Discriminatory housing policies from the past may still have an impact on heart disease risk factors and outcomes today.
More than 60 years after they were outlawed, the historical discriminatory housing practices known as “redlining” are still connected to heart disease and related risk factors in the affected districts, according to a study recently published in the Journal of the American College of Cardiology. Health disparities have been related to a number of socioeconomic, environmental, and social variables. This research adds to the increasing body of evidence demonstrating the long-term cardiovascular impacts disparities may have on vulnerable groups.
The phrase “redlining” is used to refer to a variety of discriminatory housing practices. Its roots are in a government program from the 1930s when the Home Owners’ Loan Corporation produced maps of over 200 American towns with ratings based on racial/ethnic mix, housing conditions, and local surroundings.
The graded locations were color-coded as A (“best” or green), B (“still desirable” or blue), C (“definitely declining” or yellow), and D (“hazardous” or red) depending on the potential lending risk. The areas with a D-rating were referred to as “redlined” areas. Despite the fact that these housing practices were prohibited in the 1960s, throughout the course of the last century, their consequences and other forms of discrimination have persisted to shape social and environmental structures, worsening health inequities.
“We already know historic redlining has been linked with modern-day health inequities in major urban areas, including asthma, certain types of cancer, preterm birth, mental health, and other chronic diseases,” said Sadeer Al-Kindi, MD, a cardiologist at University Hospitals Harrington Heart & Vascular Institute and Assistant Professor of Medicine at Case Western Reserve University in Cleveland and a senior author on the study. “While ours is the first study to examine the national relationship between redlined neighborhoods and cardiovascular diseases, it’s logical that many of the socioeconomic, environmental, and social impacts of redlining on other areas of residents’ health outcomes would also be seen in heart disease.”
A previous study demonstrated that Black adults living in historically redlined areas had a lower cardiovascular health score than Black adults living in A-graded neighborhoods. The current study supports this finding and extends the demonstrated health inequality nationally, showing that redlining not only affects coronary artery disease, stroke, and chronic kidney disease but also is associated with an increased risk of comorbidities and a lack of access to appropriate medical care.
The researchers used original Home Owners’ Loan Corporation (HOLC) graded data and calculated the percentage of intersection between each graded neighborhood boundary and the 2020 U.S. Census tract boundaries. They excluded any census tracts with less than 20% total area of intersection. The researchers used the graded intersections to generate a scale using their corresponding HOLC numeric scores (1-4 corresponding to A-D) and created a score that was transformed back into one of four categories: A (1), B (2), C (3) and D (4). The study defined redlined neighborhoods as D-graded census tracts and non-redlined neighborhoods as A- through C-graded census tracts.
The CDC PLACES database, which reports the prevalence estimates of census tract level health indicators, as well as census-tract level exposure of particulate matter and Diesel particulate matter from the Environmental Protection Agency’s 2021 environmental justice tool, were used to calculate potential environmental confounders. Other outcome variables and assessments used included: markers of health care access, cardiometabolic risk factors, and cardiometabolic outcomes. The researchers then linked HOLC-graded census tracts with the prevalence of cardiometabolic indicators and calculated the average of each indicator across census tracts in each HOLC grade.
More than 11,000 HOLC-graded census tracts were included, comprising over 38.5 million inhabitants. The A-graded areas covered 7.1%, B-graded areas covered 19.4%, C-graded areas covered 42% and D-graded areas covered 31.5% of census tracts. The percentage of Black and Hispanic residents increased across HOLC grades (A-D, respectively). Across HOLC grades A through D, the researchers found statistically significant increases in the prevalence of coronary artery disease, stroke, and chronic kidney disease.
“We found neighborhoods with so-called better HOLC grades had higher cholesterol screening and routine health visits when compared to neighborhoods with worse HOLC grades. And the prevalence of adults 18 to 64 years old without health insurance nearly doubled from A through D-graded areas,” said Issam Motairek, MD, lead author of the study and a clinical research associate at University Hospitals Harrington Heart & Vascular Institute in Cleveland. “In each stepwise increase across the HOLC grading spectrum, from A to D, we also observed an overall increase in rates of diabetes, obesity, hypertension, and smoking.”
According to the researchers, the association between redlining and the prevalence of cardiometabolic conditions further illustrates that historic redlining practices may impact contemporary cardiovascular outcomes by traditional and non-traditional risk factors. Residents of redlined neighborhoods, particularly minorities, are known to have lower access to public transportation, health care insurance, and healthy food choices, which increases their risk for missed prevention and adverse health outcomes.
Disparities in environmental exposures and in socioeconomic attributes may help explain the poor health outcomes in redlined neighborhoods, which are often situated next to major sources of pollution and make residents more likely to experience the detrimental health effects of disproportionately higher exposure to air pollution, less green space and other environmental toxins. Residents of redlined neighborhoods also experience financial strain, dismantled communities, and racial discrimination which may lead to increased stress and associated adverse health events.
Study limitations include self-reported health outcomes in the CDC PLACES database, which may be mischaracterized. The study was also unable to measure confounders such as behavioral and genetic factors. The definition of redlining census tract boundaries has also not been standardized across studies.
Reference: “Historical Neighborhood Redlining and Contemporary Cardiometabolic Risk” by Issam Motairek, Eun Kyung Lee, Scott Janus, Michael Farkouh, Darcy Freedman, Jackson Wright, Khurram Nasir, Sanjay Rajagopalan and Sadeer Al-Kindi, 4 July 2022, Journal of the American College of Cardiology.
“Study limitations include self-reported health outcomes in the CDC PLACES database, which may be mischaracterized. The study was also unable to measure confounders such as behavioral and genetic factors. The definition of redlining census tract boundaries has also not been standardized across studies.” Oh, really?
There is an unhealthy consensus in academe today that inquiry revolving around historical legacies of past discrimination is the source of the most interesting questions and predictions
Shoddy research, such as that detailed in this article, results and leads to conclusions and policy prescriptions that are detached from any accuracy viewing the true cause-and-effect or what to do about it.
The consequences of this are that public policy is vane and ineffective, problems then persist, and the whole we dig becomes ever deeper.
Neighborhoods that were impoverished 70 years ago were impoverished then, as now, because they are likely to be areas that are less desirable to live in, and are the most likely areas to be polluted, crime-ridden and ugly, all of which factors can contribute to poor health, then as now.
Further, poverty itself is likely to lead to poorer health. This does not imply, however, that the poverty is the result of redlining that occurred 70 years ago, nor that redlining was not simply the best credit data available to banks in its day, acting as an income proxy or as a proxy for assigning sales and credit teams territories most likely to be profitable or, to paraphrase Willie Sutton, lend in the green areas because that’s where the income and wealth are. In recent decades, better data exists so as to ferret out opportunities wherever they exist, even if the green zones remain the most profitable.
In fact, the subprime lending that predominated from 1995 through 2008, and resulted in our great financial crisis was, in part, motivated by a proactive effort by banks and mortgage lenders to engage in a form of reverse discrimination; the worse one’s credit, the more likely a loan was to be zero percent of 5% down-payment or even 10% cash-back. Federal and state regulations gave banks the right to expand more rapidly the more reverse discrimination they could show; and FNMA, GNMA and Freddie Mac would pick up the tab or, if necessary, the FDIC.
Therefore, could it be the case that this study shows the opposite of what it claims? Could it be that it is the reversal of redlining that has precipitated inferior health outcomes?
Here’s a far more useful line of inquiry:
1) which geographic areas had the worst health outcomes in the 1990s?
2) which of those areas has deteriorated the most in the past 25 years, and which have improved the most?
3) what factors best explain that deterioration or improvement and which of those factors are the most controllable and the most cost effective to ameliorate or to promote?
Good research vs. virtue-signaling research: the moral choice is clear.