Climate Change and Health Seminar Series: “Climate change and health: Research to inform equitable policy”

June 26, 2023

Information

Dr. Jaime Madrigano joined YCCCH to discuss her work on environmental justice, and policy actions to ensure equitable outcomes.

Speaker:

Dr. Jaime Madrigano; Associate Professor, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health

April 24, 2023

ID10080

To CiteDCA Citation Guide

00:00<v Dr. Chen>Hi everyone thanks for coming.</v>
00:01And this will be
00:04our last seminar of this Spring semester (indistinct)
00:09in the house and I'm very pleased to introduce you
00:14to our today's speaker, Dr. Jaime Madrigano.
00:18Dr. Madrigano is currently associate professor
00:22at Departments of house and engineering
00:25at John Hopkins Bloomberg state.
00:29Jaime has made her research focus is environmental
00:33and social determinants of health,
00:35improving climate change and all environmental
00:39and the drilling part is abcess on the environmental justice
00:44Jaime uses logical method to report policy
00:47her research was informing the development
00:52of the 2017 New York City meters
00:55$106 million here adaptation,
00:59which I talk a lot about in my own class.
01:02So you'll see to see behind the core neighborhoods
01:07New York City project,
01:09she also serves on the USEBA board of counselors
01:15and the International Society.
01:20<v ->It sounds like they're having a hard time hearing you.</v>
01:22<v ->Oh, if I'm going to wait,</v>
01:25can you hear us now?
01:28<v Mauro>That's better, Kai thank you.</v>
01:29<v ->Okay then maybe you need to stay here.</v>
01:32<v ->Okay that's okay.</v>
01:33<v ->So without further ado,</v>
01:36lets welcome Dr. J Madrigano.
01:42<v ->Thank you so much Dr. Chen</v>
01:44and it's really great to be here.
01:48I really appreciate the invitation.
01:50It's been a wonderful morning so far,
01:52meeting some faculty and trainees and I really appreciate
01:56having the chance to talk a little bit about my work.
01:59So as Dr. Chen said, I'm Jaime Madrigano,
02:03I'm currently at the Johns Hopkins Bloomberg
02:05School of Public Health.
02:07And there I'm in the Department of Environmental Health
02:09and Engineering.
02:10And I also lead the environmental challenges focused area of
02:14the Bloomberg American Health Initiative,
02:15which is really working to integrate our research practice
02:20policy and education at the school and in kind of five
02:25leading health areas that are that, that America is facing.
02:30So today I'm gonna talk about my work
02:33in climate change and health,
02:35how some of this work has been used to inform policy
02:39and just a couple of points broadly about how I think we can
02:43think about climate and health research
02:45being used to inform policy.
02:49Okay so please feel free online,
02:54I'm trying to stand close to the computer
02:56so that you can hear me well.
02:57But just let us know if there's any issues that come up.
03:06Okay.
03:07So I often like to start out my lectures
03:11with this motivating slide.
03:13And I realized when I was looking at it this morning,
03:15it's actually quite dated.
03:18So it makes me feel kind of old,
03:20but I actually think it is still very relevant
03:24and still very valid that climate change is the biggest
03:28global health threat of this century.
03:30And I strongly believe that and you know,
03:32we certainly have been facing many global health threats,
03:36but I think the thing about climate change is it really
03:38spans across all kinds of disease outcomes.
03:41So, you know,
03:42we really have been dealing with the COVID pandemic
03:46and infectious disease,
03:48but we know that climate change is changing
03:51the spread of vectors and changing the prevalence
03:54of infectious diseases around the world.
03:57But not just that we know that climate change is impacting
04:00chronic diseases in the elderly.
04:02We're seeing pediatric populations dealing with the brunt of
04:06climate change in ways we've never seen before.
04:09So I'm sure you've had a lot of great discussions in this
04:12seminar about all the broad range of health effects of
04:16climate change.
04:17I'm not gonna bill to cover that all today,
04:19but I'm gonna specifically talk about some of my work
04:23related to heat and health impacts of heat
04:25and then environmental health disparities related to heat.
04:30So speaking of heat as an epidemiologist,
04:34I generally look at historical heat waves
04:37and occurrences of temperature fluctuations
04:40and compare those to health outcomes
04:43and see associations between those weather phenomena
04:47and adverse health consequences.
04:49But what does that mean really for climate change
04:52and thinking ahead and into the future?
04:54Well we know that these weather phenomena,
04:58they have been changing over the last several decades.
05:01So this is data from the US Global Change Research Program
05:05and this shows that over the last six decades
05:08we've seen a very consistent increase.
05:12This is data from 40 large cities within the US
05:14of kind of characteristics of the heat season.
05:18So we've seen that the average number of heat waves
05:21have gone from about two on average per year
05:25to about six or more per year.
05:29And the same kind of pattern with the length
05:31of the heat season.
05:31We're seeing just a longer duration
05:34of when we might have these very extreme heat events.
05:38And so what we we know is that those patterns are continuing
05:42to get to worsen and when we can look at historical data
05:45and see the adverse health consequences
05:47associated with extreme heat events,
05:49then we can kind of project into the future
05:51about what we might continue to expect
05:53as these weather phenomenon patterns continue to change.
05:59We're really already seeing that the health impacts,
06:05particularly mortality,
06:06which has been studied a lot that are associated with these
06:10extreme heat events, they've already been,
06:12IM impacted by climate change.
06:13And this is a referenced from the multi-country,
06:18multi-city collaborative research network.
06:20I think Dr. Chen is involved in that.
06:22Some other faculty at Yale.
06:24And I just thought this,
06:25I don't know if you actually were involved in this paper,
06:27but this is a really nice paper that came out a year or two
06:30ago and again, it's not one of my studies,
06:34but I like to show this
06:35because I think it was a great paper.
06:37One of the first to really show attribution.
06:40So what was shown in this paper is they looked at,
06:46I think about the last three decades of changes in
06:50temperature and kind of disentangled what the temperature
06:54would've been had we not been undergoing climate change
06:57and what the temperature really was
07:00according to the historical record.
07:02That's the difference between those red and orange lines,
07:04you can see there.
07:05And then they were able to kind of parse out
07:08how much of the deaths that we see
07:10during these heat wave events over the last few decades
07:13in many countries around the world.
07:15You can see the map where data were pulled from,
07:18how much of those were due to that differential,
07:23to that temperature change that is associated with an
07:26anthropogenic climate change.
07:28And they showed that there were about 37% of the deaths in
07:33the warm season were attributable
07:35to that anthropogenic climate change.
07:37So the point I just wanted to make with this slide
07:41is to say that this isn't just a future problem,
07:43this is a problem that is impacting us has been for decades,
07:47people die every year from extreme heat and this is already
07:50worsened because of climate change.
07:52And you know, without kind of mitigation and adaptation,
07:57we expect that to continue to worsen.
08:01Okay, so now that everyone may be depressed,
08:04what can we do about it?
08:06So we know that, you know,
08:09as I've shown plenty of other studies have shown heat waves
08:12are deadly.
08:13But there are some things that we can try to do to mitigate
08:17those health impacts.
08:18So there are heat warning systems.
08:20Many communities implement these to put into place a wide
08:24variety of measures.
08:26Now the studies that have looked at these in a rigorous way
08:30have really shown mixed, mixed results.
08:33We don't know really if these are really effective in saving
08:36lives during heat waves.
08:38There's been kind of mixed data in some locations it seems
08:41they have been effective and others they haven't been.
08:44And there's, there's discussion around this discuss like,
08:47why limelight did that be the case?
08:49Well one reason is implementation after heat warnings
08:52is very different from community to community.
08:54What's actually done?
08:56But another question is,
08:57is the temperature threshold that triggers that warning,
09:01is it really appropriate to that local community?
09:03Sometimes it's based on a regional forecast.
09:06And so in some places people have used the epidemiologic
09:10data from that community.
09:11So particularly in New York City they did this
09:13where they actually changed the threshold
09:16to trigger that warning based on epidemiologic study
09:20and they showed that that did help
09:22to prevent hospitalization after that change was made.
09:26So that's something we can do in terms of public health
09:29research where we can try and use local contextual data to
09:33better understand what are appropriate thresholds
09:35to trigger warnings.
09:37We can also think about urban form.
09:40Where should we implement more green space
09:42or think about reflective groups to maybe lessen
09:44that urban heat island.
09:47But the question is where to target those?
09:49You know, there's only a finite amount of money usually.
09:51And so we wanna target those in the places that could most
09:54benefit and seek to gain the most
09:57health benefit in particular.
09:59It might be in the parts of the city that are hottest,
10:02but that might not be where people are living.
10:05So we really need to know where people
10:07are impacted the most.
10:09And the same thing with other types of, you know,
10:12social and financial supports.
10:14We really wanna think about who can benefit most from these
10:17types of programs and how we can get resources to those
10:20populations and neighborhoods.
10:24So that brings me to some of the work I wanted to talk about
10:26that I've done in New York City.
10:28And this was a study that I did quite a while ago,
10:30but it really has informed a lot of work that I've done
10:34since then and continue to do,
10:36which I'll talk about a little bit after that.
10:38But I wanted to set the stage with the study
10:40and this was a study on heat vulnerability in New York City.
10:46So when I started this work, what was noon already
10:50I was collaborating with people at Columbia University as
10:53well as the New York City Department of Health
10:55and Mental Hygiene.
10:56And with those collaborators at the New York City Department
10:59of Health, they had already really looked at the burden
11:02of heat on health in New York City.
11:05And they had found that they really started to see severe
11:08health impacts of heat so rises in mortality
11:11when the heat index,
11:14which is a combined temperature and humidity metric,
11:17exceeded 95 degrees Fahrenheit over a couple of days.
11:21So a prolonged period of that high heat index.
11:24So they kind of knew where they wanted to start thinking
11:27about that was their threshold
11:28where they're seeing health impacts.
11:31But what they didn't know was where specifically within
11:34New York City, which is very large and diverse city,
11:37should they be targeting resources
11:39and what populations were most at risk.
11:43That was where our collaboration came in
11:45and we really wanted to again,
11:47determine individual and neighborhood characteristics that
11:50increased the likelihood of dying during a heat wave
11:53and then use that epidemiologic data,
11:56that health informed data to create a heat vulnerability
11:59index for New York City.
12:00And we felt that we could really make the strongest case for
12:04policymakers to use that if we had the health data
12:07to back up our recommendations.
12:11So we did that with a case only study,
12:15a case only design is a kind of a nice efficient way
12:19to look at an effect modifier.
12:21So if you've already understand the relationship between an
12:25exposure and an outcome as I said,
12:28this relationship between heat and mortality was already
12:31pretty well characterized in this community,
12:36but you really wanna look at some of those third variables
12:38that might tighten that relationship.
12:42You can use a case only design and really look at the
12:45modification piece.
12:47So we were able to do that with about over 200,000 deaths in
12:52New York City over a period of just over 10 years
12:56where we looked at all of the deaths
12:57that occurred in the warm season
13:00and we tried to understand what factors
13:03were increasing vulnerability.
13:05We defined heat waves as according to this definition that
13:10was already established by the New York City Department
13:12of Health times when the heat index heated 95 degrees
13:16Fahrenheit for at least two days.
13:20And then we tried to think about,
13:21okay, how do we define vulnerability?
13:24We like to think about three components of vulnerability,
13:28what's increasing exposure?
13:31This might be something in the neighborhood that maybe makes
13:34the heat greater in one part of the city versus another.
13:39What might make a person more sensitive,
13:40maybe their their age or medications that they're on
13:44and what could give a person adaptive capacity
13:47so that they could withstand the heat.
13:49And that gets into things like maybe financial resources
13:52or other things.
13:54The problem is of course we didn't have all the ideal data
13:57that we wish we would in any study.
14:00So we were working with death certificates.
14:02So we would have to really,
14:04we were just constrained by what we could understand
14:06from the death certificate data.
14:08So the things we were able to look at are individual factors
14:11that I've listed here that are readily available
14:14on the death certificate.
14:16Then what was also available on the death certificate was
14:18the person's census tract of residence.
14:21And we could match that with other geospatial data sets to
14:24look at, you know,
14:25how much green space surrounds the person's...
14:29Is in the person's neighborhood,
14:30where in which they live using some satellite data
14:33to understand how temperature varied across the city
14:36and some other census data characteristics.
14:39So we looked at all of these factors
14:42and we found several factors came up as statistically
14:47significant modifiers.
14:49And so where we found that non-Hispanic black New Yorkers
14:54were much more likely to die during heatwave days
14:57versus non heatwave days
14:59in that same warm period than any other race
15:02or ethnic group.
15:04We also found that people were more likely to die at home
15:06than in hospitals or institutions.
15:09This could potentially be a marker of social isolation,
15:14although we weren't able to specifically measure that.
15:17And then we found that people that died during heat wave
15:22days versus non heatwave days over this warm period,
15:25relatively more of them looped in neighborhoods
15:29that were receiving more public assistance,
15:31general marker of poverty and in parts of the city
15:35that had less vegetation and consequently,
15:37higher surface temperatures.
15:40So we were able to look at all of those factors that were,
15:44again from the epidemiologic analysis came out as
15:48significant modifiers and characterized their distribution
15:52across the city.
15:53We looked at every census tract and the prevalence of these
15:56factors and we created Z-score to combine those factors
16:00into an index.
16:04And then we mapped the index.
16:06And so you can see on this map the red portions
16:10indicate a higher index score.
16:12Those are the areas that we found were the most heat
16:16vulnerable where a lot of these factors tend to cluster.
16:19And if you're familiar or not familiar
16:22with the New York City,
16:23those were in areas of upper Manhattan,
16:25the Bronx and central Brooklyn.
16:29And then of course,
16:30it's not to say that deaths during heat waves are not
16:34occurring in other areas,
16:35but relatively there are less in other areas.
16:38So we had that combined next just to see,
16:42'cause we did a very simple,
16:44we didn't really do a complicated weighting scheme.
16:46We actually wanted purposely to keep it simple so that the
16:49Department of Health could continue to update this index
16:53and, and you know, make it sort of an evergreen tool.
16:57So we just summed those factors to create the index,
17:02but we found that this is the relative odds.
17:05This graph on the left is the relative odds of dying during
17:08heat wave by quintile of the index.
17:10And we do see that it actually predicts pretty well with
17:14each increasing quintile leading to an increase odds
17:16of dying during a heat wave.
17:19So this was a very useful tool
17:22for the city health department
17:23and I'll talk a little bit
17:26about how this index was eventually used by the city,
17:29but of course I do wanna mention some limitations
17:32from this work and how it kinda got us thinking
17:34about other aspects of things to look into.
17:38The case only study is limited in that
17:42you're really looking at one modifier at a time
17:45and so many of these things are highly correlated.
17:49So we really couldn't tease out what is the most important
17:52risk factor, but that that wasn't really our goal
17:55in this work we really wanted to identify areas
17:58of most vulnerability.
17:59But if you are interested in that,
18:01this study design is limited in that way.
18:05We didn't have in information on individual socioeconomic
18:09position or measures. We used the a neighborhood measure,
18:13but of course both of those really play an important role
18:16in the ability to adapt to heat.
18:18And we did not have that.
18:21And of course like most big epidemiologic studies,
18:24we used outdoor temperatures of proxy for personal exposure.
18:28This can be a poor proxy in a lot of cases,
18:31particularly when you're talking about having air
18:34conditioning or not having air conditioning.
18:37And so, you know,
18:39when we think about the sort of relative different changes
18:42day to day,
18:43we still think it's useful but it's worth mentioning that
18:46that is a limitation of this study.
18:48And you know, correspondingly,
18:50no information on the indoor residential environment.
18:53So no information on air conditioning,
18:55no other information on the home.
18:57Again, pretty pretty par for the course
18:59for a large epidemiologic study,
19:01but left a lot of open questions for us.
19:06The one thing we decided to do after that work was complete
19:10was to try to understand some of those open questions
19:13a little bit more.
19:14And what we did is we conducted
19:16a follow-up telephone survey.
19:18So I'm not gonna get into all the details of this study,
19:21but I'll just say that we ended up
19:24doing telephone interviews.
19:25It was a landline plus cell phones sample
19:29and we did about over 700 interviews
19:32conducted in English and Spanish of New Yorkers.
19:35I think there were about 15 questions kind of ranging from
19:39some information about characteristics of people's homes,
19:41whether or not they had air conditioning,
19:43whether they used it from some demographic information
19:47and also some questions on what they did during heat waves.
19:51If they hand staple at home,
19:53what were their options, how did they protect themselves?
19:56So you can always pull up the study
20:00if you really wanna know a lot more about it.
20:03But I'll just highlight a couple of the key findings
20:05which were that we found that over a quarter of New Yorkers
20:10did not have access to functioning air conditioning
20:13or used it less than half the time
20:16when they noted that it was very,
20:18very hot outside.
20:20So that's really telling us that, you know,
20:23in general we think kinda air conditioning coverage
20:27or penetrance is pretty high,
20:29but there are a lot of people in vulnerable communities
20:34who do either don't have access or are not running it.
20:37And a lot of times, you know,
20:38that may be due to financial constraints
20:40for electricity bills.
20:43We also found that non-Hispanic black respondents,
20:47you know,
20:48which was again a priority population
20:49since we found they were dying much more during heat waves
20:52than other groups in New York
20:54were less likely to own air conditioning
20:56even when adjusting for household income.
20:59Now our household income measures are still somewhat prude,
21:03but I think what this points to is that
21:05there are other potentially systemic factors
21:08that really need to be accounted for.
21:12When we sort of do these epidemiologist studies,
21:15a lot of the things we're measuring there are things that go
21:17way beyond that.
21:18So this may be related to certain types of housing
21:21conditions that can't support air conditioning use
21:25or other things that might just not,
21:28not be solely due to the current household's income.
21:31And we need to think about those, you know,
21:33potentially systemic and structural factors that have played
21:37a role in putting populations at a higher increased risk
21:41for all kinds of climate events.
21:44And then lastly,
21:45we found that participants stay at home
21:47even when they can't keep cool.
21:49So when we asked the question about what do you do
21:52when you can't keep cool at home during very hot weather,
21:55I think it was either the top response
21:57or maybe it was the second response was just stay home.
22:00And this is, I don't know,
22:04is it intuitive or counterintuitive?
22:06What do people think?
22:11<v ->I think it's counterintuitive</v>
22:12'cause we would think people it's too hot
22:15and go out to public library or (indistinct).
22:21<v ->Yeah, I mean I think that's what a lot of us think</v>
22:24when we're thinking about potential solutions, right?
22:28We suggest operating cooling centers
22:30and you know,
22:32having people come to them.
22:33But I think if you also think about it,
22:36you can also see the perspective
22:38that it could be intuitive as well
22:40because do you really wanna leave your home
22:44where you tend to be comfortable and just go
22:48sit somewhere with strangers?
22:50So it's, you know,
22:51I think it's something to keep in mind in terms of
22:55the solutions that we're implementing
22:58because we need to think about how can we...
23:02I think cooling centers are an important measure,
23:04but also how can we keep people cool at home?
23:08And in particular, I think we thought a lot about this
23:12during the Coronavirus pandemic
23:13and New York City was one of the places
23:15that actually was able to get enough resources together
23:19to provide air conditioning at home
23:22and subsidize that for individuals
23:24because it was dangerous to go home and...
23:28Yeah?
23:28<v Student>Is there any laws that (indistinct)</v>
23:38That's actually, that's a good question.
23:40So I don't, I mean I'm sure there are,
23:44I mean maybe not in like public libraries,
23:47which are often used, but I think,
23:50I've heard sort of anecdotally that there are also concerns
23:55in some communities about sort of going to government
23:59sponsored places because of fears around other things,
24:04immigration status or other other things.
24:06So yeah, I think there's kind of like
24:09a lot of broad implications that need to be kept in mind
24:13in terms of putting this protective measure
24:16in a public space.
24:18Good question.
24:19Yeah?
24:21(indistinct)
24:29No it wasn't.
24:30So it was just a representative telephone survey
24:34of New York City, so.
24:36Oh, sorry, yeah,
24:38yeah it was a random digit telephone survey.
24:41So yeah, so I don't know if everyone heard that,
24:43but the question was,
24:45"Did this telephone survey sort of target a group residents
24:50living in an HVI area and that wasn't something
24:54we were able to do,
24:55it was a random digit dial of all New Yorkers.
25:01So, you know, so we potentially answered
25:04some of our questions but probably
25:06just ended up having more questions
25:08and I guess maybe that's good for us as researchers
25:11'cause we have more things to look at.
25:13But, you know,
25:14I think it's helpful to sometimes think about different ways
25:18of study quantitative methods, survey methods,
25:22qualitative methods to tackle different,
25:25different pieces of this complex problem.
25:29So I wanna talk a little bit about some of the impact that
25:31this work had before I move on in the discussion.
25:38So, you know, we were able...
25:42I think the findings from the epidemiologic study
25:46supported by this telephone survey
25:49and because we're working very
25:50collaboratively with the New York City Department of Health,
25:53were able to be used right away,
25:55which was a really nice, and this is...
25:59So a couple of years after the study was published,
26:02the New York City mayor implemented
26:04a cool neighborhoods NYC program.
26:06And this is, you know, what Kai was mentioning in the intro,
26:10this was a very,
26:12a lot of resources devoted to thinking about curbing the
26:16effects of extreme heat in New York City.
26:19And throughout the plan and through, you know,
26:23this is some language from the press release,
26:25you can see that the heat vulnerability index has mentioned
26:28quite a lot.
26:29And so I think, you know,
26:31what was really nice is this study had a very like,
26:35practical implication is that policymakers
26:38could take the results,
26:39look at a map pretty easily,
26:41and use this to target resources in this plan.
26:45So this part of the press release is talking about where
26:49they were doing some street tree plantings
26:51and cool roofs implementation,
26:54and you can see pretty clearly
26:55that they talk about the South Bronx,
26:57Northern Manhattan and central Brooklyn.
26:59Those were those red areas on the map
27:01and they specifically mentioned
27:03how the heat vulnerability index,
27:05those areas are ranked high according to the city's
27:07heat vulnerability index
27:09and that's why the resources
27:11are being targeted to those areas.
27:14The city also implemented a pilot program called,
27:17"Be a Buddy".
27:19And this program was also piloted
27:21in some of those high HVI neighborhoods.
27:24And in this program,
27:25this is specifically trying to get at those people
27:28who won't leave their home.
27:29This was a program to encourage neighbors
27:31to check in on others during extreme heat events.
27:36The city chooses to use the heat vulnerability index.
27:39So in 2020 during the Coronavirus pandemic,
27:43when again, we couldn't bring people to public spaces,
27:46there were some other initiatives,
27:47the cool streets initiative, and this was, you know,
27:50where they were opening fire hydrants and spray caps
27:53trying to create some mitigating effects of extreme heat in
27:57the outdoor environment,.
27:59And again, the city used the HVI
28:02to kind of target those where those measures
28:07should be collected.
28:10So a couple of takeaways from this collective work
28:15in terms of the findings, again,
28:17I wanna highlight that our study,
28:23like many, many other studies in the US
28:25has showed that black New Yorkers were much more at risk
28:29during heat wave events than other race ethnic groups.
28:33We see that pretty consistently in studies of heat
28:36and in studies of a lot of environmental stressors.
28:39But, you know, our research team tried
28:43to delve into that a little bit,
28:45but we really felt like there were a lot of unmeasured
28:47factors and this really points to kind of the potential for
28:52systemic discrimination that has been, you know,
28:54happening for years that may be at play here
28:57and in a lot of this work.
28:59And I'm gonna talk about some continuation
29:01of this work next.
29:03And I think that's an important thing to highlight.
29:07We also really feel that there's a lot more to learn about
29:11housing in the indoor environment.
29:13And I think this is probably one of the major areas
29:17of potential future research for people
29:20that are interested in heat,
29:21is really getting a better understanding
29:24and characterization of where people spend the majority
29:26of their time and the indoor environment
29:28and the kind of the range of health impacts
29:30that might be mitigated within that indoor environment.
29:36And in terms of process,
29:39we're really critical to work with stakeholders
29:42from the beginning so that this research
29:45could inform policy.
29:46And that was really one of the things I was very fortunate
29:49to work directly with the New York City Department of Health
29:51because they were able to help define the question and help
29:55and that made research able to be used.
29:59And so in future work I continue or current in future work,
30:03I continue to try to work with policymakers,
30:07with grassroots organizers to try to incorporate
30:09their ideas early on.
30:11And I think that's something that's always useful
30:13if you can find those connections
30:15to make your research relevant.
30:20And then also just the utility of maps.
30:23It seems very simple, but I think the fact that we had
30:26a nice easy to understand map really helped
30:30our vulnerability index again, to be used.
30:33It could tell a story right away to, you know,
30:37somebody that doesn't know a thing about epidemiology,
30:40but if it's very easy to it to look at a pretty map
30:45and kind of understand it.
30:46So I think, you know,
30:48that again is kind of continue on
30:50in that thread a little bit.
30:53So I wanna talk a little bit about some work I've been doing
30:57a little last couple of years,
31:00That flowed outta that New York City work
31:04to some extent and also just reflected a lot of other
31:07current thinking at the time.
31:09And this is some work that I was doing before I moved over
31:13to Johns Hopkins.
31:14About a year ago I was at a public policy research institute
31:17called RAND. And so this is where I started there
31:19with some collaborators,
31:21myself and the other lead investigator Ben Preston.
31:25And I'm continuing to work with my RAND collaborators
31:29on some of this stuff.
31:31And so this was kind of thinking about, you know,
31:34we see environmental health studies of environmental health
31:38and racial disparities over and over
31:40kinda pointing to the same factors.
31:43And in some ways it's very unsatisfying
31:46to talk about things like certain race or ethnic groups
31:51as being more vulnerable because this isn't an inherent,
31:54this is a construct, right?
31:55This isn't an inherent characteristic
31:58that makes someone more more vulnerable.
32:02There's a lot of systemic factors that have gone into this.
32:05So what we wanted to do was kind of delve into a little bit
32:09more of that systemic and structural factors that have led
32:14to the environmental health disparities that we see today.
32:19And so I will just briefly,
32:22let's see, should I,
32:30so I don't, so just for some,
32:34some added context and background,
32:36and I think, you know,
32:38in the last few years the literature's
32:39kinda exploded in this area.
32:41So I probably don't need to give this background,
32:43but I'll briefly say that one of the measures
32:46that we started looking at as well as many other researchers
32:49have been looking at is these historical maps
32:53that have characterized a discriminatory practice
32:57called redlining.
32:58And this was a practice that happened in the US in the 1930s
33:04that kind of basically codified discriminatory lending.
33:08And this is a map of Baltimore where you could see that
33:11areas in the center of the city were what we call redlined.
33:14And those were areas that were marked as being pretty risky
33:18for mortgage investment,
33:20whereas other of the surrounding areas,
33:22the kinda green and blue areas were areas that were deemed
33:25not as risky.
33:26So mortgage lending could, you know,
33:27more freely happened now.
33:29And the thought is that, you know,
33:34where this occurred,
33:36this sort of created both segregation and economic inequity
33:41that has lasted for generations.
33:44You know, creating real,
33:46real wealth gaps in communities because of these
33:50discriminatory practices that happened
33:52about a hundred years ago, right?
33:54Because people could not get mortgages,
33:57they couldn't accumulate wealth over time,
33:59they couldn't pass it on intergenerationally.
34:01And I think the key thing
34:04to think about there is some historical archives.
34:07We can see the language that was used
34:10to make some of these determinations.
34:12Now it wasn't a hundred percent always based on race
34:16or whether the residents were foreign born or not,
34:19but in many, many cases it was very explicit
34:24in terms of how they made these characterizations.
34:26So I think, you know,
34:27it's a pretty clear example of a discriminatory practice
34:33that was pretty embedded throughout the US.
34:36Now there's been also,
34:38I do wanna mention discussion in the literature
34:40as sort of whether this is,
34:42you know, was it this redlining practice
34:45and these maps or was it other types of discrimination
34:49and segregation that was happening before that?
34:51And this was sort of a result of that?
34:53I think for our purposes is, you know,
34:55a lot of epidemiologists and geographers
34:58have become interested in this.
35:00We know there were lots of discriminatory practices
35:02happening at that time.
35:04So I don't think we need to necessarily know
35:06that this was the be all and end all,
35:08but I think we can use this as a very good measure
35:12of the things that were happening.
35:13And so that's how many people have been using it.
35:16And that's how we used it in study where we really again
35:21wanted to think about how to change the dialogue,
35:24one that focuses explicitly on race and racial disparities
35:28to one that focuses on practices and policies and racism.
35:34At the time when we started this study,
35:36there was a little bit of work being done in this area.
35:39As I said, it really has exploded over the last few years,
35:43but there was a really nice paper by Jeremy Hoffman
35:45and colleagues that looked at heat islands
35:49across the US and how the spatial distribution of heat
35:53really varied within cities and mapped those
35:57pouring to these redlining maps
35:59and showed very high correlations
36:01between areas that were previously redlined
36:03and those being the areas that still retain the most heat.
36:07We kind of knew that this was the case,
36:10not just with heat, right?
36:11There's so many environmental aspects that we see
36:14in these sort of,
36:16that play a role in these environmental health disparities.
36:19So goal of this project is really to kinda bring a lot more
36:22data into the picture,
36:24look at a broad range of environmental hazards
36:27and see if we could make that data available
36:30for people to use it and kind of look at
36:32these associations more closely.
36:35Other goal of this topic was to think about solutions
36:38and what communities are currently doing to kind of mitigate
36:42these long-term systemic problems.
36:45So we did that by taking data from multiple sources.
36:51So we took some of that temperature data,
36:53but we also took data on air quality,
36:55hazardous waste sites,
36:56a lot of EPA data,
36:59the redlining maps that were digitized
37:02by the University of Richmond.
37:03We wouldn't have been able to do this project without that,
37:06as well as some land cover data.
37:08We took all of that data for our quantitative piece.
37:11The other thing we did was we worked and partnered
37:14with a grassroots organization called Groundwork USA.
37:18Groundwork USA is a network of trusts,
37:21environmental justice organizations across the country
37:24working specifically on kind of mitigating these issues of
37:29environmental inequities and communities.
37:32And we interviewed the groundwork trusts
37:34and we interviewed the policymakers
37:36that they're working with to find out
37:38what are they doing now,
37:40how are they trying to rectify this issue,
37:42what are the barriers they faced?
37:46So in terms of this study,
37:48well the first thing we did was put a publicly available
37:51tool together.
37:53And I have a link here at the bottom of the slide.
37:56The tool is finally published just about a year ago.
38:01And I also wanna highlight that someone who has way better
38:05coding skills than I do is a doctoral student,
38:09a doctoral student at the party rating school,
38:11Carlos Calvo Hernandez.
38:13So he really was instrumental in building this tool.
38:16But we have data on about 200 communities in the US
38:20and we have two dropdown menus for this tool
38:22where you can pick the community
38:24and you can pick the environmental hazard
38:26and then you can see maps comparing
38:29those historical redlining maps
38:31and as well as the distribution of all of these
38:33environmental metrics and how they exist today.
38:36And you'll see quite consistent patterns
38:39across a range of cities
38:41and across a range of environmental metrics.
38:46And in general, just to show you some descriptive results
38:49from that work,
38:50we consistently see this is from data
38:52from all of the communities.
38:54So things like diesel particulate matter
38:56are carcinogen much higher in previously redline areas
39:00than in other parts of cities.
39:03Counts of hazardous waste sites higher,
39:05again, in those formerly redline areas.
39:08When we talk specifically about climate related stressors,
39:11others have shown this.
39:13But we did look at tree canopy cover.
39:15I again see that consistent pattern where areas that were
39:18previously redlined have much less tree canopy
39:21than other parts of the community.
39:23We looked at gridded climate data,
39:27so we were able to look at average minimum temperatures
39:30over a summer season, mean temperature,
39:32maximum temperature.
39:34We know that minimum temperature can be important
39:36in terms of health because that's the time
39:38when the body can cool down in the evening
39:41and we consistently see higher minimum
39:44temperatures in those previously red line areas.
39:47And another metric that I'm really excited about,
39:50a paper that was published not too long ago,
39:53by Remedia Et al.,
39:55They put together a estimate of air conditioning
39:58prevalence by census tract in many major cities in the US
40:02And so this is,
40:03we're working on this now
40:04to get the paper ready for publication,
40:06but I looked at the air conditioning prevalence by these
40:10redlining measures and we can still see
40:12while air conditioning prevalence doesn't vary a lot,
40:15we can still see,
40:16and it's statistically significant
40:18in our regression modeling of it,
40:20that there is a lower prevalence of air conditioning
40:23in those previously redlined areas.
40:27Now, in terms of what we learned from the interviews
40:30with Groundwork USA,
40:32there is a lot,
40:33and I'm not gonna go through all of those results.
40:36We published a paper last year on those interviews
40:39and a lot of the policy solutions people are working on,
40:42so if this is something you're interested in,
40:45I encourage you to take a look at that.
40:46But the response that we heard
40:50from the trust over and over again
40:52was something that I found really interesting
40:55was that they themselves and their constituency
40:59had a lot of concerns about greening solutions
41:03and quotes from interviews,
41:07and I'll let you read them yourself,
41:08but generally these
41:14were basically within the context
41:15of people being concerned about displacement
41:18or what some people are calling green gentrification.
41:22So there are a lot of concerns about like,
41:26are you putting trees in here for me
41:28or for the person who's gonna buy up my land
41:32and displace me?
41:34And so this is something that Groundwork
41:36has taken really seriously.
41:37And one of the things that they told us that they're doing
41:40to address this issue is to really think
41:43holistically about solutions.
41:45And that is when they're advocating for greening,
41:47they're simultaneously advocating for housing protections.
41:51And I think, you know,
41:52with these types of issues,
41:53we really need to think very holistically,
41:56even as researchers when we're recommending solutions about
41:59the potential unintended consequences.
42:03So with that work we see of across a variety of hazards,
42:08we see pretty consistent spatial patterns
42:10that this systemic discriminatory practice,
42:13whether it's redlining or other things that will hopefully
42:16start to measure better soon,
42:18as potential drivers for some of the environmental
42:21inequities we see today,
42:23even with some regional variation,
42:25we still see that those relationships hold up
42:29and it's really important to think about implementing
42:32interventions that may avoid unintended consequences.
42:36So thinking about holistic solutions are really,
42:38again, an important piece
42:39of how we're gonna move forward with this and progress.
42:44So, you know,
42:45this work has really gotten me thinking a lot
42:48about how to better consider structural racism
42:51within climate and health studies.
42:53And I wanted to...
42:54This work is very much in progress.
42:56I wanted to just go highlight my doctoral student,
42:58current doctoral student, Shifali Matthews,
43:01because she's been really digging into thinking about,
43:03she's using the case study of hurricanes
43:06and trying to think about how can we do a better job
43:09of looking at these systemic upstream factors.
43:12And she's started off that work by doing a literature review
43:17to look at, well,
43:18how have we in the past considered vulnerability
43:20to hurricanes?
43:21And I know this graph
43:23isn't in the best shape at this point,
43:25it's very preliminary,
43:26but what I can tell you is the bar all the way on the left
43:29is a bar of demographic.
43:32So that's by far and a way how we generally look at
43:36vulnerability things like age,
43:39race, and ethnic groups,
43:40social economics, gender.
43:43The second to the, you know,
43:47or maybe the one, two, three, four,
43:50fifth bar over is structural factors.
43:53And I think we found maybe four or five studies that looked
43:57at structural factors and sort of
43:58upstream policy factors.
44:01So you can really see the literature has not explored that
44:05as much and Shifali's been thinking about this
44:08you know, is working on recommendations for this paper.
44:13So I wanna close out with just a mention
44:15of really briefly two studies.
44:16I know that when Dr. Chen first invited me here,
44:19I think he was hoping that I would talk about one of these
44:23and I was hoping that too,
44:24but we've had some big delays in in these studies,
44:27but, you know, maybe if I'm able to come back
44:30in a year or two, maybe I can put on some findings
44:34on some of this new work.
44:35But we have two studies
44:39that are really kicking off right now.
44:41One is very much focused on heat
44:44within the city of New Orleans.
44:46And a lot of this is building off of the New York City work.
44:51And really, again,
44:52thinking about what is the right threshold
44:54that we start to see hospitalizations.
44:56We're working with Louisiana Department of Health
44:59to look at more hospitalization data.
45:01What are the neighborhood factors?
45:03We know that there's a high proportion of the population
45:08in New Orleans that is living in poverty.
45:11And so it's a particularly heat vulnerable area.
45:13And we have three things that we're doing study first,
45:17again, sort of characterizing that burden
45:19from a threshold perspective,
45:21looking at vulnerability,
45:22very similar to the work I showed in New York City.
45:25So we're hoping to create a heat vulnerability index then.
45:29Then which is one of the most exciting parts of the study.
45:33And we'll be in the field this summer
45:35and hopefully we'll get participants and get good data,
45:38but we're partnering with a group called I See Change
45:41who has a digital application where they allow participants
45:45to just report on climate change
45:47and the findings,
45:49sightings in their own neighborhoods.
45:50So we're gonna work with I See change to get participants
45:53enrolled in our study to answer questionnaires
45:56through their app that kind of report on day-to-day
46:00subtle changes, changes in mood,
46:02changes in sleep patterns,
46:05and kinda subjective health measures
46:07that will correlate with day-to-day changes in temperature
46:11and even within day changes in temperature.
46:13So I'm really hoping that that data collection
46:15goes well this summer.
46:17The other study that is kicking off now
46:19is building off of the work I talked about
46:23related to redlining and green space
46:26and we're adding on a health component to that work
46:30and really thinking about how neighborhood factors
46:34can play a role in cognitive function.
46:36But there's been little attention
46:38on the relationship between green space
46:40and cognitive function to date.
46:42We do see huge racial disparities,
46:45and so maybe again these systemic factors
46:47that have led to very different environments
46:51where people have green space around them
46:53may play some role in in these health disparities.
46:59And you know, this question around green gentrification,
47:02does that modify the relationship?
47:03Does that make green space have benefits
47:07for some groups of people while it's detrimental to
47:10other groups of people?
47:12So in this study we're gonna be looking at,
47:14we've already kind of looked at,
47:15as I mentioned,
47:16the relationship between historical redlining
47:18and green space.
47:19We're adding on measures of cognitive function
47:21in a nationally representative study.
47:23We're gonna be examining that,
47:25looking at this maybe as a potential mediation pathway
47:29and I'm looking at gentrification as a modifying variable
47:32as well as potentially the role of social support
47:35in cognitive function.
47:37So, you know,
47:38I hope we'll have some preliminary results
47:40in that also maybe within the next year.
47:44So hopefully just sort of in wrapping up,
47:46I think, I hope you can see that there are many ways
47:49I think that climate health research can inform policy
47:53from, you know, characterizing the burden,
47:55understanding triggers and thresholds,
47:59thinking about drivers of vulnerability
48:00and how to target resources
48:03and also thinking about solutions.
48:06I didn't get to talk at all
48:07but I'm very interested in the effectiveness of solutions.
48:11I think that's a huge area for us to be working on.
48:14Love to think about that with anyone who's interested
48:17in thinking about that more.
48:19But as I did show, you know,
48:21I think solutions really we need to think about
48:23all the potential unintended consequences too,
48:26and that's a key role.
48:28So with that,
48:31I'd like thank you for your attention
48:34if you are interested in any more information,
48:38I have my website here.
48:39Probably be posting some postdoc opportunities there soon
48:43just in case anyone's interested in that.
48:44But yeah, and really thank you all very much.
48:55<v Dr. Chen>I think because of time,</v>
48:56let's have two questions.
48:59Yeah.
49:00(indistinct)
49:10<v ->It's actually a great question.</v>
49:13<v ->And I-</v>
49:14<v Dr. Chen>Could you please repeat the-</v>
49:16<v ->Oh, sorry, yes,</v>
49:17So the question from the audience was...
49:24The person here mentioned that they've heard
49:26of the Be A Buddy program in New York City
49:27and they were wondering if it was actually effective.
49:31And so the answer is I don't have the answer to that.
49:33I've actually asked the collaborators
49:36if they've ever been able to evaluate that program
49:39and I think they wanted to,
49:42but I think they had some resource constraints
49:45around actually doing an evaluation.
49:47So I'm not sure they were ever able to evaluate it.
49:49And in transparency, I actually don't know
49:53if it's continued at this point.
49:57Yeah.
49:59<v Student>When you run into (indistinct)</v>
50:28<v ->Yeah, being on so,</v>
50:30well I think I'm actually,
50:32I'm not sure.
50:34Let me repeat what you're saying
50:35and I'm not sure if I'm totally understanding the question,
50:37but I think question was,
50:38when you start to hear things about potential
50:41unintended consequences, so for example,
50:44someone responding that they're not sure the greening
50:46is really meant for them
50:48or is it meant for the person
50:49that's going to potentially displace them?
50:52What are some workarounds
50:54about not being able to quantify that risk?
50:57Is that right?
50:59So I think, yeah,
51:00there's a couple of answers to that question.
51:05So one is I think it actually does point to the value
51:08of kind of mixed methods research
51:10because and I kind of grew up trained
51:13as a quantitative researcher
51:14and it was only more recently that I've been exposed to
51:19interviewer qualitative studies.
51:21And I think there is a real value
51:23to kind of interdisciplinary collaborations
51:26because we might not have good quantitative data on that.
51:30Yeah, there are studies that are looking
51:32at green gentrification,
51:33we're gonna look at it in the study I just mentioned,
51:35but it may be happening in some places,
51:39it may not be happening in other places.
51:42There may be a lot of things
51:43that are triggering gentrification.
51:45So it's hard to tease that out.
51:47But I think we can just put some value on the words
51:50that that person is speaking.
51:52Those are the person's like feelings, right?
51:56That's how...
51:56And so whether objectively by one of the 10 ways
52:01we can define gentrification,
52:03it's happening,
52:05that person may still be dealing with mental stress
52:08and anxiety related to tho those feelings.
52:11So I think that's an important piece.
52:14So sort of thinking about how that, that might relate
52:19to mental distress and also thinking about
52:20the value of qualitative research.
52:25<v Dr. Chen>So I think because of time,</v>
52:27(indistinct) thank you again for.
52:34<v ->(indistinct) for our online audiences,</v>
52:36thanks for staying with us. <v ->Thank you.</v>
52:38<v ->We got to end this masters seminar series</v>
52:41and only all the best for the families, okay?