JCO After Hours: A Discussion With Kirsten Beyer and Jennifer Griggs

Dr. Shannon Westin, Dr. Kirsten Beyer and Dr. Jennifer Griggs discuss how mortgage lending bias and residential segregation intersect with cancer disparities and survival outcomes.

TRANSCRIPT

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SHANNON WESTIN: Hello, everyone. My name is Shannon Westin, and I'm an Associate Professor at the University of Texas MD Anderson Cancer Center in the Department of Gynecologic Oncology and Reproductive Medicine. And I currently serve as the Social Media Editor for the Journal of Clinical Oncology.

And we're starting a brand new podcast series to try to bring really exciting research that's being published in the JCO to you, and I'm so excited to kick off this series with a group of very accomplished women who are covering something that I don't think a lot of us don't know very much about. So I'm really excited to learn a ton over this next few minutes.

So it's my pleasure to introduce Dr. Kirsten Beyer, who is an Associate Professor in the Division of Epidemiology in the Institute for Health and Equity as well as the Director of the PhD program in Public and Community Health at the Medical College of Wisconsin.

We are also joined by Dr. Jennifer Griggs, who's a Professor the Department of Internal Medicine, Division of Hematology Oncology, as well as a member of the Institute of Health Care Policy and Innovation at the University of Michigan. She does predominantly practice taking care of women with breast cancer. Welcome, doctors.

JENNIFER GRIGGS: Thank you.

KIRSTEN BEYER: Thank you very much.

SHANNON WESTIN: So we're talking today about the manuscript "Mortgage Lending Bias and Breast Cancer Survival Among Older Women in the United States" that Dr. Beyer published just this month in the JCO. In addition, Dr. Griggs and her colleague Dr. Pleasant were invited to participate in an editorial called "Contemporary Residential Segregation and Cancer Disparities."

So let's get into to what was covered. So I think for me, the lowest hanging fruit here, Dr. Beyer, is understanding what exactly is redlining, because that was one of the critical exposure that you were assessing amongst these women with breast cancer.

KIRSTEN BEYER: Thank you, Dr. Westin. Yes, redlining-- I think most people think about redlining as being a historical practice, where mortgage lenders would essentially draw red lines around particular neighborhoods and then not lend mortgages in those areas, regardless of whether or not the applicant for that mortgage was otherwise qualified. So it's generally thought of as a historical practice.

But what we've done in this study is to look at some more contemporary data and create a new measure that we think represents contemporary redlining, maybe not in the legal sense in terms of housing discrimination. But this measure represents essentially the odds ratio of denial of a mortgage application for a property in a local neighborhood as compared to the metropolitan area as a whole. So we're really looking to see which areas of our US cities are systematically denied mortgage applications. By denying those mortgage applications, they are suffering from disinvestment, and I would argue structural racism is guiding a lot of that practice.

SHANNON WESTIN: So can you explore that a little bit more with us? And how do you find that type of data? Where do you get this information about these denied mortgages? How do you get into the different covariates like race, ethnicity, things like that?

KIRSTEN BEYER: Sure. So I think a little history lesson is important first. Between the historic practice of redlining and today, there have been a number of major laws that have been passed in the United States really to try to overcome housing discrimination. Some of the most important ones are-- in the Civil Rights Act of 1968, there was something called the Fair Housing Act, and that act prohibited discrimination in the sale, rental, and financing of housing based on race, religion, and national origin. And since then, they've added a few more protected categories.

And then right after the Civil Rights Act of 1968, there was something passed called the Home Mortgage Disclosure Act. And this act was essentially to bring transparency to mortgage lending in this country. The idea was that we were requiring public disclosure of loan-level information about mortgages that were lent in the country. And the goal was to shed light on lending patterns, including those that could be discriminatory.

And so the HMDA data-- it's commonly referred to as "hum-duh." That HMDA data has been collected then since 1975. And that database evolves over time, but we use that data for 2007 to '13 to really try to understand what are the mortgage lending patterns in our US cities in terms of their spatial distribution.

And so there are a number of covariates that we were able to control for there. There are some things that we're not able to control for. I'm excited that the HMDA database has recently improved, and there are some new variables that are going to become available in the coming years.

So what we did with the HMDA database was to calculate an index of redlining, so an odds ratio of denial of a mortgage application for a property in a specific neighborhood compared to all the properties across the metropolitan area. And so it's an area-level measure, a neighborhood-level measure.

And then we put that measure into a statistical model to see what happens to women diagnosed with breast cancer if they live in redlined areas compared to if they live in other areas. And so we were able to control for a number of other factors, including race, including tumor characteristics, age, stage at diagnosis, and then to see what is the added effect of redlining over and above the things that we already know impact survival.

So what we found was that women living in redlined areas in the United States were more likely to die faster after breast cancer diagnosis than women living in other areas. We also found that among people living in redlined areas, there was a discrepancy in terms of the race and ethnicity of those women. So 79% of Black women, 57% of Hispanic women, and 34% of white women lived in redlined areas in our sample.

SHANNON WESTIN: That's so interesting, because I think we've all read and seen across a number of different cancer types how race and ethnicity can be associated with worse outcomes. So I think you're starting to scratch the surface of why that might be. Now, do we think that is there an association with other factors like socioeconomic status or insurance or anything like that?

KIRSTEN BEYER: Yes, I think those are really good questions. Not all databases contain all of the information we would like. But in SEER-Medicare, which is the database we use, we know that all of the women have health insurance because it's a linked database with cancer registry data and then Medicare claims data. So health insurance wasn't a factor here, but we certainly know that it could be a factor in a larger sample of women across the age spectrum.

And I think when you get into questions of socioeconomic status, you also have to think about, as opposed to statistically controlling away the effect of socioeconomic status, what is the mediating effect? Or what is the explanation? What factors explain the relationship between redlining and breast cancer survival? So I think that's where we'll see a lot of the important explanations for how does redlining contribute to survival.

SHANNON WESTIN: Thank you. I think you nailed it right there, because finding a problem is, of course, important, but then what do we do next?

Dr. Griggs, I thought your editorial was just so great at providing context for this issue, and I was wondering if you could expand a little bit more on this idea around residential segregation and how it impacts outcomes for these patients.

JENNIFER GRIGGS: Thank you very much, and thanks for including me on this great podcast. It's so important to understand that place matters more than race, and we've known this for quite a while. So that area-level factors are associated with environment-- for example, pollutants, safe water, safe places to play, safe places to exercise, transportation fragility, for example, a robust public transport system.

We know that neighborhoods that are in redlined areas are more likely to be policed in different ways, which takes children from school being suspended at higher rates. There's less educational investment, but Dr. Beyer mentioned this disinvestment in neighborhoods basically has shutters all the way down. It shutters from childhood all the way to how we age and access to healthy food.

We know redlined areas are associated with poor markers of diabetes control, and if you take somebody from an area that's a poor neighborhood that's segregated and give them a voucher to live in a more affluent area, that markers of diabetes improve and weight goes down.

So just to think about this, that the impact of where we live affects things that we think of as personal behavior-- like, what we eat or how we control our diabetes. There are, of course, implications for access to high-quality health centers when we think about people sort of locked into certain neighborhoods, all that goes along with that, including wealth.

Wealth is probably one of the biggest predictors of health and not being able to have the wealth associated with home ownership decreases economic stability. And we know these things like allostatic load or stress, sometimes called wear-and-tear effects, are associated with things like tumor biology and breast cancer. We see more triple-negative breast cancers in areas where there's more allostatic load.

So imagine, we think about race as this fixed-- sometimes people even construe race