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Breathing Easier: Emissions Data, Environmental Justice, and Child Health

April 21, 2021

Challenges in areas ranging from education to the environment, gender to governance, health to housing don’t exist in a vacuum. Each month, Abt experts from two disciplines explore ideas for tackling these challenges in our monthly podcast, The Intersect. Sign up for monthly e-mail notifications here. Catch up with previous episodes here.

Environmental justice. Maternal and child health. Two health crises that are related yet rarely addressed together. Abt’s David Cooley and Lawrence Reichle explain how data, technology, and creativity can address both challenges collaboratively.

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    Read the Transcript

    Eric Tischler: Welcome to The Intersect. I'm Eric Tischler. Abt Associates tackles complex challenges around the world, ranging from improving health and education to assessing the impact of environmental changes. For any given problem, we bring multiple perspectives to the table. We thought it would be enlightening, and maybe even fun, to pair up colleagues from different disciplines, so they can share their ideas and perhaps spark new thinking about how we solve these challenges.

    Today, I’m joined by two of those colleagues, David Cooley and Lawrence Reichle. Lawrence was the Deputy Project Director on the Data and Technical Assistance Contractor Team to support the Health Resources and Services Administration's Collaborative Improvement and Innovation Network to Reduce Infant Mortality. His other work at Abt includes CDC-funded studies with pregnant women and infants, assessing pregnancy infant outcomes with SARS-CoV-2 exposure.

    David focuses on the public health implications of climate and air pollution policy such as the regional greenhouse gas initiative. He manages the tool for EPA, the Co-Benefit Risk Assessment Health Impact Screening and Mapping tool, which estimates the health impacts from changes in air pollution emissions. Welcome.

    David Cooley: Thanks for having me.

    Lawrence Reichle: Good to be here. Thanks.

    Eric: David, I know in your recent study with Columbia University on the environmental effects of the COVID shut down in New York City, you identified—almost as a side effect—some significant environmental justice issues vis-a-vis child and infant health. You want to talk about those findings or the broader implications of your work for child infant health in particular?

    David: Yeah, absolutely. I worked on a study with Columbia University late last year looking at the air quality and public health implications of reduced air pollution emissions from the COVID-19 shutdowns in New York City. A lot of reduced activity, transportation, and other fuel consumption in the city during the most stringent shutdown in the March, April, May 2020 timeframe really significantly improved air quality in the city. We did an analysis to look at how that impacted certain public health outcomes, with a real focus on the implications for children's health. That's a thing in these types of air pollution benefits analyses that tends to be under-studied. There's a lot of focus on outcomes for adults, but we were really focused on outcomes for children. Things like avoided preterm births, avoided low birth weights, avoided incidences of childhood asthma and things like that.

    We found some pretty significant benefits. But another thing that came out of this study was we broke the benefits down by zip code and compared how the benefits accrued to different zip codes and then stratified those based on different measures of disadvantaged communities. For example, we looked at how much the benefits accrued to different zip codes based on the proportion of people that were in that zip code that had race other than white, or the proportion of people in that zip code that were below the poverty level. In both cases, we found that the benefits of the improved air quality were disproportionately realized in those zip codes that had higher populations of disadvantaged people. Higher proportions of race other than White or higher proportions of people under the poverty line tended to get a higher share of the health benefits.

    The reason for this, though, is because people in those neighborhoods tend to have higher baseline underlying health conditions. They have a higher baseline rate of preterm birth or a higher baseline rate of low birth weight. When you already have a high rate of those health outcomes, any little improvement in air quality you tend to get a really big bang for your buck in terms of improved benefits. It underscores the need to focus on improved air quality, how that impacts different populations, and also the need to address some of the underlying baseline health conditions that some of these populations are facing.

    Eric: Great, thank you. Lawrence, I know this touches on a lot of the work you do in terms of those challenged communities and your work with mothers and infants. Do you want to talk a little bit about the work you're doing and the overlays you see?

    Lawrence: Yeah, I mean, Hearing a lot of what David said really resonates with some of the work that Abt is supporting, especially with health equity and preterm birth, low-term birth weights. Those are two of the national outcome measures that we were tracking in our Infant Mortality Collaborative with the Health Resources Service Administration.

    I think, in general, there's been a renewed focus on health equity. One, with the change in administrations, but also with the Healthy People 2030 targets already being met for non Hispanic white and Hispanic infants as far as the overall infant mortality rate. But for non-Hispanic Black and for non-Hispanic American Indian and Alaska native, their rates are almost two times higher than the 2030 goal. We saw similar disparities in our infant mortality work with HRSA from the data that we collected, where the overall infant mortality rate reduced in the last three years, but not so much for underserved populations.

    Eric: There's that baseline disparity, and then there are these environmental additional factors. Lawrence, is that stuff coming up in your work? Is that something you're seeing? Are those dots we need to connect more fully?

    Lawrence: Yeah, this is something that a lot of people are thinking about, a lot of people are working on. The last Secretary's Advisory Committee on Infant Mortality, they spent a whole day talking about the environmental effects on infant mortality and maternal morbidities and mortality. A lot of the focus is on chemicals and examples of how the Flint water crisis directly affected a whole community with lead poisoning.

    David: Let me ask, was there any focus in those discussions on air pollution in particular? I ask that because, as I said a minute ago, people—me included—that study air pollution public health impacts, there's been such little focus on children's health and maternal health. It's really just been focused on general adult health because that's the data that we have and that's what's been available to us. I have long gotten the impression that it's been an overlooked area in public health.

    Lawrence: Yeah, I would agree. That link is not one that really comes up, hasn't come up in our work over the last three years to support HRSA and their grantees. The main focus when environment comes in is thinking about the social determinants of health and the built environment effects on equity. But yeah, I think that's an area that isn't at the forefront of a lot of peoples' thoughts.

    Eric: So, Lawrence, how can you import that stuff into your work, let's say? David, you've got the COBRA tool that you work on. Both of you guys, what are some ways in which we can help make those environmental impacts, bring them to the fore as well?

    Lawrence: With the work that David is working on, it seems to directly impact preterm birth and avoided low birth weights. Those are goals that HRSA and its grantees are trying to achieve.

    David: I think one thing that could help, too, is—Eric, you mentioned the COBRA tool that we support for EPA. This is a tool that estimates the public health impacts of changes in air pollution emission. It's a really great tool that you can do quick screening level analyses to say, "All right, if I implement a policy that's going to reduce air pollution emissions in this location by X amount, what are the resulting health impacts?" Currently that tool doesn't include a lot of the things that we included in the New York City analysis that are focused on children. Things like preterm birth and low birth weight and some of these impacts to children. Developing and improving some of these existing tools so that local policy makers and others can get a sense of what are we talking about in terms of the benefits here if we implement a policy to improve air quality in our region? What does that get us in terms of reductions in some of these health outcomes?

    Lawrence: Yeah. I'd just expand upon that. I think a lot of the organizations that we work with, they use their public health dollars to meet the goals of their grants. There's a lot of competing priorities that are always happening. I mean, especially with COVID. Tools that are developed, such as COBRA, could really help them to think about the benefits of reducing air pollution and how that directly impacts the things they're already working on with some of their other strategies.

    David: I was going to just say that the COBRA tool, the way it calculates these health impacts, it really depends on several things, one of which is the change in air quality. If you're improving air quality, you're getting benefits. But, as I mentioned with the New York City study, it also depends what your baseline level of incidence is. As I said, the areas with higher levels of incidence tend to see more benefits for a change in air quality. If you already have a lot of preterm births and you have an improvement in air quality, you're going to see disproportionately large drop in preterm births.

    But one of the limitations that we've had in a lot of cases is just really good data on what that baseline incidence is. Being able to collect that at a somewhat fine geographic resolution, all of that would really improve the ability to develop and run these tools.

    Lawrence: Yeah. For infant mortality, there are certain states and counties, even, where, if the goal is to really target the already vulnerable populations and especially achieve health equity, then there could be focus or using these tools to look at those, even counties that have a higher rate of Black infant deaths, for example.

    Eric: So Lawrence, do we have that data? Is it a matter of connecting the dots here of HRSA has this data, we have this tool. Can we plug that data in? Do we have it, or are we close to having it?

    Lawrence: I think the data set that would be helpful is CDC WONDER data set. I'm not too familiar with that. For our Infant Mortality Reduction Collaborative, we collected data from the grantees of 21 states, and that was for a three-year period. But they report similar data to CDC WONDER using birth certificates and deaths that are reported to the counties.

    David: COBRA uses county level data currently. At some point, we would love to even go below the county level, but county level right now. As you were saying, that may be good enough in some cases where you can really look at things like counties with really high proportions of infant deaths or some of these other health outcomes and get a sense of how would changes in air pollution in those areas really impact those health outcomes. Are there specific targeted measures you could take to improve air quality in those regions, and what do you get in terms of the health benefits from those?

    Lawrence: Yeah. As part of the piece of the puzzle, our clients and the grantees we've been working with have been interested in multiple ways to reduce infant mortality. The purpose of the collaborative that Abt supported was to focus on new innovations in quality improvement and things that could be added to the already existing toolbox of strategies to reduce infant mortality.

    Eric: Great. It sounds like if we can get that data into COBRA, that might be another tool that could be useful or at least adapted to be useful.

    David: Yeah. I agree with the way Lawrence characterizes as sort of another tool in the toolbox. I mean, obviously there are multiple strategies for combating infant mortality and these other child health outcomes, but [addressing] air pollution is definitely one of them. This would be a good tool to help examine that.

    Eric: It is a great tool. It's great to think that it's got other applications. So hopefully Lawrence, you can guide some other organizations to that tool. And David, you too. Well, thank you both for joining me.

    David: Well, thanks.

    Lawrence: Yeah, it's been great. Thank you very much.

    Eric: … and thank you for joining us at The Intersect.

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