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Maintained green space in underserved urban neighborhoods may be an important environmental pathway to improving community health and safety, though effects may vary across population subgroups and by time of day. We examined survey responses from 442 participants (178 men and 264 women), living near vacant lots in a cluster-randomized controlled trial of a cleaning and greening intervention, on perceived safety during the day and at night. At the intervention sites after the intervention, only men reported feeling less unsafe during the day. Women reported more fear, and men reported less fear, after the intervention, although these results and tests for effect modification were not statistically significant. The clean-and-green intervention may have allayed fears for men during the day and supported their ease of movement throughout their neighborhoods. However, at night, it may have had the opposite effect on women. Though our study was under-powered, not designed to test associations stratified by gender, directions and magnitudes of associations differed substantially, indicating a need for further investigations into potential gender differences in the benefits of green space, to inform and better tailor interventions to improve perceived safety for all. [ABSTRACT FROM AUTHOR]

The article focuses on two new studies one from the United States and the other from Australia point to the potential for increased rates of preterm birth (PTB) with rising temperatures and examine the potential for rising temperatures to exacerbate prevailing PTB disparities. Topics include examines that environmental exposures are inequitably distributed across race/ethnicity and socioeconomic status.

The article discusses a study on the significant role of stress processes in mediating impacts of ozone exposures on metabolic function, which references a research paper published within the issue. It tackles the variations in interactions between pollution and stress, the ozone-induced changes in glucose production, and the implications of the lack of response to ozone shown in adrenalectomized rats for understanding biological processes.

Although intra-urban air pollution differs by season, few monitoring networks provide adequate geographic density and year-round coverage to fully characterize seasonal patterns. Here, we report winter intra-urban monitoring and land-use regression (LUR) results from the New York City Community Air Survey (NYCCAS). Two-week integrated samples of fine particles (PM2.5), black carbon (BC), nitrogen oxides (NOx) and sulfur dioxide (S02) were collected at 155 city-wide street-level locations during winter 2008-2009. Sites were selected using stratified random sampling, randomized across sampling sessions to minimize spatio-temporal confounding. LUR was used to identify GIS-based source indicators associated with higher concentrations. Prediction surfaces were produced using kriging with external drift. Each pollutant varied twofold or more across sites, with higher concentrations near midtown Manhattan. All pollutants were positively correlated, particularly PM2.5 and BC (Spearman's r= 0.84). Density of oil-burning boilers, total and truck traffic density, and temporality explained 84% of PM2.5 variation. Densities of total traffic, truck traffic, oil-burning boilers and industrial space, with temporality, explained 65% of BC variation. Temporality, built space, bus route location, and traffic density described 67% of nitrogen dioxide variation. Residual oil-burning units, nighttime population and temporality explained 77% of S02 variation. Spatial variation in combustion-related pollutants in New York City was strongly associated with oil-burning and traffic density. Chronic exposure disparities and unique local sources can be identified through year-round saturation monitoring. [ABSTRACT FROM AUTHOR]

Background: Epidemiologic evidence suggests that chronic stress may alter susceptibility to air pollution. However, persistent spatial confounding between these exposures may limit the utility of epidemiologic methods to disentangle these effects and cannot identify physiologic mechanisms for potential differential susceptibilities. Objectives: Using a rat model of social stress, we compared respiratory responses to fine concentrated ambient particles (CAPs) and examined biological markers of inflammation. Methods: Twenty-four 12-week-old male Sprague-Dawley rats were randomly assigned to four groups [stress/CAPs, stress/filtered air (FA), nonstress/ CAPs, nonstress/ FA]. Stress-group animals were individually introduced into the home cage of a dominant male twice weekly. Blood drawn at sacrifice was analyzed for immune and inflammatory markers. CAPs were generated using the Harvard ambient particle concentrator, which draws real-time urban ambient fine particles, enriching concentrations approximately 30 times. CAPs/FA exposures were delivered in single-animal plethysmographs, 5 hr/day for 10 days, and respiratory function was continuously monitored using a Buxco system. Results: Stressed animals displayed higher average C-reactive protein, tumor necrosis factor-α, and white blood cell counts than did nonstressed animals. Only among stressed animals were CAPs exposures associated with increased respiratory frequency, lower flows, and lower volumes, suggesting a rapid, shallow breathing pattern. Conversely, in animals with elevated CAPs exposures alone, we observed increased inspiratory flows and greater minute volumes (volume of air inhaled or exhaled per minute). Conclusions: CAPs effects on respiratory measures differed significantly, and substantively, by stress group. Higher CAPs exposures were associated with a rapid, shallow breathing pattern only under chronic stress. Blood measures provided evidence of inflammatory responses. Results support epidemiologic findings that chronic stress may alter respiratory response to air pollution and may help elucidate pathways for differential susceptibility. [ABSTRACT FROM AUTHOR]

Adults with better jobs enjoy better health: job title was, in fact, the social gradient metric first used to study the relationship between social class and chronic disease etiology, a core finding now replicated in most developed countries. What has been less well proved is whether this correlation is causal, and if so, through what mechanisms. During the past decade, much research has been directed at these issues. Best evidence in 2009 suggests that occupation does affect health. Most recent research on the relationship has been directed at disentangling the pathways through which lower-status work leads to adverse health outcomes. This review focuses on six areas of recent progress: (1) the role of status in a hierarchical occupational system; (2) the roles of psychosocial job stressors; (3) effects of workplace physical and chemical hazard exposures; (4) evidence that work organization matters as a contextual factor; (5) implications for the gradient of new forms of nonstandard or “precarious” employment such as contract and shift work; and (6) emerging evidence that women may be impacted differently by adverse working conditions, and possibly more strongly, than men. [ABSTRACT FROM AUTHOR]

Objective: Epidemiologic studies of air pollution effects on respiratory health report significant modification by sex, although results are not uniform. Importantly, it remains unclear whether modifications are attributable to socially derived gendered exposures, to sex-linked physiological differences, or to some interplay thereof. Gender analysis, which aims to disaggregate social from biological differences between males and females, may help to elucidate these possible sources of effect modification. Data sources and data extraction: A PubMed literature search was performed in July 2009, using the terms "respiratory" and any of "sex" or "gender" or "men and women" or "boys and girls" and either "PM2.5" (particulate matter ≤ 2.5 μm in aerodynamic diameter) or "NO2" (nitrogen dioxide). I reviewed the identified studies, and others cited therein, to summarize current evidence of effect modification, with attention to authors' interpretation of observed differences. Owing to broad differences in exposure mixes, outcomes, and analytic techniques, with few studies examining any given combination thereof, meta-analysis was not deemed appropriate at this time. Data synthesis: More studies of adults report stronger effects among women, particularly for older persons or where using residential exposure assessment. Studies of children suggest stronger effects among boys in early life and among girls in later childhood. Conclusions: The qualitative review describes possible sources of difference in air pollution response between women and men, which may vary by life stage, coexposures, hormonal status, or other factors. The sources of observed effect modifications remain unclear, although gender analytic approaches may help to disentangle gender and sex differences in pollution response. A framework for incorporating gender analysis into environmental epidemiology is offered, along with several potentially useful methods from gender analysis. [ABSTRACT FROM AUTHOR]

Abstract: Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO2) and PM2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies. [Copyright &y& Elsevier]

Objective: There is growing interest in disentangling the health effects of spatially clustered social and physical environmental exposures and in exploring potential synergies among them, with particular attention directed to the combined effects of psychosocial stress and air pollution. Both exposures may be elevated in lower-income urban communities, and it has been hypothesized that stress, which can influence immune function and susceptibility, may potentiate the effects of air pollution in respiratory disease onset and exacerbation. In this paper, we attempt to synthesize the relevant research from social and environmental epidemiology, toxicology, immunology, and exposure assessment to provide a useful framework for environmental health researchers aiming to investigate the health effects of environmental pollution in combination with social or psychological factors. Data synthesis: We review the existing epidemiologic and toxicologic evidence on synergistic effects of stress and pollution, and then describe the physiologic effects of stress and key issues related to measuring and evaluating stress as it relates to physical environmental exposures and susceptibility. Finally, we identify some of the major methodologic challenges ahead as we work toward disentangling the health effects of clustered social and physical exposures and accurately describing the interplay among these exposures. Conclusions: There is still tremendous work to be done toward understanding the combined and potentially synergistic health effects of stress and pollution. As this research proceeds, we recommend careful attention to the relative temporalities of stress and pollution exposures, to nonlinearities in their independent and combined effects, to physiologic pathways not elucidated by epidemiologic methods, and to the relative spatial distributions of social and physical exposures at multiple geographic scales. [ABSTRACT FROM AUTHOR]

Background: There is a growing body of literature linking GIS-based measures of traffic density to asthma and other respiratory outcomes. However, no consensus exists on which traffic indicators best capture variability in different pollutants or within different settings. As part of a study on childhood asthma etiology, we examined variability in outdoor concentrations of multiple traffic-related air pollutants within urban communities, using a range of GIS-based predictors and land use regression techniques. Methods: We measured fine particulate matter (PM2.5), nitrogen dioxide (NO2), and elemental carbon (EC) outside 44 homes representing a range of traffic densities and neighborhoods across Boston, Massachusetts and nearby communities. Multiple three to four-day average samples were collected at each home during winters and summers from 2003 to 2005. Traffic indicators were derived using Massachusetts Highway Department data and direct traffic counts. Multivariate regression analyses were performed separately for each pollutant, using traffic indicators, land use, meteorology, site characteristics, and central site concentrations. Results: PM2.5 was strongly associated with the central site monitor (R2 = 0.68). Additional variability was explained by total roadway length within 100 m of the home, smoking or grilling near the monitor, and block-group population density (R² = 0.76). EC showed greater spatial variability, especially during winter months, and was predicted by roadway length within 200 m of the home. The influence of traffic was greater under low wind speed conditions, and concentrations were lower during summer (R² = 0.52). NO2 showed significant spatial variability, predicted by population density and roadway length within 50 m of the home, modified by site characteristics (obstruction), and with higher concentrations during summer (R² = 0.56). Conclusion: Each pollutant examined displayed somewhat different spatial patterns within urban neighborhoods, and were differently related to local traffic and meteorology. Our results indicate a need for multi-pollutant exposure modeling to disentangle causal agents in epidemiological studies, and further investigation of site-specific and meteorological modification of the traffic-concentration relationship in urban neighborhoods. [ABSTRACT FROM AUTHOR]

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households. As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3–4 day samples of nitrogen dioxide (NO2) and fine particulate matter (PM2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor. The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO2 with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50m buffer of a home and distance from a truck route as important contributors to indoor levels of NO2 and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population. [Copyright &y& Elsevier]

Air pollution exposure patterns may contribute to known spatial patterning of asthma morbidity within urban areas. While studies have evaluated the relationship between traffic and outdoor concentrations, few have considered indoor exposure patterns within low socioeconomic status (SES) urban communities. In this study, part of a prospective birth cohort study assessing asthma etiology in urban Boston, we collected indoor and outdoor 3–4 day samples of nitrogen dioxide (NO2) and fine particulate matter (PM2.5) in 43 residences across multiple seasons from 2003 to 2005. Homes were chosen to represent low SES households, including both cohort and non-cohort residences in similar neighborhoods, and consisted almost entirely of multiunit residences. Reflectance analysis and X-ray fluorescence spectroscopy were performed on the particle filters to determine elemental carbon (EC) and trace element concentrations, respectively. Additionally, information on home characteristics (e.g. type, age, stove fuel) and occupant behaviors (e.g. smoking, cooking, cleaning) were collected via a standardized questionnaire. The contributions of outdoor and indoor sources to indoor concentrations were quantified with regression analyses using mass balance principles. For NO2 and most particle constituents (except outdoor-dominated constituents like sulfur and vanadium), the addition of selected indoor source terms improved the model's predictive power. Cooking time, gas stove usage, occupant density, and humidifiers were identified as important contributors to indoor levels of various pollutants. A comparison between cohort and non-cohort participants provided another means to determine the influence of occupant activity patterns on indoor–outdoor ratios. Although the groups had similar housing characteristics and were located in similar neighborhoods, cohort members had significantly higher indoor concentrations of PM2.5 and NO2, associated with indoor activities. We conclude that the effect of indoor sources may be more pronounced in high-density multiunit dwellings, and that future epidemiological studies in these populations should explicitly consider these sources in assigning exposures.Journal of Exposure Science and Environmental Epidemiology (2007) 17, 433–444; doi:10.1038/sj.jes.7500532; published online 18 October 2006 [ABSTRACT FROM AUTHOR]

BACKGROUND: Disproportionate life stress and consequent physiologie alteration (i.e., immune dysregulation) has been proposed as a major pathway linking socioeconomic position, environmental exposures, and health disparities. Asthma, for example, disproportionately affects lower-income urban communities, where air pollution and social stressors may be elevated. OBJECTIVES: We aimed to examine the role of exposure to violenee (ETV), as a chronic stressor, in altering susceptibility to traffic-related air pollution in asthma etiology. METHODS: We developed geographic information systems (GIS)-based models to retrospectively estimate residential exposures to traffic-related pollution for 413 children in a community-based pregnancy cohort, recruited in East Boston, Massachusetts, between 1987 and 1993, using monthly nitrogen dioxide measurements for 13 sites over 18 years. We merged pollution estimates with questionnaire data on lifetime ETV and examined the effects of both on childhood asthma etiology. RESULTS: Correcting for potential confounders, we found an elevated risk of asthma with a 1-SD (4.3 ppb) increase in NO2 exposure solely among children with ahove-median ETV [odds ratio (OR) = 1.63; 95% confidence interval (CI), 1.14-2.33)]. Among children always living in the same community, with lesser exposure measurement error, this association was magnified (OR = 2.40; 95% CI, 1.48-3.88). Of multiple exposure periods, year-of-diagnosis NO2 was most predictive of asthma outcomes. CONCLUSIONS: We found an association between traffic-related air pollution and asthma solely among urban children exposed to violence. Future studies should consider socially patterned susceptibility, common spatial distributions of social and physical environmental factors, and potential synergies among these. Prospective assessment of physical and social exposures may help determine causal pathways and critical exposure periods. [ABSTRACT FROM AUTHOR]

Research has shown that the COVID-19 pandemic affected individual's mental and physical health. The aim of this study was to estimate associations between greenspace use and proximity with perceived mental and physical health during the COVID-19 pandemic. We surveyed metropolitan Philadelphia residents, October 20–December 1, 2020, about walking time to the nearest greenspace from their home, frequency of greenspace use in the past 30 days, change in frequency of greenspace use during the COVID-19 pandemic, and perceived physical and mental health outcomes. We ran unadjusted and adjusted log-binomial regression models to derive Risk Ratio (RR) and 95% Confidence Intervals (CI) estimates of associations of loneliness, physical and mental health outcomes with: (1) self-reported walking time to nearest greenspace; (2) reported greenspace use frequency; and (3) changes in greenspace use frequency. Of 485 survey participants, 244 (51.4%) reported feeling lonelier, 147 (31.37%) reported higher perceived stress, 261 (54.9%) reported worsened mental health, and 137 (28.7%) reported worsened physical health during vs. before the start of pandemic-restrictions in mid-March of 2020. After adjustment for gender, age, and change in financial status, RR estimates suggested modest protective associations between visiting greenspaces more frequently during vs. before the pandemic and worsened mental (RR: 0.84, 95% CI: 0.70–1.00), and physical health (RR 0.77, 95% CI: 0.56–1.10), and loneliness (RR: 0.91, 95% CI: 0.75–1.1) and perceived stress (RR 0.83, 95% CI: 0.61–1.13). Shorter walking distances to the nearest greenspace were associated with reduced risk of reporting worsened physical health and higher perceived stress; however, living shorter walking distances from greenspace were not associated with protection against worsened mental health or loneliness. These results suggest that active greenspace use may provide mental and physical health protection, particularly during a stressful public health crisis. [ABSTRACT FROM AUTHOR]

In order to develop effective strategies to address noise annoyance, it is essential to develop an explanatory model of the psychological mechanism(s) by which noise becomes annoying. Two online studies were conducted in which a total of 193 participants completed speech perception tasks with varying degrees of background noise. Signal-to-noise ratio levels ranged from −2 to −10 dB. The crucial manipulation in both experiments concerned participants' sense of control over the noise level in the task. Dependent measures were task performance, a self-reported measure of frustration with the task, and self-reported sensitivity (trait) to noise. Results showed small but significant effects of noise sensitivity and sense of control on subjective frustration. In both experiments, more noise-sensitive individuals expressed greater frustration than did those reporting less noise sensitivity. In addition, in experiment 2 there was a significant interaction between sense of control and noise level. Listeners under the higher noise-level conditions expressed relatively similar degrees of frustration irrespective of their sense of control, while those under the lower noise-level condition showed lower frustration with greater sense of control. Results support Stallen's [(1999). Noise Health 1(3), 69–79] theoretical framework of noise annoyance, but also suggest the need for further research under more ecologically plausible conditions. [ABSTRACT FROM AUTHOR]

Preterm birth (PTB) remains a key public health issue that disproportionately affects Black individuals. Since spontaneous PTB (sPTB) and medically indicated PTB (mPTB) may have different causes and interventions, we quantified racial disparities for sPTB and mPTB, and we characterized the geographic patterning of these phenotypes, overall and according to race/ethnicity. We examined a pregnancy cohort of 83,952 singleton births at 2 Philadelphia hospitals from 2008–2020, and classified each PTB as sPTB or mPTB. We used binomial regression to quantify the magnitude of racial disparities between non-Hispanic Black and non-Hispanic White individuals, then generated small area estimates by applying a Bayesian model that accounts for small numbers and smooths estimates of PTB risk by borrowing information from neighboring areas. Racial disparities in both sPTB and mPTB were significant (relative risk of sPTB = 1.83, 95% confidence interval: 1.70, 1.98; relative risk of mPTB = 2.20, 95% confidence interval: 2.00, 2.42). The disparity was 20% greater in mPTB than sPTB. There was substantial geographic variation in PTB, sPTB, and mPTB risks and racial disparity. Our findings underscore the importance of distinguishing PTB phenotypes within the context of public health and preventive medicine. Future work should consider social and environmental exposures that may explain geographic differences in PTB risk and disparities. [ABSTRACT FROM AUTHOR]

Despite mounting evidence that urban greenspace protects against mortality in adults, few studies have explored the relationship between greenspace and death among infants. Here, we describe results from an analysis of associations between greenness and infant mortality in Philadelphia, PA. We used images of the normalized difference vegetation index (NDVI), derived from processed satellite data, to estimate greenness density in each census tract. We linked these data with census tract level counts of total infant mortality cases (n = 963) and births (n = 113,610) in years 2010-2014, and used Bayesian spatial areal unit, conditional autoregressive models to estimate associations between greenness and infant mortality. The models included a set of random effects to account for spatial autocorrelation between neighboring census tracts. Infant mortality counts were modeled using a Poisson distribution, and the logarithm of total births in each census tract was specified as the offset term. The following variables were included as potential confounders and effect modifiers: percentage non-Hispanic black, percentage living below the poverty line, an indicator of housing quality, and population density. In adjusted models, the rate of infant mortality was 27% higher in less green compared to more green tracts (95% CI 1.02-1.59). These results contribute further evidence that greenspace may be a health promoting environmental asset. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented regarding an article published in a previous issue concerning the effects on asthma by traffic-related air pollution and stress, in 2008.

While past research suggests that urban greenspace is associated with weaker income-based mortality inequities, little is known about associations with racial inequities, which may be distinct owing to historical and contemporary forms of racism. We quantified the extent to which different measures of greenspace modified socioeconomic and racial/ethnic inequities in all-cause and cardiovascular disease mortality. For every residential census tract in Philadelphia, PA (N = 376), we linked counts of all-cause and cardiovascular mortality (years 2008–2015) with measures of greenspace (proportion tree canopy or grass/shrub cover, proportion residents reporting park access, and the normalized difference vegetation index measure of overall greenness) and American Community Survey-based measures of sociodemographic composition (proportion of residents living in poverty, proportion identifying as non-Hispanic Black, and the index of concentration at the extremes (ICE) representing racialized economic deprivation). We used age- and sex-adjusted negative binomial models, with the natural logarithm of age-specific population counts as an offset, to quantify the magnitude of inequities by each composition variable, overall and stratified by categories of each greenspace measure. Inequities in mortality were weaker among neighborhoods with higher proportion grass/shrub cover or overall greenness. The most substantially narrowed inequities were those by the ICE. Mortality inequities did not differ substantially by perceived park access, and tree canopy was associated with weaker ICE-based inequities only. In this ecologic analysis, neighborhood greenspace was associated with weaker mortality inequities. However, associations varied across greenspace type and sociodemographic composition metrics, with generally stronger associations with overall greenness and grass/shrub coverage, and for ICE-basedinequities. [ABSTRACT FROM AUTHOR]

Global climate change is leading to higher ambient temperatures and more frequent heatwaves. To date, impacts of ambient extreme heat on childhood morbidity have been understudied, although—given children's physiologic susceptibility, with smaller body surface-to-mass ratios, and many years of increasing temperatures ahead—there is an urgent need for better information to inform public health policies and clinical approaches. In this review, we aim to (1) identify pediatric morbidity outcomes previously associated with extreme heat, (2) to identify predisposing co-morbidities which may make children more susceptible to heat-related outcomes, and (3) to map the current body of available literature. A scoping review of the current full-text literature was conducted using the Arksey and O'Malley framework Int J Soc Res Methodol 8:19-32, (2015). Search terms for (1) pediatric population, (2) heat exposures, (3) ambient conditions, and (4) adverse outcomes were combined into a comprehensive PubMed and Medline literature search. Of the 1753 publications identified, a total of 20 relevant studies were ultimately selected based on selection criteria of relevance to US urban populations. Most identified studies supported positive associations between high extreme temperature exposures and heat-related illness, dehydration/electrolyte imbalance, general symptoms, diarrhea and digestion disorders, infectious diseases/infections, asthma/wheeze, and injury. Most studies found no association with renal disease, cardiovascular diseases, or diabetes mellitus. Results were mixed for other respiratory diseases and mental health/psychological disorders. Very few of the identified studies examined susceptibility to pre-existing conditions; Cystic Fibrosis was the only co-morbidity for which we found significant evidence. Further research is needed to understand the nuances of associations between extreme heat and specific outcomes—particularly how associations may vary by child age, sex, race/ ethnicity, community characteristics, and other pre-existing conditions. [ABSTRACT FROM AUTHOR]

Abstract: Background: Epidemiological studies have linked both noise and air pollution to common adverse health outcomes such as increased blood pressure and myocardial infarction. In urban settings, noise and air pollution share important sources, notably traffic, and several recent studies have shown spatial correlations between noise and air pollution. The temporal association between these exposures, however, has yet to be thoroughly investigated despite the importance of time series studies in air pollution epidemiology and the potential that correlations between these exposures could at least partly confound statistical associations identified in these studies. Methods: An aethelometer, for continuous elemental carbon measurement, was co-located with a continuous noise monitor near a major urban highway in New York City for six days in August 2009. Hourly elemental carbon measurements and hourly data on overall noise levels and low, medium and high frequency noise levels were collected. Hourly average concentrations of fine particles and nitrogen oxides, wind speed and direction and car, truck and bus traffic were obtained from nearby regulatory monitors. Overall temporal patterns, as well as day–night and weekday–weekend patterns, were characterized and compared for all variables. Results: Noise levels were correlated with car, truck, and bus traffic and with air pollutants. We observed strong day–night and weekday–weekend variation in noise and air pollutants and correlations between pollutants varied by noise frequency. Medium and high frequency noise were generally more strongly correlated with traffic and traffic-related pollutants than low frequency noise and the correlation with medium and high frequency noise was generally stronger at night. Correlations with nighttime high frequency noise were particularly high for car traffic (Spearman rho=0.84), nitric oxide (0.73) and nitrogen dioxide (0.83). Wind speed and direction mediated relationships between pollutants and noise. Conclusions: Noise levels are temporally correlated with traffic and combustion pollutants and correlations are modified by the time of day, noise frequency and wind. Our results underscore the potential importance of assessing temporal variation in co-exposures to noise and air pollution in studies of the health effects of these urban pollutants. [Copyright &y& Elsevier]

Background: The Democratic National Convention (DNC) in Boston, Massachusetts in 2004 provided an opportunity to evaluate the impacts of a localized and short-term but potentially significant change in traffic patterns on air quality, and to determine the optimal monitoring approach to address events of this nature. It was anticipated that the road closures associated with the DNC would both influence the overall air pollution level and the distribution of concentrations across the city, through shifts in traffic patterns. Methods: To capture these effects, we placed passive nitrogen dioxide badges at 40 sites around metropolitan Boston before, during, and after the DNC, with the goal of capturing the array of hypothesized impacts. In addition, we continuously measured elemental carbon at three sites, and gathered continuous air pollution data from US EPA fixed-site monitors and traffic count data from the Massachusetts Highway Department. Results: There were significant reductions in traffic volume on the highway with closures north of Boston, with relatively little change along other highways, indicating a more isolated traffic reduction rather than an across-the-board decrease. For our nitrogen dioxide samples, while there was a relatively small change in mean concentrations, there was significant heterogeneity across sites, which corresponded with our a priori classifications of road segments. The median ratio of nitrogen dioxide concentrations during the DNC relative to non-DNC sampling periods was 0.58 at sites with hypothesized traffic reductions, versus 0.88 for sites with no changes hypothesized and 1.15 for sites with hypothesized traffic increases. Continuous monitors measured slightly lower concentrations of elemental carbon and nitrogen dioxide during road closure periods at monitors proximate to closed highway segments, but not for PM2.5 or further from major highways. Conclusion: We conclude that there was a small but measurable influence of DNC-related road closures on air quality patterns in the Boston area, and that a low-cost monitoring study combining passive badges for spatial heterogeneity and continuous monitors for temporal heterogeneity can provide useful insight for community air quality assessments. [ABSTRACT FROM AUTHOR]

Background: Emerging literature has documented heat‐related impacts on child health, yet few studies have evaluated the effects of heat among children of different age groups and comparing emergency department (ED) and hospitalisation risks. Objectives: To examine the differing associations between high ambient temperatures and risk of ED visits and hospitalisations among children by age group in New York City (NYC). Methods: We used New York Statewide Planning and Research Cooperative System (SPARCS) data on children aged 0–18 years admitted to NYC EDs (n = 2,252,550) and hospitals (n = 228,006) during the warm months (May‐September) between 2005 and 2011. Using a time‐stratified, case‐crossover design, we estimated the risk of ED visits and hospitalisations associated with daily maximum temperature (Tmax) for children of all ages and by age group. Results: The average Tmax over the study period was 80.3°F (range 50°, 104°F). Tmax conferred the greatest risk of ED visits for children aged 0–4, with a 6‐day cumulative excess risk of 2.4% (95% confidence interval [CI] 1.7, 3.0) per 13°F (ie interquartile range) increase in temperature. Children and adolescents 5–12 years (0.8%, 95% CI 0.1, 1.6) and 13–18 years (1.4%, 95% CI 0.6, 2.3) are also sensitive to heat. For hospitalisations, only adolescents 13–18 years had increased heat‐related risk, with a cumulative excess risk of 7.9% (95% CI 2.0, 14.2) per 13°F increase in Tmax over 85°F. Conclusions: This urban study in NYC reinforces that young children are particularly vulnerable to effects of heat, but also demonstrates the sensitivity of older children and adolescents as well. These findings underscore the importance of focussing on children and adolescents in targeting heat illness prevention and emergency response activities, especially as global temperatures continue to rise. [ABSTRACT FROM AUTHOR]

Background: Children in urban public housing are at high risk for asthma, given elevated environmental and social exposures and suboptimal medical care. For a multifactorial disease like asthma, design of intervention studies can be influenced by the relative prevalence of key risk factors. To better understand risk factors for asthma morbidity in the context of an environmental intervention study, we conducted a detailed baseline evaluation of 78 children (aged 4-17 years) from three public housing developments in Boston. Methods: Asthmatic children and their caregivers were recruited between April 2002 and January 2003. We conducted intake interviews that captured a detailed family and medical history, including questions regarding asthma symptom severity, access to health care, medication usage, and psychological stress. Quality of life was evaluated for both the child and caregiver with an asthma-specific scale. Pulmonary function was measured with a portable spirometer, and allergy testing for common indoor and outdoor allergens was conducted with skin testing using the prick puncture method. Exploratory linear and logistic regression models evaluating predictors of respiratory symptoms, quality of life, and pulmonary function were conducted using SAS. Results: We found high rates of obesity (56%) and allergies to indoor contaminants such as cockroaches (59%) and dust mites (59%). Only 36% of children with persistent asthma reported being prescribed any daily controller medication, and most did not have an asthma action plan or a peak flow meter. One-time lung function measures were poorly correlated with respiratory symptoms or quality of life, which were significantly correlated with each other. In multivariate regression models, household size, body mass index, and environmental tobacco smoke exposure were positively associated with respiratory symptom severity (p < 0.10). Symptom severity was negatively associated with asthma-related quality of life for the child and the caregiver, with caregiver (but not child) quality of life significantly influenced by caregiver stress and whether the child was in the intensive care unit at birth. Conclusion: Given the elevated prevalence of multiple risk factors, coordinated improvements in the social environment, the built environment, and in medical management would likely yield the greatest health benefits in this high-risk population. [ABSTRACT FROM AUTHOR]

BACKGROUND: Despite a vast air pollution epidemiology literature to date and the recognition that lower-socioeconomic status (SES) populations are often disproportionately exposed to pollution, there is little research identifying optimal means of adjusting for confounding by SES in air pollution epidemiology, nor is there a strong understanding of biases that may result from improper adjustment. OBJECTIVE: We aim to provide a conceptualization of SES and a review of approaches to its measurement in the U.S. context and discuss pathways by which SES may influence health and confound effects of air pollution. We explore bias related to measurement and operationalization and identify statistical approaches to reduce bias and confounding. DISCUSSION: Drawing on the social epidemiology, health geography, and economic literatures, we describe how SES, a multifaceted construct operating through myriad pathways, may be conceptualized and operationalized in air pollution epidemiology studies. SES varies across individuals within the contexts of place, time, and culture. Although no single variable or index can fully capture SES, many studies rely on only a single measure. We recommend examining multiple facets of SES appropriate to the study design. Furthermore, investigators should carefully consider the multiple mechanisms by which SES might be operating to identify those SES indicators that may be most appropriate for a given context or study design and assess the impact of improper adjustment on air pollution effect estimates. Last, exploring model contraction and expansion methods may enrich adjustment, whereas statistical approaches, such as quantitative bias analysis, may be used to evaluate residual confounding. [ABSTRACT FROM AUTHOR]

BACKGROUND: Chronic exposure to air pollution may prime the immune system to be reactive, increasing inflammatory responses to immune stimulation and providing a pathway to increased risk for inflammatory diseases, including asthma and cardiovascular disease. Although long-term exposure to ambient air pollution has been associated with increased circulating markers of inflammation, it is unknown whether it also relates to the magnitude of inflammatory response. OBJECTIVES: The aim of this study was to examine associations between chronic ambient pollution exposures and circulating and stimulated levels of inflammatory mediators in a cohort of healthy adults. METHODS: Circulating interleukin (IL)-6, C-reactive protein (CRP) (n=392), and lipopolysaccharide stimulated production of IL-1ß, IL-6, and tumor necrosis factor (TNF)-a (n=379) were measured in the Adult Health and Behavior II cohort. Fine particulate matter [particulate matter with aerodynamic diameter less than or equal to 2.5 µm (PM2.5)] and constituents [black carbon (BC), and lead (Pb), manganese (Mn), zinc (Zn), and iron (Fe)] were estimated for each residential address using hybrid dispersion land use regression models. Associations between pollutant exposures and inflammatory measures were examined using linear regression; models were adjusted for age, sex, race, education, smoking, body mass index, and month of blood draw. RESULTS: There were no significant correlations between circulating and stimulated measures of inflammation. Significant positive associations were found between exposure to PM2.5 and BC with stimulated production of IL-6, IL-1ß, and TNF-a. Pb, Mn, Fe, and Zn exposures were positively associated with stimulated production of IL-1ß and TNF-a. No pollutants were associated with circulating IL-6 or CRP levels. DISCUSSION: Exposure to PM2.5, BC, Pb, Mn, Fe, and Zn was associated with increased production of inflammatory mediators by stimulated immune cells. In contrast, pollutant exposure was not related to circulating markers of inflammation. These results suggest that chronic exposure to some pollutants may prime immune cells to mount larger inflammatory responses, possibly contributing to increased risk for inflammatory disease. [ABSTRACT FROM AUTHOR]

BACKGROUND: Chronic exposure to air pollution may prime the immune system to be reactive, increasing inflammatory responses to immune stimulation and providing a pathway to increased risk for inflammatory diseases, including asthma and cardiovascular disease. Although long-term exposure to ambient air pollution has been associated with increased circulating markers of inflammation, it is unknown whether it also relates to the magnitude of inflammatory response. OBJECTIVES: The aim of this study was to examine associations between chronic ambient pollution exposures and circulating and stimulated levels of inflammatory mediators in a cohort of healthy adults. METHODS: Circulating interleukin (IL)-6, C-reactive protein (CRP) (푛 = 392), and lipopolysaccharide stimulated production of IL-1β, IL-6, and tumor necrosis factor (TNF)-α (푛 = 379) were measured in the Adult Health and Behavior II cohort. Fine particulate matter [particulate matter with aerodynamic diameter less than or equal to 2.5 µm (PM2.5)] and constituents [black carbon (BC), and lead (Pb), manganese (Mn), zinc (Zn), and iron (Fe)] were estimated for each residential address using hybrid dispersion land use regression models. Associations between pollutant exposures and inflammatory measures were examined using linear regression; models were adjusted for age, sex, race, education, smoking, body mass index, and month of blood draw. RESULTS: There were no significant correlations between circulating and stimulated measures of inflammation. Significant positive associations were found between exposure to PM2.5 and BC with stimulated production of IL-6, IL-1β, and TNF-α. Pb, Mn, Fe, and Zn exposures were positively associated with stimulated production of IL-1β and TNF-α. No pollutants were associated with circulating IL-6 or CRP levels. DISCUSSION: Exposure to PM2.5, BC, Pb, Mn, Fe, and Zn was associated with increased production of inflammatory mediators by stimulated immune cells. In contrast, pollutant exposure was not related to circulating markers of inflammation. These results suggest that chronic exposure to some pollutants may prime immune cells to mount larger inflammatory responses, possibly contributing to increased risk for inflammatory disease. [ABSTRACT FROM AUTHOR]

Ambient air pollution contributes to an estimated 6.67 million deaths annually, and has been linked to cardiovascular disease (CVD), the leading cause of death. Short-term increases in air pollution have been associated with increased risk of CVD event, though relatively few studies have directly compared effects of multiple pollutants using fine-scale spatio-temporal data, thoroughly adjusting for co-pollutants and temperature, in an exhaustive citywide hospitals dataset, towards identifying key pollution sources within the urban environment to most reduce, and reduce disparities in, the leading cause of death worldwide. We aimed to examine multiple pollutants against multiple CVD diagnoses, across lag days, in models adjusted for co-pollutants and meteorology, and inherently adjusted by design for non-time-varying individual and aggregate-level covariates, using fine-scale space-time exposure estimates, in an exhaustive dataset of emergency department visits and hospitalizations across an entire city, thereby capturing the full population-at-risk. We used conditional logistic regression in a case-crossover design – inherently controlling for all confounders not varying within case month – to examine associations between spatio-temporal nitrogen dioxide (NO 2), fine particulate matter (PM 2.5), sulfur dioxide (SO 2), and ozone (O 3) in New York City, 2005–2011, on individual risk of acute CVD event (n = 837,523), by sub-diagnosis [ischemic heart disease (IHD), heart failure (HF), stroke, ischemic stroke, acute myocardial infarction]. We found significant same-day associations between NO 2 and risk of overall CVD, IHD, and HF – and between PM 2.5 and overall CVD or HF event risk – robust to all adjustments and multiple comparisons. Results were comparable by sex and race – though median age at CVD was 10 years younger for Black New Yorkers than White New Yorkers. Associations for NO 2 were comparable for adults younger or older than 69 years, though PM 2.5 associations were stronger among older adults. Discussion: Our results indicate immediate, robust effects of combustion-related pollution on CVD risk, by sub-diagnosis. Though acute impacts differed minimally by age, sex, or race, the much younger age-at-event for Black New Yorkers calls attention to cumulative social susceptibility. • Using refined spatio-temporal data and methods, we found significant associations for same-day NO 2 and risk of CVD event - particularly for IHD and HF. • Case-day PM 2.5 was also associated with cardiovascular events and HF. • Associations were strongest and robust only for NO 2 , after sensitivity tests and adjustment for multiple comparisons and multiple pollutants – emphasizing attention to local combustion sources (i.e., vehicular emissions). [ABSTRACT FROM AUTHOR]

The article discusses research which evaluated the impact of the clean heat program (CHP), which was designed to eliminate the use of residual heating oil and move toward cleaner energy forms, on air pollution levels in New York City. Topics covered include air pollution reductions attributable to CHP between 2012 and 2016, how the reductions vary by neighborhood socioeconomic status (SES), and the effects of CHP since its implementation.

Abstract During winter nights, woodsmoke may be a predominant source of air pollution, even in cities with many sources. Since two major earthquakes resulted in major structural damage in 2010 and 2011, reliance on woodburning for home heating has increased substantially in Christchurch, New Zealand (NZ), along with intensive construction/demolition activities. Further, because NZ is a relatively isolated western country, it offers the unique opportunity to disentangle multiple source impacts in the absence of long-range transport pollution. Finally, although many spatial saturation studies have been published, and levoglucosan is an established tracer for woodburning emissions, few studies have monitored multiple sites simultaneously for this or other organic constituents, with the ability to distinguish spatial patterns for daytime vs. nighttime hours, in complex urban settings. We captured seven-day integrated samples of PM 2.5 , and elemental and organic tracers of woodsmoke and diesel emissions, during "daytime" (7 a.m. – 5:30 p.m.) and "nighttime" (7 p.m. – 5:30 a.m.) hours, at nine sites across commercial and residential areas, over three weeks in early winter (May 2014). At a subset of six sites, we also sampled during hypothesized "peak" woodburning hours (7 p.m. – 12 a.m.), to differentiate emissions during "active" residential woodburning, vs. overnight smouldering. Concentrations of PM 2.5 were, on average, were twice as high during nighttime than daytime [µ = 18.4 (SD = 6.13) vs. 9.21 (SD = 6.13) µg/m3], with much greater differences in woodsmoke tracers (i.e., levoglucosan [µ = 1.83 (SD = 0.82) vs. 0.34 (SD = 0.17) µg/m3], potassium) and indicators of treated- or painted-wood burning (e.g., arsenic, lead). Only nitrogen dioxide, calcium, iron, and manganese (tracers of vehicular emissions) were higher during daytime. Levoglucosan and most PAHs were higher during "active" woodburning, vs. overnight smouldering. Our time-stratified spatial saturation detected strong spatial variability throughout the study area, which distinctly differed during daytime vs. night time hours, and quantified the substantial contribution of woodsmoke to overnight spatial variation in PM 2.5 across Christchurch. Daytime vs. nighttime differences were greater than those observed across sites. Traffic, especially diesel, contributed substantially to daytime NO 2 and spatial gradients in non-woodsmoke constituents. Highlights • Few studies examine woodburning with urban sources on spatial variance in pollution. • Few studies isolate nighttime vs. daytime pollution patterns, using source tracers. • Average concentrations differed more for daytime vs. nighttime than across sites. • We found higher woodsmoke and treated-wood tracers at night; higher NO 2 by day. • We found higher levoglucosan and PAHs during woodburning vs. smouldering. [ABSTRACT FROM AUTHOR]

Growing evidence suggests that exposure to greenness benefits health, but studies assess greenness differently. We hypothesize greenness-health associations vary by exposure assessment method. To test this, we considered four vegetation datasets (three Normalized Difference Vegetation Index datasets with different spatial resolutions and a finely-resolved land cover dataset), and six aggregation units (five radial buffer sizes and self-described neighborhoods) of each dataset. We compared associations of self-rated health and these metrics of greenness among a sample of New York City residents. Associations with self-rated health varied more by aggregation unit than by vegetation dataset; larger buffers and self-described neighborhoods showed more positive associations. Researchers should consider spatial exposure misclassification in future greenness and health research. [ABSTRACT FROM AUTHOR]

Although neighborhood factors have been consistently associated with health, technological difficulties in eliciting self-defined neighborhoods from large cohorts have compromised the interpretability of this research. Here, we offer a mixed-methods approach to elicit and validate self-defined neighborhoods. Participants used a customized Google.Maps interface to “draw” their neighborhood and answered questions about perceived map accuracy, neighborhood definition, and neighborhood activities. We compared geographic concordance of drawn and narrative neighborhood definitions, quantified differential accuracy by demographic characteristics, and examined factors influencing neighborhood definitions. We found similar geographic concordance between narrative and mapped boundaries in two cities, with no differences by neighborhood size. Selfreported neighborhoods had greater concordance with larger administrative areas (e.g., police precincts) than for smaller units (e.g., census tracts). To delineate their neighborhood boundaries, participants reported using administrative definitions, walking distance, their familiarity with people and structures, where they spend time, and physical landmarks. In New York City, participants also reported considering sociodemographic characteristics and transportation. Our method demonstrates the feasibility of collecting perceived (egocentric) neighborhoods through online mapping surveys, adaptable to many study settings. [ABSTRACT FROM AUTHOR]

Objectives High ambient temperatures are associated with significant health risk in the United States. The risk to children has been minimally explored, and often young children are considered as a single age group despite marked physiologic and social variation among this population from infancy through preschool. This study explored the heterogeneity of risk of heat among young children. Study design Using a time-stratified, case-crossover design, we evaluated associations between maximum daily temperature (Tmax) and ED visits (n = 1,002,951) to New York City (NYC) metropolitan area hospitals for children aged 0-4 years in May-September, 2005-2011. Methods Conditional logistic regression analysis estimated risks for an interquartile range of Tmax for 0-6 lag days. Stratified analyses explored age strata by year, race/ethnic groups, and diagnostic codes. Sensitivity analyses controlled for same day ambient ozone, particulate matter <2.5 microns, and relative humidity and, separately, explored race groups without ethnicity and different diagnostic code groupings. Results Children ages 0-4 years had increased risk of emergency department visits with increased Tmax on lag days 0, 1, and 3. The association was strongest on lag day 0, when an increase in Tmax of 13 °F conferred an excess risk of 2.6% (95% confidence interval [CI]: 2.2-3.0). Stratifying by age, we observed significant positive associations for same-day exposures, for 1-4 year olds. Children less than 1 year of age showed a significant positive association with Tmax only on lag day 3. The race/ethnicity stratified analysis revealed a similar lag pattern for all subgroups. The diagnostic group analysis showed percent excess risk for heat-specific diagnoses (16.6% [95% CI: 3.0-31.9]); general symptoms (10.1% [95% CI: 8.2-11.9]); infectious (4.9% [95% CI: 3.9-5.9]); and injury (5.1% [95% CI: 3.8-6.4]) diagnoses. Conclusion We found a significant risk of ED visits in young children with elevated Tmax. Risk patterns vary based on age with infants showing delayed risk and toddlers and preschoolers with same day risk. In addition, the finding of increased risk of injury associated with higher temperatures is novel. Altogether, these findings suggest a need for a tailored public health response, such as different messages to caregivers of different age children, to protect children from the effects of heat. Next steps include examining specific subcategories of diagnoses to develop protective strategies and better anticipate the needs of population health in future scenarios of climate change [ABSTRACT FROM AUTHOR]

Ambient air pollution, temperature, and social stressor exposures are linked with asthma risk, with potential synergistic effects. We examined associations for acute pollution and temperature exposures, with modification by neighborhood violent crime and socioeconomic deprivation, on asthma morbidity among children aged 5–17 years year-round in New York City. Using conditional logistic regression in a time-stratified, case-crossover design, we quantified percent excess risk of asthma event per 10-unit increase in daily, residence-specific exposures to PM 2.5 , NO 2 , SO 2 , O 3 , and minimum daily temperature (Tmin). Data on 145,834 asthma cases presenting to NYC emergency departments from 2005 to 2011 were obtained from the New York Statewide Planning and Research Cooperative System (SPARCS). Residence- and day-specific spatiotemporal exposures were assigned using the NYC Community Air Survey (NYCCAS) spatial data and daily EPA pollution and NOAA weather data. Point-level NYPD violent crime data for 2009 (study midpoint) was aggregated, and Socioeconomic Deprivation Index (SDI) scores assigned, by census tract. Separate models were fit for each pollutant or temperature exposure for lag days 0–6, controlling for co-exposures and humidity, and mutually-adjusted interactions (modification) by quintile of violent crime and SDI were assessed. We observed stronger main effects for PM 2.5 and SO 2 in the cold season on lag day 1 [4.90% (95% CI: 3.77–6.04) and 8.57% (5.99–11.21), respectively]; Tmin in the cold season on lag day 0 [2.26% (1.25–3.28)]; and NO 2 and O 3 in the warm season on lag days 1 [7.86% (6.66–9.07)] and 2 [4.75% (3.53–5.97)], respectively. Violence and SDI modified the main effects in a non-linear manner; contrary to hypotheses, we found stronger associations in lower-violence and -deprivation quintiles. At very high stressor exposures, although asthma exacerbations were highly prevalent, pollution effects were less apparent—suggesting potential saturation effects in socio-environmental synergism. [Display omitted] • Interactions of pollutants, temperature, and chronic stressors on childhood asthma. • PM2.5, SO2, and Tmin effects in the cold season, and NO2 and O3 in the warm season. • Non-linear modification by neighborhood violence and socioeconomic deprivation. • Stronger associations observed in lower-violence and -deprivation quintiles. • Potential saturation effects in socio-environmental stressor synergism. [ABSTRACT FROM AUTHOR]

Capturing intra-urban variation in diesel-related pollution exposures remains a challenge, given its complex chemical mix, and relatively few well-characterized ambient-air tracers for the multiple diesel sources in densely-populated urban areas. To capture fine-scale spatial resolution (50 × 50 m grid cells) in diesel-related pollution, we used geographic information systems (GIS) to systematically allocate 36 sampling sites across downtown Pittsburgh, PA, USA (2.8 km 2 ), cross-stratifying to disentangle source impacts (i.e., truck density, bus route frequency, total traffic density). For buses, outbound and inbound trips per week were summed by route and a kernel density was calculated across sites. Programmable monitors collected fine particulate matter (PM 2.5 ) samples specific to workweek hours (Monday–Friday, 7 am–7 pm), summer and winter 2013. Integrated filters were analyzed for black carbon (BC), elemental carbon (EC), organic carbon (OC), elemental constituents, and diesel-related organic compounds [i.e., polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes]. To our knowledge, no studies have collected this suite of pollutants with such high sampling density, with the ability to capture spatial patterns during specific hours of interest. We hypothesized that we would find substantial spatial variation for each pollutant and significant associations with key sources (e.g. diesel and gasoline vehicles), with higher concentrations near the center of this small downtown core. Using a forward stepwise approach, we developed seasonal land use regression (LUR) models for PM 2.5 , BC, total EC, OC, PAHs, hopanes, steranes, aluminum (Al), calcium (Ca), and iron (Fe). Within this small domain, greater concentration differences were observed in most pollutants across sites, on average, than between seasons. Higher PM 2.5 and BC concentrations were found in the downtown core compared to the boundaries. PAHs, hopanes, and steranes displayed different spatial patterning across the study area by constituent. Most LUR models suggested a strong influence of bus-related emissions on pollution gradients. Buses were more dominant predictors compared to truck and vehicular traffic for several pollutants. Overall, we found substantial variation in diesel-related concentrations in a very small downtown area, which varied across elemental and organic components. [ABSTRACT FROM AUTHOR]

Because fine particulate matter (PM 2.5 ) differs in chemical composition, source apportionment is frequently used for identification of relative contributions of multiple sources to outdoor concentrations. Indoor air pollution and source apportionment is often overlooked, though people in northern climates may spend up to 90% of their time inside. We selected 21 homes for a 1-week indoor sampling session during summer (July to September 2011), repeated in winter (January to March 2012). Elemental analysis was performed using inductively-coupled plasma mass spectrometry (ICP-MS), and factor analysis was used to determine constituent grouping. Multivariate modeling was run on factor scores to corroborate interpretations of source factors based on a literature review. For each season, a 5-factor solution explained 86–88% of variability in constituent concentrations. Indoor sources (i.e. cooking, smoking) explained greater variability than did outdoor sources in these industrial communities. A smoking factor was identified in each season, predicted by number of cigarettes smoked. Cooking factors were also identified in each season, explained by frequency of stove cooking and stovetop frying. Significant contributions from outdoor sources including coal and motor vehicles were also identified. Higher coal and secondary-related elemental concentrations were detected during summer than winter. Our findings suggest that source contributions to indoor concentrations can be identified and should be examined in relation to health effects. [ABSTRACT FROM AUTHOR]

BACKGROUND: Recent studies have suggested associations between air pollution and various birth outcomes, but the evidence for preterm birth is mixed. OBJECTIVE: We aimed to assess the relationship between air pollution and preterm birth using 2008-2010 New York City (NYC) birth certificates linked to hospital records. METHODS: We analyzed 258,294 singleton births with 22-42 completed weeks gestation to nonsmoking mothers. Exposures to ambient fine particles (PM2.5) and nitrogen dioxide (NO2) during the first, second, and cumulative third trimesters within 300 m of maternal address were estimated using data from the NYC Community Air Survey and regulatory monitors. We estimated the odds ratio (OR) of spontaneous preterm (gestation < 37 weeks) births for the first- and second-trimester exposures in a logistic mixed model, and the third-trimester cumulative exposures in a discrete time survival model, adjusting for maternal characteristics and delivery hospital. Spatial and temporal components of estimated exposures were also separately analyzed. RESULTS: PM2.5 was not significantly associated with spontaneous preterm birth. NO2 in the second trimester was negatively associated with spontaneous preterm birth in the adjusted model (OR = 0.90; 95% CI: 0.83, 0.97 per 20 ppb). Neither pollutant was significantly associated with spontaneous preterm birth based on adjusted models of temporal exposures, whereas the spatial exposures showed significantly reduced odds ratios (OR = 0.80; 95% CI: 0.67, 0.96 per 10 µg/m³ PM2.5 and 0.88; 95% CI: 0.79, 0.98 per 20 ppb NO2). Without adjustment for hospital, these negative associations were stronger. CONCLUSION: Neither PM2.5 nor NO2 was positively associated with spontaneous preterm delivery in NYC. Delivery hospital was an important spatial confounder. [ABSTRACT FROM AUTHOR]

Characterizing near-source spatio-temporal variation is a long -standing challenge in air pollution epidemiology, and common intra-urban modeling approaches [e.g., land use regression (LUR)], do not account for short-term meteorological variation. Atmospheric dispersion modeling approaches, such as AERMOD, can account for near-source pollutant behavior by capturing source-meteorological interactions, but requires external validation and resolved background concentrations. In this study, we integrate AERMOD-based predictions for source-specific fine particle (PM 2.5 ) concentrations into LUR models derived from total ambient PM 2.5 measured at 36 unique sites selected to represent different source and elevation profiles, during summer and winter, 2012–2013 in Pittsburgh, Pennsylvania (PA). We modeled PM 2.5 emissions from 207 local stationary sources in AERMOD, utilizing the monitoring locations as receptors, and hourly meteorological information matching each sampling period. Finally, we compare results of the integrated LUR/AERMOD hybrid model to those of the AERMOD + background and standard LUR models, at the full domain scale and within a 5 km 2 sub-domain surrounding a large industrial facility. The hybrid model improved out-of-sample prediction accuracy by 2–10% over LUR alone, though performance differed by season, in part due to within-season temporal variability. We found differences up to 10 μg/m 3 in predicted concentrations, and observed the largest differences within the industrial sub-domain. LUR underestimated concentrations from 500 to 2500 m downwind of major sources. The hybrid modeling approach we developed may help to improve intra-urban exposure estimates, particularly in regions of large industrial sources, sharp elevation gradients, or complex meteorology (e.g., frequent inversion events), such as Pittsburgh, PA. More broadly, the approach may inform the development of spatio-temporal modeling frameworks for air pollution exposure assessment for epidemiology. [ABSTRACT FROM AUTHOR]

Land use regression (LUR) has evolved as a standard tool for estimating intra-urban variation in long-term air pollution exposures. LUR, however, generally relies on observed spatial relationships between distributed sources and pollution measures, rather than meteorological or physio-chemical information. Incorporating traffic-meteorological interaction information into LURs via dispersion models may improve accuracy and physical interpretability. To examine whether deterministic dispersion output improves LUR predictions for nitrogen dioxide (NO 2 ), we incorporated hourly Caline3QHCR dispersion information into existing winter-time regression models originally designed to disentangle effects of multiple sources (e.g., legacy industry, vehicle traffic) and concentration modifiers (e.g., elevation) across Pittsburgh, PA. Caline3QHCR output improved overall cross-validated R 2 values by 0.10, 0.03, and 0.05 for the weekday, full-week, and merged years models, respectively. The addition of Caline3 output as an independent covariate effectively displaced two road-specific predictors, one built environment predictor and one meteorological predictor across two winter-season models. The incorporation of study-specific dispersion principles may corroborate overall LUR model interpretability and could be applied similarly to preexisting LUR models that lack strong source-concentration relationships. Model improvements were observed at sites with relatively higher NO 2 concentrations that exhibited higher traffic volumes and were in closer proximity to roadways (< 300 m), which may have an important bearing towards better characterizing exposures in both near-roadway and high-traffic environments. [ABSTRACT FROM AUTHOR]

Impacts of industrial emissions on outdoor air pollution in nearby communities are well-documented. Fewer studies, however, have explored impacts on indoor air quality in these communities. Because persons in northern climates spend a majority of their time indoors, understanding indoor exposures, and the role of outdoor air pollution in shaping such exposures, is a priority issue. Braddock and Clairton, Pennsylvania, industrial communities near Pittsburgh, are home to an active steel mill and coke works, respectively, and the population experiences elevated rates of childhood asthma. Twenty-one homes were selected for 1-week indoor sampling for fine particulate matter (PM 2.5 ) and black carbon (BC) during summer 2011 and winter 2012. Multivariate linear regression models were used to examine contributions from both outdoor concentrations and indoor sources. In the models, an outdoor infiltration component explained 10 to 39% of variability in indoor air pollution for PM 2.5 , and 33 to 42% for BC. For both PM 2.5 models and the summer BC model, smoking was a stronger predictor than outdoor pollution, as greater pollutant concentration increases were identified. For winter BC, the model was explained by outdoor pollution and an open windows modifier. In both seasons, indoor concentrations for both PM 2.5 and BC were consistently higher than residence-specific outdoor concentration estimates. Mean indoor PM 2.5 was higher, on average, during summer (25.8 ± 22.7 μg/m 3 ) than winter (18.9 ± 13.2 μg/m 3 ). Contrary to the study's hypothesis, outdoor concentrations accounted for only little to moderate variability (10 to 42%) in indoor concentrations; a much greater proportion of PM 2.5 was explained by cigarette smoking. Outdoor infiltration was a stronger predictor for BC compared to PM 2.5 , especially in winter. Our results suggest that, even in industrial communities of high outdoor pollution concentrations, indoor activities – particularly cigarette smoking – may play a larger role in shaping indoor exposures. [ABSTRACT FROM AUTHOR]

Research on the health effects of fine particulate matter (PM2.5) frequently disregards the differences in particle composition between that measured on an ambient filter versus that measured in the corresponding extraction solution used for toxicological testing. This study presents a novel method for characterizing the differences, in metallic and organic species, between the ambient samples and the corresponding extracted solutions through characterization of extracted PM2.5 suspended on filters. Removal efficiency was found to be 98.0 ± 1.4% when measured using pre- and post-removal filter weights, however, this efficiency was significantly reduced to 80.2 ± 0.8% when measured based on particle mass in the extraction solution. Furthermore, only 47.2 ± 22.3% of metals and 24.8 ± 14.5% of organics measured on the ambient filter were found in the extraction solution. Individual metallic and organic components were extracted with varying efficiency, with many organics being lost entirely during extraction. Finally, extraction efficiencies of specific PM2.5 components were inversely correlated with total mass. This study details a method to assess compositional alterations resulting from extraction of PM2.5 from filters, emphasizing the need for standardized procedures that maintain compositional integrity of ambient samples for use in toxicology studies of PM2.5. [ABSTRACT FROM AUTHOR]

Numerous studies have linked air pollution with adverse birth outcomes, but relatively few have examined differential associations across the socioeconomic gradient. To evaluate interaction effects of gestational nitrogen dioxide (NO 2 ) and area-level socioeconomic deprivation on fetal growth, we used: (1) highly spatially-resolved air pollution data from the New York City Community Air Survey (NYCCAS); and (2) spatially-stratified principle component analysis of census variables previously associated with birth outcomes to define area-level deprivation. New York City (NYC) hospital birth records for years 2008–2010 were restricted to full-term, singleton births to non-smoking mothers ( n =243,853). We used generalized additive mixed models to examine the potentially non-linear interaction of nitrogen dioxide (NO 2 ) and deprivation categories on birth weight (and estimated linear associations, for comparison), adjusting for individual-level socio-demographic characteristics and sensitivity testing adjustment for co-pollutant exposures. Estimated NO 2 exposures were highest, and most varying, among mothers residing in the most-affluent census tracts, and lowest among mothers residing in mid-range deprivation tracts. In non-linear models, we found an inverse association between NO 2 and birth weight in the least-deprived and most-deprived areas ( p -values<0.001 and 0.05, respectively) but no association in the mid-range of deprivation ( p =0.8). Likewise, in linear models, a 10 ppb increase in NO 2 was associated with a decrease in birth weight among mothers in the least-deprived and most-deprived areas of −16.2 g (95% CI: −21.9 to −10.5) and −11.0 g (95% CI: −22.8 to 0.9), respectively, and a non-significant change in the mid-range areas [ β =0.5 g (95% CI: −7.7 to 8.7)]. Linear slopes in the most- and least-deprived quartiles differed from the mid-range (reference group) ( p -values<0.001 and 0.09, respectively). The complex patterning in air pollution exposure and deprivation in NYC, however, precludes simple interpretation of interactive effects on birth weight, and highlights the importance of considering differential distributions of air pollution concentrations, and potential differences in susceptibility, across deprivation levels. [ABSTRACT FROM AUTHOR]

There is growing interest in the role of psychosocial stress in health disparities. Identifying which social stressors are most important to community residents is critical for accurately incorporating stressor exposures into health research. Using a community-academic partnered approach, we designed a multi-community study across the five boroughs of New York City to characterize resident perceptions of key neighborhood stressors. We conducted 14 community focus groups; two to three in each borough, with one adolescent group and one Spanish-speaking group per borough. We then used systematic content analysis and participant ranking data to describe prominent neighborhood stressors and identify dominant themes. Three inter-related themes regarding the social and structural sources of stressful experiences were most commonly identified across neighborhoods: (1) physical disorder and perceived neglect, (2) harassment by police and perceived safety and (3) gentrification and racial discrimination. Our findings suggest that multiple sources of distress, including social, political, physical and economic factors, should be considered when investigating health effects of community stressor exposures and psychological distress. Community expertise is essential for comprehensively characterizing the range of neighborhood stressors that may be implicated in psychosocial exposure pathways. [ABSTRACT FROM AUTHOR]

The causes of autism spectrum disorder (ASD) are not well known. Recent investigations have suggested that air pollution, including PM 2.5 , may play a role in the onset of this condition. The objective of the present work was to investigate the association between prenatal and early childhood exposure to fine particulate matter (PM 2.5 ) and risk for childhood ASD. A population-based case-control study was conducted in children born between January 1, 2005 and December 31, 2009 in six counties in Southwestern Pennsylvania. ASD cases were recruited from specialty autism clinics, local pediatric practices, and school-based special needs services. ASD cases were children who scored 15 or above on the Social Communication Questionnaire (SCQ) and had written documentation of an ASD diagnosis. Controls were children without ASD recruited from a random sample of births from the Pennsylvania state birth registry and frequency matched to cases on birth year, gender, and race. A total of 217 cases and 226 controls were interviewed. A land use regression (LUR) model was used to create person- and time-specific PM 2.5 estimates for individual (pre-pregnancy, trimesters one through three, pregnancy, years one and two of life) and cumulative (starting from pre-pregnancy) key developmental time periods. Logistic regression was used to investigate the association between estimated exposure to PM 2.5 during key developmental time periods and risk of ASD, adjusting for mother's age, education, race, and smoking. Adjusted odds ratios (AOR) were elevated for specific pregnancy and postnatal intervals (pre-pregnancy, pregnancy, and year one), and postnatal year two was significant, (AOR=1.45, 95% CI=1.01–2.08). We also examined the effect of cumulative pregnancy periods; noting that starting with pre-pregnancy through pregnancy, the adjusted odds ratios are in the 1.46–1.51 range and significant for pre-pregnancy through year 2 (OR=1.51, 95% CI=1.01–2.26). Our data indicate that both prenatal and postnatal exposures to PM 2.5 are associated with increased risk of ASD. Future research should include multiple pollutant models and the elucidation of the biological mechanism for PM 2.5 and ASD. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has resulted in an extraordinary incidence of morbidity and mortality, with almost 6 million deaths worldwide at the time of this writing (https://covid19.who.int/). There has been a pressing need for research that would shed light on factors – especially modifiable factors – that could reduce risks to human health. At least several hundred studies addressing the complex relationships among transmission of SARS-CoV-2, air pollution, and human health have been published. However, these investigations are limited by available and consistent data. The project goal was to seek input into opportunities to improve and fund exposure research on the confluence of air pollution and infectious agents such as SARS-CoV-2. Thirty-two scientists with expertise in exposure science, epidemiology, risk assessment, infectious diseases, and/or air pollution responded to the outreach for information. Most of the respondents expressed value in developing a set of common definitions regarding the extent and type of public health lockdown. Traffic and smoking ranked high as important sources of air pollution warranting source-specific research (in contrast with assessing overall ambient level exposures). Numerous important socioeconomic factors were also identified. Participants offered a wide array of inputs on what they considered to be essential studies to improve our understanding of exposures. These ranged from detailed mechanistic studies to improved air quality monitoring studies and prospective cohort studies. Overall, many respondents indicated that these issues require more research and better study design. As an exercise to solicit opinions, important concepts were brought forth that provide opportunities for scientific collaboration and for consideration for funding prioritization. Further conversations on these concepts are needed to advance our thinking on how to design research that moves us past the documented limitations in the current body of research and prepares us for the next pandemic. • Extant research on air pollution and COVID-19 has documented limitations. • We offer ideas from numerous scientists for overcoming current research limitations. • A common definition for pandemic-related societal restrictions is recommended. • Consideration of socio-economic status is critical to pandemic research. • Suggested concepts can be used for research and funding prioritization. [ABSTRACT FROM AUTHOR]

Background Recent toxicological and epidemiological evidence suggests that chronic psychosocial stress may modify pollution effects on health. Thus, there is increasing interest in refined methods for assessing and incorporating non-chemical exposures, including social stressors, into environmental health research, towards identifying whether and how psychosocial stress interacts with chemical exposures to influence health and health disparities. We present a flexible, GIS-based approach for examining spatial patterns within and among a range of social stressors, and their spatial relationships with air pollution, across New York City, towards understanding their combined effects on health. Methods We identified a wide suite of administrative indicators of community-level social stressors (2008-2010), and applied simultaneous autoregressive models and factor analysis to characterize spatial correlations among social stressors, and between social stressors and air pollutants, using New York City Community Air Survey (NYCCAS) data (2008-2009). Finally, we provide an exploratory ecologic analysis evaluating possible modification of the relationship between nitrogen dioxide (NO2) and childhood asthma Emergency Department (ED) visit rates by social stressors, to demonstrate how the methods used to assess stressor exposure (and/or consequent psychosocial stress) may alter model results. Results Administrative indicators of a range of social stressors (e.g., high crime rate, residential crowding rate) were not consistently correlated (rho = - 0.44 to 0.89), nor were they consistently correlated with indicators of socioeconomic position (rho = - 0.54 to 0.89). Factor analysis using 26 stressor indicators suggested geographically distinct patterns of social stressors, characterized by three factors: violent crime and physical disorder, crowding and poor access to resources, and noise disruption and property crimes. In an exploratory ecologic analysis, these factors were differentially associated with area-average NO2 and childhood asthma ED visits. For example, only the 'violent crime and disorder' factor was significantly associated with asthma ED visits, and only the 'crowding and resource access' factor modified the association between area-level NO2 and asthma ED visits. Conclusions This spatial approach enabled quantification of complex spatial patterning and confounding between chemical and non-chemical exposures, and can inform study design for epidemiological studies of separate and combined effects of multiple urban exposures. [ABSTRACT FROM AUTHOR]

Background Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. Methods We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. Results During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Conclusions Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling. [ABSTRACT FROM AUTHOR]

Building on a unique exposure assessment project in New York, New York, we examined the relationship of particulate matter with aerodynamic diameter less than 2.5 μm and nitrogen dioxide with birth weight, restricting the population to term births to nonsmokers, along with other restrictions, to isolate the potential impact of air pollution on growth. We included 252,967 births in 2008–2010 identified in vital records, and we assigned exposure at the residential location by using validated models that accounted for spatial and temporal factors. Estimates of association were adjusted for individual and contextual sociodemographic characteristics and season, using linear mixed models to quantify the predicted change in birth weight in grams related to increasing pollution levels. Adjusted estimates for particulate matter with aerodynamic diameter less than 2.5 μm indicated that for each 10-µg/m3 increase in exposure, birth weights declined by 18.4, 10.5, 29.7, and 48.4 g for exposures in the first, second, and third trimesters and for the total pregnancy, respectively. Adjusted estimates for nitrogen dioxide indicated that for each 10-ppb increase in exposure, birth weights declined by 14.2, 15.9, 18.0, and 18.0 g for exposures in the first, second, and third trimesters and for the total pregnancy, respectively. These results strongly support the association of urban air pollution exposure with reduced fetal growth. [ABSTRACT FROM PUBLISHER]

Background: Recent epidemiological studies have examined the associations between air pollution and birth outcomes. Regulatory air quality monitors often used in these studies, however, were spatially sparse and unable to capture relevant within-city variation in exposure during pregnancy. Methods: This study developed two-week average exposure estimates for fine particles (PM2.5) and nitrogen dioxide (NO2) during pregnancy for 274,996 New York City births in 2008-2010. The two-week average exposures were constructed by first developing land use regression (LUR) models of spatial variation in annual average PM2.5 and NO2 data from 150 locations in the New York City Community Air Survey and emissions source data near monitors. The annual average concentrations from the spatial models were adjusted to account for city-wide temporal trends using time series derived from regulatory monitors. Models were developed using Year 1 data and validated using Year 2 data. Two-week average exposures were then estimated for three buffers of maternal address and were averaged into the last six weeks, the trimesters, and the entire period of gestation. We characterized temporal variation of exposure estimates, correlation between PM2.5 and NO2, and correlation of exposures across trimesters. Results: The LUR models of average annual concentrations explained a substantial amount of the spatial variation (R2 = 0.79 for PM2.5 and 0.80 for NO2). In the validation, predictions of Year 2 two-week average concentrations showed strong agreement with measured concentrations (R2 = 0.83 for PM2.5 and 0.79 for NO2). PM2.5 exhibited greater temporal variation than NO2. The relative contribution of temporal vs. spatial variation in the estimated exposures varied by time window. The differing seasonal cycle of these pollutants (bi-annual for PM2.5 and annual for NO2) resulted in different patterns of correlations in the estimated exposures across trimesters. The three levels of spatial buffer did not make a substantive difference in estimated exposures. Conclusions: The combination of spatially resolved monitoring data, LUR models and temporal adjustment using regulatory monitoring data yielded exposure estimates for PM2.5 and NO2 that performed well in validation tests. The interaction between seasonality of air pollution and exposure intervals during pregnancy needs to be considered in future studies. [ABSTRACT FROM AUTHOR]