicians should continue to encourage older adults to modify their individual risk factors, policy changes are needed to mitigate social determinants of health in the community.
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