Many rural communities experience health disparities due to social drivers of poor health and lack of health care access. However, rural America is not a monolith, and outcomes vary substantially between rural places. Even the phrase “rural health” oversimplifies the diverse health and health care needs of these communities. To address place-based health disparities with evidence-based policy, more robust, nuanced data and research are needed. Specifically, researchers need a clear framework for selecting rural definitions, and data that focus on disparities within and between rural places.
Part of addressing rural health disparities is thinking critically about what constitutes “rural.” There are numerous systems for defining urban and rural (or metropolitan and non-metropolitan) areas in the United States, resulting in a lack of standardization in government and health services research. At the federal level, some of these include the Census Bureau’s urban areas, Office of Management and Budget’s core-based statistical areas, National Center for Health Statistics rural classification scheme, Federal Office of Rural Health Policy, and four from the U.S. Department of Agriculture’s Economic Research Service: the Rural-Urban Continuum Codes (RUCC), Urban Influence Codes (UICs), Rural-Urban Commuting Area Codes (RUCAs), and Frontier and Remote Access (FAR) Codes. Complicating things further, other definitions are used in research, such as the Index of Relative Rurality, and state-based surveys may adopt their own taxonomies. Most of these definitions rely on a small set of factors, including population density, population size, and degree of urbanization, which are often applied at the county level, though census tracts and zip codes are also used. Additionally, some capture gradations of rurality, which is important for investigating disparities between rural areas, though others do not.
Recent research has called attention to this issue and offered guidance on selecting appropriate classification schemes for research. Still, the plethora of definitions and scales at which they are applied muddies our ability to understand rural health disparities. It also affects policy decisions as well as program and funding eligibility including for health clinics, Federal Office of Rural Health Policy grants, and rural development programs. As a result, researchers and policymakers alike should be concerned with the lack of standardization in classification.
Precisely defining rurality at the appropriate geographical unit is necessary, but insufficient for understanding disparities within and between rural areas. This is because rural health varies considerably by region in the United States, with the worst outcomes in the rural South, Appalachia, the U.S-Mexico border, and western Tribal lands. It is also important to consider variation by state and location on the rural-urban continuum, as these factors may be associated with different health profiles. Data collection that allows for these comparisons in research is crucial. Otherwise, disparities may be masked making it difficult to address population health and health care needs adequately.
Moreover, rural communities have diverse socioeconomic environments, and the economic divides can be staggering. Numerous studies have found that rural areas with higher levels of poverty and greater proportions of Black or Indigenous populations experience poorer health-related outcomes. And like with urban neighborhoods, variation within rural counties exists as well. Robust data that links health outcomes and contextual factors at the county and census tract level, in addition to the use of novel methods such as GIS spatial buffers and activity zones, are needed to ensure that programs and funding are directed to the right places.
Finally, to make evidence-based policy recommendations, we need rigorous, intersectional research on subpopulation health within and across rural communities. For example, researching the mechanisms driving health outcomes for those with disabilities from racially minoritized groups across rural U.S. regions could inform equitable health initiatives. Yet limited data availability and small group sizes make it difficult to do so with population health surveys, as does the lack of interoperability of administrative data. Allocating federal funds to improving data collection on health and health care needs of marginalized groups in rural areas can help us understand and improve outcomes.
In sum, research comparing health outcomes between rural and urban areas is a starting point for understanding health disparities. But even this is difficult due to conflicting definitions. Standardization of rural classification, or at minimum, a standardized process for selection in research could be useful. Additionally, nuanced data are essential for researchers to analyze health needs within rural places. Not only to identify health disparities, but to understand what is working well in rural areas. Policymakers should ensure adequate funding for agencies who collect population health data, such as the National Center for Health Statistics. With these resources, agencies should improve the interoperability of data, engage in community partnerships to identify hard-to-reach rural populations and adopt cutting-edge research methodologies to move towards health equity.