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The Delta-Omicron wave of the COVID-19 pandemic (Wave 4) in the United States occurred in Fall of 2021 through Spring of 2022. Although vaccinations were widely available, this was the deadliest period to date in the U.S., and the toll was especially high in rural areas, exacerbating an existing rural mortality penalty. This paper uses county-level multilevel regression models and publicly available data for 47 U.S. states and the District of Columbia. We describe differences in COVID-19 case and mortality rates across the rural-urban continuum during Wave 4 of the COVID-19 pandemic. Using a progressive modeling approach, we evaluate the relative contribution of a range of explanatory factors for the rural disadvantage we observe, including: pre-pandemic population health composition, vaccination rates, political partisanship, socioeconomic composition, access to broadband internet rate, and primary care physicians per capita. Results show that rural counties had higher observed burdens of cases and deaths in Wave 4 compared to more urban counties. The most remote rural counties had Wave 4 COVID-19 mortality rates 52% higher than the most urban counties. Older age composition, worse pre-pandemic population health, lower vaccination rates, higher share of votes cast for Donald Trump in the 2020 Presidential election, and lower socioeconomic composition completely explained the rural disadvantage in reported COVID-19 case rates in Wave 4, and accounting for these factors reversed the observed rural disadvantage in COVID-19 mortality. In models of mortality rate, Trump vote share had the largest effect size, followed by the percentage of the population age 50 or older, the poverty rate, the pre-pandemic mortality rate, the share of residents with a 4-year college degree, and the vaccination rate. These findings add to a growing literature describing the disproportionate toll of the COVID-19 pandemic on rural America, highlighting the combined effect of multiple sources of rural disadvantage. • Rural counties had higher case and death rates in the Delta-Omicron wave. • Rural counties had up to 51% more deaths per capita than the most urban counties. • Age, health, and SES composition partially explained the rural disadvantage. • Vaccination and Trump vote share were separate factors in the rural disadvantage. • Multiple sources of disadvantage combined in rural areas to produce poor outcomes. [ABSTRACT FROM AUTHOR]

Opioid overdose events and deaths have become a serious public health crisis in the United States, and understanding the spatiotemporal evolution of the disease occurrences is crucial for developing effective prevention strategies, informing health systems policy and planning, and guiding local responses. However, current research lacks the capability to observe the dynamics of the opioid crisis at a fine spatial-temporal resolution over a long period, leading to ineffective policies and interventions at the local level. This paper proposes a novel regionalized sequential alignment analysis using opioid overdose events data to assess the spatiotemporal similarity of opioid overdose evolutionary trajectories within regions that share similar socioeconomic status. The model synthesizes the shape and correlation of space-time trajectories to assist space-time pattern mining in different neighborhoods, identifying trajectories that exhibit similar spatiotemporal characteristics for further analysis. By adopting this methodology, we can better understand the spatiotemporal evolution of opioid overdose events and identify regions with similar patterns of evolution. This enables policymakers and health researchers to develop effective interventions and policies to address the opioid crisis at the local level. The proposed methodology provides a new framework for understanding the spatiotemporal evolution of opioid overdose events, enabling policymakers and health researchers to develop effective interventions and policies to address this growing public health crisis. • New framework for understanding spatiotemporal dynamic of opioid overdose evolution. • Identifies patterns and regions for effective crisis interventions. • Fills the gap in fine spatial-temporal resolution research. • Guides policymakers in addressing the opioid overdose crisis. [ABSTRACT FROM AUTHOR]

Neighborhood effects on health research has grown over the past 20 years. While the substantive findings of this literature have been published in systematic reviews, meta-analyses, and commentaries, operational details of the research have been understudied. We identified 7140 multi-level neighborhoods and health papers published on US populations between 1995 and 2014, and present data on the study characteristics of the 256 papers that met our inclusion criteria. Our results reveal rapid growth in neighborhoods and health research in the mid-2000s, illustrate the dominance of observational cross-sectional study designs, and show a heavy reliance on single-level, census-based neighborhood definitions. Socioeconomic indicators were the most commonly analyzed neighborhood variables and body mass was the most commonly studied health outcome. Well-known challenges associated with neighborhood effects research were infrequently acknowledged. We discuss how these results move the agenda forward for neighborhoods and health research. [ABSTRACT FROM AUTHOR]

Abstract Previous research findings across a variety of nations show that affiliation with the conservative party is associated with greater longevity; however, it is thus far unclear what characteristics contribute to this relationship. We examine the political party/mortality relationship in the United States context. The goal of this paper is two-fold: first, we seek to replicate the mortality difference between Republicans and Democrats in two samples, controlling for demographic confounders. Second, we attempt to isolate and test two potential contributors to the relationship between political party affiliation and mortality: (1) socioeconomic status and (2) dispositional traits reflecting a personal responsibility ethos, as described by the Republican party. Graduate and sibling cohorts from the Wisconsin Longitudinal Study were used to estimate mortality risk from 2004 to 2014. In separate Cox proportional hazards models controlling for age and sex, we adjusted first for markers of socioeconomic status (such as wealth and education), then for dispositional traits (such as conscientiousness and active coping), and finally for both socioeconomic status and dispositional traits together. Clogg's method was used to test the statistical significance of attenuation in hazard ratios for each model. In both cohorts, Republicans exhibited lower mortality risk compared to Democrats (Hazard Ratios = 0.79 and 0.73 in graduate and sibling cohorts, respectively [p < 0.05]). This relationship was explained, in part, by socioeconomic status and traits reflecting personal responsibility. Together, socioeconomic factors and dispositional traits account for about 52% (graduates) and 44% (siblings) of Republicans' survival advantage. This study suggests that mortality differences between political parties in the US may be linked to structural and individual determinants of health. These findings highlight the need for better understanding of political party divides in mortality rates. Highlights • Republicans have greater longevity compared to Democrats, adjusting for demographics. • This relationship is partly explained by Republican's higher socioeconomic status. • This relationship is partly explained by Republican's personal responsibility ethos. [ABSTRACT FROM AUTHOR]

The objective of this study is to report on research production and publications on health inequalities through a bibliometric analysis covering publications from 1966 to 2014 and a content analysis of the 25 most-cited papers. A database of 49,294 references was compiled from the search engine Web of Science. The first article appears in 1966 and deals with equality and civil rights in the United States and the elimination of racial discrimination in access to medical care. By 2003, the term disparity has gained in prominence relative to the term inequality which was initially elected by the researchers. Marmot's 1991 article is one of the five papers with the largest number of citations and contributes to the central perspective of social determinants of health and the British influence on the international status of research on social inequalities of health. [ABSTRACT FROM AUTHOR]

Heroin overdose, more accurately termed ‘heroin-related overdose’ due to the frequent involvement of other drugs, is the leading cause of mortality among regular heroin users. (Degenhardt et al., 2010) Heroin injectors are at greater risk of hospital admission for heroin-related overdose (HOD) in the eastern United States where Colombian-sourced powder heroin is sold than in the western US where black ‘tar’ heroin predominates. (Unick et al., 2014) This paper examines under-researched influences on HOD, both fatal and non-fatal, using data from a qualitative study of injecting drug users of black tar heroin in San Francisco and powder heroin in Philadelphia Data were collected through in-depth, semi-structured interviews carried out in 2012 that were conducted against a background of longer-term participant-observation, ethnographic studies of drug users and dealers in Philadelphia (2007–12) and of users in San Francisco (1994–2007, 2012). Our findings suggest three types of previously unconsidered influences on overdose risk that arise both from structural socio-economic factors and from the physical properties of the heroin source-types: 1) retail market structure including information flow between users; 2) marketing techniques such as branding, free samples and pricing and 3) differences in the physical characteristics of the two major heroin source forms and how they affect injecting techniques and vascular health. Although chosen for their contrasting source-forms, we found that the two cities have contrasting dominant models of drug retailing: San Francisco respondents tended to buy through private dealers and Philadelphia respondents frequented an open-air street market where heroin is branded and free samples are distributed, although each city included both types of drug sales. These market structures and marketing techniques shape the availability of information regarding heroin potency and its dissemination among users who tend to seek out the strongest heroin available on a given day. The physical characteristics of these two source-types, the way they are prepared for injecting and their effects on vein health also differ markedly. The purpose of this paper is to examine some of the unexplored factors that may lead to heroin-related overdose in the United States and to generate hypotheses for further study. [ABSTRACT FROM AUTHOR]

Previous studies have shown that financial turbulence is associated with a short-term increase in road traffic collisions, largely due to drivers' emotional state, distraction, sleep deprivation and alcohol consumption. In this paper we advance this debate by studying the association between economic uncertainty and road traffic mortality in the United States. We used a State-level uncertainty index and State fatalities for the period 2008–2017 and found that a one standard deviation increase in economic uncertainty is associated with an additional 0.013 monthly deaths per 100,000 people per State, on average (a 1.1% increase) - or 40 more monthly deaths in total nationwide. Results are robust to different model specifications. Our findings show that, similar to drink-driving, it is important to raise awareness about driving when distracted due to financial worries and during periods of economic uncertainty. • Financial turbulence has been associated with an increase in road traffic collisions. • We study the link between economic uncertainty and road traffic mortality in the US. • A one standard deviation increase in uncertainty is linked to 1.1% higher mortality. [ABSTRACT FROM AUTHOR]

Whites in the USA are the dominant racial group, with greater than average access to most material and social rewards. Yet, while whites have better outcomes than other racial groups on some health indicators, whites paradoxically compare poorly on other measures. Further, whites in the USA also rank poorly in international health comparisons. In this paper, we present a framework that combines the concept of whiteness—a system that socially, economically, and ideologically benefits European descendants and disadvantages people in other groups—with research from a variety of fields in order to comprehensively model the social factors that influence whites' health. The framework we present describes how whiteness and capitalism in the USA shape societal conditions, individual social characteristics and experiences, and psychosocial responses to circumstances to influence health outcomes. We detail specific examples of how social policies supported by whiteness, the narratives of whiteness, and the privileges of whiteness may positively and negatively affect whites' health. In doing so, we suggest several areas for future research that can expand our understanding of how social factors affect health and can contribute to the patterns and paradoxes of whites' health. By expanding research to include theoretically-grounded analyses of the dominant group's health, we can achieve a more complete picture of how systems of racial inequity affect health. [ABSTRACT FROM AUTHOR]

There has been a great deal of state-level legislative activity focused on immigration and immigrants over the past decade in the United States. Some policies aim to improve access to education, transportation, benefits, and additional services while others constrain such access. From a social determinants of health perspective, social and economic policies are intrinsically health policies, but research on the relationship between state-level immigration-related policies and Latino health remains scarce. This paper summarizes the existing evidence about the range of state-level immigration policies that affect Latino health, indicates conceptually plausible but under-explored relationships between policy domains and Latino health, traces the mechanisms through which immigration policies might shape Latino health, and points to key areas for future research. We examined peer-reviewed publications from 1986 to 2016 and assessed 838 based on inclusion criteria; 40 were included for final review. These 40 articles identified four pathways through which state-level immigration policies may influence Latino health: through stress related to structural racism; by affecting access to beneficial social institutions, particularly education; by affecting access to healthcare and related services; and through constraining access to material conditions such as food, wages, working conditions, and housing. Our review demonstrates that the field of immigration policy and health is currently dominated by a “one-policy, one-level, one-outcome” approach. We argue that pursuing multi-sectoral, multi-level, and multi-outcome research will strengthen and advance the existing evidence base on immigration policy and Latino health. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the effects of state-level Earned Income Tax Credit (EITC) laws in the U.S. on maternal health behaviors and infant health outcomes. Using multi-state, multi-year difference-in-differences analyses, we estimated effects of state EITC generosity on maternal health behaviors, birth weight and gestation weeks. We find little difference in maternal health behaviors associated with state-level EITC. In contrast, results for key infant health outcomes of birth weight and gestation weeks show small improvements in states with EITCs, with larger effects seen among states with more generous EITCs. Our results provide evidence for important health benefits of state-level EITC policies. [ABSTRACT FROM AUTHOR]

Increasing “patient engagement” has become a priority for health care organizations and policy-makers seeking to reduce cost and improve the quality of care. While concepts of patient engagement have proliferated rapidly across health care settings, little is known about how health care providers make use of these concepts in clinical practice. This paper uses 20 months of ethnographic and interview research carried out from 2015 to 2016 to explore how health care providers working at two public, urban, safety-net hospitals in the United States define, discuss, and assess patient engagement. We investigate how health care providers describe engagement for high cost patients—the “super-utilizers” of the health care system—who often face complex challenges related to socioeconomic marginalization including poverty, housing insecurity, exposure to violence and trauma, cognitive and mental health issues, and substance use. The health care providers in our study faced institutional pressure to assess patient engagement and to direct care towards engaged patients. However, providers considered such assessments to be highly challenging and oftentimes inaccurate, particularly because they understood low patient engagement to be the result of difficult socioeconomic conditions. Providers tried to navigate the demand to assess patient engagement in care by looking for explicit positive and negative indicators of engagement, while also being sensitive to more subtle and intuitive signs of engagement for marginalized patients. [ABSTRACT FROM AUTHOR]

Socioeconomic inequalities in childhood Body Mass Index (BMI) are becoming increasingly more pronounced across the world. Although countries differ in the direction and strength of these inequalities, cross-national comparative research on this topic is rare. This paper draws on harmonized longitudinal cohort data from four wealthy countries—Germany, the Netherlands, the United Kingdom (UK), and the United States (US)—to 1) map cross-country differences in the magnitude of socioeconomic inequalities in childhood BMI, and 2) to examine cross-country differences in the role of three energy-balance-related behaviors—physical activity, screen time, and breakfast consumption—in explaining these inequalities. Children were aged 5–7 at our first timepoint and were followed up at age 8–11. We used data from the German National Educational Panel Study, the Dutch Generation R study, the UK Millennium Cohort Study and the US Early Childhood Longitudinal-Kindergarten Study. All countries revealed significant inequalities in childhood BMI. The US stood out in having the largest inequalities. Overall, inequalities between children with low versus medium educated parents were smaller than those between children with high versus medium educated parents. The role of energy-balance-related behaviors in explaining inequalities in BMI was surprisingly consistent. Across countries, physical activity did not, while screen time and breakfast consumption did play a role. The only exception was that breakfast consumption did not play a role in the US. Cross-country differences emerged in the relative contribution of each behavior in explaining inequalities in BMI: Breakfast consumption was most important in the UK, screen time explained most in Germany and the US, and breakfast consumption and screen time were equally important in the Netherlands. Our findings suggest that what constitutes the most effective policy intervention differs across countries and that these should target both children from medium as well as low educated families. • All countries showed substantial socioeconomic inequalities in childhood BMI. • In all countries, inequalities in BMI steepen over course of primary school. • Protective factors among the most advantaged seem to mainly drive inequalities. • Across most countries, underlying mechanisms for inequalities in BMI are similar. • The relative contribution of each mechanism to BMI inequalities differs per country. [ABSTRACT FROM AUTHOR]

Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010–2000) in sociodemographics. Spatial patterns were assessed using Global Moran's I to measure overall clustering of change and Local Moran's I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran's indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time. [ABSTRACT FROM AUTHOR]

This paper discusses increasing differentiation of U.S. dietary components by socioeconomic strata and its health implications. While upper-income groups have had increasing access to higher-quality foods, lower-to-middle-income class diets are heavily focused on “energy-dense” fares. This neoliberal diet is clearly associated with the proliferation of obesity that disproportionately affects the poor. We provide a critical review of the debate about obesity from within the critical camp in food studies, between individual-focused and structural perspectives. Using official data, we show how the US diet has evolved since the 1960s to a much greater emphasis on refined carbohydrates and vegetable oils. Inequality is demonstrated by dividing the population into households-income quintiles and how they spend on food. We then introduce our Neoliberal Diet Risk Index (NDR), comprised of measures of food-import dependency, the Gini coefficient, rates of urbanization, female labor-force participation, and economic globalization. Our index serves to measure the risk of exposure to the neoliberal diet comparatively, across time and between nations. We conclude that only a societal actor like the state can redirect the food-production system by modifying its agricultural subsidy policies. Inequality-reducing policies will make the healthier food involved in such change widely available for all. [ABSTRACT FROM AUTHOR]

Many low and middle-income countries in Asia experience greater food availability as their economies grow, potentially solving previous problems of undernutrition. However, economic growth may not sufficiently reduce undernutrition and instead increase over nutrition, creating a double burden of malnutrition. In this paper we investigate one of the most prevalent and seemingly paradoxical manifestations of the double burden, a stunted child and an overweight mother (SCOM) living in the same household. We use household-level data from 11 Asian countries from 2005 to 2018, as well as macroeconomic data on the Gross Domestic Product (GDP) and the GDP growth of these countries to estimate which household-level and macroeconomic factors predict SCOM. We also determine the relative predictive power of our variables for SCOM and investigate if predictors of SCOM also predict other forms of malnutrition. We find that the predictive power of household-level factors for SCOM is comparatively more important than that of macroeconomic variables. Additionally, we explore the effect of including population subgroup-level trends in maternal overweight and child stunting on the predictive power of our macro-level and household-level variables. The increasing prevalence of SCOM is driven by a rise in maternal overweight, coupled with stagnant rates of child stunting, but remains a unique phenomenon that differs from other indicators of malnutrition. This supports explanations that suggest increasing consumption of high-energy but low-nutrient foods is the underlying cause of SCOM, leading to weight gain in adults and stunting in under-five children. • Increasing rates of Asian households with overweight mothers and stunted children. • A nutritional transition in the wake of economic growth an often-conjectured driver. • Known household-level determinants confirmed in large cross-country dataset. • Both growth and household-level determinants are predictors of the double burden. • Household-level factors with greater direct predictive power than economic growth. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has triggered a notable increase in the expression of prejudicial and xenophobic attitudes that threaten the wellbeing of minority groups and contribute to the overall public health toll of the virus. However, while there is evidence documenting the growth in discrimination and xenophobia, little is known about how the COVID-19 outbreak is activating the expression of such negative attitudes. The goal of the current paper therefore was to investigate what aspects of the COVID-19 pandemic may be contributing to this rise in expressions of prejudice and xenophobia. More specifically, this study used an experimental design to assess the effects of using stigmatized language to describe the virus as well as the threat to physical health and economic wellbeing posed by the virus on COVID-19 prejudice. Data were collected from a national sample of 1451 adults residing within the United States. Results from 2 × 2 x 2 between-subjects analyses of covariance demonstrated that emphasizing the connection between China and COVID-19, rather than framing the virus neutrally, increased negative attitudes toward Asian Americans, beliefs that resources should be prioritized for Americans rather than immigrants, and general xenophobia. Emphasizing the severity of the economic impact of the virus also increased beliefs that Asian Americans are a threat to resources and general xenophobia. In contrast, messages which emphasized the serious health risks of COVID-19 did not increase bias toward Asian Americans or xenophobia. Our findings suggest that specific types of public health messaging related to infectious diseases, especially framing the virus in terms of its country of origin or its likely economic impact, may elicit prejudice and xenophobia. Public health campaigns that emphasize the severity of the virus, however, are not likely to trigger the same negative attitudes. Implications for public health responses to health crises are discussed. • The framing of COVID-19 information shapes prejudice and xenophobia. • Emphasizing COVID-19's origin in China increases anti-Asian and xenophobic attitudes. • Emphasizing severe economic harm also increases negative outgroup attitudes. • Messaging about the health threat of the virus is unrelated to outgroup bias. [ABSTRACT FROM AUTHOR]