A Fay-Herriot Model for Estimating Subjective Cognitive Decline among Military Veterans

Although studies have examined the geographic distribution of dementia among the general population in order to develop geographically targeted interventions, no studies have examined the geographic distribution of subjective cognitive decline (SCD) among military veterans specifically.

To map the geographic distribution of subjective cognitive decline from 2011-2019 in the United States among military veterans.

Cross-sectional.

United States.

Individuals reporting previous service in the United States Armed Forces.

Using 2011 Behavioral Risk Factor Surveillance System (BRFSS) data, which is last year for which geocoded SCD data is publicly available, we estimated the survey-weighted county-level prevalence of veteran SCD for counties with >30 veterans (43 counties in 7 states). We then developed a Fay-Herriot small area estimation linear model using auxiliary data from the Census, with county-level veteran-specific covariates including % >65 years old, % female, % college educated, and median income. Following model validation, we created beta-weighted predictions of veteran SCD for all USA counties for 2011-2019 using relevant time-specific Census auxiliary data. We provide choropleth maps of our predictions.

Results of our model on 43 counties showed that county-level rates of SCD were significantly associated with all auxiliary variables except annual income (F = 1.49, df = 4, 38). Direct survey-weighted rates were correlated with model-predicted rates in 43 counties (Pearson r = 0.32). Regarding predicted rates for the entire USA, the average county-level prevalence rate of veteran SCD in 2011 was 13.83% (SD = 7.35), but 29.13% in 2019 (SD = 14.71) - although variation in these rates were evident across counties.

SCD has increased since 2011 among veterans. Veterans Affairs hospitals should implement plans that include cognitive assessments, referral to resources, and monitoring patient progress, especially in rural areas.