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Empirical evidence points to a persistent Black-White racial gap in police-caused homicides. Some scholarship treats the gap as denoting criminal justice exposure either in terms of involvement in crime or living in a high-crime context. By contrast, health scholarship typically points to the importance of racism including the attitudes, institutional practices, and overall structures that operate to privilege one group over another. Still, given the demographics of US society, the Black-White racial contrast overlooks the 25% of Americans who are neither Black nor White: Native Americans, Latinos, and Asians. The question of how the groups should be organized vis-a-vis the current Black-White model and theories arises. An answer is not straightforward. There is a rank-ordering to the groups' mortality rates as well as an exponential increase in the number of possible comparisons. In this paper we systematically review the literature on race and police-caused homicide with a particular focus on studies that attempt to move beyond the Black-White model. We find that studies on race and police-caused homicide either make no comparison between the groups, or, alternatively, use a White-non-White, a Black-non-Black, and/or a Black-Native American-Latino vs. White-Asian comparison. We use data on group-specific mortality rates to examine the strengths and limits of each of these practices. The limits are the selection of counterfactual gaps, the selection of smaller gaps, and/or the omission of larger gaps. To address these limits, we propose that a Black-Native American vs. Latino-White-Asian model best captures the higher and lower mortality rates in police-caused homicide data. • Mortality rates from police-caused homicide vary by race and ethnicity. • The Black group has the highest rate followed by the Native American, Latino, White and Asian groups. • The literature makes one of several contrasts between these groups. • These are White-non-White; Black-non-Black, or Black-Native American-Latino vs. White-Asian. • Black-Native American vs. Latino-White-Asian contrast best reflects the groups' mortality rates. [ABSTRACT FROM AUTHOR]

In many parts of the world nursing home residents have experienced a disproportionate risk of exposure to COVID-19 and have died at much higher rates than other groups. There is a critical need to identify the factors driving COVID-19 risk in nursing homes to better understand and address the conditions contributing to their vulnerability during public health crises. This study investigates the characteristics associated with COVID-19 cases and deaths among residents in U.S. nursing homes from 2020 to 2021, with a focus on geospatial and racial inequalities. Using data from the Centers for Medicare and Medicaid Services and LTCFocus, this paper uses zero-inflated negative binomial regression models, Kruskal-Wallis tests, and Local Moran's I to generate statistical and geospatial results. Our analysis reveals that majority Hispanic facilities have alarmingly high COVID-19 cases and deaths, suggesting that these facilities have the greatest need for policy improvements in staffing and financing to reduce racial inequalities in nursing home care. At the same time we also detect COVID-19 hot spots in rural areas with predominately White residents, indicating a need to rethink public messaging strategies in these areas. The top states with COVID-19 hot spots are Kentucky, Pennsylvania, Illinois, and Oklahoma. This research provides new insights into the socio-spatial contexts and inequities that contribute to the vulnerability of nursing home residents during a pandemic. • Geographic and racial inequalities are important indicators of covid-19 risk. • Covid-19 cases & deaths are high among facilities with majority Hispanic residents. • Facilities with majority Hispanic residents have high covid-19 vaccination rates. • Most covid-19 hot spots of cases & deaths are in predominantly White, rural areas. • The top states with covid-19 hot spots of cases & deaths are KY, PA, IL, and OK. [ABSTRACT FROM AUTHOR]

While the overall impact of the COVID-19 pandemic on U.S. population health has been devastating, it has not affected everyone equally. The risks of hospitalization and death from the disease are relatively low for the population as a whole, but much higher for specific subpopulations defined by age, health status, and race or ethnicity. The extent to which Americans perceive these disparities is an open question, with potentially important political implications. Recognition of unequal impacts may prime concerns about justice and fairness, making Americans more concerned and willing to support government intervention. On the other hand, belief that the pandemic primarily threatens "other people" or out-groups may reduce, rather than increase, a person's concern. Partisanship and media consumption habits are also likely to play a role in these perceptions, as they do in most issues related to COVID-19. In this paper, we use original survey data from the Cooperative Election Study (N = 1000) to explore Americans' perceptions of which groups are most harmed by the pandemic, the demographic and political determinants of these perceptions, and the relationship of these perceptions with their opinions about COVID-related mitigation policy. We find that, on average, people perceived accurately that certain groups (e.g., Black Americans, older people) were more affected, but these group perceptions varied by demographic and political characteristics of respondents. We find, in contrast with recent experimental evidence, that the perception that populations of color were harmed was associated with more support for pandemic mitigation strategies. More research should investigate the relationships among pandemic politics and the racial dynamics of the target populations most affected. • In fall 2020, survey participants recognized groups harmed by COVID based on age. • They had lower recognition of racial groups harmed, lowest for Native Americans. • Perceptions of groups harmed varies by information exposure and politics. • Perceiving group disparities was associated with more support for pandemic policy. • The racial dynamics surrounding the politics of COVID-19 requires more attention. [ABSTRACT FROM AUTHOR]

This paper presents the first longitudinal study of sex disparities in COVID-19 cases and mortalities across U.S. states, derived from the unique 13-month dataset of the U.S. Gender/Sex COVID-19 Data Tracker. To analyze sex disparities, weekly case and mortality rates by sex and mortality rate ratios were computed for each U.S. state, and a multilevel crossed-effects conditional logistic binomial regression model was fitted to estimate the variation of the sex disparity in mortality over time and across states. Results demonstrate considerable variation in the sex disparity in COVID-19 cases and mortalities over time and between states. These data suggest that the sex disparity, when present, is modest, and likely varies in relation to context-sensitive variables, which may include health behaviors, preexisting health status, occupation, race/ethnicity, and other markers of social experience. • First report of findings from unique longitudinal dataset of sex-disaggregated COVID-19 data in U.S. states. • Sex disparities in COVID-19 are highly heterogeneous in magnitude and direction and vary across states and over time. • Gender-related and other social and contextual factors likely shape COVID-19 sex disparities. • Single-factor approaches are ill-positioned to explain patterns in sex disparities in COVID-19 outcomes. [ABSTRACT FROM AUTHOR]

Over the past five decades in the United States, White women have breastfed at higher rates than Black women. While a small but growing body of social historical research has examined racial disparities in breastfeeding over time, empirical research, particularly quantitative research, has focused on single historical snapshots, unintentionally treating the persistent racial disparities in breastfeeding as a static phenomenon, rather than one with distinct social mechanisms at different points in time. Further, few studies on racial disparities in health deconstruct difference both within and across racial groups. But what if we thought about persistent racial disparities instead as discrete trends with distinct social mechanisms at different points in time? In a binary logistic regression of breastfeeding initiation rates from 1973 to 2015 using the National Survey of Family Growth (NSFG), I found that the persistent racial disparities were actually comprised of three distinct types of changing racial disparities: (1) increases in racial disparities that derive from improvements for Whites not captured by Blacks (1973–1982); (2) decreases in racial disparities that stem from improvements for Whites captured even more strongly by Blacks (1995–2006); and, (3) leveling off of racial disparities (2006–2015). Placing results of this quantitative analysis within the context of public policy and social movement history, I identify three distinct mechanisms that drive the different trends in racial disparities in breastfeeding. This paper contributes to the literature on motherhood, race, and health a more nuanced understanding of the social historical mechanisms that pattern breastfeeding, and more broadly, racial disparities in health. • From 1973 to 2015, White women breastfed at higher rates than Black women. • Three distinct types of disparities comprised persistent racial disparities in breastfeeding. • Public policy & social movements impact people differently based on social location. [ABSTRACT FROM AUTHOR]