Symma Finn: Good afternoon and welcome to the Partnerships for Environmental Public Health Webinar, entitled Environmental Health Disparities. My name is Symma Finn, and I’m a Program Administrator at the National Institute of Environmental Health Sciences, Division of Extramural Research and Training. I will be the Moderator for today’s session, but I wanted to acknowledge the Coordinator of the Partnerships for Environmental Public Health Program, Liam O’Fallon, for organizing this session today. I’m very pleased to introduce our presenters for today — Dr. Peggy Reynolds and Dr. Thu Quach of the Cancer Prevention Institute of California, Wig Zamore of the Somerville Transportation Equity Partnership, and Dr. Christina Fuller of Georgia State University. The first presentation will be given by Drs. Reynolds and Quach. Dr. Reynolds is a Senior Research Scientist at the Cancer Prevention Institute of California. Her primary research interests have focused on social and environmental influences in the etiology of cancer. She has conducted a number of occupational epidemiology studies, including a study of malignant melanoma among Lawrence Livermore Laboratory employees, cancer incidents among California teachers, and cancer incidents among flight attendants. Dr. Reynolds was a co-investigator for a multicenter study that has become one of the most influential human health studies on the risk of lung cancer from secondhand smoke. The landmark publications from this study have figured prominently in national and international assessments of secondhand smoke as a cause of lung cancer in nonsmokers and have provided some of the critical underpinnings for the dramatic changes in public policy over the last decade regarding regulating smoking in the workplace. She’s one of the founding members of the California Teachers Study, a large, ongoing prospective study of 133,479 women, established in 1995. Within this cohort study she’s examining air pollution, secondhand smoke, and persistent organic pollutants in relation to cancer risk. Dr. Quach’s primary research interest has focused on immigrant populations and the environmental, occupational and sociocultural factors that may influence their health. She has conducted a number of studies focusing on occupational exposure, health and safety in nail salon workers, many of whom are Vietnamese immigrants. Her research in this area has influenced local, state and national policies and has helped to promote workplace change. In addition to her role as Research Scientist at the Cancer Prevention Institute of California, Dr. Quach is the Research Director of Asian Health Services, a community health center in Oakland, California’s Chinatown, serving low income patients, many whom are Asian immigrants and Pacific Islanders. She has a strong commitment to community-based participatory research and has worked with different advocacy, environmental, and community-based organizations to leverage public health goals that promote the health and wellbeing of underserved populations. Dr. Reynolds and Quach? Peggy Reynolds: Well, thank you for the opportunity to talk about our work on this morning’s webinar. I will start out by giving a very brief project overview, then turn it over to Thu to give a little more detail about that, some information about results of this project, and a word or two about conclusions and next steps. Starting with project overview, this was designed as a community-based participatory research project with the objective to identify and characterize neighborhood level environmental hazards and health barriers for Vietnamese population in California. I should say that this was funded as one of the Challenge Grants from NIEHS to address the challenge area of health disparities and in response to the challenge topic, building trust between researchers through capacity building and environmental public health. As such, our primary purpose was to develop strong partnerships between researchers and community members to promote environmental public health. So, as I mentioned, the target population was Vietnamese Americans with a special emphasis on hair and nail salon workers because this really was designed to build upon ongoing work around promoting worker health and safety in the nail and hair care sector. We targeted four areas of California, bringing up the map now, these were areas with high density of Vietnamese populations. If you’re familiar with California you may know about Little Saigon in Orange County and the very high density in these populations in Santa Clara and Alameda County. What may seem unusual to you is the inclusion of Marin County, not necessarily known for environmental health disparities, but as we learned in the process of working with our community partners, it’s actually an area of there’s an area of Marin County that is very densely populated by immigrant populations and where there are a number of environmental justice issues at play. So the partnership really came under the umbrella of our ongoing work as part of the healthy nail salon collaborative and a close partnership between CPIC and Asian Health Services in Oakland. Asian Health Services actually integrates and incorporated participation from several [CDOs] in California representing each of the four geographic areas of interest which, in turn, recruited community members to participate in this project. And so the project was designed to be somewhat iterative, certainly circular. We began with the community with focus groups to identify specific concerns, moved that on into the community audit, which we’ll discuss with you in a little more detail. We trained community members. Together we selected audit areas, conducted the survey. And then we conducted a series of debriefings, along with our partners, the community auditors, who then joined us to circle back to the general community to present community forums in each of the four areas of study. As part of Phase I, we conducted 16 focus groups with Vietnamese community members. We conducted them in each of the four regions of interest and different age groups. We wanted to get input and insights from youth, from the elderly, and in general from adults in the community. There were a total of 94 participants across those groups. As part of the focus group process, we used topic guides to elicit information about community perceived economic, environmental, social and built environmental stressors, as well as health access barriers, and to really get a flavor of what the participants thought about environmental concerns and health. Phase two, and the primary activity for this project, was the community audit. We ended up training 66 community members to conduct surveys of the neighborhoods where they live, work, and play. The objectives really were to characterize differences in those neighborhoods and a host of factors economic, environmental, social, and built environmental stressors and also to raise the consciousness of participants through the process where they collected data about their own neighborhoods. As part of that process we identified both work and home areas and areas, some additional areas that community members identified as being particularly important for their own communities, and then we selected audit segments based on one of those areas and trying to get a balance between residential and business areas and just to give you an idea here is an audit map of selecting the street segments for one of the audit groups in Marin County. And so, with that, I think I will turn this over to Thu to give you a little more detail about the nature of the community audit and on some, a few snippets of results. For those of you on the webinar, Thu actually is pictured here, as the left-hand partner and setting up a community audit survey, so, Thu? Thu Quach: Thanks, Peggy. So, again, I just want to go over what a community audit is and here we have just pictures of some of our staff, posing in very fashionable orange vests there, that we also have the community auditors wear for their own safety. But we usually encourage folks to go in pairs or in groups of three, and what we would ask during for them to do during the audit was really to do this Photovoice process, where they actually took pictures in the segments where they were assigned of things that they thought were important or negative. So the first person on the left would write down, log down what they took and why they thought it was important, whether it was a positive or a negative. The person in the middle is holding a camera where she or he would take a picture of something and then also press the GPS button so that we know where the pictures were taken. And then the third person is actually completing the community audit survey, which we’ll go over in a little bit, and also carrying a black carbon monitor right I think she’s carrying it by the little bag, the blue bag that you see, and that’s a really small, real-time sensor that allows us to detect some of the black carbon. So why black carbon? Black carbon comes from the burning of fossil fuels, biofuels and biomass. It’s caused some health concerns because it’s a really it’s a [soot] particulate, but it’s really small and can deposit in the lungs, and it’s often an indicator of exposures to diesel exhaust, which has been classified as a toxic air contaminant, as well as a probable human carcinogen. In California we have I think three stationery monitors only, that’s really doing all this real-time collection, so there’s not a lot in terms of data collected around black carbon even though it’s been an emerging concern. In terms of our community audit survey we actually based it upon an existing audit survey developed for the aging population from the St. Louis University School of Public Health, but we made some modifications based on what our findings were from our focus group. Here you see some pictures of the community audit. We took information around whether it was a residence, what kind of residential areas and buildings were there. We also took — we also had them write down food destinations, retail places, like gas stations, auto repair shops, nail salons, drycleaners, and also recreational facilities. And then here are some of the audit survey items that came from our focus group. Really there were some concerns around idling trucks or buses, which really contribute to black carbon levels, so we had them note that. One of the things that came from the focus group was around neighborhood safety, and so we had them document things around graffiti, broken cars and glasses, metal bars on windows of storefronts were really important. And also another thing that came out in some of the regions was around secondhand smoking, and the high smoking rates in the Vietnamese population. So what we tried to do is capture things around cigarette and tobacco advertisements, as well as cigarette butts on the ground. The other thing was around litter, and so a lot of the community members talked about littering. And so we had them kind of take pictures, as well as document litter that they saw in the yards, as well as in the street. So what we asked auditors to do during the process? Here is an example of what a street segment may look like, and you often would have two, possibly three auditors carrying their survey, as well as a camera. And what we asked them to do is walk down the street and cross over and just circle back to where they started, really giving them the time to really observe their surroundings, really take note of things and take pictures before they started completing their audit survey. And then when they’re done with that, we had them walk the middle of the segment and actually conduct a five-minute car and truck count, so they would count the number of cars and trucks that pass by in five minutes on one side of the street. Here is a breakdown of our community auditors by the four regions that we focus on, as well as the number of audit segments that they conducted and then also the break-down of men and women in our community auditors. We see a lot more women participating in this. Some brief results for us — again, the issue around metal bars on storefronts to indicate some issues around neighborhood safety. Here are some pictures taken in various areas, including in Oakland. And here is a graph, these are — we intentionally showed you the same graph that we presented back at the community forum to get a flavor of what we were presenting back to the community. You really see here that over 50% of the street segments that were done in Alameda actually had metal bars on their stores, much less than in the other regions. Graffiti was another issue, and you see some pictures here taken by our auditors. Here you have the breakdown of the four counties, again. And you see it’s a little higher in Orange County in Santa Clara and closely in Alameda, and less so in the Marin County area. Cigarette butts, again, showing some of the concerns over secondhand smoking. Here are some pictures there. And then you see sort of some of the cigarette butts, and they’re somewhat comparable across the four counties, led mostly by Alameda. Pictures of litter on the streets, some very interesting pictures taken by our auditors, we had a whole array of pictures that we took of all kinds of litter that they saw in the neighborhoods where they audited. And you really see, again, that there, you know, in Alameda there’s about 70% of the street segments that they did that actually had litter in it and then closely followed by Orange County and Santa Clara. I should say that in no way are we suggesting that the neighborhood segments are representative of the entire county. Again, these segments were selected based on the addresses of where our auditors live, work, or what they noted were important in their community because we really wanted them to conduct an audit that they were familiar with and neighborhoods where they were familiar with. Tobacco ads, this is a picture taken by one of our auditors around some of the storefronts, with a lot of tobacco ads on it. There wasn’t a huge amount, you know, here you see a scale of zero to 10%, but in Orange County we saw a lot more than in other areas. I should say that in our focus groups the overriding theme that came out, particularly among our young adults, was around smoking that’s being taken up by some of the young Vietnamese and so it’s interesting that we saw this. Here are the box plots of 5-min car counts and you can see that overall on average they’re about the same number of car counts that we were seeing except in some areas, like in Orange County, you see as much as 150 over a five-minute count. So on average are the same, but in some regions there is a lot more traffic. Five-minute truck counts, again, they’re similar except Orange County really does stand out in this one more so than some of the others. Here is a picture of the black carbon concentrations that were taken, and on average the different counties, the neighborhoods in each of those counties were similar, not — but they are usually around 1.0 micrograms per cubic meter. Interesting enough, we actually show you the state-wide measurements. Again, those are based on the three stationery monitors that California has for weekdays, and it is below one, suggesting that when you do these community collected audits, where you’re walking, it may have different numbers than what you would see if you’re using some of the existing data collected by the government. And this really came out as a big theme for us, you know, that as researchers if we came in relying on those stationery monitors we often may be underestimating the exposures. Another table showing the four counties, and in parenthesis next to the counties you see the county median levels. Again, they were close to one, however, when we started zooming into certain neighborhoods you will see that certain neighborhoods actually had peak concentrations that were 10 times, often even more than what we were reading from the county really, again, underscoring this issue around variation in terms of black carbon exposure. And we definitely don’t want to forget the positives that were really noted by our auditors. Here you have some pictures taken in Marin about showing the diversity in the neighborhood, faith communities, water, this is like open where people often like to exercise around [inaudible] and a lot of greeneries in there, a library, taken by one of our auditors, Kaiser, a healthcare place for them. And trashcans really suggest the sort of promotion of not littering. And Laney College, which is one of the community colleges there. Our auditors’ experience, which was really key for us in all of this, was they really expressed that they were proud to be a part of the project and to have contributed to research that benefits the community. They really — they told us they had a lot of fun doing it, going out there and exercising while they’re taking note of their neighborhoods, but it really provided them with an opportunity to meet new people and to make friends, really the social network type of theme. After the project, auditors thought that they were more aware of their environment, you know, and this really came out in the focus groups when we first started asking them questions around environmental health and there were a lot of the participants were saying, well, we really don’t think about it that much. But as the themes started coming out around traffic and trash and pollution the question was really raised, and they started asking a lot more questions, both in terms of the focus group, as well as the community audit process. And the auditors who were recent immigrants who participated really enjoyed this because they felt like they could meet new people and get to know their community. Many of them said they would love to participate again. One thing we were really happy about was they felt this ownership of the data and the project. Oftentimes we will look at the data from each of the regions and realize, oh, well, maybe we should collect more data because this one seems a little bit high and we just want to make sure about it. And when we brought this up to the community based agencies and the auditors themselves they would often volunteer to do this, really indicating this ownership and wanting to have really good data to present back to the community. When it came to presenting at the community forums many of them volunteered to co-present with our team, as well as with the community organizations. And a number of them have asked, well, what’s next? You know, we’ve started doing this, we want to do more, so we’re in discussions about future projects that have community engagement in it. Conclusions, really around this issue of community collected data, highlighting neighborhood level aesthetics, neighborhood safety, litter, traffic, sidewalk conditions and air quality as major community concerns. The community auditors really helped to identify contributing factors to environmental hazards. During the debriefing sessions we would show them, oh, well, here’s a neighborhood where we really saw some high concentrations of black carbon, and they would tell us, well, that’s interesting because that’s where a lot of the school buses come or that’s where we have a lot of idling trucks. The same thing around graffiti, like, well, what would be reasons why there would be graffiti? They really offered these explanations around, you know, feelings around gangs and, or feelings around youth really feeling displaced and wanting to have a place of belonging. So we really looked to them to explain a lot of the data that we saw. We saw differences between community collected snapshot data and government monitoring data and which can help us — which can help inform us on future research that we do, and it really provides the community with data that can be used to address local environmental concerns. There’s already been discussions about bringing it to their local council to address things like sidewalk conditions and all that. So, you know, we really are encouraging them to use this data. And it really helps to build positive relationships with the project participants, as well as our community partners. Next steps, we actually have been really busy. We’ve actually submitted several papers, one led by our community partner around community engagement process. And we’ll continue to work on a few others. We also are finalizing our fact sheets that we’re going to be giving to our community agencies. We’ll pass it around to the community so that we really are honoring this idea that whatever we find we really report back to the community. And we’re in discussions for applying for future grants that utilize a similar method of community engagement and focusing on environmental public health actions. And in the last minute I really do want to give a shout out to our different community based organizations that were a part of this project, that they really were at the helm of this in engaging the community. I think some of them are on the call, and again I just want to acknowledge them for all their hard work put forth and continued partnership in all of this. Symma Finn: Well, thank you, Dr. Reynolds and Dr. Quach. The first question that we did receive asks what is the environmental health disparity? How did your research study address environmental health disparity in the communities you studied? Thu Quach: You know, that’s an interesting question. I think that when we started engaging in this it really was this issue, particularly with the Asian American, Pacific Islander community in terms of often we go out to address these huge environmental disparities that it seems like, oh, it’s very obvious that there is something. But what’s come up is, well, what happens when we’re not sure? No one is really out there monitoring if there are disparities, and this project really gets that fact. We were looking into some of the enclave areas where the Vietnamese populations live, and we wanted them to be able to collect the data and identify if there are disparities. And in the results that we saw we saw that there definitely are some differences in the black carbon levels for certain neighborhoods. We’re looking more and more into that, but we definitely found some differences, depending on certain neighborhoods in terms of air quality. Symma Finn: Thank you so much for that answer. We do have another question — how can you compare communities when areas surveyed were not representative? Were there other more rigorous comparisons that you can make? Peggy Reynolds: You know, I will just start that off and then hand it over to Thu. I think keeping in mind that the objective of this project really was to engage partnerships with Vietnamese communities to better characterize the neighborhoods in which these people lived and worked, that clearly, for instance, in the Marin Vietnamese community, which has lots of new immigrant groups, including a very large Latino population, the characteristics of those neighborhoods are not representative of the characteristics of neighborhoods in Marin County in general. So we were really trying to start from a grassroots, ground up level in terms of people characterizing their own neighborhoods. So, yes, it may not be representative of all of the neighborhoods of Vietnamese communities in California or all, certainly not of all communities in California, but this is part of some ongoing grassroots work that we have been doing with this population. You want to add anything? Thu Quach: Yes, and I think here you really have to build up, you know, to ask a question of whether it’s representative or not? I think we really wanted to engage some communities to start exploring what environmental concerns they had and to really give them some of the tools to begin to collect their own data. This really gave us the opportunity to develop a tool that they can use again and again, along with some of the black carbon monitors. So we’re not looking to be representative, we’re looking into engaging the community to address some of the concerns that they may have. Peggy Reynolds: I might just add, again, that on the disparities issue, one of the issues that our group has been very engaged in studying are — is the heterogeneity of Asian groups, and we have many in California, and so that there are a number of disparities that are really unrecognized because Asians tend to be lumped into a single category and then we don’t really pay attention to some of the individual subgroup issues. And so this was an attempt to work with one particular Asian ethnicity that actually does have a number of certainly occupational risks in terms of some of the predominant occupations, but also some adverse neighborhood exposures, as well. Symma Finn: Well, okay. Well, thank you. We have several additional questions. We’ll ask one more now and we’ll save the other question for the end of the session. So our next question is did the community members collect GPS, GIS data on where the measurements were taken and could they be put into a map, so that they could be put into a map? Thu Quach: Yes, we had all that information, and they have been put in a map. Actually, when we went back and presented it we presented it in a map form for them so they can really see where they went and pictures that went along with it, pictures that they took, as well, aerial pictures of the neighborhood. Peggy Reynolds: And part of that objective of that mapping really was from the epidemiologic perspective, then compare some of the observations from these audit surveys to other data that are available, for instance, traffic density data that’s available for some of these street segments. Symma Finn: Well, thank you so much, Dr. Reynolds and Dr. Quach for the interesting presentation and for the answers. We will revisit the last question we had received, again, later in the session. But at this time I’d like to introduce the speakers for our second presentation — Mr. Wig Zamore and Dr. Christina Fuller. Mr. Zamore has a master’s in real estate development from the Massachusetts Institute of Technology’s Department of Urban Studies and Planning. He focuses on the continuum of issues that revolve around urban economic development, regional transportation, environmental quality and local public health, in short, sustainable development. In Somerville, Massachusetts he has been an advocate for dense transit oriented development and a leader in successful campaigns for a new subway stop and two new light rail branches. In 2007 and 2008 after reviewing excess heart attack and lung cancer mortality patterns in Massachusetts Mr. Zamore initiated and helped manage pilot-scale near-highway pollution studies with Environmental Health and Engineering, and with Aerodyne Research Incorporated. About the same time, he and other members of the Somerville Transportation Equity Partnership approached Doug Brugge of Tufts Medical School seeking collaborative community based research opportunities. Mr. Zamore has helped design and steer the Tufts-based Community Assessment of Freeway Exposure and Health, the CAFEH Study. Dr. Fuller is a Postdoctoral Research Associate in the Institute of Public Health at Georgia State University. Her research interests include characterization of pollution exposure, environmental epidemiology, environmental justice, and community engaged research. Her current research is in the area of traffic related air pollution, specifically ultrafine particles and its effect on biomarkers of cardiovascular disease. Dr. Fuller has worked as an Environmental Engineer in Chicago and as an advocate for environmental justice in New York City. She earned her bachelor’s degree in environmental engineering from the Northwestern University and master’s and doctoral degrees in environmental health from the Harvard School of Public Health. Mr. Zamore and Dr. Fuller? Wig Zamore: This is Wig Zamore, and I’m going to give the first half of this presentation and then hand it off to Christina for the second half. I’m happy to be included today. I think I’m the civilian representative. So our project is called CAFEH, Community Assessment of Freeway Exposures and Health, and it’s organized around Interstate 93 and investigates highway pollution gradients and neighborhood cardiovascular health at various distances from the highway. The second slide shows Interstate 93 going through Somerville, with Boston in the background, and our largest public housing project on the right. Our funders are lower left. We greatly appreciate the support of NIEHS. And on the right are partners in the project, with a few of the field team members in the center bottom. Next, I thought I would show you the different field years. We had three field years in this five-year project, of which we have about a half year left to do a final analyses. So lower left you can see Somerville, which is my community, and Interstate 93 and the various distances of study, of participants. Lower right are second year in Dorchester and South Boston. Top right Chinatown and downtown Boston. And top left Malden, which we used as a background population for the Chinatown year of study. This is the only — these slides here are just a reminder that air pollution affects more than just air and more than just people. And now a little bit on the study design. On the left lower we have a very well-equipped mobile laboratory, with both particle and gas instruments, and we’ll be creating an ultrafine particle model that will give values per hour for every participant for each field year and then a detailed prime activity analysis that came out of surveys. We have lead biomarkers from clinics, including C-reactive protein, and it will all be put through a structural equation model in the hopes that we can get a lot more significance than would come out of a simple proximity analysis. To go through how the community came up with this project, because it originated in Somerville and then extended to Tufts, and Tufts’ longstanding other community partners. We focused, first, actually on economic development in a community that’s mostly residential and lacks jobs and tax base. That led us to focus on regional transportation capacity and supply and that, in turn, led us to look at air quality and public health as levers in the public debates. So here’s Somerville, top left in gray, only four square miles. We pretty much had no clean light rail or subway transportation, but through advocacy of the last decade we have gotten the State to commit to a billion dollars of new subway and light rail transit. The orange T-stop is in Assembly Square, which is an area we focus on for economic development. The two green lines are the first new light rail projects in Massachusetts in a generation, and the subway stop is also the first in a generation. I’m going to talk a little bit more about the economic development, but that’s it for the transportation. So this area, Assembly Square, was largely industrial, had a big Ford plant and largely underutilized. And the bottom, I’ve tipped the orientation 90 degrees to show on the left the original developer’s preference, which was largely for waterfront parking lots and big box stores, and on the right the community preference for dense mixed use, mixed income housing and a lot of job diversity, as well. And we had quite a battle, but ended up with a nice settlement about six years ago, that involved taking 50,000 vehicles per day out of what was projected to be 100,000 vehicles per day to and from this area. Had a large cash commitment from the developers to transit. And, also, at the community’s desire ended up with dense mixed use plan for 10 million square feet, a little bit upside down from traditional NIMBY. And this is the picture of three urban multistory mixed use blocks underway this year and also the T-stop, which is underway. All of those will be open in two years. Now to go to the environmental health and air quality, we started to realize that we had a real issue, that it wasn’t just a political lever. And so we started to look at the literature and also to do some pilot studies of our own. And to go quickly, of course, Yifang Zhu’s seminal 2002 work showing that primary pollution gradients from highways did not really relate to PM 2.5 and regional standards. A nice paper by Gail Hagler out of EPA’s Mobile Labs Group, showing zero correlation between PM 2.5, PM 10, and ultrafine particles, meaning to us that there was no protection afforded by those max standards. And then the first ultrafine model world, we’re aware of which is in Stockholm, done by Gidhagan. And to move on to some of the seminal health studies, we again looked at Stockholm and the Nyberg lung cancer study, which showed that all the statistical significance from air pollution in Stockholm connected with lung cancer was coming from mobile sources and it was all coming from the top 10% of exposure, it wasn’t coming from an inter-quartile range. A similar study in Oslo, which I’m not showing. Then Mike Jarrett’s nice study of Toronto, where proximity alone was not statistically significant but he got a pretty good association of cardiovascular mortality, and NO2 as a mobile marker, and again a much higher relative risk for people closest to the pollution sources. And then finally a great series of studies in Vancouver by Gan and Brauer, where they found a 450,000 population, a very high cardiovascular mortality among the people who lived within 50 meters of the highway, somewhat less for a study of multi-pollutant ranges within the City, that multi-pollutant study had black carbon and nitrogen oxides completely eliminating PM 2.5 association with mortality within the City. Just to stay on housing for a second, these are pictures on the left of Eastern Massachusetts major affordable housing projects and on the right of highway pollution hazards marked by 50 or 100,000 vehicles per day. What you see is that the maps are identical. Our affordable housing is pretty much going in the highest hazard locations, at least in Eastern Massachusetts from an air pollution point of view. C-reactive active proteins, an important marker for us. It’s a little study by Hertel and Barbara Hoffman in Germany, showing sub chronic 21, 28 days and a little bit less statistical significance for ultrafine particle number count and CRP but not a statistical association with PM 2.5 or PM 10 in that study. Similar, but more complex study from Ralph Delfino with senior citizens in California, again, showing a CRP connected with mobile markers, although more black carbon in this case and primary organic carbon from mobile sources. Longer term study from Stockholm by Panasevich, pretty good statistical significance with IL-6, as well as CRP. And then Paul Ridker is one of our team members, but I’m not going to go into this slide. This is what I kind of use as my back of the envelope for health effects for people living very close to highways, basically, 50% to 100% higher cardiovascular, heart attack, and lung cancer mortality, as well as childhood asthma. To move a little bit to a description of the community, these are the cities that surround — Boston, Somerville is the densest city in the State, Chelsea also has a lot of immigrants, and is second densest. I often use these two together in presenting to people because of the pollution and socioeconomic issues. They’re quite similar, one and two, in density of immigrants, population, multifamily housing, a lot of need for State support per year because of shortage of jobs. Transit is largely buses and very high mobile pollution. The main difference being that Somerville also has a great density of college grads at this point who can contribute some mental energy to some of these issues. As I said, a lot of mobile pollution, and when you have a lot of mobile pollution and a dense population you tend to get fairly high health effects on a per square mile basis. So this is a five-year compilation of heart attack and lung cancer from Massachusetts public data, showing the greatest density of excess deaths in Somerville and Chelsea. It’s not epidemiology, obviously, but it corresponds with the literature and this was one of the things that spurred us on a little bit. And then just a sample of some of the really good socioeconomic and segregation work that’s been done from a large study by Rachel Morello-Frosch at Berkeley, looking at all the Census [facts] and air toxics, including diesel. Some of our pilot studies, we did two pretty, pretty important studies to us. One was the Environmental Health and Engineering that had some good outcomes from time integrated NO2 as a mobile marker, and then on the right we were fortunate enough to use Aerodyne Research and their really fabulous equipment set to look at a typical winter morning rush hour in Somerville. Some of the results, this is from the NO2 study, showing much higher concentrations in mobile pollutants near the highway, as would be expected. And here’s a — just a graph off the highway center on the left, showing how steep that time integrated NO2 signal is. And then here a nice paper we got from the Aerodyne work in Atmospheric Chemistry and Physics, on the right showing especially early morning, very steep gradients of ultrafine nitrogen oxides and other primary mobile pollutants. So we took these to Tufts and got together with their community based participatory research group, run by Doug Brugge. This is a picture of the CAFEH mobile lab and two of the grad students that have worked on it. On the left is Allison Patton, who has got the arduous task of creating the ultrafine particle model and that’s pretty, pretty well underway. Here is one year of results from 55 representative days of monitoring. In the center of each of these panels is Interstate 93, and you can see the gradients in either direction for the full year, top left, by season top right, the colder weather has stronger primary pollution gradients. On the bottom left is day of week. Sunday we don’t have a lot of sampling. And then bottom right is different times of day. And what you see especially is a pretty steep drop-off on the right-hand side, which is downwind, left-hand side is more center city in Somerville. Where we’re going from here kind of under the CAFEH umbrella, we have two sibling studies. We have a sub study that’s part of a large Puerto Rican health study, and the sub study is looking at mobile pollution and cardiovascular outcomes. On the right we have a HUD funded pilot study of HEPA filter intervention in Mystic Housing residence. It’s right next to Interstate 93, to see if we can lower indoor pollution and cardiovascular inflammatory biomarkers. And then, of course, on the bottom what remains the hard analytic work from CAFEH, and I think that Christina is going to talk a little bit about that, namely integrating the ultrafine particle model, the time activity, and the structural equation model. And, just to show you, we have very detailed time activities for all of our participants. The red being residential, in the top superfluous fulltime students for workers, the bottom is more retirees, and also time on highway and that kind of thing. And two concluding slides. From the community point of view the quandary is that we think the science is already there, that there’s very high relative risk of mortality and morbidity for people who live and spend a lot of time next to highways, but in the absence of some federal authority declaring this to be a hazard and getting that message out to both the public and policymakers, it’s going to be very hard outside of some places, like California, with their own science and policy to really start to design healthy cities. And we all know that cities are among the healthiest places on earth, but we really should be designing them in ways that will be healthy for a much longer time. Our infrastructure and our buildings last a long time, and we really can’t afford to throw another generation in the dumpster on these issues. So I’ll stop there. Thank you very much. Symma Finn: Thank you, Dr. — Mr. Zamore. Dr. Fuller? Christina Fuller: Thank you, Wig, for starting off our presentation. I just wanted to highlight more about CAFEH, that being a five-year cross-sectional study of ultrafine particles near highways and markers of information on blood pressure, which is cardiovascular health. And Wig and I will both be happy to answer any additional questions about how the study was structured and how we were able to make it a community based project at the end, but actually right now I’m going to discuss more about the preliminary results that we’ve had. So there are three areas included in the CAFEH study, as Wig mentioned — Somerville, South Boston, and Dorchester, and Chinatown and Malden. And here are more detailed maps of the study areas, to which I will be referring in this presentation — Somerville and South Boston/Dorchester. If you recall, the final analyses will use modeled hourly ultrafine particle concentrations as a measure of exposure and a structural equation model of health effects. But leading up to the full analysis we have examined health effects in our population with exposure measured in ways commonly used in literature. By this I would mean using central site data to look at acute exposure and proximity data to look at chronic exposures. And by doing these preliminary analyses we can elucidate the factors important to consider in our SEM and also to have points of comparison for the full model. From the Somerville sample of 142 people we looked at acute to sub acute affects associated with exposure to ultrafine particle concentrations that were measured at a distant site and located in Boston, about seven kilometers from our study area, which is an exposure that has been used in past epidemiological studies. And what this shows, on the left-hand side, are some characteristics of the Somerville population. And on the right-hand side are box plots showing our exposure measurements, lags of zero, one, and two days, and moving averages of three up to 28 days. On the Y axis are the percent increases in both [IL-6 and C-reactive protein. And there are estimates of the affects are for 5,000 particles per cubic centimeter increase in ultrafine particles, and what you can see is that for IL-6 there’s a 50% increase in IL-6 for a three-day moving average, up to the highest effect estimate which is 91% increase for a 28-day moving average. C-reactive protein was similar, with the highest effect estimates being a 74% increase for a 28-day moving average. And although our assessed estimates are larger than previous studies, possibly due to the imprecision of our measurements, as you can see by the wide confidenc intervals, which is not surprising based on the modest sample size. We’re just using our Somerville population. In CAFEH we have a rich dataset of personal characteristics, and although it is difficult to see differences in this modest sample size there are some factors that warrant further exploration in the full SEM model. There is suggestion that diabetes increases the effect of ultrafine particles on IL-6, as you can see from the box plot to the left, and also BMI greater than 30 may increase effect estimates of exposure to CRP and possibly dampen response in IL-6. As we look at longer time periods of exposure, our longest being 28 days, we become more interested in factors that may change chronic exposure, so 28 days is pretty much a sub acute near chronic exposure. And one chronic exposure factor that we’re interested in is the roadway. So see the highlights annual household income and education, which may be expected to result in health disparities and has done so in past studies. And so what I highlighted here are household incomes broken down by this is a highway less than 100 meters, 100 to 400 meters, and greater than 1,000 meters. And our background area, which is greater than 1,000 meters, the populations that have an income less than $16,499 is only 2% of that population, however, in our 100 to 400 meter group it’s 38%, and then 100 meters is actually 15%. When we looked down at 100,000, you see that there’s higher income people in our urban background neighborhood and fewer percentages at that income level in the nearer to highway locations. Our subsequent analysis of chronic exposures included both Somerville and Dorchester/South Boston neighborhoods. The distance for this analysis was broken down into five distance bins, as you can see in the upper left-hand corner. And this biograph shows CRP and IL-6 levels by distance to highway. All distance groups had an average CRP exceeding three milligrams per liter, which would be categorized as an elevated risk, and CRP was highest in the 150 to 250 meter group, followed by the zero to 50, and 250 to 450 meter group. Of particular note is how similar the CRP and IL-6 values are between the 50 and 150 meter group and the urban background. And some of the demographic and health measure variables were actually similar between those two groups. But what we were really interested in is how much CRP levels in the exposed distance groups, which we defined as 100 to 400 meters, how they differ from the urban background. And when we analyzed the data by restricting it to each study area we discovered that there are some differences. What this map is showing is the percent difference in CRP levels between each of the exposed distance groups compared to their urban background. And those percent differences are represented by the color scheme, with light being less than urban backgrounds, and lightest blue being zero to 50% difference, and up from there. So what we see in Somerville is that all the distance groups have a percent CRP difference greater than their urban backgrounds, with the highest difference being between the urban backgrounds and the zero to 50 and 150 to 250 meter groups. But when we look at Dorchester/South Boston we see a very different picture, where only the zero to 50 and 150 meter groups have a CRP percent difference above the urban backgrounds, it’s a much flatter slope. When we look at IL-6 we see, again, that there’s a difference in the patterns compared to the urban background by study area. For Somerville IL-6 of all distance categories have positive associations with the two furthest exposed groups contain a significant percent difference. When we examine the Dorchester/South Boston map we see that the percent difference is pretty flat across the exposed distance groups but the zero to 50 meter group contained the largest percent difference compared to the urban background. So we have hypothesized some potential reasons for these disparate findings between these two study areas. And one of them is that the urban background comparison group in Dorchester and South Boston has other participants that live adjacent to Dorchester Avenue, which you can see in the figure to the right, going north and south, and that is a significant source of ultrafine particles. However, when you look in Somerville there’s a road called Broadway, and there are no study participants that live very close to that highway. This shows, again, disparities in the chronic effects. So pretty much you look at the combined associations for IL-6 at the bottom, and CRP at the top, and you can see associations with distance to the highway compared to the urban background. When you break them out into Somerville versus South Boston/Dorchester you see that the associations are different depending on the study area and also depending on other factors, such as the city, how we recruited our sample, random and convenience, and being on one or the other side of the highway, but those are not quite as clear. So, in summary, with our key analysis we do see an increasing trend in affects for IL-6 and CRP, with increasing ultrafine particle concentrations, and that diabetes and BMI may play a factor. We also see chronic associations, as well, but there is a lot of variation depending on things like personal characteristics, like BMI, or exposure characteristics, such as time activity. Now I’m going to turn more to talk about how variability in exposure due to ambient or indoor concentrations for time activity can change the associations that we find. So if we examine this more, we looked at data from Somerville and collected particle number concentrations [as our proxy] for ultrafine particles. So we had instruments monitoring at six sites, they are represented here by BBB, which is one site, MAC, Mystic Activity Center, is another site, both in the study area. And then a central distance site, SPH, that’s School of Public Health that was in Boston. We did long-term monitoring there for a year, and then at a selection of 18 homes within Somerville we collected one to two weeks of monitoring there. So this table shows four models of outdoor residential ultrafine particles. For the first two lines you see the asterisk represents a percent of increase in residential outdoor ultrafine particles for a 10% increase in the fixed site ultrafine particles. Here, this first line, the School of Public Health, that’s the distance site & the second line, the Mystic Activity Center, is the near highway site. So what is shown is that more ultrafine particle variation at homes in the study area were explained by variation at the near highway sites as opposed to the central site. And one of the take home points is that near highway populations may be a vulnerable population. Using only central site data or proximity may not sufficiently capture these exposure variations for people who live close to highways. In addition, people spend the majority of their time indoors and it’s important to evaluate the representativeness of ambient concentrations when people spend most of their time indoors. So using our monitored data we looked at this, as well. And what this shows in a nutshell is that there’s evidence that highway ultrafine particle easily migrates indoors because overall indoor/outdoor ratios were close to one, although there was significant variation throughout the day and between homes. This is representative of during warm periods in this community, so that’s the only time where we took these measurements. So next there are several factors that impact the indoor ultrafine particle concentrations, and those include the outdoor concentrations were the largest predictor of what’s indoors, but also other factors, such air-conditioning, time of day, and meteorology. And what I have here is a time series plot of data from two houses — the one on top, which did not have central air-conditioning, and the one bottom that used central air-conditioning just to illustrate how air-conditioning can modify infiltration of ambient particles indoors. And to revisit the CAFEH diagram, which we’ve shown at the very beginning, of the plan for spacial temporal modeling of ultrafine particle concentrations, to look at our health effects, we see that each neighborhood is different in population and also in pollution landscape, which can lead to differences in health effects. And some do not exactly fit what we may expect to find in terms of demographic information or near highway concentrations. Central site monitors may not adequately capture exposures present near highways for pollutants with large [inaudible] variations, which may lead to exposure misclassification. And, therefore, we conclude that detailed exposure data and knowledge of population characteristics are really necessary for us to understand fully associations between ultrafine particles and cardiovascular health and will also give us the ability to highlight some of the underlying health disparities in a diverse data set. So that’s the last slide, and we’d like to, again, acknowledge our funders and also the CAFEH partners and community participants. Symma Finn: Thank you so much, Dr. Reynolds. We do have a question already — has there been any attempt to use buffer zones or anti-idling ordinances for trucks in order to improve the air quality in the area? Wig Zamore: Yes, there is an anti-idling law in Massachusetts. It’s not always upheld, but there have been some interesting forays by students, junior high school students, high school students, giving out tickets and bringing awareness to the issue. There’s also another group in Boston, which focuses on diesel pollution, and they’ve got quite a good campaign going in the City of Boston with regard to construction equipment, which is another large urban source. Symma Finn: Thank you. We also have a question for the first two speakers, Peggy and Thu, that we weren’t able to ask earlier — what policy change or change in public health do you expect to achieve from the program, what did the communities request in terms of changing the environmental health of their neighborhoods? Thu Quach: This is Thu. I first want to say that a lot of the work that we were doing was very developmental, that we were just starting off in this. However, when we presented at the different community forums the community had organized to bring out some of the politicians to show some of this. One of the issues that Peggy highlighted was what we found in Marin County, was that a lot of the Vietnamese living there actually lived in an area called, what they call the canal area, and there is a lot of Vietnamese and Latino population there. And they really brought up issues around air quality, as well as some of the racial tension. And during the presentation of some of this they had voiced some of their concerns to some of the policy decision makers at the community forum, so this is just the beginning of the community getting engaged in issues around environmental health. And so we are still in discussions around what we want to do next with it. Peggy Reynolds: I would just add that it’s also very relevant to the very impressive and extensive work that you’d seen in the second presentation because one of the major concerns in the Alameda County group had to do with traffic and there is actually concern about creating a new freeway off-ramp in the Chinatown area, which would even furthermore impact exposures in that area. And so our colleagues at Asian Health Services have seen this also as a valuable way to collect some both qualitative and quantitative data to inform the debates that are going on right now on that issue. Do you want to add anything? Thu Quach: Yes, I think that we’re in the process of discussing with Asian Health Services and some of their other community allies on providing the audit tool, as well as the black carbon monitors, and then working with others to secure particulate matter monitors for community members to conduct the same audits around neighborhoods where they want to put the off-ramp and then the other areas. So we are continuing to do research and collecting data that would inform some of the work that the community is doing and organizing around for local policies. Peggy Reynolds: And, again, many of these are issues that have been initiated with the community, so in that partnership they have primary ownership, they’re partners in a lot of it. Symma Finn: Thank you so much for that very comprehensive answer. We have another question for the second two speakers — they’re asking when will the Boston study be published? Wig Zamore: We’ve probably got about four papers out there in various pieces. Christina has a recent paper in Atmospheric Environment, and we put the Somerville year in Atmospheric Environment, as well. I think that our analysis is going to take another half year, at least, before we can get out some comprehensive conclusions. And, of course, we’ve got our fingers crossed that the original hypothesis of getting detailed personal exposure over the course of a year, plus the time activity and the use of the structural equation model will produce results that are clearer than the small short pieces that we’ve put out using kind of more, more traditional and less accurate methods to date, but we wanted to get going on some things to guide the fuller analysis. So that’s why we’ve proceeded that way. Symma Finn: Thank you so much, and thanks to everyone for participating in today’s session. Before we close I’d like to make a few announcements. Your feedback is very important. After today’s webinar please take a moment to fill out the short evaluation form. Your feedback is very vital to helping us ensure that we’re providing the highest quality speakers and information to meet your needs. Please keep in touch with PEPH with the listserv and the PEPH eNews, sign up today by e-mailing [email protected] on your screen now. Upcoming webinars, at the end of October we have plans for a webinar focusing on children’s environmental health and information about that and other upcoming webinars, as well as the registration links will be on the PEPH Events page as soon as they are available. The Events page is shown here on the screen. And we really want to thank, once again, to all our presenters for your most interesting presentations today — Dr. Peggy Reynolds, Dr. Thu Quach, Mr. Wig Zamore, and Dr. Christina Fuller. That concludes today’s webinar. Thank you, again, for participating.