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Objectives. To describe the creation of an interactive dashboard to advance the understanding of the COVID-19 pandemic from an equity and urban health perspective across 30 large US cities that are members of the Big Cities Health Coalition (BCHC). Methods. We leveraged the Drexel‒BCHC partnership to define the objectives and audience for the dashboard and developed an equity framework to conceptualize COVID-19 inequities across social groups, neighborhoods, and cities. We compiled data on COVID-19 trends and inequities by race/ethnicity, neighborhood, and city, along with neighborhood- and city-level demographic and socioeconomic characteristics, and built an interactive dashboard and Web platform to allow interactive comparisons of these inequities across cities. Results. We launched the dashboard on January 21, 2021, and conducted several dissemination activities. As of September 2021, the dashboard included data on COVID-19 trends for the 30 cities, on inequities by race/ethnicity in 21 cities, and on inequities by neighborhood in 15 cities. Conclusions. This dashboard allows public health practitioners to contextualize racial/ethnic and spatial inequities in COVID-19 across large US cities, providing valuable insights for policymakers. (Am J Public Health. 2022;112(6):904–912. https://doi.org/10.2105/AJPH.2021.306708 )

Understanding health disparity causes is an important first step toward developing policies or interventions to eliminate disparities, but their nature makes identifying and addressing their causes challenging. Potential causal factors are often correlated, making it difficult to distinguish their effects. These factors may exist at different organizational levels (e.g., individual, family, neighborhood), each of which needs to be appropriately conceptualized and measured. The processes that generate health disparities may include complex relationships with feedback loops and dynamic properties that traditional statistical models represent poorly. Because of this complexity, identifying disparities’ causes and remedies requires integrating findings from multiple methodologies. We highlight analytic methods and designs, multilevel approaches, complex systems modeling techniques, and qualitative methods that should be more broadly employed and adapted to advance health disparities research and identify approaches to mitigate them.

To evaluate trends in premature death rates by cause of death, age, race, and urbanization level in the United States.We calculated cause-specific death rates using the Compressed Mortality File, National Center for Health Statistics data for adults aged 25 to 64 years in 2 time periods: 1999 to 2001 and 2013 to 2015. We defined 48 subpopulations by 10-year age groups, race/ethnicity, and county urbanization level (large urban, suburban, small or medium metropolitan, and rural).The age-adjusted premature death rates for all adults declined by 8% between 1999 to 2001 and 2013 to 2015, with decreases in 39 of the 48 subpopulations. Most decreases in death rates were attributable to HIV, cardiovascular disease, and cancer. All 9 subpopulations with increased death rates were non-Hispanic Whites, largely outside large urban areas. Most increases in death rates were attributable to suicide, poisoning, and liver disease.The unfavorable recent trends in premature death rate among non-Hispanic Whites outside large urban areas were primarily caused by self-destructive health behaviors likely related to underlying social and economic factors in these communities.

Objectives. We described the associations of ambient air pollution exposure with race/ethnicity and racial residential segregation. Methods. We studied 5921 White, Black, Hispanic, and Chinese adults across 6 US cities between 2000 and 2002. Household-level fine particulate matter (PM2.5) and nitrogen oxides (NOX) were estimated for 2000. Neighborhood racial composition and residential segregation were estimated using US census tract data for 2000. Results. Participants in neighborhoods with more than 60% Hispanic populations were exposed to 8% higher PM2.5 and 31% higher NOX concentrations compared with those in neighborhoods with less than 25% Hispanic populations. Participants in neighborhoods with more than 60% White populations were exposed to 5% lower PM2.5 and 18% lower NOX concentrations compared with those in neighborhoods with less than 25% of the population identifying as White. Neighborhoods with Whites underrepresented or with Hispanics overrepresented were exposed to higher PM2.5 and NOX concentrations. No differences were observed for other racial/ethnic groups. Conclusions. Living in majority White neighborhoods was associated with lower air pollution exposures, and living in majority Hispanic neighborhoods was associated with higher air pollution exposures. This new information highlighted the importance of measuring neighborhood-level segregation in the environmental justice literature.

Objectives. To examine the impact of neighborhood conditions resulting from racial residential segregation on cardiovascular disease (CVD) risk in a socioeconomically diverse African American sample. Methods. The study included 4096 African American women (n = 2652) and men (n = 1444) aged 21 to 93 years from the Jackson Heart Study (Jackson, Mississippi; 2000–2011). We assessed neighborhood disadvantage with a composite measure of 8 indicators from the 2000 US Census. We assessed neighborhood-level social conditions, including social cohesion, violence, and disorder, with self-reported, validated scales. Results. Among African American women, each standard deviation increase in neighborhood disadvantage was associated with a 25% increased risk of CVD after covariate adjustment (hazard ratio = 1.25; 95% confidence interval = 1.05, 1.49). Risk also increased as levels of neighborhood violence and physical disorder increased after covariate adjustment. We observed no statistically significant associations among African American men in adjusted models. Conclusions. Worse neighborhood economic and social conditions may contribute to increased risk of CVD among African American women. Policies directly addressing these issues may alleviate the burden of CVD in this group.

The author reflects on distinctions and differences between the terms public health and population health and speculates on if the public health community should distinguish itself from it. She suggests the discussion over terminology provides the public health community with an opportunity to clarify what they believe public health is or should be about. It mentions that health care services are not excluded by the population health approach but is placed in context.

Objectives. We examined the social patterning of cumulative dysregulation of multiple systems, or allostatic load, among African Americans adults. Methods. We examined the cross-sectional associations of socioeconomic status (SES) with summary indices of allostatic load and neuroendocrine, metabolic, autonomic, and immune function components in 4048 Jackson Heart Study participants. Results. Lower education and income were associated with higher allostatic load scores in African American adults. Patterns were most consistent for the metabolic and immune dimensions, less consistent for the autonomic dimension, and absent for the neuroendocrine dimension among African American women. Associations of SES with the global allostatic load score and the metabolic and immune domains persisted after adjustment for behavioral factors and were stronger for income than for education. There was some evidence that the neuroendocrine dimension was inversely associated with SES after behavioral adjustment in men, but the immune and autonomic components did not show clear dose–response trends, and we observed no associations for the metabolic component. Conclusions. Findings support our hypothesis that allostatic load is socially patterned in African American women, but this pattern is less consistent in African American men.

Objectives. Using Jackson Heart Study data, we examined whether perceived discrimination was associated with prevalent hypertension in African Americans. Methods. Everyday discrimination, lifetime discrimination, burden of discrimination, and stress from discrimination were examined among 4939 participants aged 35 to 84 years (women = 3123; men = 1816). We estimated prevalence ratios of hypertension by discrimination, and adjusted for age, gender, socioeconomic status, and risk factors. Results. The prevalence of hypertension was 64.0% in women and 59.7% in men. After adjustment for age, gender, and socioeconomic status, lifetime discrimination and burden of discrimination were associated with greater hypertension prevalence (prevalence ratios for highest vs lowest quartile were 1.08 [95% confidence interval (CI) = 1.02, 1.15] and 1.09 [95% CI = 1.02,1.16] for lifetime discrimination and burden of discrimination, respectively). Associations were slightly weakened after adjustment for body mass index and behavioral factors. No associations were observed for everyday discrimination. Conclusions. Further understanding the role of perceived discrimination in the etiology of hypertension may be beneficial in eliminating hypertension disparities.

Complex systems approaches have received increasing attention in public health because reductionist approaches yield limited insights in the context of dynamic systems. Most discussions have been highly abstract. There is a need to consider the application of complex systems approaches to specific research questions. I review the features of population health problems for which complex systems approaches are most likely to yield new insights, and discuss possible applications of complex systems to health disparities research. I provide illustrative examples of how complex systems approaches may help address unanswered and persistent questions regarding genetic factors, life course processes, place effects, and the impact of upstream policies. The concepts and methods of complex systems may help researchers move beyond current impasse points in health disparities research.

Objectives. We assessed whether markers of acculturation (birthplace and number of US generations) and socioeconomic status (SES) are associated with markers of subclinical cardiovascular disease—carotid artery plaque, internal carotid intima-media thickness, and albuminuria—in 4 racial/ethnic groups. Methods. With data from the Multi-Ethnic Study of Atherosclerosis (n = 6716 participants aged 45–84 years) and race-specific binomial regression models, we computed prevalence ratios adjusted for demographics and traditional cardiovascular risk factors. Results. The adjusted US- to foreign-born prevalence ratio for carotid plaque was 1.20 (99% confidence interval [CI] = 0.97, 1.39) among Whites, 1.91 (99% CI = 0.94, 2.94) among Chinese, 1.62 (99% CI = 1.28, 2.06) among Blacks, and 1.23 (99% CI = 1.15, 1.31) among Hispanics. Greater carotid plaque prevalence was found among Whites, Blacks, and Hispanics with a greater number of generations with US residence (P < .001) and among Whites with less education and among Blacks with lower incomes. Similar associations were observed with intima-media thickness. There was also evidence of an inverse association between albuminuria and SES among Whites and Hispanics. Conclusions. Greater US acculturation and lower SES were associated with a higher prevalence of carotid plaque and greater intima-media thickness but not with albuminuria. Maintenance of healthful habits among recent immigrants should be encouraged.

Objectives. We investigated relations between changes in neighborhood ethnic composition and changes in body mass index (BMI) and waist circumference among Chinese and Hispanic immigrants in the United States. Methods. We used Multi-Ethnic Study of Atherosclerosis data over a median 9-year follow-up (2000–2002 to 2010–2012) among Chinese (n = 642) and Hispanic (n = 784) immigrants aged 45 to 84 years at baseline. We incorporated information about residential moves and used econometric fixed-effects models to control for confounding by time-invariant characteristics. We characterized neighborhood racial/ethnic composition with census tract–level percentage Asian for Chinese participants and percentage Hispanic for Hispanic participants (neighborhood coethnic concentration). Results. In covariate-adjusted longitudinal fixed-effects models, results suggested associations between decreasing neighborhood coethnic concentration and increasing weight, although results were imprecise: within-person BMI increases associated with an interquartile range decrease in coethnic concentration were 0.15 kilograms per meters squared (95% confidence interval [CI] = 0.00, 0.30) among Chinese and 0.17 kilograms per meters squared (95% CI = –0.17, 0.51) among Hispanic participants. Results did not differ between those who did and did not move during follow-up. Conclusions. Residential neighborhoods may help shape chronic disease risk among immigrants.

Objectives. The resurgence of tuberculosis (TB) in New York City has been attributed to AIDS and immigration; however, the role of poverty in the epidemic is unclear. We assessed the relation between neighborhood poverty and TB at the height of the epidemic and longitudinally from 1984 through 1992. Methods. Census block groups were used as proxies for neighborhoods. For each neighborhood, we calculated TB and AIDS incidence in 1984 and 1992 with data from the Bureaus of Tuberculosis Control and AIDS Surveillance and obtained poverty rates from the census. Results. For 1992, 3343 TB cases were mapped to 5482 neighborhoods, yielding a mean incidence of 46.5 per 100 000. Neighborhood poverty was associated with TB (relative risk = 1.33; 95% confidence interval = 1.30, 1.36 per 10% increase in poverty). This association persisted after adjustment for AIDS, proportion foreign-born, and race/ethnicity. Neighborhoods with declining income from 1980 to 1990 had larger increases in TB incidence than did neighborhoods with increasing income. Conclusions. Leading up to and at the height of the TB epidemic in New York City, neighborhood poverty was strongly associated with TB incidence. Public health interventions should target impoverished areas.

OBJECTIVES: This study examined the prevalence, social correlates, and clustering of cardiovascular disease risk factors in a predominantly Black, poor, urban community. METHODS: Associations of risk factor prevalences with sociodemographic variables were examined in a population-based sample of 695 men and women aged 18 to 65 years living in Central Harlem. RESULTS: One third of the men and women were hypertensive, 48% of the men and 41% of the women were smokers, 25% of the men and 49% of the women were overweight, and 23% of the men and 35% of the women reported no leisure-time physical activity over the past month. More than 80% of the men and women had at least 1 of these risk factors, and 9% of the men and 19% of the women had 3 or more risk factors. Income and education were inversely related to hypertension, smoking, and physical inactivity. Having 3 or more risk factors was associated with low income and low education (extreme odds ratio [OR] = 10.2, 95% confidence interval [CI] = 3.0, 34.5 for education; OR = 3.7, CI = 1.6, 8.9 for income) and with a history of unstable work or of homelessness. CONCLUSIONS: Disadvantaged, urban communities are at high risk for cardiovascular disease. These results highlight the importance of socioenvironmental factors in shaping cardiovascular risk.

We are encouraged that other researchers have been investigating the health impacts associated with the availability of food stores. It is unfortunate, although not surprising, that the absence of commercial food institutions in low-income, minority neighborhoods is an international concern. Documenting the structural effects of racial segregation on the well-being of residents is paramount in determining the extent to which racial isolation of Black Americans over the past decades constrains individual change. Understanding the mechanisms involved in dietary choices requires theory and analysis that address the interactions of cultural factors, food costs, individual income and education, dietary habits, and availability of foods. Factors influencing diet, from agriculture to advertising, from the local food environment to choices at the shelf, are historical, not fixed. Certainly, further quantitative research is needed to better understand the ways in which environmental contexts affect health, and the approaches Cummins suggests will be key in this regard. However, at a time when expanding economic inequalities and residential segregation threaten to further degrade the “foodscape” of low-income, minority communities, there are already strong theoretical and empirical grounds to expect that food environments offering both affordable and healthy choices are increasingly critical to these communities.