https://orcid.org/0000-0003-1848-1386
Federal policies and programs are typically written with place-neutral intent or without considering how they might affect places differently depending on population compositions or geographic contexts. On average, rural areas are older, sicker, and poorer and have weaker health care infrastructures than urban areas (Jensen et al., 2020). Therefore, we should anticipate that place-neutral policies would impact health and aging differently in rural versus urban areas. Moreover, rural America is not homogenous, but demographically and economically diverse, with a variety of labor markets and social and health service contexts (Leider et al., 2020). Therefore, place-neutral policies will also have differential impacts across the enormous diversity of rural communities.
We discuss three large, national policies/programs as exemplars of how policies differentially affect population health and aging in rural versus urban populations: the Older Americans Act, the Affordable Care Act, and the Supplemental Nutrition Assistance Program. We also discuss implications for policymakers and identify promising areas for research on the spatially disparate impacts of policies on population health and aging.
Older Americans Act
The Older Americans Act (OAA) is a federal program that provides services and protections to older adults (age 60+ years), including funding services to help older adults live as independently as possible (Colello & Napili, 2020). Through OAA Title III grants, older adults access home- and community-based services (HCBS; Colello & Napili, 2020; Ujvari et al., 2019). Area Agencies on Aging (AAA), which are responsible for local administration of OAA services, have substantial autonomy in program delivery, but are required to target services to older adults with the greatest economic and social needs, including rural older adults (Older Americans Act, 2020). In 2018, 10.8 million older adults were served by OAA’s Title III programs (Administration for Community Living, n.d.).
Of the AAA service areas, 41% are considered predominantly rural and 39% are considered partially rural (National Association of Area Agencies on Aging, 2018). However, the program has different impacts in rural versus urban areas. For example, costs may be higher for rural AAAs providing services over large geographic areas (National Association of Area Agencies on Aging, 2018). Limited infrastructure (e.g., poorly maintained roads, few transportation options, low-quality housing, and technology limitations) and widely dispersed populations present challenges for delivering OAA services in rural areas (Government Accountability Office, 2019). For example, limited rural technology infrastructure, such as broadband Internet and cell phone service, create challenges for client outreach and programming (Government Accountability Office, 2019). The shrinking population of working-age adults also limits availability of social service professionals, volunteers, and family members to support the rural aging population (Super, 2020).
Disparities in AAA resources often translate into unequal service availability. Rural AAAs are less likely to provide vital services like adult day care, care transition services, money management counseling, and integrated care (Mabli et al., 2015; National Association of Area Agencies on Aging, 2018). Even when AAAs offer such services, rural residents may face long waitlists (Lewin Group, 2016) or learn that certain services (e.g., home-delivered meals) are unavailable in rural parts of a service area (Mabli et al., 2015). Limited HCBS access may result in increased nursing home placement, with negative consequences for rural older adults’ health and quality of life (Davis, 2018). Reducing avoidable nursing home placements is desirable both because of potential Medicaid savings and because nursing home quality is poorer in rural areas (Bowblis et al., 2013). Finally, rural older adults are about twice as likely as their urban counterparts to use Title III HCBS services (authors’ calculations; U.S. Census Bureau, 2018; National Aging Program Information Systems, 2018). This may reflect a greater need for HCBS in rural areas due to higher rates of poverty and multiple chronic conditions (Schroeder, 2018), as well as more limited family support (Super, 2020).
We encourage federal agencies to fund research on differential access to OAA services across places and demographic groups, and on the impacts of these services on social, economic, and health outcomes for rural older adults, including identifying the impacts on medical and long-term care costs and the remaining unmet needs in rural areas. Such investments will inform future evidence-based policy and program recommendations. Finally, AAA have rapidly adapted services due to increased demand during the coronavirus disease 2019 (COVID-19) pandemic (National Association of Area Agencies on Aging, 2020). Whether OAA services are equitably reaching diverse populations during the pandemic is a critical area for research.
Affordable Care Act
The Patient Protection and Affordable Care Act (ACA) sought to improve access to health care and outcomes while controlling rising health-care costs. However, the degree to which those goals were achieved varies geographically, with long-term implications for geographic disparities in health and aging. Here, we describe the geographically differential impacts of the ACA’s Medicaid Expansion and Accountable Care Organizations (ACOs) components and their implications for rural health and aging.
Medicaid Expansion
Beginning in 2014, Medicaid expansion increased access to health insurance by establishing consistent eligibility thresholds across states. Before expansion, many states excluded childless adults, and income eligibility standards varied drastically. Under expansion, all adults ages 18–64 years with incomes at or below 138% of the federal poverty line qualify for Medicaid, regardless of whether they have children. By August 2020, 12 states had not expanded Medicaid. The count of 12 states that had not expanded Medicaid as of August 2020 excludes Nebraska, Oklahoma, and Missouri, which adopted but have not yet implemented Medicaid Expansion. These states exclude childless adults and have income thresholds as low as 18% of the federal poverty line (Alabama). Consequently, coverage rates have increased significantly more in states that expanded Medicaid (Rhubart, 2017).
Rural adults disproportionately live in states that did not expand Medicaid (Figure 1). Prior to the ACA (i.e., 2013), average nonmetropolitan (nonmetro) county-level insurance rates were lower than those in metropolitan (metro) counties, both in states that eventually expanded Medicaid and those that did not (Figure 2). As a result, nonmetro counties benefited more than metro counties, but only in states that expanded.
The distribution of adults aged 18–64 years by Medicaid expansion status. Data source: U.S. Census Bureau (2010) Decennial census. Metro: rural–urban continuum codes (RUCC) 1–3; nonmetro: RUCCs 4–9; completely rural: RUCCs 8 and 9 (Economic Research Service, 2013).
County-level insurance coverage rates for adults aged 18–64 years, by year, expansion status, and rural–urban continuum code (RUCC). Data sources: U.S. Census Bureau small area health insurance estimates 2013 and 2018 (U.S. Census Bureau, 2020) and American community survey 5-year estimates (U.S. Census Bureau, 2018). N = 3141 counties. Error bars represent 95% confidence intervals for the percent insured in 2018. Data are from 2013 (pre-ACA) and 2018 (most recent year available). Therefore, 2018 expansion statuses were used to classify states. RUCCs: 1 = counties in metro areas of 1 million population or more; 2 = counties in metro areas of 250,000 to 1 million population; 3 = counties in metro areas of <250,000 population; 4 = nonmetro with urban population of 20,000+, adjacent to a metro area; 5 = nonmetro with urban population of 20,000+, not adjacent to a metro area; 6 = nonmetro with urban population of 2,500 to 19,999, adjacent to a metro area; 7 = nonmetro with urban population of 2,500 to 19,999, not adjacent to a metro area; 8 = completely rural or <2,500 urban population, adjacent to a metro area; and 9 = completely rural or <2,500 urban population, not adjacent to a metro area.
Among expansion states, the average insured rates increased from 80.3% to 89.9% among nonmetro counties and from 83.1% to 91.5% among metro counties between 2013 and 2018. Although coverage rates also increased some in non-expansion states, increases were smaller and rates remained lower, and there was no significant difference in rate increases between metro and nonmetro counties.
Figure 2 also shows that across all rural–urban continuum codes (RUCCs; Economic Research Service, 2013), the average insured rates started out higher and increased more in expansion versus nonexpansion states. In expansion states, the average rate increased 7.6 percentage points in large metro counties and 11.0 percentage points in remote rural counties, halving the coverage gap between large metro and remote rural counties. The better nonmetro improvement is largely because rural counties had more room for improvement. Among counties in nonexpansion states, coverage rate increases were smaller but were consistent across RUCCs.
Medicaid is a vital resource for working-age adults but, because some states did not expand, many rural residents have been left behind. Lack of health insurance during working-age years has implications for population health and aging. Failure to expand Medicaid means that working-age residents in nonexpansion states have less access to preventive, chronic, and acute care, potentially resulting in higher risks of disability, chronic health conditions, and premature mortality as they move into older adulthood.
There are also broader implications for rural economies. Medicaid is a major source of revenue for many hospitals (Beatty et al., 2020). Not only did the risk of hospital closure decrease in Medicaid expansion states, but rural areas experienced larger financial improvements than urban areas in expansion states (Lindrooth et al., 2018). Not expanding Medicaid puts vital health infrastructure at risk, compounding the rural health disadvantage. Therefore, we recommend immediate expansion for those states that have still not expanded. We strongly discourage the use of Section 1115 waivers to implement work requirements, as this will disadvantage rural areas that are faced with persistently limited, seasonal, part-time, and precarious employment opportunities (McLaughlin & Coleman-Jensen, 2008). Finally, we recommend research on the differential impacts of Medicaid expansion on rural population aging, including whether failure to expand results in elevated spending burdens, as previously uninsured adults graduate into Medicare eligibility.
Accountable Care Organizations
ACOs are managed-care models that seek to reduce costs and improve health outcomes among Medicare patients. Enrolling a large number of Medicare patients, purchasing expensive electronic health record systems, collecting and managing data, integrating fragmented physician practices, and building infrastructure to provide comprehensive care are essential for ACO formation and success, but are also more challenging for rural hospitals (MacKinney et al., 2010; Zhu et al., 2020). However, through the Centers for Medicare and Medicaid Services ACO Investment Model (AIM), launched in 2015, additional capital and support were given to ACOs in rural and underserved areas to address this disparity (Kopping et al., 2018). AIM is an example of recognizing the unique challenges facing rural and underserved hospital systems, and subsequently designing resources to level the playing field. AIM has been successful in reducing Medicare spending among ACOs in rural and underserved areas (Trombley et al., 2019). From 2014 to 2016, the growth in nonmetro Medicare beneficiaries in ACOs outpaced that of metro ACOs (MacKinney et al., 2018). Policymakers should continue to invest in AIM and other models that account for the unique needs of rural health-care systems seeking to improve care outcomes and reduce costs for Medicare beneficiaries.
Supplemental Nutrition Assistance Program
Food insecurity is a significant issue for older adults. In the United States, 21% of all food-insecure households include older adults (Coleman-Jensen et al., 2019). Like any marker of economic hardship, food insecurity is unequally distributed. For example, food insecurity rates are higher among the youngest older adults (ages 60–64 years) than the oldest adults (ages 70+ years; Ziliak & Gundersen, 2020). Rural versus urban residence also matters. Overall, nonmetro households consistently have higher food insecurity rates than metro households (Coleman-Jensen et al., 2019). The same nonmetro disadvantage was seen for older adults (ages 60+ years) from 2014 to 2018 (Ziliak & Gundersen, 2020). Possible explanations include greater distances to stores and food assistance programs, higher prices, a lack of public transit options, a greater prevalence of food deserts, and other factors related to availability and affordability (Coleman-Jensen & Steffen, 2017; Tanaka et al., 2014).
The most prominent U.S. food insecurity program is the Supplemental Nutrition Assistance Program (SNAP), formerly the Food Stamp Program. SNAP reduces food insecurity and ameliorates poverty by freeing up income to purchase nonfood necessities (Keith-Jennings et al., 2019; Nestle, 2019). Given the links between food insecurity and poor health (Hanson & Olson, 2012; Keith-Jennings et al., 2019), SNAP’s public health benefits are obvious. Participation has been shown to reduce health-care expenditures among low-income adults, presumably by ameliorating food insecurity (Berkowitz et al., 2017).
While overall SNAP participation rates (receipt among those eligible) are higher in nonmetro (90.2%) than metro (82.5%) areas (Vigil, 2019), in persistently poor regions SNAP receipt is lower in the most rural counties (Slack & Myers, 2012). The SNAP participation rate among those 60+ years has been on the rise, increasing from 33% to 48% between 2010 and 2017 (Vigil, 2019). However, there is minimal documentation of rural–urban trends in SNAP utilization among older adults, and insufficient evaluation of the ameliorative effects of SNAP for rural older adults.
Work requirements for accessing SNAP render ineligible many rural, working-age adults who are faced with more precarious employment opportunities (McLaughlin & Coleman-Jensen, 2008). Thus, higher nonmetro participation rates may partly reflect the absence from the denominator of those individuals who do not meet work requirements for reasons outside their control, but who are otherwise in need and deserving of support. This rural, working-age disadvantage poses potential long-term health consequences in older adulthood.
Federal agencies should fund research on the rural SNAP–food insecurity paradox (similar SNAP participation rates but higher nonmetro food insecurity) and its implications for later-life health outcomes. This should include determining whether this paradox would disappear if states were to waive work requirements in counties with high rates of precarious employment. Finally, the U.S. Department of Agriculture should partner with researchers to better explore whether spatial disparities in SNAP participation exist for the older adult population.
Conclusion
This paper highlighted three federal policies that have had or could have differential impacts on population health and aging in rural versus urban areas. Programs that are not designed solely for older adults (SNAP and Medicaid Expansion) have impacts on later-life health and, therefore, implications for rural population health and aging. However, rural areas are not monolithic (Jensen et al., 2020). Much more attention must be given to policy impacts across different types of rural areas (e.g., by region, race/ethnic composition, labor market structure). Research should use more refined definitions of place (e.g., the Economic Research Service RUCC codes, regional and labor market differences) to account for within-rural differences and the unique spatial contexts of aging.
Given space constraints, we did not discuss how these policies also differentially affect racial/ethnic minorities, immigrants, and other marginalized populations. Immigrants face restrictions in accessing programs such as those we describe here. Undocumented immigrants are largely ineligible for most federal programs. Given sharp immigrant population growth in many U.S. rural areas (Lichter, 2015), we should anticipate negative health impacts as immigrants age, and negative impacts for the children of immigrants. Federal agencies should fund research on how race and immigrant status intersect with metro status to influence policy effects on health and aging across the life course.
The impacts of local, state, and federal policies on health and healthy aging are embedded within broader economic, social, and demographic contexts.
Failure to acknowledge the spatially differential impacts of federal and state policies and programs stymies the development of tailored approaches and resources to level the playing field and support health and well-being across the life course.
Funding
This work was supported by two NIA-funded networks: The Interdisciplinary Network on Rural Population Health and Aging (R24-AG065159) and the Network on Life Course Dynamics and Disparities (2R24AG045061). We also acknowledge support from the National Institute of Food and Agriculture, USDA (multistate research project W4001, “Social, Economic and Environmental Causes and Consequences of Demographic Change in Rural America”), the Population Research Institute at Pennsylvania State University funded by NICHD (5P2CHD041025-19) and the Center for Aging and Policy Studies at Syracuse University funded by NIA (P30 AG066583).
Conflict of Interest
None declared.
Acknowledgments
The authors thank Michael Commons from the Address and Spatial Analysis Branch of the Geography Division of the U.S. Census Bureau for providing American Community Survey 5-year estimates for the older adult population by urban area classification.
