Socioeconomic and ethnic inequalities in exposure to air and noise pollution in London

Tonne, Cathryn; Milà, Carles; Fecht, Daniela; Álvarez, Mar; Gulliver, John; Smith, Jane; Beevers, Sean; Anderson, Hugh; Kelly, Frank J.

doi:10.1016/j.envint.2018.03.023

Cited by 97 publications

(71 citation statements)

References 31 publications

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“…A study from London, UK, analysing socioeconomic and ethnic inequalities in exposure to noise pollution, reported that individuals with the highest household income, white ethnicity, and lowest income deprivation group were more likely to be exposed to aircraft noise. Participants in the group with the most area-level income deprivation were most likely to be exposed to rail noise [34]. A study from Ghent, Belgium, analysing residential exposure to noise found that only neighbourhoods with a higher percentage of people of a specific foreign origin (non-EU and non-Turkish-Maghreb) had a significantly higher exposure [35].…”

Section: Discussionmentioning

confidence: 99%

Social Inequalities in Environmental Noise Exposure: A Review of Evidence in the WHO European Region

Dreger

Schüle

Hilz

et al. 2019

IJERPH

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Environmental noise is an important public health problem, being among the top environmental risks to health. The burden of noise exposure seems to be unequally distributed in societies. Up to now there is fragmentary evidence regarding which social groups are most affected. The aim of this review was to systematically assess published evidence on social inequalities in environmental noise exposure in the WHO European Region, taking different sociodemographic and socioeconomic dimensions as well as subjective and objective measures of environmental noise exposure into account. Articles published in English in a peer reviewed journal between 2010 and 2017 were included in the review. Eight studies were finally included in the review, four of them analysed aggregated data and four analysed individual data. Though results of social inequalities in noise exposures were mixed between and within studies, there was a trend that studies using indicators of material deprivation and deprivation indices showed higher environmental noise exposures in groups with lower socioeconomic position. More research on the social distribution of environmental noise exposure on a small spatial scale is needed, taking into account aspects of vulnerability and procedural justice.

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Section: Discussionmentioning

confidence: 99%

Social Inequalities in Environmental Noise Exposure: A Review of Evidence in the WHO European Region

Dreger

Schüle

Hilz

et al. 2019

IJERPH

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“…This result might be due to the potential bias of subjectively reported data on mental disorders and occupational stress for people with higher income levels [ 76 ]. Moreover, people with higher income levels have been found to suffer from more personal exposure to traffic-related air pollution, which might worsen their subjective health evaluations [ 77 ].…”

Section: Discussionmentioning

confidence: 99%

A Multilevel Analysis of Perceived Noise Pollution, Geographic Contexts and Mental Health in Beijing

Kwan

et al. 2018

IJERPH

100

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With rapid urbanization and increase in car ownership, ambient noise pollution resulting from diversified sources (e.g., road traffic, railway, commercial services) has become a severe environmental problem in the populated areas in China. However, research on the spatial variation of noise pollution and its potential effects on urban residents’ mental health has to date been quite scarce in developing countries like China. Using a health survey conducted in Beijing in 2017, we for the first time investigated the spatial distributions of multiple noise pollution perceived by residents in Beijing, including road traffic noise, railway (or subway) noise, commercial noise, and housing renovation (or construction) noise. Our results indicate that there is geographic variability in noise pollution at the neighborhood scale, and road traffic and housing renovation/construction are the principal sources of noise pollution in Beijing. We then employed Bayesian multilevel logistic models to examine the associations between diversified noise pollution and urban residents’ mental health symptoms, including anxiety, stress, fatigue, headache, and sleep disturbance, while controlling for a wide range of confounding factors such as socio-demographics, objective built environment characteristics, social environment and geographic context. The results show that perceived higher noise-pollution exposure is significantly associated with worse mental health, while physical environment variables seem to contribute little to variations in self-reported mental disorders, except for proximity to the main road. Social factors or socio-demographic attributes, such as age and income, are significant covariates of urban residents’ mental health, while the social environment (i.e., community attachment) and housing satisfaction are significantly correlated with anxiety and stress. This study provides empirical evidence on the noise-health relationships in the Chinese context and sheds light on the policy implications for environmental pollution mitigation and healthy city development in China.

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“…An ensemble of conditional quantile functions was analyzed by fitting separate bivariate models between individual exposure and nine characteristics (age, education, income, commute time, vehicle possession, smoking, ventilation system, BMI, respiratory disease) for quantile levels 0.1 to 0.9 at the interval of 0.05. Bootstrapping is used to estimate standard errors and confidence intervals, accounting for the hierarchical data structure [21]. The coefficients, which are interpreted as the impact of a one-unit change of the covariate on the personal exposure (μg/m 3 ) while holding all other variables constant, will be compared against those derived from the ordinary least square (OLS) regression.…”

Section: Methodsmentioning

confidence: 99%

Assessment of personal exposure to particulate air pollution: the first result of City Health Outlook (CHO) project

Gong

Cong

et al. 2019

BMC Public Health

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Background To mitigate air pollution-related health risks and target interventions towards the populations bearing the greatest risks, the City Health Outlook (CHO) project aims to establish multi-scale, long-lasting, real-time urban environment and health monitoring networks. A major goal of CHO is to collect data of personal exposure to particulate air pollution through a full profile that consists of a matrix of activities and micro-environments. As the first paper of a series, this paper is targeted at illustrating the characteristics of the participants and examining the effects of different covariates on personal exposure at various air pollution exposure levels. Methods In the first campaign, volunteers are recruited to wear portable environmental sensors to record their real-time personal air pollution exposure and routes. After a web-based social media recruitment strategy, 50 eligible subjects joined the first campaign in Beijing from January 8 to January 20, 2018. The mean personal exposures were measured at 19.36, 37.65, and 43.45 μg/m 3 for particulate matter (PM) with a diameter less than 1, 2.5, and 10 μm, respectively, albeit with the high spatial-temporal variations. Results Unequal distribution of exposures was observed in the subjects with different sociodemographic status, travel behavior, living and health conditions. Quantile regression analysis reveals that subjects who are younger, less educated, exposed to passive smoking, low to middle household income, overweight, without ventilation system at home or office, and do not possess private vehicles, are more susceptible to PM pollution. The differences, however, are generally insignificant at low exposure levels and become evident on bad air quality days. Conclusions The heterogeneity in personal exposure found in this the first CHO campaign highlighted the importance of studying the pollution exposure at the individual scale. It is at the critical stage to bridge the knowledge gap of environmental inequality in different populations, which can lead to great health implications. Electronic supplementary material The online version of this article (10.1186/s12889-019-7022-8) contains supplementary material, which is available to authorized users.

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Socioeconomic and ethnic inequalities in exposure to air and noise pollution in London

Cited by 97 publications

References 31 publications

Social Inequalities in Environmental Noise Exposure: A Review of Evidence in the WHO European Region

Social Inequalities in Environmental Noise Exposure: A Review of Evidence in the WHO European Region

A Multilevel Analysis of Perceived Noise Pollution, Geographic Contexts and Mental Health in Beijing

Assessment of personal exposure to particulate air pollution: the first result of City Health Outlook (CHO) project

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