OBJECTIVE: 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.
RESULTS: 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.

Research on the COVID-19 pandemic in the United States has consistently found disproportionately high mortality among ethnoracial minorities, but reports differ with respect to the magnitude of mortality disparities and reach different conclusions regarding which groups were most impacted. We suggest that these variations stem from differences in the temporal scope of the mortality data used and difficulties inherent in measuring race and ethnicity. To circumvent these issues, we link Social Security Administration death records for 2010 through 2021 to decennial census and American Community Survey race and ethnicity responses. We use these linked data to estimate excess all-cause mortality for age-, sex-, race-, and ethnicity-specific subgroups and examine ethnoracial variation in excess mortality across states and over the course of the pandemic\'s first year. Results show that non-Hispanic American Indians and Alaska Natives experienced the highest excess mortality of any ethnoracial group in the first year of the pandemic, followed by Hispanics and non-Hispanic Blacks. Spatiotemporal and age-specific ethnoracial disparities suggest that the socioeconomic determinants driving health disparities prior to the pandemic were amplified and expressed in new ways in the pandemic\'s first year to disproportionately concentrate excess mortality among racial and ethnic minorities.

The authors identified tumor, treatment, and patient characteristics that may contribute to differences in breast cancer (BC) mortality by race, rurality, and area-level socioeconomic status (SES) among women diagnosed with stage IIIB-IV BC in Georgia.
Using the Georgia Cancer Registry, 3084 patients with stage IIIB-IV primary BC (2013-2017) were identified. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) comparing mortality among non-Hispanic Black (NHB) versus non-Hispanic White (NHW), residents of rural versus urban neighborhoods, and residents of low- versus high-SES neighborhoods by tumor, treatment, and patient characteristics. The mediating effects of specific characteristics on the association between race and BC mortality were estimated.
Among the study population, 41% were NHB, 21% resided in rural counties, and 72% resided in low SES neighborhoods. The authors observed mortality disparities by race (HR, 1.27; 95% CI, 1.13, 1.41) and rurality (HR, 1.14; 95% CI, 1.00, 1.30), but not by SES (HR, 1.04; 95% CI, 0.91, 1.19). In the stratified analyses, racial disparities were the most pronounced among women with HER2 overexpressing tumors (HR, 2.30; 95% CI, 1.53, 3.45). Residing in a rural county was associated with increased mortality among uninsured women (HR, 2.25; 95% CI, 1.31, 3.86), and the most pronounced SES disparities were among younger women (<40 years: HR, 1.46; 95% CI, 0.88, 2.42).
There is considerable variation in racial, regional, and socioeconomic disparities in late-stage BC mortality by tumor, treatment, and patient characteristics.

There are persistent disparities in mortality rates between Native Americans and other groups in the USA. Public-use mortality data severely limits the ability of researchers to examine contextual factors that might explain these disparities. Using restricted-use mortality microdata, we examine the relationship between geographic location, specific causes of death, and age at death. We show that Native American women, on average, die 13 years earlier than White women; Native American men, on average, die 12 years earlier than White men. These disparities are largest in the northern Great Plains and Rocky Mountain states. The disparity in age at death is in part due to Native Americans dying from diseases at younger ages than White Americans. Native American women and men die younger and more often from homicide in counties with persistently higher White male to female ratios. Native American men also die younger and more often from homicide when White male to female ratios increase within their county over time.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s41996-021-00095-0.

UNASSIGNED: Recent research underscores the exceptionally young age distribution of Covid-19 deaths in the United States compared with international peers. This brief characterizes how high levels of Covid mortality at midlife ages (45-64) are deeply intertwined with continuing racial inequity in Covid-19 mortality.
UNASSIGNED: Mortality data from Minnesota in 2020-2022 were analyzed in June 2022. Death certificate data and published vaccination rates in Minnesota allow vaccination and mortality rates to be observed with greater age and temporal precision than national data.
UNASSIGNED: Black, Hispanic, and Asian adults under age 65 were all more highly vaccinated than white populations of the same ages during most of Minnesota\'s substantial and sustained Delta surge and all of the subsequent Omicron surge. However, white mortality rates were lower than those of all other groups. These disparities were extreme; at midlife ages (ages 45-64), during the Omicron period, more highly-vaccinated populations had COVID-19 mortality that was 164% (Asian-American), 115% (Hispanic), or 208% (Black) of white Covid-19 mortality at these ages. In Black, Indigenous, and People of Color (BIPOC) populations as a whole, Covid-19 mortality at ages 55-64 was greater than white mortality at 10 years older.
UNASSIGNED: This discrepancy between vaccination and mortality patterning by race/ethnicity suggests that, if the current period is a \"pandemic of the unvaccinated,\" it also remains a \"pandemic of the disadvantaged\" in ways that can decouple from vaccination rates. This result implies an urgent need to center health equity in the development of Covid-19 policy measures.

OBJECTIVE: We addressed three research questions: (1) Are there racial mortality disparities in the adult Hispanic population that resemble those observed in the non-Hispanic population in the US? (2) Does nativity mediate the race-mortality relationship in the Hispanic population? and (3) What does the Hispanic mortality advantage relative to the non-Hispanic white population look like when Hispanic race is considered?
METHODS: We estimated a series of parametric hazard models on eight years of mortality follow-up data and calculated life expectancy estimates using the Mortality Disparities in American Communities database.
RESULTS: Hispanic white adults experience lower mortality than their Hispanic black, American Indian and Alaska Native, Some Other Race, and multiple race counterparts. This Hispanic white advantage is found mostly among the US born. The Hispanic advantage relative to the non-Hispanic white population operates for most Hispanic race groups among the foreign born but either disappears or converts to a disadvantage for most of the non-white Hispanic groups among the US born.
UNASSIGNED: Our study extends the literature on the Hispanic Mortality Paradox by revealing that the adult Hispanic population experiences racial mortality disparities that closely resemble those observed in the non-Hispanic population. The Hispanic mortality advantage is mediated not only by nativity but by race. These results indicate that race is a critical factor that should be considered in any study with the goal of understanding the health and mortality profiles of the Hispanic population in the US.

Theoretical models of mortality selection have great utility in explaining otherwise puzzling phenomena. The most famous example may be the Black-White mortality crossover: at old ages, Blacks outlive Whites, presumably because few frail Blacks survive to old ages while some frail Whites do. Yet theoretical models of unidimensional heterogeneity, or frailty, do not speak to the most common empirical situation for mortality researchers: the case in which some important population heterogeneity is observed and some is not. I show that, when one dimension of heterogeneity is observed and another is unobserved, neither the observed nor the unobserved dimension need behave as classic frailty models predict. For example, in a multidimensional model, mortality selection can increase the proportion of survivors who are disadvantaged, or \"frail,\" and can lead Black survivors to be more frail than Whites, along some dimensions of disadvantage. Transferring theoretical results about unidimensional heterogeneity to settings with both observed and unobserved heterogeneity produces misleading inferences about mortality disparities. The unusually flexible behavior of individual dimensions of multidimensional heterogeneity creates previously unrecognized challenges for empirically testing selection models of disparities, such as models of mortality crossovers.

Cancer contributes substantially to the life expectancy gap between US blacks and whites, and racial cancer disparities remain stubborn to eradicate. Disparities vary geographically, suggesting that they are not inevitable.
The authors examined the relationship between housing discrimination and the size of cancer disparities across large US metropolitan statistical areas (MSAs). MSA-level cancer disparities were measured using data from the US Centers for Disease Control and Prevention. Mortgage discrimination for each MSA was estimated using the Home Mortgage Disclosure Act database, and MSA racial segregation was determined using US Census data. Patterns of housing discrimination and cancer disparities were mapped, and the associations between these place-based factors and cancer disparities across MSAs were measured.
Black-to-white cancer mortality disparities (rate ratios) varied geographically, ranging from 1.50 to 0.86; 88% of mortality ratios were >1, indicating higher mortality for blacks. In areas with greater mortgage discrimination, the gap between black and white cancer mortality rates was larger (correlation coefficient [r] = 0.32; P = .001). This relationship persisted in sex-specific analyses (males, r = 0.37; P < .001; females, r = 0.23; P = .02) and in models controlling for confounders. In contrast, segregation was inconsistently associated with disparities. Adjusting for incidence disparities attenuated, but did not eliminate, the correlation between mortgage discrimination and mortality disparities (r = 0.22-0.24), suggesting that cancer incidence and survival each account for part of the mortality disparity.
Mortgage discrimination is associated with larger black-to-white cancer mortality disparities. Some areas are exceptions to this trend. Examination of these exceptions and of policies related to housing discrimination may offer novel strategies for explaining and eliminating cancer disparities.

In the 1960s and 1970s, the countries of Central and Eastern Europe and the Soviet Union experienced an unanticipated stagnation in the process of mortality reduction that was accelerating in the west. This was followed by even starker fluctuations and overall declines in life expectancy during the 1980s and 1990s. We identify statistically the extent to which, since the 1990s, the countries of the post-communist region have converged as a group towards other regional or cross-regional geopolitical blocks, or whether there are now multiple steady-states (\'convergence clubs\') emerging among these countries. We apply a complex convergence club methodology, including a recursive analysis, to data on 30 OECD countries (including 11 post-communist countries) drawn from the Human Mortality Database and spanning the period 1959-2010. We find that, rather than converging uniformly on western life expectancy levels, the post-communist countries have diverged into multiple clubs, with the lowest seemingly stuck in low-level equilibria, while the best performers (e.g. Czech Republic) show signs of catching-up with the leading OECD countries. As the post-communist period has progressed, the group of transition countries themselves has become more heterogeneous and it is noticeable that distinctive gender and age patterns have emerged. We are the first to employ an empirical convergence club methodology to help understand the complex long-run patterns of life expectancy within the post-communist region, one of very few papers to situate such an analysis in the context of the OECD countries, and one of relatively few to interpret the dynamics over the long-term.

After several decades of negative trends and short-term fluctuations, life expectancy has been increasing in Russia since 2004. Between 2003 and 2014, the length of life rose by 6.6 years among males and by 4.6 years among females. While positive trends in life expectancy are observed in all regions of Russia, these trends are unfolding differently in different regions. First, regions entered the phase of life expectancy growth at different points in time. Second, the age- and cause-specific components of the gains in life expectancy and the number of years added vary noticeably. In this paper, we apply decomposition techniques-specifically, the stepwise replacement algorithm-to examine the age- and cause-specific components of the changes in inter-regional disparities during the current period of health improvement. The absolute inter-regional disparities in length of life, measured by the population-weighted standard deviation, decreased slightly between 2003 and 2014, from 3.3 to 3.2 years for males, and from 2.0 to 1.8 years for females. The decomposition of these small changes by ages and causes of death shows that these shifts were the result of diverse effects of mortality convergence at young and middle ages, and of mortality divergence at older ages. With respect to causes of death, the convergence is mainly attributable to external causes, while the inter-regional divergence of trends is largely determined by cardiovascular diseases. The two major cities, Moscow and Saint Petersburg, are currently pioneering mortality improvements in Russia and are making the largest contributions to the inter-regional divergence.