Developing and Implementing Racial Health Equity Plans in Four Large US Cities: A Qualitative Study.

CONTEXT: Local health departments (LHDs) and their partners are critical components of the fight for racial health equity, particularly given the variation in levels of, and pathways to, inequities at the local level. OBJECTIVE: To inform continued progress in this area, we qualitatively examined the development and implementation of equity-related plans and initiatives of LHDs within 4 large US cities: Baltimore, Boston, Chicago, and Philadelphia. DESIGN AND MEASURES: We conducted 15 semistructured interviews with 21 members of LHDs, academic institutions, health systems, and community-based organizations involved with health equity strategies or activities in their respective cities. Outcomes included perceptions of the effectiveness of the local health equity plan, participation in other equity-related initiatives, stakeholder engagement, and best practices. RESULTS: We contacted 49 individuals, of whom 2 declined and 21 accepted our interview invitation. Recruitment was stopped after we reached saturation. Thematic analysis identified 5 themes across interviews: (1) organizations were flexible in reallocating resources to address racial and health equity; (2) multidisciplinary teams are necessary for effective development and implementation of health equity plans; (3) community collaboration is required for meaningful and sustainable change; (4) there is a direct relationship between racism, structural inequities, and health outcomes; and (5) health departments have prioritized health equity plan development, but further work is required to address root causes. CONCLUSIONS: In the United States, health departments have begun to develop and implement strategic health plans focused on equity. However, the extent to which these plans result in actual initiatives (both internal and external) varied across cities. The current study increases our understanding of how different partners are working to implement structural changes, programs, and policies to reach equity-related goals in our largest urban areas, providing valuable insight for urban health advocates across the country.

Life Expectancy Gaps Among Black and White Persons and Contributing Causes of Death in 3 Large US Cities, 2018-2019.

Importance: US cities have substantial, but varying, levels of racial mortality inequities, a consequence of structural racism. As committed partners increasingly pledge to eliminate health inequities, local data are required to focus and unify efforts. Objective: To analyze the contributions of 26 cause-of-death categories to Black to White life expectancy gaps within 3 large US cities. Design, Setting, and Participants: In this cross-sectional study, data were extracted from the 2018 and 2019 National Vital Statistics System Multiple Cause of Death Restricted Use data files for deaths by race, ethnicity, sex, age, place of residence, and underlying and contributing causes of death in Baltimore, Maryland; Houston, Texas; and Los Angeles, California. Life expectancy at birth was calculated for non-Hispanic Black and non-Hispanic White populations overall and by sex using abridged life tables with 5-year age intervals. Data analysis was performed from February to May 2022. Main Outcomes and Measures: Using the Arriaga method, the proportion of the Black to White life expectancy gap was calculated overall and by sex for each city that was attributable to 26 cause-of-death categories defined using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes for underlying and contributing causes of death. Results: A total of 66 321 death records from 2018 to 2019 were analyzed, with 29 057 individuals (44%) were identified as Black, 34 745 (52%) as male, and 46 128 (70%) as aged 65 years and older. Black to White life expectancy gaps were 7.60 years for Baltimore, 8.06 years for Houston, and 9.57 years for Los Angeles. Circulatory diseases, cancer, injuries, and diabetes and endocrine disorders were top contributors to the gaps, although the order and magnitude varied by city. The contribution of circulatory diseases was 11.3 percentage points higher in Los Angeles than in Baltimore (3.76 years [39.3%] vs 2.12 years [28.0%]). The contribution of injuries to Baltimore's racial gap (2.22 years [29.3%]) was twice as large as in Houston (1.11 years [13.8%]) and Los Angeles (1.36 years [14.2%]). Conclusions and Relevance: By assessing the composition of Black to White life expectancy gaps for 3 large US cities and categorizing deaths at a more granular level than past studies, this study provides insight into the differing underpinnings of urban inequities. This type of local data can support local resource allocation that more effectively addresses racial inequities.

Comparison of All-Cause Mortality Rates and Inequities Between Black and White Populations Across the 30 Most Populous US Cities.

Importance: To address elevated mortality rates and historically entrenched racial inequities in mortality rates, the United States needs targeted efforts at all levels of government. However, few or no all-cause mortality data are available at the local level to motivate and guide city-level actions for health equity within the country's biggest cities. Objectives: To provide city-level data on all-cause mortality rates and racial inequities within cities and to determine whether these measures changed during the past decade. Design, Setting, and Participants: This cross-sectional study used mortality data from the National Vital Statistics System and American Community Survey population estimates to calculate city-level mortality rates for the non-Hispanic Black (Black) population, non-Hispanic White (White) population, and total population from January 2016 to December 2018. Changes from January 2009 to December 2018 were examined with joinpoint regression. Data were analyzed for the United States and the 30 most populous US cities. Data analysis was conducted from February to November 2020. Exposure: City of residence. Main Outcomes and Measures: Total population and race-specific age-standardized mortality rates using 3-year averages, mortality rate ratios between Black and White populations, excess Black deaths, and annual average percentage change in mortality rates and rate ratios. Results: The study included 26 295 827 death records. In 2016 to 2018, all-cause mortality rates ranged from 537 per 100 000 population in San Francisco to 1342 per 100 000 in Las Vegas compared with the overall US rate of 759 per 100 000. The all-cause mortality rate among Black populations was 24% higher than among White populations nationally (rate ratio, 1.236; 95% CI, 1.233 to 1.238), resulting in 74 402 excess Black deaths annually. At the city level, this ranged from 6 excess Black deaths in El Paso to 3804 excess Black deaths every year in Chicago. The US rate remained constant during the study period (average annual percentage change, -0.10%; 95% CI, -0.34% to 0.14%; P = .42). The racial inequities in rates for the US decreased between 2008 and 2019 (annual average percentage change, -0.51%; 95% CI, -0.92% to -0.09%; P =0.02). Only 14 of 30 cities (46.7%) experienced improvements in overall mortality rates during the past decade. Racial inequities increased in more cities (6 [20.0%]) than in which it decreased (2 [6.7%]). Conclusions and Relevance: In this study, mortality rates and inequities between Black and White populations varied substantially among the largest US cities. City leaders and other health advocates can use these types of local data on the burden of death and health inequities in their jurisdictions to increase awareness and advocacy related to racial health inequities, to guide the allocation of local resources, to monitor trends over time, and to highlight effective population health strategies.

Homicide Mortality Inequities in the 30 Biggest Cities in the U.S.

INTRODUCTION: Homicide is a leading cause of death across the U.S., and it disproportionally affects Blacks in urban areas. This study fills a gap in the literature by examining homicide mortality and Black-White homicide disparities in the 30 biggest U.S. cities and for the entire U.S. across 2 time periods (2008-2012 and 2013-2017). METHODS: Using data from the National Vital Statistics System for 2008-2017, this study calculated age-adjusted homicide mortality rates (per 100,000) for the total, White, and Black populations in the 30 biggest cities, and the U.S. Black-to-White rate ratios were calculated to examine homicide mortality across the time periods. Data were analyzed in 2020. RESULTS: A total of 26 cities were included in the final analysis. Results show that U.S. homicides increased slightly but significantly across the time periods (p<0.05). A total of 6 cities saw significant increases in homicides and 5 saw significant decreases. Homicide mortality rates were 1.8 times to >20 times greater for Blacks than for Whites, and these disparities persisted across the time periods for most cities. Only 2 of 26 cities had mortality rates and racial inequities in rates that were lower than the national average. CONCLUSIONS: Homicide mortality increased slightly across the U.S. and most cities from 2008 to 2017. The majority of cities faced high homicide mortality rates and large inequities. Black-White disparities in homicide remain substantial at the national and city levels. These findings can inform city leaders in their efforts to address the homicide, violence, and racial inequities associated with them through the implementation of policies and programs.

Extending the income inequality hypothesis: ecological results from the 2005 and 2009 Argentine National Risk Factor Surveys.

A consensus on income inequality as a social determinant of health is yet to be reached. In particular, we know little about the cross-sectional versus lagged effect of inequality and the robustness of the relationship to indicators that are sensitive to varying parts of the income spectrum. We test these issues with data from Argentina's 2005 and 2009 National Risk Factor Surveys. Inequality was operationalised at the provincial level with the Gini coefficient and the Generalised Entropy (GE) index. Population health was defined as the age-standardised percentage of adults with poor/fair self-rated health by province. Our cross-sectional results indicate a significant relationship between inequality (Gini) and poor health (r=0.58, p<0.01) in 2005. Using the GE index, a gradient pattern emerges in the correlation, and the r values increase as the index becomes sensitive to the top of the distribution. The relationship between 2005 inequality and 2009 health displays a similar pattern, but with generally smaller correlations than the 2005 cross-sectional results. Further advances in the income inequality and health literature require new theoretical models to account for how inequalities in different parts of the income spectrum may influence population health in different ways.

Socioeconomic status and tobacco consumption among adolescents: a multilevel analysis of Argentina's Global Youth Tobacco Survey.

INTRODUCTION: The relationship between poverty and tobacco consumption among adolescents has not been extensively studied, and what evidence exists has come almost entirely from developed countries. Moreover, the impact of contextual factors--such as school-level poverty--remains unclear. METHODS: We obtained information about smoking behavior from the Global Youth Tobacco Survey in Argentina in 2007. School-level characteristics were derived by matching schools to census areas from the 2001 Census. Additional school-level information was obtained from the Ministry of Education. Random intercept models were used to evaluate the associations of school-level variables (poverty in the census area of the school, school receipt of social assistance, and public or private status) with current smoking, intention to quit, secondhand smoke exposure outside the home, support for smoke-free laws, purchase of single cigarettes among smokers, and susceptibility to smoking in 5 years among nonsmokers. RESULTS: After controlling for age and sex, students attending schools receiving social assistance were more likely to smoke (odds ratio [OR] 1.35, 95% CI 1.02-1.80) and to purchase loose cigarettes (OR 1.66, 95% CI 1.08-2.54), whereas school poverty was significantly associated with secondhand smoke exposure (OR 1.27, 95% CI 1.04-1.58). CONCLUSION: This study shows that an association exists between unfavorable contextual school characteristics and tobacco consumption and related measures among youth in Argentina. Efforts to prevent smoking may need to address the school-level factors that place youth at higher risk.

Understanding the health transitions of immigrants to Canada: research priorities.

Understanding changes in the health of immigrants has been an important area of research in Canadian public health. Recent years have seen important developments, with studies moving away from what might be called 'sick immigrant' versus 'healthy immigrant' debates towards analyzing transitions and how they are influenced by a diverse set of social determinants. The release of data from all three waves of the Longitudinal Survey of Immigrants to Canada has also spurred new theoretical understandings of why immigrants' initial health advantage is lost over time, with the experience of discrimination becoming an increasingly important predictor. Three research priorities are emerging as particularly important in this area. These are the need for multilevel analyses that incorporate contextual effects, the need for comparative international studies, and the need to refine the conceptualization of race/ethnicity to take advantage of developments in social theory.

Understanding chronic non-communicable diseases in Latin America: towards an equity-based research agenda.

Although chronic non-communicable diseases are traditionally depicted as diseases of affluence, growing evidence suggests they strike along the fault lines of social inequality. The challenge of understanding how these conditions shape patterns of population health in Latin America requires an inter-disciplinary lens. This paper reviews the burden of chronic non-communicable diseases in the region and examines key myths surrounding their prevalence and distribution. It argues that a social justice approach rooted in the idea of health inequity needs to be at the core of research in this area, and concludes with discussion of a new approach to guide empirical research, the 'average/deprivation/inequality' framework.

Mitigating social and health inequities: community participation and Chagas disease in rural Argentina.

Chagas disease (CD) causes 12,500 deaths annually in Latin America. As a neglected disease primarily associated with poverty, it is a major driver of health inequity. Argentina's efforts to control vector transmission have been unsuccessful. Using new survey data (n=400 households), we compare the social patterning of the burden of CD by examining socio-demographic predictors of self-reported CD and the presence of vinchucas in two areas of rural northern Argentina known to have experienced different interventions in surveillance and control. Our analyses suggest that Avellaneda, an area known for horizontal intervention strategies which nurture community participation is quite distinct from Silipica, an area which has experienced a vertical intervention strategy since 1990. Avellaneda has higher level of self-reported Chagas infection and lower level of vinchuca presence; Silipica has pronounced and statistically significant differences patterned by the head of household's level of educational attainment. A greater awareness of the disease and its transmission, along with community mobilisation and spraying, may bring about more self-reported CD and less vinchuca presence in Avellaneda than in Silipica. This suggests that strategies based on community participation may be effective in reducing the social patterning of the burden of disease, even in poor places.

Immigration as pathogenic: a systematic review of the health of immigrants to Canada.

This review investigates the health of immigrants to Canada by critically examining differences in health status between immigrants and the native-born population and by tracing how the health of immigrants changes after settling in the country. Fifty-one published empirical studies met the inclusion criteria for this review. The analysis focuses on four inter-related questions: (1) Which health conditions show transition effects and which do not? (2) Do health transitions vary by ethnicity/racialized identity? (3) How are health transitions influenced by socioeconomic status? and (4) How do compositional and contextual factors interact to affect the health of immigrants? Theoretical and methodological challenges facing this area of research are discussed and future directions are identified. This area of research has the potential to develop into a complex, nuanced, and useful account of the social determinants of health as experienced by different groups in different places.

Desigualdad en el ingreso como determinante social de la salud / Income inequality as a social determinant of health

A pesar de la vasta literatura empírica, no se alcanzó un consenso respecto de los efectos en la salud derivados de la desigualdad en el ingreso. Este estudio se suma a los debates en curso y analiza la solidez de la relación entre la desigualdad del ingreso y la salud de la población en la Argentina, valiéndose de cinco índices diferentes para medir la desigualdad en el ingreso (cada uno de ellos, sensible a las desigualdades en las distintas partes del espectro del ingreso) y cinco mediciones de la salud de la población. Este trabajo está basado en la Encuesta de Condiciones de Vida (Argentina, 2001) y en las tasas provinciales de la esperanza de vida femenina y masculina, y la mortalidad infantil. El análisis muestra que la esperanza de vida se correlaciona en la dirección esperada con la desigualdad en el ingreso a nivel provincial (operacionalizada como el coeficiente de Gini) para hombres (r= -0,55, p < 0,01) y para mujeres (r= -0,61, p < 0,01). Sin embargo esta asociación no es sólida en los cinco índices de desigualdad en el ingreso. Por el contrario, la mortalidad infantil, la autopercepción del estado de salud y la limitación de la actividad informada por los individuos no se correlacionan con ninguno de los índices de desigualdad en el ingreso. Este artículo agrega mayor complejidad al estudio de los efectos en la salud derivados de la desigualdad en el ingreso y destaca la importancia de los efectos de las definiciones operacionales.

Despite a large body of empirical literature, a consensus has not been reached concerning the health effects of income inequality. This study contributes to ongoing debates by examining the robustness of the income inequality-population health relationship in Argentina, using five different income inequality indexes (each sensitive to inequalities in differing parts of the income spectrum) and five measures of population health. The study is based on an analysis of Argentina's 2001 Encuesta de Condiciones de Vida and provincial rates of male/female life expectancy and infant mortality. The analysis shows that life expectancy is correlated in the expected direction with provincial-level income inequality (operationalised as the Gini coefficient) for both males (r = -0.55, p < 0.01) and females (r = -0.61, p < 0.01), but this association is not robust to all five income inequality indexes. In contrast, infant mortality, self-reported poor health, and self-reported activity limitation are not correlated with any of the income inequality indexes. This study adds further complexity to the study of the health effects of income inequality, by highlighting the importance of effects of operational definitions.

The deterioration of health status among immigrants to Canada.

A growing body of literature suggests that immigrants to Canada experience deterioration in their health status after settling in the country. While self-selection processes and Canadian immigration policy ensure that, at the time of arrival, immigrants are healthier than the Canadian-born population, this health advantage does not persist over time. This study uses new data from the Longitudinal Survey of Immigrants to Canada (N=7720) to examine how health transitions vary among immigrants. Logistic regression analyses indicate that visible minorities and immigrants who experienced discrimination or unfair treatment are most likely to experience a decline in self-reported health status. The results also confirm a clear inverse socioeconomic gradient with respect to increasing levels of feelings of sadness, depression and loneliness. These findings reflect important dimensions driving population health patterns in Canada, a country with a highly lauded health care system based on the principles of universality and comprehensiveness. Our findings suggest that discrimination and inequality partly drive the health transitions of immigrants. These factors, which largely operate outside of the formal health care system, need to be understood and addressed if health inequities are to be reduced.

An average/deprivation/inequality (ADI) analysis of chronic disease outcomes and risk factors in Argentina.

BACKGROUND: Recognition of the global economic and epidemiological burden of chronic non-communicable diseases has increased in recent years. However, much of the research on this issue remains focused on individual-level risk factors and neglects the underlying social patterning of risk factors and disease outcomes. METHODS: Secondary analysis of Argentina's 2005 Encuesta Nacional de Factores de Riesgo (National Risk Factor Survey, N = 41,392) using a novel analytical strategy first proposed by the United Nations Development Programme (UNDP), which we here refer to as the Average/Deprivation/Inequality (ADI) framework. The analysis focuses on two risk factors (unhealthy diet and obesity) and one related disease outcome (diabetes), a notable health concern in Latin America. Logistic regression is used to examine the interplay between socioeconomic and demographic factors. The ADI analysis then uses the results from the logistic regression to identify the most deprived, the best-off, and the difference between the two ideal types. RESULTS: Overall, 19.9% of the sample reported being in poor/fair health, 35.3% reported not eating any fruits or vegetables in five days of the week preceding the interview, 14.7% had a BMI of 30 or greater, and 8.5% indicated that a health professional had told them that they have diabetes or high blood pressure. However, significant variation is hidden by these summary measures. Educational attainment displayed the strongest explanatory power throughout the models, followed by household income, with both factors highlighting the social patterning of risk factors and disease outcomes. As educational attainment and household income increase, the probability of poor health, unhealthy diet, obesity, and diabetes decrease. The analyses also point toward important provincial effects and reinforce the notion that both compositional factors (i.e., characteristics of individuals) and contextual factors (i.e., characteristics of places) are important in understanding the social patterning of chronic diseases. CONCLUSION: The application of the ADI framework enables identification of the regions or groups worst-off for each outcome measure under study. This can be used to highlight the variation embedded within national averages; as such, it encourages a social perspective on population health indicators that is particularly attuned to issues of inequity. The ADI framework is an important tool in the evaluation of policies aiming to prevent or control chronic non-communicable diseases.

Ecological analysis of the health effects of income inequality in Argentina.

OBJECTIVES: Despite a large body of empirical literature, a consensus has not been reached concerning the health effects of income inequality. This study contributes to ongoing debates by examining the robustness of the income inequality-population health relationship in Argentina, using five different income inequality indexes (each sensitive to inequalities in differing parts of the income spectrum) and five measures of population health. STUDY DESIGN: Cross-sectional, ecological study. METHODS: Income and self-reported morbidity data from Argentina's 2001 Encuesta de Condiciones de Vida (Survey of living conditions) were analysed at the provincial level. Provincial rates of male/female life expectancy and infant mortality were drawn from the Instituto Nacional de Estadistica y Censos database. RESULTS: Life expectancy was correlated in the expected direction with provincial-level income inequality (operationalized as the Gini coefficient) for both males (r=-0.55, P<0.01) and females (r=-0.61, P<0.01), but this association was not robust for all five income inequality indexes. In contrast, infant mortality, self-reported poor health and self-reported activity limitation were not correlated with any of the income inequality indexes. CONCLUSIONS: This study adds further complexity to the literature on the health effects of income inequality by highlighting the important effects of operational definitions. Mortality and morbidity data cannot be used as reasonably interchangeable variables (a common practice in this literature), and the choice of income inequality indicator may influence the results.

Income inequality measures.

The Gini coefficient has been the most popular method for operationalising income inequality in the public health literature. However, a number of alternative methods exist, and they offer researchers the means to develop a more nuanced understanding of the distribution of income. Income inequality measures such as the generalised entropy index and the Atkinson index offer the ability to examine the effects of inequalities in different areas of the income spectrum, enabling more meaningful quantitative assessments of qualitatively different inequalities. This glossary provides a conceptual introduction to these and other income inequality measures.