Characterising socio-economic inequalities in exposure to air pollution: A comparison of socio-economic markers and scales of measurement

Goodman, Anna; Wilkinson, Paul; Stafford, Mai; Tonne, Cathryn

doi:10.1016/j.healthplace.2011.02.002

Cited by 72 publications

(60 citation statements)

References 30 publications

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“…the Income domain and the Employment domain) only, keeping the original proportion of weights (equal weight for each domain) at the Lower-level Super Output Area (LSOA), following the approaches used in previous studies [38][39][40]. This is to avoid the duplication in explanatory and dependent variables in the analysis, though high correlation between the original and modified deprivation index (Pearson's r = 0.95) suggests little effect on the main results.…”

Section: Measurement Of Socioeconomic Deprivationmentioning

confidence: 99%

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

et al. 2017

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Background: Socioeconomically disadvantaged populations often have higher exposures to particulate air pollution, which can be expected to contribute to differentials in life expectancy. We examined socioeconomic differentials in exposure and air pollution-related mortality relating to larger scale (5 km resolution) variations in background concentrations of selected pollutants across England. Methods: Ozone and particulate matter (sub-divided into PM 10 , PM 2.5 , PM 2.5-10 , primary, nitrate and sulphate PM 2.5 ) were simulated at 5 km horizontal resolution using an atmospheric chemistry transport model (EMEP4UK). Annual mean concentrations of these pollutants were assigned to all 1,202,578 residential postcodes in England, which were classified by urban-rural status and socioeconomic deprivation based on the income and employment domains of the 2010 English Index of Multiple Deprivation for the Lower-level Super Output Area of residence. We used life table methods to estimate PM 2.5 -attributable life years (LYs) lost in both relative and absolute terms. Results: Concentrations of the most particulate fractions, but not of nitrate PM 2.5 or ozone, were modestly higher in areas of greater socioeconomic deprivation. Relationships between pollution level and socioeconomic deprivation were non-linear and varied by urban-rural status. The pattern of PM 2.5 concentrations made only a small contribution to the steep socioeconomic gradient in LYs lost due to PM 2.5 per 10 3 population, which primarily was driven by the steep socioeconomic gradient in underlying mortality rates. In rural areas, the absolute burden of air pollution-related LYs lost was lowest in the most deprived deciles. Conclusions: Air pollution shows modest socioeconomic patterning at 5 km resolution in England, but absolute attributable mortality burdens are strongly related to area-level deprivation because of underlying mortality rates. Measures that cause a general reduction in background concentrations of air pollution may modestly help narrow socioeconomic differences in health.

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Section: Measurement Of Socioeconomic Deprivationmentioning

confidence: 99%

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

et al. 2017

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“…Doing so avoided 'double counting' the health and air pollution components that would have occurred had the summary WIMD score been used and therefore minimised the possibility of delivering skewed results. 7,18,23 It was not possible to account for all confounding factors. Smoking, for example, is a key risk factor for the health outcomes of interest in this study, but only Local Authority-level smoking prevalence data were available which were based on self-reported survey responses from a sample of the Welsh population.…”

Section: Limitationsmentioning

confidence: 99%

“…6 Thus, a triple jeopardy exists where air pollution, impaired health and deprivation can combine to create increased and disproportionate disease burdens between and within regions. 7,8 Given these relationships, regarding local air pollution problems as isolated concerns is a mistake; they should be considered in the broadest possible public health context. 9 However, this is rarely recognised or realised.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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“…Air pollution inequality is rising across regions in China, and the more heavily polluted regions suffer more health damage [4]. To parallel recent studies on examining air pollution inequality in the US [5][6][7][8] and Europe [9][10][11][12], it is important to bring the equal opportunity for people to have the healthy and clean environment [7]. Therefore, it is worthy to investigate emission disparities in China regions and what trends have occurred in air pollution inequality in recent years.…”

Section: Introductionmentioning

confidence: 99%

Air Pollution Inequality and Its Sources in SO2 and NOX Emissions among Chinese Provinces from 2006 to 2015

2018

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This paper investigates inequality in SO 2 and NO X emissions, by observing their extraordinary levels and uneven distribution in China during the period of the 11th and 12th Five-Year Plans (FYPs, 2006(FYPs, -2015. This provincial and regional analysis utilizing the Theil index and Kaya factors help us to find the trajectory of inequality and its primary sources. Based on our analysis, we conclude the driving factors behind emissions inequalities are as follows. There are four economic factors of per capita SO 2 emission: SO 2 emission intensity of coal consumption, coal intensity of power generation, power intensity of GDP, and per capita GDP. Additionally, there are four urban development factors of per capita NO X emission: NO X emission intensity of gasoline consumption, proportion of gasoline vehicles, vehicle use in urban population, and urbanization rate. The SO 2 emission results represent an increase of 6% in overall inequality where the inequality of power intensity of GDP is the main contributor. In terms of NO X emission, the 3% growth in total inequality is related to the high effect of NO X emission intensity of gasoline consumption. We also examine the effect of other factors affecting the trajectory of inequalities. To apply these results in practice, we compare the 11th and 12th FYPs and give some policy suggestions.

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Characterising socio-economic inequalities in exposure to air pollution: A comparison of socio-economic markers and scales of measurement

Cited by 72 publications

References 30 publications

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

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

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

Air Pollution Inequality and Its Sources in SO2 and NOX Emissions among Chinese Provinces from 2006 to 2015

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