Do socioeconomic characteristics modify the short term association between air pollution and mortality? Evidence from a zonal time series in Hamilton, Canada

Effects of the lockdown measure amid COVID-19 pandemic on outpatient department visits associated with air pollution reduction in Thailand

We investigated the effects of COVID-19 lockdown on air quality and its consequences health and economic benefits in Thailand. The conditional Poisson regression model was applied to examine the association between air pollution and outpatient department (OPD) visits in each province and pooled the province-specific estimates using the random-effects meta-analysis to derive the national estimates. We then applied a random forest model with meteorological normalization approach to predict the concentration of air pollutants by means of business as usual during the lockdown period (April 3-May 3) in 2020 and further calculated the changes in the number of OPD visits and their consequent expenditure attributable to air pollution reduction using the obtained risk function performed earlier. The number of cardiovascular OPD visits attributed to PM10, PM2.5 and NO2 decreased by 4,414 (95% CI 982, 8,401), 4,040 (95% CI 326, 7,770), and 13,917 (95% CI 1,675, 27,278) cases, respectively, leading to reduced medical expenditure by 14,7180.21, 13,4708.31, and 46,4025.04 USD, respectively. The number of respiratory OPD visits attributed to PM10, PM2.5, NO2, and O3 reduction decreased by 2,298 (95% CI 1,223, 3,375), 2,056 (95% CI 740, 3,252), 3,326 (95% CI 542, 6,295), and 1,160 (95% CI 5,26, 1,804) cases, respectively, where the consequent medical expenditure was reduced by 76,618.48, 68,566.36, 11,0908.31, and 38,685.50 USD, respectively. Finding from this study showed that air quality during the lockdown period in Thailand was improved, contributing to the reduction of cardiovascular and respiratory OPD visits, and consequent medical service costs attributable to air pollution.

Long-term exposure to ambient black carbon is associated with sleep disturbance in college students

BACKGROUND

Evidence suggests an association of air pollution with sleep quality. However, there is limited knowledge regarding the effect of black carbon, a key component of ambient particulate matter, on sleep.

OBJECTIVES

To investigate the association of long-term exposure to black carbon and sleep quality in a group of college students.

METHODS

A retrospective cohort study was conducted in five universities in different regions of China. The concentrations of black carbon and other environment factors were defined as the averages during the 6 years prior to the recruitment. Averagely daily dose of black carbon exposure was estimated according to the respiratory rate. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI) with a cutoff >5 indicating sleep disturbance. Linear regression and logistic regression models were used to estimate the association. The sensitivity analyses were conducted to estimate the effects of 1-month, 6-month and 1-year mean levels of exposure to black carbon on sleep quality.

RESULTS

A total of 20,053 incoming college students were included. 29.3% reported impaired sleep quality, with a mean PSQI score of 4.3 ± 2.2. The logistic regression showed that the risk of impaired sleep quality was positively associated with black carbon exposure, especially in the highest quantile (OR: 1.26, 95% CI: 1.11-1.43) compared with the lowest quartile after adjusting for potential confounders. Subgroup analysis showed that the effect of black carbon on sleep quality was stronger in participants with higher BMI, lower household income, and lower parental educational level. The results of sensitivity analyses were similar with main analyses.

CONCLUSION

Long-term exposure to black carbon is associated with sleep disturbance in college students. Improvement of air quality may help improve sleep quality.

An approach to quantifying the potential importance of residual confounding in systematic reviews of observational studies: A GRADE concept paper

Small relative effect sizes are common in observational studies of exposure in environmental and public health. However, such effects can still have considerable policy importance when the baseline rate of the health outcome is high, and many persons are exposed. Assessing the certainty of the evidence based on these effect sizes is challenging because they can be prone to residual confounding due to the non-randomized nature of the evidence. When applying GRADE, a precise relative risk >2.0 increases the certainty in an existing effect because residual confounding is unlikely to explain the association. GRADE also suggests rating up when opposing plausible residual confounding exists for other effect sizes. In this concept paper, we propose using the E-value, defined as the smallest effect size of a confounder that still can reduce an observed RR to the null value, and a reference confounder to assess the likelihood of residual confounding. We propose a 4-step approach. 1. Assess the association of interest for relevant exposure levels. 2. Calculate the E-value for this observed association. 3. Choose a reference confounder with sufficient strength and information and assess its effect on the observed association using the E-value. 4. Assess how likely it is that residual confounding will still bias the observed RR. We present three case studies and discuss the feasibility of the approach.

Social status and susceptibility to wildfire smoke among outdoor-housed female rhesus monkeys: A natural experiment

Introduction

Wildfire smoke (WFS) exposure is a growing threat to human health, and lower socioeconomic position (SEP) has been shown to increase pollution susceptibility. Studies of SEP-related susceptibility, however, are often compromised due to spatial confounding between lower-SEP and pollution. Here we examine outdoor-housed nonhuman primates, living in natural social hierarchy in a common location, born during years of high vs. low WFS, to examine the separate and combined effects of WFS and social rank, an analog to SEP, on lung and immune function.

Methods

Twenty-one females were born during extreme WFS events in summer 2008; 22 were born in summer 2009, during low WFS. Pulmonary function and circulating cytokines were measured three years later, in adolescence. We estimated fine particulate (PM_2.5) and ozone exposures during each animal's first 90 days and three years of age using regulatory data. Early-life social status was estimated using maternal rank at birth, as rank in females is relatively stable throughout life, and closely approximates mother's rank. We tested associations among WFS exposure, rank, and endpoints using linear regression and ANOVA.

Results

Higher WFS exposure in infancy was, on average, associated with lower functional residual capacity (FRC), residual volume (RV), tissue compliance (Ct), and IL-8 secretion in adolescence. Higher social rank conferred significantly higher expiratory reserve volume (ERV) and functional residual capacity (FRC) solely among those born in the high-WFS year (2008). Differences in effects of rank between years were not significant after adjustment for multiple comparisons.

Conclusions

Exposure to WFS in infancy generally conferred lower adolescent respiratory volumes and inflammatory cytokines. Higher rank conferred higher respiratory volumes only among females born during WFS, suggesting the possibility that the health benefits of rank may be more apparent under environmental challenge.

Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease

INTRODUCTION

Cardiovascular disease (CVD) is the leading cause of death in the United States, and substantial research has linked ambient air pollution to elevated rates of CVD etiology and events. Much of this research identified increased effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are also often higher. The complex spatial confounding between air pollution and SEP makes it very challenging, however, to disentangle the impacts of these very different exposure types and to accurately assess their interactions. The specific causal components (i.e., specific social stressors) underlying this SEP-related susceptibility remain unknown, because there are myriad pathways through which poverty and/or lower-SEP conditions may influence pollution susceptibility - including diet, smoking, coexposures in the home and occupational environments, health behaviors, and healthcare access. Growing evidence suggests that a substantial portion of SEP-related susceptibility may be due to chronic psychosocial stress - given the known wide-ranging impacts of chronic stress on immune, endocrine, and metabolic function - and to a higher prevalence of unpredictable chronic stressors in many lower-SEP communities, including violence, job insecurity, and housing instability. As such, elucidating susceptibility to pollution in the etiology of CVD, and in the risk of CVD events, has been identified as a research priority. This interplay among social and environmental conditions may be particularly relevant for CVD, because pollution and chronic stress both impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes relevant to CVD etiology. Because pollution exposures are often spatially patterned by SEP, disentangling their effects - and quantifying any interplay - is especially challenging. Doing so, however, would help to improve our ability to identify and characterize susceptible populations and to improve our understanding of how community stressors may alter responses to multiple air pollutants. More clearly characterizing susceptible populations will improve our ability to design and target interventions more effectively (and cost-effectively) and may reveal greater benefits of pollution reduction in susceptible communities, strengthening cost-benefit and accountability analyses, ultimately reducing the disproportionate burden of CVD and reducing health disparities.

METHODS

In the current study, we aimed to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using a number of unique datasets we have compiled and verified, including the following. 1. Poverty metrics, violent crime rates, a composite socioeconomic deprivation index (SDI), an index of racial and economic segregation, noise disturbance metrics, and three composite spatial factors produced from a factor analysis of 27 community stressors. All indicators have citywide coverage and were verified against individual reports of stress and stressor exposure, in citywide focus groups and surveys. 2. Spatial surfaces for multiple pollutants from the New York City (NYC) Community Air Survey (NYCCAS), which monitored multiple pollutants year-round at 150 sites and used land use regression (LUR) modeling to estimate fine-scale (100-m) intra-urban spatial variance in fine particles (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). 3. Daily data and time-trends derived from all U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) monitors in NYC for 2005-2011, which we combined with NYCCAS surfaces to create residence- and day-specific spatiotemporal exposure estimates. 4. Complete data on in- and out-patient unscheduled CVD events presented in NYC hospitals for 2005-2011 (n = 1,113,185) from the New York State (NYS) Department of Health's Statewide Planning and Research Cooperative System (SPARCS). In the study, we quantified relationships between multiple pollutant exposures and both community CVD event rates and individual risk of CVD events in NYC and tested whether pollution-CVD associations varied by community SEP and social stressor exposures. We hypothesized (1) that greater chronic community-level SEP, stressor, and pollution exposures would be associated with higher community CVD rates; (2) that spatiotemporal variations in multiple pollutants would be associated with excess risk of CVD events; and (3) that pollution-CVD associations would be stronger in communities of lower SEP or higher stressor exposures.

RESULTS

To first understand the separate and combined associations with CVD for both stressors and pollutants measured at the same spatial and temporal scale of resolution, we used ecological cross-sectional models to examine spatial relationships between multiple chronic pollutant and stressor exposures and age-adjusted community CVD rates. Using census-tract-level annual averages (n = 2,167), we compared associations with CVD rates for multiple pollutant concentrations and social stressors. We found that associations with community CVD rates were consistently stronger for social stressors than for pollutants, in terms of both magnitude and significance. We note, however, that this result may be driven by the relatively greater variation (on a proportional basis) for stressors than for pollutants in NYC. We also tested effect modification of pollutant-CVD associations by each social stressor and found evidence of stronger associations for NO2, PM2.5, and wintertime SO2 with CVD rates, particularly across quintiles of increasing community violence or assault rates (P trend < 0.0001). To examine individual-level associations between spatiotemporal exposures to multiple pollutants and the risk of CVD events, across multiple lag days, we examined the combined effects of multiple pollutant exposures, using spatiotemporal (day- and residence-specific) pollution exposure estimates and hospital data on individual CVD events in case-crossover models, which inherently adjust for nontime-varying individual confounders (e.g., sex and race) and comorbidities. We found consistent significant relationships only for same-day pollutant exposures and the risk of CVD events, suggesting very acute impacts of pollution on CVD risk. Associations with CVD were positive for NO2, PM2.5, and SO2, as hypothesized, and we found inverse associations for O3 (a secondary pollutant chemically decreased ["scavenged"] by fresh emissions that, in NYC, displays spatial and temporal patterns opposite those of NO2). Finally, to test effect modification by chronic community social stressors on the relationships between spatiotemporal pollution measures and the risk of CVD events, we used individual-level case-crossover models, adding interaction terms with categorical versions of each social stressor. We found that associations between NO2 and the risk of CVD events were significantly elevated only in communities with the highest exposures to social stressors (i.e., in the highest quintiles of poverty, socioeconomic deprivation, violence, or assault). The largest positive associations for PM2.5 and winter SO2 were generally found in the highest-stressor communities but were not significant in any quintile. We again found inverse associations for O3, which were likewise stronger for individuals living in communities with greater stressor exposures.

CONCLUSIONS

In ecological models, we found stronger relationships with community CVD rates for social stressors than for pollutant exposures. In case-crossover analyses, higher exposures to NO2, PM2.5, and SO2 were associated with greater excess risk of CVD events but only on the case day (there were no consistent significant lagged-day effects). In effect-modification analyses at both the community and individual level, we found evidence of stronger pollution-CVD associations in communities with higher stressor exposures. Given substantial spatial confounding across multiple social stressors, further research is needed to disentangle these effects in order to identify the predominant social stressors driving this observed differential susceptibility.

The impact of life behavior and environment on particulate matter in chronic obstructive pulmonary disease

BACKGROUND

The effect of exposure to particulate matter (PM) on human health is a global public health concern. To develop an effective strategy to reduce PM exposure, we performed detailed questionnaire surveys regarding the type of lifestyle required to avoid PM exposure in patients with chronic obstructive pulmonary disease (COPD). We correlated the data with real-time PM concentration during the winter season.

METHODS

We enrolled 104 patients with COPD aged 40 years or older. Detailed questionnaire surveys were conducted among participants, and internet of things-based sensors were installed at their homes to measure the indoor PM_2.5 concentration, which was continuously monitored between December 2019 and February 2020. The associations among PM_2.5 concentration, patients' lifestyles, and the impact of both concentration and lifestyle on COPD exacerbation were analyzed.

RESULTS

Mean outdoor PM_2.5 concentration was higher than mean indoor PM_2.5 concentration during the study period (21.28 ± 5.09 μg/m³ vs. 12.75 ± 7.64 μg/m³), with a mean difference of 8.53 ± 7.99 μg/m³. Among the various social factors and practices that aim to avoid exposure to PM, six practices and economic statuses were confirmed to reduce indoor PM_2.5 concentration compared to outdoor concentration; Contrarily, these practices created a significant difference between the outdoor and indoor PM_2.5 concentrations. The six practice items that showed a significant difference were 1) checking air quality forecast (the difference: -13.31 ± 1.35 μg/m³, p = 0.013), 2) indoor air filter operated (-15.43 ± 1.32 μg/m³, p < 0.001), 3) ventilating home by opening the windows (-13.14 ± 1.28 μg/m³, p = 0.013), 4) checking filters of the air filter (-13.95 ± 1.50 μg/m³, p = 0.002), 5) refraining from going out when outside PM is high (-12.52 ± 1.37 μg/m³, p = 0.039), 6) wearing a mask when going out (-13.38 ± 1.32 μg/m³, p = 0.017). The higher the household income and economic level, the more significant the difference in the PM_2.5 concentration. Severe exacerbation was more prevalent among patients with acute exacerbation as the exposure time of PM_2.5≥35 μg/m³ or PM_2.5≥75 μg/m³.

CONCLUSION

Lifestyle and economic levels can affect the indoor PM_2.5 concentration, which may impact COPD exacerbation.

Multi-dimensional community characteristics in linking particulate matter pollution and cause-specific mortality: 72 communities of South Korea

Concentration-response function for exposure to ambient particulate matter (PM) and mortality (i.e., relative risk, RR) may be inequal across communities by socioeconomic conditions. Investigation on specific mechanisms of this inequality regarding susceptibility to PM, beyond non-specific "socioeconomic conditions", would provide policy-relevant implications for tackling this inequality. However, such investigation via epidemiological studies is challenged by residual confounding by correlated mechanisms and different loss of life expectancy by PM exposures between communities. Here, we aimed to assess community characteristics including different aspects of socioeconomic deprivation, medical resources, health behaviors, air quality, and greenness in their relation to inequal RR for PM₁₀ and cause-specific mortality in 72 municipalities in South Korea, 2006-2013, considering these challenges. We found that a 10 μg/m³ increase in PM₁₀ on average across 46 days was associated with a 1.05% (95% CI: 0.24, 1.88) increase in all-cause mortality (ALL), 1.32% (95% CI: -0.29, 2.95) increase in cardiovascular mortality (CVD), and 6.47% (95% CI: 3.06, 10.00) increase in respiratory mortality (RES). The association between PM₁₀ and mortality was higher in communities with higher ratio of SO₂ to PM₁₀ (ALL and RES), higher material deprivation (ALL, CVD, and RES), lower medical resources (CVD), higher prevalence of drinking (ALL and CVD), and lower prevalence of smoking (CVD and RES). Lag-structures showed smaller loss of life expectancy by PM exposures in communities with higher prevalence of smoking. Our findings suggest that PM-related health inequalities are shaped by a variety of mechanisms relating to susceptibility to PM exposures and different loss of life expectancy. Health policies controlling community characteristics may contribute to minimizing PM₁₀-related health inequalities in those perspectives.

Do socioeconomic factors modify the effects of PM1 and SO2 on lung cancer incidence in China?

BACKGROUND

It remains uncertain whether socioeconomic factors modify the effect of air pollution on human health. Moreover, studies investigating socioeconomic modifying roles on the effect of PM1 are quite limited, especially in developing countries.

OBJECTIVES

The present study aims to investigate socioeconomic modification effects on the associations of the incidence rate of male lung cancer with ambient PM1 and SO2 in China.

METHODS

We conducted a nationwide analysis in 345 Chinese counties (districts) between 2014 and 2015. In terms of multivariable linear regression models, we examined the modification effects of urban-rural division, education level and proportion of construction workers in the stratified and combined datasets according to the tertile and binary divisions of the three factors. Moreover, we performed three sensitivity analyses to test the robustness of socioeconomic modification effects.

RESULTS

We found a larger effect of PM1 on the incidence rate of male lung cancer in urban areas than in rural areas. The association between PM1 (or SO2) and the incidence rate of male lung cancer was stronger in counties with low education levels than in those with high education levels. The findings of the significant modification effects of urban-rural division and education level were robust in the three sensitivity analyses. No significant modification effect was observed for the proportion of construction workers.

CONCLUSIONS

Male residents in urban areas have a high risk of lung cancer incidence associated with ambient PM1. Male residents with low education levels suffer from larger effects of PM1 and SO2 on the incidence rate of lung cancer. Area- and population-specific strategies should be developed to reduce the urban-rural and educational disparities in air pollution effects, which thereby alleviates air pollution-associated health disparities in China.

Mortality risks due to long-term ambient sulphur dioxide exposure: large variability of relative risk in the literature

Several studies have been published about the potential health effects due to long-term exposure to sulphur dioxide (SO₂) and the relative risks (RRs) for different causes of mortality. Broad differences in the RR values are found, however. In this study, we performed an analysis of these studies aiming finding potential explanations for the high variability of the RR reported. The RRs for stratified subgroups were also analysed to identify more susceptible subgroups. A total of 14 studies were identified. Some of them related strong associations between mortality and long-term ambient SO₂ exposure, while others found insignificant or no associations to the same mortality indexes. The mean RR values ranged from 0.95 to 1.14 for mortality due to all causes, 0.99 to 3.05 for lung cancer, 0.87 to 1.3 for respiratory diseases, 0.96 to 1.14 cardiovascular diseases and 0.97 to 1.05 for cardiopulmonary diseases mortality. Among the factors that may affect the RR estimations, only the size of studied population and the spatial scales used in exposure assessment showed notable influences. The female population was found to be more susceptible to long-term SO₂ exposure. For other stratified subgroups including age, smoking status and income levels, no obvious relationship with RR was observed.

Selecting a Scale for Spatial Confounding Adjustment

Unmeasured, spatially-structured factors can confound associations between spatial environmental exposures and health outcomes. Adding flexible splines to a regression model is a simple approach for spatial confounding adjustment, but the spline degrees of freedom do not provide an easily interpretable spatial scale. We describe a method for quantifying the extent of spatial confounding adjustment in terms of the Euclidean distance at which variation is removed. We develop this approach for confounding adjustment with splines and using Fourier and wavelet filtering. We demonstrate differences in the spatial scales these bases can represent and provide a comparison of methods for selecting the amount of confounding adjustment. We find the best performance for selecting the amount of adjustment using an information criterion evaluated on an outcome model without exposure. We apply this method to spatial adjustment in an analysis of fine particulate matter and blood pressure in a cohort of United States women.

Assessing the Impact of Ozone and Particulate Matter on Mortality Rate from Respiratory Disease in Seoul, Korea

The evidence linking ozone and particulate matter with adverse health impacts is increasing. The goal of this study was to assess the impact of air pollution on the mortality rate from respiratory disease in Seoul, Korea, between 2008 and 2017. The analysis was conducted using a decision tree model in two ways: using 24-hour average concentrations and using 1-hour maximum values to compare any health impacts from the different times of exposure to pollution. Results show that in spring an elevated level of ozone is one of the most important factors, but in summer temperature has a greater impact than air pollution. Nitrogen dioxide is one of the most important factors in fall, while high levels of particles less than 2.5 μm (PM2.5) and 10 μm in size (PM10) and cooler temperatures are key factors in winter. We checked the accuracy of our results through a 10-fold cross validation method. Error rates using 24-hour average and 1-hour maximum concentrations were in the ranges of 24.9%–42% and 27.6%–42%, respectively, indicating that 24-hour average concentrations are slightly more directly related with mortality rate. These results could be useful for policy makers in determining the temporal scale of predicted pollutant concentrations for an air quality warning system to help minimize the adverse impacts of air pollution.

Air pollution and lung cancer incidence in China: Who are faced with a greater effect?

BACKGROUND

Whether socioeconomic indicators modify the relationship between air pollution exposure and health outcomes remains uncertain, especially in developing countries.

OBJECTIVE

This work aims to examine modification effects of socioeconomic indicators on the association between PM2.5 and annual incidence rate of lung cancer for males in China.

METHODS

We performed a nationwide analysis in 295 counties (districts) from 2006 to 2014. Using multivariable linear regression models controlling for weather conditions and socioeconomic indicators, we examined modification effects in the stratified and combined datasets according to the tertile and binary divisions of socioeconomic indicators. We also extensively investigated whether the roles of socioeconomic modifications were sensitive to the further adjustment of demographic factors, health and behaviour covariates, household solid fuel consumption, the different operationalization of socioeconomic indicators and PM2.5 exposure with single and moving average lags.

RESULTS

We found a stronger relationship between PM2.5 and incidence rate of male lung cancer in urban areas, in the lower economic or lower education counties (districts). If PM2.5 changes by 10 μg/m³, then the shift in incidence rate relative to its mean was significantly higher by 3.97% (95% CI: 2.18%, 4.96%, p = 0.000) in urban than in rural areas. With regard to economic status, if PM2.5 changes by 10 μg/m³, then the change in incidence rate relative to its mean was significantly lower by 0.99% (95% CI: -2.18%, 0.20%, p = 0.071) and 1.39% (95% CI: -2.78%, 0.00%, p = 0.037) in the middle and high economic groups than in the low economic group, respectively. The change in incidence rate relative to its mean was significantly lower by 1.98% (95% CI: -3.18%, -0.79%, p = 0.001) and 2.78% (95% CI: -4.17%, -1.39%, p = 0.000) in the middle and high education groups compared with the low education group, respectively, if PM2.5 changes by 10 μg/m³. We found no robust modification effects of employment rate and urbanisation growth rate.

CONCLUSION

Male residents in urban areas, in the lower economic or lower education counties are faced with a greater effect of PM2.5 on the incidence rate of lung cancer in China. The findings emphasize the need for public health intervention and urban planning initiatives targeting the urban-rural, educational or economic disparities in health associated with air pollution exposure. Future prediction on air pollution-induced health effects should consider such socioeconomic disparities, especially for the dominant urban-rural disparity in China.

Social Inequalities in Exposure to Ambient Air Pollution: A Systematic Review in the WHO European Region

Ambient air pollution is a long-standing and significant public health issue. The aim of this review is to systematically examine the peer-reviewed evidence on social inequalities and ambient air pollution in the World Health Organization European Region. Articles published between 2010 and 2017 were analyzed in the review. In total 31 articles were included in the review. There is good evidence from ecological studies that higher deprivation indices and low economic position are usually linked with higher levels of pollutants such as particulate matter (particulate matter under 2.5 and 10 microns in diameter, PM_2.5, PM₁₀) and oxides of nitrogen (e.g., NO₂, and NO_x). There is also evidence that ethnic minorities experience a mixed exposure in comparison to the majority population being sometimes higher and sometimes lower depending on the ethnic minority under consideration. The studies using data at the individual level in this review are mainly focused on pregnant women or new mothers, in these studies deprivation and ethnicity are more likely to be linked to higher exposures of poor air quality. Therefore, there is evidence in this review that the burden of higher pollutants falls disproportionally on different social groups.

Personal NO2 and Volatile Organic Compounds Exposure Levels are Associated with Markers of Cardiovascular Risk in Women in the Cape Town Region of South Africa

Exposure to ambient NO2 and benzene, toluene ethyl-benzene and m+p- and o-xylenes (BTEX) is associated with adverse cardiovascular effects, but limited information is available on the effects of personal exposure to these compounds in South African populations. This 6-month follow-up study aims to determine 7-day personal ambient NO2 and BTEX exposure levels via compact passive diffusion samplers in female participants from Cape Town, and investigate whether exposure levels are associated with cardiovascular risk markers. Overall, the measured air pollutant exposure levels were lower compared to international standards. NO2 was positively associated with systolic and diastolic blood pressure (SBP and DBP), and inversely associated with the central retinal venular equivalent (CRVE) and mean baseline brachial artery diameter. o-xylene was associated with DBP and benzene was strongly associated with carotid intima media thickness (cIMT). Our findings showed that personal air pollution exposure, even at relatively low levels, was associated with several markers of cardiovascular risk in women residing in the Cape Town region.

Utilization of the Maryland Environmental Justice Screening Tool: A Bladensburg, Maryland Case Study

Maryland residents' knowledge of environmental hazards and their health effects is limited, partly due to the absence of tools to map and visualize distribution of risk factors across sociodemographic groups. This study discusses the development of the Maryland EJSCREEN (MD EJSCREEN) tool by the National Center for Smart Growth in partnership with faculty at the University of Maryland School of Public Health. The tool assesses environmental justice risks similarly to the U.S. Environmental Protection Agency's (USEPA) EJSCREEN tool and California's tool, CalEnviroScreen 3.0. We discuss the architecture and functionality of the tool, indicators of importance, and how it compares to USEPA's EJSCREEN and CalEnviroScreen. We demonstrate the use of MD EJSCREEN through a case study on Bladensburg, Maryland, a town in Prince George's County (PG) with several environmental justice concerns including air pollution from traffic and a concrete plant. Comparison reveals that environmental and demographic indicators in MD EJSCREEN most closely resemble those in EPA EJSCREEN, while the scoring is most similar to CalEnviroScreen. Case study results show that Bladensburg has a Prince George's environmental justice score of 0.99, and that National Air Toxics Assessment (NATA) air toxics cancer risk is concentrated in communities of color.

Early life stress, air pollution, inflammation, and disease: An integrative review and immunologic model of social-environmental adversity and lifespan health

Socially disadvantaged individuals are at greater risk for simultaneously being exposed to adverse social and environmental conditions. Although the mechanisms underlying joint effects remain unclear, one hypothesis is that toxic social and environmental exposures have synergistic effects on inflammatory processes that underlie the development of chronic diseases, including cardiovascular disease, diabetes, depression, and certain types of cancer. In the present review, we examine how exposure to two risk factors that commonly occur with social disadvantage-early life stress and air pollution-affect health. Specifically, we identify neuroimmunologic pathways that could link early life stress, inflammation, air pollution, and poor health, and use this information to propose an integrated, multi-level model that describes how these factors may interact and cause health disparity across individuals based on social disadvantage. This model highlights the importance of interdisciplinary research considering multiple exposures across domains and the potential for synergistic, cross-domain effects on health, and may help identify factors that could potentially be targeted to reduce disease risk and improve lifespan health.

Air pollution, deprivation and health: understanding relationships to add value to local air quality management policy and practice in Wales, UK

Background

Air pollution exposure reduces life expectancy. Air pollution, deprivation and poor-health status combinations can create increased and disproportionate disease burdens. Problems and solutions are rarely considered in a broad public health context, but doing so can add value to air quality management efforts by reducing air pollution risks, impacts and inequalities.

Methods

An ecological study assessed small-area associations between air pollution (nitrogen dioxide and particulate matter), deprivation status and health outcomes in Wales, UK.

Results

Air pollution concentrations were highest in 'most' deprived areas. When considered separately, deprivation-health associations were stronger than air pollution-health associations. Considered simultaneously, air pollution added to deprivation-health associations; interactions between air pollution and deprivation modified and strengthened associations with all-cause and respiratory disease mortality, especially in 'most' deprived areas where most-vulnerable people lived and where health needs were greatest.

Conclusion

There is a need to reduce air pollution-related risks for all. However, it is also the case that greater health gains can result from considering local air pollution problems and solutions in the context of wider health-determinants and acting on a better understanding of relationships. Informed and co-ordinated air pollution mitigation and public health action in high deprivation and pollution areas can reduce risks and inequalities. To achieve this, greater public health integration and collaboration in local air quality management policy and practice is needed.

Health status and air pollution related socioeconomic concerns in urban China

Background

China is experiencing environmental issues and related health effects due to its industrialization and urbanization. The health effects associated with air pollution are not just a matter of epidemiology and environmental science research, but also an important social science issue. Literature about the relationship of socioeconomic factors with the environment and health factors is inadequate. The relationship between air pollution exposure and health effects in China was investigated with consideration of the socioeconomic factors.

Methods

Based on nationwide survey data of China in 2014, we applied the multilevel mixed-effects model to evaluate how socioeconomic status (represented by education and income) contributed to the relationship between self-rated air pollution and self-rated health status at community level and individual level.

Results

The findings indicated that there was a non-linear relationship between the community socioeconomic status and community air pollution in urban China, with the highest level of air pollution presented in the communities with moderate socioeconomic status. In addition, health effects associated air pollution in different socioeconomic status groups were not equal. Self-rated air pollution had the greatest impact on self-rated health of the lower socioeconomic groups. With the increase of socioeconomic status, the effect of self-rated air pollution on self-rated health decreased.

Conclusions

This study verified the different levels of exposure to air pollution and inequality in health effects among different socioeconomic groups in China. It is imperative for the government to urgently formulate public policies to enhance the ability of the lower socioeconomic groups to circumvent air pollution and reduce the health damage caused by air pollution.

Air Pollution and Human Development in Europe: A New Index Using Principal Component Analysis

EU countries to measure human development incorporating the ambient PM2.5 concentration effect. Using a principal component analysis, we extract the information for 2010 and 2015 using the Real GDP/capita, the life expectancy at birth, tertiary educational attainment, ambient PM2.5 concentration, and the death rate due to exposure to ambient PM2.5 concentration for 29 European countries. This paper has two main results: it gives an overview about the relationship between human development and ambient PM2.5 concentration, and second, it provides a new quantitative measure, PHDI, which reshapes the concept of human development and the exposure to ambient PM2.5 concentration. Using rating classes, we defined thresholds for both HDI and PHDI values to group the countries in four categories. When comparing the migration matrix from 2010 to 2015 for HDI values, some countries improved the development indicator (Romania, Poland, Malta, Estonia, Cyprus), while no downgrades were observed. When comparing the transition matrix using the newly developed indicator, PHDI, the upgrades observed were for Denmark and Estonia, while some countries like Spain and Italy moved to a lower rating class due to ambient PM2.5 concentration.

Socioeconomic and urban-rural differentials in exposure to air pollution and mortality burden in England

BACKGROUND

Socioeconomically disadvantaged populations often have higher exposures to particulate air pollution, which can be expected to contribute to differentials in life expectancy. We examined socioeconomic differentials in exposure and air pollution-related mortality relating to larger scale (5 km resolution) variations in background concentrations of selected pollutants across England.

METHODS

Ozone and particulate matter (sub-divided into PM₁₀, PM_2.5, PM_2.5-10, primary, nitrate and sulphate PM_2.5) were simulated at 5 km horizontal resolution using an atmospheric chemistry transport model (EMEP4UK). Annual mean concentrations of these pollutants were assigned to all 1,202,578 residential postcodes in England, which were classified by urban-rural status and socioeconomic deprivation based on the income and employment domains of the 2010 English Index of Multiple Deprivation for the Lower-level Super Output Area of residence. We used life table methods to estimate PM_2.5-attributable life years (LYs) lost in both relative and absolute terms.

RESULTS

Concentrations of the most particulate fractions, but not of nitrate PM_2.5 or ozone, were modestly higher in areas of greater socioeconomic deprivation. Relationships between pollution level and socioeconomic deprivation were non-linear and varied by urban-rural status. The pattern of PM_2.5 concentrations made only a small contribution to the steep socioeconomic gradient in LYs lost due to PM_2.5 per 10³ population, which primarily was driven by the steep socioeconomic gradient in underlying mortality rates. In rural areas, the absolute burden of air pollution-related LYs lost was lowest in the most deprived deciles.

CONCLUSIONS

Air pollution shows modest socioeconomic patterning at 5 km resolution in England, but absolute attributable mortality burdens are strongly related to area-level deprivation because of underlying mortality rates. Measures that cause a general reduction in background concentrations of air pollution may modestly help narrow socioeconomic differences in health.

Environmental Pollutants and Neurodevelopment: Review of Benefits From Closure of a Coal-Burning Power Plant in Tongliang, China

Background. Understanding preventable causes of neurodevelopmental disorders is a public health priority. Polycyclic aromatic hydrocarbons (PAH) from combustion of fossil fuel, lead, and mercury are among known neurodevelopmental toxicants. Method. For the first time, we comprehensively review the findings from a study by the Columbia Center for Children's Environmental Health and Chinese partners that followed 2 groups of mother-child pairs, one from 2002 and another from 2005, in Tongliang County, China. Pregnant mothers in the 2 cohorts experienced different exposure to PAH because a local coal-burning power plant was shut down in 2004. Investigators assessed change in prenatal PAH exposure, measured using a biomarker (benzo[a]pyrene [BaP]-DNA adducts in cord blood). Developmental quotients were measured using the Gesell Developmental Scales at age 2 and IQ was assessed using the Wechsler Intelligence Scale for Children at age 5. Biologic markers of preclinical response were measured in cord blood: methylation status of long interspersed nuclear elements (LINE1), an indicator of genomic stability, and brain-derived neurotrophic factor (BDNF), a neuronal growth promoter. Analyses accounted for co-exposure to lead and mercury. Results. BaP-DNA adducts were significantly inversely associated with Gesell Developmental Scales scores in the first cohort but not in the second cohort; and levels of BDNF and LINE1 methylation were higher in the second cohort. Conclusion. In this study, reduced exposure to PAH was associated with beneficial effects on neurodevelopment as well as molecular changes related to improved brain development and health. These benefits should encourage further efforts to limit exposure to these toxic pollutants.

Fatores de risco para mortalidade por doenças cardiovasculares associados à alta exposição ao tráfego veicular

RESUMO: Objetivo: Identificar áreas e fatores de risco para a mortalidade causada por doenças cardiovasculares (DC) associados à poluição do ar proveniente da alta exposição ao tráfego. Métodos: Estudo transversal da mortalidade por DC em 2.617 indivíduos de 45 a 85 anos residentes na zona urbana de Cuiabá e Várzea Grande, Mato Grosso, entre 2009 e 2011. Utilizou-se a proximidade residencial de até 150 metros de uma via de grande fluxo de veículos como proxy da alta exposição à poluição atmosférica proveniente do tráfego. A associação entre idade, sexo, renda e intensidade do trânsito com a exposição ao tráfego foi avaliada por meio de regressão logística múltipla. Foram realizadas análises estratificadas para observar a influência das estações do ano e dos grupos de causas. Utilizou-se modelo espacial de probabilidade de Bernoulli para identificação de áreas de risco. Resultados: Os principais fatores de risco para mortalidade por DC associados à alta exposição ao tráfego foram: residir em setores censitários com renda muito desigual (OR = 1,78; IC95% 1,36 - 2,33), trânsito intenso (OR = 1,20; IC95% 1,01 - 1,43) e sexo feminino (OR = 1,18; IC95% 1,01 - 1,38). O risco de mortalidade por DC aumenta cerca de 10% no período de seca. Foram identificadas nove áreas de risco. Conclusão: A alta exposição ao tráfego está associada à mortalidade por DC em Cuiabá e Várzea Grande. A desigualdade de renda, a intensidade do trânsito e o sexo feminino apresentaram-se como os principais determinantes dessa exposição, além da estação seca potencializá-la.

PM2.5 and Mortality in 207 US Cities: Modification by Temperature and City Characteristics

BACKGROUND

The reported estimated effects between long-term PM2.5 exposures and mortality vary spatially. We assessed whether community-level variables, including socioeconomic status indicators and temperature, modify this association.

METHODS

We used data from >35 million Medicare enrollees from 207 US cities (2000-2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites. We used a variation of a causal modeling approach and fitted city-specific Cox models, which we then pooled using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education and greenness, modify the long-term PM2.5-mortality association.

RESULTS

We found an association between long-term PM2.5 and survival (hazard ratio = 1.2; 95% confidence interval [CI]: 1.1, 1.3 per 10 μg/m increase in the annual PM2.5 average concentrations). We observed elevated estimates in the Southeastern, South and Northwestern US (hazard ratio = 1.9; 95% CI: 1.7, 2.2, and 1.4; 95% CI: 1.2, 1.7, and 1.4; 95% CI: 1.1, 1.9, respectively). We observed a higher association between long-term PM2.5 exposure and mortality in warmer cities. Furthermore, we observed increasing estimates with increasing obesity rates, %residents and families in poverty, %black residents and %population without a high school degree, and lower effects with increasing median household income and %white residents.

CONCLUSIONS

To the best of our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the long-term PM2.5-survival association. Our findings suggest that living in cities with high temperatures and low socio economic status (SES) is associated with higher effect estimates.

The modifying effect of socioeconomic status on the relationship between traffic, air pollution and respiratory health in elementary schoolchildren

The volume and type of traffic and exposure to air pollution have been found to be associated with respiratory health, but few studies have considered the interaction with socioeconomic status at the household level. We investigated the relationships of respiratory health related to traffic type, traffic volume, and air pollution, stratifying by socioeconomic status, based on household income and education, in 3591 schoolchildren in Windsor, Canada. Interquartile range changes in traffic exposure and pollutant levels were linked to respiratory symptoms and objective measures of lung function using generalised linear models for three levels of income and education. In 95% of the relationships among all cases, the odds ratios for reported respiratory symptoms (a decrease in measured lung function), based on an interquartile range change in traffic exposure or pollutant, were greater in the lower income/education groups than the higher, although the odds ratios were in most cases not significant. However, in up to 62% of the cases, the differences between high and low socioeconomic groups were statistically significant, thus indicating socioeconomic status (SES) as a significant effect modifier. Our findings indicate that children from lower socioeconomic households have a higher risk of specific respiratory health problems (chest congestion, wheezing) due to traffic volume and air pollution exposure.

Understanding Global Cancer Disparities: The Role of Social Determinants from System Dynamics Perspective

BACKGROUND

In 2012, almost 57% of all cancer cases and 65% of cancer deaths occurred in low-and middle-income countries. If the current trend continues, the burden of cancer will increase to 22 million new cases annually by 2030, with 81% of new cases and almost 88% of mortality occurring in less developed countries.

METHODS

A qualitative review of the literature was conducted. This included a systematic search of eight electronic databases namely, PubMed, Academic Search Premier, CINAHL, Applied Social Sciences Index, EMBASE, SCOPUS, Cochrane and PsycINFO. The reference list of articles retrieved were also thoroughly searched. Inclusion criteria were studies that addressed global health, cancer disparities and global or economic development.

RESULTS

Thirty-one articles were identified that met the eligibility criteria. Results were synthesized in the form of a system dynamics causal loop diagram or map which led to identification of eight major stocks or system variables. These included, children and adult population, overall population health, pollution, quality of healthcare delivery, quality of neighborhood and built environment, social and community cohesiveness, healthy and social norms and attitudes, and literacy level. Based on this, a dynamic hypothesis of global health cancer disparities was developed. The causal loop diagram showed the role of multiple interacting feedback mechanisms as explanations for trends in global health cancer disparities and the underlying consequences.

CONCLUSIONS

Addressing these determinants of health requires an effective dynamic approach to improving global cancer health. Application of a systems thinking methodological approach has the potential to provide new understanding to how global development trends in combination with global health efforts to improve population health could shift cancer disparities and burden associated with the disease.

Estimating the Baseline and Threshold for the Incidence of Diseases with Seasonal and Long-Term Trends

In epidemiology, it is very important to estimate the baseline incidence of infectious diseases. From this baseline, the epidemic threshold can be derived as a clue to recognize an excess incidence, i.e. to detect an epidemic by mathematical methods. Nevertheless, a problem is posed by the fact that the incidence may vary during the year, as a rule, in a season dependent manner. To model the incidence of a disease, some authors use seasonal trend models. For instance, Serfling applies the sine function with a phase shift and amplitude. A similar model based on the analysis of variance with kernel smoothing and Serfling's higher order models, i.e. models composed of multiple sine-cosine function pairs with a variably long period, will be presented below. Serfling's model uses a long-term linear trend, but the linearity may not be always acceptable. Therefore, a more complex, long-term trend estimation will also be addressed, using different smoothing methods. In addition, the issue of the time unit (mostly a week) used in describing the incidence is discussed.

Air pollution and mortality in São Paulo, Brazil: Effects of multiple pollutants and analysis of susceptible populations

Health impacts of air pollution may differ depending on sex, education, socioeconomic status (SES), location at time of death, and other factors. In São Paulo, Brazil, questions remain regarding roles of individual and community characteristics. We estimate susceptibility to air pollution based on individual characteristics, residential SES, and location at time of death (May 1996-December 2010). Exposures for particulate matter with an aerodynamic diameter ≤ 10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were estimated using ambient monitors. Time-stratified case-crossover analysis was used with individual-level health data. Increased risk of non-accidental, cardiovascular, and respiratory mortality were associated with all pollutants (P < 0.05), except O3 and cardiovascular mortality. For non-accidental mortality, effect estimates for those with > 11 years education were lower than estimates for those with 0 years education for NO2, SO2, and CO (1.66% (95% confidence interval: 0.23%, 3.08%); 1.51% (0.51%, 2.51%); and 2.82% (0.23%, 5.35%), respectively). PM10 cardiovascular mortality effects were (3.74% (0.044%, 7.30%)) lower for the high education group (> 11 years) compared with the no education group. Positive, significant associations between pollutants and mortality were observed for in-hospital deaths, but evidence of differences in air pollution-related mortality risk by location at time of death was not strong.

Short term effect of air pollution, noise and heat waves on preterm births in Madrid (Spain)

BACKGROUND

Preterm birth (PTB) refers to delivery before 37 weeks of gestation and represents the leading cause of early-life mortality and morbidity in developed countries. PTB can lead to serious infant health outcomes. The etiology of PTB remains uncertain, but epidemiologic studies have consistently shown elevated risks with different environmental variables as traffic-related air pollution (TRAP). The aim of the study was to evaluate with time series methodology the short-term effect of air pollutants, noise levels and ambient temperature on the number of births and preterm births occurred in Madrid City during the 2001-2009 period.

METHODS

A time-series analysis was performed to assess the short term impact of daily mean concentrations (µg/m(3)) of PM2.5 and PM10, O3 and NO2. Measurements of Acoustic Pollution in dB(A) analyzed were: Leqd, equivalent diurnal noise level and Leqn, equivalent nocturnal noise level. Maximum and Minimum daily temperature (°C), mean Humidity in the air (%) and Atmospheric Pressure (HPa), were included too. Linear trends, seasonality, as well as the autoregressive nature of the series itself were controlled. We added as covariate the day of the week too. Autoregressive over-dispersed Poisson regression models were performed and the environmental variables were included with short-term lags (from 0 to 7 days) in reference to the date of birth. Firstly, simple models for the total number of births and preterm births were done separately. In a second stage, a model for total births adjusted for preterm births was performed.

RESULTS

A total of 298,705 births were analyzed. The results of the final models were expressed in relative risks (RRs) for interquartile increase. We observed evidence of a short term effect at Lag 0, for the following environmental variables analyzed, PM2.5 (RR: 1.020; 95% CI:(1.008 1.032)) and O3 (RR: 1.012; 95% CI:(1.002 1.022)) concentrations and Leqd (RR: 1.139; 95% CI:( (1.124 1.154)) for the total number of births, and besides these, heat temperatures at Lag 1 (RR: 1.055; 95% CI:( (1.018 1.092)) on preterm births in Madrid City during the studied period. In the model adjusted for preterm births, similar RR was obtained for the same environmental variables.

CONCLUSIONS

Especially PM2.5, diurnal noise levels and O3 have a short-term impact on total births and heat temperatures on preterm births in Madrid City during the studied period. Our results suggest that, given the widespread exposure of the population to the environmental factors analyzed and the possible effects on long-term health associated to low birth weight. There is a clear need to minimize this exposure through the decrease of air pollution and noise levels and through the behavior modification of the mothers.

Nutritional Solutions to Reduce Risks of Negative Health Impacts of Air Pollution

Air pollution worldwide has been associated with cardiovascular and respiratory morbidity and mortality, particularly in urban settings with elevated concentrations of primary pollutants. Air pollution is a very complex mixture of primary and secondary gases and particles, and its potential to cause harm can depend on multiple factors—including physical and chemical characteristics of pollutants, which varies with fine-scale location (e.g., by proximity to local emission sources)—as well as local meteorology, topography, and population susceptibility. It has been hypothesized that the intake of anti-oxidant and anti-inflammatory nutrients may ameliorate various respiratory and cardiovascular effects of air pollution through reductions in oxidative stress and inflammation. To date, several studies have suggested that some harmful effects of air pollution may be modified by intake of essential micronutrients (such as B vitamins, and vitamins C, D, and E) and long-chain polyunsaturated fatty acids. Here, we review the existing literature related to the potential for nutrition to modify the health impacts of air pollution, and offer a framework for examining these interactions.

Health impact metrics for air pollution management strategies

Health impact assessments (HIAs) inform policy and decision making by providing information regarding future health concerns, and quantitative HIAs now are being used for local and urban-scale projects. HIA results can be expressed using a variety of metrics that differ in meaningful ways, and guidance is lacking with respect to best practices for the development and use of HIA metrics. This study reviews HIA metrics pertaining to air quality management and presents evaluative criteria for their selection and use. These are illustrated in a case study where PM2.5 concentrations are lowered from 10 to 8μg/m(3) in an urban area of 1.8 million people. Health impact functions are used to estimate the number of premature deaths, unscheduled hospitalizations and other morbidity outcomes. The most common metric in recent quantitative HIAs has been the number of cases of adverse outcomes avoided. Other metrics include time-based measures, e.g., disability-adjusted life years (DALYs), monetized impacts, functional-unit based measures, e.g., benefits per ton of emissions reduced, and other economic indicators, e.g., cost-benefit ratios. These metrics are evaluated by considering their comprehensiveness, the spatial and temporal resolution of the analysis, how equity considerations are facilitated, and the analysis and presentation of uncertainty. In the case study, the greatest number of avoided cases occurs for low severity morbidity outcomes, e.g., asthma exacerbations (n=28,000) and minor-restricted activity days (n=37,000); while DALYs and monetized impacts are driven by the severity, duration and value assigned to a relatively low number of premature deaths (n=190 to 230 per year). The selection of appropriate metrics depends on the problem context and boundaries, the severity of impacts, and community values regarding health. The number of avoided cases provides an estimate of the number of people affected, and monetized impacts facilitate additional economic analyses useful to policy analysis. DALYs are commonly used as an aggregate measure of health impacts and can be used to compare impacts across studies. Benefits per ton metrics may be appropriate when changes in emissions rates can be estimated. To address community concerns and HIA objectives, a combination of metrics is suggested.

Can the Air Pollution Index be used to communicate the health risks of air pollution?

The validity of using the Air Pollution Index (API) to assess health impacts of air pollution and potential modification by individual characteristics on air pollution effects remain uncertain. We applied distributed lag non-linear models (DLNMs) to assess associations of daily API, specific pollution indices for PM10, SO2, NO2 and the weighted combined API (APIw) with mortality during 2003-2011 in Guangzhou, China. An increase of 10 in API was associated with a 0.88% (95% confidence interval (CI): 0.50, 1.27%) increase of non-accidental mortality at lag 0-2 days. Harvesting effects appeared after 2 days' exposure. The effect estimate of API over lag 0-15 days was statistically significant and similar with those of pollutant-specific indices and APIw. Stronger associations between API and mortality were observed in the elderly, females and residents with low educational attainment. In conclusion, the API can be used to communicate health risks of air pollution.

Is there a Hispanic Health Paradox in Sensitivity to Air Pollution? Hospital Admissions for Asthma, Chronic Obstructive Pulmonary Disease and Congestive Heart Failure Associated with NO2 and PM2.5 in El Paso, TX, 2005-2010

STUDY OBJECTIVE

Linkages between pollution and morbidity have been observed in numerous studies. But race/ethnicity has been underemphasized as a modifier of that association, and few studies have tested for a Hispanic Health Paradox in sensitivity to air pollution.

METHODS

Daily asthma, chronic obstructive pulmonary disease (COPD) and congestive heart failure (CHF) hospital admissions in El Paso, Texas were studied in age groups and insurance groups. Daily PM2.5 and NO2 were calculated from pollution monitors and all models adjusted for apparent temperature and wind speed. Conditional logistic regression for the case-crossover design was used for a between-group comparison and for a within-group comparison for Hispanics.

RESULTS

Hispanics were at lower risk than non-Hispanic whites and non-Hispanics of other races for NO2-associated admissions, but at greater risk for PM2.5-associated admissions. While Hispanics were generally protected with regards to NO2, Hispanic children (vs. elderly) faced increased risk for asthma and uninsured Hispanics (vs. Private) faced increased risk for COPD admissions. While Hispanics were at increased risk of PM2.5-associated admissions, certain characteristics heightened their risks: being a Hispanic child (vs. Elderly) for asthma; being a Hispanic with Medicare (vs. Private) for asthma; and being a Hispanic with private insurance (vs. all other insurance types) for CHF. The main effect of pollution on admissions was more significant for asthma and CHF than for COPD, which had the fewest cases.

CONCLUSIONS

There was heterogeneity in sensitivity to air pollution based on social characteristics and moderate evidence for a Hispanic Health Paradox in sensitivity to NO2.

Traffic-related air pollution and sleep in the Boston Area Community Health Survey

Little is known about environmental determinants of sleep. We investigated the association between black carbon (BC), a marker of traffic-related air pollution, and sleep measures among participants of the Boston Area Community Health Survey. We also sought to assess the impact of sociodemographic factors, health conditions, and season on associations. Residential 24-h BC was estimated from a validated land-use regression model for 3821 participants and averaged over 1-6 months and 1 year. Sleep measures included questionnaire-assessed sleep duration, sleep latency, and sleep apnea. Linear and logistic regression models controlling for confounders estimated the association between sleep measures and BC. Effect modification was tested with interaction terms. Main effects were not observed between BC and sleep measures. However, in stratified models, males experienced 0.23 h less sleep (95% CI: -0.42, -0.03) and those with low SES 0.25 h less sleep (95% CI: -0.48, -0.01) per IQR increase in annual BC (0.21 μg/m(3)). In blacks, sleep duration increased with annual BC (β=0.34 per IQR; 95% CI: 0.12, 0.57). Similar findings were observed for short sleep (≤5 h). BC was not associated with sleep apnea or sleep latency, however, long-term exposure may be associated with shorter sleep duration, particularly in men and those with low SES, and longer sleep duration in blacks.

Neighbourhood Characteristics and Long-Term Air Pollution Levels Modify the Association between the Short-Term Nitrogen Dioxide Concentrations and All-Cause Mortality in Paris

Background

While a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO₂ ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO₂ and all-cause mortality in Paris (France).

Methods

A time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO₂ variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO₂ exposure. The data was estimated at the census block scale (n=866).

Results

The mean of the NO₂ concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95%CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95%CI=[1.41-4.90], p<0.001). Among these deprived census blocks, excess risk was even higher where long-term average NO₂ concentrations were above 55.8 μg/m³ (the top tercile of distribution): ER=4.84% (95%CI=[1.56;8.24], p for interaction=0.02).

Conclusion

Our results show that people living in census blocks characterized by low socioeconomic status are more vulnerable to air pollution episodes. There is also an indication that people living in these disadvantaged census blocks might experience even higher risk following short-term air pollution episodes, when they are also chronically exposed to higher NO₂ levels.

Disaggregating data on Asian American and Pacific Islander women to provide new insights on potential exposures to hazardous air pollutants in California

BACKGROUND

The Asian American and Pacific Islander (AAPI) population is heterogeneous and rapidly growing in the United States, with a high proportion concentrated in California. Although traditionally assumed to have lower rates of breast cancer than non-Hispanic white women, recent studies have suggested considerable variation in incidence by AAPI ethnic group, with rates in some exceeding those in non-Hispanic whites. The potential role of environmental toxicants has not been well explored and may provide insights into these patterns.

METHODS

We created an exposure potential index (EPI) score for 24 hazardous air pollutants modeled by the U.S. Environmental Protection Agency National-Scale Air Toxics Assessment considered to be mammary gland carcinogens, and compared values at the census tract level for "geographically concentrated" AAPI groups throughout the State. "Geographically concentrated" populations were defined as census tracts with at least 100 individuals from a specified racial/ethnic population as enumerated by the 2000 Census.

RESULTS

Although EPI scores differed little between census tracts with aggregated AAPI (mean EPI = 0.53) and non-Hispanic white women (mean EPI = 0.63), there was substantial variation between tracts for disaggregated AAPI groups, with notably higher EPI scores for tracts enumerated for Korean or Japanese women (mean EPI of 0.78 and 0.77, respectively) compared with other AAPI groups.

CONCLUSIONS

Our findings underscore the importance of disaggregating data for the heterogeneous AAPI population to identify differences in potential environmental exposures across groups.

IMPACT

Future cancer etiology studies should examine environmental exposure differences within and across groups for the diverse AAPI population.

The effects of outdoor air pollution on the respiratory health of Canadian children: A systematic review of epidemiological studies

BACKGROUND

Outdoor air pollution is a global problem with serious effects on human health, and children are considered to be highly susceptible to the effects of air pollution.

OBJECTIVE

To conduct a comprehensive and updated systematic review of the literature reporting the effects of outdoor air pollution on the respiratory health of children in Canada.

METHODS

Searches of four electronic databases between January 2004 and November 2014 were conducted to identify epidemiological studies evaluating the effect of exposure to outdoor air pollutants on respiratory symptoms, lung function measurements and the use of health services due to respiratory conditions in Canadian children. The selection process and quality assessment, using the Newcastle-Ottawa Scale, were conducted independently by two reviewers.

RESULTS

Twenty-seven studies that were heterogeneous with regard to study design, population, respiratory outcome and air pollution exposure were identified. Overall, the included studies reported adverse effects of outdoor air pollution at concentrations that were below Canadian and United States standards. Heterogeneous effects of air pollutants were reported according to city, sex, socioeconomic status and seasonality. The present review also describes trends in research related to the effect of air pollution on Canadian children over the past 25 years.

CONCLUSION

The present study reconfirms the adverse effects of outdoor air pollution on the respiratory health of children in Canada. It will help researchers, clinicians and environmental health authorities identify the available evidence of the adverse effect of outdoor air pollution, research gaps and the limitations for further research.

Associations between air pollution and socioeconomic characteristics, ethnicity and age profile of neighbourhoods in England and the Netherlands

Air pollution levels are generally believed to be higher in deprived areas but associations are complex especially between sensitive population subgroups. We explore air pollution inequalities at national, regional and city level in England and the Netherlands comparing particulate matter (PM10) and nitrogen dioxide (NO2) concentrations and publicly available population characteristics (deprivation, ethnicity, proportion of children and elderly). We saw higher concentrations in the most deprived 20% of neighbourhoods in England (1.5 μg/m(3) higher PM10 and 4.4 μg/m(3) NO2). Concentrations in both countries were higher in neighbourhoods with >20% non-White (England: 3.0 μg/m(3) higher PM10 and 10.1 μg/m(3) NO2; the Netherlands: 1.1 μg/m(3) higher PM10 and 4.5 μg/m(3) NO2) after adjustment for urbanisation and other variables. Associations for some areas differed from the national results. Air pollution inequalities were mainly an urban problem suggesting measures to reduce environmental air pollution inequality should include a focus on city transport.

Air quality and social deprivation in four French metropolitan areas--a localized spatio-temporal environmental inequality analysis

Several studies have documented that more deprived populations tend to live in areas characterized by higher levels of environmental pollution. Yet, time trends and geographic patterns of this disproportionate distribution of environmental burden remain poorly assessed, especially in Europe. We investigated the spatial and temporal relationship between ambient air nitrogen dioxide (NO2) concentrations and socioeconomic and demographic data in four French metropolitan areas (Lille in the North, Lyon in the center, Marseille in the South, and Paris) during two different time periods. The geographical unit used was the census block. The dependent variable was the NO2 annual average concentration (μg/m(3)) per census block, and the explanatory variables were a neighborhood deprivation index and socioeconomic and demographic data derived from the national census. Generalized additive models were used to account for spatial autocorrelation. We found that the strength and direction of the association between deprivation and NO2 estimates varied between cities. In Paris, census blocks with the higher social categories are exposed to higher mean concentrations of NO2. However, in Lille and Marseille, the most deprived census blocks are the most exposed to NO2. In Lyon, the census blocks in the middle social categories were more likely to have higher concentrations than in the lower social categories. Despite a general reduction in NO2 concentrations over the study period in the four metropolitan areas, we found contrasting results in the temporal trend of environmental inequalities. There is clear evidence of city-specific spatial and temporal environmental inequalities that relate to the historical socioeconomic make-up of the cities and its evolution. Hence, general statements about environmental and social inequalities can be made.

Air quality and social deprivation in four French metropolitan areas--a localized spatio-temporal environmental inequality analysis

Several studies have documented that more deprived populations tend to live in areas characterized by higher levels of environmental pollution. Yet, time trends and geographic patterns of this disproportionate distribution of environmental burden remain poorly assessed, especially in Europe. We investigated the spatial and temporal relationship between ambient air nitrogen dioxide (NO2) concentrations and socioeconomic and demographic data in four French metropolitan areas (Lille in the North, Lyon in the center, Marseille in the South, and Paris) during two different time periods. The geographical unit used was the census block. The dependent variable was the NO2 annual average concentration (μg/m(3)) per census block, and the explanatory variables were a neighborhood deprivation index and socioeconomic and demographic data derived from the national census. Generalized additive models were used to account for spatial autocorrelation. We found that the strength and direction of the association between deprivation and NO2 estimates varied between cities. In Paris, census blocks with the higher social categories are exposed to higher mean concentrations of NO2. However, in Lille and Marseille, the most deprived census blocks are the most exposed to NO2. In Lyon, the census blocks in the middle social categories were more likely to have higher concentrations than in the lower social categories. Despite a general reduction in NO2 concentrations over the study period in the four metropolitan areas, we found contrasting results in the temporal trend of environmental inequalities. There is clear evidence of city-specific spatial and temporal environmental inequalities that relate to the historical socioeconomic make-up of the cities and its evolution. Hence, general statements about environmental and social inequalities can be made.

Long-term exposure to outdoor air pollution and the incidence of chronic obstructive pulmonary disease in a national English cohort

Objectives

The role of outdoor air pollution in the incidence of chronic obstructive pulmonary disease (COPD) remains unclear. We investigated this question using a large, nationally representative cohort based on primary care records linked to hospital admissions.

Methods

A cohort of 812 063 patients aged 40–89 years registered with 205 English general practices in 2002 without a COPD diagnosis was followed from 2003 to 2007. First COPD diagnoses recorded either by a general practitioner (GP) or on admission to hospital were identified. Annual average concentrations in 2002 for particulate matter with an aerodynamic diameter <10 µm (PM₁₀) and <2.5 µm (PM_2.5), nitrogen dioxide (NO₂), ozone and sulfur dioxide (SO₂) at 1 km² resolution were estimated from emission-based dispersion models. Hazard ratios (HRs) per interquartile range change were estimated from Cox models adjusting for age, sex, smoking, body mass index and area-level deprivation.

Results

16 034 participants (1.92%) received a COPD diagnosis from their GP and 2910 participants (0.35%) were admitted to hospital for COPD. After adjustment, HRs for GP recorded COPD and PM₁₀, PM_2.5 and NO₂ were close to unity, positive for SO₂ (HR=1.07 (95% CI 1.03 to 1.11) per 2.2 µg/m³) and negative for ozone (HR=0.94 (0.89 to 1.00) per 3 µg/m³). For admissions HRs for PM_2.5 and NO₂ remained positive (HRs=1.05 (0.98 to 1.13) and 1.06 (0.98 to 1.15) per 1.9 µg/m³ and 10.7 µg/m³, respectively).

Conclusions

This large population-based cohort study found limited, inconclusive evidence for associations between air pollution and COPD incidence. Further work, utilising improved estimates of air pollution over time and enhanced socioeconomic indicators, is required to clarify the association between air pollution and COPD incidence.

Quantifying the contribution of ambient and indoor-generated fine particles to indoor air in residential environments

Indoor fine particles (FPs) are a combination of ambient particles that have infiltrated indoors, and particles that have been generated indoors from activities such as cooking. The objective of this paper was to estimate the infiltration factor (Finf ) and the ambient/non-ambient components of indoor FPs. To do this, continuous measurements were collected indoors and outdoors for seven consecutive days in 50 non-smoking homes in Halifax, Nova Scotia in both summer and winter using DustTrak (TSI Inc) photometers. Additionally, indoor and outdoor gravimetric measurements were made for each 24-h period in each home, using Harvard impactors (HI). A computerized algorithm was developed to remove (censor) peaks due to indoor sources. The censored indoor/outdoor ratio was then used to estimate daily Finfs and to determine the ambient and non-ambient components of total indoor concentrations. Finf estimates in Halifax (daily summer median = 0.80; daily winter median = 0.55) were higher than have been reported in other parts of Canada. In both winter and summer, the majority of FP was of ambient origin (daily winter median = 59%; daily summer median = 84%). Predictors of the non-ambient component included various cooking variables, combustion sources, relative humidity, and factors influencing ventilation. This work highlights the fact that regional factors can influence the contribution of ambient particles to indoor residential concentrations.

PRACTICAL IMPLICATIONS

Ambient and non-ambient particles have different risk management approaches, composition, and likely toxicity. Therefore, a better understanding of their contribution to the indoor environment is important to manage the health risks associated with fine particles (FPs) effectively. As well, a better understanding of the factors Finf can help improve exposure assessment and contribute to reduced exposure misclassification in epidemiologic studies.

Cumulative exposure to particulate matter air pollution and long-term post-myocardial infarction outcomes

INTRODUCTION

Chronic environmental exposure to particulate matter <2.5μm in diameter (PM2.5) has been associated with cardiovascular disease; however, the effect of air pollution on myocardial infarction (MI) survivors is not clear. We studied the association of chronic exposure to PM2.5 with death and recurrent cardiovascular events in MI survivors.

METHODS

Consecutive patients aged ≤65years admitted to all medical centers in central Israel after first-MI in 1992-1993 were followed through 2005 for cardiovascular events and 2011 for survival. Data on sociodemographic and prognostic factors were collected at baseline and during follow-up. Residential exposure to PM2.5 was estimated for each patient based on data recorded at air quality monitoring stations. Cox and Andersen-Gill proportional hazards models were used to study the pollution-outcome association.

RESULTS

Among the 1120 patients, 469 (41.9%) died and 541 (48.3%) experienced one or more recurrent cardiovascular event. The adjusted hazard ratios associated with a 10μg/m(3) increase in PM2.5 exposure were 1.3 (95% CI 0.8-2.1) for death and 1.5 (95% CI 1.1-1.9) for multiple recurrences of cardiovascular events (MI, heart failure and stroke).

CONCLUSION

When adjustment for socio-demographic factors is performed, cumulative chronic exposure to PM2.5 is positively associated with recurrence of cardiovascular events in patients after a first MI.

Race, socioeconomic status, and air pollution exposure in North Carolina

BACKGROUND

Although studies suggest that exposure to pollutants is associated with race/ethnicity and socio-economic status (SES), many studies are limited to the geographic regions where monitoring stations are located.

OBJECTIVES

This study uses modeled predictive surfaces to examine the relationship between air pollution exposure, race/ethnicity, and measures of SES across the entire State of North Carolina.

METHODS

The daily predictions of particulate matter <2.5 µm in aerodynamic diameter (PM2.5) and ozone (O3) were determined using a spatial model that fused data from two sources: point air monitoring data and gridded numerical output. These daily predicted pollution levels for 2002 were linked with Census data. We examine the relationship between the census-tract level predicted concentration measures, SES, and racial composition.

RESULTS

SES and race/ethnicity were related to predicted concentrations of both PM2.5 and O3 for census tracts in North Carolina. Lower SES and higher proportion minority population were associated with higher levels of PM2.5. An interquartile range (IQR) increase of median household income reduced the predicted average PM2.5 level by 0.10 µg/m3. The opposite relationship was true for O3. An IQR increase of median household income increased the predicted average O3 measure by 0.11 ppb.

CONCLUSIONS

The analyses demonstrate that SES and race/ethnicity are related to predicted estimates of PM2.5 and O3 for census tracts in North Carolina. These findings offer a baseline for future exposure modeling work involving SES and air pollution for the entire state and not just among the populations residing near monitoring networks.

Socioeconomic status and exposure to outdoor NO2 and benzene in the Asturias INMA birth cohort, Spain

Background

It is commonly assumed that low socioeconomic levels are associated with greater exposure to pollution, but this is not necessarily valid. Our goal was to examine how individual socioeconomic characteristics are associated with exposure levels in a Spanish region included in the INfancia y Medio Ambiente (INMA) cohort.

Methods

The study population comprised 430 pregnant women from the Asturias INMA cohort. Air pollution exposure was estimated using land-use regression techniques. Information about the participants’ lifestyle and socioeconomic variables was collected through questionnaires. In multivariate analysis, the levels of NO₂ and benzene assigned to each woman were considered as dependent variables. Other variables included in the models were residential zone, age, education, parity, smoking, season, working status during pregnancy and social class.

Results

The average NO₂ level was 23.60 (SD=6.50) μg/m³. For benzene, the mean value was 2.31 (SD=1.32) μg/m³. We found no association of any pollutant with education. We observed an association between social class and benzene levels. Social classes I and II had the highest levels. The analysed socioeconomic and lifestyle variables accounted for little variability in air pollution in the models; this variability was explained mainly by residential zone (adjusted R²: 0.27 for NO₂; 0.09 for benzene).

Conclusions

Education and social class were not clearly associated with pollution. Administrations should monitor the environment of residential areas regardless of the socioeconomic level, and they should increase the distances between housing and polluting sources to prevent settlements at distances that are harmful to health.

Characteristics and popular topics of latest researches into the effects of air particulate matter on cardiovascular system by bibliometric analysis

In recent years, many epidemiological and toxicological studies have investigated the adverse effects of air particulate matter (PM) on the cardiovascular system. However, it is difficult for the researchers to have a timely and effective overall command of the latest characteristics and popular topics in such a wide field. Different from the previous reviews, in which the research characteristics and trends are empirically concluded by experts, we try to have a comprehensive evaluation of the above topics for the first time by bibliometric analysis, a quantitative tool in information exploration. This study aims to introduce the bibliometric method into the field of PM and cardiovascular system. The articles were selected by searching PubMed/MEDLINE (from 2007 to 2012) using Medical Subject Headings (MeSH) terms "particulate matter" and "cardiovascular system". A total of 935 eligible articles and 1895 MeSH terms were retrieved and processed by the software Thomson Data Analyzer (TDA). The bibliographic information and the MeSH terms of these articles were classified and analyzed to summarize the research characteristics. The top 200 high-frequency MeSH terms (the cumulative frequency percentage was 74.2%) were clustered for popular-topic conclusion. We summarized the characteristics of published articles, of researcher collaborations and of the contents. Ten clusters of MeSH terms are presented. Six popular topics are concluded and elaborated for reference. Our study presents an overview of the characteristics and popular topics in the field of PM and cardiovascular system in the past five years by bibliometric tools, which may provide a new perspective for future researchers.

Cluster analysis of social and environment inequalities of infant mortality. A spatial study in small areas revealed by local disease mapping in France

Mapping spatial distributions of disease occurrence can serve as a useful tool for identifying exposures of public health concern. Infant mortality is an important indicator of the health status of a population. Recent literature suggests that neighborhood deprivation status can modify the effect of air pollution on preterm delivery, a known risk factor for infant mortality. We investigated the effect of neighborhood social deprivation on the association between exposure to ambient air NO2 and infant mortality in the Lille and Lyon metropolitan areas, north and center of France, respectively, between 2002 and 2009. We conducted an ecological study using a neighborhood deprivation index estimated at the French census block from the 2006 census data. Infant mortality data were collected from local councils and geocoded using the address of residence. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk. The average death rate was 4.2‰ and 4.6‰ live births for the Lille and Lyon metropolitan areas during the period. We found evidence of statistically significant precise clusters of elevated infant mortality for Lille and an east-west gradient of infant mortality risk for Lyon. Exposure to NO2 did not explain the spatial relationship. The Lille MA, socioeconomic deprivation index explained the spatial variation observed. These techniques provide evidence of clusters of significantly elevated infant mortality risk in relation with the neighborhood socioeconomic status. This method could be used for public policy management to determine priority areas for interventions. Moreover, taking into account the relationship between social and environmental exposure may help identify areas with cumulative inequalities.