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

The mediating role of air pollutants in the association between education and lung function among the elderly, the HAPIEE study

BACKGROUND

Chronic exposure to air pollutants harms human health, and at a geographical level, concentrations of air pollutants are often associated with socioeconomic disadvantage.

OBJECTIVES

The aim of this study was to investigate the effects of educational attainment and air pollution on lung function in older adults, and whether air pollution may mediate the effect of education.

METHODS

The study included 6381 individuals (mean age 58.24 ± 7.14 years) who participated in the Czech HAPPIE (Health, Alcohol, and Psychosocial Factors in Eastern Europe) study. Participants' residential addresses were linked to air pollution data, including mean exposures to PM10 (particulate matter of aerodynamic diameter below 10 μm) and NO2 (nitrogen dioxide). We used path analysis to link educational attainment and air pollutants to a standardized measure of the Forced Expiratory Volume in the first second (FEV1).

RESULTS

Higher levels of participants' education were associated with lower exposures to PM10 and NO2. Individuals with tertiary education had higher standardized FEV1 than individuals with primary education (88 % vs 95 %). Path analysis revealed a direct positive effect of education on FEV1, while about 12 % of the relationship between education and lung function was mediated by PM10 and NO2. CONCLUSIONS: Education (typically completed at young ages) appeared to have a protective effect on lung function later in life, and a small part of this effect was mediated by air pollution.

When Space and Time Matter in Environmental Injustice: A Bayesian Analysis of the Association between Socio-economic Disadvantage and Air Pollution in Greater Mexico City

Environmental injustice refers to the unequal burden of pollutants on groups with lower socioeconomic status. An increasing number of studies have identified associations between high levels of pollution and socioeconomic disadvantage. However, few studies have controlled adequately for spatio-temporal variations in pollution. This study uses a Bayesian approach to explore the association between socioeconomic disadvantage and pollution in Mexico City Metropolitan Area. We quantify the association of socioeconomic disadvantage with PM10 and ozone and evaluate the impact of accounting for spatio-temporal structure of the pollution data. We find a significant positive association between socio-economic disadvantage and pollution for levels of PM10, but not ozone. The inclusion of the spatio-temporal element in the modeling results in improved weaker estimates of this association but this does not alter results substantially. These findings confirm the robustness of previous studies that found signs of environmental injustice where spatio-temporal variations have not been explicitly considered, confirming that targeted policies to reduce pollution in socio-economically disadvantaged areas are required.

Environmental and social inequities in continental France: an analysis of exposure to heat, air pollution, and lack of vegetation

BACKGROUND

Cumulative environmental exposures and social deprivation increase health vulnerability and limit the capacity of populations to adapt to climate change.

OBJECTIVE

Our study aimed at providing a fine-scale characterization of exposure to heat, air pollution, and lack of vegetation in continental France between 2000 and 2018, describing spatiotemporal trends and environmental hotspots (i.e., areas that cumulate the highest levels of overexposure), and exploring any associations with social deprivation.

METHODS

The European (EDI) and French (FDep) social deprivation indices, the normalized difference vegetation index, daily ambient temperatures, particulate matter (PM2.5 and PM10), nitrogen dioxide, and ozone (O3) concentrations were estimated for 48,185 French census districts. Reference values were chosen to characterize (over-)exposure. Hotspots were defined as the areas cumulating the highest overexposure to temperature, air pollution, and lack of vegetation. Associations between heat overexposure or hotspots and social deprivation were assessed using logistic regressions.

RESULTS

Overexposure to heat was higher in 2015-2018 compared with 2000-2014. Exposure to all air pollutants except for O3 decreased during the study period. In 2018, more than 79% of the urban census districts exceeded the 2021 WHO air quality guidelines. The evolution of vegetation density between 2000 and 2018 was heterogeneous across continental France. In urban areas, the most deprived census districts were at a higher risk of being hotspots (odds ratio (OR): 10.86, 95% CI: 9.87-11.98 using EDI and OR: 1.07, 95% CI: 1.04-1.11 using FDep).

IMPACT STATEMENT

We studied cumulative environmental exposures and social deprivation in French census districts. The 2015-2018 period showed the highest overexposure to heat between 2000 and 2018. In 2018, the air quality did not meet the 2021 WHO guidelines in most census districts and 8.6 million people lived in environmental hotspots. Highly socially deprived urban areas had a higher risk of being in a hotspot. This study proposes for the first time, a methodology to identify hotspots of exposure to heat, air pollution, and lack of vegetation and their associations with social deprivation at a national level.

Inequalities in Environmental Cancer Risk and Carcinogen Exposures: A Scoping Review

Background: Cancer is the leading cause of death in Canada and a major cause of death worldwide. Environmental exposure to carcinogens and environments that may relate to health behaviors are important to examine as they can be modified to lower cancer risks. Built environments include aspects such as transit infrastructure, greenspace, food and tobacco environments, or land use, which may impact how people move, exercise, eat, and live. While environments may play a role in overall cancer risk, exposure to carcinogens or healthier environments is not equitably spread across space. Exposures to carcinogens commonly concentrate among socially and/or economically disadvantaged populations. While many studies have examined inequalities in exposure or cancer risk, this has commonly been for one exposure. Methods: This scoping review collected and synthesized research that examines inequities in carcinogenic environments and exposures. Results: This scoping review found that neighborhoods with higher proportions of low-income residents, racialized people, or same-sex couples had higher exposures to carcinogens and environments that may influence cancer risk. There are currently four main themes in research studying inequitable exposures: air pollution and hazardous substances, tobacco access, food access, and other aspects of the built environment, with most research still focusing on air pollution. Conclusions: More work is needed to understand how exposures to these four areas intersect with other factors to reduce inequities in exposures to support longer-term goals toward cancer prevention.

Disparities in ambient nitrogen dioxide pollution in the United States

Average ambient concentrations of nitrogen dioxide (NO2), an important air pollutant, have declined in the United States since the enactment of the Clean Air Act. Despite evidence that NO2 disproportionately affects racial/ethnic minority groups, it remains unclear what drives the exposure disparities and how they have changed over time. Here, we provide evidence by integrating high-resolution (1 km × 1 km) ground-level NO2 estimates, sociodemographic information, and source-specific emission intensity and location for 217,740 block groups across the contiguous United States from 2000 to 2016. We show that racial/ethnic minorities are disproportionately exposed to higher levels of NO2 pollution compared with Whites across the United States and within major metropolitan areas. These inequities persisted over time and have worsened in many cases, despite a significant decrease in the national average NO2 concentration over the 17-y study period. Overall, traffic contributes the largest fraction of NO2 disparity. Contributions of other emission sources to exposure disparities vary by location. Our analyses offer insights into policies aimed at reducing air pollution exposure disparities among races/ethnicities and locations.

Socio-demographic characteristics and inequality in exposure to PM2.5: A case study in the Sichuan basin, China

The Chengyu Metropolitan Area (CYMA), located in the Sichuan Basin, is an unevenly developed region with high PM_2.5 concentrations and a population of approximately 100 million. Although exposure inequality in air pollution has received increasing concern, no related research has been carried out in the CYMA to date. In this work, we used the concentration index to assess inequality of PM_2.5 population-weighted exposure in the CYMA among different subgroups, including age, education, gender, occupation and GDP per capita in the city of residence. Our findings revealed that the non-disadvantaged subgroups (people aged 15-64, people with senior and higher education, people with high-income occupations and residents of cities with high GDP per capita) had a higher PM_2.5 exposure in the CYMA, with the concentration indices of -0.03 (95% CI: 0.064, -0.001), -0.14 (95% CI: 0.221, -0.059), -0.15 (95% CI: 0.238, -0.056) and -0.27 (95% CI: 0.556, 0.012), opposite to previous studies in developed countries such as the United States and France. In addition, exposure differences among cities were much larger than those among populations in the CYMA. These findings may benefit the government in identifying disproportionately exposed subgroups in developing regions, and suggest that related measures should initially be carried out for cities exposed to high PM_2.5 concentrations rather than for populations exposed to high PM_2.5 concentrations.

Pathways to Environmental Inequality: How Urban Traffic Noise Annoyance Varies across Socioeconomic Subgroups

The article investigates how socioeconomic background affects noise annoyance caused by residential road traffic in urban areas. It is argued that the effects of socioeconomic variables (migration background, education, and income) on noise annoyance tend to be underestimated because these effects are mainly indirect. We specify three indirect pathways. (1) A "noise exposure path" assumes that less privileged households are exposed to a higher level of noise and therefore experience stronger annoyance. (2) A "housing attributes path" argues that less privileged households can shield themselves less effectively from noise due to unfavorable housing conditions and that this contributes to annoyance. (3) Conversely, an "environmental susceptibility path" proposes that less privileged people are less concerned about the environment and have a lower noise sensitivity, and that this reduces their noise annoyance. Our analyses rest on a study carried out in four European cities (Mainz and Hanover in Germany, Bern and Zurich in Switzerland), and the results support the empirical validity of the three indirect pathways.

Neighborhood characteristics as confounders and effect modifiers for the association between air pollution exposure and subjective cognitive functioning

BACKGROUND

Air pollution has been associated with cognitive function in the elderly. Previous studies have not evaluated the simultaneous effect of neighborhood-level socioeconomic status (N-SES), which can be an essential source of bias.

OBJECTIVES

We explored N-SES as a confounder and effect modifier in a cross-sectional study of air pollution and subjective cognitive function.

METHODS

We included 12,058 participants age 50+ years from the Emory Healthy Aging Study in Metro Atlanta using the Cognitive Function Instrument (CFI) score as our outcome, with higher scores representing worse subjective cognitive function. We estimated 9-year average ambient carbon monoxide (CO), nitrogen oxides (NOx), and fine particulate matter (PM2.5) concentrations at residential addresses using a fusion of dispersion and chemical transport models. We collected census-tract level N-SES indicators and created two composite measures via principal component analysis and k-means clustering. Associations between pollutants and CFI and effect modification by N-SES were estimated via linear regression models adjusted for age, education, race and N-SES.

RESULTS

N-SES confounded the association between air pollution and CFI, independent of individual characteristics. We found significant effect modifications by N-SES for the association between air pollution and CFI (p-values<0.001) suggesting that effects of air pollution differ depending on N-SES. Participants living in areas with low N-SES were most vulnerable to air pollution. In the lowest N-SES urban areas, interquartile range (IQR) increases in CO, NOx, and PM2.5 were associated with 5.4% (95%-confidence interval, -0.2,11.3), 4.9% (-0.4,10.4), and 9.8% (2.2,18.0) changes in CFI, respectively. In lowest N-SES suburban areas, IQR increases in CO, NOx, and PM2.5 were associated with higher changes in CFI, namely 13.0% (0.9,26.5), 13.0% (-0.1,27.8), and 17.3% (2.5,34.2), respectively.

DISCUSSION

N-SES is an important confounder and effect modifier in our study. This finding could have implications for studying health effects of air pollution and identifying susceptible populations.

Does the environmental inequality matter? A literature review

The environmental inequality theory reveals that the risk of environmental pollution exposure varies among regions and groups and that particular groups face a higher threat of environmental pollution. In recent years, studies on the environmental inequality issue in developed countries have been increasing, while related literature on developing countries is very scarce. It has been found that some factors, such as race and economic status, have a close relationship with the risk of environmental pollution exposure faced by individuals. For the first time, this paper provides an extensive review of existing theoretical and empirical studies on environmental inequality. We review, in detail, the evolution of the environmental inequality theory, including the definition and measurement of environmental inequality. Further, we provide a systematic refresher on the main performance of environmental inequality, including health, education, labor productivity, and real estate prices. We also identify several causes of environmental inequality, such as ethnic differences, economic status, human capital, and household registration systems. Finally, we discuss prospects for the future research on this issue.

Ambient Air Pollution and Socioeconomic Status in China

BACKGROUND

Air pollution disparities by socioeconomic status (SES) are well documented for the United States, with most literature indicating an inverse relationship (i.e., higher concentrations for lower-SES populations). Few studies exist for China, a country accounting for 26% of global premature deaths from ambient air pollution.

OBJECTIVE

Our objective was to test the relationship between ambient air pollution exposures and SES in China.

METHODS

We combined estimated year 2015 annual-average ambient levels of nitrogen dioxide (NO 2 ) and fine particulate matter [PM ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 )] with national demographic information. Pollution estimates were derived from a national empirical model for China at 1 -km spatial resolution; demographic estimates were derived from national gridded gross national product (GDP) per capita at 1 -km resolution, and (separately) a national representative sample of 21,095 individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2015 cohort. Our use of global data on population density and cohort data on where people live helped avoid the spatial imprecision found in publicly available census data for China. We quantified air pollution disparities among individual's rural-to-urban migration status; SES factors (education, occupation, and income); and minority status. We compared results using three approaches to SES measurement: individual SES score, community-averaged SES score, and gridded GDP per capita.

RESULTS

Ambient NO 2 and PM 2.5 levels were higher for higher-SES populations than for lower-SES population, higher for long-standing urban residents than for rural-to-urban migrant populations, and higher for the majority ethnic group (Han) than for the average across nine minority groups. For the three SES measurements (individual SES score, community-averaged SES score, gridded GDP per capita), a 1-interquartile range higher SES corresponded to higher concentrations of 6 - 9   μ g / m 3 NO 2 and 3 - 6   μ g / m 3 PM 2.5 ; average concentrations for the highest and lowest 20th percentile of SES differed by 41-89% for NO 2 and 12-25% for PM 2.5 . This pattern held in rural and urban locations, across geographic regions, across a wide range of spatial resolution, and for modeled vs. measured pollution concentrations.

CONCLUSIONS

Multiple analyses here reveal that in China, ambient NO 2 and PM 2.5 concentrations are higher for high-SES than for low-SES individuals; these results are robust to multiple sensitivity analyses. Our findings are consistent with the idea that in China's current industrialization and urbanization stage, economic development is correlated with both SES and air pollution. To our knowledge, our study provides the most comprehensive picture to date of ambient air pollution disparities in China; the results differ dramatically from results and from theories to explain conditions in the United States. https://doi.org/10.1289/EHP9872.

Association of neighbourhood disadvantage and individual socioeconomic position with all-cause mortality: a longitudinal multicohort analysis

BACKGROUND

Few studies have examined the interactions between individual socioeconomic position and neighbourhood deprivation and the findings so far are heterogeneous. Using a large sample of diverse cohorts, we investigated the interaction effect of neighbourhood socioeconomic deprivation and individual socioeconomic position, assessed using education, on mortality.

METHODS

We did a longitudinal multicohort analysis that included six cohort studies participating in the European LIFEPATH consortium: the CoLaus (Lausanne, Switzerland), E3N (France), EPIC-Turin (Turin, Italy), EPIPorto (Porto, Portugal), Melbourne Collaborative Cohort Study (Melbourne, VIC, Australia), and Whitehall II (London, UK) cohorts. All participants with data on mortality, educational attainment, and neighbourhood deprivation were included in the present study. The data sources were the databases of each cohort study. Poisson regression was used to estimate the mortality rates and associations (relative risk, 95% CIs) with neighbourhood deprivation (Q1 being least deprived to Q5 being the most deprived). Baseline educational attainment was used as an indicator of individual socioeconomic position. Estimates were combined using pooled analysis and the relative excess risk due to the interaction was computed to identify additive interactions.

FINDINGS

The cohorts comprised a total population of 168 801 individuals. The recruitment dates were 2003-06 for CoLaus, 1989-91 for E3N, 1992-98 for EPIC-Turin, 1999-2003 for EPIPorto, 1990-94 for MCCS, and 1991-94 for Whitehall II. We use baseline data only and mortality data obtained using record linkage. Age-adjusted mortality rates were higher among participants residing in more deprived neighbourhoods than those in the least deprived neighbourhoods (Q1 least deprived neighbourhoods, 369·7 per 100 000 person-years [95% CI 356·4-383·2] vs Q5-most deprived neighbourhoods 445·7 per 100 000 person-years [430·2-461·7]), but the magnitude of the association varied according to educational attainment (relative excess risk due to interaction=0·18, 95% CI 0·08-0·28). The relative risk for Q5 versus Q1 was 1·31 (1·23-1·40) among individuals with primary education or less, but less pronounced among those with secondary education (1·12; 1·04-1·21) and tertiary education (1·16; 1·07-1·27). Associations remained after adjustment for individual-level factors, such as smoking, physical activity, and alcohol intake, among others.

INTERPRETATION

Our study suggests that the detrimental health effect of living in disadvantaged neighbourhoods is more pronounced among individuals with low education attainment, amplifying social inequalities in health. This finding is relevant to policies aimed at reducing health inequalities, suggesting that these issues should be addressed at both the individual level and the community level.

FUNDING

The European Commission, European Regional Development Fund, the Portugese Foundation for Science and Technology.

Annoyance due to residential road traffic and aircraft noise: Empirical evidence from two European cities

Based on a study in two European cities, Mainz in Germany and Zurich in Switzerland, the article investigates both acoustical and non-acoustical factors affecting indoor annoyance due to residential road traffic and aircraft noise. We specifically focus on three factors: (1) the role of windows as a feature of the building where people live; (2) the role of individual environmental concern as a general attitude; and (3) the role of household income as an indicator of socioeconomic resources. Empirical results show that closed windows in general and closed high-quality windows in particular are an important barrier against outdoor road traffic and aircraft noise, as well as a helpful subjective coping tool against corresponding annoyances. Environmental concern, too, proves to be a significant predictor of noise annoyance. Environmentally highly concerned people articulate feelings of annoyance more often than environmentally less concerned ones. As expected income is negatively related to road traffic noise annoyance. However, we find a positive association of income with annoyance from aircraft noise. Although objective exposure to aircraft noise is lower for high-income households, they feel stronger annoyed by noise from airplanes. Income shows various indirect effects on noise annoyance. A comparative analysis of road traffic and aircraft noise annoyance yields similarities, but also remarkable differences in terms of their influence factors.

Does air pollution contribute to urban-rural disparity in male lung cancer diseases in China?

It remains unknown whether exposure to ambient air pollution can be a mediator linking socioeconomic indicator to health outcome. The present study aims to examine the mediation effect of PM2.5 air pollution on the association between urban-rural division and the incidence (mortality) rate of male lung cancer. We performed a nationwide analysis in 353 counties (districts) of China between 2006 and 2015. A structural equation model was developed to determine the mediation effect of exposure to PM2.5. We also tested whether the findings of the mediation effect of exposure to PM2.5 are sensitive to the controls of smoking factors and additional air pollutant, and PM2.5 exposures with different lag structures. According to the results, we found that exposure to PM2.5 significantly mediated the association between urban-rural division and the incidence rate of male lung cancer. Specifically, there were significant associations between urban-rural division, exposure to PM2.5, and the incidence rate of male lung cancer, with PM2.5 exposure accounting for 29.80% of total urban-rural difference in incidence rates of male lung cancer. A similar pattern of results was observed for the mortality rate of male lung cancer. That is, there was a significant mediation effect by PM2.5 on the association of the mortality rate with urban-rural division. The findings of exposure to PM2.5 as a mediator were robust in the three sensitivity analyses. In conclusion, urban-rural difference in exposures to PM2.5 may be a potential factor that contributes to urban-rural disparity in male lung cancer diseases in China. The findings inform that air pollution management and control may be effective measures to alleviate the great difference in male lung cancer diseases between urban and rural areas in China.

Environmental inequity in hilly neighborhood using multi-source data from a health promotion view

The study focused on the justice of residents' opportunity to engage in healthy behavior under different environments is not vast, especially in a hilly dwelling environment. Therefore, this paper investigates environmental inequalities in a hilly urban environment in the context of the booming real estate market in China, comprised of health promotion-related elements, namely, built environment, physical activity facilities, street infrastructure, green spaces, and environmental perceptions. The multi-source data are used to calculate environmental attributes and the socioeconomic status of communities. We take the central districts of Dalian city as the research area and measure environmental equity across different socioeconomic residential areas using the Kruskal-Wallis one-way analysis of variance. The results reveal the spatial disparities in physical activity facilities, street greening, and positive perceptions between different communities. However, green injustice is mitigated in the hilly neighborhoods when we consider only ground-level greenness. This paper studies environmental justice by taking a health-enhancing view, and the results of this study can provide guidance on hilly urban development for government leaders and planners.

A Vector Field Approach to Estimating Environmental Exposure Using Human Activity Data

Environmental exposure of people plays an important role in assessing the quality of human life. The most existing methods that estimate the environmental exposure either focus on the individual level or do not consider human mobility. This paper adopts a vector field generated from the observed locations of human activities to model the environmental exposure at the population level. An improved vector-field-generation method was developed by considering people’s decision-making factors, and we proposed two indicators, i.e., the total exposure indicator (TEI) and the average exposure indicator (AEI), to assess various social groups’ environmental exposure. A case study about the risky environmental exposure of coronavirus disease 2019 (COVID-19) was conducted in Guangzhou, China. Over 900 participants with various socioeconomic backgrounds were involved in the questionnaire, and the survey-based activity locations were extracted to generate the vector field using the improved method. COVID-19 pandemic exposure (or risk) was estimated for different social groups. The findings show that people in the low-income group have an 8% to 10% higher risk than those in the high-income group. This new method of vector field may benefit geographers and urban researchers, as it provides opportunities to integrate human activities into the metrics of pandemic risk, spatial justice, and other environmental exposures.

Fine resolution air quality dynamics related to socioeconomic and land use factors in the most polluted desert metropolitan in the American Southwest

Air pollution kills approximately 4.2 million people every year. As air pollution varies significantly in different urban areas, the assessment of urban emissions is key to taking appropriate actions and formulating policies for sustainable built environments and to promote the wellbeing of people. The overarching goal of this study was to generate fine resolution aerosol optical depth (AOD) using Landsat imagery and examine both the socioeconomic inequalities of air pollution exposure and the air quality variation related to different land-use categories. This study has focused on a period of unusual population growth, 2000-2010, in the Phoenix Metropolitan Area. It was found that socioeconomic factors, vegetation indexes, and land use land cover types are all strong predictors of AOD, and the negative coefficients of socioeconomic values reveal insight into the social inequality of air pollution exposure. Results suggest that the government regulation on air pollution during the study period helped to improve air quality. Meanwhile, planting vegetation to mitigate air pollution should be carefully examined in order to find the right vegetation species and spatial configuration of vegetation cover in urban settings.

Campania and cancer mortality: An inseparable pair? The role of environmental quality and socio-economic deprivation

The region of Campania in Southern Italy features high levels of socio-economic deprivation and low levels of environmental quality. A vast strand of the scientific literature has tried to verify whether poor environmental quality and widespread socio-economic deprivation might explain the high cancer mortality rates (CMRs) observed, especially in the municipalities - infamously labelled as the 'Land of Fires' - that were hit most severely by the crisis. While some studies managed to identify links between these two confounding factors and cancer mortality, the evidence is overall mixed. Interesting information may be drawn from the observation of municipal data: in spite of previous claims, some municipalities featuring high environmental quality and low socio-economic deprivation also display high CMRs, while other Campanian municipalities facing disastrous environmental and socio-economic conditions are characterised by low CMRs. These figures, in contrast to common sentiment and previous studies, need to be investigated thoroughly in order to assess the exact role of the confounding factors. In this work, we aim to identify the municipalities where confounding factors act as driving forces in the determination of high CMRs through an original multi-step analysis based on frequentist and Bayesian analysis. Pinpointing these municipalities could allow policymakers to design targeted and effective policy measures aimed at reducing cancer mortality.

Impact of COVID-19 lockdown on NO2 and PM2.5 exposure inequalities in London, UK

Amid the COVID-19 pandemic, a nationwide lockdown was imposed in the United Kingdom (UK) on March 23, 2020. These sudden control measures led to radical changes in human activities in the Greater London Area (GLA). During this lockdown, transportation use was significantly reduced and non-key workers were required to work from home. This study aims to understand how population exposure to PM2.5 and NO2 changed spatially and temporally across London, in different microenvironments, following the lockdown period relative to the previous three-year average in the same calendar period. Our research shows that population exposure to NO2 declined significantly (52.3% ± 6.1%), while population exposure to PM2.5 showed a smaller relative reduction (15.7% ± 4.1%). Changes in population activity had the strongest relative influence on exposure levels during morning rush hours, when prior to the lockdown a large percentage of people would normally commute or be at the workplace. In particular, a very high exposure decrease was observed for both pollutants (approximately 66% for NO2 and 19% for PM2.5) at 08:00am, consistent with the radical changes in population commuting. The infiltration of outdoor air pollution into housing modifies the degree of exposure change both temporally and spatially. Moreover, this study shows that the impacts on air pollution exposure vary across groups with different socioeconomic status (SES), with a disproportionate positive effect on the areas of the city home to more economically deprived communities.

Confounding by Socioeconomic Status in Epidemiological Studies of Air Pollution and Health: Challenges and Opportunities

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. https://doi.org/10.1289/EHP7980.

Maternal Ambient Exposure to Atmospheric Pollutants during Pregnancy and Offspring Term Birth Weight in the Nationwide ELFE Cohort

Background: Studies have reported associations between maternal exposure to atmospheric pollution and lower birth weight. However, the evidence is not consistent and uncertainties remain. We used advanced statistical approaches to robustly estimate the association of atmospheric pollutant exposure during specific pregnancy time windows with term birth weight (TBW) in a nationwide study. Methods: Among 13,334 women from the French Longitudinal Study of Children (ELFE) cohort, exposures to PM_2.5, PM₁₀ (particles < 2.5 µm and <10 µm) and NO₂ (nitrogen dioxide) were estimated using a fine spatio-temporal exposure model. We used inverse probability scores and doubly robust methods in generalized additive models accounting for spatial autocorrelation to study the association of such exposures with TBW. Results: First trimester exposures were associated with an increased TBW. Second trimester exposures were associated with a decreased TBW by 17.1 g (95% CI, −26.8, −7.3) and by 18.0 g (−26.6, −9.4) for each 5 µg/m³ increase in PM_2.5 and PM₁₀, respectively, and by 15.9 g (−27.6, −4.2) for each 10 µg/m³ increase in NO₂. Third trimester exposures (truncated at 37 gestational weeks) were associated with a decreased TBW by 48.1 g (−58.1, −38.0) for PM_2.5, 38.1 g (−46.7, −29.6) for PM₁₀ and 14.7 g (−25.3, −4.0) for NO₂. Effects of pollutants on TBW were larger in rural areas. Conclusions: Our results support an adverse effect of air pollutant exposure on TBW. We highlighted a larger effect of air pollutants on TBW among women living in rural areas compared to women living in urban areas.

Systemic inequalities in indoor air pollution exposure in London, UK

Deprived communities in many cities are exposed to higher levels of outdoor air pollution, and there is increasing evidence of similar disparities for indoor air pollution exposure. There is a need to understand the drivers for this exposure disparity in order to develop effective interventions aimed at improving population health and reducing health inequities. With a focus on London, UK, this paper assembles evidence to examine why indoor exposure to PM2.5, NOx and CO may disproportionately impact low-income groups. In particular, five factors are explored, namely: housing location and ambient outdoor levels of pollution; housing characteristics, including ventilation properties and internal sources of pollution; occupant behaviours; time spent indoors; and underlying health conditions. Evidence is drawn from various sources, including building physics models, modelled outdoor air pollution levels, time-activity surveys, housing stock surveys, geographical data, and peer-reviewed research. A systems framework is then proposed to integrate these factors, highlighting how exposure to high levels of indoor air pollution in low-income homes is in large part due to factors beyond the control of occupants, and is therefore an area of systemic inequality.

POLICY RELEVANCE

There is increasing public and political awareness of the impact of air pollution on public health. Strong scientific evidence links exposure to air pollution with morbidity and mortality. Deprived communities may be more affected, however, with limited evidence on how deprivation may influence their personal exposure to air pollution, both outdoors and indoors. This paper describes different factors that may lead to low-income households being exposed to higher levels of indoor air pollution than the general population, using available data and models for London (i.e. living in areas of higher outdoor air pollution, in poor-quality housing, undertaking more pollution-generating activities indoors and spending more time indoors). A systems approach is used to show how these factors lead to systemic exposure inequalities, with low-income households having limited opportunities to improve their indoor air quality. This paper can inform actions and public policies to reduce environmental health inequalities, considering both indoor and outdoor air.

The impact of urban and transport planning on health: Assessment of the attributable mortality burden in Madrid and Barcelona and its distribution by socioeconomic status

BACKGROUND

The population living in urban areas is growing rapidly. The level of exposure to adverse environmental factors is detrimental to human health and is directly related to urban and transport planning practices.

OBJECTIVE

To estimate the premature mortality burden of non-compliance with international exposure guidelines for air pollution, noise, access to green space and heat for Barcelona and Madrid (Spain), and its distribution among the population by the socioeconomic status (SES).

METHODS

The Urban and TranspOrt planning Health Impact Assessment (UTOPHIA) tool was applied and the attributable premature mortality due to non-compliance with recommended exposure levels was estimated. The distribution of the attributable mortality burden among the population by SES was investigated through Generalized Additive Models (GAMs) adjusting for spatial autocorrelation and a cluster analysis was performed to identify attributable mortality hot spots.

RESULTS

Annually, 7.1% and 3.4% of premature mortality in Barcelona and Madrid, respectively, could be attributed to non-compliance with the international exposure recommendations for air pollution, noise, heat and access to green space. In addition, analysis by SES showed that in Barcelona lower SES areas had an overall greater attributable mortality rate, while in Madrid, the distribution of the attributable mortality burden by SES varied by exposure.

CONCLUSION

This study shows the impact of environmental exposures on mortality and highlights the importance of taking integrated actions when designing cities considering the health impacts, but also the specificities of each city such as the socio-demographic context. Moreover, the high precision scale of the analysis enables the identification of environmental hazards and mortality hot spots providing a powerful tool to support priority-setting and guide policymakers towards a healthy, sustainable and just city for all of their residents.

The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong

Human mortality is in part a function of multiple socioeconomic factors that differ both spatially and temporally. Adjusting for other covariates, the human lifespan is positively associated with household wealth. However, the extent to which mortality in a geographical region is a function of socioeconomic factors in both that region and its neighbors is unclear. There is also little information on the temporal components of this relationship. Using the districts of Hong Kong over multiple census years as a case study, we demonstrate that there are differences in how wealth indicator variables are associated with longevity in (a) areas that are affluent but neighbored by socially deprived districts versus (b) wealthy areas surrounded by similarly wealthy districts. We also show that the inclusion of spatially-distributed variables reduces uncertainty in mortality rate predictions in each census year when compared with a baseline model. Our results suggest that geographic mortality models should incorporate nonlocal information (e.g., spatial neighbors) to lower the variance of their mortality estimates, and point to a more in-depth analysis of sociospatial spillover effects on mortality rates.

Exposure to indoor air pollution across socio-economic groups in high-income countries: A scoping review of the literature and a modelling methodology

Disparities in outdoor air pollution exposure between individuals of differing socio-economic status is a growing area of research, widely explored in the environmental health literature. However, in developed countries, around 80% of time is spent indoors, meaning indoor air pollution may be a better proxy for personal exposure. Building characteristics - such as build quality, volume and ventilation - and occupant behaviour, mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Much of the existing literature has focused on inequalities in exposure to outdoor air pollution, and there is thus a lack of an evidence base reviewing data for indoor environments. In this study, a scoping review of the literature on indoor air pollution exposures across different socio-economic groups is performed, examining evidence from both monitoring and modelling studies in the developed world. The literature was reviewed, identifying different indoor pollutants, definitions for socio-economic status and pre- and post- housing interventions. Based on the review, the study proposes a modelling methodology for evaluating the effects of environmental policies on different socio-economic populations. Using a sample size calculation, obstacles in obtaining sufficiently large samples of monitored data are demonstrated. A modelling framework for the rapid quantification of daily home exposure is then outlined as a proof of concept. While significant additional research is required to examine inequalities in indoor exposures, modelling approaches may provide opportunities to quantify exposure disparities due to housing and behaviours across populations of different socio-economic status.

Who are more exposed to PM2.5 pollution: A mobile phone data approach

BACKGROUND

Few studies have examined exposure disparity to ambient air pollution outside North America and Europe. Moreover, very few studies have investigated exposure disparity in terms of individual-level data or at multi-temporal scales.

OBJECTIVES

This work aims to examine the associations between individual- and neighbourhood-level economic statuses and individual exposure to PM2.5 across multi-temporal scales.

METHODS

The study population included 742,220 mobile phone users on a weekday in Shenzhen, China. A geo-informed backward propagation neural network model was developed to estimate hourly PM2.5 concentrations by the use of remote sensing and geospatial big data, which were then combined with individual trajectories to estimate individual total exposure during weekdays at multi-temporal scales. Coupling the estimated PM2.5 exposure with housing price, we examined the associations between individual- and neighbourhood-level economic statuses and individual exposure using linear regression and two-level hierarchical linear models. Furthermore, we performed five sensitivity analyses to test the robustness of the two-level effects.

RESULTS

We found positive associations between individual- and neighbourhood-level economic statuses and individual PM2.5 exposure at a daytime, daily, weekly, monthly, seasonal or annual scale. Findings on the effects of the two-level economic statuses were generally robust in the five sensitivity analyses. In particular, despite the insignificant effects observed in three of newly selected time periods in the sensitivity analysis, individual- and neighbourhood-level economic statuses were still positively associated with individual total exposure during each of other newly selected periods (including three other seasons).

CONCLUSIONS

There are statistically positive associations of individual PM2.5 exposure with individual- and neighbourhood-level economic statuses. That is, people living in areas with higher residential property prices are more exposed to PM2.5 pollution. Findings emphasize the need for public health intervention and urban planning initiatives targeting socio-economic disparity in ambient air pollution exposure, thus alleviating health disparities across socioeconomic groups.

Exposure to indoor air pollution across socio-economic groups in high-income countries: A scoping review of the literature and a modelling methodology

Disparities in outdoor air pollution exposure between individuals of differing socio-economic status is a growing area of research, widely explored in the environmental health literature. However, in developed countries, around 80% of time is spent indoors, meaning indoor air pollution may be a better proxy for personal exposure. Building characteristics - such as build quality, volume and ventilation - and occupant behaviour, mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Much of the existing literature has focused on inequalities in exposure to outdoor air pollution, and there is thus a lack of an evidence base reviewing data for indoor environments. In this study, a scoping review of the literature on indoor air pollution exposures across different socio-economic groups is performed, examining evidence from both monitoring and modelling studies in the developed world. The literature was reviewed, identifying different indoor pollutants, definitions for socio-economic status and pre- and post- housing interventions. Based on the review, the study proposes a modelling methodology for evaluating the effects of environmental policies on different socio-economic populations. Using a sample size calculation, obstacles in obtaining sufficiently large samples of monitored data are demonstrated. A modelling framework for the rapid quantification of daily home exposure is then outlined as a proof of concept. While significant additional research is required to examine inequalities in indoor exposures, modelling approaches may provide opportunities to quantify exposure disparities due to housing and behaviours across populations of different socio-economic status.

New directions in understanding the role of environmental contaminants in child development: Four themes

Environmental contaminants, which include several heavy metals, persistent organic pollutants, and other harmful chemicals, impair several domains of child development. This article describes four themes from recent research on the impact of environmental contaminants on child development. The first theme, disparities in exposure, focuses on how marginalized communities are disproportionately exposed to harmful environmental contaminants. The second theme, complexity of exposures, encapsulates recent emphases on timing of exposures and mixtures of multiple exposures. The third theme, mechanisms that link exposures to outcomes, focuses on processes that elucidate how contaminants impact outcomes. The fourth theme, mitigating risks associated with exposures, sheds light on potential protective factors that could ameliorate many of the harmful effects of contaminant exposures. Developmental scientists are well positioned to contribute to interdisciplinary research that addresses these themes, which could foster additional conceptual and empirical innovations and inform policies and practices to mitigate risks and improve children's well-being.

Environmental Justice Dimensions of Oil and Gas Flaring in South Texas: Disproportionate Exposure among Hispanic communities

Unconventional extraction techniques including hydraulic fracturing or "fracking" have led to a boom in oil and gas production in the Eagle Ford shale play, Texas, one of the most productive regions in the United States. Nearly 400000 people live within 5 km of an unconventional oil or gas well in this largely rural area. Flaring is associated primarily with unconventional oil wells and is an increasingly common practice in the Eagle Ford to dispose of excess gas through combustion. Flares can operate continuously for months and release hazardous air pollutants such as particulate matter and volatile organic compounds in addition to causing light and noise pollution and noxious odors. We estimated ethnic disparities in exposure to flaring using satellite observations from the Visible Infrared Imaging Spectroradiometer between March 2012-December 2016. Census blocks with majority Hispanic (>60%) populations were exposed to twice as many nightly flare events within 5 km as those with <20% Hispanics. We found that Hispanics were exposed to more flares despite being less likely than non-Hispanic White residents to live near unconventional oil and gas wells. Our findings suggest Hispanics are disproportionately exposed to flares in the Eagle Ford shale, a pattern known as environmental injustice, which could contribute to disparities in air pollution and other nuisance exposures.

Is a liveable city a healthy city? Health impacts of urban and transport planning in Vienna, Austria

Each year, The Economist Intelligence Unit (EIU) computes the Global Liveability Index and determines the most liveable cities around the world. Vienna, Austria, was ranked by the EIU as the most liveable city worldwide in 2018 and 2019. However, the relationship between a liveable as well as healthy and environmentally-just city has not been previously explored. To explore whether the most liveable city is also a healthy and environmentally-just one, we estimated the premature mortality burden related to non-compliance with international exposure level recommendations for physical activity (PA), air pollution (PM_2.5 and NO₂), road traffic noise, green space and heat for Vienna, as well as its distribution by socioeconomic status (SES). We applied the Urban and TranspOrt Planning Health Impact Assessment (UTOPHIA) methodology and estimated the annual mortality, life expectancy (LE) and economic impact of non-compliance with exposure guidelines for the Viennese adult population ≥ 20 years. We compared current with recommended exposure levels, quantified the association between exposures and mortality and calculated attributable health impact fractions. Eight percent of premature mortality (i.e. 1239 deaths, 95% CI: 679-1784) was estimated to be attributable to non-compliance with the recommended exposure levels. Seventy-six percent of the attributable premature mortality was due to PM_2.5 exposure and insufficient PA. Non-compliance also resulted in an average of 199 days of LE lost for the adult population (95% CI: 111-280) and an economic impact of 4.6 (95% CI: 2.5-6.7) billion 2015€ annually. Overall, residents of lower SES neighbourhoods faced higher risk of premature mortality due to higher exposure to NO₂, road traffic noise, heat and less green space. Despite high liveability standards according to EIU definition, a considerable premature mortality burden was attributable to non-compliance with exposure recommendations, and socioeconomic inequalities were estimated. Although the exposure attributable mortality burden was lower than in other European cities and local Viennese policies favour the reduction of motorized traffic, alongside the promotion of active and public transport and urban greening, there is room for further alignment of liveability, environmental health and justice objectives.

Spatial Association Pattern of Air Pollution and Influencing Factors in the Beijing-Tianjin-Hebei Air Pollution Transmission Channel: A Case Study in Henan Province

The Beijing–Tianjin–Hebei (BTH) air pollution transmission channel and its surrounding areas are of importance to air pollution control in China. Based on daily data of air quality index (AQI) and air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) from 2015 to 2016, this study analyzed the spatial and temporal characteristics of air pollution and influencing factors in Henan Province, a key region of the BTH air pollution transmission channel. The result showed that non-attainment days and NAQI were slightly improved at the provincial scale during the study period, whereas that in Hebi, Puyang, and Anyang became worse. PM_2.5 was the largest contributor to the air pollution in all cities based on the number of non-attainment days, but its mean frequency decreased by 21.62%, with the mean occurrence of O₃ doubled. The spatial distribution of NAQI presented a spatial agglomeration pattern, with high-high agglomeration area varying from Jiaozuo, Xinxiang, and Zhengzhou to Anyang and Hebi. In addition, the NAQI was negatively correlated with sunshine duration, temperature, relative humidity, wind speed, and positively to atmospheric pressure and relative humidity in all four clusters, whereas relationships between socioeconomic factors and NAQI differed among them. These findings highlight the need to establish and adjust regional joint prevention and control of air pollution as well as suggest that it is crucially important for implementing effective strategies for O₃ pollution control.

Development of Serious Games (Equit'Game) to Address Health and Environmental Inequalities: Protocol for an App-Delivered Program to Perform a Territorial Diagnosis

BACKGROUND

Territorial diagnosis is a prerequisite for local actions concerning public health and for the reduction of social, environmental, and health-related inequalities. To orient local programs or initiatives targeting health inequalities, policymakers need a simulation of territorial diagnosis tools. Yet, very few platforms have been developed for the purpose of guiding public authorities as they seek to reduce these social inequalities.

OBJECTIVE

This study aimed to describe the design and methods of the development process of a territorial diagnosis tool based on a serious game named Equit'Game that puts learners at the heart of the territorial diagnosis process, asking them to review the current state of health, environmental state, and socioeconomic state of their territory.

METHODS

The realistic situations employed in our serious game should encourage players, in a fun and playful manner, to (1) appropriate the data of their own territory, (2) apply their methodological knowledge in a practical way, (3) reflect on the most pertinent statistical or spatial tools for their situation, and (4) ultimately, to acquire new knowledge and skills in the use of territorial diagnosis tools with a spatial dynamic. Equit'Game was deployed over the course of a week's training and structured into 4 levels: level 1, Dataminer (identifying relevant information to respond to the question); level 2, Analyst (selecting the appropriate method of analysis); level 3, Atlas (mapping the data); and level 4, Cluster (extraction of statistical and spatial information). Equit'Game has also been designed as a sort of virtual campus, creating a fun learning environment in which each door represents a level. Users can access Equit'Game via a platform compatible with tablets, PCs, and mobile phones.

RESULTS

In the first step, we tested our application interface designed especially for adults among a panel of local health professionals. The following are some of the most relevant points: font size and colors used, voice accompaniment in texts and messages guiding the user, clear and easy interfaces, and the change between successive game levels. In the second step, we used our application, Equit'Game, with postgraduate students from the School of Public Health (École des hautes études en santé publique). At the end of the game session, we conducted a satisfaction survey, including several items covering both the application interface and the execution of the game.

CONCLUSIONS

Equit'Game was developed to help learners with the techniques of territorial diagnosis, with the aim of creating an innovative tool for public health capable of conveying educational messages and providing a structure for training.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/11786.

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.

Sustainability and Environmental Inequality: Effects of Animal Husbandry Pollution in China

Environmental inequality in animal husbandry is an important issue that matters in sustainable livestock production and environmental sustainability. In this context, the objective of this study is to measure and analyze the chemical oxygen demand (COD) discharge inequality from animal husbandry in the Liaoning province in China, as a case study in environmental inequality. Using the pollutant discharge coefficient method and environmental inequality indices, the study looks specifically at the impacts on unequal distribution and unequal economic efficiency in Liaoning in the period 2000 to 2016. The study explores the determinants of COD discharge inequality by constructing panel threshold regression models. The major findings are as follows. First, there is COD discharge inequality in distribution and in economic efficiency in Liaoning, and these were not reduced over time, despite a decline in the absolute quantity of COD discharge after 2013. Second, the impact of COD discharge inequality in economic efficiency lasted longer and was more serious across Liaoning compared with COD discharge inequality in distribution. Third, the quantitative upgrading of the agricultural industrial structure did not significantly reduce COD discharge inequality, and even led to a rise in inequality, especially in terms of economic efficiency. Ultimately, regional economic development turned out to be the key factor in inequality reduction. In addition, improvement in public fiscal support for science and technology also led to greater reduction in inequality.

Elderly Health Inequality in China and its Determinants: A Geographical Perspective

Inter-regional health differences and apparent inequalities in China have recently received significant attention. By collecting health status data and individual socio-economic information from the 2015 fourth sampling survey of the elderly population in China (4th SSEP), this paper uses the geographical differentiation index to reveal the spatial differentiation of health inequality among Chinese provinces. We test the determinants of inequalities by multilevel regression models at the provincial and individual levels, and find three main conclusions: 1) There were significant health differences on an inter-provincial level. For example, provinces with a very good or good health rating formed a good health hot-spot region in the Yangtze River Delta, versus elderly people living in Gansu and Hainan provinces, who had a poor health status. 2) Nearly 2.4% of the health differences in the elderly population were caused by inter-provincial inequalities; access (or lack of access) to economic, medical and educational resources was the main reason for health inequalities. 3) At the individual level, inequalities in annual income served to deepen elderly health differences, and elderly living in less developed areas were more vulnerable to urban vs. rural-related health inequalities.

Enabling Green and Blue Infrastructure to Improve Contributions to Human Well-Being and Equity in Urban Systems

The circumstances under which different ecosystem service benefits can be realized differ. The benefits tend to be coproduced and to be enabled by multiple interacting social, ecological, and technological factors, which is particularly evident in cities. As many cities are undergoing rapid change, these factors need to be better understood and accounted for, especially for those most in need of benefits. We propose a framework of three systemic filters that affect the flow of ecosystem service benefits: the interactions among green, blue, and built infrastructures; the regulatory power and governance of institutions; and people's individual and shared perceptions and values. We argue that more fully connecting green and blue infrastructure to its urban systems context and highlighting dynamic interactions among the three filters are key to understanding how and why ecosystem services have variable distribution, continuing inequities in who benefits, and the long-term resilience of the flows of benefits.

The Role of Socioeconomic Status in the Association of Lung Function and Air Pollution-A Pooled Analysis of Three Adult ESCAPE Cohorts

Ambient air pollution is a leading environmental risk factor and its broad spectrum of adverse health effects includes a decrease in lung function. Socioeconomic status (SES) is known to be associated with both air pollution exposure and respiratory function. This study assesses the role of SES either as confounder or effect modifier of the association between ambient air pollution and lung function. Cross-sectional data from three European multicenter adult cohorts were pooled to assess factors associated with lung function, including annual means of home outdoor NO₂. Pre-bronchodilator lung function was measured according to the ATS-criteria. Multiple mixed linear models with random intercepts for study areas were used. Three different factors (education, occupation and neighborhood unemployment rate) were considered to represent SES. NO₂ exposure was negatively associated with lung function. Occupation and neighborhood unemployment rates were not associated with lung function. However, the inclusion of the SES-variable education improved the models and the air pollution-lung function associations got slightly stronger. NO₂ associations with lung function were not substantially modified by SES-variables. In this multicenter European study we could show that SES plays a role as a confounder in the association of ambient NO₂ exposure with lung function.

Socioeconomic factors increase the adverse effects of air pollution and temperature on mortality

OBJECTIVE

To verify the effects of PM2.5 and temperature on mortality due to cardiovascular diseases according to socioeconomic status and traffic proximity.

METHOD

Time series were used, using the generalized additive models with the Poisson regression option, at 5% significance level. Interactionbetween proximity of traffic and socioeconomic status was analyzed through stratification. The proximity to the traffic was divided into distances up to 150m or over 150m. Socioeconomic status in the residential environment was categorized as high and low based on the median (3.9%). The relative risk percentage (%RR) of cardiovascular disease deaths was calculated for each linear increase of 10 µg/m3 at PM2.5 and 1ºC at the maximum temperature.

RESULTS

Mortality due to cardiovascular diseases presented %RR 1.64 (95%CI -0.03; 3.33), related to the maximum temperature and %RR 4.60 (95%CI 0.78; 8.56) related to PM2.5, in areas with high traffic exposure. In areas with poor living conditions, %RR 1.34 (95%CI -0.31; 3.01) was observed, related to maximum temperature and RR% 3.95 (95%CI -0.27; 8.34) associated with PM2.5.

CONCLUSION

Areas with poor living conditions and high-exposure to vehicular traffic had an increased risk of cardiovascular disease mortality related to high temperature and PM2.5.

Socioeconomic Deprivation Status and Air Pollution by PM10 and NO2: An Assessment at Municipal Level of 11 Years in Italy

The aim of this observational study was to assess the relationship between environmental risk factors and some aspects of social economic status (SES) of the population in different Italian municipalities. Nitrogen dioxide (NO₂) and particulate matter (PM₁₀) annual means were extracted from ISPRA-BRACE (environmental information system of 483 Italian municipalities, 6% of the total amount of administrative units) from 2002 to 2012. As an indicator of sociodemographic and SES data, we collected the following: resident population, foreign nationality, low level of education, unemployment, nonhome ownership, single-parent family, and overcrowding. Low educational level, unemployment, and lack of home ownership were indirectly associated with the higher mean values of NO₂ at the statistically significant level (p < 0.05). Major resident population and rental housing percentage determined higher levels of PM₁₀. Northern regions showed similar results compared to the national level, with the exception of foreign residency that showed direct correlation with the increase of PM₁₀. The central regions showed a direct relationship between NO₂ and PM₁₀ levels and higher educational levels and between NO₂ levels and percentage of single-parent family. In the southern areas, higher NO₂ levels were correlated with a higher rental housing percentage, as well as higher PM₁₀ levels with a higher percentage of unemployment and lower housing density. The study shows high heterogeneity in the findings but confirms the relationship between high educational level and employment with the increased concentration of pollutants. The higher rental housing percentage may increase the pollutants' levels too. The housing density does not seem to be in relationship with NO₂ and PM₁₀ at the national level. The analysis stratified by geographical areas showed that the direction of the correlations was different over time as the analysis was at a national level. The study represents an example of how data from national information systems can provide a preliminary evaluation and be a comparative tool for policy-makers to assess environmental risk factors and social inequalities.

Unequal residential exposure to air pollution and noise: A geospatial environmental justice analysis for Ghent, Belgium

Following the growing empirical evidence on the health effects of air pollution and noise, the fair distribution of these impacts receives increasing attention. The existing environmental inequality studies often focus on a single environmental impact, apply a limited range of covariates or do not correct for spatial autocorrelation. This article presents a geospatial data analysis on Ghent (Belgium), combining residential exposure to air pollution and noise with socioeconomic variables and housing variables. The global results show that neighborhoods with lower household incomes, more unemployment, more people of foreign origin, more rental houses, and higher residential mobility, are more exposed to air pollution, but not to noise. Multiple regression models to explain exposure to air pollution show that residential mobility and percentage of rental houses are the strongest predictors, stressing the role of the housing market in explaining which people are most at risk. Applying spatial regression models leads to better models but reduces the importance of all covariates, leaving income and residential mobility as the only significant predictors for air pollution exposure. While traditional multiple regression models were not significant for explaining noise exposure, spatial regression models were, and also indicate the significant contribution of income to the model. This means income is a robust predictor for both air pollution and noise exposure across the whole urban territory. The results provide a good starting point for discussions about environmental justice and the need for policy action. The study also underlines the importance of taking spatial autocorrelation into account when analyzing environmental inequality.

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We found socioeconomic inequalities in exposure to air pollution and noise.

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Median household income was the most significant predictor overall.

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Residential mobility was an important predictor for air pollution exposure.

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Spatial autocorrelation distorts traditional multiple regression results.

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The results contribute to environmental justice debates.

Does residential mobility during pregnancy induce exposure misclassification for air pollution?

BACKGROUND

Prenatal exposure to outdoor air pollution has been shown to have health effects in many studies; low birth weight, preterm delivery, small for gestational age, and stillbirth are the most often cited. However, exposure of pregnant women is difficult to quantify, especially with regard to their mobility, which is rarely taken into account in epidemiological studies. This study aimed to assess the impact of mobility of pregnant women living in Paris, France, on their exposure estimates to nitrogen dioxide (NO₂).

METHODS

A total of 486 pregnant women were recruited in 5 maternity hospitals in Paris between January and April 2016. A questionnaire was used to collect mothers' characteristics (demography, education, etc.) and to assess their daily mobility during pregnancy (time spent at work, commuting time and mode used to move from residential to occupational places). Daily NO₂ concentrations were estimated based on the combination of annual average concentrations modeled at the census block scale and daily concentrations measured from fixed monitoring stations. Different models were used to compare the exposure of pregnant women in residential and occupational places, also taking into account travel time and travel mode. The socioeconomic profile of the census blocks was characterized using a multi-component index.

RESULTS

During the first trimester of pregnancy, women living in the least deprived census blocks were exposed to higher concentrations of NO₂ than those living in the most deprived ones. Occupational mobility had a small impact on exposure levels (average increase after taking account of mobility: + 0.52 μg/m³) which was not related to the socioeconomic profile of the women. The commuting mode made a greater difference (+ 1.46 μg/m³ on average), in particular among women living in the most deprived census blocks.

CONCLUSIONS

Our study illustrates that air pollution exposure can be underestimated when ignoring occupational mobility and commuting mode of pregnant women. This effect might be differential according to the neighborhood deprivation profile.

Tobacco-attributable burden of cancer according to socioeconomic position in France

Smoking is a major preventable cause of cancers and is increasingly concentrated among the most deprived individuals leading to increasing socioeconomic inequalities in the incidence of cancers linked to smoking. We aimed to estimate the tobacco-attributable cancer burden according to socioeconomic position in France. The analysis was restricted to cancer sites for which tobacco smoking was recognized as a risk factor. Cancer cases by sex, age group and European Deprivation Index (EDI) among people aged 30-74 between 2006 and 2009 were obtained from cancer registries covering ∼20% of the French population. The tobacco-attributable burden of cancer according to EDI was estimated applying the population attributable fraction (PAF) computed with the Peto-Lopez method. The PAF increased from 56% in the least deprived EDI quintile to 70% in the most deprived EDI quintile among men and from 26% to 38% among women. In total, 28% of the excess cancer cases in the four most deprived EDI quintiles in men and 43% in women could be prevented if smoking in these 4 EDI quintiles was similar to that of the least deprived EDI quintile. A substantial smoking-attributable burden of cancer by socioeconomic position was observed in France. The results highlight the need for policies reducing tobacco consumption. More comprehensive interventions integrating the various dimensions of health determinants and proportionate according to socioeconomic position may essentially contribute to the reduction of socioeconomic inequalities in cancer.

Spatial associations between social groups and ozone air pollution exposure in the Beijing urban area

Few studies have linked social factors to air pollution exposure in China. Unlike the race or minority concepts in western countries, the Hukou system (residential registration system) is a fundamental reason for the existence of social deprivation in China. To assess the differences in ozone (O₃) exposure among social groups, especially groups divided by Hukou status, we assigned estimates of O₃ exposure to the latest census data of the Beijing urban area using a kriging interpolation model. We developed simultaneous autoregressive (SAR) models that account for spatial autocorrelation to identify the associations between O₃ exposure and social factors. Principal component regression was used to control the multicollinearity bias as well as explore the spatial structure of the social data. The census tracts (CTs) with higher proportions of persons living alone and migrants with non-local Hukou were characterized by greater exposure to ambient O₃. The areas with greater proportions of seniors had lower O₃ exposure. The spatial distribution patterns were similar among variables including migrants, agricultural population and household separation (population status with separation between Hukou and actual residences), which fit the demographic characteristics of the majority of migrants. Migrants bore a double burden of social deprivation and O₃ pollution exposure due to city development planning and the Hukou system.

Neighborhood Socioeconomic Deprivation and Allostatic Load: A Scoping Review

Residing in socioeconomically deprived neighborhoods may pose substantial physiological stress, which can then lead to higher allostatic load (AL), a marker of biological wear and tear that precedes disease. The aim of the present study was to map the current evidence about the relationship between neighborhood socioeconomic deprivation and AL. A scoping review approach was chosen to provide an overview of the type, quantity, and extent of research available. The review was conducted using three bibliographic databases (PubMed, SCOPUS, and Web of Science) and a standardized protocol. Fourteen studies were identified. Studies were predominantly from the USA, cross-sectional, focused on adults, and involved different races and ethnic groups. A wide range of measures of AL were identified: the mode of the number of biomarkers per study was eight but with large variability (range: 6⁻24). Most studies (n = 12) reported a significant association between neighborhood deprivation and AL. Behaviors and environmental stressors seem to mediate this relationship and associations appear more pronounced among Blacks, men, and individuals with poor social support. Such conclusions have important public health implications as they enforce the idea that neighborhood environment should be improved to prevent physiological dysregulation and consequent chronic diseases.

Reconsidering the Relationship between Air Pollution and Deprivation

This paper critically examines the relationship between air pollution and deprivation. We argue that focusing on a particular economic or social model of urban development might lead one to erroneously expect all cities to converge towards a particular universal norm. A naive market sorting model, for example, would predict that poor households will eventually be sorted into high pollution areas, leading to a positive relationship between air pollution and deprivation. If, however, one considers a wider set of theoretical perspectives, the anticipated relationship between air pollution and deprivation becomes more complex and idiosyncratic. Specifically, we argue the relationship between pollution and deprivation can only be made sense of by considering processes of risk perception, path dependency, gentrification and urbanization. Rather than expecting all areas to eventually converge to some universal norm, we should expect the differences in the relationship between air pollution and deprivation across localities to persist. Mindful of these insights, we propose an approach to modeling which does not impose a geographically fixed relationship. Results for Scotland reveal substantial variations in the observed relationships over space and time, supporting our argument.

Neighbours matter: A nation-wide small-area assessment of environmental inequality in Germany

This study investigates the presence of environmental inequality in Germany and analyses its spatial pattern on a very fine grained level. Using the 2011 German census and pollution measures of the E-PRTR, the study relies on nearly 100,000 one squared km census cells over Germany. SLX and community-fixed SLX models incorporate spatial spillover-effects into the analysis to account for the spatial distribution of socio-demographic characteristics. Results reveal that the share of minorities within a census cell indeed positively correlates with the exposure to industrial pollution. Furthermore, spatial spillover effects are highly relevant: the characteristics of the neighbouring spatial units matter in predicting the amount of pollution. Especially within urban areas, clusters of high minority neighbourhoods are affected by high levels of environmental pollution. This highlights the importance of spatial clustering processes in environmental inequality research.

Ability of ecological deprivation indices to measure social inequalities in a French cohort

Background

Despite the increasing interest in place effect to explain health inequalities, there is currently no consensus on which kind of area-based socioeconomic measures researchers should use to assess neighborhood socioeconomic position (SEP). The study aimed to evaluate the reliability of different area-based deprivation indices (DIs) in capturing socioeconomic residential conditions of French elderly women cohort.

Methods

We assessed area-based SEP using 3 DIs: Townsend Index, French European Deprivation Index (FEDI) and French Deprivation index (FDep), among women from E3N (Etude épidémiologique auprès des femmes de la Mutuelle Générale de l’Education Nationale). DIs were derived from the 2009 French census at IRIS level (smallest geographical units in France). Educational level was used to evaluate individual-SEP. To evaluate external validity of the 3 DIs, associations between two well-established socially patterned outcomes among French elderly women (smoking and overweight) and SEP, were compared. Odd ratios were computed with generalized estimating equations to control for clustering effects from participants within the same IRIS.

Results

The analysis was performed among 63,888 women (aged 64, 47% ever smokers and 30% overweight). Substantial agreement was observed between the two French DIs (Kappa coefficient = 0.61) and between Townsend and FEDI (0.74) and fair agreement between Townsend and FDep (0.21). As expected among French elderly women, those with lower educational level were significantly less prone to be ever smoker (Low vs. High; OR [95% CI] = 0.43 [0.40–0.46]) and more prone to being overweight (1.89 [1.77–2.01]) than women higher educated. FDep showed expected associations at area-level for both smoking (most deprived vs. least deprived quintile; 0.77 [0.73–0.81]) and overweight (1.52 [1.44–1.62]). For FEDI opposite associations with smoking (1.13 [1.07–1.19]) and expected association with overweight (1.20 [1.13–1.28]) were observed. Townsend showed opposite associations to those expected for both smoking and overweight (1.51 [1.43–1.59]; 0.93 [0.88–0.99], respectively).

Conclusion

FDep seemed reliable to capture socioeconomic residential conditions of the E3N women, more educated in average than general French population. Results varied strongly according to the DI with unexpected results for some of them, which suggested the importance to test external validity before studying social disparities in health in specific populations.

Electronic supplementary material

The online version of this article (10.1186/s12889-017-4967-3) contains supplementary material, which is available to authorized users.

Do Individual and Neighborhood Characteristics Influence Perceived Air Quality?

Background: Despite improvements, air pollution still remains a major public health issue. Numerous epidemiological studies have demonstrated the adverse health effects of air pollution exposure based on modeled measures, but only a few have considered the health impact of perceived air quality. Improving our knowledge of individual perceptions is crucial to defining targeted actions and promoting appropriate intervention measures. Our objective is to investigate the relationship between subjective and objective measures of air pollution and to focus on how individual characteristics combined with the neighborhood socioeconomic deprivation index, measured at a fine spatial scale, may or may not alter this relationship. Materials and Methods: The subjective measures of air quality reported by a sample of Lyon residents were collected via an individual questionnaire. The objective measures of air pollution were modeled by the local air quality monitoring network of the Rhône-Alpes region at census block level. We used a socioeconomic deprivation index to capture the different socioeconomic dimensions at census block level. The statistical analysis was structured in two steps: (1) identification of individual determinants of the subjective measures of air quality using multiple correspondence analysis followed by hierarchical clustering; (2) identification of individual and contextual characteristics that may alter the relationship between the objective and subjective measures of air pollution. Results: Among the youngest and the middle aged population (ages 30 to 59), consistent results between level of satisfaction, perceived air quality and objective measures of air pollution were found whatever the individual characteristics of the population. It is less clear among the oldest population: globally no significant difference between the NO₂ concentrations and the level of satisfaction was observed. Conclusions: We found a significant relationship between the subjective and objective measures of air pollution in many population sub-groups with different combinations of individual characteristics. The relationship is less clear among the oldest population, which confirms previous findings. Our finding highlights that age combined with low level of education and unemployment, or women or health problems as well as the neighborhood deprivation index influence the level of air quality satisfaction.