Native American Age at Death in the USA.

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. Supplementary Information: The online version contains supplementary material available at 10.1007/s41996-021-00095-0.

Adequacy of Existing Surveillance Systems to Monitor Racism, Social Stigma and COVID Inequities: A Detailed Assessment and Recommendations.

The populations impacted most by COVID are also impacted by racism and related social stigma; however, traditional surveillance tools may not capture the intersectionality of these relationships. We conducted a detailed assessment of diverse surveillance systems and databases to identify characteristics, constraints and best practices that might inform the development of a novel COVID surveillance system that achieves these aims. We used subject area expertise, an expert panel and CDC guidance to generate an initial list of N > 50 existing surveillance systems as of 29 October 2020, and systematically excluded those not advancing the project aims. This yielded a final reduced group (n = 10) of COVID surveillance systems (n = 3), other public health systems (4) and systems tracking racism and/or social stigma (n = 3, which we evaluated by using CDC evaluation criteria and Critical Race Theory. Overall, the most important contribution of COVID-19 surveillance systems is their real-time (e.g., daily) or near-real-time (e.g., weekly) reporting; however, they are severely constrained by the lack of complete data on race/ethnicity, making it difficult to monitor racial/ethnic inequities. Other public health systems have validated measures of psychosocial and behavioral factors and some racism or stigma-related factors but lack the timeliness needed in a pandemic. Systems that monitor racism report historical data on, for instance, hate crimes, but do not capture current patterns, and it is unclear how representativeness the findings are. Though existing surveillance systems offer important strengths for monitoring health conditions or racism and related stigma, new surveillance strategies are needed to monitor their intersecting relationships more rigorously.

Identifying Disparities in Health Outcomes and Mortality for American Indian and Alaska Native Populations Using Tribally Disaggregated Vital Statistics and Health Survey Data.

Objectives. To determine the impact of disaggregated mortality and health surveillance data on the ability to identify health disparities for American Indian and Alaska Native (AI/AN) subpopulations. Methods. We conducted a systematic review of reporting categories for AI/AN decedents on official death certificates for all 50 US states. Using public data from the 2017-2018 California Health Interview Survey (CHIS), we conducted bivariate and multivariate analyses to assess disparities in health conditions and outcomes for tribally enrolled and non‒tribally enrolled AI/AN persons compared with non-Hispanic Whites. Results. There was no standard for the collection of tribal enrollment data or AI/AN race on death certificates across all 50 states. There were stark differences in the incidence and prevalence of various health risk factors and chronic diseases for the tribally enrolled AI/AN subpopulation, non‒tribally enrolled AI/AN subpopulation, and non-Hispanic White comparison group. Conclusions. The collection of tribal enrollment data in vital statistics and health surveillance systems is necessary to identify and respond to health disparities among AI/AN subpopulations. These efforts must be conducted in partnership with tribal nations and consider Indigenous data sovereignty.

Indigenous Peoples' Data During COVID-19: From External to Internal.

Global disease trackers quantifying the size, spread, and distribution of COVID-19 illustrate the power of data during the pandemic. Data are required for decision-making, planning, mitigation, surveillance, and monitoring the equity of responses. There are dual concerns about the availability and suppression of COVID-19 data; due to historic and ongoing racism and exclusion, publicly available data can be both beneficial and harmful. Systemic policies related to genocide and racism, and historic and ongoing marginalization, have led to limitations in quality, quantity, access, and use of Indigenous Peoples' COVID-19 data. Governments, non-profits, researchers, and other institutions must collaborate with Indigenous Peoples on their own terms to improve access to and use of data for effective public health responses to COVID-19.

The impact of Medicaid on medical utilization in a vulnerable population: Evidence from COFA migrants.

In March 2015, the State of Hawaii stopped covering the majority of migrants from countries belonging to the Compact of Free Association (COFA) in its Medicaid program. COFA migrants were required to obtain private insurance in the exchanges established under the Affordable Care Act. Using statewide hospital discharge data, we show that Medicaid-funded hospitalizations and emergency room visits declined in this population by 31% and 19%, respectively. Utilization funded by private insurance did increase but not enough to offset the declines in Medicaid-funded utilization. We show that the expiration of benefits increased uninsured ER visits. Finally, we exploit a feature of the policy change to provide evidence that the declines in utilization are due to higher rates of uninsured migrants rather than higher levels of cost sharing on private plans.

The Mortality Effects of Reduced Medicaid Coverage Among International Migrants in Hawaii: 2012-2018.

Objectives. To study the impact on mortality in Hawaii from the revoked state Medicaid program coverage in March 2015 for most Compact of Free Association (COFA) migrants who were nonblind, nondisabled, and nonpregnant.Methods. We computed quarterly crude mortality rates for COFA migrants, Whites, and Japanese Americans from March 2012 to November 2018. We employed a difference-in-difference research design to estimate the impact of the Medicaid expiration on log mortality rates.Results. We saw larger increases in COFA migrant mortality rates than White mortality rates after March 2015. By 2018, the increase was 43% larger for COFA migrants (P = .003). Mortality trends over this period were similar for Whites and Japanese Americans, who were not affected by the policy.Conclusions. Mortality rates of COFA migrants increased after Medicaid benefits expired despite the availability of state-funded premium coverage for private insurance and significant outreach efforts to reduce the impact of this coverage change.

American Indian Reservations and COVID-19: Correlates of Early Infection Rates in the Pandemic.

OBJECTIVE: To determine the household and community characteristics most closely associated with variation in COVID-19 incidence on American Indian reservations in the lower 48 states. DESIGN: Multivariate analysis with population weights. SETTING: Two hundred eighty-seven American Indian Reservations and tribal homelands (in Oklahoma) and, as of April 10, 2020, 861 COVID-19 cases on these reservation lands. MAIN OUTCOME MEASURES: The relationship between rate per 1000 individuals of publicly reported COVID-19 cases at the tribal reservation and/or community level and average household characteristics from the 2018 5-Year American Community Survey records. RESULTS: By April 10, 2020, in regression analysis, COVID-19 cases were more likely by the proportion of homes lacking indoor plumbing (10.83, P = .001) and were less likely according to the percentage of reservation households that were English-only (-2.43, P = .03). Household overcrowding measures were not statistically significant in this analysis (-6.40, P = .326). CONCLUSIONS: Failure to account for the lack of complete indoor plumbing and access to potable water in a pandemic may be an important determinant of the increased incidence of COVID-19 cases. Access to relevant information that is communicated in the language spoken by many reservation residents may play a key role in the spread of COVID-19 in some tribal communities. Household overcrowding does not appear to be associated with COVID-19 infections in our data at the current time. Previous studies have identified household plumbing and overcrowding, and language, as potential pandemic and disease infection risk factors. These risk factors persist. Funding investments in tribal public health and household infrastructure, as delineated in treaties and other agreements, are necessary to protect American Indian communities.

Race Matters: Income Shares, Income Inequality, and Income Mobility for All U.S. Races.

Using unique linked data, we examine income inequality and mobility across racial and ethnic groups in the United States. Our data encompass the universe of income tax filers in the United States for the period 2000-2014, matched with individual-level race and ethnicity information from multiple censuses and American Community Survey data. We document both income inequality and mobility trends over the period. We find significant stratification in terms of average incomes by racial/ethnic group and distinct differences in within-group income inequality. The groups with the highest incomes-whites and Asians-also have the highest levels of within-group inequality and the lowest levels of within-group mobility. The reverse is true for the lowest-income groups: blacks, American Indians, and Hispanics have lower within-group inequality and immobility. On the other hand, low-income groups are also highly immobile in terms of overall, rather than within-group, mobility. These same groups also have a higher probability of experiencing downward mobility compared with whites and Asians. We also find that within-group income inequality increased for all groups between 2000 and 2014, and the increase was especially large for whites. The picture that emerges from our analysis is of a rigid income structure, with mainly whites and Asians positioned at the top and blacks, American Indians, and Hispanics confined to the bottom.

How Does Household Income Affect Child Personality Traits and Behaviors?

We examine the effects of a quasi-experimental unconditional household income transfer on child emotional and behavioral health and personality traits. Using longitudinal data, we find that there are large beneficial effects on children's emotional and behavioral health and personality traits during adolescence. We find evidence that these effects are most pronounced for children who start out with the lowest initial endowments. The income intervention also results in improvements in parental relationships which we interpret as a potential mechanism behind our findings.

Young Adult Obesity and Household Income: Effects of Unconditional Cash Transfers.

We investigate the effect of household cash transfers during childhood on young adult body mass indexes (BMI). The effects of extra income differ depending on the household's initial socioeconomic status (SES). Children from the initially poorest households have a larger increase in BMI relative to children from initially wealthier households. Several alternative mechanisms are examined. Initial SES holds up as the most likely channel behind the heterogeneous effects of extra income on young adult BMI. (JEL D14, H23, H75, I12, J13, J15).

Parents' Incomes and Children's Outcomes: A Quasi-Experiment.

We examine the role that an exogenous increase in household income due to a government transfer unrelated to household characteristics plays in children's long run outcomes. Children in affected households have higher levels of education in their young adulthood and a lower incidence of criminality for minor offenses. Effects differ by initial household poverty status. An additional $4000 per year for the poorest households increases educational attainment by one year at age 21 and reduces having ever committed a minor crime by 22% at ages 16-17. Our evidence suggests that improved parental quality is a likely mechanism for the change.