COVID-19, Public Health And Disinvestment

Just Economy Conference – May 5, 2021

Focused on the NCRC Redlining and COVID report, this panel discussion will incorporate speakers from NCRC as well as public health and community investment speakers to help the audience understand the relationship between health and investment.

MODERATOR:
Bruce Mitchell,Ph.D.Senior Research Analyst, NCRC

SPEAKERS:
Dr Helen Meier, Assistant Research Scientist, University of Michigan, Ann Arbor, WI
Rita Harris, National Board of Directors, Sierra Club, Olive Branch, Mississippi
Jad Edlebi, Senior GIS Specialist, Research, NCRC

Transcript

NCRC video transcripts are produced by a third-party transcription service and may contain errors. They are lightly edited for style and clarity.

 

Mitchell, 03:42 

Welcome to our presentation on COVID-19 public health and disinvestment. our panel today consists of me, Percy Mitchell of ncrc research, Dr. Helen CS Meyer of the University of Michigan Institute for Social Research, Rita Harris of the Sierra Club, National Board of Directors, and Jad Ed Lemmy of ncrc research. Some of the work that we’ll be discussing comes out of a study that we completed last year, which examined the HLC redlining maps, and their association and their association with public health outcomes. that study was a joint collaboration between ncrc the University of Wisconsin Milwaukee is Joseph Jaisalmer School of Public Health and the University of Richmond digital scholarship lab. And I’ll just share my screen here so that we can look at the presentation. There we go. So part of what we’ll cover today is redlining and its role in the establishment of structural racism. Then how redlining and other segregationist policies concentrated disadvantage in many neighborhoods. This has impacted the range of opportunities, education, wealth building, and also public health, both through exposures and access to services. The public health effects are in many cases also health risk factors for adverse outcomes for COVID-19, which lm I will discuss. Rena Harris will discuss how the concentration of disadvantage plays out today, and disproportionate environmental exposure and major considerations of environmental justice. And finally, Jad Ed levy will cut will govern example of the mapping application. Winner took the study as an expansion of our work on the role of residential segregation and concentrating neighborhood disadvantage. And policies like redlining, which is detailed in the HLC maps in the 1930s are an example of how structural racism was embedded quite literally, and the American neighborhoods during a crucial time in their development, the post war period, up until redlining was made illegal in 1968. When we say structural racism, what we mean is the totality of ways in which societies foster racial discrimination. These are mutually reinforcing inequitable systems, like housing, education, employment, earnings and benefits, credit, media, health care, our criminal justice system and so on. These in turn, reinforce discriminatory beliefs, values and the distribution of resources, which together affect the risk of adverse health outcomes. So what was the HLC? And how did the redlining maps come to be? The homeowners loan Corporation was a new deal agency established in 1934, during the Great Depression during that time of crisis, and million homeowners were in jeopardy of default, and the HLC back there mortgages, preventing foreclosures and bank failures. It also modernized the mortgage market system in many ways. So why are we interested in the HLC today? Well, the agency also conducted what was called the serious survey program, in which they dispatched examiners to over 200 US cities to evaluate neighborhoods for the risk of default. The HLC utilized a standardized form to grade neighborhoods, which institutionalize segregations practices through the evaluation system. Residential neighborhoods were graded at four levels, she has an evaluation sheets, and then mapped the highest were the best neighborhoods that were mapped in green. The blue neighborhoods are concerned still desirable, yellow neighborhoods indicated declining. And finally a hazardous grade, which was mapped in red in the maps. The red or red line neighborhoods were deemed to be of high risk areas make it extremely difficult if not impossible. To get a mortgage or access to credit. These grades had an impact. In earlier work, we found that 74% of redlined neighborhoods are low and moderate income and 64% are majority minority 80 years after the HLC map graded them as hazardous. And this example, with a 1937 Philadelphia map, the original map on the left and examiner’s grading sheet is to the right. This neighborhood of frankford was great in de hazards, and some of the factors have to do with the valuation of the properties themselves. And we find the comment that the properties are now condition but also under detrimental influences. We find a general mixture of population indicated then it notes in form one mixture of Italians, and infiltration of black residents. In fact, neighborhoods with black residents were invariably given the lowest grade and redlined by the examiners, denying access to mortgages or other forms of credit. So access to credit was not evaluated based on individual properties, but tied to the entire neighborhood and its social composition. So as far as Philadelphia goes, what was the impact there? When we look at the highest graded best areas of Philadelphia today, we find that 94% of them are middle to upper income, and 70% are majority white while the hazardous redlined neighborhoods 61% of those are low and moderate income, and 69% are minority today. So how is access to credit in these neighborhoods now, these maps show the distribution of loans of Philadelphia’s neighborhoods between 2012 and 2016. Here we can see small business lending on the left, and mortgage lending on the right. The orange shaded areas were the low graded neighborhoods that were graded as hazardous reclining, while the teal areas had high grades of best or still desirable. As you look across the neighborhoods in this map, there’s a clear pattern of greater lending in the teal shaded areas. But there’s an exception, the neighborhoods in downtown Philadelphia, what’s going on there? Well, these neighborhoods which had indications of gentrification during the past decade. This map shows the gentrified areas more clearly. The map on the right has blue coded areas and indicating that gentrification with escalating property values increases in income and higher percentage of college graduates moving in since 2000, probably occurred there. The neighborhood’s coded in red and orange also have indications of gentrification, but they have the additional factor of black residents being displaced. Over the decades there are many cases in which there’s a cycle of disinvestment, abandonment, followed by gentrification and displacement in neighborhoods. During the past year, there have been many studies and reports of disparities and health outcomes for minorities, especially black and Native American people. In fact, there’s been a persistent racial mortality gap between white and black Americans. This chart emphasizes how mortality spiked for white and black people during the last pandemic of 1980 9019, but also shows how the gap or mortality rates in the early 20th century still exists today. a New York Times article examined this and noted several disparities during the current pandemic, that black people are 12% of the workforce, but 17% of frontline workers, that black renters are much more likely to live in crowded conditions that white people have higher exposure to air pollution than white people. Also that the lack of insurance and underrepresentation as doctors are part of health care disparities. most startling thing for me are the stark differences in life expectancy within many cities. If we turn back to Philadelphia and the hazards neighborhood we looked at before frankford, we find that the gap in life expectancy of 68 years life expectancy and birth contrast it with the higher graded neighborhood of ash born, where it’s at three years. So two miles distance means a 15 year difference in life expectancy. This is a pattern we found over and over when comparing low graded neighborhoods, natural LC maps with higher graded areas, and health expectancy, life expectancy today. Not only does a disinvestment in these neighborhoods persist, but the difference in life expectancy is profound. So our study of health disparities expands on this to examine public health outcomes in redlined neighborhoods, and how these areas are associated with adverse health outcomes, which lead to greater morbidity from COVID-19. Last year, we started working with Emily Lynch and Helen Meier at the University of Wisconsin. Now Helens with the University of Michigan to develop a historic redlining score. This will provide a way to look at the old HLC maps and assess degraded neighborhoods so that we can compare them with social, economic, and health data from the day. We also wanted to determine whether redlining was related to COVID-19 risk factors. This is one of the first studies to examine historic redlining across the nation, and present day neighborhood health outcomes. Now, Dr. Meier will cover that public health perspective and share our results. 

 

Meier, 14:30 

Thank you for having me. My name is Helen Meier, and I’m an assistant research scientist at the University of Michigan’s Institute for Social Research. I’m an epidemiologist by training and my portion of today’s session will focus on how redlining is connected to health. There are many proposed pathways linking redlining policies to health. For example, redlining created segregated neighborhoods and trajectories of investment and disinvestment. This in Influence place based resources for healthy lifestyles such as Parks and Recreation, as well as air pollution. And then this all influences our health behaviors as well as stress of the stress of neighborhood residents. And this all results in inequities in health outcomes. So let’s go through one more specific example. redlining has influenced racialized perceptions of neighborhood value and practices that have perpetuated racial inequities in lending. This has led to disinvestment in redlined neighborhoods. This disinvestment in neighborhoods, how they had lower home values, which meant less tax revenue to fund schools and services, and this results in poor education and reduced access to resources for residents. And all of these factors impact neighborhood health. In addition, the racialized perceptions of neighborhood, and their value resulted in restricted access to capital and equity to build wealth, and wealth is inextricably tied to health. redlining and health is of growing interest, you can see that there were relatively few publications over the last 10 years or so. And now we’re seeing a spike in peer reviewed publications into in 2020. And we already have seen several published in 2021. So many are interested in formerly studying redlining and health, but we have a problem. The neighborhoods in the HOLC maps are based on boundaries established by the HOLC examiners themselves. And those boundaries do not align with US Census Tract boundaries, for which many sources of neighborhood data in the US are currently available. And so we have a space spatial mismatch. Our solution was to use ArcGIS to create redlining scores for 2010 census tract boundaries. And I’m going to walk you through how we did that. So here is the redlining shapefile for Detroit, Michigan. And you can see the different color grades with the green and a graded to the red D grades. We overlaid on these red line and grades are the 2010 census tracks. To measure historic redlining. We calculated a redlining score to assess the degree of redlining a census tract was subject to we assigned a numerical value to each of the four HOLC risk categories, one for a grade two for b grade three for C grade and four for D grade. Then we calculated the proportion of the whole grades contained within a 2010 census tract boundary, and multiplied that proportion by the score corresponding to the grade. This created a census tract level continuous historic redlining score for approximately 150 cities in the University of Richmond’s mapping inequality project, with values closer to one representing low redlining values closer to four representing high redlining. We then created ranked quartile values at both the city or cbsa level as well as nationally for our analyses. So I know that might be a little hard to grasp. And so I have an example here for you. You can see that I’ve highlighted a census tract in this orangey yellow circle. And you can see in this example, if 50% of the census tracts grade was a and 50% of the track was B, the calculation would be one times point five plus two times point five resulting in a historic redlining score of 1.5. When we then created our core tiles, this census track what ended up in the lowest quartile of redlining, so it did not experience much redlining.  So then here you can see again, going back to that Detroit map, I showed you the initial historic redlining grade on the left, and our resulting scores for the tracks on the right. So now that we have apples to apples data, we were able to conduct a national study of redlining and current neighborhood health indicators. We looked at historic redlining score in relation to both current neighborhood socio Demographic and Health Indicators, some of which were COVID-19 risk factors including chronic kidney disease, COPD, obesity, type two diabetes and asthma. For our health data, we tapped into the Center for Disease Control 500 cities project and we also use data from the US Census Bureau. We found through our analysis that today redlined neighborhoods suffer from greater poverty, reduce wealth, lower life expectancy, higher prevalence of chronic diseases, as well as higher social vulnerability, which is a CDC index of vulnerability to natural disasters, such as the pandemic, which we are currently living through. Here are some more specific of natural, excuse me of our national results. So the highest redlining quartiles nationally compared to the lowest core titles, nationally, had, again, a higher percentage of minority residents, greater poverty and a lower life expectancy. But we also see statistically significant associations between greater redlining and general indicators of population health, including higher prevalence of chronic diseases such as obesity, mental health, diabetes, and asthma. So what does this all tell us? redlining is related to adverse socio economic in factor, socio economic factors. redlining is also associated with adverse health outcomes. We saw that life expectancy is reduced on average of 3.5 years in red line tracks, but that this varies nationally. For example, in Rochester, New York, we saw a decrease of 14.7 years in life expectancy. redlining was also associated with pre existing conditions for heightened risk of morbidity due to COVID-19, like hypertension, diabetes, and obesity. So, when we think about the role of structural racism in the pandemic, we know that the relationship of greater redlining and adverse adverse neighborhood level risk for adverse COVID excuse me and adverse neighborhood level risk for COVID-19 is an example of structural racism in America’s urban areas. COVID-19 has exacerbated racial health inequities that existed before the pandemic. We’re seeing differences in social, economic and environmental conditions that have produced inequities and COVID-19 infection, transmission and illness severity. And these health inequities are going to persist until we address the legacy of structural racism, particularly in the housing market.  Our results reinforce the impact of how place and policy influence health and shows us how insidious racism is in our society. For example, the decision by assessors to redlined neighborhoods in Milwaukee was overwhelmingly anti immigrant and anti semitic versus other cities like Richmond, where it was clearly anti black racism. Milwaukee’s black population largely arrived in the second Great Migration which occurred after the whole maps were made. So I have Milwaukee’s whole map up here. And I’ve highlighted one neighborhood for you. Here’s the Hulk assessment remarks for this neighborhood. 25 years ago, this was a good middle class section of Milwaukee occupied by second generation of Germans, Jews began to move in 20 years ago, in 2017, I’ve highlighted on the right that same neighborhood, it is 95% minority, which is overwhelmingly black 40% 43% live in poverty 14%. It has a 14% prevalence of asthma 41% prevalence of high blood pressure 44% prevalence of obesity and 19% prevalence of mental health problems. And remember, redlined communities were intentionally cut off from lending and investment. And the legacy of these redlining decisions have impacted the trajectories of neighborhoods and the health of residents who are not even born. When these determinations were made. blacks in Milwaukee are dispersed. Fortunately, living in historically redlined areas that have been disinvested in over the last 80 years, we see concentrated disadvantage in these neighborhoods that were redlined. They have on average, a median income of $20,000 less than neighborhoods that were not redlined. They have 20% less home ownership and a 20% percentage point deficit in the number of residents with a college education. We see greater chronic disease prevalence associated with these factors. And so it’s not individual black and white differences. These health inequities are associated with racist policies that determine the trajectory of the place which in turn has affected health. I hope this has given you some insight into how upstream factors and policies from 80 years ago influence health and underscores that housing policy is health policy. addressing poverty is health policy, and improving current neighborhoods socio economic conditions such as reducing unemployment supporting it initiatives to assess assist with home ownership or also health policy. Thank you. 

 

Mitchell, 25:08 

Thank you, Helen. And now Rita Harris. The chair club will go over some of the environmental justice implications of redlining and its impact in a city like Memphis, Tennessee. 

 

Harris, 25:22 

Thanks for having me today. I have lived and worked in Memphis, Tennessee all my life and actually live about 30 minutes south of Memphis now in North Mississippi. Memphis is an excellent example of environmental injustice, or environmental racism as some call it. Over the years, it has always been a constant struggle fighting against industrial and mobile source, air pollution. Because of the way the city was built and developed, the older African American neighborhoods were usually sitting dangerously close to polluting factories, landfills, and brownfields. The locally unwanted land uses some called Lulus. We’re always placed in African American communities, and the railroad tracks seem to always follow them. I have a couple of maps that I’d like to show at this point. The map on the left shows the county, our county is Shelby County, Tennessee, and the majority, low income areas are highlighted in pink. These areas are also the areas with the highest percentage of hazardous or toxic facilities. You can also see the icons that indicate industrial facilities, their toxic Release Inventory sites, the active polluting factories, they are indicated and with the green diamonds. The map on the right shows majority people of color communities, Memphis as a majority people of color city, mainly African American. And those areas are indicated in dark purple and lavender. Thank you for the maps, for example. And the North Memphis section of the city. There’s a community called Douglas the Douglas neighborhood. At one time, there were six polluting industries within a three mile radius. We knew this because we had studied the toxic Release Inventory each year. The toxic Release Inventory or TX t ri, as it is called, lists all of the industrial facilities that handled or used or even disposed of specific chemical substances that the EPA, the Environmental Protection Agency characterized as toxic or hazardous to human health. And some were even classified as persistent chemicals or forever chemicals, such as p FOSS. Because once they made their way into the environment, they did not break down or dissipate but persistent to hang around and cause harm long after they came in contact with our air and water or land. This same Douglas neighborhood is home to the Hollywood dump site. This was our first Superfund site in Memphis years ago. And it is 171 acres. And a part of this is a 46 acre polluted lake that we demanded EPA and the city fence off and install adequate signage because people were fishing and boating there on a daily basis. So we end up having community members living dangerously close to several contamination pathways, toxic air, polluted rivers and streams and polluted land or soil where dumping of some kind has taken place. All of these situations become stressors on our immune system and causes us to not be able to fight off various illnesses. The most prevalent illness you will find and high pollution areas and certainly in North Memphis is asthma, and also other related breathing disorders. Memphis ranked high and has done it for many, many years as an asthma capital. By the way American Lung Association. Obviously, a weakened immune system allows for viruses and other diseases to wreak havoc on individuals living in these areas. So when COVID-19 hit us last year, it was not a shock to see how devastating it was and African American communities across the country. I’m talking about Memphis today, but other communities across the country have very similar. folks in many of these communities have been dealing with poor health for many years, some for their whole lifetime. For years, I was involved in the creation of a couple of reports that linked health problems and diseases with specific chemical substances that were being emitted from factories and industrial sites and county. There’s these reports had nice names, like the Dirty Dozen, or the terrible 10. They listed the hazardous emissions from industrial plants, and listed the known health effects of each of those chemical substances. What we explained to the community is that even though we were listing these health effects and sharing this information, it would be even more difficult to draw definite conclusions about health effects. Because these chemicals were in varying concentrations, and mixed in with numerous other toxic chemicals that were being emitted into our air and water in our land by several different sources. And many of these sources were very close to one another. So in order to draw a significant conclusion, you would need to know the synergistic effects of all of the many different chemicals that are mixed together in our air. And it’s almost impossible. We knew it was bad news, but not sure just how bad if you add this information together with the fact that we knew even less about the individual lives of our community members, meaning what they had been exposed to, and then that work sites or what have you in their, you know, where they lived other than North Memphis, what genetic problems they might have, then the whole stressors of poverty, poor diet, and etc. All of these things had to be factored in to come to some conclusion. We could go on and on. All of this adds to the detrimental effects of a deadly virus like COVID. It had a horrible, horrible effect on our population, a population already dealing with poor health indicators. COVID helps shine a light on the weaknesses that we seen in our black and brown communities, including lack of adequate health care. And my mind, health care should be a human right. And it is definitely not, it doesn’t appear to be. And as we discuss how we can overcome poor health indicators and build a healthier community, we have to deal with or fight against racism, stereotypes and classism that perpetuate the disinvestment of our neighborhoods. And neighborhoods are begging for grocery stores where folks can shop for healthy foods instead of fast food and instead of junk food from corner stores, promoting investment and so called poor areas is what we need more of investing in our communities also includes the fight for living wages, affordable health care, a better educational system, and etc. All of these things will improve the quality of life for our communities, and those living in them. Thanks so much. 

 

Mitchell, 34:15 

Thank you, Rita. Thank you for linking these things together as a quality of health and quality of life issue. Now, Jad Edlebi will go over the mapping application, and how you can look at your community and find what the hlcm app said about your community and what the current health impacts are within your community. JOHN. 

 

Edlebi, 34:37 

Thank you, Bruce. I’d like to thank our partners, Robert Nelson, Justin hadron and their team at the University of Richmond digital scholarship lab for spearheading the design of the web application. It’s pretty easy to access. I’m going to go ahead and share my screen. So we begin on our reports page. Where we can scroll down and find the link that connects us to our maps and data. Once we click on the link, it will zoom us all the way to the bottom of the page where it will give us a list of cities to choose from. And these studies are all sorted out by state. So for this one, I’m going to take a look at Philadelphia.  So here we have two sides of a map showing the city of Philadelphia. On the surface, this may seem like a lot to take in, so let’s just walk right through it. For those who are familiar with the University of Richmond’s mapping and equality project, this tool is similar in that it shows the residential security maps designed by the HLC in the 1930s. However, it is different in that it actually compares these maps to the current status of public health in each neighborhood within the city. This provides a visual approach when looking at the spread of the data geographically. On the left, you have the residential security map written by the HLC in 1937. And on the right you’ll see a social vulnerability index broken down by census tract. The social vulnerability index, or SPI is an index developed by the Center for Disease Control, which measures neighborhoods vulnerability to disasters, such as economic recessions, natural disasters, and in this case, pandemics. The green colors that you see on the right side, show lower values in the social vulnerability index. And the red the magenta colors show higher values. To make it simpler, red is bad, and shows particularly vulnerable neighborhoods to major issues such as the covid 19 pandemic. So let’s zoom in on a neighborhood that is particularly on the red side. Let me go ahead and zoom in real quick. Bruce mentioned a neighborhood just before Frankford this area that was graded, the right here is the census tract that holds the data for that neighborhood.  On the left, you’ll see the census tract overlaid on top of some of the hlcs graded areas. This particular tract aligns with the majority degraded or redlined area. And in the middle section here, you’ll see a breakdown of the notes written by the HLC examiner who observed this neighborhood. I will note that these notes use racial and ethnic language that may be offensive or disturbing. You can also view the full HLC description by clicking this link. The current spread of demographic measurements such as life expectancy, median age, and poverty, can also be viewed in the middle section and just below the examiners notes. As you scroll down, you’ll also come across the public health variables we use in the study. These variables include asthma, cancer, diabetes, high blood pressure, kidney disease, mental health, obesity, and pulmonary disease. When comparing this track to the rest of the data across the city, this area shows to be in the red for almost all variables shown. For example, half the population living in this tract almost half are have been obese, or are obese rather, as well as high blood pressure being about 36%. One in five people are also living with a mental health problem as well. Again, the tracks selected is what is highlighted in this section. In contrast, when we go to the other neighborhood that Bruce had mentioned,  Ashburn  and also Lawndale this tract right over here, we can see stark differences in the public health outlooks in this neighborhood, just a few blocks away from Frankfort. Much of the variables in this area show to be on the green side of the spectrum, with much lower social vulnerability and higher life expectancy by almost 15 years. On average, these neighborhoods show a stark difference even though they are only about two miles apart or seven minutes by car. This is no by no means an isolated issue. similar patterns can be found in parts of New York, Chicago, and St. Louis. even smaller cities like Rochester, New York and Dayton, Ohio have neighborhoods with which resemble this similar pattern. These are just small examples of the systemic appliance of segregationist policies that have shaped to public health in cities all across the country, this tool is great in that it offers that geographic viewpoint. If you’d like to see a particular city on this list that you’re interested in viewing, you can easily change the city by clicking on the drop down menu at the top right corner of the page. I’ll also share the link to this mapping tool. At this point, I will turn it back over to Bruce, Bruce. 

 

Mitchell, 40:27 

Jeff, thank you so much for that a demo and explanation of the mapping tool. As you can see, residential segregation and redlining are important factors not just in the past, but in shaping opportunities for prosperity, and good health, the quality of life for people today, we invite you to explore the maps of your community for yourself using the web application, and Jad has posted the URL for it so that you can access it and have a look for yourself in your own community. I want to thank all of our presenters today, panelists today, greatly appreciate your presentations. And now if you have any questions, please let us know. Thanks so much. I want to thank the audience members for watching our presentation and let them know that if they do have any questions at this point we’d be be very open to taking their questions. Unfortunately, Rita was not able to join us today for our session that we have, myself Dr. Helen Meyer and Jad at lobby along with Jason Richardson, the director of NCRC research. Thank you, Bruce. 

 

Richardson, 41:52 

Thank you, Bruce. Actually, we do have a good question in the comments there. Bruce, you see that from about the census data. And so Fran Bond was asking since the state has been 2020 data from the census is suspect on many levels. Does anybody know the census will be able to be relied upon in the future? That’s a little off topic. But I bet Bruce has an answer for that.

 

Mitchell, 42:21 

The 2020 census data. So yeah, there are questions about undercounts in some cases, right? And, you know, the census has a variety of statistical methods by which you can go through and check their counts, and kind of get an idea of what the margins of error might be, on particular questions, particularly issues having to do with demographics, and socio economics. But, yeah, this has been an ongoing kind of question about the 2020 census that it was conducted during a pandemic, which was difficult itself, plus the Census Bureau introduced a number of new techniques, new surveying techniques for the census. So I do think there are some questions about the validity of some of some of the data in it that hopefully they will deal with. 

 

Richardson, 43:21 

Listen, I don’t see any other questions in the chat right now. So if anybody has any questions, please put them in the chat. You know, Bruce, if you don’t mind that I was going to add a couple of questions just because I wasn’t able to participate in the recording. Is that all right, if I if I take the lead? 

 

Mitchell, 43:35 

Sure, Gordon. Yeah. 

 

Richardson, 43:36 

Actually, you know, what I think is interesting, when we do these things, especially we did the bulk of this work, you know, several months ago. So we’ve had time to kind of think back and look over it again. with with with that, that gap in time. Are there any of the results of the findings here that a you feel in this is really open to to anybody? Any questions that we feel were a surprise at the time? Or are there new things that we’ve thought about since this report came out earlier this year? That that we’re thinking about expanding on and doing more? Further research? For example, I know you guys are working on the historical redlining score, and some other projects. And actually, there is a question now about the redlining score. So let’s turn to that first is the redlining score available for download either city by city or nationally. 

 

Mitchell, 44:34 

So the historic redlining score that is and we go into the paper, we talked about how that was developed with the methodology is where that historical red line score. Currently, Dr. Meyer and myself we are working on making those available for 2010 and also adapting it so it will be available for the 2020 census data also. Because what happens is the 2010 census tracks and the 2020 census tracks. There’s not a one to one relationship from decennial census to decennial census, the boundaries can change, which changes the areas of the boundaries. census tracks can be dissolved. So that where you have two census tracts that can be dissolved possibly in a one, or US Census Tract can be split from one census tract into two census tracts. So this causes a lot of changes, and there’s not a one to one relationship between the 2010 data and the 2020 data. So we’re working on reconciling that data at this point so that we can release this updated set, which include 2010 and 2020. Correct boundaries?  

 

Meier, 45:46 

Yeah, so just happen there. Yeah. So once we have this, we’re working on making that resource available now. And then I saw that there’s another question in the chat asking us if we were able to parse out the data by gender, or racial gender line. So the project that we did was at an ecological level. So the level of analysis, the unit of analysis was at the census tract. So we aren’t able to look at individual effects. With the paper that are with the report that we were discussing today. However, we have some additional projects in the pipeline that would look at the impact of the structural racism, redlining, on individual health outcomes. So some of that is in the works right now. 

 

Richardson, 46:37 

Thanks, Helen, that was great. You know, what has gotten a lot of attention about this project is is also the interface. And if any of you watching have had a chance to look at it, that’s great. If you have any questions, let us know. But if you look in the chat, Jad posted earlier, a link to the mapping interface, or you can go right to the report and scroll down and click on the button and choose the city to look at. But I would encourage you to do so. Now, the HLC mapped about 200 cities across the US during their time in operation. So those maps are there. And you know, it’s interesting to scroll in and see the extent to which the segregation of the period translates to health outcomes today. And if you look at your community, or a city you’re familiar with, my experience has been that when I look I often, you know, can can pick out neighborhoods and say, yeah, there there are severe disparities in health. And lo and behold, they tend to be in areas that were redlined over a city or a century ago. And so the extent to which those policies and those practices of segregation have echoed over time, constantly kind of surprises me.  So, you know, I think Ramona posted something in the chat about is I think she was talking or Yes, he was talking about heat disparities. Certainly, we know, we don’t touch on those. But Bruce has done quite a bit of work there around the heat island issues as well. But that’s not covered in this report.  

 

Mitchell, 48:06 

But yeah, right. If you’re talking about the urban heat island, and the relationship with redlining, the urban heat island, there has been some academic work done in that area. I think the thing to remember about the redlined areas and these areas of the map is that these are areas of concentrated disadvantage, and concentrated disadvantage goes across a number of different levels. It includes health disparities, it includes economic disparity, it includes disparity in different opportunities, including up to exposure to the urban heat island, and climate change. So the red line communities, they were disadvantaged in a number of different dimensions, of which health is a very important part. But there are also other areas, environmental exposures, in particular, which Rita certainly addressed, looking at the environmental exposures within Memphis, and the proximity of these toxic Release Inventory sites, to redlined areas and to majority minority areas within Memphis. And that’s, that’s an issue that goes across the country. It’s not just Memphis, that you have this sort of exposure relationship between environmental exposures and minority communities. redlined areas. 

 

Richardson, 49:30 

Yeah, exactly. And I kind of wanted to direct a response also to Victoria, you asked a question in the chat. Can anyone use the mapping app to track app activities in their neighborhood? Yes, as long as your neighborhood was one that was mapped by the HLC in the 1930s, that covers about 200 metro areas across the US. So there are some glaring gaps in those maps. For example, Washington, DC did not have an HLC map. So it’s not Part of this project, but many of those many cities are. So take a look at the application and take a look at your city and see if it’s there. And then you can scroll in and see, you know, what the correlation looks like between health outcomes today and the red lining from the past. And what one thing we found throughout this project is that there’s a growing understanding of that, that that redlining and segregation, have connections to other issues. And public health is obviously the focus of this report. And Dr. Meyer has done quite a bit of work presenting that, you know, details from this project to other audiences. And and, Helen, you had a great comment one time you said that in the public health sphere, there there is your kind of a similar growing understanding of the relationship between redlining and public health. Do you think you could talk about that a little bit and explain what that means? 

 

Meier, 50:54 

Yeah, sure. So,  um, in my,  in my slides, you know, I have the graph of I just pulled the number of PubMed papers that have been published over time that involve redlining, right, and you could just see that spike, right. So as public health comes around to recognizing structural racism as a public health problem, it’s just becoming a bigger topic. And you know, when the government is serious about it, or when public health officials are serious, because they put their money where their mouth is, and there is currently a NIH, the National Institutes of Health grant funding opportunity about structural racism and incorporating measures such as redlining, segregation, gentrification, other structural forces, that  including those those measures into ongoing research, right, so to continue to understand the relationship between the structural forces and individual level health. And so so I think, in the last year, even I think it’s just become such a bigger topic. I know. So I currently live in the city of Milwaukee and Milwaukee, public health department, City Public Health Department, has was one of the first cities to recognize racism as a public health problem. And I think, you know, that’s just gaining traction nationally. So I think that there’s kind of some it’s interesting, cuz I think there’s some practical aspect of it all, like everyone’s like, yeah, of course, you know, it makes a lot of sense. But then we also need to follow up with the research aspect of it and and really kind of make these connections and think about the pathways in which these policies and other kind of structural forces have have shaped our health. 

 

Richardson, 52:48 

Yeah, great. Thanks. I appreciate that. So we still have a couple minutes left, are there any other questions about the project or about the the web application itself or about future ideas for research or things that you’d like to see more research done on by ncrc. And remember, if you’re a member of ncrc, you have access to our team for technical questions, to get help with your own research just to bounce ideas off of or help getting data or or even doing some analysis on data in your area. We also have a new tool that’s been made available to ntrc members called the fair lending report tool. And if you sign into ncrc. org, you’ll be able to get into that tool that lets you pull reports on your home area, including data on mortgage lending, business lending, and branch branch locations. So combining the two, if you wanted to look at your your, your, your, your city and the HLC tool that that this team developed, you can also compare that to, to current lending patterns and see if there’s a correlation, because I’ll tell you, there probably is, redline committee communities from the past are often today not seeing the level of investment that that they should get, you know, given the population that’s there. So I would encourage you to do all of that. And of course, if you if you have any questions, just you can always email myself, Bruce Chad, any of the ncrc staff, and we’re happy to to answer those questions for you. And I don’t see any additional questions coming in. 

 

Mitchell, 54:25 

Looks like there’s one question about which audiences sectors have been most receptive to this message. And I’d say that, you know, since we released the port report has been kind of a broad segment, that we have had some interest from policymakers. Regarding the issue. Much of that has been interest around the economic effects, though, of redlining as opposed to the public health effects. I think the public health effects is kind of a cutting edge area of this. That is getting more attention as Helen just discussed a few minutes ago. Given that this is something that is getting more and more interest as we recognize that segregation, and racial disparities are a public health issue. 

 

Richardson, 55:12 

Yeah, I’m glad you brought that up. You know, another staff, staff member of ncrc, Karen colleague has been doing some great work at talking to public health organizations, public health providers, and helping them understand the link between what they do in the public health space and investment in communities. And I think that that, you know, as a as a, as an area of advocacy, I think is going to become more and more central to this kind of work as we as we really start to understand more about the relationship between your redlining, segregation, investment, and public health. So I’m excited to see that and I think I saw a question from Karen in the chat, actually. So she might be watching right now. So if you if you have any questions about that she’s available as well. 

 

Mitchell, 56:02 

I just have one general comment about redlining. And a question that we do sometimes get, and that’s that, how can maps that were made 80 years ago? How can they have an impact today? And, yes, the maps were made 80 years ago. And really what they did was they documented the existing patterns of segregation in American cities at that time. But then they had the further effect by entering into the FHA system, the VA lending system, the HPLC system of constraining basically where people could get mortgages. And the thing we have to remember is that after World War Two, the period, after which these maps were made after World War Two, we had this real explosion of suburbanization in the United States of the US urban system, where you had phenomenon like white flight, or you had white people leaving downtown areas, moving to the newly developed suburbs. And of course, those areas, they were outside of the HLC maps. So there was no restriction on financing development and credit for homeowners who are moving to these areas. And there were heavy restrictions on whether a black family could move into those areas. So this whole urban explosion, suburban explosion in the post war period, greatly favored white families moving to suburban areas, where they could invest in houses, get low interest, mortgages, and basically build wealth and engage in a lifelong wealth building activity of owning their own house. While inner city areas, downtown areas did not have the same advantage. 

 

Meier, 58:10 

Jason, you’re muted. 

 

Richardson, 58:14 

Sorry, there was a rookie mistake. Bob’s Edenic posts posted a comment in the chat and and Bob’s a former ncrc staff, and he’s just a great advocate for for these issues. He’s in the Bay Area. Now. He’s noting that Oakland and Richmond are aware refineries and contaminants are, and they are still killing people in the Bay Area. Yeah, and that kind of understanding about the how these things relate is important for this, the relationship between long standing policies of segregation and disinvestment, and then present day, so there’s a direct link between these two. And I think work like ours does a good job at at at highlighting that link, which is kind of the first step to, you know, to think about ways to resolve it, I think. Well, I think we’re at a questions and it looks like we’re just about out of time. So I’ll give one more. Shout out to Dr. Mitchell, Dr. Meier and Jad for a great presentation. And if anybody has any further questions, please email us or let us know. 

 

Mitchell, 59:30 

Thank you, everybody. 

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Redlining and Neighborhood Health

Before the pandemic devastated minority communities, banks and government officials starved them of capital.

Lower-income and minority neighborhoods that were intentionally cut off from lending and investment decades ago today suffer not only from reduced wealth and greater poverty, but from lower life expectancy and higher prevalence of chronic diseases that are risk factors for poor outcomes from COVID-19, a new study shows.

The new study, from the National Community Reinvestment Coalition (NCRC) with researchers from the University of Wisconsin–Milwaukee Joseph J. Zilber School of Public Health and the University of Richmond’s Digital Scholarship Lab, compared 1930’s maps of government-sanctioned lending discrimination zones with current census and public health data.

Table of Content

  • Executive Summary
  • Introduction
  • Redlining, the HOLC Maps and Segregation
  • Segregation, Public Health and COVID-19
  • Methods
  • Results
  • Discussion
  • Conclusion and Policy Recommendations
  • Citations
  • Appendix

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