Geographic Variation of Prevalence of Alzheimer’s Disease and Related Dementias in Central Appalachia

INTRODUCTION

The burden of Alzheimer’s disease and related dementias (ADRD) is rapidly increasing alongside the growing population of older adults, where ADRD currently impacts an estimated 6.7 million adults aged 65 years and older in the United States (US). 1 However, this burden varies geographically,2–5 possibly reflecting contextual influences, such as sociodemographic and environmental factors.1,6, 1,6 Specifically, known individual-level ADRD risk factors, such as chronic diseases, lifestyle factors, and education, may be influenced by contextual factors that are contributing to the disparate geographic patterning of ADRD prevalence.2,6–8, 2,6–8 Additionally, the availability of health care resources likely influences health care access and, in turn, diagnosed prevalence of ADRD.6,9, 6,9 Adequate health care access is an ongoing concern in Appalachian regions of the US.10,11, 10,11

The prevalence of ADRD varies within US Appalachian regions and likely by rurality. In Ohio, Appalachian counties had a lower prevalence of ADRD compared to non-Appalachian counties from 2007 to 2017, and the burden varied by rural/urban designation. 2 Additionally, rural counties in Kentucky and West Virginia had a lower reported prevalence of ADRD compared to urban counties. 4 These observed differences persisted after accounting for demographics and comorbidities in both regions.2,4, 2,4 While trends in educational attainment have been improving over time in rural areas, the rural/urban education disparity still exists, where both rural and Appalachian regions are characterized by low rates of educational attainment compared to their urban and non-Appalachian counterparts.12,13, 12,13 Additionally, the prevalence of ADRD is likely underestimated in rural and/or Appalachian regions where access to adequate detection resources is limited. 6 Yet, the burden of ADRD has not yet been examined in larger geographic regions to help determine if the differences in prevalence between rural and urban regions can be attributed to disease detection access.

Individual characteristics and contextual characteristics alike can influence the development and/or the detection of ADRD. In regions with less access to diagnostic resources, it follows that there may be an underestimate of ADRD prevalence due to the lack of detection. The Appalachian region has a unique mix of higher levels of ADRD risk factors and limited diagnostic access.6,13, 6,13 Our objective was to assess ADRD prevalence in the Central Appalachian region stratifying by rural/urban status and Appalachian county designation from 2015 to 2018. We hypothesized that after accounting for individual demographics, county-level sociodemographics, and multiple measures of diagnostic access (i.e., numbers of primary care providers (PCPs), neurologists, and image scans) that ADRD prevalence would be higher in Appalachian and rural counties compared to non-Appalachian and urban counties.

MATERIALS AND METHODS

RESULTS

Crude average county-level ADRD prevalence among Medicare FFS beneficiaries ranged from 6.86 to 29.91% in the Central Appalachian region from 2015 to 2018 (Fig. 1). Overall, the county-level average age among the 65 years and older FFS population was 70.4 years (SD = 1.81) and counties had slightly fewer males than females (54% female; Table 1). Rural-Appalachian counties were slightly younger with an average age among the FFS population of 69 years compared to urban-Appalachian (70 years) and rural- and urban-non-Appalachian counties (71 years). Rural-Appalachian counties also had fewer females compared to rural-non-Appalachian and urban-Appalachian/non-Appalachian counties. However, the proportion of Medicaid eligible persons was highest in rural-Appalachian counties (31.2%), followed by urban-Appalachian (23.5%), rural-non-Appalachian (23.0%), and lowest in urban-Appalachian counties (17.5%). The proportions of older adults with diabetes, heart failure, and hypertension were highest among rural counties compared to urban counties. Educational attainment and renter-occupied housing was lowest among rural-Appalachian counties, followed by rural-non-Appalachian, urban-Appalachian, and highest among urban-non-Appalachian counties. Appalachian counties had lower proportions of Black and Hispanic older adults and a lower average life expectancy than that among non-Appalachian counties. The average number of yearly PCP visits, neurology visits, and imaging scans were highest among urban-non-Appalachian counties, followed by urban-Appalachian, rural-non-Appalachian, and rural-Appalachian counties.

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Fig. 1

County-level distribution of mean ADRD prevalence from 2015 to 2018 in the Central Appalachian region of the US.

Overall, small variation in ADRD prevalence between Appalachian (12.0%; 95% CI: 11.9%, 12.1%) and non-Appalachian (11.6%; 95% CI: 11.5%, 11.7%) counties was observed, where ADRD prevalence in Appalachian counties was 3% higher than ADRD prevalence in non-Appalachian counties before adjustment (95% confidence interval (CI): 1.02, 1.04; Table 2). Adjustment for demographic characteristics of the Medicare population in Model 2 attenuated this variation in ADRD prevalence overall (Prevalence ratio (PR): 1.00; 95% CI: 0.99, 1.01). However, adjustment for sociodemographic characteristics and housing tenure (PR: 1.02; 95% CI: 1.01, 1.03) and then diagnostic resources (PR: 1.02; 95% CI: 1.01, 1.03) reintroduced a marginal disparity. These associations were similar within rural and urban counties, however, the attenuation in the Appalachian/non-Appalachian disparity observed following demographic adjustment in Model 2 was only apparent in urban counties (PR: 0.99; 95% CI: 0.98, 1.00) relative to rural counties (PR: 1.02; 95% CI: 1.01, 1.04). Additionally, with each level of successive covariate adjustment, the estimated number of excess cases of ADRD per Appalachian county gets smaller. This is true on the population level as well; the excess number of expected cases overall would still see 3531 (95% CI: 1619, 5443) additional ADRD cases in Appalachian counties within Central Appalachia even after accounting for sociodemographic and access-related factors.

The geographic variations in ADRD prevalence observed overall and by rural and urban county designation differed by state in the fully adjusted model (p-value of 3-way interaction between Appalachian, rural/urban, and state designation: 0.004; Table 3). Kentucky (PR: 1.06; 95% CI: 1.02, 1.10), Tennessee (PR: 1.08; 95% CI: 1.05, 1.11), and Virginia (PR: 1.05; 95% CI: 1.01, 1.10; Table 3) drove the Appalachian/non-Appalachian disparities in ADRD prevalence in rural counties. Subsequently, Appalachian/non-Appalachian variation in ADRD prevalence in urban counties was driven by North Carolina (PR: 1.05; 95% CI: 1.01, 1.08) and Tennessee (PR: 1.05; 95% CI: 1.03, 1.07). West Virginia is completely Appalachian, so within state comparisons were not estimable.

DISCUSSION

In this ecologic study of the Central Appalachian region, we hypothesized that geographic variation in county-level ADRD prevalence would markedly differ between Appalachian and rural counties, however the data did not support this hypothesis. ADRD prevalence did vary slightly on the relative scale, but these differences between Appalachian and non-Appalachian counties were only of the magnitude of 2– 3%. While these associations were consistent with previous findings from Ohio only, 2 we hypothesized that the magnitude would have increased by accounting for differences in diagnostic access between counties in this region. Several potential reasons may account for these findings: the case mixture of the dual eligible population or MA populations in the region, the accuracy of measurement of the outcome, and the impact of educational attainment in the region.

Our analysis focused on the prevalence of ADRD among all FFS Medicare enrollees. However, the distribution of FFS compared to MA plans could contribute to the measurement of ADRD if there were systematic demographic differences between FFS and MA, and if this varied by area, we could be under- or overestimating the prevalence. Overall, there is small variation in the proportion of FFS Part A and B beneficiaries ever enrolled in MA across county types. A recent study comparing demographics and measures of health care access, use, and affordability among low-income MA and FFS beneficiaries did not find variation in access between enrollees of MA compared to FFS; low-income adults with MA were less likely to be from rural areas than low income adults with FFS. 28 Studies comparing key metrics of MA and FFS beneficiaries demonstrate more preventive care visits among MA than FFS. The lack of variation is likely not attributed to selection bias, as it seems FFS beneficiaries may be more prone to underdiagnosis. 29 Additionally, there is a varying proportion of persons in the population that are dual-eligible, where they have FFS Medicare, but are also Medicaid eligible. There was a higher proportion of Medicaid eligible persons in Rural-Appalachian counties (31.24%) than among all other county types, where the lowest proportion of Medicaid eligible persons is among urban non-Appalachian counties (17.52%) (Table 1). However, we accounted for Medicaid eligibility in our models and while it was individually associated with higher ADRD prevalence, its inclusion did not change the overall findings.

The use of administrative claims data is imperfect for measuring or capturing disease cases. Identifying a patient with ADRD in CMS uses the CCW case definition of over a three-year period, there must be at least 1 inpatient, skilled nursing facility, home health agency, hospital outpatient or Carrier claim with a valid ICD-9/10 code for an enrollee to be identified as having ADRD. 24 The CMS/CCW definition identifies 75– 80% of cases, but that means that there are 25% of cases that are potentially missed. 25 Zhu et al. reported that milder ADRD cases are often missed in claims data. 30 Additionally, claims algorithms underestimated ADRD among rural cases and cases with lower educational attainment, 31 indicating that misclassification may be differential by region type (e.g., lower sensitivity in Appalachian and rural counties). If only the more severe cases being detected among rural/Appalachian areas in claims data, such that PR is underestimated partially because shorter time to death among cases in rural areas (i.e., differences should be larger than observed).5,32, 5,32

In our analysis, we selected factors that are largely negative influences on cognition and ADRD, however, there are protective factors that may delay the onset of cognitive decline or prevent ADRD such as educational attainment and socialization. Educational attainment has grown in the US. Nearly 90% of adults 25 and older were high school graduates in 2017 compared to 82% in 1997, with bachelor’s degree attainment increasing from 16% to 21.3% in that same time period. 33 It has been thought that educational attainment influences cognitive reserve, and that education may be a mechanism to preserve cognition or slow cognitive decline.34–36 Living in a rural community can influence the rate of cognitive decline. 32 Yet even when considering the changes in educational distribution, rural-urban differences persist in dementia. 3 Bachelor’s education has been growing in the Appalachian region, but not as fast as in the non-Appalachian regions of the same areas.37,38, 37,38 The US on average went up 3.3%, but Central Appalachia only increased 1.5% comparing 2012– 2016 to 2017– 2021. Additionally, education is related to health care access, as those with higher education may be best able to navigate through a dementia diagnosis. 39 The lag in education and the discrepancy in access means that differences in cognitive reserve would be more pronounced, so we would have anticipated more differences for ADRD rather than having the groups be more similar. Relatedly, socialization may also contribute to lower ADRD prevalence in rural and/or Appalachian regions. The tight-knit nature of rural communities have been found to be more socially cohesive than their urban counterparts, 40 which aligns with evidence supporting high frequencies of social interactions often reported among older rural compared to older urban residents. 41 With a known positive link between social engagement and cognition among older adults, higher levels of social cohesion that in turn positively influence social participation among rural residents may contribute to lower ADRD prevalence in rural areas. 42 Yet our analysis may have also been limited by the absence of other factors, such as air quality or built environment infrastructure, that could have had positive or negative influences on county-level ADRD prevalence. Future work should continue to explore the influence of protective health factors of the rural and Appalachian regions on ADRD prevalence.

PCP and neurologists are instrumental providers for the screening, detection, and diagnosis of dementia. While PCP availability is known to be limited in remote areas, 43 recent growth in the number of nurse practitioners (NPs) and Physician Assistants (PAs) poses opportunities for additional access to screening and initial diagnosis of dementia in underserved areas.44,45, 44,45 Telehealth is also emerging as a strategy for dementia detection in Appalachian or rural areas, however, differential availability of telehealth services by rurality and Appalachian designation still exists. 46 Higher rates of neurological disorders in Appalachian regions exist due to the poor sociodemographic makeup of these areas compared to their non-Appalachian counterparts. This variation in the burden of neurological disorders is increasing and, alternatively, supports a rising demand for specialty care in Appalachian areas over time. 47 The disparate need for neurologists exists even with consideration of rurality and area deprivation, where Appalachian census tracts were recently found to have between 25% and 35% lower spatial access to neurologists compared to non-Appalachian census tracts.46,48,49, 46,48,49 We observed that having more neurologists was associated with higher prevalence similar to Lin et al., yet while supply of neurologists differs by geography, variation in demand is small and, for dementia specifically, use of specialist care rises with increasing supply of neurologists. 50 The vast majority of evidence that points to the declining availability of dementia support services and care providers rather demonstrates a rising need for additional diagnostic care access in Appalachian areas. The minimal relative variation in ADRD prevalence observed by Appalachian County designation may be indicative of that there is some other care-related factor that operates differentially for Appalachian areas such that the measurement of ADRD is offset to look equal to that in more resourced areas.

The magnitude of the overall differences in ADRD prevalence by Appalachian designation were smaller than originally hypothesized, however, some states demonstrated more pronounced variation than others. Overall variation in Appalachian compared to non-Appalachian counties existed in Kentucky, North Carolina, and Tennessee, where the difference was most pronounced in Tennessee. However, only Virginia showed variation by rurality as a driver of the Appalachian/non-Appalachian difference in rural but not urban counties. Our previous work demonstrated slightly lower ADRD prevalence among FFS beneficiaries in Appalachian compared to non-Appalachian counties from 2007 to 2017 in Ohio alone, where rural Appalachian counties had slightly higher ADRD prevalence and urban Appalachian counties had slightly lower prevalence than their non-Appalachian county counterparts from 2012 to 2017. 2 Conversely, we did not observe variation in ADRD prevalence by Appalachian designation overall or by rurality from 2015 to 2018 in Ohio specifically, even after accounting for differences in sociodemographics and diagnostic access. Our prior work motivated the current study’s evaluation of variation in ADRD prevalence across multiple Appalachian states likely characterized by poorer access to care than Ohio. For example, the lower ADRD prevalence observed in rural counties of Kentucky and West Virginia compared to urban counties in 2013 was hypothesized to be due to lack of diagnostic access corresponding with the disproportionate underdiagnosis of ADRD in rural areas. 4 However, we observed a higher ADRD prevalence in rural Appalachian counties of Kentucky compared to all other counties in the state across each level of adjustment, including PCP and neurologist counts. Our results may be reflecting recent increases in the burden of ADRD that disproportionately influences rural areas with large aging populations. The largely rural state’s sociodemographic and comorbid makeup may contribute to Tennessee being a main driver of the Appalachian/non-Appalachian variation in ADRD prevalence, 51 however, within state differences should be further explored.

Appalachian counties in Central Appalachia had relatively higher ADRD prevalence compared to non-Appalachian counties, but these differences may yet be understated. While accounting for socio-demographic and diagnostic access factors did not completely account for the relative difference, we hypothesize that the ascertainment of our outcome may be differentially misclassified which may mask the true magnitude of an Appalachian/non-Appalachian ADRD disparity. Future work should further evaluate if state level variation is a more appropriate scale than the entire Central Appalachian region.

AUTHOR CONTRIBUTIONS

Jeffrey J. Wing (Conceptualization; Funding acquisition; Methodology; Project administration; Supervision; Writing – original draft); Jenna I. Rajczyk (Data curation; Formal analysis; Writing – original draft); James F. Burke (Methodology; Supervision; Writing – review & editing).