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

Reducing air pollution does not necessarily reduce related adults' mortality burden: Variations in 177 countries with different economic levels

Prolonged exposure to PM2.5 is associated with increased mortality. However, reducing air pollution concentrations does not necessarily reduce the related burden of deaths. Here, we aim to estimate the variations in PM2.5-related mortality due to contributions from key factors - PM2.5 concentration, population exposure, and healthcare levels - for 177 countries from 2000 to 2018 at the 1-km grid scale according to the Global Mortality Exposure Model (GEMM) model. We find that global reductions in PM2.5-related deaths mainly come from high and upper-middle income countries, where lowered air pollutant concentration and better healthcare can offset mortality burdens caused by increasing exposed populations. Changes in population exposure to PM2.5 contribute the most (54 %) to change in global related deaths over the examined period, followed by changes in healthcare (-42 %) and pollution concentrations (4 %). The impacts vary across countries and regions within them due to other drivers, which are significantly influenced by development status. Policies aiming at reducing PM2.5 associated health risks need to account for country-specific balances of these key socioeconomic drivers.

A GIS-based approach to determining optimal location for decentralized inner city smart filters: Toward net zero cities

Climate change has already begun to take visible effect globally in recent years. Given the climate change paradox and urbanization trends, cities' success would not only depend on smartness and sustainability, but also resilience to all forthcoming economic, environmental, or behavioral changes. Numerous technologies have surfaced and proved effective in CO2 removal from the local environment. However, the optimal placement of these smart filters is a complex task and require logical and strategic decision-making. Determining the optimal location is one of the key factors for establishing a network of smart air filters. This study used a GIS-based suitability analysis for identifying optimal locations for smart filters based on pollution hotspots (population and spatial proximity to industry, commercial centers, roads, high-traffic areas, and intersections). The spatial analysis involves the determination and preparation of input layers, ranking layers, assigning weights to each criterion, and generation of a suitability map. The sites with a higher suitability score (7 or above) are optimum sites for air filters. The sites are spatially distributed over different regions. The findings revealed that GIS-based suitability analysis can be an effective technique for placing smart filters within an urban environment. These findings can help decision-makers to prioritize the location considering environmental constraints. The proposed solution aims to pave the way for fostering resilient, smart, and sustainable cities through a community sensing platform targeting hotspots within spatial variations.

The Uncontrollable Mortality Risk Hypothesis: Theoretical foundations and implications for public health

The 'Uncontrollable Mortality Risk Hypothesis' employs a behavioural ecological model of human health behaviours to explain the presence of social gradients in health. It states that those who are more likely to die due to factors beyond their control should be less motivated to invest in preventative health behaviours. We outline the theoretical assumptions of the hypothesis and stress the importance of incorporating evolutionary perspectives into public health. We explain how measuring perceived uncontrollable mortality risk can contribute towards understanding socioeconomic disparities in preventative health behaviours. We emphasize the importance of addressing structural inequalities in risk exposure, and argue that public health interventions should consider the relationship between overall levels of mortality risk and health behaviours across domains. We suggest that measuring perceptions of uncontrollable mortality risk can capture the unanticipated health benefits of structural risk interventions, as well as help to assess the appropriateness of different intervention approaches.

Environmental Exposome and Atrial Fibrillation: Emerging Evidence and Future Directions

There has been increased awareness of the linkage between environmental exposures and cardiovascular health and disease. Atrial fibrillation is the most common sustained cardiac arrhythmia, affecting millions of people worldwide and contributing to substantial morbidity and mortality. Although numerous studies have explored the role of genetic and lifestyle factors in the development and progression of atrial fibrillation, the potential impact of environmental determinants on this prevalent condition has received comparatively less attention. This review aims to provide a comprehensive overview of the current evidence on environmental determinants of atrial fibrillation, encompassing factors such as air pollution, temperature, humidity, and other meteorologic conditions, noise pollution, greenspace, and the social environment. We discuss the existing evidence from epidemiological and mechanistic studies, critically evaluating the strengths and limitations of these investigations and the potential underlying biological mechanisms through which environmental exposures may affect atrial fibrillation risk. Furthermore, we address the potential implications of these findings for public health and clinical practice and identify knowledge gaps and future research directions in this emerging field.

Association of Environmental Injustice and Cardiovascular Diseases and Risk Factors in the United States

BACKGROUND

While the impacts of social and environmental exposure on cardiovascular risks are often reported individually, the combined effect is poorly understood.

METHODS AND RESULTS

Using the 2022 Environmental Justice Index, socio-environmental justice index and environmental burden module ranks of census tracts were divided into quartiles (quartile 1, the least vulnerable census tracts; quartile 4, the most vulnerable census tracts). Age-adjusted rate ratios (RRs) of coronary artery disease, strokes, and various health measures reported in the Prevention Population-Level Analysis and Community Estimates data were compared between quartiles using multivariable Poisson regression. The quartile 4 Environmental Justice Index was associated with a higher rate of coronary artery disease (RR, 1.684 [95% CI, 1.660-1.708]) and stroke (RR, 2.112 [95% CI, 2.078-2.147]) compared with the quartile 1 Environmental Justice Index. Similarly, coronary artery disease 1.057 [95% CI,1.043-1.0716] and stroke (RR, 1.118 [95% CI, 1.102-1.135]) were significantly higher in the quartile 4 than in the quartile 1 environmental burden module. Similar results were observed for chronic kidney disease, hypertension, diabetes, obesity, high cholesterol, lack of health insurance, sleep <7 hours per night, no leisure time physical activity, and impaired mental and physical health >14 days.

CONCLUSIONS

The prevalence of CVD and its risk factors is highly associated with increased social and environmental adversities, and environmental exposure plays an important role independent of social factors.

OLYMPUS-POPGEN: A synthetic population generation model to represent urban populations for assessing exposure to air quality

SCIENTIFIC QUESTION

With the new individual- and activity-based approaches to simulating exposure to air pollutants, exposure models must now provide synthetic populations that realistically reflect the demographic profiles of individuals in an urban territory. Demographic profiles condition the behavior of individuals in urban space (activities, mobility) and determine the resulting risks of exposure and environmental inequalities. In this context, there is a strong need to determine the relevance of the population modeling methods to reproduce the combinations of socio-demographic parameters in a population from the existing databases. The difficulty of accessing complete, high-resolution databases indeed proves to be very limiting for the ambitions of the different approaches.

OBJECTIVE

This work proposes to evaluate the potential of a statistical approach for the numerical modeling of synthetic populations, at the scale of dwellings and including the representation of coherent socio-demographic profiles. The approach is based on and validated against the existing open databases. The ambition is to be able to build upon such synthetic populations to produce a comprehensive assessment of the risk of environmental exposure that can be cross-referenced with lifestyles, indicators of social, professional or demographic category, and even health vulnerability data.

METHOD

The approach implemented here is based on the use of conditional probabilities to model the socio-demographic properties of individuals, via the deployment of a Monte Carlo Markov Chain (MCMC) simulation. Households are assigned to housing according to income and house price classes. The resulting population generation model was tested in the Paris region (Ile de France) for the year 2010, and applied to a population of almost 12 million individuals. The approach is based on the use of census and survey databases.

RESULTS

Validation, carried out by comparison with regional census data, shows that the model accurately reproduces the demographic attributes of individuals (age, gender, professional category, income) as well as their combination, at both regional and sub-municipal levels. Notably, population distribution at the scale of the model buildings remains consistent with observed data patterns.

CONCLUSIONS AND RELEVANCE

The outcomes of this work demonstrate the ability of our approach to create, from public data, a coherent synthetic population with broad socio-demographic profiles. They give confidence for the use of this approach in an activity-based air quality exposure study, and thus for exploring the interrelations between social determinants and environmental risks. The non-specific nature of this work allows us to consider its extension to broader demographic profiles, including health indicators, and to different study regions.

The Relationship Between Perceived Uncontrollable Mortality Risk and Health Effort: Replication, Secondary Analysis, and Mini Meta-analysis

BACKGROUND

The Uncontrollable Mortality Risk Hypothesis (UMRH) states that those who are more likely to die due to factors beyond their control should be less motivated to invest in preventative health behaviors. Greater levels of perceived uncontrollable mortality risk (PUMR) have been associated with lower health effort in previous research, but the topic remains understudied.

PURPOSE

To examine the evidence for the UMRH by replicating a previous study investigating the effects of PUMR on social gradients in health effort, and conducting a mini meta-analysis of the overall relationship between PUMR and health effort.

METHODS

We replicated Pepper and Nettle (2014), who reported a negative relationship between PUMR and health effort, and that the positive effect of subjective socioeconomic position on health effort was explained away by PUMR. We also compared the predictive effect of PUMR on health effort with that of dimensions from the Multidimensional Health Locus of Control scale-a well-used measure of a similar construct, which is frequently found to be associated with health behavior. Finally, we conducted a mini meta-analysis of the relationship between PUMR and health effort from the available research.

RESULTS

PUMR was negatively associated with health effort, and mediated 24% of the total effect of subjective socioeconomic position on health effort, though this mediation effect was weaker than in Pepper and Nettle (2014). PUMR was shown to be a substantially stronger predictor of health effort than the relevant dimensions of the MHLC scale. Finally, our mini meta-analysis indicated a medium-sized negative relationship between PUMR and health effort.

CONCLUSIONS

Our findings offer support for the role of PUMR in mediating the relationship between subjective socioeconomic position and health effort. The results highlight the importance of measuring and understanding PUMR in studying socioeconomic inequalities in health behaviors. We discuss potential areas for future research, including determining the accuracy of PUMR, investigating influential cues, examining the role of media in shaping risk perceptions, and understanding individuals' awareness of their own perceptions of mortality risk.

Physical characteristics of microplastic particles and potential for global atmospheric transport: A meta-analysis

Recent interest in microplastic pollution of natural environments has brought forth samples which confirm the pollutant's omnipresence in a variety of ecosystems. This includes locations furthest removed from human activity. Atmospheric transport and deposition are suspected as the primary transport pathway to these remote locations. The factors most influential on participation in atmospheric transport are yet to be determined. This meta-analysis aims to identify patterns that exist between physical characteristics of microplastic particles and their potential for atmospheric transport. Our review addresses the following questions: Which characteristics of microplastic particles promote atmospheric transport and deposition into remote regions, and how significant are these factors in determining distance transported from their sources? This article analyzes commonly reported physical attributes-- shape, polymer composition and color-- from studies in urban and remote areas. The analysis of 68 studies, composed of data from 2078 samples, shows higher occurrence of microplastic particles in remote samples with fiber shapes, polyester compositions, and red, blue, and transparent colors. This meta-analysis is the first to identify patterns between physical properties of microplastic particles and extent of their participation in atmospheric transport to global remote locations.

Ethnic and socioeconomic inequalities in air pollution exposure: a cross-sectional analysis of nationwide individual-level data from the Netherlands

BACKGROUND

Air pollution contributes to a large disease burden and some populations are disproportionately exposed. We aimed to evaluate ethnic and socioeconomic differences in exposure to air pollution in the Netherlands.

METHODS

We did a nationwide, cross-sectional analysis of all residents of the Netherlands on Jan 1, 2019. Sociodemographic information was centralised by Statistics Netherlands and mainly originated from the National Population Register, the tax register, and education registers. Concentrations of NO2, PM2·5, PM10, and elemental carbon, modelled by the National Institute for Public Health and the Environment, were linked to the individual-level demographic data. We assessed differences in air pollution exposures across the 40 largest minority ethnic groups. Evaluation of how ethnicity intersected with socioeconomic position in relation to exposures was done for the ten largest ethnic groups, plus Chinese and Indian groups, in both urban and rural areas using multivariable linear regression analyses.

FINDINGS

The total study population consisted of 17 251 511 individuals. Minority ethnic groups were consistently exposed to higher levels of air pollution than the ethnic Dutch population. The magnitude of inequalities varied between the minority ethnic groups, with 3-44% higher exposures to NO2 and 1-9% higher exposures to PM2·5 compared with the ethnic Dutch group. Average exposures were highest for the lowest socioeconomic group. Ethnic inequalities in exposure remained after adjustment for socioeconomic position and were of similar magnitude in urban and rural areas.

INTERPRETATION

The variability in air pollution exposure across ethnic and socioeconomic subgroups in the Netherlands indicates environmental injustice at the intersection of social characteristics. The health consequences of the observed inequalities and the underlying processes driving them warrant further investigation.

FUNDING

The Gravitation programme of the Dutch Ministry of Education, Culture, and Science, the Netherlands Organization for Scientific Research, the Netherlands Organisation for Health Research and Development, and Amsterdam University Medical Center.

A cross-sectional study of inequalities in digital air pollution information access and exposure reducing behavior uptake in the UK

Air pollution is a pervasive global environmental challenge that presents substantial and differential risk across populations. Individual-level pollution exposure is a function of varying factors, including but not limited to geographic location, proximity to point sources, ventilation, and behavioral patterns. Mounting evidence suggests that informational interventions can play a substantial role in mediating exposures for specific population subgroups and reduce downstream adverse health outcomes. The literature has yet to address whether access to air quality information is sociodemographically stratified, and whether such access correlates with increased uptake of exposure reducing behaviors at the population level. This study represents a first step in answering these questions by analysing responses from the "Clean Air Public Insight Tracker" nationally representative survey (n = 1,993) of the UK population, administered by UK charity Global Action Plan. Results from logistic regression and zero-inflated negative binomial models estimate 28% of the population have accessed air pollution information, while the odds of younger individuals (ages 18-36), men, and non-white individuals of accessing digitally available air quality information are greater that those outside these categories. Additionally, the odds of behavior uptake is greater if an individual accesses digital information sources like the internet, mobile apps or social media, has a higher education qualification or cares for someone with a health condition. These findings contribute to the growing literature surrounding which population groups engage with environmental and health-relevant information channels, and what connects engagement with air quality channels and uptake of exposure reducing behaviors. These results reinforce the need for additional research around air pollution informational alerts and exploring causal links between specific exposure reducing behaviours and improved health outcomes. It can also help inform the flow of resources and targeting of informational campaigns towards sociodemographic groups that are less likely to engage with air quality information.

Impacts of net zero policies on air quality in a metropolitan area of the United Kingdom: Towards world health organization air quality guidelines

Climate change and air pollution are closely interlinked since carbon dioxide and air pollutants are co-emitted from fossil fuel combustion. Net Zero (NZ) policies aiming to reduce carbon emissions will likely bring co-benefits in air quality and associated health. However, it is unknown whether regional NZ policies alone will be sufficient to reduce air pollutant levels to meet the latest 2021 World Health Organisation (WHO) guidelines. Here, we carried out high resolution air quality modelling for in the West Midlands region, a typical metropolitan area in the UK, to quantify the effects of different NZ policies on air quality. Results show that NZ policies will significantly improve air quality in the West Midlands, with up to 6 μg m-3 (21%) reduction in annual mean NO2 (mostly through the electrification of vehicle fleet, EV) and up to 1.4 μg m-3 (12%) reduction in annual mean PM2.5 projected for 2030 relative to levels under a "business as usual" (BAU) scenario. Under BAU, 2030 PM2.5 concentrations in most wards would be below 10 μg m-3 whilst under the Net Zero scenario, those in all wards would be below 10 μg m-3. This means that the ward averages in the West Midlands would meet the UK PM2.5 of 10 μg m-3target a decade early under the Net Zero scenario. However, no ward-level-averaged annual mean PM2.concentrations meet the 2021 WHO Air Quality guideline level of 5 μg m-3 under any scenario. Similarly for NO2 only 18 wards (8% of the region's population) are predicted to have NO2 concentrations below the 2021 WHO guideline level (10 μg m-3). Decarbonisation policies linked to Net Zero deliver substantial regional air quality benefits, but are not in isolation sufficient to deliver clean air with air pollutant levels low enough to meet the 2021 WHO guidelines.

Integrating the social environment with an equity perspective into the exposome paradigm: A new conceptual framework of the Social Exposome

The importance of the social environment and social inequalities in disease etiology is well-known due to the profound research and conceptual framework on social determinants of health. For a long period, in exposome research with its classical orientation towards detrimental health effects of biological, chemical, and physical exposures, this knowledge remained underrepresented. But currently it gains great awareness and calls for innovations in rethinking the role of social environmental health determinants. To fill this gap that exists in terms of the social domain within exposome research, we propose a novel conceptual framework of the Social Exposome, to integrate the social environment in conjunction with the physical environment into the exposome concept. The iterative development process of the Social Exposome was based on a systematic compilation of social exposures in order to achieve a holistic portrayal of the human social environment - including social, psychosocial, socioeconomic, sociodemographic, local, regional, and cultural aspects, at individual and contextual levels. In order to move the Social Exposome beyond a mere compilation of exposures, three core principles are emphasized that underly the interplay of the multitude of exposures: Multidimensionality, Reciprocity, and Timing and continuity. The key focus of the conceptual framework of the Social Exposome is on understanding the underlying mechanisms that translate social exposures into health outcomes. In particular, insights from research on health equity and environmental justice have been incorporated to uncover how social inequalities in health emerge, are maintained, and systematically drive health outcomes. Three transmission pathways are presented: Embodiment, Resilience and Susceptibility or Vulnerability, and Empowerment. The Social Exposome conceptual framework may serve as a strategic map for, both, research and intervention planning, aiming to further explore the impact of the complex social environment and to alter transmission pathways to minimize health risks and health inequalities and to foster equity in health.

The Relationship Between Air Quality, Health Outcomes, and Socioeconomic Impacts of the COVID-19 Pandemic in the US

COVID-19 lockdowns caused significant improvements in air quality in US states where traffic emissions are the main pollution source. In this study, we investigate the socioeconomic impacts of the COVID-19-related lockdowns in states which experienced the greatest changes in air quality, especially among different demographic populations and those with contraindications to health. We administered a 47-question survey and collected 1,000 valid responses in these cities. Our results show that 74% of respondents within our survey sample had some level of concern regarding air quality. In agreement with previous literature, perceptions of air quality were not significantly correlated with measured air quality criteria but rather seemed to be influenced by other factors. Respondents in Los Angeles were the most concerned about air quality followed by Miami, San Francisco, and New York City. However, those from Chicago and Tampa Bay expressed the least amount of concern about air quality. Age, education, and ethnicity were all factors affecting peoples' concerns about air quality. Respiratory conditions, living in proximity to industrial areas, and financial impacts from the COVID-19 lockdowns influenced concerns about air quality. About 40% of the survey sample reported greater concern for air quality during the pandemic, while approximately 50% stated that the lockdown didn't affect their perception. Furthermore, respondents seemed concerned about air quality in general, not a specific pollutant, and are willing to adopt additional measures and more stringent policies to improve air quality in all investigated cities.

Economic and racial disparities of the weather impact on air quality in Brazil

Several studies have quantified the air pollution exposure disparities across racial and income groups. However, there is still a lack of investigations assessing disparities related to the impacts of weather on air pollution, which could indicate target air pollution reduction strategies under different climate scenarios. Our study aims to address this gap by estimating the economic and racial disparities of the weather impact on air quality in Brazil between 2003 and 2018. First, we used a generalized additive approach to estimate the weather-related changes in PM_2.5. This framework derived "weather penalty", which a positive penalty suggests that an increase in PM_2.5 was associated with long-term weather changes in the study period. Then, we estimated the population-weighted weather penalty for racial and income groups. Average penalty for the White population (the most-exposed group) was 31% higher than that of the Pardo population (the least-exposed group, mainly people of light brown skin color) in Brazil. In the stratification analysis by region, the Midwest and South were the regions where the black population was the most-exposed group. For the income group, our results indicate that the high-income population group was the most-exposed group in all analyses, including the national and the regional analyses. These findings are somewhat surprising, as previous studies have shown that minority and low-income populations tend to be more exposed to air pollution, than white and higher-income populations. However, our study suggests that disparities in exposure to air pollution may be more complex and nuanced than previously thought. Further research is needed to better understand the underlying drivers of these environmental disparities, and to develop targeted interventions to reduce exposures.

Effects of Sociodemographic Characteristics, Comorbidity, and Coexposures on the Association between Air Pollution and Type 2 Diabetes: A Nationwide Cohort Study

BACKGROUND

Exposure to air pollution has been associated with a higher risk of type 2 diabetes (T2D), but studies investigating whether deprived groups are more susceptible to the harmful effects of air pollution are inconsistent.

OBJECTIVES

We aimed to investigate whether the association between air pollution and T2D differed according to sociodemographic characteristics, comorbidity, and coexposures.

METHODS

We estimated residential exposure to PM2.5, ultrafine particles (UFP), elemental carbon, and NO2 for all persons living in Denmark in the period 2005-2017. In total, 1.8 million persons 50-80 y of age were included for main analyses of whom 113,985 developed T2D during follow-up. We conducted additional analyses on 1.3 million persons age 35-50 y. Using Cox proportional hazards model (relative risk) and Aalens additive hazard model (absolute risk), we calculated associations between 5-y time-weighted running means of air pollution and T2D in strata of sociodemographic variables, comorbidity, population density, road traffic noise, and green space proximity.

RESULTS

Air pollution was associated with T2D, especially among people age 50-80 y, with hazard ratios of 1.17 [95% confidence interval (CI): 1.13, 1.21] per 5 μg/m3 PM2.5 and 1.16 (95% CI: 1.13, 1.19) per 10,000  UFP/cm3. In the age 50-80 y population, we found higher associations between air pollution and T2D among men in comparison with women, people with lower education vs. individuals with high education, people with medium income vs. those with low or high income, people cohabiting vs. those living alone, and people with comorbidities vs. those without comorbidities. We observed no marked changes according to occupation, population density, road noise, or surrounding greenness. In the age 35-50 y population, similar tendencies were observed, except in relation to sex and occupation, where we observed associations with air pollution only among women and blue-collar workers.

DISCUSSION

We found stronger associations between air pollution and T2D among people with existing comorbidities and weaker associations among people with high socioeconomic status in comparison with those with lower socioeconomic status. https://doi.org/10.1289/EHP11347.

Urban centre green metrics in Great Britain: A geospatial and socioecological study

Green infrastructure plays a vital role in urban ecosystems. This includes sustaining biodiversity and human health. Despite a large number of studies investigating greenspace disparities in suburban areas, no known studies have compared the green attributes (e.g., trees, greenness, and greenspaces) of urban centres. Consequently, there may be uncharacterised socioecological disparities between the cores of urban areas (e.g., city centres). This is important because people spend considerable time in urban centres due to employment, retail and leisure opportunities. Therefore, the availability of--and disparities in--green infrastructure in urban centres can affect many lives and potentially underscore a socio-ecological justice issue. To facilitate comparisons between urban centres in Great Britain, we analysed open data of urban centre boundaries with a central business district and population of ≥100,000 (n = 68). Given the various elements that contribute to 'greenness', we combine a range of different measurements (trees, greenness, and accessible greenspaces) into a single indicator. We applied the normalised difference vegetation index (NDVI) to estimate the mean greenness of urban centres and the wider urban area (using a 1 km buffer) and determined the proportion of publicly accessible greenspace within each urban centre with Ordnance Survey Open Greenspace data. Finally, we applied a land cover classification algorithm using i-Tree Canopy to estimate tree coverage. This is the first study to define and rank urban centres based on multiple green attributes. The results suggest important differences in the proportion of green attributes between urban centres. For instance, Exeter scored the highest with a mean NDVI of 0.15, a tree coverage of 11.67%, and an OS Greenspace coverage of 0.05%, and Glasgow the lowest with a mean NDVI of 0.02, a tree cover of 1.95% and an OS Greenspace coverage of 0.00%. We also demonstrated that population size negatively associated with greenness and tree coverage, but not greenspaces, and that green attributes negatively associated with deprivation. This is important because it suggests that health-promoting and biodiversity-supporting resources diminish as population and deprivation increase. Disparities in green infrastructure across the country, along with the population and deprivation-associated trends, are important in terms of socioecological and equity justice. This study provides a baseline and stimulus to help local authorities and urban planners create and monitor equitable greening interventions in urban/city centres.

The Association Between Living Area in Childhood and Respiratory Disease Mortality in Adulthood

Objective: No studies have examined the association between characteristics of urban areas and future respiratory disease mortality. We examined whether the type of living area during childhood was associated with all-cause and respiratory disease mortality in adulthood.

Methods: A total of 81,413 Japanese participants aged 40–79 years old completed a lifestyle questionnaire including the type of childhood living areas. The Cox proportional hazards regression model was used to calculate the multivariable hazard ratios (HRs) with 95% confidence intervals (CIs) of all-cause and respiratory disease mortality.

Results: Living in large city areas in childhood was associated with a higher risk of all-cause mortality [HR = 1.05 (95% CI, 1.01–1.10)], but not with respiratory disease mortality [HR = 1.04 (95% CI, 0.92–1.18)] compared to rural and remote areas. The excess risk of all-cause and respiratory disease mortality was primarily found in industrial areas among men; the respective multivariable HRs were 1.28 (95% CI, 1.00–1.64) and 1.90 (95% CI: 1.10–3.29).

Conclusion: Eliminating childhood health hazards associated with living in industrial areas suggested to reduce the risk of mortality from respiratory diseases in adulthood.

The digital rainbow: Digital determinants of health inequities

The widely used socioecological rainbow model from Dahlgren and Whitehead specifies determinants of health inequity on multiple hierarchical levels and suggests that these determinants may interact both within and between levels. At the time of its inception, digital determinants only played a minor role in tackling inequities in public health and were therefore not specifically considered. This has dramatically changed: From today's perspective, health inequities increasingly depend on digital determinants. In this article, we suggest adapting the Dahlgren-Whitehead model to reflect these developments. We propose a model that allows formulating testable hypotheses, interpreting research findings, and developing policy implications against the background of the global spread of digital technologies. This may facilitate the development of a new line of research and logic models for public health interventions in the digital age. Using the COVID-19 pandemic as a case study, we illustrate how the digitization of all aspects of life affects the different levels of determinants of health inequities in the Dahlgren-Whitehead model. In doing so, we deliberately argue for not introducing a separate digital sphere in its own right, but for understanding digitization as a phenomenon that permeates all levels of determinants of health inequities. As a result, we present a digital rainbow model that integrates Dahlgren and Whitehead's 1991 model with digital environments to identify current health promotion and research issues without changing the rainbow model's initial structure.

The Impact of Climate Change on Mental Health and Emotional Wellbeing: A Narrative Review of Current Evidence, and its Implications

Converging global evidence highlights the dire consequences of climate change for human mental health and wellbeing. This paper summarises literature across relevant disciplines to provide a comprehensive narrative review of the multiple pathways through which climate change interacts with mental health and wellbeing. Climate change acts as a risk amplifier by disrupting the conditions known to support good mental health, including socioeconomic, cultural and environmental conditions, and living and working conditions. The disruptive influence of rising global temperatures and extreme weather events, such as experiencing a heatwave or water insecurity, compounds existing stressors experienced by individuals and communities. This has deleterious effects on people's mental health and is particularly acute for those groups already disadvantaged within and across countries. Awareness and experiences of escalating climate threats and climate inaction can generate understandable psychological distress; though strong emotional responses can also motivate climate action. We highlight opportunities to support individuals and communities to cope with and act on climate change. Consideration of the multiple and interconnected pathways of climate impacts and their influence on mental health determinants must inform evidence-based interventions. Appropriate action that centres climate justice can reduce the current and future mental health burden, while simultaneously improving the conditions that nurture wellbeing and equality. The presented evidence adds further weight to the need for decisive climate action by decision makers across all scales.

Regional disparities in SARS-CoV-2 infections by labour market indicators: a spatial panel analysis using nationwide German data on notified infections

Background

Regional labour markets and their properties are named as potential reasons for regional variations in levels of SARS-CoV-2 infections rates, but empirical evidence is missing.

Methods

Using nationwide data on notified laboratory-confirmed SARS-CoV-2 infections, we calculated weekly age-standardised incidence rates (ASIRs) for working-age populations at the regional level of Germany’s 400 districts. Data covered nearly 2 years (March 2020 till December 2021), including four main waves of the pandemic. For each of the pandemic waves, we investigated regional differences in weekly ASIRs according to three regional labour market indicators: (1) employment rate, (2) employment by sector, and (3) capacity to work from home. We use spatial panel regression analysis, which incorporates geospatial information and accounts for regional clustering of infections.

Results

For all four pandemic waves under study, we found that regions with higher proportions of people in employment had higher ASIRs and a steeper increase of infections during the waves. Further, the composition of the workforce mattered: rates were higher in regions with larger secondary sectors or if opportunities of working from home were comparatively low. Associations remained consistent after adjusting for potential confounders, including a proxy measure of regional vaccination progress.

Conclusions

If further validated by studies using individual-level data, our study calls for increased intervention efforts to improve protective measures at the workplace, particularly among workers of the secondary sector with no opportunities to work from home. It also points to the necessity of strengthening work and employment as essential components of pandemic preparedness plans.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07643-5.

Validity of self-reported air pollution annoyance to assess long-term exposure to air pollutants in Belgium

In epidemiological studies, assessment of long term exposure to air pollution is often estimated using air pollution measurements at fixed monitoring stations, and interpolated to the residence of survey participants through Geographical Information Systems (GIS). However, obtaining georeferenced address data from national registries requires a long and cumbersome administrative procedure, since this kind of personal data is protected by privacy regulations. This paper aims to assess whether information collected in health interview surveys, including air pollution annoyance, could be used to build prediction models for assessing individual long term exposure to air pollution, removing the need for data on personal residence address. Analyses were carried out based on data from the Belgian Health Interview Survey (BHIS) 2013 linked to GIS-modelled air pollution exposure at the residence place of participants older than 15 years (n = 9347). First, univariate linear regressions were performed to assess the relationship between air pollution annoyance and modelled exposure to each air pollutant. Secondly, a multivariable linear regression was performed for each air pollutant based on a set of variables selected with elastic net cross-validation, including variables related to environmental annoyance, socio-economic and health status of participants. Finally, the performance of the models to classify individuals in three levels of exposure was assessed by means of a confusion matrix. Our results suggest a limited validity of self-reported air pollution annoyance as a direct proxy for air pollution exposure and a weak contribution of environmental annoyance variables in prediction models. Models using variables related to the socio-economic status, region, urban level and environmental annoyance allow to predict individual air pollution exposure with a percentage of error ranging from 8% to 18%. Although these models do not provide very accurate predictions in terms of absolute exposure to air pollution, they do allow to classify individuals in groups of relative exposure levels, ranking participants from low over medium to high air pollution exposure. This model represents a rapid assessment tool to identify groups within the BHIS participants undergoing the highest levels of environmental stress.

Exploring Environmental Health Inequalities: A Scientometric Analysis of Global Research Trends (1970-2020)

Environmental health inequalities (EHI), understood as differences in environmental health factors and in health outcomes caused by environmental conditions, are studied by a wide range of disciplines. This results in challenges to both synthesizing key knowledge domains of the field. This study aims to uncover the global research status and trends in EHI research, and to derive a conceptual framework for the underlying mechanisms of EHI. In total, 12,320 EHI publications were compiled from the Web of Science core collection from 1970 to 2020. Scientometric analysis was adopted to characterize the research activity, distribution, focus, and trends. Content analysis was conducted for the highlight work identified from network analysis. Keyword co-occurrence and cluster analysis were applied to identify the knowledge domain and develop the EHI framework. The results show that there has been a steady increase in numbers of EHI publications, active journals, and involved disciplines, countries, and institutions since the 2000s, with marked differences between countries in the number of published articles and active institutions. In the recent decade, environment-related disciplines have gained importance in addition to social and health sciences. This study proposes a framework to conceptualize the multi-facetted issues in EHI research referring to existing key concepts.

Cytogenetic Effects in Children Exposed to Air Pollutants: A Systematic Review and Meta-Analysis

The aim of this systematic review and meta-analysis was to assess the association between exposure to ambient air pollutants and micronuclei (MN) frequency in children. This work was performed according to the Cochrane Collaboration and the PRISMA guidelines and recommendations. Articles published before November 2021 were identified by an advanced search on PubMed/MEDLINE, Scopus and Web of Science databases. A critical appraisal using a specific tool was conducted to assess the quality of each included study. All analyses were carried out by using the Review Manager (RevMan) 5.4 software (The Cochrane Collaboration, London, UK). One hundred and forty-five references were firstly identified, and, at the end of selection process, 13 studies met the inclusion criteria. Six studies carried out a direct evaluation through the use of air samplers, whereas the other ones accessed environmental databases (n = 2) or used other tools (n = 3). In two cases, exposure was not directly investigated, with children sampled in two different areas with well-known different levels of pollution. The overall effect size (ES) was 1.57 ((95% CI = 1.39; 1.78), p-value < 0.00001) (total evaluated subjects: 4162), which highlighted a statistically significant association between outdoor air pollution and MN frequency in children. As a high MN frequency has been associated with a number of pathological states and a higher risk of developing chronic degenerative diseases, our results should be taken into consideration by policy makers to design and implement interventions aimed at reducing the introduction of pollutants in the atmosphere as well as at minimizing the exposure extent, particularly in children.

Air pollution at the residence of Danish adults, by socio-demographic characteristics, morbidity, and address level characteristics

BACKGROUND

Exposure to outdoor air pollution is associated with adverse health effects. Previous studies have indicated higher levels of air pollution in socially deprived areas.

AIM

To investigate associations between air pollution and socio-demographic variables, comorbidity, stress, and green space at the residence in Denmark.

METHODS

We included 2,237,346 persons living in Denmark, aged 35 years or older in 2017. We used the high resolution, multi-scale DEHM/UBM/AirGIS air pollution modelling system to calculate mean concentrations of air pollution with PM_2.5, elemental carbon, ultrafine particles and NO₂ at residences held the preceding five years. We used nationwide registries to retrieve information about socio-demographic indicators at the individual and neighborhood levels. We used general linear regression models to analyze associations between socio-demographic indicators and air pollution at the residence.

RESULTS

Individuals with high SES (income, higher white-collar worker and high educational level) and of non-Danish origin were exposed to higher levels of air pollution than individuals of low SES and of Danish origin, respectively. We found comparable levels of air pollution according to sex, stress events and morbidity. For neighborhood level SES indicators, we found high air pollution levels in neighborhoods with low SES measured as proportion of social housing, sole providers, low income and unemployment. In contrast, we found higher air pollution levels in neighborhoods with higher educational level and a low proportion of manual labor. People living in an apartment and/or with little green space had higher air pollution levels.

CONCLUSION

In Denmark, high levels of residential air pollution were associated with higher individual SES and non-Danish origin. For neighborhood-level indicators of SES, no consistent pattern was observed. These results highlight the need for analyzing many different socio-demographic indicators to understand the complex associations between SES and exposure to air pollution.

Neighbourhood socio-economic vulnerability and access to COVID-19 healthcare during the first two waves of the pandemic in Geneva, Switzerland: A gender perspective

BACKGROUND

Neighbourhood socio-economic inequities have been shown to affect COVID-19 incidence and mortality, as well as access to tests. This article aimed to study how associations of inequities and COVID-19 outcomes varied between the first two pandemic waves from a gender perspective.

METHODS

We performed an ecological study based on the COVID-19 database of Geneva between Feb 26, 2020, and June 1, 2021. Outcomes were the number of tests per person, the incidence of COVID-19 cases, the incidence of COVID-19 deaths, the positivity rate, and the delay between symptoms and test. Outcomes were described by neighbourhood socio-economic levels and stratified by gender and epidemic waves (first wave, second wave), adjusting for the proportion of inhabitants older than 65 years.

FINDINGS

Low neighbourhood socio-economic levels were associated with a lower number of tests per person (incidence rate ratio [IRR] of 0.88, 0.85 and 0.83 for low, moderate, and highly vulnerable neighbourhood respectively), a higher incidence of COVID-19 cases and of COVID-19 deaths (IRR 2.3 for slightly vulnerable, 1.9 for highly vulnerable). The association between socio-economic inequities and incidence of COVID-19 deaths was mainly present during the first wave of the pandemic, and was stronger amongst women. The increase in COVID-19 cases amongst vulnerable populations appeared mainly during the second wave, and originated from a lower access to tests for men, and a higher number of COVID-19 cases for women.

INTERPRETATION

The COVID-19 pandemic affected people differently depending on their socio-economic level. Because of their employment and higher prevalence of COVID-19 risk factors, people living in neighbourhoods of lower socio-economic levels, especially women, were more exposed to COVID-19 consequences.

FUNDING

This research was supported by the research project SELFISH, financed by the Swiss National Science Foundation, grant number 51NF40-160590 (LIVES centre international research project call).

Air (ine)quality in the European Union

Purpose of Review

This paper presents an analytical review of recent research on social inequality caused or compounded by ambient air pollution in the European Union.

Recent Findings

While empirical studies have developed significantly both in the academic and institutional arena, they have largely focused on only one aspect: the exposure and sensitivity of individuals and groups to air pollution according to various criteria, documenting substantial and overlapping inequality.

Summary

While EU policy should better address this proven impact inequality, research is also needed on new fronts of air (ine)quality (namely mental health impact and indoor air quality) as well as other types of ambient air inequality (such as inequality in responsibility and impact of air pollution mitigation policy).

Supplementary Information

The online version contains supplementary material available at 10.1007/s40572-022-00348-6.

Long-term exposure to fine particle elemental components and mortality in Europe: Results from six European administrative cohorts within the ELAPSE project

Evidence for the association between long-term exposure to ambient particulate matter components and mortality from natural causes is sparse and inconsistent. We evaluated this association in six large administrative cohorts in the framework of the Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) project. We analyzed data from country-wide administrative cohorts in Norway, Denmark, the Netherlands, Belgium, Switzerland and in Rome (Italy). Annual 2010 mean concentrations of copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn) in fine particulate matter (PM_2.5) were estimated using 100 × 100 m Europe-wide hybrid land use regression models assigned to the participants' residential addresses. We applied cohort-specific Cox proportional hazard models controlling for area- and individual-level covariates to evaluate associations with natural mortality. Two pollutant models adjusting for PM_2.5 total mass or nitrogen dioxide (NO₂) were also applied. We pooled cohort-specific estimates using a random effects meta-analysis. We included almost 27 million participants contributing more than 240 million person-years. All components except Zn were significantly associated with natural mortality [pooled Hazard Ratios (HRs) (95% CI): 1.037 (1.014, 1.060) per 5 ng/m³ Cu; 1.069 (1.031, 1.108) per 100 ng/m³ Fe; 1.039 (1.018, 1.062) per 50 ng/m³ K; 1.024 (1.006, 1.043) per 1 ng/m³ Ni; 1.036 (1.016, 1.057) per 200 ng/m³ S; 1.152 (1.048, 1.266) per 100 ng/m³ Si; 1.020 (1.006, 1.034) per 2 ng/m³ V]. Only K and Si were robust to PM_2.5 or NO₂ adjustment [pooled HRs (95% CI) per 50 ng/m³ in K: 1.025 (1.008, 1.044), 1.020 (0.999, 1.042) and per 100 ng/m³ in Si: 1.121 (1.039, 1.209), 1.068 (1.022, 1.117) adjusted for PM_2.5 and NO₂ correspondingly]. Our findings indicate an association of natural mortality with most components, which was reduced after adjustment for PM_2.5 and especially NO₂.

Air Pollution and Environmental Justice in Latin America: Where Are We and How Can We Move Forward?

PURPOSE OF REVIEW

Air pollution in Latin America is a major environmental threat, yet few studies have focused on aspects of environmental justice with regard to air pollution in the region. We examined the scientific literature and described whether and how this issue has been addressed, identify possible gaps in knowledge, and offer suggestions for future research to contribute to policies that seek greater equity concerning air pollution impacts in Latin America.

RECENT FINDINGS

There is a limited literature that has addressed issues of environmental justice or environmental health inequalities about air pollution in Latin America, with studies concentrated in Brazil, Mexico, and Chile. Studies that examined disparities in exposure to air pollution found a clear pattern of higher exposure in socially deprived areas. Studies that examined disparities in health impacts associated with air pollution have mixed results, but many found a clear modification of effect with those in the lower socioeconomic groups presenting greater effects. Despite Latin America's colonial and slavery history, no studies have considered ethnicity or minority populations. The literature shows that health risks (exposure and susceptibility) associated with air pollution are unevenly distributed among Latin American populations. Methodological approaches varied and can be improved in future studies, especially for exposure assessment to air pollution, as well as for assigning socioeconomic position to individuals. Using smaller geographic units and spatial regression techniques will allow a reduction in measurement error. Attempts should be made to include both individual and contextual socioeconomic indicators in the analysis. Better quality information will help understand these differential exposures and effects and provide inputs to policies to tackle these inequalities.

[Societal inequalities and the urban exposome: Social origins for different exposures]

Today, many epidemiological studies have proved the adverse health consequences of environmental exposure. For instance, air pollution exposure is recognized to be related with respiratory and cardiovascular diseases as well as adverse pregnancy outcomes. Noise nuisances are also known to increase cardiovascular diseases and to disturb the sleeping quality. Inversely, the access and availability of various resources, as parks, green spaces, and playgrounds positively affect health, psychological and physical well-being, and favorable health behaviors. In this present literature review, we will focus on the urban dimension of exposome, defined by Robinson et al. as the accumulation of all urban settings favorable or unfavorable to health, from the time of life in utero [1].

Long term exposure to air pollution, mortality and morbidity in New Zealand: Cohort study

OBJECTIVES

To investigate associations between long-term exposure to PM_2.5, NO₂, mortality and morbidity in New Zealand, a country with low levels of exposure.

DESIGN

Retrospective cohort study.

SETTING

The New Zealand resident population.

METHOD

The main analyses included all adults aged 30 years and over with complete data on covariates: N = 2,223,507. People who died, or were admitted to hospital, (2013-2016) were linked anonymously to the 2013 census, and to estimates of ambient PM_2.5, and NO₂ concentration. We fitted Poisson regression models of mortality and morbidity in adults (≥30) for all natural causes of death, and by sub- group of major cause. Person-time of exposure, censored at the time of death, was included as an offset. We adjusted for confounding by age, sex, ethnicity, income, education, smoking status and ambient temperature. Further analyses stratified by ethnic group, and investigated respiratory hospital admissions in children.

RESULTS

There were statistically significant positive associations between pollutants and natural causes of death: RR (per 10 μg/m³) for PM_2.5 1.11 (1.07 to 1.15) and for NO₂ 1.10 (1.07 to 1.12). For morbidity, the strongest associations were for PM_2.5 and ischaemic heart disease in adults, RR: 1.29 (1.23 to 1.35) and for NO₂ and asthma in children, RR: 1.18 (1.09 to 1.28). In models restricted to specific ethnic groups, we found no consistent differences in any of the associations.

CONCLUSIONS

The results for NO₂ are higher than those published previously. Other studies have reported that the dose-response for PM_2.5 may be higher at low concentrations, but less is known about NO₂. It is possible NO₂ is acting as a proxy for other traffic-related pollutants that are causally related to health impacts. This study underlines the importance of controlling pollution caused by motor vehicles.

Mutual effects of fine particulate matter, nitrogen dioxide, and fireworks on cause-specific acute cardiovascular mortality: A case-crossover study in communities affected by aircraft noise

Ambient air pollution is the leading cause of environmental mortality and morbidity worldwide. However, the individual contributions to acute mortality of traffic-related air pollutants such as nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) are still debated. We conducted a time-stratified case-crossover study for a population located around Zurich airport in Switzerland, including 24,886 adult cardiovascular deaths from the Swiss National Cohort. We estimated the risk of cause-specific cardiovascular mortality associated with daily NO₂ and PM_2.5 concentrations at home using distributed lag models up to 7 days preceding death, adjusted for daily temperature, precipitation, acute night-time aircraft noise, firework celebrations, and holidays. Cardiovascular mortality was associated with NO₂, whereas the association with PM_2.5 disappeared upon adjustment for NO₂. The strongest association was observed between NO₂ and ischemic stroke mortality (odds ratio = 1.55 per 10 μg/m³, 95% confidence intervals = 1.20-2.00). Cause-specific mortality analyses showed differences in terms of delayed effect: odds ratios were highest at 1-3 days after exposure for most outcomes but at lags of 3-5 days for heart failure. Individual vulnerabilities to NO₂ associated cardiovascular mortality also varied by cause of death, possibly highlighting the role of different behaviours and risk factors in the most susceptible groups. The risk of cardiovascular mortality was also increased on firework days and after public holidays, independent from NO₂ and PM_2.5 concentrations. This study confirms the association between ambient NO₂, as a marker for primary emissions, and acute cardiovascular mortality in a specific setting around a major airport. Future research should clarify the role of additional air pollutants including ultra-fine particles on cardiovascular diseases to inform most efficient control measures.

A novel approach of creating sustainable urban planning solutions that optimise the local air quality and environmental equity in Helsinki, Finland: The CouSCOUS study protocol

Background

Air pollution is one of the major environmental challenges cities worldwide face today. Planning healthy environments for all future populations, whilst considering the ongoing demand for urbanisation and provisions needed to combat climate change, remains a difficult task.

Objective

To combine artificial intelligence (AI), atmospheric and social sciences to provide urban planning solutions that optimise local air quality by applying novel methods and taking into consideration population structures and traffic flows.

Methods

We will use high-resolution spatial data and linked electronic population cohort for Helsinki Metropolitan Area (Finland) to model (a) population dynamics and urban inequality related to air pollution; (b) detailed aerosol dynamics, aerosol and gas-phase chemistry together with detailed flow characteristics; (c) high-resolution traffic flow addressing dynamical changes at the city environment, such as accidents, construction work and unexpected congestion. Finally, we will fuse the information resulting from these models into an optimal city planning model balancing air quality, comfort, accessibility and travelling efficiency.

Variation of Cancer Incidence between and within GRELL Countries

Variation in cancer incidence between countries and groups of countries has been well studied. However cancer incidence is linked to risk factors that may vary within countries, and may subsist in localized geographic areas. In this study we investigated between- and within-country variation in the incidence of all cancers combined for countries belonging to the Group for Cancer Epidemiology and Registration in Latin Language Countries (GRELL). We hypothesized that investigation at the micro-level (circumscribed regions and local cancer registry areas) would reveal incidence variations not evident at the macro level and allow identification of cancer incidence hotspots for research, public health, and to fight social inequalities. Data for all cancers diagnosed in 2008–2012 were extracted from Cancer Incidence in Five Continents, Vol XI. Incidence variation within a country or region was quantified as r/R, defined as the difference between the highest and lowest incidence rates for cancer registries within a country/region (r), divided by the incidence rate for the entire country/region × 100. We found that the area with the highest male incidence had an ASRw 4.3 times higher than the area with the lowest incidence. The area with the highest female incidence had an ASRw 3.3 times higher than the area with the lowest incidence. Areas with the highest male ASRws were Azores (Portugal), Florianopolis (Brazil), Metropolitan France, north Spain, Belgium, and north-west and north-east Italy. Areas with the highest female ASRws were Florianopolis (Brazil), Belgium, north-west Italy, north-east Italy, central Italy, Switzerland and Metropolitan France. Our analysis has shown that cancer incidence varies markedly across GRELL countries but also within several countries: the presence of several areas with high cancer incidence suggests the presence of area-specific risk factors that deserve further investigation.

Air Pollution From Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor

Forest and vegetation fires, used as tools for agriculture and deforestation, are a major source of air pollutants and can cause serious air quality issues in many parts of Asia. Actions to reduce fire may offer considerable, yet largely unrecognized, options for rapid improvements in air quality. In this study, we used a combination of regional and global air quality models and observations to examine the impact of forest and vegetation fires on air quality degradation and public health in Southeast Asia (including Mainland Southeast Asia and south-eastern China). We found that eliminating fire could substantially improve regional air quality across Southeast Asia by reducing the population exposure to fine particulate matter (PM2.5) concentrations by 7% and surface ozone concentrations by 5%. These reductions in PM2.5 exposures would yield a considerable public health benefit across the region; averting 59,000 (95% uncertainty interval (95UI): 55,200-62,900) premature deaths annually. Analysis of subnational infant mortality rate data and PM2.5 exposure suggested that PM2.5 from fires disproportionately impacts poorer populations across Southeast Asia. We identified two key regions in northern Laos and western Myanmar where particularly high levels of poverty coincide with exposure to relatively high levels of PM2.5 from fires. Our results show that reducing forest and vegetation fires should be a public health priority for the Southeast Asia region.

Long-term exposure to air pollution and mortality in a prospective cohort: The Ontario Health Study

BACKGROUND

Air pollution has been associated with increased mortality. However, updated evidence from cohort studies with detailed information on various risk factors is needed, especially in regions with low air pollution levels. We investigated the associations between long-term exposure to air pollution and mortality in a prospective cohort.

METHODS

We studied 88,615 participants aged ≥30 years from an ongoing cohort study in Ontario, Canada from 2009 to 2017. Exposure to ambient fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) was estimated at participants' residence. Cox proportional hazard models were used to investigate the associations between air pollution and non-accidental, cardiovascular, and respiratory mortality, adjusted for a wide array of individual-level and contextual covariates. Potential effect modification by socio-demographic and behavioral factors was also examined in exploratory stratified analyses.

RESULTS

The fully adjusted hazard ratios (HRs) per 1 µg/m³ increment in PM_2.5 were 1.037 [95% confidence interval (CI): 1.018, 1.057]¸ 1.083 (95% CI: 1.040, 1.128) and 1.109 (95% CI: 1.035, 1.187) for non-accidental, cardiovascular, and respiratory mortality, respectively. Positive associations were also found for NO₂; the corresponding HRs per 1 ppb increment were 1.027 (95% CI: 1.021, 1.034), 1.032 (95% CI: 1.019, 1.046) and 1.044 (95% CI: 1.020, 1.068). We found suggestive evidence of stronger associations in physically active participants, smokers, and those with lower household income.

CONCLUSIONS

Long-term exposure to PM_2.5 and NO₂ was associated with increased risks for non-accidental, cardiovascular, and respiratory mortality, suggesting potential benefits of further improvement in air quality even in low-exposure environments.

Introducing the Microbes and Social Equity Working Group: Considering the Microbial Components of Social, Environmental, and Health Justice

Humans are inextricably linked to each other and our natural world, and microorganisms lie at the nexus of those interactions. Microorganisms form genetically flexible, taxonomically diverse, and biochemically rich communities, i.e., microbiomes that are integral to the health and development of macroorganisms, societies, and ecosystems. Yet engagement with beneficial microbiomes is dictated by access to public resources, such as nutritious food, clean water and air, safe shelter, social interactions, and effective medicine. In this way, microbiomes have sociopolitical contexts that must be considered. The Microbes and Social Equity (MSE) Working Group connects microbiology with social equity research, education, policy, and practice to understand the interplay of microorganisms, individuals, societies, and ecosystems. Here, we outline opportunities for integrating microbiology and social equity work through broadening education and training; diversifying research topics, methods, and perspectives; and advocating for evidence-based public policy that supports sustainable, equitable, and microbial wealth for all.

Green infrastructure can limit but not solve air pollution injustice

Outdoor air pollution contributes to millions of deaths worldwide yet air pollution has differential exposures across racial/ethnic groups and socioeconomic status. While green infrastructure has the potential to decrease air pollution and provide other benefits to human health, vegetation alone cannot resolve health disparities related to air pollution injustice. We discuss how unequal access to green infrastructure can limit air quality improvements for marginalized communities and provide strategies to move forward.

Taking a deep breath: a qualitative study exploring acceptability and perceived unintended consequences of charging clean air zones and air quality improvement initiatives amongst low-income, multi-ethnic communities in Bradford, UK

Background

Poor air quality is the one of the biggest causes of early death and illness across the lifespan. In the UK, 28 local authorities with illegal pollution levels have been mandated by the Government to develop plans to rapidly reduce pollution to legal limits. These plans include consideration of implementing one of four of charging 'Clean Air Zone’ (CAZ) classes in areas of high pollution which would charge older polluting vehicles a daily charge to enter. While this offers a potential to improve air quality, the extent to which CAZ might impact (for example, economically) on socio-economically deprived groups and local businesses is unclear.

Aims

To explore the acceptability and perceived unintended consequences of a CAZ and other initiatives to improve air quality with seldom-heard communities living in deprived, multi-ethnic areas within the city of Bradford, UK.

Methods

Ten semi-structured focus groups were conducted with people who live in areas of high pollution and deprivation. A total of 87 people participated from a diverse range of ethnic backgrounds with the majority of Pakistani origin. Recorded data were transcribed, coded and analysed using thematic analysis.

Findings

As poor air quality was not always visible it was seen as a hidden issue by many, and not prioritised over other more visible environmental issues (e.g. fly-tipping, littering). There was resistance to proposals which included charging private vehicles. Many felt that low-income families did not have the resources to purchase compliant vehicles or pay daily charges, placing a disproportionate burden on them. It was also felt that low-income taxi drivers would be disproportionately affected financially by proposals. Public transport infrastructure was felt to be inadequate. Other traffic management or emission reduction activities were also explored. Views towards these initiatives were more positive if they did not directly affect individuals financially.

Conclusion

Air quality initiatives such as CAZs were felt to be likely to financially disadvantage communities already living in socio-economic and environmental poverty. Policy makers need to carefully consider appropriate mitigation strategies to ensure that health and economic inequalities are not increased by implementation of CAZ. Given air quality is low priority for some groups, careful engagement and communication will be required to increase acceptance interventions such as CAZs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11337-z.

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.

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.

Exposure to Particulate Matter Air Pollution and Anosmia

IMPORTANCE

Anosmia, the loss of the sense of smell, has profound implications for patient safety, well-being, and quality of life, and it is a predictor of patient frailty and mortality. Exposure to air pollution may be an olfactory insult that contributes to the development of anosmia.

OBJECTIVE

To investigate the association between long-term exposure to particulate matter (PM) with an aerodynamic diameter of no more than 2.5 μm (PM2.5) with anosmia.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study examined individuals who presented from January 1, 2013, through December 31, 2016, at an academic medical center in Baltimore, Maryland. Case participants were diagnosed with anosmia by board-certified otolaryngologists. Control participants were selected using the nearest neighbor matching strategy for age, sex, race/ethnicity, and date of diagnosis. Data analysis was conducted from September 2020 to March 2021.

EXPOSURES

Ambient PM2.5 levels.

MAIN OUTCOMES AND MEASURES

Novel method to quantify ambient PM2.5 exposure levels in patients diagnosed with anosmia compared with matched control participants.

RESULTS

A total of 2690 patients were identified with a mean (SD) age of 55.3 (16.6) years. The case group included 538 patients with anosmia (20%), and the control group included 2152 matched control participants (80%). Most of the individuals in the case and control groups were women, White patients, had overweight (BMI 25 to <30), and did not smoke (women: 339 [63.0%] and 1355 [63.0%]; White patients: 318 [59.1%] and 1343 [62.4%]; had overweight: 179 [33.3%] and 653 [30.3%]; and did not smoke: 328 [61.0%] and 1248 [58.0%]). Mean (SD) exposure to PM2.5 was significantly higher in patients with anosmia compared with healthy control participants at 12-, 24-, 36-, 60-month time points: 10.2 (1.6) μg/m3 vs 9.9 (1.9) μg/m3; 10.5 (1.7) μg/m3 vs 10.2 (1.9) μg/m3; 10.8 (1.8) μg/m3 vs 10.4 (2.0) μg/m3; and 11.0 (1.8) μg/m3 vs 10.7 (2.1) μg/m3, respectively. There was an association between elevated PM2.5 exposure level and odds of anosmia in multivariate analyses that adjusted for age, sex, race/ethnicity, body mass index, alcohol or tobacco use, and medical comorbidities (12 mo: odds ratio [OR], 1.73; 95% CI, 1.28-2.33; 24 mo: OR, 1.72; 95% CI, 1.30-2.29; 36 mo: OR, 1.69; 95% CI, 1.30-2.19; and 60 mo: OR, 1.59; 95% CI, 1.22-2.08). The association between long-term exposure to PM2.5 and the odds of developing anosmia was nonlinear, as indicated by spline analysis. For example, for 12 months of exposure to PM2.5, the odds of developing anosmia at 6.0 µg/m3 was OR 0.79 (95% CI, 0.64-0.97); at 10.0 µg/m3, OR 1.42 (95% CI, 1.10-1.82); at 15.0 µg/m3, OR 2.03 (95% CI, 1.15-3.58).

CONCLUSIONS AND RELEVANCE

In this study, long-term airborne exposure to PM2.5 was associated with anosmia. Ambient PM2.5 represents a potentially ubiquitous and modifiable risk factor for the loss of sense of smell.

Short and long term exposure to air pollution increases the risk of ischemic heart disease

Previous studies have suggested an increased risk of ischemic heart disease related to air pollution. This study aimed to explore both the short-term and long-term effects of air pollutants on the risk of ischemic heart disease after adjusting for meteorological factors. The Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2013 was used. Overall, 2155 participants with ischemic heart disease and 8620 control participants were analyzed. The meteorological data and air pollution data, including SO₂ (ppm), NO₂ (ppm), O₃ (ppm), CO (ppm), and particulate matter (PM)₁₀ (μg/m³), were analyzed using conditional logistic regression. Subgroup analyses were performed according to age, sex, income, and region of residence. One-month exposure to SO₂ was related to 1.36-fold higher odds for ischemic heart disease (95% confidence interval [95% CI] 1.06–1.75). One-year exposure to SO₂, O₃, and PM₁₀ was associated with 1.58- (95% CI 1.01–2.47), 1.53- (95% CI 1.27–1.84), and 1.14 (95% CI 1.02–1.26)-fold higher odds for ischemic heart disease. In subgroup analyses, the ≥ 60-year-old group, men, individuals with low income, and urban groups demonstrated higher odds associated with 1-month exposure to SO₂. Short-term exposure to SO₂ and long-term exposure to SO_2, O₃, and PM₁₀ were related to ischemic heart disease.

[Higher risk of COVID-19 hospitalization for unemployed: an analysis of health insurance data from 1.28 million insured individuals in Germany]

BACKGROUND AND OBJECTIVE

Unemployment is related to poverty and is a risk factor for poor health. The present study investigates if unemployment increases the risk of COVID-19 hospitalization for men and women of working age in Germany.

METHODS

The study uses the health insurance data from AOK Rhineland/Hamburg (from 1 January 2020 until 18 June 2020) of 1,288,745 persons aged between 18 and 65. Four employment situations are distinguished: (1) regular employment, (2) low-wage employment with social support, (3) unemployment with receipt of unemployment benefit 1, and (4) long-term unemployment with receipt of unemployment benefit 2. COVID-19 hospitalizations are measured on the basis of the ICD codes U07.1 and U07.2 reported by the hospitals. Multiple logistic regression models are calculated (adjusted for age and sex).

RESULTS

During the observation period, 1521 persons had hospitalization with COVID-19 as primary or secondary diagnosis. Overall, this corresponds to a rate of 118 cases per 100,000 insured persons. Rates varied by employment situation. Compared with regularly employed persons, the odds ratio for a hospitalization was 1.94 (CI 95%: 1.74-2.15) for long-term unemployment, 1.29 (0.86-1.94) for unemployed, and 1.33 (0.98-1.82) for low-wage employment.

CONCLUSION

The results are in line with earlier studies from the USA and Great Britain reporting socioeconomic inequalities in COVID-19 hospitalization risk. This provides the first empirical support that socioeconomic inequalities in the severity of COVID-19 also exists in Germany.

Socioeconomic Differences in Walking Time of Children and Adolescents to Public Green Spaces in Urban Areas-Results of the German Environmental Survey (2014-2017)

Public green spaces have a high potential for a positive impact on people's health and wellbeing, especially in urban areas. Studies on environmental justice indicate socially unequal access possibilities to urban green spaces. This article presents results on associations between individual socioeconomic position (SEP) and walking time from home to public green spaces in young people living in urban areas with more than 20,000 inhabitants in Germany. Data were derived from the German Environmental Survey for Children and Adolescents 2014-2017 (GerES V), the environmental module of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS Wave 2). The sample comprises 1149 participants aged 3 to 17 years. A total of 51.5% of the participants reach a public green space on foot within five and 72.8% within ten minutes from home. The lower the participant's SEP, the longer the walking time. Logistic regression models controlling for age group, sex, migration background, and region of residence show that participants with a low SEP have a significantly higher risk (odds ratio = 1.98; 95% confidence interval: 1.31-2.99) of needing more than ten minutes to walk from home to a public green space than participants with a high SEP. GerES V data indicate that young people living in urban areas in Germany do not equally benefit from the health-promoting potential of green spaces, which is an important aspect of environmental health inequalities.

Residential exposure to air pollution and access to neighborhood greenspace in relation to hair cortisol concentrations during the second and third trimester of pregnancy

BACKGROUND

Exposure to air pollution during pregnancy has been associated with adverse pregnancy outcomes in studies worldwide, other studies have described beneficial effects of residential greenspace on pregnancy outcomes. The biological mechanisms that underlie these associations are incompletely understood. A biological stress response, which implies release of cortisol, may underlie associations of air pollution exposure and access to neighborhood greenspaces with health.

METHODS

We explored residential exposure to air pollution and residential access to neighborhood greenspaces in relation to hair cortisol concentrations of participants in a prospective pregnancy cohort study in Flanders, Belgium. Hair samples were collected at the end of the second pregnancy trimester (n = 133) and shortly after delivery (n = 81). Cortisol concentrations were measured in 3-cm scalp-near hair sections, to reflect second and third pregnancy trimester cortisol secretion. We estimated long-term (3 months before sampling) residential exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and black carbon (BC), assessed residential distance to major roads and residential access to neighborhood greenspaces (NHGS). Associations between residential exposures and hair cortisol concentrations were studied using linear regression models while adjusting for season of sampling.

RESULTS

Three-month mean residential NO₂ and BC concentrations were positively associated with third pregnancy trimester hair cortisol concentrations (p = 0.008 and p = 0.017). Access to a large NHGS (10 ha or more within 800 m from residence) was negatively associated with third trimester hair cortisol concentrations (p = 0.019). Access to a large NHGS significantly moderated the association between residential proximity to major roads and second trimester hair cortisol concentrations (p = 0.021). Residential distance to major roads was negatively associated with second trimester hair cortisol concentrations of participants without access to a large NHGS (p = 0.003). The association was not significant for participants with access to a large NHGS. The moderation tended towards significance in the third pregnancy trimester (p < 0.10).

CONCLUSIONS

Our findings suggest a positive association between long-term residential exposure to air pollution and biological stress during pregnancy, residential access to neighborhood greenspaces may moderate the association. Further research is needed to confirm our results.

TRIAL REGISTRATION

The IPANEMA study is registered under number  NCT02592005 at clinicaltrials.gov .

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.

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.

Long-term effects of ambient PM2.5 on hypertension in multi-ethnic population from Sichuan province, China: a study based on 2013 and 2018 health service surveys

Hypertension, a major risk factor of many severe chronic diseases and leading cause of global disease burden, is reported to be associated with long-term exposure to PM_2.5. China's high PM_2.5 pollution level has become a major public health issue. However, existing studies from China have got inconsistent results with very limited investigation into the multi-ethnic peoples. This study adds multi-ethnic evidence from Sichuan Province, southwestern China, and assesses ethnic differences of PM_2.5 exposure effect on hypertension. We pooled large cross-sectional data from two surveys conducted in 2013 and 2018 to examine the association of long-term exposure to PM_2.5 on prevalence of hypertension in adults aged 30 years old and above. Community-specified annual PM_2.5 concentration was estimated using satellite data. Thirty-one thousand four hundred sixty-two participants with average exposure concentration of 32.8 μg/m³ were included. The proportions of the Han, the Tibetan, the Yi, and other ethnic people were 89.2%, 7.3%, 3.2%, and 0.3%, respectively. The adjusted odds ratio (OR) was 1.08 (95% CI, 1.04-1.12) for a 10 μg/m³ PM_2.5 concentration increment. The adjusted ORs for the Han, the Tibetan, and the Yi were 1.08 (95% CI, 1.04-1.12), 0.03 (95% CI, 0.00-0.27), and 1.75 (95% CI, 1.28-2.38) for a 10 μg/m³ PM_2.5 concentration increment, respectively. Stratification analysis found stronger associations in participants with chronic diseases and Yi minority population. The results showed that long-term exposure to PM_2.5 may increase the risk of hypertension prevalence in Chinese multi-ethnic adults. The associations were different among ethnicities.

Performance of a Low-Cost Sensor Community Air Monitoring Network in Imperial County, CA

Air monitoring networks developed by communities have potential to reduce exposures and affect environmental health policy, yet there have been few performance evaluations of networks of these sensors in the field. We developed a network of over 40 air sensors in Imperial County, CA, which is delivering real-time data to local communities on levels of particulate matter. We report here on the performance of the Network to date by comparing the low-cost sensor readings to regulatory monitors for 4 years of operation (2015-2018) on a network-wide basis. Annual mean levels of PM10 did not differ statistically from regulatory annual means, but did for PM2.5 for two out of the 4 years. R2s from ordinary least square regression results ranged from 0.16 to 0.67 for PM10, and increased each year of operation. Sensor variability was higher among the Network monitors than the regulatory monitors. The Network identified a larger number of pollution episodes and identified under-reporting by the regulatory monitors. The participatory approach of the project resulted in increased engagement from local and state agencies and increased local knowledge about air quality, data interpretation, and health impacts. Community air monitoring networks have the potential to provide real-time reliable data to local populations.