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

Transcript

• 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?