The Contribution of Health Care and Other Interventions to Black-White Disparities in Life Expectancy, 1980-2007

The Contribution of Health Care and Other Interventions to Black-White Disparities in Life Expectancy, 1980-2007
Population Research and Policy Review, Vol. 33, no. 1 (Feb 2014), pp. 97-126. doi: 10.1007/s11113-013-9309-2

Elo, I.T., H. Beltran-Sanchez, and J. Macinko

Black–white mortality disparities remain sizable in the United States. In this study, we use the concept of avoidable/amenable mortality to estimate cause-of-death contributions to the difference in life expectancy between whites and blacks by gender in the United States in 1980, 1993, and 2007. We begin with a review of the concept of “avoidable mortality” and results of prior studies using this cause-of-death classification. We then present the results of our empirical analyses. We classified causes of death as amenable to medical care, sensitive to public health policies and health behaviors, ischemic heart disease, suicide, HIV/AIDS, and all other causes combined. We used vital statistics data on deaths and Census Bureau population estimates and standard demographic decomposition techniques. In 2007, causes of death amenable to medical care continued to account for close to 2 years of the racial difference in life expectancy among men (2.08) and women (1.85). Causes amenable to public health interventions made a larger contribution to the racial difference in life expectancy among men (1.17 years) than women (0.08 years). The contribution of HIV/AIDS substantially widened the racial difference among both men (1.08 years) and women (0.42 years) in 1993, but its contribution declined over time. Despite progress observed over the time period studied, a substantial portion of black–white disparities in mortality could be reduced given more equitable access to medical care and health interventions.

Spatial Segmentation and the Black Middle Class

Spatial Segmentation and the Black Middle Class
American Journal of Sociology, Vol. 119 no. 4, pp. 903-54. The University of Chicago

Sharkey, P.

Ethnographic studies of the black middle class focus attention on the ways in which residential environments condition the experiences of different segments of the black class structure. This study places these arguments in a larger demographic context by providing a national analysis of neighborhood inequality and spatial inequality of different racial and ethnic groups in urban America. The findings show that there has been no change over time in the degree to which majority-black neighborhoods are surrounded by spatial disadvantage. Predominantly black neighborhoods, regardless of socioeconomic composition, continue to be spatially linked with areas of severe disadvantage. However, there has been substantial change in the degree to which middle- and upper-income African-American households have separated themselves from highly disadvantaged neighborhoods. These changes are driven primarily by the growing segment of middle- and upper-income African-Americans living in neighborhoods in which they are not the majority group, both in central cities and in suburbs.

Hospitalization for Ambulatory-care sensitive conditions (ACSC) in Ile de France: A view from across the Atlantic

Hospitalization for Ambulatory-care sensitive conditions (ACSC) in Ile de France: A view from across the Atlantic
Revue française des affaires sociales 2013/3 (n° 3)

Rodwin, V., Gusmano, M. and Weisz, D.

This article presents an indicator used in the United States and other OECD nations (hospitalizations for ambulatory-care sensitive conditions – ACSC) to assess access to primary care services and their capacity to handle a set of medical conditions before they require acute hospital treatment. Based on a study of Ile de France, which relies on residence-based hospital discharge data on patient diagnoses and treatments, the indicator identifies areas where hospitalizations for ACSC appear particularly high. Such hospital stays are considered potentially avoidable. Based on data from the Programme de m.dicalisation des syst.mes d’information (PMSI), disparities are measured. We rely on logistic regression analysis to identify a range of individual factors and neighborhood-level factors that explain these disparities. Access to primary care appears to be worse among residents in areas with average household income in the lowest quartile and among those hospitalized in public hospitals. This raises an important question for the future of health policy. Should areas with higher hospital discharge rates of ACSC be understood as having populations with poor health-seeking behaviors or health care systems not well enough organized to target higher-risk populations?

Mobility and the Metropolis

Mobility and the Metropolis
Washington, D.C.: The Economic Mobility Project, An Initiative of The Pew Charitable Trusts

Graham, B., and P. Sharkey

In a 2011 public opinion poll, The Pew Charitable Trusts asked Americans how important they thought a number of factors were in determining whether people in the United States get ahead or fall behind economically. More than 80 percent of respondents identified factors such as hard work, ambition, and access to education as key drivers of upward mobility, while less than half viewed growing up in a good neighborhood as an important factor. On the contrary, respondents strongly agreed that a young person with drive, ambition, and creativity growing up in a poor neighborhood is more likely to get ahead economically than someone growing up in a more affluent neighborhood who lacks those attributes.

Contrary to these perceptions, however, evidence is building that location actually matters a great deal and that Americans’ economic mobility prospects vary by state, locality, and even neighborhood.

For example, a 2009 Pew study indicated that a person who experienced high neighborhood poverty throughout childhood had a much higher risk of moving down the economic ladder as an adult. Other recent research examining mobility among metropolitan areas, including nearby towns and rural areas, showed that economic mobility varied widely across these localities. And, in a 2012, first-of-its-kind analysis of Americans’ economic mobility at the state level, Pew found that a number of states, primarily in the Mideast and New England regions, had higher mobility than the national average, and other states, primarily in the South, had lower mobility. 

This report adds to the growing body of research as it examines economic mobility across 96 U.S. metropolitan areas and the role of place in Americans’ prospects of moving up or down the economic ladder. It also offers insight on why and how location matters. Although a host of factors, such as state and local policies and labor market conditions, could influence mobility, this analysis considers one: neighborhood economic segregation, or the degree to which the poor and the wealthy live apart from each other. To begin to answer this question, Pew commissioned original research that, using three longitudinal data sets, measures differences in economic mobility across American metro areas over the last generation and identifies above-average-, average-, and below-average-mobility areas. The analysis then looks at whether metro areas’ rates of economic segregation are related to their rates of economic mobility.

Monitoring the pulse of hospital activity: Electronic health record utilization as a measure of care intensity

Monitoring the pulse of hospital activity: Electronic health record utilization as a measure of care intensity
Journal of Hospital Medicine, Vol. 8, no. 9, pp. 513-518. DOI: 10.1002/jhm.2068

Blecker, S., J.S. Austrian, D. Shine, R. Scott Braithwaite, M.J. Radford, and M.N. Gourevitch

Background: Hospital care on weekends has been associated with reduced quality and poor clinical outcomes, suggesting that decreases in overall intensity of care may have important clinical effects. We describe a new measure of hospital intensity of care based on utilization of the electronic health record (EHR).

Methods: We measured global intensity of care at our academic medical center by monitoring the use of the EHR in 2011. Our primary measure, termed EHR interactions, was the number of accessions of a patient's electronic record by a clinician, adjusted for hospital census, per unit of time. Our secondary measure was percent of total available central processing unit (CPU) power used to access EHR servers at a given time.

Results: EHR interactions were lower on weekend days as compared to weekdays at every hour (P < 0.0001), and the daytime peak in intensity noted each weekday was blunted on weekends. The relative rate and 95% confidence interval (CI) of census-adjusted record accessions per patient on weekdays compared with weekends were: 1.76 (95% CI: 1.74-1.77), 1.52 (95% CI: 1.50-1.55), and 1.14 (95% CI: 1.12-1.17) for day, morning/evening, and night hours, respectively. Percent CPU usage correlated closely with EHR interactions (r = 0.90).

Conclusions: EHR usage is a valid and easily reproducible measure of intensity of care in the hospital. Using this measure we identified large, hour-specific differences between weekend and weekday intensity. EHR interactions may serve as a useful measure for tracking and improving temporal variations in care that are common, and potentially deleterious, in hospital systems.

Disparities in access to health care in three French regions

Disparities in access to health care in three French regions
Health Policy, DOI 10.1016/j.healthpol.

Michael K. Gusmano, Daniel Weisz, Victor G. Rodwin, Jonas Lang, Meng Quian, Aurelie Bocquier, Veronique Moysan, Pierre Verger

Objectives: This paper compares access to primary and specialty care in three metropolitan regions of France: Ile de France (IDF), Nord-Pas-de-Calais (NPC) and Provence-Alpes-Côte d’Azur (PACA); and identifies the factors that contribute to disparities in access to care within and among these regions.

Methods: To assess access to primary care, we compare variation among residence-based, age-adjusted hospital discharge rates for ambulatory care sensitive conditions (ASC). To assess access on one dimension of specialty care, we compare residence-based, age- adjusted hospital discharge rates for revascularization – bypass surgery and angioplasty – among patients diagnosed with ischemic heart disease (IHD). In addition, for each region we rely on a multilevel generalized linear mixed effect model to identify a range of individual and area-level factors that affect the discharge rates for ASC and revascularization. Results: In comparison with other large metropolitan regions, in France, access to primary care is greater in Paris and its surrounding region (IDF) than in NPC but worse than in PACA. With regard to revascularization, after controlling for the burden of IHD, use of services is highest in PACA followed by IDF and NPC. In all three regions, disparities in access are much greater for revascularization than for ASC. Residents of low-income areas and those who are treated in public hospitals have poorer access to primary care and revascularizations. In addition, the odds of hospitalization for ASC and revascularization are higher for men. Finally, people who are treated in public hospitals, have poorer access to primary care and revascularization services than those who are admitted for ASC and revascularization services in private hospitals.

Conclusions: Within each region, we find significant income disparities among geographic areas in access to primary care as well as revascularization. Even within a national health insurance system that minimizes the financial barriers to health care and has one of the highest rates of spending on health care in Europe, the challenge of minimizing these disparities remains.

Why Do Higher Income Households Move Into Low Income Neighborhoods: Pioneering or Thrift?

Why Do Higher Income Households Move Into Low Income Neighborhoods: Pioneering or Thrift?
Urban Studies, September 2013; vol. 50, 12: pp. 2478-2495.

Ellen, Ingrid, Katherine O’Regan and Keren Horn

This paper offers several hypotheses about which US higher-income households choose to move into low-income neighbourhoods and why. It first explores whether the probability that a household moves into a relatively low-income neighbourhood (an RLIN move) varies with predicted household and metropolitan area characteristics. Secondly, it estimates a residential choice model to examine the housing and neighbourhood preferences of the households making such moves. Thirdly, it explores responses to survey questions about residential choices. Evidence is found that, in the US, households who place less value on neighbourhood services and those who face greater constraints on their choices are more likely to make an RLIN move. No evidence is found that households making RLIN moves are choosing neighbourhoods that are more accessible to employment. Rather, it is found that households making RLIN moves appear to place less weight on neighbourhood amenities than other households and more weight on housing costs.

Stuck in Place: Urban Neighborhoods and the End of Progress toward Racial Equality

Stuck in Place: Urban Neighborhoods and the End of Progress toward Racial Equality
University of Chicago Press

Sharkey, P.

In the 1960s, many believed that the civil rights movement’s successes would foster a new era of racial equality in America. Four decades later, the degree of racial inequality has barely changed. To understand what went wrong, Patrick Sharkey argues that we have to understand what has happened to African American communities over the last several decades. In Stuck in Place, Sharkey describes how political decisions and social policies have led to severe disinvestment from black neighborhoods, persistent segregation, declining economic opportunities, and a growing link between African American communities and the criminal justice system.

As a result, neighborhood inequality that existed in the 1970s has been passed down to the current generation of African Americans. Some of the most persistent forms of racial inequality, such as gaps in income and test scores, can only be explained by considering the neighborhoods in which black and white families have lived over multiple generations. This multigenerational nature of neighborhood inequality also means that a new kind of urban policy is necessary for our nation’s cities. Sharkey argues for urban policies that have the potential to create transformative and sustained changes in urban communities and the families that live within them, and he outlines a durable urban policy agenda to move in that direction.


Winner of the Mirra Komarovsky Book Award, Eastern Sociological Society.

Winner of The American Publishers Award for Professional and Scholarly Excellence (PROSE Award) in Sociology and Social Work. ​

A new approach to understanding racial disparities in prostate cancer treatment

A new approach to understanding racial disparities in prostate cancer treatment
Journal of Geriatric Oncology, Vol. 4, no. 1, pp. 1-8. DOI: 10.1016/j.jgo.2012.07.005

Presley, C.J., A.C. Raldow, L.D. Cramer, P.R. Soulos, J.B. Long, J.B. Yu, D.V. Makarov, and C.P. Gross

Objective: Previous studies addressing racial disparities in treatment for early-stage prostate cancer have focused on the etiology of undertreatment of black men. Our objective was to determine whether racial disparities are attributable to undertreatment, overtreatment, or both.

Methods: Using the SEER-Medicare dataset, we identified men 67–84 years-old diagnosed with localized prostate cancer from 1998 to 2007. We stratified men into clinical benefit groups using tumor aggressiveness and life expectancy. Low-benefit was defined as low-risk tumors and life expectancy < 10 years; high-benefit as moderate-risk tumors and life expectancy ≥ 10 years; all others were intermediate-benefit. Logistic regression modeled the association between race and treatment (radical prostatectomy or radiotherapy) across benefit groups.

Results: Of 68,817 men (9.8% black and 90.2% white), 56.2% of black and 66.3% of white men received treatment (adjusted odds ratio (OR) = 0.65; 95% CI, 0.62–0.69). The percent of low-, intermediate-, and high-benefit men who received treatment was 56.7%, 68.4%, and 79.6%, respectively (P = < 0.001). In the low-benefit group, 51.9% of black vs. 57.2% of white patients received treatment (OR = 0.74; 95% CI, 0.67–0.81) compared to 57.2% vs. 69.6% in the intermediate-benefit group (OR = 0.64; 95% CI, 0.59–0.70). Racial disparity was largest in the high-benefit group (64.2% of black vs. 81.4% of white patients received treatment; OR = 0.57; 95% CI, 0.48–0.68). The interaction between race and clinical benefit was significant (P < 0.001).

Conclusion: Racial disparities were largest among men most likely to benefit from treatment. However, a substantial proportion of both black and white men with a low clinical benefit received treatment, indicating a high level of overtreatment.

Who Experiences Discrimination in Brazil? Evidence From a Large Metropolitan Region

Who Experiences Discrimination in Brazil? Evidence From a Large Metropolitan Region
International Journal for Equity in Health, 2012 Dec 18;11:80. doi: 10.1186/1475-9276-11-80

Macinko, J., P. Mullachery, F.A. Proietti, and M.F. Lima-Costa

Introduction Perceived discrimination is related to poor health and has been offered as one explanation for the persistence of health inequalities in some societies. In this study, we explore the prevalence and correlates of perceived discrimination in a large, multiracial Brazilian metropolitan area.

Methods The study uses secondary analysis of a regionally representative household survey conducted in 2010 (n=12,213). Bivariate analyses and multiple logistic regression assess the magnitude and statistical significance of covariates associated with reports of any discrimination and with discrimination in specific settings, including when seeking healthcare services, in the work environment, in the family, in social occasions among friends or in public places, or in other situations.

Results Nearly 9% of the sample reported some type of discrimination. In multivariable models, reports of any discrimination were higher among people who identify as black versus white (OR 1.91), higher (OR 1.21) among women than men, higher (OR 1.33) among people in their 30’s and lower (OR 0.63) among older individuals. People with many health problems (OR 4.97) were more likely to report discrimination than those with few health problems. Subjective social status (OR 1.23) and low social trust (OR 1.27) were additional associated factors. Perceived discrimination experienced while seeking healthcare differed from all other types of discrimination, in that it was not associated with skin color, social status or trust, but was associated with sex, poverty, and poor health.

Conclusions There appear to be multiple factors associated with perceived discrimination in this population that may affect health. Policies and programs aimed at reducing discrimination in Brazil will likely need to address this wider set of interrelated risk factors across different populations.


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