Social and political correlates of adult and dependent-child COVID-19 vaccination behavior in rural America.

Objective: This paper describes the individual-level correlates of self and dependent-child COVID-19 vaccination behavior among adults in rural America. Methods: We draw on the data from a large-scale survey of rural Americans conducted in 2022, after most Americans had the opportunity to receive the vaccination easily and freely. The survey yielded an analytic sample of 841 adults and 530 adults with dependent children. We fit a series of linear probability models predicting vaccine refusal and full vaccination for adult respondents and vaccine refusal and full vaccine coverage among their dependent children. Predictors of interest include political party, social and economic conservatism, race and ethnicity, age, education, and workplace vaccine requirements. Results: We find political party, ideology, education, and work requirements were significant (p <.05) drivers of rural adults' vaccination behavior, and that the correlates of vaccine refusal and full vaccination largely mirrored one another among adults. For dependent children, few of our focal predictors are associated with vaccination. Politics played a lesser role in children's vaccination than for adults, and older parents were the least likely to refuse vaccines for their children. Race and ethnicity had inconsistent associations across outcomes and model specifications. Conclusion: This analysis presents important evidence on the drivers of COVID-19 vaccine behaviors among rural American households. Documentation of vaccination behaviors in settings when vaccines are widely available can isolate demand- from supply-side factors and thus inform future public health crises.

Temperature anomalies undermine the health of reproductive-age women in low- and middle-income countries.

Climate change is expected to undermine population health and well-being in low- and middle-income countries, but relatively few analyses have directly examined these effects using individual-level data at global scales, particularly for reproductive-age women. To address this lacuna, we harmonize nationally representative data from the Demographic and Health Surveys on reproductive health, body mass index (BMI), and temporary migration from 2.5 million adult women (ages 15 to 49) in approximately 109,000 sites across 59 low- and middle-income countries, which we link to high-resolution climate data. We use this linked dataset to estimate fixed-effect logistic regression models of demographic and health outcomes as a function of climate exposures, woman-level and site-level characteristics, seasonality, and regional time trends, allowing us to plausibly isolate climate effects from other influences on health and migration. Specifically, we measure the effects of recent exposures to temperature and precipitation anomalies on the likelihood of having a live birth in the past year, desire for another child, use of modern contraception, underweight (BMI < 18.5), and temporary migration, and subsequently allow for nonlinearity as well as heterogeneity across education, rural/urban residence, and baseline climate. This analysis reveals that exposures to high temperatures increase live births, reduce desire for another child, increase underweight, and increase temporary migration, particularly in rural areas. The findings represent clear evidence that anthropogenic temperature increases contribute to temporary migration and are a significant threat to women's health and reproductive autonomy in low- and middle-income countries.

The Childhood Origins of Climate-Induced Mobility and Immobility.

The literature on climate exposures and human migration has focused largely on assessing short-term responses to temperature and precipitation shocks. In this paper, we suggest that this common coping strategies model can be extended to account for mechanisms that link environmental conditions to migration behavior over longer periods of time. We argue that early-life climate exposures may affect the likelihood of migration from childhood through early adulthood by influencing parental migration, community migration networks, human capital development, and decisions about household resource allocation, all of which are correlates of geographic mobility. After developing this conceptual framework, we evaluate the corresponding hypotheses using a big data approach, analyzing 20 million individual georeferenced records from 81 censuses implemented across 31 countries in tropical Africa, Latin America, and Southeast Asia. For each world region, we estimate regression models that predict lifetime migration (a change in residence between birth and ages 30-39) as a function of temperature and precipitation anomalies in early life, defined as the year prior to birth through age four. Results suggest that early-life climate is systematically associated with changes in the probability of lifetime migration in most regions of the tropics, with the largest effects observed in sub-Saharan Africa. In East and Southern Africa, the effects of temperature shocks vary by sex and educational attainment and in a manner that suggests women and those of lower socioeconomic status are most vulnerable. Finally, we compare our main results with models using alternative measures of climate exposures. This comparison suggests climate exposures during the prenatal period and first few years of life are particularly (but not exclusively) salient for lifetime migration, which is most consistent with the hypothesized human capital mechanism.

Unequal From the Start? Poverty Across Immigrant Generations of Hispanic Children.

Recent cohorts of U.S. children increasingly consist of immigrants or the immediate descendants of immigrants, a demographic shift that has been implicated in high rates of child poverty. Analyzing data from the 2014-2018 Current Population Survey and using the U.S. Census Bureau's Supplemental Poverty Measure, we describe differences in child poverty rates across immigrant generations and assess how these disparities are rooted in generational differences in the prevalence and impact of key poverty risk factors. Our estimates show that poverty rates among Hispanic children are very high, particularly among first-generation children and second-generation children with two foreign-born parents. Low family employment is the most significant risk factor for poverty, but the prevalence of this risk varies little across immigrant generations. Differences in parental education account for the greatest share of observed intergenerational disparities in child poverty. Supplemental comparisons with third+-generation non-Hispanic White children underscore the disadvantages faced by all Hispanic children, highlighting the continued salience of race and ethnicity within the U.S. stratification system. Understanding the role of immigrant generation vis-à-vis other dimensions of inequality has significant policy implications given that America's population continues to grow more diverse along multiple social axes.

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.

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.

Exposure to Armed Conflict and Fertility in Sub-Saharan Africa.

Changes in fertility patterns are hypothesized to be among the many second-order consequences of armed conflict, but expectations about the direction of such effects are theoretically ambiguous. Prior research, from a range of contexts, has also yielded inconsistent results. We contribute to this debate by using harmonized data and methods to examine the effects of exposure to conflict on preferred and observed fertility outcomes across a spatially and temporally extensive population. We use high-resolution georeferenced data from 25 sub-Saharan African countries, combining records of violent events from the Armed Conflict Location and Event Data Project (ACLED) with data on fertility goals and outcomes from the Demographic and Health Surveys (n = 368,765 women aged 15-49 years). We estimate a series of linear and logistic regression models to assess the effects of exposure to conflict events on ideal family size and the probability of childbearing within the 12 months prior to the interview. We find that, on average, exposure to armed conflict leads to modest reductions in both respondents' preferred family size and their probability of recent childbearing. Many of these effects are heterogeneous between demographic groups and across contexts, which suggests systematic differences in women's vulnerability or preferred responses to armed conflict. Additional analyses suggest that conflict-related fertility declines may be driven by delays or reductions in marriage. These results contribute new evidence about the demographic effects of conflict and their underlying mechanisms, and broadly underline the importance of studying the second-order effects of organized violence on vulnerable populations.

Climate exposures and child undernutrition: Evidence from Indonesia.

Global climate change has the potential to disrupt agricultural systems, undermine household socioeconomic status, and shape the prevalence and distribution of diseases. Each of these changes may influence children's nutritional status, which is sensitive to food availability, access, and utilization, and which may have lasting consequences for later-life health and socioeconomic outcomes. This paper contributes to the emerging literature on climate and child health by studying the effects of temperature and precipitation exposures on children's height and weight in Indonesia. Drawing on five rounds of the Indonesian Family Life Survey (IFLS) implemented between 1993 and 2015, we estimate fixed-effects regression models of height-for-age (HFA) and weight-for-height (WFH) among samples of children ages 24-59 months and 0-23 months, respectively. We test for heterogeneity in these effects across sub-populations expected to vary in their vulnerability. Results show that delays in monsoon onset are consistently associated with worse child health outcomes. Delays in monsoon onset during the prenatal period are associated with reduced child height among children age 2-4 years. The weight of young (<2 years) children is adversely affected by delays in the most recent monsoon season, and this relationship is particularly strong among residents of Java. Overall, our results underline the need for interventions that protect children's nutrition and underlying health against the effects of climate change.

Characterizing the Indigenous Forest Peoples of Latin America: Results from Census Data.

Indigenous populations in Latin America are central to regional and global efforts toward achieving socially and environmentally sustainable development. However, existing demographic research on indigenous forest peoples (IFPs) has many limitations, including a lack of comparable cross-national evidence. We address this gap by linking representative census microdata to satellite-derived tree cover estimates for nine countries in the region. Our analyses describe the demographic and socioeconomic characteristics of IFPs, and draw comparisons with reference groups. Our first goal is to examine within- and between-population variation in the age structure, human capital attainment, and economic status of IFPs. We then analyze patterns of fertility among indigenous forest-dwelling women and comparison groups. Finally, we examine the association between migration patterns and tree cover among indigenous and non-indigenous populations. Findings demonstrate that Latin America's IFPs are materially deprived and characterized by high fertility levels overall. Importantly for sustainable development efforts, we show that non-indigenous forest-dwellers outnumber IFPs by more than eight to one and that IFPs have lower fertility than their non-indigenous counterparts when other characteristics are accounted for. Additionally, we find that most in-migrants to heavily-forested areas are non-indigenous, and that in-migrants tend to settle in areas that are forested but have few indigenous inhabitants. These results provide new cross-national evidence on the state of IFPs in Latin America, and highlight the need to empower these groups in the face of growing social and environmental crises in the region.

Population Change and Income Inequality in Rural America.

This paper examines the effects of population growth and decline on county-level income inequality in the rural United States from 1980 to 2016. Findings from previous research have shown that population growth is positively associated with income inequality. However, these studies are largely motivated by theories of urbanization and growth in metropolitan areas, and do not explicitly test for differences between the impacts of population growth and decline. Examining the effects of both forms of population change on income inequality is particularly important in rural counties of the United States, the majority of which are experiencing population decline. We analyze county-level data (N=11,320 county-decades) from the U.S. Decennial Census and American Community Survey, applying fixed-effects regression models to estimate the respective effects of population growth and decline on income inequality within rural counties. We find that both forms of population change have significant effects on income inequality relative to stable growth. Population decline is associated with increases in income inequality, while population growth is marginally associated with decreases in inequality. These relationships are consistent across a variety of model specifications, including models that account for counties' employment, sociodemographic, and ethno-racial composition. We also find that the relationship between income inequality and population change varies by counties' geographic region, baseline level of inequality, and baseline population size, suggesting that the links between population change and income inequality are not uniform across rural America.

Climate Variability and Child Nutrition: Findings from Sub-Saharan Africa.

Climatic variability affects many underlying determinants of child malnutrition, including food availability, access, and utilization. Evidence of the effects of changing temperatures and precipitation on children's nutritional status nonetheless remains limited. Research addressing this knowledge gap is merited given the short- and long-run consequences of malnutrition. We address this issue by estimating the effects of temperature and precipitation anomalies on the weight and wasting status of children ages 0-59 months across 16 countries in sub-Saharan Africa. Linear regression models show that high temperatures and low precipitation are associated with reductions in child weight, and that high temperatures also lead to increased risk of wasting. We find little evidence of substantively meaningful differences in these effects across sub-populations of interest. Our results underscore the vulnerability of young children to climatic variability and its second-order economic and epidemiological effects. The study also highlights the corresponding need to design and assess interventions to effectively mitigate these impacts.

Race, Residence, and Underemployment: Fifty Years in Comparative Perspective, 1968-2017.

High underemployment has been a chronic structural feature of the rural United States for decades. In this paper, we assess whether and how inequalities in underemployment between metropolitan (metro) and nonmetropolitan (nonmetro) areas have changed over the course of the last five decades. Drawing on data from the March Current Population Survey (CPS) from 1968 to 2017, we analyze inequality in the prevalence of underemployment between metro and nonmetro areas of the United States, paying special attention to differences between white, black, and Hispanic workers. Our results show that the underlying risk of underemployment has increased in both metro and nonmetro areas over the last fifty years. Nonmetro workers have consistently faced greater employment hardship compared to their metro counterparts, and these differences cannot be fully explained by differences in population characteristics. Nonmetro ethnoracial minorities have experienced particularly poor labor market outcomes. The disadvantage of ethnoracial minority status and rural residence is especially pronounced for nonmetro black workers, among whom underemployment has remained persistently high with only modest convergence with other workers. Hispanic workers also face elevated risk of underemployment, but we observe a unique convergence between metro and nonmetro workers within this population.

The Great Recession and America's Geography of Unemployment.

BACKGROUND: The Great Recession of 2007-2009 was the most severe and lengthy economic crisis in the U.S. since the Great Depression. The impacts on the population were multi-dimensional, but operated largely through local labor markets. OBJECTIVE: To examine differences in recession-related changes in county unemployment rates and assess how population and place characteristics shaped these patterns. METHODS: We calculate and decompose Theil Indexes to describe recession-related changes in the distribution of unemployment rates between counties and states. We use exploratory spatial statistics to identify geographic clusters of counties that experienced similar changes in unemployment. We use spatial regression to evaluate associations between county-level recession impacts on unemployment and demographic composition, industrial structure, and state context. RESULTS: The recession was associated with increased inequality between county labor markets within states, but declining between-state differences. Counties that experienced disproportionate recession-related increases in unemployment were spatially clustered and characterized by large shares of historically disadvantaged racial and ethnic minority populations, low educational attainment, and heavy reliance on pro-cyclical industries. Associations between these sources of vulnerability were partially explained by unobserved state-level factors. CONCLUSIONS: The local consequences of macroeconomic trends are associated with county population characteristics, as well as the structural contexts and policy environments in which they are embedded. The recession placed upward pressure on within-state inequality between local labor market conditions. CONTRIBUTION: To present new estimates of the recession's impact on local labor markets, quantify how heterogeneous impacts affected the distribution of unemployment prevalence, and identify county characteristics associated with disproportionately large recession-related increases in unemployment.