Environmental inequity in England: small area associations between socio-economic status and environmental pollution

Environmental justice issues in drinking water contaminant exposure in a European context

Previous studies have documented ethnic and sociodemographic disparities in exposure to drinking water (DW) contaminants. A majority were conducted in the U.S., with fewer studies conducted in other regions. This research aims to assess available evidence regarding environmental justice (EJ) issues in Europe, identify contaminants and potential drivers. A Scoping Review was conducted, exploring the existing European studies from 1990 to 2022. The review encompasses types of DW contaminants studied in relation to EJ, research designs, and potential drivers contributing to inequalities in exposure to specific contaminants. In addition, a case study was conducted in Ille-et-Vilaine, France, focusing on contaminants identified in the review and using a national monitoring database. Inequalities in contaminants' exposure were assessed using a composite deprivation index, FDep, at the census tract level (IRIS) applied in multilevel models and geographically weighted regression models, accounting for the rural-urban heterogeneity. Results show a limited number of primary studies focusing on EJ and DW contaminants exposure in Europe (n = 16). Various chemical contaminants such as nitrates, trihalomethanes (THMs), heavy metals, fluoride and pesticides have been assessed. Case study findings suggest some association between FDep and contaminants, with a different level of correlation depending on the contaminant. THMs show a negative correlation with deprivation, while lead displays a positive correlation related to the FDep. Disparities in exposure were also found according to the spatial scale of analysis. In rural areas, higher deprivation levels were associated with higher levels of nitrate (OR: 1.47; 95%CI: 1.02, 2.15) and lower level of fluoride (OR: 0.16; 95%CI: 0.07, 0.30) or THMs (OR: 0.73; 95%CI: 0.55, 0.98) in tap water. This study emphasizes the need for comprehensive research on EJ and DW contaminants exposure on a larger scale. Understanding complex interactions between contaminant distribution, socioeconomic factors, and exposure is essential for addressing EJ in drinking water.

An investigation of inequalities in exposure to PM2.5 air pollution across small areas in Ireland

The link between exposure to air pollution and adverse effects on human health is well documented. Yet, in a European context, research on the spatial distribution of air pollution and the characteristics of areas is relatively scarce, and there is a need for research using different spatial scales, a wider variety of socioeconomic indicators (such as ethnicity) and new methodologies to assess these relationships. This study uses comprehensive data on a wide range of demographic and socioeconomic indicators, matched to data on PM2.5 concentrations for small areas in Ireland, to assess the relationship between social vulnerability and PM2.5 air pollution. Examining a wide range of socioeconomic indicators revealed some differentials in PM2.5 concentration levels by measure and by rural and urban classification. However, statistical modelling using concentration curves and concentration indices did not present substantial evidence of inequalities in PM2.5 concentrations across small areas. In common with other western European countries, an overall decline in the levels of PM2.5 between 2011 and 2016 was observed in Ireland, though the data indicates that almost all small areas in Ireland were found to have exceeded the World Health Organization (WHO)'s PM2.5 annual guideline (of 5 µg/m3), calling for greater policy efforts to reduce air pollution in Ireland. The recent Clean Air Strategy contains a commitment to achieve the WHO guideline limits for PM2.5 by 2040, with interim targets at various points over the next two decades. Achieving these targets will require policy measures to decarbonise home heating, promote active travel and the transition to electric vehicles, and further regulations on burning fossil fuels and enforcing environmental regulations more tightly. From a research and information-gathering perspective, installing more monitoring stations at key points could improve the quality and spatial dimension of the data collected and facilitate the assessment of the implementation of the measures in the Clean Air Strategy.

Air pollution and public health vulnerabilities, susceptibilities and inequalities in Wales, UK

BACKGROUND

Outdoor air pollution is the largest environmental risk to health. Air pollution, deprivation and poor health status are inextricably linked; highlighting issues of environmental injustice, social and health inequalities.

METHODS

Air pollution (nitrogen dioxide, NO2 and fine particulate matter, PM2.5), population and deprivation data were identified at Lower Super Output Area level in Wales, UK, for 2012-18. Air pollution data were categorized according to different air pollution concentrations. Population and deprivation data were considered simultaneously to describe population vulnerabilities, susceptibilities and inequalities. Simple statistical analyses were performed using a difference in proportions method with 95% confidence intervals.

RESULTS

Over time, the majority of Welsh people transitioned to living in areas of lower NO2 and PM2.5 pollution. Areas of worse air pollution comprised more young people than people aged 65+; both populations are known to be susceptible to air pollution exposure. By 2018, significant socioeconomic inequality gaps were found where 'most deprived' population groups for both pollutants experienced greater disadvantage.

CONCLUSION

Air quality in Wales is improving. However, local-level variations in exposure risk still exist. System-wide action must ensure that air quality improvement-related benefits are equitable and acknowledge current evidence about the harms that even low levels of air pollution can have on health.

Analysis of the Coordination Relationship between the Green Principle of Civil Law and Environmental Law in Environmental Pollution and Ecological Destruction

Under the dual influence of environmental pollution and ecological damage, the green principles of civil law and environmental law can be better coordinated and developed. In the past, environmental pollution and ecological damage in the author's country were very serious. Hence, they designed and experimented with data extraction technology and environmental big data sets. A distribution model investigates it. Experiments show the following: (1) The system is developed from big data and can fully reflect the ecological environment of all parts of the country. Finally, it is concluded that the author's country's environmental pollution and ecological damage are very serious. (2) According to the experimental data of the figures and tables, it is concluded that the cooperation and coordination relationship between the green principles of civil law and environmental law not only has a protective effect on the ecological environment but also increases the economy of society and people. With the continuous updating and coordination of environmental laws and green prototypes, the author's country's environmental pollutants are significantly declining. The author believes that in the future, the country's ecological environment will become better, and the green principles of civil law will be more closely related to environmental law. The country's environmental pollution and people's lives are becoming more closely related. To better solve environmental problems, we have introduced the green principles of civil law and environmental law. It makes people's quality of life and the economy better. The main significance of the study is to use the method with the least damage to the environment to obtain the maximum economic benefit to achieve long-term sustainable development.

Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model

Environmental pollution is a problem of universal concern throughout the globe. The development of real estate industry not only consumes huge resources, but also has close ties with high-consumption industries such as the construction industry. However, previous studies have rarely explored the impact of real estate development on environmental pollution. Therefore, this paper employs the entropy method to construct a comprehensive index of environmental pollution based on panel data of 31 provinces in China from 2000 to 2017, and empirically examines the impact of real estate development on environmental pollution. This article uses real estate investment to measure the development of the real estate industry. In view of the high spatial autocorrelation of environmental pollution, this paper selects a spatial econometric model. The empirical study found that: (1) By using the Spatial Durbin Model, real estate development has an inverted U-shaped impact on environmental pollution. Meanwhile, most cities have not yet reached the turning point; that is, with the continuous development of the real estate industry, environmental pollution will continue to increase. (2) Further regional heterogeneity found that the inverted U-shaped relationship still exists in coastal and inland areas. (3) Finally, this article used the Spatial Mediation Model to explain the nonlinear impact of real estate development on environmental pollution, with two important mediating variables: population density and industrial structure. Through the above analysis, it can be observed that real estate development has a significant impact on environmental pollution. Thus, the country and the government can reduce environmental pollution by improving the investment structure, using environmentally friendly building materials, guiding population flow and promoting industrial upgrading.

Impact of local air quality management policies on emergency hospitalisations for respiratory conditions in the North West Coast region of England: a longitudinal controlled ecological study

Background

Air quality is monitored at a local level in the UK as part of the Local Air Quality Management (LAQM) system. If air quality objectives within an area are not achieved an Air Quality Management Area (AQMA) is declared and action plan developed. The efficacy of this system in reducing air pollution has increasingly come into question, however very little is known about its impact on health or health inequalities. We therefore investigated the effect of declaring an AQMA on emergency hospitalisations for respiratory conditions in the North West Coast region of England, and examined whether the effect differed between more compared to less deprived neighbourhoods.

Methods

This longitudinal controlled ecological study analysed neighbourhoods located within or touching the boundaries of AQMAs declared in the North West Coast region between 2006 and 2016. Each of these intervention neighbourhoods were matched with five control neighbourhoods which had never been located within/touching an AQMA boundary. Difference-in-differences methods were used to compare the change in hospitalisation rates in the intervention neighbourhoods to the change in hospitalisation rates in the matched control neighbourhoods, before and after the declaration of an AQMA.

Results

In total, 108 intervention neighbourhoods and 540 control neighbourhoods were analysed over the period 2005–2017, giving a total sample size of 8424 neighbourhood-years. Emergency hospitalisations for respiratory conditions decreased in the intervention neighbourhoods by 158 per 100,000 per year [95% CI 90 to 227] after an AQMA was declared relative to the control neighbourhoods. There was a larger decrease in hospitalisation rates following the declaration of an AQMA in more compared to less income deprived neighbourhoods.

Conclusions

Our results suggest the LAQM system has contributed to a reduction in emergency hospitalisations for respiratory conditions, and may represent an effective strategy to reduce inequalities in health. These findings highlight the importance of measuring the success of air quality policies not just in terms of air pollution but also in terms of population health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-021-01598-w.

Is Technological Progress Selective for Multiple Pollutant Emissions?

Current research on technological progress does not focus on whether there is a biased selection of technological progress based on the resulting pollutant emissions and the emission reduction effect. This paper measures green total factor productivity for 30 provinces in China from 2004–2018 and tests whether technological progress is selectively biased towards the pollutants emitted. The results find a selective bias of technological progress on pollutant emissions, and there is also heterogeneity in the selective bias across regions. The current level of technological progress is on the right side of the inverted U-shaped inflection point for SO₂ and PM_2.5 and the left side of the inverted U-shaped inflection point for CO₂. The improvement of technological progress can reduce the emissions of SO₂ and PM_2.5. Still, the results indicate that the reduction effect of these two pollutants originates from the treatment process rather than reducing the source of the production side. The inability of technological advancement to reduce CO₂ emissions suggests some carbon lock-in in China’s technological advancement. The Chinese government should increase the proportion of new energy applications and reduce the production methods of polluting industries to reduce pollutants effectively.

Community Environment Perception on Depression: The Mediating Role of Subjective Social Class

Depression has become a major social issue of global concern, which has seriously threatened the quality of an individual’s life. Although the relationship between community environment and depression has aroused heated debate, the empirical research on the relationship between community environment perception and public depression is still relatively insufficient. Data for this study are from China Family Panel Studies in 2016, which were conducted by the institute of Social Science Survey, Peking University. This paper has tested group differences in the influence of community environment on public depression, as well as the mediating role of subjective social class between community environment perception and depression, so as to further explore the social psychological effect of community environment. The empirical study found that there are group differences in the impacts of community environment perception on depression. Specifically, men, rural residents, and people aged 60 and under are more likely to be depressed which were affected by the perception of community environment. Furthermore, we have found that the subjective social class can partly mediate community environment perception and depression. That is to say, the perception of community environment can induce depression by influencing the individual’s subjective social class. Among them, community living environment and community public facilities have the greatest impact, community emotional attachment and community security situation have the second impact, and neighborhood mutual aid and neighborhood relationship have the least impact. In other words, the community environment is deeply endowed with a social psychological effect. To ameliorate the public’s depression, it is necessary to consider the construction of community physical environment and the cultivation of harmonious community culture as powerful measures not to be ignored. In short, the important role of community environmental intervention in alleviating the public’s depression caused by social class cognition deserves attention.

Spatial and temporal variations in indoor radon concentrations in Pennsylvania, USA from 1988 to 2018

Indoor radon poses one of the most significant environmental threats to public health as it is the second leading cause of lung cancer in the United States. Developing a more thorough understanding of the factors that affect radon concentrations is key for developing risk maps, identifying where testing should be a priority, and education about indoor radon exposure. The objectives of this study are to investigate seasonal and annual variation of indoor radon concentrations in Pennsylvania, USA from 1988 to 2018, to explore the hotspot areas for high indoor radon concentrations, and to analyze the association with various factors such as weather conditions, housing types, and floor levels. Based on a total of 1,808,294 radon tests conducted from 1988 to 2018, we found that 61% of the area (by zip codes), 557,869 tests conducted in the basement and 49,141 tests conducted on the ground floor in homes in Pennsylvania had higher radon levels than the U.S. EPA action level concentration of 148 Bq/m³ (equivalent to 4 pCi/L). Winter and fall had significantly higher indoor radon concentrations than summer and spring. Case studies conducted in Pittsburgh, Philadelphia, and Harrisburg showed that there was no significant correlation of daily temperature, precipitation, or relative humidity with indoor radon concentration on the day a radon test occurred.

Cost-effectiveness of radon remediation programmes in the UK in the 2020s

Radon, a gaseous radioactive decay product of naturally-occurring uranium is widely distributed in the environment in rocks and soils and, in certain circumstances, can accumulate in the built environment. Initial studies confirmed a direct link between exposure to both radon gas and its short-lived radioactive progeny, and increased lung-cancer incidence, and demonstrated that radon levels in domestic housing can be sufficiently high to expose occupants to increased risk of lung-cancer. Subsequent studies worldwide have shown that it is cost-effective to detect and reduce domestic radon levels in order to reduce this risk. Recent advances in the early detection of lung-cancer, coupled with the development of improved treatment procedures, have progressively improved survival from the disease, with the numbers surviving at 5 years doubling over recent years, during which period the real costs of lung cancer treatment have risen by around 30%. In the meantime, however, in addition to radon and tobacco-smoke, other airborne pollutants have been identified as risk-factors for lung-cancer. This paper reviews both these actual developments and anticipated future trends, and concludes that since these advances in diagnosis and treatment of lung-cancer have had only a modest effect on cost-effectiveness, it is still important to conduct radon monitoring and remediation programmes. While the general increase in life-expectancy improves the cost-effectiveness of radon remediation programmes significantly, reducing tobacco-smoking incidence reduces that cost-effectiveness but with the overall benefit of reducing radon-related lung-cancers. The challenge remains of encouraging affected householders to remediate their homes to reduce radon levels.

Relationship of economic development, family income and health status in China: The moderating role of environmental pollution perception

Based on the matched data set of the 2013 Chinese General Social Survey and the gross domestic product per capita data extracted from China Statistical Yearbook 2013, this study used hierarchical regression analysis and structural equation models to examine whether environmental pollution perception would moderate the association between economic development and health status. Results revealed that economic development had a mediating effect via family income on health status. A moderated actor effect showed higher level of pollution perception weakens the relationship between family income and health status. Our findings suggested that appropriate environmental regulations should be implemented to sustain healthy economic growth in China.

Advances in mapping population and demographic characteristics at small-area levels

Temporally and spatially highly resolved information on population characteristics, including demographic profile (e.g. age and sex), ethnicity and socio-economic status (e.g. income, occupation, education), are essential for observational health studies at the small-area level. Time-relevant population data are critical as denominators for health statistics, analytics and epidemiology, to calculate rates or risks of disease. Demographic and socio-economic characteristics are key determinants of health and important confounders in the relationship between environmental contaminants and health. In many countries, census data have long been the source of small-area population denominators and confounder information. A strength of the traditional census model has been its careful design and high level of population coverage, allowing high-quality detailed data to be released for small areas periodically, e.g. every 10 years. The timeliness of data, however, becomes a challenge when temporally and spatially highly accurate annual (or even more frequent) data at high spatial resolution are needed, for example, for health surveillance and epidemiological studies. Additionally, the approach to collecting demographic population information is changing in the era of open and big data and may eventually evolve to using combinations of administrative and other data, supplemented by surveys. We discuss different approaches to address these challenges including (i) the US American Community Survey, a rolling sample of the US population census, (ii) the use of spatial analysis techniques to compile temporally and spatially high-resolution demographic data and (iii) the use of administrative and big data sources as proxies for demographic characteristics.

Small-area methods for investigation of environment and health

Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographical scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast-growing computational capabilities, permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but has also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases.

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.

Radon, an invisible killer in Canadian homes: perceptions of Ottawa-Gatineau residents

OBJECTIVES

Canadians have reason to care about indoor air quality as they spend over 90% of the time indoors. Although indoor radon causes more deaths than any other environmental hazard, only 55% of Canadians have heard of it, and of these, 6% have taken action. The gap between residents' risk awareness and adoption of actual protective behaviour presents a challenge to public health practitioners. Residents' perception of the risk should inform health communication that targets motivation for action. In Canada, research about the public perception of radon health risk is lacking. The aim of this study was to describe residents' perceptions of radon health risks and, applying a theoretical lens, evaluate how perceptions correlate with protection behaviours.

METHODS

We conducted a mixed online and face-to-face survey (N = 557) with both homeowners and tenants in Ottawa-Gatineau census metropolitan area. Descriptive, correlation, and regression analyses addressed the research questions.

RESULTS

Compared to the gravity of the risk, public perception remained low. While 32% of residents expressed some concern about radon health risk, 12% of them tested and only 3% mitigated their homes for radon. Residents' perceptions of the probability and severity of the risk, social influence, care for children, and smoking in home correlated significantly with their intention to test; these factors also predicted their behaviours for testing and mitigation.

CONCLUSION

Health risk communication programs need to consider the affective aspects of risk perception in addition to rational cognition to improve protection behaviours. A qualitative study can explore the reasons behind the gap between testing and mitigation.

Exploring the relationship between social deprivation and domestic radon levels in the East Midlands, UK

The natural radioactive gas radon is widely present in the built environment and at high concentrations is associated with enhanced risk of lung-cancer. This risk is significantly enhanced for habitual smokers. Although populations with higher degrees of social deprivation are frequently exposed to higher levels of many health-impacting pollutants, a recent study suggests that social deprivation in the UK is associated with lower radon concentrations. The analysis reported here, based on published data on social deprivation and domestic radon in urban and rural settings in the English East Midlands, identifies a weak association between increasing deprivation and lower radon areas. This is attributed to the evolution of the major urban centres on low-permeability, clay-rich alluvial soils of low radon potential. In addition, the predominance of high-rise dwellings in towns and cities will further reduce average exposure to radon in populations in those areas.

Spatial Relationships between Urban Structures and Air Pollution in Korea

Urban structures facilitate human activities and interactions but are also a main source of air pollutants; hence, investigating the relationship between urban structures and air pollution is crucial. The lack of an acceptable general model poses significant challenges to investigations on the underlying mechanisms, and this gap fuels our motivation to analyze the relationships between urban structures and the emissions of four air pollutants, including nitrogen oxides, sulfur oxides, and two types of particulate matter, in Korea. We first conduct exploratory data analysis to detect the global and local spatial dependencies of air pollutants and apply Bayesian spatial regression models to examine the spatial relationship between each air pollutant and urban structure covariates. In particular, we use population, commercial area, industrial area, park area, road length, total land surface, and gross regional domestic product per person as spatial covariates of interest. Except for park area and road length, most covariates have significant positive relationships with air pollutants ranging from 0 to 1, which indicates that urbanization does not result in a one-to-one negative influence on air pollution. Findings suggest that the government should consider the degree of urban structures and air pollutants by region to achieve sustainable development.

Born to be Wise: a population registry data linkage protocol to assess the impact of modifiable early-life environmental exposures on the health and development of children

INTRODUCTION

Deficiencies in childhood development is a major global issue and inequalities are large. The influence of environmental exposures on childhood development is currently insufficiently explored. This project will analyse the impact of various modifiable early life environmental exposures on different dimensions of childhood development.

METHODS

Born to be Wise will study a Canadian cohort of approximately 34 000 children who have completed an early development test at the age of 5. Land use regression models of air pollution and spatially defined noise models will be linked to geocoded data on early development to analyse any harmful effects of these exposures. The potentially beneficial effect on early development of early life exposure to natural environments, as measured by fine-grained remote sensing data and various land use indexes, will also be explored. The project will use data linkages and analyse overall and age-specific impact, including variability depending on cumulative exposure by assigning time-weighted exposure estimates and by studying subsamples who have changed residence and exposure. Potentially moderating effects of natural environments on air pollution or noise exposures will be studied by mediation analyses. A matched case-control design will be applied to study moderating effects of natural environments on the association between low socioeconomic status and early development. The main statistical approach will be mixed effects models, applying a specific software to deal with multilevel random effects of nested data. Extensive confounding control will be achieved by including data on a range of detailed health and sociodemographic variables.

ETHICS AND DISSEMINATION

The study protocol has been ethically approved by the Behavioural Research Ethics Board at the University of British Columbia. The findings will be published in peer-reviewed journals and presented at scholarly conferences. Through stakeholder engagement, the results will also reach policy and a broader audience.

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.

Neighborhood deprivation and biomarkers of health in Britain: the mediating role of the physical environment

BACKGROUND

Neighborhood deprivation has been consistently linked to poor individual health outcomes; however, studies exploring the mechanisms involved in this association are scarce. The objective of this study was to investigate whether objective measures of the physical environment mediate the association between neighborhood socioeconomic deprivation and biomarkers of health in Britain.

METHODS

We linked individual-level biomarker data from Understanding Society: The UK Household Longitudinal Survey (2010-2012) to neighborhood-level data from different governmental sources. Our outcome variables were forced expiratory volume in 1 s (FEV1%; n=16,347), systolic blood pressure (SBP; n=16,846), body mass index (BMI; n=19,417), and levels of C-reactive protein (CRP; n=11,825). Our measure of neighborhood socioeconomic deprivation was the Carstairs index, and the neighborhood-level mediators were levels of air pollutants (sulphur dioxide [SO2], particulate matter [PM10], nitrogen dioxide [NO2], and carbon monoxide [CO]), green space, and proximity to waste and industrial facilities. We fitted a multilevel mediation model following a multilevel structural equation framework in MPlus v7.4, adjusting for age, gender, and income.

RESULTS

Residents of poor neighborhoods and those exposed to higher pollution and less green space had worse health outcomes. However, only SO2 exposure significantly and partially mediated the association between neighborhood socioeconomic deprivation and SBP, BMI, and CRP.

CONCLUSION

Reducing air pollution exposure and increasing access to green space may improve population health but may not decrease health inequalities in Britain.

Public health air pollution impacts of pathway options to meet the 2050 UK Climate Change Act target: a modelling study

Background

The UK’sClimate Change Act 2008(CCA; Great Britain.Climate Change Act 2008. Chapter 27. London: The Stationery Office; 2008) requires a reduction of 80% in carbon dioxide-equivalent emissions by 2050 on a 1990 base. This project quantified the impact of air pollution on health from four scenarios involving particulate matter of ≤ 2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Two scenarios met the CCA target: one with limited nuclear power build (nuclear replacement option; NRPO) and one with no policy constraint on nuclear (low greenhouse gas). Another scenario envisaged no further climate actions beyond those already agreed (‘baseline’) and the fourth kept 2011 concentrations constant to 2050 (‘2011’).

Methods

The UK Integrated MARKAL–EFOM System (UKTM) energy system model was used to develop the scenarios and produce projections of fuel use; these were used to produce air pollutant emission inventories for Great Britain (GB) for each scenario. The inventories were then used to run the Community Multiscale Air Quality model ‘air pollution model’ to generate air pollutant concentration maps across GB, which then, combined with relationships between concentrations and health outcomes, were used to calculate the impact on health from the air pollution emitted in each scenario. This is a significant improvement on previous health impact studies of climate policies, which have relied on emissions changes. Inequalities in exposure in different socioeconomic groups were also calculated, as was the economic impact of the pollution emissions.

Results

Concentrations of NO2declined significantly because of a high degree of electrification of the GB road transport fleet, although the NRPO scenario shows large increases in oxides of nitrogen emissions from combined heat and power (CHP) sources. Concentrations of PM2.5show a modest decrease by 2050, which would have been larger if it had not been for a significant increase in biomass (wood burning) use in the two CCA scenarios peaking in 2035. The metric quantifying long-term exposure to O3is projected to decrease, while the important short-term O3exposure metric increases. Large projected increases in future GB vehicle kilometres lead to increased non-exhaust PM2.5and particulate matter of ≤ 10 µm emissions. The two scenarios which achieve the CCA target resulted in more life-years lost from long-term exposures to PM2.5than in the baseline scenario. This is an opportunity lost and arises largely from the increase in biomass use, which is projected to peak in 2035. Reduced long-term exposures to NO2lead to many more life-years saved in the ‘CCA-compliant’ scenarios, but the association used may overestimate the effects of NO2itself. The more deprived populations are estimated currently to be exposed to higher concentrations than those less deprived, the contrast being largest for NO2. Despite reductions in concentrations in 2050, the most socioeconomically deprived are still exposed to higher concentrations than the less deprived.

Limitations

Modelling of the atmosphere is always uncertain; we have shown the model to be acceptable through comparison with observations. The necessary complexity of the modelling system has meant that only a small number of scenarios were run.

Conclusions

We have established a system which can be used to explore a wider range of climate policy scenarios, including more European and global scenarios as well as local measures. Future work could explore wood burning in more detail, in terms of the sectors in which it might be burned and the spatial distribution of this across the UK. Further analyses of options for CHP could also be explored. Non-exhaust emissions from road transport are an important source of particles and emission factors are uncertain. Further research on this area coupled with our modelling would be a valuable area of research.

Funding

The National Institute for Health Research Public Health Research programme.

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.

Heterogeneity in the Relationship between Disinfection By-Products in Drinking Water and Cancer: A Systematic Review

The epidemiological evidence demonstrating the effect of disinfection by-products (DBPs) from drinking water on colon and rectal cancers is well documented. However, no systematic assessment has been conducted to assess the potential effect measure modification (EMM) in the relationship between DBPs and cancer. The objective of this paper is to conduct a systematic literature review to determine the extent to which EMM has been assessed in the relationship between DBPs in drinking water in past epidemiological studies. Selected articles (n = 19) were reviewed, and effect estimates and covariates that could have been used in an EMM assessment were gathered. Approximately half of the studies assess EMM (n = 10), but the majority of studies only estimate it relative to sex subgroups (n = 6 for bladder cancer and n = 2 both for rectal and colon cancers). Although EMM is rarely assessed, several variables that could have a potential modification effect are routinely collected in these studies, such as socioeconomic status or age. The role of environmental exposures through drinking water can play an important role and contribute to cancer disparities. We encourage a systematic use of subgroup analysis to understand which populations or territories are more vulnerable to the health impacts of DBPs.

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.

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.

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.

An Overview of Literature Topics Related to Current Concepts, Methods, Tools, and Applications for Cumulative Risk Assessment (2007-2016)

Cumulative risk assessments (CRAs) address combined risks from exposures to multiple chemical and nonchemical stressors and may focus on vulnerable communities or populations. Significant contributions have been made to the development of concepts, methods, and applications for CRA over the past decade. Work in both human health and ecological cumulative risk has advanced in two different contexts. The first context is the effects of chemical mixtures that share common modes of action, or that cause common adverse outcomes. In this context two primary models are used for predicting mixture effects, dose addition or response addition. The second context is evaluating the combined effects of chemical and nonchemical (e.g., radiation, biological, nutritional, economic, psychological, habitat alteration, land-use change, global climate change, and natural disasters) stressors. CRA can be adapted to address risk in many contexts, and this adaptability is reflected in the range in disciplinary perspectives in the published literature. This article presents the results of a literature search and discusses a range of selected work with the intention to give a broad overview of relevant topics and provide a starting point for researchers interested in CRA applications.

Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

Reducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice.

Modelling collinear and spatially correlated data

In this work we present a statistical approach to distinguish and interpret the complex relationship between several predictors and a response variable at the small area level, in the presence of (i) high correlation between the predictors and (ii) spatial correlation for the response. Covariates which are highly correlated create collinearity problems when used in a standard multiple regression model. Many methods have been proposed in the literature to address this issue. A very common approach is to create an index which aggregates all the highly correlated variables of interest. For example, it is well known that there is a relationship between social deprivation measured through the Multiple Deprivation Index (IMD) and air pollution; this index is then used as a confounder in assessing the effect of air pollution on health outcomes (e.g. respiratory hospital admissions or mortality). However it would be more informative to look specifically at each domain of the IMD and at its relationship with air pollution to better understand its role as a confounder in the epidemiological analyses. In this paper we illustrate how the complex relationships between the domains of IMD and air pollution can be deconstructed and analysed using profile regression, a Bayesian non-parametric model for clustering responses and covariates simultaneously. Moreover, we include an intrinsic spatial conditional autoregressive (ICAR) term to account for the spatial correlation of the response variable.

Neighbourhood walkability, road density and socio-economic status in Sydney, Australia

BACKGROUND

Planning and transport agencies play a vital role in influencing the design of townscapes, travel modes and travel behaviors, which in turn impact on the walkability of neighbourhoods and residents' physical activity opportunities. Optimising neighbourhood walkability is desirable in built environments, however, the population health benefits of walkability may be offset by increased exposure to traffic related air pollution. This paper describes the spatial distribution of neighbourhood walkability and weighted road density, a marker for traffic related air pollution, in Sydney, Australia. As exposure to air pollution is related to socio-economic status in some cities, this paper also examines the spatial distribution of weighted road density and walkability by socio-economic status (SES).

METHODS

We calculated walkability, weighted road density (as a measure of traffic related air pollution) and SES, using predefined and validated measures, for 5858 Sydney neighbourhoods, representing 3.6 million population. We overlaid tertiles of walkability and weighted road density to define "sweet-spots" (high walkability-low weighted road density), and "sour- spots" (low walkability-high weighted road density) neighbourhoods. We also examined the distribution of walkability and weighted road density by SES quintiles.

RESULTS

Walkability and weighted road density showed a clear east-west gradient across the region. Our study found that only 4 % of Sydney's population lived in sweet-spot" neighbourhoods with high walkability and low weighted road density (desirable), and these tended to be located closer to the city centre. A greater proportion of neighbourhoods had health limiting attributes of high weighted road density or low walkability (about 20 % each), and over 5 % of the population lived in "sour-spot" neighbourhoods with low walkability and high weighted road density (least desirable). These neighbourhoods were more distant from the city centre and scattered more widely. There were no linear trends between walkability/weighted road density and neighbourhood SES.

CONCLUSIONS

Our walkability and weighted road density maps and associated analyses by SES can help identify neighbourhoods with inequalities in health-promoting or health-limiting environments. Planning agencies should seek out opportunities for increased neighbourhood walkability through improved urban development and transport planning, which simultaneously minimizes exposure to traffic related air pollution.

Assessment of environmental injustice in Korea using synthetic air quality index and multiple indicators of socioeconomic status: A cross-sectional study

Despite the existence of the universal right to a healthy environment, the right is being violated in some populations. The objective of the current study is to verify environmental discrimination associated with socioeconomic status in Korea, using synthetic air quality index and multiple indicators of socioeconomic status. The concentrations of NO₂(nitrogen dioxide), CO (carbon monoxide), SO₂(sulfur dioxide), PM10 (particulate matter with an aerodynamic diameter <10 μm), and O₃(ozone) in ambient air were integrated into a synthetic air quality index. Socioeconomic status was measured at individual level (income, education, number of household members, occupation, and National Basic Livelihood status) and area level (neighborhood index). The neighborhood index was calculated in the finest administrative unit (municipality) by performing standardization and integration of municipality-level data of the following: number of families receiving National Basic Livelihood, proportion of people engaged in an elementary occupation, population density, and number of service industries. Each study participant was assigned a neighborhood index value of the municipality in which they reside. Six regression models were generated to analyze the relationship between socioeconomic status and overall air pollution. All models were adjusted with sex, age, and smoking status. Stratification was conducted by residency (urban/rural). Moran's I was calculated to identify spatial clusters, and adjusted regression analysis was conducted to account for spatial autocorrelation. Results showed that people with higher neighborhood index, people living with smaller number of family members, and people with no education lived in municipalities with better overall air quality. The association differed by residency in some cases, and consideration of spatial autocorrelation altered the association. This study gives strength to the idea that environmental discrimination exists in some socioeconomic groups in Korea, and that residency and spatial autocorrelation must be considered in order to fully understand environmental disparities.

IMPLICATIONS

This is the first study that provides the possible evidence of the environmental injustice in Korea using air quality index. The findings suggested that air quality index was negatively correlated with several important socioeconomic status measured at either individual or area level. The main implication of this paper, therefore, is to provide another insight to environmental policy makers to consider environmental injustice problem into community intervention for resolving the public health problems by air pollution.

Characterizing Urban Household Waste Generation and Metabolism Considering Community Stratification in a Rapid Urbanizing Area of China

The relationship between social stratification and municipal solid waste generation remains uncertain under current rapid urbanization. Based on a multi-object spatial sampling technique, we selected 191 households in a rapidly urbanizing area of Xiamen, China. The selected communities were classified into three types: work-unit, transitional, and commercial communities in the context of housing policy reform in China. Field survey data were used to characterize household waste generation patterns considering community stratification. Our results revealed a disparity in waste generation profiles among different households. The three community types differed with respect to family income, living area, religious affiliation, and homeowner occupation. Income, family structure, and lifestyle caused significant differences in waste generation among work-unit, transitional, and commercial communities, respectively. Urban waste generation patterns are expected to evolve due to accelerating urbanization and associated community transition. A multi-scale integrated analysis of societal and ecosystem metabolism approach was applied to waste metabolism linking it to particular socioeconomic conditions that influence material flows and their evolution. Waste metabolism, both pace and density, was highest for family structure driven patterns, followed by lifestyle and income driven. The results will guide community-specific management policies in rapidly urbanizing areas.

Investigating social inequalities in exposure to drinking water contaminants in rural areas

Few studies have assessed social inequalities in exposure to drinking water contaminants. This study explores this issue in 593 rural municipalities of Québec, Canada. Quartiles of an ecological composite deprivation index were used as a proxy of socioeconomic status. Total trihalomethanes (TTHMs) and lead were chosen as proxies of chemical drinking water quality. The results show that the majority of deprived rural municipalities apply no treatment to their water (26%) or use a basic treatment (51%), whereas a relative majority of the wealthiest municipalities (40%) use advanced treatment. The proportion of municipalities having important lead (>5 μg/L) levels is highest in most deprived municipalities. Moreover, most deprived municipalities have a higher risk of high tap lead levels (RR = 1.33; 95%CI: 1.30, 1.36). Conversely, most deprived municipalities have a lower risk of high TTHMs levels (RR = 0.78; 95%CI: 0.69, 0.86). These findings suggest an environmental inequality in drinking water contaminants distribution in rural municipalities.

Socioeconomic Disparities and Air Pollution Exposure: a Global Review

The existing reviews and meta-analyses addressing unequal exposure of environmental hazards on certain populations have focused on several environmental pollutants or on the siting of hazardous facilities. This review updates and contributes to the environmental inequality literature by focusing on ambient criteria air pollutants (including NOx), by evaluating studies related to inequality by socioeconomic status (as opposed to race/ethnicity) and by providing a more global perspective. Overall, most North American studies have shown that areas where low-socioeconomic-status (SES) communities dwell experience higher concentrations of criteria air pollutants, while European research has been mixed. Research from Asia, Africa, and other parts of the world has shown a general trend similar to that of North America, but research in these parts of the world is limited.

Predictors of Indoor Radon Concentrations in Pennsylvania, 1989-2013

BACKGROUND

Radon is the second-leading cause of lung cancer worldwide. Most indoor exposure occurs by diffusion of soil gas. Radon is also found in well water, natural gas, and ambient air. Pennsylvania has high indoor radon concentrations; buildings are often tested during real estate transactions, with results reported to the Department of Environmental Protection (PADEP).

OBJECTIVES

We evaluated predictors of indoor radon concentrations.

METHODS

Using first-floor and basement indoor radon results reported to the PADEP between 1987 and 2013, we evaluated associations of radon concentrations (natural log transformed) with geology, water source, building characteristics, season, weather, community socioeconomic status, community type, and unconventional natural gas development measures based on drilled and producing wells.

RESULTS

Primary analysis included 866,735 first measurements by building, with the large majority from homes. The geologic rock layer on which the building sat was strongly associated with radon concentration (e.g., Axemann Formation, median = 365 Bq/m3, IQR = 167-679 vs. Stockton Formation, median = 93 Bq/m3, IQR = 52-178). In adjusted analysis, buildings using well water had 21% higher concentrations (β = 0.191, 95% CI: 0.184, 0.198). Buildings in cities (vs. townships) had lower concentrations (β = -0.323, 95% CI: -0.333, -0.314). When we included multiple tests per building, concentrations declined with repeated measurements over time. Between 2005 and 2013, 7,469 unconventional wells were drilled in Pennsylvania. Basement radon concentrations fluctuated between 1987 and 2003, but began an upward trend from 2004 to 2012 in all county categories (p < 0.001), with higher levels in counties having ≥ 100 drilled wells versus counties with none, and with highest levels in the Reading Prong.

CONCLUSIONS

Geologic unit, well water, community, weather, and unconventional natural gas development were associated with indoor radon concentrations. Future studies should include direct environmental measurement of radon, as well as building features unavailable for this analysis.

CITATION

Casey JA, Ogburn EL, Rasmussen SG, Irving JK, Pollak J, Locke PA, Schwartz BS. 2015. Predictors of indoor radon concentrations in Pennsylvania, 1989-2013. Environ Health Perspect 123:1130-1137; http://dx.doi.org/10.1289/ehp.1409014.

Air pollution in moderately polluted urban areas: How does the definition of "neighborhood" impact exposure assessment?

Environmental health studies commonly quantify subjects' pollution exposure in their neighborhood. How this neighborhood is defined can vary, however, leading to different approaches to quantification whose impacts on exposure levels remain unclear. We explore the relationship between neighborhood definition and exposure assessment. NO2, benzene, PM10 and PM2.5 exposure estimates were computed in the vicinity of 10,825 buildings using twelve exposure assessment techniques reflecting different definitions of "neighborhood". At the city scale, its definition does not significantly influence exposure estimates. It does impact levels at the building scale, however: at least a quarter of the buildings' exposure estimates for a 400 m buffer differ from the estimated 50 m buffer value (±1.0 μg/m(3) for NO2, PM10 and PM2.5; and ±0.05 μg/m(3) for benzene). This variation is significantly related to the definition of neighborhood. It is vitally important for investigators to understand the impact of chosen assessment techniques on exposure estimates.

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.

Trihalomethanes in public drinking water and stillbirth and low birth weight rates: an intervention study

During 2003-2004, United Utilities water company in North West England introduced enhanced coagulation (EC) to four treatment works to mitigate disinfection by-product (DBP) formation. This enabled examination of the relation between DBPs and birth outcomes whilst reducing socioeconomic confounding. We compared stillbirth, and low and very low birth weight rates three years before (2000-2002) with three years after (2005-2007) the intervention, and in relation to categories of THM change. We created exposure metrics for EC and trihalomethane (THM) concentration change (n=258 water zones). We linked 429,599 live births and 2279 stillbirths from national birth registers to the water zone at birth. We used Poisson regression to model the differences in birth outcome rates with an interaction between before/after the intervention and EC or THM change. EC treatment reduced chloroform concentrations more than non-treatment (mean -29.7 µg/l vs. -14.5 µg/l), but not brominated THM concentrations. Only 6% of EC water zones received 100% EC water, creating exposure misclassification concerns. EC intervention was not associated with a statistically significant reduction in birth outcome rates. Areas with the highest chloroform decrease (30 - 65 μg/l) had the greatest percentage decrease in low -9 % (-12, -5) and very low birth weight -16% (-24, -8) rates. The interaction between before/after intervention and chloroform change was statistically significant only for very low birth weight, p=0.02. There were no significant decreases in stillbirth rates. In a novel approach for studying DBPs and adverse reproductive outcomes, the EC intervention to reduce DBPs did not affect birth outcome rates. However, a measured large decrease in chloroform concentrations was associated with statistically significant reductions in very low birth weight rates.

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.

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.

Trends and inequalities in cardiovascular disease mortality across 7932 English electoral wards, 1982-2006: Bayesian spatial analysis

Background Cardiovascular disease (CVD) mortality has more than halved in England since the 1980s, but there are few data on small-area trends. We estimated CVD mortality by ward in 5-year intervals between 1982 and 2006, and examined trends in relation to starting mortality, region and community deprivation.

Methods We analysed CVD death rates using a Bayesian spatial technique for all 7932 English electoral wards in consecutive 5-year intervals between 1982 and 2006, separately for men and women aged 30–64 years and ≥65 years.

Results Age-standardized CVD mortality declined in the majority of wards, but increased in 186 wards for women aged ≥65 years. The decline was larger where starting mortality had been higher. When grouped by deprivation quintile, absolute inequality between most- and least-deprived wards narrowed over time in those aged 30–64 years, but increased in older adults; relative inequalities worsened in all four age–sex groups. Wards with high CVD mortality in 2002–06 fell into two groups: those in and around large metropolitan cities in northern England that started with high mortality in 1982–86 and could not ‘catch up’, despite impressive declines, and those that started with average or low mortality in the 1980s but ‘fell behind’ because of small mortality reductions.

Conclusions Improving population health and reducing health inequalities should be treated as related policy and measurement goals. Ongoing analysis of mortality by small area is essential to monitor local effects on health and health inequalities of the public health and healthcare systems.

Small-area analysis of social inequalities in residential exposure to road traffic noise in Marseilles, France

BACKGROUND

Few studies have focused on the social inequalities associated with environmental noise despite its significant potential health effects. This study analysed the associations between area socio-economic status (SES) and potential residential exposure to road traffic noise at a small-area level in Marseilles, second largest city in France.

METHODS

We calculated two potential road noise exposure indicators (PNEI) at the census block level (for 24-h and night periods), with the noise propagation prediction model CadnaA. We built a deprivation index from census data to estimate SES at the census block level. Locally estimated scatterplot smoothing diagrams described the associations between this index and PNEIs. Since the extent to which coefficient values vary between standard regression models and spatial methods are sensitive to the specific spatial model, we analysed these associations further with various regression models controlling for spatial autocorrelation and conducted sensitivity analyses with different spatial weight matrices.

RESULTS

We observed a non-linear relation between the PNEIs and the deprivation index: exposure levels were highest in the intermediate categories. All the spatial models led to a better fit and more or less pronounced reductions of the regression coefficients; the shape of the relations nonetheless remained the same.

CONCLUSION

Finding the highest noise exposure in midlevel deprivation areas was unexpected, given the general literature on environmental inequalities. It highlights the need to study the diversity of the patterns of environmental inequalities across various economic, social and cultural contexts. Comparative studies of environmental inequalities are needed, between regions and countries, for noise and other pollutants.

Racial and ethnic disparities in hospital care resulting from air pollution in excess of federal standards

This study investigates racial and ethnic disparities in hospital admission and emergency room visit rates resulting from exposure to ozone and fine particulate matter levels in excess of federal standards ("excess attributable risk"). We generate zip code-level ambient pollution exposures and hospital event rates using state datasets, and use pollution impact estimates in the epidemiological literature to calculate excess attributable risk for racial/ethnic groups in California over 2005-2007. We find that black residents experienced roughly 2.5 times the excess attributable risk of white residents. Hispanic residents were exposed to the highest levels of pollution, but experienced similar excess attributable risk to whites. Asian/Pacific Islander residents had substantially lower excess attributable risk compared to white. We estimate the distinct contributions of exposure and other factors to these results, and find that factors other than exposure can be critical determinants of pollution-related disparities.

Socioeconomic status and exposure to disinfection by-products in drinking water in Spain

BACKGROUND

Disinfection by-products in drinking water are chemical contaminants that have been associated with cancer and other adverse effects. Exposure occurs from consumption of tap water, inhalation and dermal absorption.

METHODS

We determined the relationship between socioeconomic status and exposure to disinfection by-products in 1271 controls from a multicentric bladder cancer case-control study in Spain. Information on lifetime drinking water sources, swimming pool attendance, showering-bathing practices, and socioeconomic status (education, income) was collected through personal interviews.

RESULTS

The most highly educated subjects consumed less tap water (57%) and more bottled water (33%) than illiterate subjects (69% and 17% respectively, p-value = 0.003). These differences became wider in recent time periods. The time spent bathing or showering was positively correlated with attained educational level (p < 0.001). Swimming pool attendance was more frequent among highly educated subjects compared to the illiterate (odds ratio = 3.4; 95% confidence interval 1.6-7.3).

CONCLUSIONS

The most highly educated subjects were less exposed to chlorination by-products through ingestion but more exposed through dermal contact and inhalation in pools and showers/baths. Health risk perceptions and economic capacity may affect patterns of water consumption that can result in differences in exposure to water contaminants.

Social factors associated with nitrogen dioxide (NO2) exposure during pregnancy: the INMA-Valencia project in Spain

Numerous studies have focused on the effects of exposure to air pollution on health; however, certain subsets of the population tend to be more exposed to such pollutants depending on their social or demographic characteristics. In addition, exposure to toxicants during pregnancy may play a deleterious role in fetal development as fetuses are especially vulnerable to external insults. The present study was carried out within the framework of the INMA (Infancia y Medio Ambiente or Childhood and the Environment) multicenter cohort study with the objective of identifying the social, demographic, and life-style factors associated with nitrogen dioxide (NO(2)) exposure in the subjects in the cohort. The study comprised 785 pregnant women who formed part of the INMA cohort in Valencia, Spain. Outdoor levels of NO(2) were measured at 93 sampling sites spread over the study area during four different sampling periods lasting 7 days each. Multiple regression models were used for mapping outdoor NO(2) throughout the area. Individual exposure was assigned as: 1) the estimated outdoor NO(2) levels at home, and 2) the average of estimated outdoor NO(2) levels at home and work, weighted according to the time spent in each environment. The subjects' socio-demographic and life-style information was obtained through a questionnaire. In the multiple linear analyses, the outdoor NO(2) levels assigned to each home were taken to be the dependent variable. Other variables included in the model were: age, country of origin, smoking during pregnancy, parity, season of the year, and social class. These same variables remained in the model when the dependent variable was changed to the NO(2) levels adjusted for the subjects' time-activity patterns. We found that younger women, those coming from Latin American countries, and those belonging to the lower social strata were exposed to higher NO(2) levels, both as measured outside their homes as well as when time-activity patterns were taken into account. These subgroups also have a higher probability of being exposed to NO(2) levels over 40 μg/m(3), which is the annual limit for maximum safe exposure, as established by European Directive 2008/50/EC.