Racism and health: segregation and causes of death amenable to medical intervention in major U.S. cities

Association of racial residential segregation with all-cause and cancer-specific mortality in the reasons for geographic and racial differences in stroke (REGARDS) cohort study

•Increased racial residential segregation increased the risk of all-cause mortality among White participants.•Higher interaction lowered the risk of all-cause mortality among White participants.•Higher isolation lowered the risk of cancer mortality among Black participants.

Racial-Ethnic Residential Clustering and Early COVID-19 Vaccine Allocations in Five Urban Texas Counties

Previous research has indicated that racial-ethnic minority communities lack a wide variety of health-related organizations. We examine how this relates to the early COVID-19 vaccine rollout. In a series of spatial error and linear growth models, we analyze how racial-ethnic residential segregation is associated with the distribution of vaccine sites and vaccine doses across ZIP codes in the five largest urban counties in Texas. We find that Black and Latino clustered ZIP codes are less likely to have vaccine distribution sites and that this disparity is partially explained by the lack of hospitals and physicians' offices in these areas. Moreover, Black clustering is also negatively related to the number of allocated vaccine doses, and again, this is largely explained by the unequal distribution of health care resources. These results suggest that extant disparities in service provision are key to understanding racial-ethnic inequality in an acute crisis like the COVID-19 pandemic.

Relationship between Residential Segregation, Later-Life Cognition, and Incident Dementia across Race/Ethnicity

Systemic racism leads to racial/ethnic residential segregation, which can result in health inequities. We examined if the associations between residential segregation and later-life cognition and dementia differed based on segregation measure and by participant race/ethnicity. Tests of memory (n = 4616), language (n = 4333), visuospatial abilities (n = 4557), and incident dementia (n = 4556) were analyzed in older residents of Northern Manhattan, New York (mean age: 75.7 years). Segregation was measured at the block group-level using three indices: dissimilarity, isolation, and interaction. We fit multilevel linear or Cox proportional hazards models and included a race/ethnicity × segregation term to test for differential associations, adjusting for socioeconomic and health factors. Living in block groups with higher proportions of minoritized people was associated with -0.05 SD lower language scores. Living in block groups with higher potential contact between racial/ethnic groups was associated with 0.06-0.1 SD higher language scores. The findings were less pronounced for other cognitive domains and for incident dementia. Non-Hispanic Black adults were most likely to experience negative effects of neighborhood segregation on cognition (language and memory) and dementia. All indices partly capture downstream effects of structural racism (i.e., unequal distributions of wealth/resources) on cognition. Therefore, desegregation and equitable access to resources have the potential to improve later-life cognitive health.

Using machine learning to estimate the effect of racial segregation on COVID-19 mortality in the United States

This study examines the role that racial residential segregation has played in shaping the spread of COVID-19 in the United States as of September 30, 2020. The analysis focuses on the effects of racial residential segregation on mortality and infection rates for the overall population and on racial and ethnic mortality gaps. To account for potential confounding, I assemble a dataset that includes 50 county-level factors that are potentially related to residential segregation and COVID-19 infection and mortality rates. These factors are grouped into eight categories: demographics, density and potential for public interaction, social capital, health risk factors, capacity of the health care system, air pollution, employment in essential businesses, and political views. I use double-lasso regression, a machine learning method for model selection and inference, to select the most important controls in a statistically principled manner. Counties that are 1 SD above the racial segregation mean have experienced mortality and infection rates that are 8% and 5% higher than the mean. These differences represent an average of four additional deaths and 105 additional infections for each 100,000 residents in the county. The analysis of mortality gaps shows that, in counties that are 1 SD above the Black-White segregation mean, the Black mortality rate is 8% higher than the White mortality rate. Sensitivity analyses show that an unmeasured confounder that would overturn these findings is outside the range of plausible covariates.

Cancer Pain in Relation to Metropolitan Area Segregation and Nursing Home Racial and Ethnic Composition

OBJECTIVES

To estimate pain reporting among residents with cancer in relation to metropolitan area segregation and NH racial and ethnic composition.

DESIGN

Cross-sectional study.

SETTING AND PARTICIPANTS

383,757 newly admitted black (B), Hispanic (H), or white (W) residents with cancer in 12,096 US NHs (2011-2013).

METHODS

Using the Minimum Data Set 3.0, pain in past 5 days was determined by self-report or use of pain management. The Theil entropy index, a measure of metropolitan area segregation, was categorized [high (up to 0.20), very high (0.20-0.30), or extreme (0.30-0.53)].

RESULTS

Pain prevalence decreased across segregation level (black: high = 77%, very high = 75%, extreme = 72%; Hispanic: high = 79%, very high = 77%, extreme = 70%; white: high = 80%, very high = 77%, extreme = 74%). In extremely segregated areas, all residents were less likely to have recorded pain [adjusted prevalence ratios: blacks, 4.6% less likely, 95% confidence interval (CI) 3.1%-6.1%; Hispanics, 6.9% less likely, 95% CI 4.2%-9.6%; whites, 7.4% less likely, 95% CI 6.5%-8.2%] than in the least segregated areas. At all segregation levels, pain was recorded more frequently for residents (black or white) in predominantly white (>80%) NHs than in mostly black (>50%) NHs or residents (Hispanic or white) in predominantly white NHs than mostly Hispanic (>50%) NHs.

CONCLUSIONS AND IMPLICATIONS

We observed decreased pain recording in metropolitan areas with greater racial and ethnic segregation. This may occur through the inequitable distribution of resources between NHs, resident-provider empathy, provider implicit bias, resident trust, and other factors.

Neighborhood context and non-small cell lung cancer outcomes in Florida non-elderly patients by race/ethnicity

OBJECTIVE

The purpose of this study was to investigate the relationship between neighborhood environment and lung cancer outcomes among Florida residents younger than 65 years of age.

METHODS AND MATERIALS

This was a retrospective cohort study that included patients diagnosed with non-small cell lung cancer (NSCLC) in Florida from January 2005 to December 2014 (n = 22,750). Multi-level, mixed-effect logistic regression models were used for two outcomes: receipt of treatment and receipt of surgery. Survival analyses, using proportional subdistribution hazard models, were conducted to examine the impact of neighborhood characteristics on risk of death due to lung cancer with adjustment for individual-level variables. Neighborhood exposures of interest were census tract level black and Hispanic segregation combined with economic deprivation.

RESULTS

White patients who lived in low black segregation/high deprivation areas had 15 % lower odds of receiving surgery (95 % CI: 0.76-0.93). However, the likelihood of receiving surgery for black patients who lived in high black segregation/low deprivation and high black segregation/high deprivation was lower than for black patients who lived in low black segregation/low deprivation neighborhoods (level 3 AOR = 0.56 [0.38-0.85]; level 4 AOR = 0.69 [0.54-0.88]). Living in suburban and rural areas increased the risk of lung cancer death for white patients by 14 % (95 % CI: 1.05-1.24) and 26 % (95 % CI: 1.08-1.46), respectively. Living in rural areas increased the risk of death for black patients by 54 % r (SHR = 1.54 [1.19-2.0]). Black patients who live in high Hispanic segregation/high deprivation had 36 % increased risk of death compared to black patients who lived in low Hispanic segregation/low deprivation areas.

CONCLUSION

This study suggests that when investigating cancer disparities, merely adjusting for race/ethnicity does not provide sufficient explanation to understand survival and treatment variations. Lung cancer outcomes are impacted by neighborhood environments that are formed based on the distribution of race, ethnicity and class.

Separate and Sick: Residential Segregation and the Health of Children and Youth in Metropolitan Statistical Areas

The purpose of this study was to better understand residential segregation and child/youth health by examining the relationship between a measure of Black-White residential segregation, the index of dissimilarity, and a suite of child and youth health measures in 235 U.S. metropolitan statistical areas (MSAs). MSAs are urban areas with a population of 50,000 or more and adjacent communities that share a high degree of economic and social integration. MSAs are defined by the Office of Management and Budget. Health-related measures included child mortality (CDC WONDER), teen births (NCHS natality data), children in poverty (SAIPE program), and disconnected youth (Measure of America). Simple linear regression and two-level hierarchical linear regression models, controlling for income, total population, % Black, and census region, examined the association between segregation and Black health, White health, and Black-White disparities in health. As segregation increased, Black children and youth had worse health across all four measures, regardless of MSA total and Black population size. White children and youth in small MSAs with large Black populations had worse levels of disconnected youth and teen births with increasing segregation, but no associations were found for White children and youth in other MSAs. Segregation worsened Black-White health disparities across all four measures, regardless of MSA total and Black population size. Segregation adversely affects the health of Black children in all MSAs and White children in smaller MSAs with large Black populations, and these effects are seen in measures that span all of childhood. Residential segregation may be an important target to consider in efforts to improve neighborhood conditions that influence the health of families and children.

The Role of Racial Residential Segregation in Black-White Disparities in Firearm Homicide at the State Level in the United States, 1991-2015

OBJECTIVE

To investigate the relationship between racial residential segregation and differences in Black-White disparities in overall firearm homicides across U.S states.

METHODS

Using a linear regression, we evaluated the relationship between racial residential segregation, as measured by the index of dissimilarity, and the Black-White firearm homicide disparity ratio in 32 states over the period 1991-2015. To account for clustering of observations within states, we used a generalized estimating equations approach.

RESULTS

After controlling for measures of White and Black deprivation, multivariate analysis showed that racial segregation was positively associated with the Black-White firearm homicide disparity. For each 10-point increase in the index of dissimilarity, the ratio of Black to White firearm homicide rates in a state increased by 39%. After controlling for levels of White and Black deprivation, racial segregation remained negatively associated with White firearm homicide rates and positively associated with Black firearm homicide rates.

CONCLUSIONS

These findings suggest that racial segregation may increase the disparity in firearm homicide between the Black and White population.

The Effects of Residential Segregation and Neighborhood Characteristics on Surgery and Survival in Patients with Early-Stage Non-Small Cell Lung Cancer

BACKGROUND

Although the negative effects of lower socioeconomic status on non-small cell lung cancer (NSCLC) treatment and survival have been widely studied, the impact of residential segregation on prognosis and the receipt of treatment has yet to be determined.

METHODS

This is a retrospective, cohort study of NSCLC patients in Georgia (2000-2009; n = 8,322) using data from the Georgia Comprehensive Cancer Registry. The effects of segregation, economic deprivation, and combined segregation/deprivation on the odds of receiving surgery were examined in separate multilevel models. To determine the association for the exposures of interest on the risk of death for different racial groups, separate multilevel survival models were conducted for black and white patients.

RESULTS

Living in areas with the highest [AOR = 0.35, 95% confidence interval (CI), 0.19-0.64] and second highest (AOR = 0.37, 95% CI, 0.20-0.68) levels of segregation was associated with decreased odds of receipt of surgery. Black patients living in areas with high residential segregation and high economic deprivation were 31% (95% CI, 1.04-1.66) more likely to die, even after surgery was controlled for. For white patients, economic deprivation was associated with decreased odds of surgery but not survival. Segregation had no effect.

CONCLUSION

Our findings suggest how black and white individuals experience segregation and area-level poverty is likely different leading to differences in adverse health outcomes.

IMPACT

Identifying neighborhood characteristics impacting health outcomes within different racial groups could help reduce health disparities across racial groups by implementing targeted policies and interventions. Cancer Epidemiol Biomarkers Prev; 25(5); 750-8. ©2016 AACR.

Stress and the kidney

The prevalence of CKD has increased considerably over the past 2 decades. The rising rates of CKD have been attributed to known comorbidities such as diabetes, hypertension, and obesity; however, recent research has begun to explore the degree to which social, economic, and psychological factors have implications for the prevalence and progression of CKD, especially among high-risk populations such as African Americans. It has been suggested that stress can have implications for CKD, but this area of research has been largely unexplored. One contributing factor associated with the paucity of research on CKD is that many of the social, psychological, and environmental stressors cannot be recreated or simulated in a laboratory setting. Social science has established that stress can have implications for health, and we believe that stress is an important determinant of the development and progression of CKD. We draw heavily from the social scientific and social epidemiologic literature to present an intersectional conceptual frame specifying how stress can have implications for kidney disease, its progression, and its complications through multiple stressors and pathways.

Neighborhood-level racial/ethnic residential segregation and incident cardiovascular disease: the multi-ethnic study of atherosclerosis

BACKGROUND

Previous research suggests that neighborhood-level racial/ethnic residential segregation is linked to health, but it has not been studied prospectively in relation to cardiovascular disease (CVD).

METHODS AND RESULTS

Participants were 1595 non-Hispanic black, 2345 non-Hispanic white, and 1289 Hispanic adults from the Multi-Ethnic Study of Atherosclerosis free of CVD at baseline (aged 45-84 years). Own-group racial/ethnic residential segregation was assessed by using the Gi* statistic, a measure of how the neighborhood racial/ethnic composition deviates from surrounding counties' racial/ethnic composition. Multivariable Cox proportional hazards modeling was used to estimate hazard ratios for incident CVD (first definite angina, probable angina followed by revascularization, myocardial infarction, resuscitated cardiac arrest, coronary heart disease death, stroke, or stroke death) over 10.2 median years of follow-up. Among blacks, each standard deviation increase in black segregation was associated with a 12% higher hazard of developing CVD after adjusting for demographics (95% confidence interval, 1.02-1.22). This association persisted after adjustment for neighborhood-level characteristics, individual socioeconomic position, and CVD risk factors (hazard ratio, 1.12; 95% confidence interval, 1.02-1.23). For whites, higher white segregation was associated with lower CVD risk after adjusting for demographics (hazard ratio, 0.88; 95% confidence interval, 0.81-0.96), but not after further adjustment for neighborhood characteristics. Segregation was not associated with CVD risk among Hispanics. Similar results were obtained after adjusting for time-varying segregation and covariates.

CONCLUSIONS

The association of residential segregation with cardiovascular risk varies according to race/ethnicity. Further work is needed to better characterize the individual- and neighborhood-level pathways linking segregation to CVD risk.

Capturing the two dimensions of residential segregation at the neighborhood level for health research

Two conceptual and methodological foundations of segregation studies are that (i) segregation involves more than one group, and (ii) segregation measures need to quantify how different population groups are distributed across space. Therefore, percentage of population belonging to a group is not an appropriate measure of segregation because it does not describe how populations are spread across different areal units or neighborhoods. In principle, evenness and isolation are the two distinct dimensions of segregation that capture the spatial patterns of population groups. To portray people’s daily environment more accurately, segregation measures need to account for the spatial relationships between areal units and to reflect the situations at the neighborhood scale. For these reasons, the use of local spatial entropy-based diversity index (SH_i) and local spatial isolation index (S_i) to capture the evenness and isolation dimensions of segregation, respectively, are preferable. However, these two local spatial segregation indexes have rarely been incorporated into health research. Rather ineffective and insufficient segregation measures have been used in previous studies. Hence, this paper empirically demonstrates how the two measures can reflect the two distinct dimensions of segregation at the neighborhood level, and argues conceptually and set the stage for their future use to effectively and meaningfully examine the relationships between residential segregation and health.

Residential segregation and the health of African-American infants: does the effect vary by prevalence?

Segregation effects may vary between areas (e.g., counties) of low and high low birth weight (LBW; <2,500 g) and preterm birth (PTB; <37 weeks of gestation) rates due to interactions with area differences in risks and resources. We assess whether the effects of residential segregation on county-level LBW and PTB rates for African-American infants vary by the prevalence of these conditions. The study sample includes 368 counties of 100,000 or more residents and at least 50 African-American live births in 2000. Residentially segregated counties are identified alternatively by county-level dissimilarity and isolation indices. Quantile regression is used to assess how residential segregation affects the entire distributions of county-level LBW and PTB rates (i.e. by prevalence). Residential segregation increases LBW and PTB rates significantly in areas of low prevalence, but has no such effects for areas of high prevalence. As a sensitivity analysis, we use metropolitan statistical area level data and obtain similar results. Our findings suggest that residential segregation has adverse effects mainly in areas of low prevalence of LBW and preterm birth, which are expected overall to have fewer risk factors and more resources for infant health, but not in high prevalence areas, which are expected to have more risk factors and fewer resources. Residential policies aimed at area resource improvements may be more effective.

Integration of social epidemiology and community-engaged interventions to improve health equity

The past quarter century has seen an explosion of concern about widening health inequities in the United States and worldwide. These inequities are central to the research mission in 2 arenas of public health: social epidemiology and community-engaged interventions. Yet only modest success has been achieved in eliminating health inequities. We advocate dialogue and reciprocal learning between researchers with these 2 perspectives to enhance emerging transdisciplinary language, support new approaches to identifying research questions, and apply integrated theories and methods. We recommend ways to promote transdisciplinary training, practice, and research through creative academic opportunities as well as new funding and structural mechanisms.

Metropolitan isolation segregation and Black-White disparities in very preterm birth: a test of mediating pathways and variance explained

Residential isolation segregation (a measure of residential inter-racial exposure) has been associated with rates of preterm birth (<37 weeks gestation) experienced by Black women. Epidemiologic differences between very preterm (<32 weeks gestation) and moderately preterm births (32-36 weeks) raise questions about whether this association is similar across gestational ages, and through what pathways it might be mediated. Hierarchical Bayesian models were fit to answer three questions: is the isolation-prematurity association similar for very and moderately preterm birth; is this association mediated by maternal chronic disease, socioeconomic status, or metropolitan area crime and poverty rates; and how much of the geographic variation in Black-White very preterm birth disparities is explained by isolation segregation? Singleton births to Black and White women in 231 U.S. metropolitan statistical areas in 2000-2002 were analyzed and isolation segregation was calculated for each. We found that among Black women, isolation is associated with very preterm birth and moderately preterm birth. The association may be partially mediated by individual level socioeconomic characteristics and metropolitan level violent crime rates. There is no association between segregation and prematurity among White women. Isolation segregation explains 28% of the geographic variation in Black-White very preterm birth disparities. Our findings highlight the importance of isolation segregation for the high-burden outcome of very preterm birth, but unexplained excess risk for prematurity among Black women is substantial.

Association of socioeconomic status and CKD among African Americans: the Jackson Heart Study

BACKGROUND

Socioeconomic status (SES) is recognized as a key social environmental factor because it has implications for access to resources that help individuals care for themselves and others. Few studies have examined the association of SES with chronic kidney disease (CKD) in high-risk populations.

STUDY DESIGN

Single-site longitudinal population-based cohort.

SETTING & PARTICIPANTS

Data for this study were drawn from the baseline examination of the Jackson Heart Study. The analytic cohort consisted of 3,430 African American men and women living in the tricounty region of the Jackson, MS, metropolitan area with complete data to determine CKD status.

PREDICTOR

High SES (defined as having a family income at least 3.5 times the poverty level or having at least 1 undergraduate degree).

OUTCOMES & MEASUREMENTS

CKD (defined as the presence of albuminuria or decreased estimated glomerular filtration rate [<60 mL/min/1.73 m(2)]). Associations were explored using bivariable analyses and multivariable logistic regression analyses adjusting for CKD and cardiovascular disease risk factors, as well as demographic factors.

RESULTS

The prevalence of CKD in the Jackson Heart Study was 20% (865 of 3,430 participants). Proportions of the Jackson Heart Study cohort with albuminuria and decreased estimated glomerular filtration rate were 12.5% (429 of 3,430 participants) and 10.1% (347 of 3,430 participants), respectively. High SES was associated inversely with CKD. The odds of having CKD were 41% lower for affluent participants than their less affluent counterparts. There were no statistically significant interactions between sex and education or income, although subgroup analysis showed that high income was associated with CKD in men (OR, 0.47; 95% CI, 0.23-0.97), but not women (OR, 0.64; 95% CI, 0.40-1.03).

LIMITATIONS

Models were estimated using cross-sectional data.

CONCLUSION

CKD is associated with SES. Additional research is needed to elucidate the impact of wealth and social contexts in which individuals are embedded and the mediating effects of sociocultural factors.

Is segregation bad for your health?

For decades, racial residential segregation has been observed to vary with health outcomes for African Americans, although only recently has interest increased in the public health literature. Utilizing a systematic review of the health and social science literature, the authors consider the segregation-health association through the lens of 4 questions of interest to epidemiologists: How is segregation best measured? Is the segregation-health association socially or biologically plausible? What evidence is there of segregation-health associations? Is segregation a modifiable risk factor? Thirty-nine identified studies test an association between segregation and health outcomes. The health effects of segregation are relatively consistent, but complex. Isolation segregation is associated with poor pregnancy outcomes and increased mortality for blacks, but several studies report health-protective effects of living in clustered black neighborhoods net of social and economic isolation. The majority of reviewed studies are cross-sectional and use coarse measures of segregation. Future work should extend recent developments in measuring and conceptualizing segregation in a multilevel framework, build upon the findings and challenges in the neighborhood-effects literature, and utilize longitudinal data sources to illuminate opportunities for public health action to reduce racial disparities in disease.

Social environmental stressors, psychological factors, and kidney disease

Kidney disease is one of the most striking examples of health disparities in American public health. Disparities in the prevalence and progression of kidney disease are generally thought to be a function of group differences in the prevalence of kidney disease risk factors such as diabetes, hypertension, and obesity. However, the presence of these comorbidities does not completely explain the elevated rate of progression from chronic kidney disease (CKD) to end-stage renal disease among high-risk populations such as African Americans. We believe that the social environment is an important element in the pathway from CKD risk factors to CKD and end-stage renal disease. This review of the literature draws heavily from social science and social epidemiology to present a conceptual frame specifying how social, economic, and psychosocial factors interact to affect the risks for and the progression of kidney disease.

The dynamics of income and neighborhood context for population health: do long-term measures of socioeconomic status explain more of the black/white health disparity than single-point-in-time measures?

Socioeconomic status, though a robust and strong predictor of health, has generally been unable to fully explain the health gap between blacks and whites in the United States. However, at both the individual and neighborhood levels, socioeconomic status is often treated as a static factor with only single-point-in-time measurements. These cross-sectional measures fail to account for possible heterogeneous histories within groups who may share similar characteristics at a given point in time. As such, ignoring the dynamic nature of socioeconomic status may lead to the underestimation of its importance in explaining health and racial health disparities. In this study, I use national longitudinal data to investigate the relationship between neighborhood poverty and respondent-rated health, focusing on whether the addition of a temporal dimension reveals a stronger relationship between neighborhood poverty and health, and a greater explanatory power for the health gap between blacks and whites. Results indicate that long-term neighborhood measures are stronger predictors of health outcomes and explain a greater amount of the black/white health gap than single-point measures.

Health through the urban lens

Cities are now the major sites of human habitation worldwide, a trend that will continue for the foreseeable future, not only in the developed world but in developing countries. Urban residence impacts health and health prospects both positively and negatively through a complex mix of exposures and mechanisms. In addition, cities concentrate population subsets of various demographic, economic, and social characteristics, some with particular health risks and vulnerabilities. Looking at health through the urban lens allows increased understanding of disparate risks and emphasizes the essentiality of collaborative efforts in protecting and enhancing the health of populations, especially those living in cities.

Measuring managed care and its environment using national surveys: a review and assessment

Measuring the characteristics of managed care plans and of the health care markets in which the plans operate is a complex undertaking. Based on a previously developed framework of health plan factors, we review measures of managed care plans and the characteristics of the area in which an individual resides using two national surveys, the Medical Expenditure Panel Survey (MEPS) and the National Health Interview Survey (NHIS), and other data sources such as the Area Resources File and the United States census. We provide empirical applications of these measures and also discuss common analytical issues that should be considered. Despite the many analytical challenges presented by these complex surveys, the MEPS and NHIS are rich sources of data for examining the impact of health plans and the characteristics of markets or areas on health care expenditures and outcomes.

Racism and health: The relationship between experience of racial discrimination and health in New Zealand

Accumulating research suggests that racism may be a major determinant of health. Here we report associations between self-reported experience of racial discrimination and health in New Zealand. Data from the 2002/2003 New Zealand Health Survey, a cross-sectional survey involving face-to-face interviews with 12,500 people, were analysed. Five items were included to capture racial discrimination in two dimensions: experience of ethnically motivated attack (physical or verbal), or unfair treatment because of ethnicity (by a health professional, in work or when gaining housing). Ethnicity was classified using self-identification to one of four ethnic groups: Māori, Pacific, Asian and European/Other peoples. Logistic regression, accounting for the survey design, age, sex, ethnicity and deprivation, was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Māori reported the highest prevalence of "ever" experiencing any of the forms of racial discrimination (34%), followed by similar levels among Asian (28%) and Pacific peoples (25%). Māori were almost 10 times more likely to experience multiple types of discrimination compared to European/Others (4.5% vs. 0.5%). Reported experience of racial discrimination was associated with each of the measures of health examined. Experience of any one of the five types of discrimination was significantly associated with poor or fair self-rated health; lower physical functioning; lower mental health; smoking; and cardiovascular disease. There was strong evidence of a dose-response relationship between the number of reported types of discrimination and each health measure. These results highlight the need for racism to be considered in efforts to eliminate ethnic inequalities in health.

Evaluating Chicago's success in reaching the Healthy People 2000 goal of reducing health disparities

OBJECTIVE

This study was designed to assess Chicago's progress from 1980 to 1998 in addressing the Healthy People 2000 goal of reducing health disparities.

METHODS

Chicago vital statistics and surveillance data were used to calculate black:white rate ratios of mortality and morbidity for 1980-1998. Mortality and morbidity rate ratios were also used to compare people living in areas with the lowest median household income with those living in the highest for 1979-1981, 1991-1993, and 1996-1998. The health measures included mortality associated with leading causes of death; all-cause mortality, incidence rates for two communicable diseases; and two birth outcomes.

RESULTS

Both black:white and low-income:high-income rate ratios monotonically increased for virtually all measures of mortality and morbidity. Almost all of the rate ratios and linear trends were statistically significant. From 1980 to 1998, the black:white rate ratio for all-cause mortality increased by 57% to 2.03. From 1979-1981 to 1996-1998, the low-income:high-income rate ratio for all-cause mortality increased by 56% to 2.68.

CONCLUSIONS

These findings provide clear evidence that disparities in health did not decrease in Chicago. Instead, racial and economic disparities increased for almost all measures of mortality and morbidity used in this study. The fact that the Healthy People 2000 campaign to reduce and then eliminate health disparities was not effective must serve as a stimulus for improved strategies.

Evaluating Chicago's success in reaching the Healthy People 2000 goal of reducing health disparities

OBJECTIVE

This study was designed to assess Chicago's progress from 1980 to 1998 in addressing the Healthy People 2000 goal of reducing health disparities.

METHODS

Chicago vital statistics and surveillance data were used to calculate black:white rate ratios of mortality and morbidity for 1980-1998. Mortality and morbidity rate ratios were also used to compare people living in areas with the lowest median household income with those living in the highest for 1979-1981, 1991-1993, and 1996-1998. The health measures included mortality associated with leading causes of death; all-cause mortality, incidence rates for two communicable diseases; and two birth outcomes.

RESULTS

Both black:white and low-income:high-income rate ratios monotonically increased for virtually all measures of mortality and morbidity. Almost all of the rate ratios and linear trends were statistically significant. From 1980 to 1998, the black:white rate ratio for all-cause mortality increased by 57% to 2.03. From 1979-1981 to 1996-1998, the low-income:high-income rate ratio for all-cause mortality increased by 56% to 2.68.

CONCLUSIONS

These findings provide clear evidence that disparities in health did not decrease in Chicago. Instead, racial and economic disparities increased for almost all measures of mortality and morbidity used in this study. The fact that the Healthy People 2000 campaign to reduce and then eliminate health disparities was not effective must serve as a stimulus for improved strategies.