Rural/urban differences in receipt of governmental rental assistance: Relationship to health and disability.

PURPOSE: Housing is essential to health. Governmental rental assistance is one way to increase access to affordable housing, but little is known about how it varies by rural/urban location. This paper seeks to address that gap by examining rural/urban and within-rural differences in receipt of rental assistance, with particular attention differences by health and disability. METHODS: We used data from the 2021 National Health Interview Survey (n = 28,254) to conduct bivariate analyses to identify significant differences in receipt of rental assistance by rural/urban location. We then conducted logistic regression analyses to generate odds ratios of receiving rental assistance, adjusting for self-rated health, disability, sociodemographic characteristics, and the US Census region. FINDINGS: When limiting the sample to those who rent (20.6% of rural residents and 29.6% of urban residents), rural residents were nearly 5 percentage points more likely to receive rental assistance (13.1% vs 8.2%, P<.001). Rural recipients of rental assistance were more likely to have a disability than urban residents (27.9% vs 20.3%, P<.05) and were more likely to report fair/poor health (41.6% vs 31.4%, P<.05). CONCLUSIONS: Rural residents are less likely to rent their homes, but, among those who rent, they are more likely to receive governmental rental assistance. This may be reflective of the greater need for rental assistance among rural residents, who were in poorer health and of lower socioeconomic status than urban renters. As housing is essential to good health, policy attention must prioritize addressing a persistent and growing need for affordable housing in rural and urban areas alike.

Availability of cancer care services and the organization of care delivery at critical access hospitals.

INTRODUCTION: Critical access hospitals (CAHs) provide an opportunity to meet the needs of individuals with cancer in rural areas. Two common innovative care delivery methods include the use of traveling oncologists and teleoncology. It is important to understand the availability and organization of cancer care services in CAHs due to the growing population with cancer and expected declines in oncology workforce in rural areas. METHODS: Stratified random sampling was used to generate a sample of 50 CAHs from each of the four U.S. Census Bureau-designated regions resulting in a total sample of 200 facilities. Analyses were conducted from 135 CAH respondents to understand the availability of cancer care services and organization of cancer care across CAHs. RESULTS: Almost all CAHs (95%) provided at least one cancer screening or diagnostic service. Forty-six percent of CAHs reported providing at least one component of cancer treatment (chemotherapy, radiation, or surgery) at their facility. CAHs that offered cancer treatment reported a wide range of health care staff involvement, including 34% of respondents reporting involvement of a local oncologist, 38% reporting involvement of a visiting oncologist, and 28% reporting involvement of a non-local oncologist using telemedicine. CONCLUSION: Growing disparities within rural areas emphasize the importance of ensuring access to timely screening and guideline-recommended treatment for cancer in rural communities. These data demonstrated that CAHs are addressing the growing need through a variety of approaches including the use of innovative models that utilize non-local providers and telemedicine to expand access to crucial services for rural residents with cancer.

Unmet Needs for Help With Mobility Limitations Among Older Adults Aging in Place: The Role of Rurality.

OBJECTIVES: This study identifies differences in unmet mobility needs among older adults living in rural versus urban areas. METHODS: We used data from Round 9 of the National Health and Aging Trends Study (NHATS), limiting our analyses to respondents who had not moved since baseline (average housing tenure of 27 years; n = 3343). We conducted bivariate and multivariate analyses to detect rural/urban differences in unmet mobility needs, adjusting for socio-demographics, health status, and housing characteristics. RESULTS: Rural residence was associated with higher odds of any unmet mobility needs for older adults aging in place (adjusted odds ratio: 1.64, 95% confidence interval: 1.10-2.44, p < .05). The relationship between rurality and unmet needs for help with mobility limitations remained significant in fully adjusted models. DISCUSSION: Rural older adults aging in place have greater unmet needs for help with mobility limitations. This study highlights several important gaps in supporting rural older adults aging in place.

Approaches to Serving Rural Older Adults in State Plans on Aging: A Policy Content Evaluation.

Every state is required to submit a State Plan on Aging describing how it will use resources from the Older Americans Act (OAA), including a section specific to serving rural older adults. This paper describes a policy content evaluation of all 50 State Plans on Aging, focusing on Section 307(a)(10), which describes how states will serve rural older adults. We identified the most common and innovative approaches to using OAA funds to serve rural older adults across states. The most common information included about using OAA funds to serve rural older adults was describing the funding formula used to allocate resources. However, states varied in their definition of rural and in the details of their funding formulas. A minority of states also described additional approaches to serving rural older adults, including prioritizing Black, Indigenous, or rural residents of color; outreach; and targeted service delivery.

Contact by Collection Agencies for Medical Debt: Rural-Urban Differences Among Older and Younger Medicare Beneficiaries.

Geographic disparities in health and health care are increasingly well-documented, as are financial barriers to accessing care. Still, less is known about whether Medicare beneficiaries differ in their ability to pay for care by rurality. Using data from the 2016 Medicare Current Beneficiary Survey (n = 12,688 U.S. community-dwelling beneficiaries), we analyzed rural-urban differences in rates of collection agency contact for unpaid medical bills using chi-square tests and multivariable logistic regression for the full sample and by age (65+ and <65). Nearly 10% of Medicare beneficiaries had been contacted by a collection agency for medical debt in the previous year, with higher percentages among rural beneficiaries (8% for urban vs 10% for rural micropolitan and 11% for rural noncore, p < .05). This difference attenuated after adjusting for educational attainment and income, suggesting that attention to socio-economic status among rural Medicare beneficiaries would help to address financial barriers to care and decrease medical debt.

"They're not leaving their home; this is where they were born, this is where they will die.": Key Informant Perspectives From the U.S. Counties With the Greatest Concentration of the Oldest Old.

The "oldest old," age 85 and older, constitute one of the fastest growing segments of the U.S. population. Yet, surprisingly little is known about the characteristics of U.S. counties with the highest percentage of the oldest old, nearly all of which are rural. We used qualitative analysis of key informant interviews (n = 50) with county commissioners and other county-level representatives from rural counties with the highest prevalence of the oldest old, targeting the 54 rural counties with ≥5% of the population age 85+. We found that the rural counties with the highest proportion of residents age 85+ face unique challenges to supporting successful aging among the oldest old, including resource constraints, limited services, isolated locations, and widespread service areas. Still, interviewees identified particular reasons why the oldest old remain in their counties, with many highlighting positive aspects of rural environments and community.

Differences by Rurality in Satisfaction with Care Among Medicare Beneficiaries.

PURPOSE: There are stark differences between rural and urban areas in demographic characteristics, health status, and health care, yet less is known about rural-urban differences in Medicare beneficiaries' satisfaction with care. We seek to identify rural-urban differences in satisfaction with care for Medicare beneficiaries and whether those differences are explained by differences in beneficiary characteristics. METHODS: We used data from the 2016 Medicare Current Beneficiary Survey (n = 10,625), in which beneficiaries indicated their level of satisfaction for 9 measures related to quality and access/affordability of care. We first assessed bivariate differences in satisfaction with care by rural-urban location (metropolitan, rural micropolitan, and rural noncore) across each measure. We then used logistic regression to assess whether differences remained after adjusting for sociodemographic and health characteristics. RESULTS: For nearly all measures, satisfaction with care decreased with increasing rurality. Differences in satisfaction persisted for satisfaction with ease of getting to the doctor from home (adjusted odds ratio [AOR] micropolitan: 0.63, P = .037; AOR noncore: 0.61, P = .023) and availability of care by specialists (AOR micropolitan: 0.51, P = .001; AOR noncore: 0.61, P < .001) after adjusting for sociodemographic and health characteristics. CONCLUSIONS: Rural Medicare beneficiaries reported lower satisfaction with care than their urban counterparts across a variety of measures, and some of these differences remained after adjustments were made for sociodemographic and health characteristics. These findings may have implications for access to and quality of care that rural Medicare beneficiaries receive and their subsequent health outcomes.

Rural-Urban Difference in Workplace Supports and Impacts for Employed Caregivers.

PURPOSE: This study examines rural-urban differences in employed caregivers' access to workplace supports, negative impacts of caregiving on work, and the association between work and caregiver strain, which can have negative impacts on health. METHODS: We used a cross-sectional analysis of employed caregivers (n = 635) from the 2015 Caregiving in the US survey, including bivariate comparisons of caregiver characteristics, access to workplace benefits, and workplace impacts by rural-urban location, as well as ordered logistic regression models to assess the relationship between workplace benefits and impacts and caregiver strain, stratified by rural-urban location. FINDINGS: Employed rural caregivers had significantly fewer workplace benefits available to them (1.3 out of 5 vs 1.9, P < .001), compared with urban caregivers. In particular, employed rural caregivers were less likely to have access to telecommuting, employee assistance programs, and paid leave. For the full sample, having more negative workplace impacts was associated with greater caregiver strain (adjusted odds ratio [AOR]: 1.65, P < .001); for employed rural caregivers, using paid help for caregiving was associated with more strain (AOR: 4.39, P < .05). CONCLUSIONS: More should be done to support all employed caregivers, especially those in rural locations who have more limited access to workplace supports and who may be more negatively impacted by the financial toll of caregiving and of missing work because of caregiving responsibilities. Interventions could range from employer-initiated programs to local, state, or national policies to improve supports provided to employed caregivers in urban and rural areas.

A National Examination of Caregiver Use of and Preferences for Support Services: Does Rurality Matter?

Objective: The objective of this study was to assess rural-urban differences in caregiver use of and preferences for support services. Method: Using the 2015 Caregiving in the U.S. survey data (n = 1,389), we analyzed rural-urban differences by caregiver residence in use of and preferences for support services. We analyzed bivariate differences in service use and preferences, as well as in sociodemographic and caregiving relationship characteristics. We also assessed the correlates of service use using stratified ordered logistic regression models. Results: Approximately one third of all caregivers had used no supportive services, with few differences in service use and preference by location. For caregivers in both locations, having more financial strain was associated with greater use of services. Discussion: This article identifies broad needs for caregiver support across all geographic locations. Targeted efforts should be made to ensure access to supportive services accounting for unique barriers by geography.