A community participatory study of cardiovascular health and exposure to near-highway air pollution: study design and methods

The Exposure Peaks of Traffic-Related Ultrafine Particles Associated with Inflammatory Biomarkers and Blood Lipid Profiles

In this article, we explored the effects of ultrafine particle (UFP) peak exposure on inflammatory biomarkers and blood lipids using two novel metrics-the intensity of peaks and the frequency of peaks. We used data previously collected by the Community Assessment of Freeway Exposure and Health project from participants in the Greater Boston Area. The UFP exposure data were time-activity-adjusted hourly average concentration, estimated using land use regression models based on mobile-monitored ambient concentrations. The outcome data included C-reactive protein, interleukin-6 (IL-6), tumor necrosis factor-alpha receptor 2 (TNF-RII), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides and total cholesterol. For each health indicator, multivariate regression models were used to assess their associations with UFP peaks (N = 364-411). After adjusting for age, sex, body mass index, smoking status and education level, an increase in UFP peak exposure was significantly (p < 0.05) associated with an increase in TNF-RII and a decrease in HDL and triglycerides. Increases in UFP peaks were also significantly associated with increased IL-6 and decreased total cholesterol, while the same associations were not significant when annual average exposure was used. Our work suggests that analysis using peak exposure metrics could reveal more details about the effect of environmental exposures than the annual average metric.

Relationship between traffic-related air pollution and inflammation biomarkers using structural equation modeling

BACKGROUND

Evidence suggests that exposure to traffic-related air pollution (TRAP) and social stressors can increase inflammation. Given that there are many different markers of TRAP exposure, socio-economic status (SES), and inflammation, analytical approaches can leverage multiple markers to better elucidate associations. In this study, we applied structural equation modeling (SEM) to assess the association between a TRAP construct and a SES construct with an inflammation construct.

METHODS

This analysis was conducted as part of the Community Assessment of Freeway Exposure and Health (CAFEH; N = 408) study. Air pollution was characterized using a spatiotemporal model of particle number concentration (PNC) combined with individual participant time-activity adjustment (TAA). TAA-PNC and proximity to highways were considered for a construct of TRAP exposure. Participant demographics on education and income for an SES construct were assessed via questionnaires. Blood samples were analyzed for high sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), and tumor necrosis factor-α receptor II (TNFRII), which were considered for the construct for inflammation. We conducted SEM and compared our findings with those obtained using generalized linear models (GLM).

RESULTS

Using GLM, TAA-PNC was associated with multiple inflammation biomarkers. An IQR (10,000 particles/cm3) increase of TAA-PNC was associated with a 14 % increase in hsCRP in the GLM. Using SEM, the association between the TRAP construct and the inflammation construct was twice as large as the associations with any individual inflammation biomarker. SES had an inverse association with inflammation in all models. Using SEM to estimate the indirect effects of SES on inflammation through the TRAP construct strengthened confidence in the association of TRAP with inflammation.

CONCLUSION

Our TRAP construct resulted in stronger associations with a combined construct for inflammation than with individual biomarkers, reinforcing the value of statistical approaches that combine multiple, related exposures or outcomes. Our findings are consistent with inflammatory risk from TRAP exposure.

Air pollution exposure assessment at schools and playgrounds in Williamsburg Brooklyn NYC, with a view to developing a set of policy solutions

Community science offers unique opportunities for non-professional involvement of volunteers in the scientific process, not just during the data acquisition, but also in other phases, like problem definition, quality assurance, data analysis and interpretation, and the dissemination of results. Moreover, community science can be a powerful tool for public engagement and empowerment during policy formulation. This paper aims to present a pilot study on personal exposure to fine particulate matter (PM_2.5) and raises awareness of the hazards of air pollution. As part of data acquisition conducted in 2019, high school students gathered data at their schools, schoolyards, and playgrounds using low-cost monitors AirBeam2. The data was automatically uploaded every second onto the AirCasting mobile app. Besides, a stationary network of air monitors (fixed stations) was deployed in the neighborhood to collect real-time ambient air concentrations of PM_2.5. Students involved in the project attended workshops, training sessions, and researched to better understand air pollution, as part of their science class curriculum and portfolio. This air quality monitoring was incorporated into the "Our Air/Nuestro Aire" - El Puente grassroots campaign. The main goals of this campaign included sharing the data collected with the community, engaging academic partners to develop a set of policy and urban design solutions, and to be considered into a 5-point policy platform.

A new exposure metric for the cumulative effect of short-term exposure peaks of traffic-related ultrafine particles

INTRODUCTION

The adverse health outcomes of traffic-related ultrafine particles (UFPs) disproportionally impact near-highway neighborhoods. Current studies focus on either short-term health outcomes associated with short-term UFP exposures averaged over days or weeks, or long-term outcomes associated with long-term (yearly or longer) average UFP exposures. We hypothesized that frequent and repeated exposure to short-term UFP peaks that last for just hours could overwhelm or alter physiological defensive responses, resulting in long-term health issues. Herein, we propose a new exposure metric for measuring the cumulative effect of these peak exposures.

METHOD

We used UFP exposure data estimated by the Community Assessment of Freeway Exposure and Health (CAFEH) project, which recruited 704 participants from three pairs of near-highway/urban background neighborhoods in the Greater Boston Area between 2009 and 2012. CAFEH developed land use regression (LUR) models to estimate hourly averages of ambient UFP levels within the study areas based on mobile-monitored UFP data, and applied time-activity adjustment (TAA) to calculate adjusted final hourly estimates. Our alternative metric assigns cumulative peak exposure, which is determined as either the intensity (a high percentile of an individual's adjusted hourly UFP estimates) or the frequency (the number of hours with adjusted UFP estimates greater than a high percentile of all adjusted hourly UFP estimates of all participants in the study area) of UFP peaks.

RESULTS

After TAA was applied, for most of the time, our cumulative peak exposure metrics were not strongly correlated with the annual average. However, the level of correlation varied greatly from neighborhood to neighborhood (Spearman's R ranges from 0.39 to 0.97).

CONCLUSION

There was variation in UFP peak exposure that was not explained by the annual average, suggesting that our proposed peak metric distinct from annual average exposure metric.

Participatory research in Northwest Atlanta's Proctor Creek Watershed: Using photovoice to explore environmental health risks at the water's edge

In this study we used a participatory research method, photovoice, to explore community perceptions about environmental health risks, community assets, and strengths in and around an urban, degraded watershed in Northwest Atlanta, Georgia. This watershed, formed by Proctor Creek, is a focal point for redevelopment and infrastructure investments for years to come. Using a community-based participatory research approach, 10 Proctor Creek residents (watershed researchers), and a university partner, engaged in data collection; participatory data analysis; internal discussions; translation of research findings into watershed restoration, community revitalization, remedial action, and policy solutions; and dissemination of results to fellow watershed residents, stakeholders, and decision makers. We present a conceptual model linking the watershed researchers' understanding of urban policies and practice in the Proctor Creek Watershed to environmental, neighborhood and housing conditions and their influence on health outcomes and quality of life. Engaging community members in defining their own community environmental health challenges and assets yielded the following primary themes: 1) threats to the natural environment, 2) built environment stressors that influence health, 3) blight and divestment of public resources, and 4) hope for the future. Residents' vision for the future of the watershed - a restored creek, revitalized neighborhoods, and restored people - is fueled by a strong connection to history, memory, and sense of place. We demonstrate the value of local knowledge in identifying previously unaddressed environmental health risks in the Proctor Creek Watershed as well as solutions to reduce or eliminate them.

A Statistical Calibration Framework for Improving Non-Reference Method Particulate Matter Reporting: A Focus on Community Air Monitoring Settings

Recent advancement in lower-cost air monitoring technology has resulted in an increased interest in community-based air quality studies. However, non-reference monitoring (NRM; e.g., low-cost sensors) is imperfect and approaches that improve data quality are highly desired. Herein, we illustrate a framework for adjusting continuous NRM measures of particulate matter (PM) with field-based comparisons and non-linear statistical modeling as an example of instrument evaluation prior to exposure assessment. First, we collected continuous measurements of PM with a NRM technology collocated with a US EPA federal equivalent method (FEM). Next, we fit a generalized additive model (GAM) to establish a non-linear calibration curve that defines the relationship between the NRM and FEM data. Then, we used our fitted model to generate calibrated NRM PM data. Evaluation of raw NRM PM2.5 data revealed strong correlation with FEM (R = 0.9) but an average bias (AB) of −2.84 µg/m3 and a root mean square error (RMSE) of 2.85 µg/m3, with 406 h of data. Fitting of our GAM revealed that the correlation structure was maintained (r = 0.9) and that average bias (AB = 0) and error (RMSE = 0) were minimized. We conclude that field-based statistical calibration models can be used to reduce bias and improve NRM data used for community air monitoring studies.

Associations Between Sub-Clinical Markers of Cardiometabolic Risk and Exposure to Residential Indoor Air Pollutants in Healthy Adults in Perth, Western Australia: A Study Protocol

BACKGROUND

A growing body of epidemiological and clinical evidence has implicated air pollution as an emerging risk factor for cardiometabolic disease. Whilst individuals spend up to two-thirds of daily time in their domestic residential environment, very few studies have been designed to objectively measure the sub-clinical markers of cardiometabolic risk with exposure to domestic indoor air pollutants. This cross-sectional study aims to investigate associations between the components of domestic indoor air quality and selected sub-clinical cardiometabolic risk factors in a cohort of healthy adults living in Perth, Western Australia.

METHODS

One hundred and eleven non-smoking adults (65% female) living in non-smoking households who were aged between 35-69 years were recruited for the project. Study subjects were invited to participate in all sections of the study, which included: Domestic indoor air monitoring along with the concurrent 24 h ambulatory monitoring of peripheral and central blood pressure and measures of central hemodynamic indices, standardized questionnaires on aspects relating to current health status and the domestic environment, a 24 h time-activity diary during the monitoring period, and clinic-based health assessment involving collection of blood and urine biomarkers for lipid and glucose profiles, as well as measures of renal function and an analysis of central pulse wave and pulse wave velocity.

RESULTS

This study provides a standardized approach to the study of sub-clinical cardiometabolic health effects that are related to the exposure to indoor air pollution.

CONCLUSION

The findings of this study may provide direction for future research that will further contribute to our understanding of the relationship that exists between indoor air pollution and sub-clinical markers of cardiometabolic risk.

Metabolomic assessment of exposure to near-highway ultrafine particles

Exposure to traffic-related air pollutants has been associated with increased risk of adverse cardiopulmonary outcomes and mortality; however, the biochemical pathways linking exposure to disease are not known. To delineate biological response mechanisms associated with exposure to near-highway ultrafine particles (UFP), we used untargeted high-resolution metabolomics to profile plasma from 59 participants enrolled in the Community Assessment of Freeway Exposure and Health (CAFEH) study. Metabolic variations associated with UFP exposure were assessed using a cross-sectional study design based upon low (mean 16,000 particles/cm³) and high (mean 24,000 particles/cm³) annual average UFP exposures. In comparing quantified metabolites, we identified five metabolites that were differentially expressed between low and high exposures, including arginine, aspartic acid, glutamine, cystine and methionine sulfoxide. Analysis of the metabolome identified 316 m/z features associated with UFP, which were consistent with increased lipid peroxidation, endogenous inhibitors of nitric oxide and vehicle exhaust exposure biomarkers. Network correlation analysis and metabolic pathway enrichment identified 38 pathways and included variations related to inflammation, endothelial function and mitochondrial bioenergetics. Taken together, these results suggest UFP exposure is associated with a complex series of metabolic variations related to antioxidant pathways, in vivo generation of reactive oxygen species and processes critical to endothelial function.

Relationship of Time-Activity-Adjusted Particle Number Concentration with Blood Pressure

Emerging evidence suggests long-term exposure to ultrafine particulate matter (UFP, aerodynamic diameter < 0.1 µm) is associated with adverse cardiovascular outcomes. We investigated whether annual average UFP exposure was associated with measured systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), and hypertension prevalence among 409 adults participating in the cross-sectional Community Assessment of Freeway Exposure and Health (CAFEH) study. We used measurements of particle number concentration (PNC, a proxy for UFP) obtained from mobile monitoring campaigns in three near-highway and three urban background areas in and near Boston, Massachusetts to develop PNC regression models (20-m spatial and hourly temporal resolution). Individual modeled estimates were adjusted for time spent in different micro-environments (time-activity-adjusted PNC, TAA-PNC). Mean TAA-PNC was 22,000 particles/cm³ (sd = 6500). In linear models (logistic for hypertension) adjusted for the minimally sufficient set of covariates indicated by a directed acyclic graph (DAG), we found positive, non-significant associations between natural log-transformed TAA-PNC and SBP (β = 5.23, 95%CI: −0.68, 11.14 mmHg), PP (β = 4.27, 95%CI: −0.79, 9.32 mmHg), and hypertension (OR = 1.81, 95%CI: 0.94, 3.48), but not DBP (β = 0.96, 95%CI: −2.08, 4.00 mmHg). Associations were stronger among non-Hispanic white participants and among diabetics in analyses stratified by race/ethnicity and, separately, by health status.

Lessons from in-home air filtration intervention trials to reduce urban ultrafine particle number concentrations

BACKGROUND

Exposure to airborne ultrafine particle (UFP; <100 nm in aerodynamic diameter) is an emerging public health problem. Nevertheless, the benefit of using high efficiency particulate arrestance (HEPA) filtration to reduce UFP concentrations in homes is not yet clear.

METHODS

We conducted a randomized crossover study of HEPA filtration without a washout period in 23 homes of low-income Puerto Ricans in Boston and Chelsea, MA (USA). Most participants were female, older adults who were overweight or obese. Particle number concentrations (PNC, a proxy for UFP) were measured indoors and outdoors at each home continuously for six weeks. Homes received both HEPA filtration and sham filtration for three weeks each in random order.

RESULTS

Median PNC under HEPA filtration was 50-85% lower compared to sham filtration in most homes, but we found no benefit in terms of reduced inflammation; associations between hsCRP, IL-6, or TNFRII in blood samples and indoor PNC were inverse and not statistically significant.

CONCLUSIONS

Limitations to our study design likely contributed to our findings. Limitations included carry-over effects, a population that may have been relatively unresponsive to UFP, reduction in PNC even during sham filtration that limited differences between HEPA and sham filtration, window opening by participants, and lack of fine-grained (room-specific) participant time-activity information. Our approach was similar to other recent HEPA intervention studies of particulate matter exposure and cardiovascular risk, suggesting that there is a need for better study designs.

Lessons from in-home air filtration intervention trials to reduce urban ultrafine particle number concentrations

BACKGROUND

Exposure to airborne ultrafine particle (UFP; <100 nm in aerodynamic diameter) is an emerging public health problem. Nevertheless, the benefit of using high efficiency particulate arrestance (HEPA) filtration to reduce UFP concentrations in homes is not yet clear.

METHODS

We conducted a randomized crossover study of HEPA filtration without a washout period in 23 homes of low-income Puerto Ricans in Boston and Chelsea, MA (USA). Most participants were female, older adults who were overweight or obese. Particle number concentrations (PNC, a proxy for UFP) were measured indoors and outdoors at each home continuously for six weeks. Homes received both HEPA filtration and sham filtration for three weeks each in random order.

RESULTS

Median PNC under HEPA filtration was 50-85% lower compared to sham filtration in most homes, but we found no benefit in terms of reduced inflammation; associations between hsCRP, IL-6, or TNFRII in blood samples and indoor PNC were inverse and not statistically significant.

CONCLUSIONS

Limitations to our study design likely contributed to our findings. Limitations included carry-over effects, a population that may have been relatively unresponsive to UFP, reduction in PNC even during sham filtration that limited differences between HEPA and sham filtration, window opening by participants, and lack of fine-grained (room-specific) participant time-activity information. Our approach was similar to other recent HEPA intervention studies of particulate matter exposure and cardiovascular risk, suggesting that there is a need for better study designs.

Community-based participatory research for the study of air pollution: a review of motivations, approaches, and outcomes

Neighborhood level air pollution represents a long-standing issue for many communities that, until recently, has been difficult to address due to the cost of equipment and lack of related expertise. Changes in available technology and subsequent increases in community-based participatory research (CBPR) have drastically improved the ability to address this issue. However, much still needs to be learned as these types of studies are expected to increase in the future. To assist, we review the literature in an effort to improve understanding of the motivations, approaches, and outcomes of air monitoring studies that incorporate CBPR and citizen science (CS) principles. We found that the primary motivations for conducting community-based air monitoring were concerns for air pollution health risks, residing near potential pollution sources, urban sprawl, living in "unmonitored" areas, and a general quest for improved air quality knowledge. Studies were mainly conducted using community led partnerships. Fixed site monitoring was primarily used, while mobile, personal, school-based, and occupational sampling approaches were less frequent. Low-cost sensors can enable thorough neighborhood level characterization; however, keeping the community involved at every step, understanding the limitations and benefits of this type of monitoring, recognizing potential areas of debate, and addressing study challenges are vital for achieving harmony between expected and observed study outcomes. Future directions include assessing currently unregulated pollutants, establishing long-term neighborhood monitoring sites, performing saturation studies, evaluating interventions, and creating CS databases.

Association of Long-Term Near-Highway Exposure to Ultrafine Particles with Cardiovascular Diseases, Diabetes and Hypertension

Ultrafine particle (UFP) concentrations are elevated near busy roadways, however, their effects on prevalence of cardiovascular diseases, diabetes, and hypertension are not well understood. To investigate these associations, data on demographics, diseases, medication use, and time of activities were collected by in-home surveys for 704 participants in three pairs of near-highway and urban background neighborhoods in and near Boston (MA, USA). Body mass index (BMI) was measured for a subset of 435 participants. Particle number concentration (PNC, a measure of UFP) was collected by mobile monitoring in each area. Intra-neighborhood spatial-temporal regression models (approximately 20 m resolution) were used to estimate hourly ambient PNC at the residences of participants. We used participant time activity information to adjust annual average residential PNC values and assign individualized time activity adjusted annual average PNC exposures (TAA-PNC). Using multivariate logistic regression models, we found an odds ratio (OR) of 1.35 (95% CI: 0.83, 2.22) of TAA-PNC with stroke and ischemic heart diseases (S/IHD), an OR of 1.14 (95% CI: 0.81, 1.62) with hypertension, and an OR of 0.71 (95% CI: 0.46, 1.10) for diabetes. A subset analysis controlling for BMI produced slightly stronger associations for S/IHD (OR = 1.61, 95% CI: 0.88, 2.92) and hypertension (OR = 1.28, 95% CI: 0.81, 2.02), and no association with diabetes (OR = 1.09, 95% CI = 0.61, 1.96). Further research is needed with larger sample sizes and longitudinal follow-up.

Participatory Democracy, Community Organizing and the Community Assessment of Freeway Exposure and Health (CAFEH) Partnership

Background: Conflicting interests, power imbalance and relationships characterized by distrust are just a few of the many challenges community–academic research partnerships face. In addition, the time it takes to build relationships is often overlooked, which further complicates matters and can leave well-intentioned individuals re-creating oppressive conditions through inauthentic partnerships. This paper presents a novel approach of using meeting minutes to explore partnership dynamics. The Community Assessment of Freeway Exposure and Health (CAFEH) partnership is used as an illustrative case study to identify how community academic partnerships overcome the challenges associated with community-based participatory research (CBPR). CAFEH is a study of ultrafine particle exposure (UFP) near highways in the Boston, MA area. Methods: Qualitative analysis was applied to meeting minutes and process evaluation reports from the first three years of the CAFEH study (n = 73 files). In addition, a group meeting was held with project partners in order to contextualize the findings from the document analysis. Results: The three most commonly referenced challenges included language barriers, the overall project structure and budgetary constraints. Meanwhile, a heavy emphasis on process and an approach steeped in participatory democracy facilitated CAFEH’s ability to overcome these challenges, as well as sustain and augment strong partnership ties. Conclusions: This experience suggests that leadership that incorporates an organizing approach and a transformational style facilitates CBPR processes and helps teams surmount challenges.

Aviation Emissions Impact Ambient Ultrafine Particle Concentrations in the Greater Boston Area

Ultrafine particles are emitted at high rates by jet aircraft. To determine the possible impacts of aviation activities on ambient ultrafine particle number concentrations (PNCs), we analyzed PNCs measured from 3 months to 3.67 years at three sites within 7.3 km of Logan International Airport (Boston, MA). At sites 4.0 and 7.3 km from the airport, average PNCs were 2- and 1.33-fold higher, respectively, when winds were from the direction of the airport compared to other directions, indicating that aviation impacts on PNC extend many kilometers downwind of Logan airport. Furthermore, PNCs were positively correlated with flight activity after taking meteorology, time of day and week, and traffic volume into account. Also, when winds were from the direction of the airport, PNCs increased with increasing wind speed, suggesting that buoyant aircraft exhaust plumes were the likely source. Concentrations of other pollutants [CO, black carbon (BC), NO, NO2, NOx, SO2, and fine particulate matter (PM2.5)] decreased with increasing wind speed when winds were from the direction of the airport, indicating a different dominant source (likely roadway traffic emissions). Except for oxides of nitrogen, other pollutants were not correlated with flight activity. Our findings point to the need for PNC exposure assessment studies to take aircraft emissions into consideration, particularly in populated areas near airports.

Association of modeled long-term personal exposure to ultrafine particles with inflammatory and coagulation biomarkers

BACKGROUND

Long-term exposure to fine particulate matter has been linked to cardiovascular disease and systemic inflammatory responses; however, evidence is limited regarding the effects of long-term exposure to ultrafine particulate matter (UFP, <100nm). We used a cross-sectional study design to examine the association of long-term exposure to near-highway UFP with measures of systemic inflammation and coagulation.

METHODS

We analyzed blood samples from 408 individuals aged 40-91years living in three near-highway and three urban background areas in and near Boston, Massachusetts. We conducted mobile monitoring of particle number concentration (PNC) in each area, and used the data to develop and validate highly resolved spatiotemporal (hourly, 20m) PNC regression models. These models were linked with participant time-activity data to determine individual time-activity adjusted (TAA) annual average PNC exposures. Multivariable regression modeling and stratification were used to assess the association between TAA-PNC and single peripheral blood measures of high-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor-necrosis factor alpha receptor II (TNFRII) and fibrinogen.

RESULTS

After adjusting for age, sex, education, body mass index, smoking and race/ethnicity, an interquartile-range (10,000particles/cm(3)) increase in TAA-PNC had a positive non-significant association with a 14.0% (95% CI: -4.6%, 36.2%) positive difference in hsCRP, an 8.9% (95% CI: -0.4%, 10.9%) positive difference in IL-6, and a 5.1% (95% CI: -0.4%, 10.9%) positive difference in TNFRII. Stratification by race/ethnicity revealed that TAA-PNC had larger effect estimates for all three inflammatory markers and was significantly associated with hsCRP and TNFRII in white non-Hispanic, but not East Asian participants. Fibrinogen had a negative non-significant association with TAA-PNC.

CONCLUSIONS

Our findings suggest an association between annual average near-highway TAA-PNC and subclinical inflammatory markers of CVD risk.

Gender, Ethnicity and Environmental Risk Perception Revisited: The Importance of Residential Location

Studies in the U.S. have found that white men are less concerned about pollution than are women or people of other ethnicity. These studies have not assessed respondents' proximity to localized sources of pollution. Our objective was to assess lay perceptions of risk from air pollution in an ethnically diverse sample in which proximity to a major perceptible source of pollution is known. Cross sectional interview study of combined area probability and convenience sample of individuals 40 and older in the Boston area, selected according to proximity to high traffic controlled access highways. Of 697 respondents 46% were white, 37% Asian (mostly Chinese), 6.3% African-American, 6.3% Latino, and 7.6% other ethnicity. While white respondents, and particularly white men, were less concerned about air pollution than others, this effect disappeared when controlling for distance from the highway. White men were slightly less supportive than others of government policy to control pollution. The "white male" effect may in part be accounted for by the greater likelihood of minority respondents to live near perceptible localized sources of pollution.

Effect of time-activity adjustment on exposure assessment for traffic-related ultrafine particles

Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time.

A Randomized Cross-over Air Filtration Intervention Trial for Reducing Cardiovascular Health Risks in Residents of Public Housing near a Highway

Exposure to traffic-generated ultrafine particles (UFP; particles <100 nm) is likely a risk factor for cardiovascular disease. We conducted a trial of high-efficiency particulate arrestance (HEPA) filtration in public housing near a highway. Twenty residents in 19 apartments living <200 m from the highway participated in a randomized, double-blind crossover trial. A HEPA filter unit and a particle counter (measuring particle number concentration (PNC), a proxy for UFP) were installed in living rooms. Participants were exposed to filtered air for 21 days and unfiltered air for 21 days. Blood samples were collected and blood pressure measured at days 0, 21 and 42 after a 12-hour fasting period. Plasma was analyzed for high sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor necrosis factor alpha-receptor II (TNF-RII) and fibrinogen. PNC reductions ranging from 21% to 68% were recorded in 15 of the apartments. We observed no significant differences in blood pressure or three of the four biomarkers (hsCRP, fibrinogen, and TNF-RII) measured in participants after 21-day exposure to HEPA-filtered air compared to measurements after 21-day exposure to sham-filtered air. In contrast, IL-6 concentrations were significantly higher following HEPA filtration (0.668 pg/mL; CI = 0.465-0.959) compared to sham filtration. Likewise, PNC adjusted for time activity were associated with increasing IL-6 in 14- and 21-day moving averages, and PNC was associated with decreasing blood pressure in Lags 0, 1 and 2, and in a 3-day moving average. These negative associations were unexpected and could be due to a combination of factors including exposure misclassification, unsuccessful randomization (i.e., IL-6 and use of anti-inflammatory medicines), or uncontrolled confounding. Studies with greater reduction in UFP levels and larger sample sizes are needed. There also needs to be more complete assessment of resident time activity and of outdoor vs. indoor source contributions to UFP exposure. HEPA filtration remains a promising, but not fully realized intervention.

Developing Community-Level Policy and Practice to Reduce Traffic-Related Air Pollution Exposure

The literature consistently shows associations of adverse cardiovascular and pulmonary outcomes with residential proximity to highways and major roadways. Air monitoring shows that traffic-related pollutants (TRAP) are elevated within 200-400 m of these roads. Community-level tactics for reducing exposure include the following: 1) HEPA filtration; 2) Appropriate air-intake locations; 3) Sound proofing, insulation and other features; 4) Land-use buffers; 5) Vegetation or wall barriers; 6) Street-side trees, hedges and vegetation; 7) Decking over highways; 8) Urban design including placement of buildings; 9) Garden and park locations; and 10) Active travel locations, including bicycling and walking paths. A multidisciplinary design charrette was held to test the feasibility of incorporating these tactics into near-highway housing and school developments that were in the planning stages. The resulting designs successfully utilized many of the protective tactics and also led to engagement with the designers and developers of the sites. There is a need to increase awareness of TRAP in terms of building design and urban planning.

Transferability and generalizability of regression models of ultrafine particles in urban neighborhoods in the Boston area

Land use regression (LUR) models have been used to assess air pollutant exposure, but limited evidence exists on whether location-specific LUR models are applicable to other locations (transferability) or general models are applicable to smaller areas (generalizability). We tested transferability and generalizability of spatial-temporal LUR models of hourly particle number concentration (PNC) for Boston-area (MA, U.S.A.) urban neighborhoods near Interstate 93. Four neighborhood-specific regression models and one Boston-area model were developed from mobile monitoring measurements (34-46 days/neighborhood over one year each). Transferability was tested by applying each neighborhood-specific model to the other neighborhoods; generalizability was tested by applying the Boston-area model to each neighborhood. Both the transferability and generalizability of models were tested with and without neighborhood-specific calibration. Important PNC predictors (adjusted-R(2) = 0.24-0.43) included wind speed and direction, temperature, highway traffic volume, and distance from the highway edge. Direct model transferability was poor (R(2) < 0.17). Locally-calibrated transferred models (R(2) = 0.19-0.40) and the Boston-area model (adjusted-R(2) = 0.26, range: 0.13-0.30) performed similarly to neighborhood-specific models; however, some coefficients of locally calibrated transferred models were uninterpretable. Our results show that transferability of neighborhood-specific LUR models of hourly PNC was limited, but that a general model performed acceptably in multiple areas when calibrated with local data.

Biomarker as a research tool in linking exposure to air particles and respiratory health

Some of the environmental toxicants from air pollution include particulate matter (PM₁₀), fine particulate matter (PM_2.5), and ultrafine particles (UFP). Both short- and long-term exposure could result in various degrees of respiratory health outcomes among exposed persons, which rely on the individuals' health status. Methods. In this paper, we highlight a review of the studies that have used biomarkers to understand the association between air particles exposure and the development of respiratory problems resulting from the damage in the respiratory system. Data from previous epidemiological studies relevant to the application of biomarkers in respiratory system damage reported from exposure to air particles are also summarized. Results. Based on these analyses, the findings agree with the hypothesis that biomarkers are relevant in linking harmful air particles concentrations to increased respiratory health effects. Biomarkers are used in epidemiological studies to provide an understanding of the mechanisms that follow airborne particles exposure in the airway. However, application of biomarkers in epidemiological studies of health effects caused by air particles in both environmental and occupational health is inchoate. Conclusion. Biomarkers unravel the complexity of the connection between exposure to air particles and respiratory health.

Association of PNC, BC, and PM2.5 measured at a central monitoring site with blood pressure in a predominantly near highway population

Elevated blood pressure is an indicator of cardiovascular stress and increased risk of cardiovascular-related morbidity and mortality. There is emerging evidence suggesting air pollutants, including particulate matter (PM), could promote hypertension, thereby increasing cardiovascular disease risk. Repeated measurement analyses were conducted to examine the associations of three types of PM with systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) in 220 participants, (mean age = 58.5 years) from the Community Assessment of Freeway Exposure and Health study (CAFEH), most of whom live near a major highway. Ambient levels of air pollutants including particle number concentration (PNC; a measure of ultrafine particle (UFP) concentration), fine PM (PM_2.5, Particle diameter <2.5 µm), and black carbon (BC) were measured at a central site <7 km from the study areas. Central sites are good at capturing short-term temporal trends in pollution associated with meteorological changes over regional areas. Linear mixed-effect models that accounted for repeated measures within one person were used to examine the associations between blood pressure variables and daily average of ambient PNC, PM_2.5, or BC, controlling for demographic characteristics and major confounders including temperature. Our PNC model predicted that a higher PNC of 10,000 particles/cm³ was associated with higher DBP of 2.40 mmHg (p = 0.03), independent of other factors in the model. There were no significant associations for PM_2.5 or BC. Post hoc subgroup analyses by obesity status showed that positive associations of DBP with PNC were more pronounced among obese individuals than non-obese individuals. These results suggested that PNC levels are associated with increased blood pressure, which may contribute to cardiovascular disease risk. More research is needed to assess the relationship between PNC and blood pressure and to address possible residual confounding.

Response of biomarkers of inflammation and coagulation to short-term changes in central site, local, and predicted particle number concentrations

PURPOSE

Previous studies have reported acute (hours-28 days) associations between ambient ultrafine particles (UFP; diameter <0.1) and biomarkers of cardiovascular health using central site data. We evaluated particle number concentration (a proxy measure for UFP) measured at a central site, a local near-highway site and predicted residential concentrations with response of biomarkers of inflammation and coagulation in a near-highway population.

METHODS

Participants provided two blood samples for analysis of interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-α receptor II, and fibrinogen. Mixed effect models were used to evaluate the association between PNC levels on the same day, prior 2 days, and moving averages of 3 to 28 days.

RESULTS

Estimated effects on biomarkers of a 5000 unit increase in central site PNC generally increased with longer averaging times for IL-6, hs-CRP, and fibrinogen. Effect estimates were highest for a 28-day moving average, with 91% (95% confidence interval [CI]: 9, 230) higher IL-6 levels, 74% (95% CI: -7, 220) higher hs-CRP levels, and 59% (95% CI: -13, 130) higher fibrinogen levels. We observed no clear trend between near-highway or predicted residential PNC and any of the biomarkers.

CONCLUSIONS

Only central site PNC increased blood markers of inflammation while near-highway and predicted residential values did not. We cannot fully explain this result, although differing PNC composition is a possibility. Future studies would assist in understanding these findings.

"We make the path by walking it": building an academic community partnership with Boston Chinatown

BACKGROUND

The potential for academic community partnerships are challenged in places where there is a history of conflict and mistrust. Addressing Disparities in Asian Populations through Translational Research (ADAPT) represents an academic community partnership between researchers and clinicians from Tufts Medical Center and Tufts University and community partners from Boston Chinatown. Based in principles of community-based participatory research and partnership research, this partnership is seeking to build a trusting relationship between Tufts and Boston Chinatown.

OBJECTIVES

This case study aims to provides a narrative story of the development and formation of ADAPT as well as discuss challenges to its future viability.

METHODS

Using case study research tools, this study draws upon a variety of data sources including interviews, program evaluation data and documents.

RESULTS

Several contextual factors laid the foundation for ADAPT. Weaving these factors together helped to create synergy and led to ADAPT's formation. In its first year, ADAPT has conducted formative research, piloted an educational program for community partners and held stakeholder forums to build a broad base of support.

CONCLUSIONS

ADAPT recognizes that long term sustainability requires bringing multiple stakeholders to the table even before a funding opportunity is released and attempting to build a diversified funding base.

Spatial and temporal differences in traffic-related air pollution in three urban neighborhoods near an interstate highway

Relatively few studies have characterized differences in intra- and inter-neighborhood traffic-related air pollutant (TRAP) concentrations and distance-decay gradients in along an urban highway for the purposes of exposure assessment. The goal of this work was to determine the extent to which intra- and inter-neighborhood differences in TRAP concentrations can be explained by traffic and meteorology in three pairs of neighborhoods along Interstate 93 (I-93) in the metropolitan Boston area (USA). We measured distance-decay gradients of seven TRAPs (PNC, pPAH, NO, NO_X, BC, CO, PM_2.5) in near-highway (<400 m) and background areas (>1 km) in Somerville, Dorchester/South Boston, Chinatown and Malden to determine whether (1) spatial patterns in concentrations and inter-pollutant correlations differ between neighborhoods, and (2) variation within and between neighborhoods can be explained by traffic and meteorology. The neighborhoods ranged in area from 0.5 to 2.3 km². Mobile monitoring was performed over the course of one year in each pair of neighborhoods (one pair of neighborhoods per year in three successive years; 35-47 days of monitoring in each neighborhood). Pollutant levels generally increased with highway proximity, consistent with I-93 being a major source of TRAP; however, the slope and extent of the distance-decay gradients varied by neighborhood as well as by pollutant, season and time of day. Correlations among pollutants differed between neighborhoods (e.g., ρ = 0.35-0.80 between PNC and NO_X and ρ = 0.11-0.60 between PNC and BC) and were generally lower in Dorchester/South Boston than in the other neighborhoods. We found that the generalizability of near-road gradients and near-highway/urban background contrasts was limited for near-highway neighborhoods in a metropolitan area with substantial local street traffic. Our findings illustrate the importance of measuring gradients of multiple pollutants under different ambient conditions in individual near-highway neighborhoods for health studies involving inter-neighborhood comparisons.

Evidence for the healthy immigrant effect in older Chinese immigrants: a cross-sectional study

BACKGROUND

Previous work has found that first-generation immigrants to developed nations tend to have better health than individuals born in the host country. We examined the evidence for the healthy immigrant effect and convergence of health status between Chinese immigrants (n = 147) and U.S. born whites (n = 167) participating in the cross-sectional Community Assessment of Freeway Exposure and Health study and residing in the same neighborhoods.

METHODS

We used bivariate and multivariate models to compare disease prevalence and clinical biomarkers.

RESULTS

Despite an older average age and lower socioeconomic status, Chinese immigrants were less likely to have asthma (OR = 0.20, 95% CI = 0.09-0.48) or cardiovascular disease (OR = 0.44, 95% CI = 0.20-0.94), had lower body mass index (BMI), lower inflammation biomarker levels, lower average sex-adjusted low-density lipoprotein (LDL) cholesterol, and higher average sex-adjusted high-density lipoprotein (HDL) cholesterol. However, there was no significant difference in the prevalence of diabetes or hypertension. Duration of time in the U.S. was related to cardiovascular disease and asthma but was not associated with diabetes, hypertension, BMI, HDL cholesterol, LDL cholesterol, socioeconomic status, or health behaviors.

CONCLUSIONS

The lower CVD and asthma prevalence among the Chinese immigrants may be partially attributed to healthier diets, more physical activity, lower BMI, and less exposure to cigarette smoke. First generation immigrant status may be protective even after about two decades.

An hourly regression model for ultrafine particles in a near-highway urban area

Estimating ultrafine particle number concentrations (PNC) near highways for exposure assessment in chronic health studies requires models capable of capturing PNC spatial and temporal variations over the course of a full year. The objectives of this work were to describe the relationship between near-highway PNC and potential predictors, and to build and validate hourly log-linear regression models. PNC was measured near Interstate 93 (I-93) in Somerville, MA using a mobile monitoring platform driven for 234 h on 43 days between August 2009 and September 2010. Compared to urban background, PNC levels were consistently elevated within 100-200 m of I-93, with gradients impacted by meteorological and traffic conditions. Temporal and spatial variables including wind speed and direction, temperature, highway traffic, and distance to I-93 and major roads contributed significantly to the full regression model. Cross-validated model R(2) values ranged from 0.38 to 0.47, with higher values achieved (0.43 to 0.53) when short-duration PNC spikes were removed. The model predicts highest PNC near major roads and on cold days with low wind speeds. The model allows estimation of hourly ambient PNC at 20-m resolution in a near-highway neighborhood.

Highway proximity associated with cardiovascular disease risk: the influence of individual-level confounders and exposure misclassification

BACKGROUND

Elevated cardiovascular disease risk has been reported with proximity to highways or busy roadways, but proximity measures can be challenging to interpret given potential confounders and exposure error.

METHODS

We conducted a cross sectional analysis of plasma levels of C-Reactive Protein (hsCRP), Interleukin-6 (IL-6), Tumor Necrosis Factor alpha receptor II (TNF-RII) and fibrinogen with distance of residence to a highway in and around Boston, Massachusetts. Distance was assigned using ortho-photo corrected parcel matching, as well as less precise approaches such as simple parcel matching and geocoding addresses to street networks. We used a combined random and convenience sample of 260 adults >40 years old. We screened a large number of individual-level variables including some infrequently collected for assessment of highway proximity, and included a subset in our final regression models. We monitored ultrafine particle (UFP) levels in the study areas to help interpret proximity measures.

RESULTS

Using the orthophoto corrected geocoding, in a fully adjusted model, hsCRP and IL-6 differed by distance category relative to urban background: 43% (-16%,141%) and 49% (6%,110%) increase for 0-50 m; 7% (-39%,45%) and 41% (6%,86%) for 50-150 m; 54% (-2%,142%) and 18% (-11%,57%) for 150-250 m, and 49% (-4%, 131%) and 42% (6%, 89%) for 250-450 m. There was little evidence for association for TNF-RII or fibrinogen. Ortho-photo corrected geocoding resulted in stronger associations than traditional methods which introduced differential misclassification. Restricted analysis found the effect of proximity on biomarkers was mostly downwind from the highway or upwind where there was considerable local street traffic, consistent with patterns of monitored UFP levels.

CONCLUSION

We found associations between highway proximity and both hsCRP and IL-6, with non-monotonic patterns explained partly by individual-level factors and differences between proximity and UFP concentrations. Our analyses emphasize the importance of controlling for the risk of differential exposure misclassification from geocoding error.

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis

BACKGROUND

The growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.

METHODS

We compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a "gold standard" residential geocoding process that used ortho-photos, large multi-building parcel layouts or large multi-unit building floor plans. The potential effect of positional error for each geocoding method was assessed as part of a proximity to highway epidemiological study in the Boston area, using all participants with complete address information (N = 703). Hourly time-activity data for the most recent workday/weekday and non-workday/weekend were collected to examine time spent in five different micro-environments (inside of home, outside of home, school/work, travel on highway, and other). Analysis included examination of whether time-activity patterns were differentially distributed either by proximity to highway or across demographic groups.

RESULTS

Median positional error was significantly higher in street network geocoding (StreetMap USA = 23 m; TIGER = 22 m) than parcel geocoding (8 m). When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels = 24 m; StreetMap USA = 28 m; TIGER = 37 m). Street network geocoding also differentially introduced greater amounts of positional error in the proximity to highway study in the 0-50 m proximity category. Time spent inside home on workdays/weekdays differed significantly by demographic variables (age, employment status, educational attainment, income and race). Time-activity patterns were also significantly different when stratified by proximity to highway, with those participants residing in the 0-50 m proximity category reporting significantly more time in the school/work micro-environment on workdays/weekdays than all other distance groups.

CONCLUSIONS

These findings indicate the potential for both differential and non-differential exposure misclassification due to geocoding error and time-activity patterns in studies of highway proximity. We also propose a multi-stage manual correction process to minimize positional error. Additional research is needed in other populations and geographic settings.