Maureen R. Benjamins - Unequal Cities: Structural Racism and the Death Gap in Americas Largest Cities

UNEQUAL CITIES

HEALTH EQUITY IN AMERICA

Daniel E. Dawes, Series Editor

STRUCTURAL RACISM AND THE DEATH GAP IN AMERICAS LARGEST CITIES

Edited by Maureen R. Benjamins and Fernando G. De Maio

Foreword by Julie Morita

JOHNS HOPKINS UNIVERSITY PRESS | Baltimore

2021 Johns Hopkins University Press

All rights reserved. Published 2021

Printed in the United States of America on acid-free paper

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Library of Congress Cataloging-in-Publication Data

Names: Benjamins, Maureen R., editor. | De Maio, Fernando, 1976 editor.

Title: Unequal cities : structural racism and the death gap in Americas Largest Cities / edited by Maureen R. Benjamins, Fernando G. De Maio ; foreword by Julie Morita.

Description: Baltimore : Johns Hopkins University Press, [2021] | Series: Health equity in America | Includes bibliographical references and index.

Identifiers: LCCN 2020033843 | ISBN 9781421440996 (hardcover ; alk. paper) | ISBN 9781421441009 (ebook)

Subjects: MESH: Health Equity | Urban Health | Health Status Disparities | Healthcare Disparities | Race Factors | United States

Classification: LCC RA418 | NLM W 76 AA1 | DDC 362.1/042dc23

LC record available at https://lccn.loc.gov/2020033843

A catalog record for this book is available from the British Library.

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To a visionary advocate for social justice,
Steve Whitman, PhD, in memoriam

You know, its one thing to talk about data. But, I think, maybe its possible to get lost in the data; remember that this is literally a matter of life and death. I mean literally. Not as an expression.

Steve Whitman, PhD

Address to the MacLean Center for Clinical Medical Ethics at the University of Chicago, 2010

While complying with Illinoiss COVID-19 Stay at Home order during the spring of 2020, my heart sank as I listened to a report about the high percentage of COVID-19 deaths among Black Chicagoans. Specifically, while 29% of Chicagos population was Black, 70% of the recorded deaths were among Black residents. I was saddened by the news, but I was not surprised. This was not the first time that a public health emergency disproportionately affected Black residents of Chicago: during the 1989 measles epidemic, Black children made up more than 70% of Chicagos cases, In addition to Black Chicagoans having high poverty, unemployment, and uninsured rates, all of which limit their ability to comply with the public health measures recommended to prevent COVID-19 infections (e.g., avoid public transportation, work remotely), they have high rates of obesity, diabetes, and lung and heart disease, which are risk factors for severe illness or death from COVID-19. The COVID-19 pandemic and other public health crises expose the deep structural inequities that lead to the conditions that induce chronic, underlying poor health and contribute to dramatic disparities in morbidity and mortality.

As I listened to the COVID-19 story, the salience of the present volume was clear. This book details Black:white inequities in mortality, how these inequities vary across the 30 largest cities of the United States, and then dives deeper to examine inequities in the leading causes of death. Perhaps most importantly, the book is not just a description of the problemit goes beyond, to describe a community-based approach in Chicago intended to reduce the life expectancy gap in the city.

During the two decades I served as Immunization Program Medical Director, Chief Medical Officer, and Commissioner of the Chicago Department of Public Health (CDPH), addressing racial and ethnic health disparities was among the departments top priorities. We were able to focus on these disparities because we had access to and the ability to analyze data that revealed the disparities. Shortly after starting at CDPH in 1999, I joined a team of public health workers and community members in a door-to-door survey designed to determine childhood immunization coverage levels in one of Chicagos South Side neighborhoods. The survey revealed a dramatic difference in immunization coverage levels of this predominately Black neighborhood when compared to citywide levels. Although federal and state programs had eliminated financial barriers to vaccines, other barriers persisted. We used the neighborhood coverage levels to address these barriers strategically; we opened immunization-only clinics, ran public awareness campaigns, helped health care providers establish reminder systems, and operated case management programs in the areas with the lowest coverage levels. Granular data informed how and where we directed our resources.

The household survey made clear the immunization coverage disparities, and it also opened my eyes to other striking inequities among Chicago neighborhoods. It revealed the poverty, poor housing quality, lack of public transportation, and competing priorities experienced by many South Side parents compared to the experiences of my North Side neighbors. In subsequent years, we used city- and neighborhood-level data to inform HIV prevention efforts and to respond to meningococcal disease and hepatitis A outbreaks. And yet, few of our interventions addressed the structural or social factors that contributed to increased disease rates or disparities. Although our disease-specific interventions led to modest success in decreasing health disparities, city- and neighborhood-level data revealed persistent disparities in chronic health conditions.

This prompted the department to begin focusing on addressing health equity by eliminating systemic barriers to health such as poverty and lack of access to good jobs, quality education and housing, safe environments, and health care. In 2015, CDPH and our partners committed to addressing the social determinants of health in our community health improvement plan, Healthy Chicago 2.0. This plan incorporated quantitative and qualitative data, highlighted the critical role that social and economic factors (e.g., housing, education, transportation) play in health, reflected evidence-based approaches for addressing health challenges, and utilized a process for cross-sector partners and community members to contribute to plan development and implementation.

Citywide and neighborhood-level data served CDPH well. We used maps comparing life expectancy among neighborhoods to raise awareness among key decision makers, including elected officials, about the inequity that exists in Chicago neighborhoods. We also used maps of neighborhoods with the lowest levels of socioeconomic opportunity for children and overlaid them on maps of neighborhoods with the poorest health outcomes for nontraditional partners in education, parks and recreation, housing, and transportation to demonstrate the relationship between their work and the health and well-being of Chicagoans. CDPH and our partners continuously tapped into city-level data to monitor progress toward achieving the Healthy Chicago 2.0 goals and to inform the next 5-year plan, Healthy Chicago 2025. Unfortunately, not all cities have access to local data like Chicago does. For the largest cities in the United States, the Centers for Disease Control and Prevention (CDC) and other federal agencies provide important data on health behaviors, chronic conditions, and other health outcomes at the city level through initiatives like the National Immunization Survey and the Behavioral Risk Factor Surveillance System (for youth and adults). In addition, the largest US cities (e.g., New York, Los Angeles, and Chicago) have the resources to operate population-based surveys that provide city- and neighborhood-level estimates of health concerns and social, environmental, and neighborhood factors associated with health. Having access to local-level morbidity and mortality data allows public health agencies to identify and focus their resources on populations and communities at greatest risk for poor health outcomes. Unfortunately, as the COVID-19 pandemic underscored, there is wide variability in data quality and availability at the state, county, and city levels. This lack of consistently available, high-quality data contributed to inconsistent coordination and execution of public health responses.