Impacts of the COVID-19 pandemic on rural America.

Despite considerable social scientific attention to the impacts of the COVID-19 pandemic on urbanized areas, very little research has examined its impact on rural populations. Yet rural communities-which make up tens of millions of people from diverse backgrounds in the United States-are among the nation's most vulnerable populations and may be less resilient to the effects of such a large-scale exogenous shock. We address this critical knowledge gap with data from a new survey designed to assess the impacts of the pandemic on health-related and economic dimensions of rural well-being in the North American West. Notably, we find that the effects of the COVID-19 pandemic on rural populations have been severe, with significant negative impacts on unemployment, overall life satisfaction, mental health, and economic outlook. Further, we find that these impacts have been generally consistent across age, ethnicity, education, and sex. We discuss how these findings constitute the beginning of a much larger interdisciplinary COVID-19 research effort that integrates rural areas and pushes beyond the predominant focus on cities and nation-states.

Elevated serious psychological distress, economic disruption, and the COVID-19 pandemic in the nonmetropolitan American West.

In this study we examined the psychological distress, self-rated health, COVID-19 exposure, and economic disruption of a sample of the nonmetropolitan western U.S. population and labor force one year after the start of the COVID-19 pandemic. Using novel primary survey data from non-metropolitan counties in the eleven contiguous western United States collected from February 28 until April 3, 2021 (n = 1203), we descriptively analyzed variables and estimated binomial and multinomial logit models of the association between economic disruption, COVID-19 exposure, self-rated health, and psychological distress. Results showed there was widespread presence of psychological distress, COVID-19 exposure, and economic disruption among the overall sample and members of the labor force. There was extremely high incidence of serious psychological distress (14.8% CI [12.1,17.8] of the weighted sample), which was heightened among the labor force (16.6%, CI [13.0,20.9] of those in the labor force). We found economic disruption was associated with severe psychological distress, but exposure to infection was not. Comparatively, overall self-rated health was at similar levels as prior research and was not significantly associated with economic disruption or COVID-19 exposure. COVID-19, particularly its associated economic effects, had a significant relationship with serious psychological distress in this sample of adults in the nonmetropolitan western United States.

The Poverty Balancing Equation: Expressing Poverty of Place as a Population Process.

The accurate measurement of poverty is essential for the development of effective poverty policy. Unfortunately, approaches that use poverty rates to assess the causes and consequences of poverty do not fully capture the components of change in the poverty population because changes in the conventional poverty rate can occur owing to processes of natural increase, migration, or transitions in and out of poverty. This article presents an accounting framework for changes in poverty within and between places. The framework, termed the poverty balancing equation, generates a series of summary statistics that can be used in place of the conventional poverty rate in future research. The approach is demonstrated using the 2014 panel of the Survey of Income and Program Participation to generate state-level estimates of the poverty components of change for three states in the American South between January and December of 2013. Results show that even when poverty rates remain constant, there is significant dynamism within poor and nonpoor populations. By applying this approach, either completely or in part, researchers can provide more specific and actionable evidence for poverty alleviation policy.

County Reclassifications and Rural-Urban Mortality Disparities in the United States (1970-2018).

Objectives. To demonstrate how inferences about rural-urban disparities in age-adjusted mortality are affected by the reclassification of rural and urban counties in the United States from 1970 to 2018.Methods. We compared estimates of rural-urban mortality disparities over time, produced through a time-varying classification of rural and urban counties, with counterfactual estimates of rural-urban disparities, assuming no changes in rural-urban classification since 1970. We evaluated mortality rates by decade of reclassification to assess selectivity in reclassification.Results. We found that reclassification amplified rural-urban mortality disparities and accounted for more than 25% of the rural disadvantage observed from 1970 to 2018. Mortality rates were lower in counties that reclassified from rural to urban than in counties that remained rural.Conclusions. Estimates of changing rural-urban mortality differentials are significantly influenced by rural-urban reclassification. On average, counties that have remained classified as rural over time have elevated mortality. Longitudinal research on rural-urban health disparities must consider the methodological and substantive implications of reclassification.Public Health Implications. Attention to rural-urban reclassification is necessary when evaluating or justifying policy interventions focusing on geographic health disparities.

The uneven impact of Medicaid expansion on rural and urban Black, Latino/a, and White mortality.

PURPOSE: To determine the differential impact of Medicaid expansion on all-cause mortality between Black, Latino/a, and White populations in rural and urban areas, and assess how expansion impacted mortality disparities between these groups. METHODS: We employ a county-level time-varying heterogenous treatment effects difference-in-difference analysis of Medicaid expansion on all-cause age-adjusted mortality for those 64 years of age or younger from 2009 to 2019. For all counties within the 50 US States and the District of Columbia, we use restricted-access vital statistics data to estimate Average Treatment Effect on the Treated (ATET) for all combinations of racial and ethnic group (Black, Latino/a, White), rurality (rural, urban), and sex. We then assess aggregate ATET, as well as how the ATET changed as time from expansion increased. FINDINGS: Medicaid expansion led to a reduction in all-cause age-adjusted mortality for urban Black populations, but not rural Black populations. Urban White populations experienced mixed effects dependent on years after expansion. Latino/a populations saw no appreciable impact. While no effect was observed for rural Black and Latino/a populations, rural White all-cause age-adjusted mortality unexpectedly increased due to Medicaid expansion. These effects reduced rural- and urban-specific Black-White mortality disparities but did not shrink the rural-urban mortality gap. CONCLUSIONS: The mortality-reducing impact of Medicaid expansion has been uneven across racial and ethnic groups and rural-urban status; suggesting that many populations-particularly rural individuals-are not seeing the same benefits as others. It is imperative that states work to ensure Medicaid expansion is being appropriately implemented in rural areas.

Informal modes of social support among residents of the rural American West during the COVID-19 pandemic.

During the first year of the COVID-19 pandemic, federal spending to government safety net programs in the U.S. increased dramatically. Despite this unparalleled spending, government safety nets were widely critiqued for failing to fully meet many households' needs. Disaster research suggests that informal modes of social support often emerge during times of disruption, such as the first year of the pandemic. However, use of formal government programs and informal support are rarely examined relative to each other, resulting in an incomplete picture of how households navigate disaster impacts and financial shocks. This study compares estimates of informal social support to formal government program use in the rural U.S. West, drawing on data from a rapid-response survey fielded during the summer of 2020 and the 2021 Annual Social and Economic Supplement of the Current Population Survey (CPS-ASEC). We find that informal social support systems were, on aggregate, used almost as extensively as long-standing government programs. Our findings highlight the critical role of person-to-person assistance, such as sharing financial resources, among rural households during a disruptive disaster period. Routine and standardized data collection on these informal support behaviors could improve future disaster research and policy responses, especially among rural populations.

Cost of Living Variation, Nonmetropolitan America, and Implications for the Supplemental Poverty Measure.

Poverty scholarship in the United States is increasingly reliant upon the Supplemental Poverty Measure (SPM) as opposed to the Official Poverty Measure of the United States for research and policy analysis. However, the SPM still faces several critiques from scholars focused on poverty in nonmetropolitan areas. Key among these critiques is the geographic adjustment for cost of living employed in the SPM, which is based solely upon median rental costs and pools together all nonmetropolitan counties within each state. Here, we evaluate the current geographic adjustment of the SPM using both microdata and aggregate data from the American Community Survey for 2014-2018. By comparing housing costs, tenure, and commuting, we determine that median rent is likely an appropriate basis for geographic adjustment. However, by demonstrating the wide variability between median rents of nonmetropolitan counties within the same state, we show that the current operationalization of this geographic adjustment could be improved through the use of more-specific categories such as metropolitan adjacency or Rural Urban Continuum Codes.

The 2020 US Census Differential Privacy Method Introduces Disproportionate Discrepancies for Rural and Non-White Populations.

The recently finalized changes to the disclosure avoidance policies of the U.S. Census Bureau for the 2020 census, grounded in differential privacy, have faced increasing criticism from demographers and other social scientists. Scholars have found that estimates generated via Census-released test data are accurate for aggregate total population statistics of larger spatial units (e.g. counties), but introduce considerable discrepancies for estimates of subgroups. At present, the ramifications of this new approach remain unclear for rural populations. In this brief, we focus on rural populations and evaluate the ability of the finalized differential privacy algorithm to provide accurate population counts and growth rates from 2000 to 2010 across the rural-urban continuum for the total, non-Hispanic white, non-Hispanic Black, Hispanic or Latino/a, and non-Hispanic American Indian population. We find the method introduces significant discrepancies relative to the prior approach into counts and growth rate estimates at the county level for all groups except the total and non-Hispanic white population. Further, discrepancies increase dramatically as we move from urban to rural. Thus, the differential privacy method likely introduced significant discrepancies for rural and non-white populations into 2020 census tabulations.

Decomposing Differences in Poor Self-rated Health between Those in Agriculture and Natural Resource Occupations and the Rest of the Labor Force.

Objective: Occupations in agriculture and natural resources persistently have some of the highest rates of injury and illness. Additionally, these fields are dominated by segments of the population known to demonstrate poorer health, such as those with less education, lower family income, and more irregular labor force participation. Thus, it is unclear if health disparities between those in these sectors and the rest of the labor force are unique to these occupations, or a reflection of their demographic composition. The objective of this study was to determine how much of the difference in self-rated health between those who work agriculture and natural resource occupations - meaning farming, forestry, fishing, hunting, and resource extraction - and the rest of the labor force was due to demographic characteristics versus unexplained factors unique to the occupations.Methods: Using the National Health Interview Survey from 2008 to 2017, a two-way Oaxaca-Blinder decomposition of linear probability models predicting poor self-rated health between those reporting agriculture and natural resource occupations and other working adults with sociodemographic characteristics was performed.Results: Results show more than the total difference in the probability of poor self-rated health between the two groups (0.0173) can be explained by demographic composition (0.0303). If the agriculture and natural resource workforce had the average demographic composition between them and the rest of the labor force, they would have lower rates of poor self-rated health than the broader labor force.Conclusion: While agriculture and natural resource occupations are hazardous, the prevalence of poor self-rated health in the labor force is not unique to these occupations, but appears common among all occupations dominated by those with low income and education.

The widespread and unjust drinking water and clean water crisis in the United States.

Many households in the United States face issues of incomplete plumbing and poor water quality. Prior scholarship on this issue has focused on one dimension of water hardship at a time, leaving the full picture incomplete. Here we complete this picture by documenting the full scope of water hardship in the United States and find evidence of a regionally-clustered, socially unequal nationwide household water crisis. Using data from the American Community Survey and the Environmental Protection Agency, we show there are 489,836 households lacking complete plumbing, 1,165 community water systems in Safe Drinking Water Act Serious Violation, and 21,035 Clean Water Act permittees in Significant Noncompliance. Further, we demonstrate this crisis is regionally clustered, with the specific spatial pattern varying by the specific form of water hardship. Elevated levels of water hardship are associated with the social dimensions of rurality, poverty, indigeneity, education, and age-representing a nationwide environmental injustice.

Rural-urban differences in the labor-force impacts of COVID-19 in the United States.

COVID-19 has had dramatic impacts on economic outcomes across the United States, yet most research on the pandemic's labor-market impacts has had a national or urban focus. We overcome this limitation using data from the U.S. Current Population Survey's COVID-19 supplement to study pandemic-related labor-force outcomes in rural and urban areas from May 2020 through February 2021. We find the pandemic has generally had more severe labor-force impacts on urban adults than their rural counterparts. Urban adults were more often unable to work, go unpaid for missed hours, and be unable to look for work due to COVID-19. However, rural workers were less likely to work remotely than urban workers. These differences persist even when adjusting for adults' socioeconomic characteristics and state-level factors. Our results suggest rural-urban differences in the nature of work during the pandemic cannot be explained by well-known demographic and political differences between rural and urban America.

The relationship between parks and recreation per capita spending and mortality from 1980 to 2010: A fixed effects model.

Evidence concerning the link between park access, use, programming and health has continued to grow. However, government funding for parks and recreation is highly susceptible to the ebbs and flows of the national economy. Given this, the purpose of this study was to test the relationship between county area spending on parks and recreation operations and all-cause mortality in the United States from the years 1980-2010. Using data from 1980 to 2010 collected from the U.S. Census Bureau and the Institute for Health Metrics and Evaluation, we analyzed the relationship between per capita county area spending on parks and recreation and county-level all-cause age-standardized female, male, and overall mortality using county and year fixed effects as well as relevant time-variant controls. The study was conducted during 2017 and 2018. County area spending on parks and recreation was negatively associated with overall and female-specific mortality from 1980 to 2010. According to our models for female and overall all-cause age-standardized mortality, when holding all else equal, a hundred-dollar increase in 2010 dollars in per capita parks and recreation operational expenditures was associated with an average decrease in morality of 3.9 and 3.4 deaths per 100,000, respectively. Although not commonly viewed as a form of healthcare spending, increased government funding for parks and recreation services had a significant association with decreased county level mortality. Our results suggest higher levels of per capita spending on parks and recreation may lead to lower levels of mortality.

Injustice in Mobile Leisure: A Conceptual Exploration of Pokémon Go.

In augmented reality, video games and the physical world converge as individuals participate in digital leisure overlaid on physical spaces. In Pokémon Go, game play in the physical world is impacted by constraints that limit access and play of marginalized groups. Global popularity of Pokémon Go created an opportunity to explore experiences of marginalized groups participating in augmented reality game play. Grey literature surrounding Pokémon Go is rich with accounts of constraints experienced by marginalized groups, particularly individuals self-identifying as White women, Black women, or Black men. Their experiences with Pokémon Go illustrate the need for social justice in digital leisure. Because the lifespan of mobile applications is limited, the gradual process from research to social change may be insufficient in addressing ever evolving digital platforms. Researchers need to strategically work with industry partners to identify needs for social justice during the planning and designing stages.