Recent social movements have highlighted fatal police violence as an enduring public health problem in the United States. To solve it, the public requires basic information, such as understanding where rates of fatal police violence are particularly high, and for which groups. Existing mapping efforts, though critically important, often use inappropriate statistical methods and can produce misleading, unstable rates when denominators are small. To fill this gap, we use inverse-variance-weighted multilevel models to estimate overall and race-stratified rates of fatal police violence for all Metropolitan Statistical Areas (MSAs) in the U.S. (2013–2017), as well as racial inequities in these rates. We analyzed the most recent, reliable data from Fatal Encounters, a citizen science initiative that aggregates and verifies media reports. Rates of police-related fatalities varied dramatically, with the deadliest MSAs exhibiting rates nine times those of the least deadly. Overall rates in Southwestern MSAs were highest, with lower rates in the northern Midwest and Northeast. Yet this pattern was reversed for Black-White inequities, with Northeast and Midwest MSAs exhibiting the highest inequities nationwide. Our main results excluded deaths that could be considered accidents (e.g., vehicular collisions), but sensitivity analyses demonstrated that doing so may underestimate the rate of fatal police violence in some MSAs by 60%. Black-White and Latinx-White inequities were slightly underestimated nationally by excluding reportedly ‘accidental’ deaths, but MSA-specific inequities were sometimes severely under- or over-estimated. Preventing fatal police violence in different areas of the country will likely require unique solutions. Estimates of the severity of these problems (overall rates, racial inequities, specific causes of death) in any given MSA are quite sensitive to which types of deaths are analyzed, and whether race and cause of death are attributed correctly. Monitoring and mapping these rates using appropriate methods is critical for government accountability and successful prevention.

In this article, Todd Grindal, Laura Schifter, Gabriel Schwartz, and Thomas Hehir examine race/ethnicity differences in students' special education identification and subsequent placement in segreg...

Introduction: Housing insecurity is increasingly commonplace among disadvantaged women and children. We measured the individual- and population-level impact of severe housing insecurity during pregnancy on adverse birth and infant outcomes. Methods: We analyzed data from 3428 mother–infant dyads enrolled in the Fragile Families and Child Wellbeing Study, a prospective cohort study representing births in 20 large U.S. cities from 1998 to 2000. Severe housing insecurity was defined as threatened eviction or homelessness during pregnancy. Outcomes included low birth weight and/or preterm birth, admission to a neonatal intensive care unit (NICU) or stepdown facility, extended hospitalization after delivery, and infant health and temperament. We estimated exposure–outcome associations with risk ratios adjusted for pre-pregnancy maternal sociodemographic and heath factors and calculated a population attributable fraction (PAF) of outcomes attributable to severe housing insecurity. Results: We found statistically significant associations between severe housing insecurity during pregnancy and low birth weight and/or preterm birth (risk ratio (RR] 1.73, 95% confidence interval (CI) 1.28, 2.32), NICU or stepdown stay (RR 1.64, CI 1.17, 2.31), and extended hospitalization (RR 1.66, CI 1.28, 2.16). Associations between housing insecurity and infant fair or poor health (RR 2.62, CI 0.91, 7.48) and poor temperament (RR 1.52, CI 0.98, 2.34) were not statistically significant. PAF estimates ranged from 0.9–2.7%, suggesting that up to three percent of adverse birth and infant outcomes could be avoided by eliminating severe housing insecurity among low-income, pregnant women in US cities. Conclusions: Results suggest that housing insecurity during pregnancy shapes neonatal and infant health in disadvantaged urban families.

Eviction affects a substantial share of U.S. children, but its effects on child health are largely unknown. Our objectives were to examine how eviction relates to 1) children's health and sociodemographic characteristics at birth, 2) neighborhood poverty and food security at age 5, and 3) obesity in later childhood and adolescence. We analyzed data from the Fragile Families and Child Wellbeing Study, a longitudinal cohort of children born in 20 large U.S. cities. Children who lived in rental housing with known eviction histories and measured outcomes were included. We compared maternal and infant health and sociodemographic characteristics at the time of the child's birth. We then characterized the associations between eviction and neighborhood poverty and food security at age 5 and obesity at ages 5, 9, and 15 using log binomial regression with inverse probability of treatment and censoring weights. Of the 2556 children included in objective 1, 164 (6%) experienced eviction before age 5. Children who experienced eviction had lower household income and maternal education and were more likely to be born to mothers who were unmarried, smoked during pregnancy, and had mental health problems. Evicted and non-evicted children were equally likely to experience high neighborhood poverty at age 5 (prevalence ratio (PR) = 1.03, 95% CI 0.82, 1.29) but had an increased prevalence of low food security (PR = 2.16, 95% CI 1.46, 3.19). Obesity prevalence did not differ at age 5 (PR = 1.01; 95% CI 0.58, 1.75), 9 (PR = 1.08; 95% CI 0.715, 1.55); or 15 (PR = 1.05; 95% CI 0.51, 2.18). In conclusion, children who went on to experience eviction showed signs of poor health and socioeconomic disadvantage already at birth. Eviction in early childhood was not associated with children's likelihood of neighborhood poverty, suggesting that eviction may not qualitatively change children's neighborhood conditions in this disadvantaged sample. Though we saw evidence supporting an association with low child food security at age 5, we did not find eviction to be associated with obesity in later childhood and adolescence.

Evidence suggests that being evicted harms health. Largely ignored in the existing literature is the possibility that evictions exert community-level health effects, affecting evicted individuals' social networks and shaping broader community conditions. In this narrative review, we summarize evidence and lay out a theoretical model for eviction as a community health exposure, mediated through four paths: 1) shifting ecologies of infectious disease and health behaviors, 2) disruption of neighborhood social cohesion, 3) strain on social networks, and 4) increasing salience of eviction risk. We describe methods for parsing eviction's individual and contextual effects and discuss implications for causal inference. We conclude by addressing eviction's potentially multilevel consequences for policy advocacy and cost-benefit analyses.