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Ambient air pollution is a long-standing and significant public health issue. The aim of this review is to systematically examine the peer-reviewed evidence on social inequalities and ambient air pollution in the World Health Organization European Region. Articles published between 2010 and 2017 were analyzed in the review. In total 31 articles were included in the review. There is good evidence from ecological studies that higher deprivation indices and low economic position are usually linked with higher levels of pollutants such as particulate matter (particulate matter under 2.5 and 10 microns in diameter, PM2.5, PM10) and oxides of nitrogen (e.g., NO2, and NOx). There is also evidence that ethnic minorities experience a mixed exposure in comparison to the majority population being sometimes higher and sometimes lower depending on the ethnic minority under consideration. The studies using data at the individual level in this review are mainly focused on pregnant women or new mothers, in these studies deprivation and ethnicity are more likely to be linked to higher exposures of poor air quality. Therefore, there is evidence in this review that the burden of higher pollutants falls disproportionally on different social groups.

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Residential green and blue spaces and their potential health benefits have received increasing attention in the context of environmental health inequalities, because an unequal social distribution of these resources may contribute to inequalities in health outcomes. This systematic review synthesised evidence of environmental inequalities, focusing on availability and accessibility measures of green and blue spaces. Studies in the World Health Organisation (WHO) European Region published between 2010 and 2017 were considered for the review. In total, 14 studies were identified, where most of them (n = 12) analysed inequalities of green spaces. The majority had an ecological study design that mostly applied deprivation indices on the small area level, whereas cross-sectional studies on the individual level mostly applied single social measures. Ecological studies consistently showed that deprived areas had lower green space availability than more affluent areas, whereas mixed associations were found for single social dimensions in cross-sectional studies on the individual level. In order to gain more insights into how various social dimensions are linked to the distribution of environmental resources within the WHO European Region, more studies are needed that apply comparable methods and study designs for analysing social inequalities in environmental resources.

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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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Perceived annoyance due to traffic noise and lack of urban green space is mostly determined using data from self-administered questionnaires. However, there is still no clear evidence to what extent such perceived measures are related to objectively assessed environmental data and whether socioeconomic dimensions modify such relationships. In a cross-sectional study in Dortmund, Germany, georeferenced home addresses from parents with preschool aged children were used to analyse relations between exposures to objectively measured green space and traffic noise and subjective annoyance due to noise and lack of green space with the additional consideration of socioeconomic characteristics as effect modifiers. Higher perceived annoyance correlated with higher objectively measured traffic noise and lower objectively measured green, respectively. Stratified logistic regression models indicated a modifying role of socioeconomic characteristics. The strengths of associations between objectively measured environmental exposures and perceived annoyance differed by socioeconomic strata. Especially for noise, odds ratios were higher in low socioeconomic strata than in high socioeconomic strata. Therefore, using objective measures of the built environment as a proxy for individual perception should be made with caution as negative relations between objectively assessed built environments and health could be underestimated when considering individual socioeconomic position only as a confounder.

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BACKGROUND: The environmental justice framework states that besides environmental burdens also resources may be social unequally distributed both on the individual and on the neighbourhood level. This ecological study investigated whether neighbourhood socioeconomic position (SEP) was associated with neighbourhood public green space availability in a large German city with more than 1 million inhabitants. METHODS: Two different measures were defined for green space availability. Firstly, percentage of green space within neighbourhoods was calculated with the additional consideration of various buffers around the boundaries. Secondly, percentage of green space was calculated based on various radii around the neighbourhood centroid. An index of neighbourhood SEP was calculated with principal component analysis. Log-gamma regression from the group of generalized linear models was applied in order to consider the non-normal distribution of the response variable. All models were adjusted for population density. RESULTS: Low neighbourhood SEP was associated with decreasing neighbourhood green space availability including 200m up to 1000m buffers around the neighbourhood boundaries. Low neighbourhood SEP was also associated with decreasing green space availability based on catchment areas measured from neighbourhood centroids with different radii (1000m up to 3000 m). With an increasing radius the strength of the associations decreased. CONCLUSIONS: Social unequally distributed green space may amplify environmental health inequalities in an urban context. Thus, the identification of vulnerable neighbourhoods and population groups plays an important role for epidemiological research and healthy city planning. As a methodical aspect, log-gamma regression offers an adequate parametric modelling strategy for positively distributed environmental variables.

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Spatial differences in urban environmental conditions contribute to health inequalities within cities. The purpose of the paper is to map environmental inequalities relevant for health in the City of Dortmund, Germany, in order to identify needs for planning interventions. We develop suitable indicators for mapping socioeconomically-driven environmental inequalities at the neighborhood level based on published scientific evidence and inputs from local stakeholders. Relationships between socioeconomic and environmental indicators at the level of 170 neighborhoods were analyzed continuously with Spearman rank correlation coefficients and categorically applying chi-squared tests. Reclassified socioeconomic and environmental indicators were then mapped at the neighborhood level in order to determine multiple environmental burdens and hotspots of environmental inequalities related to health. Results show that the majority of environmental indicators correlate significantly, leading to multiple environmental burdens in specific neighborhoods. Some of these neighborhoods also have significantly larger proportions of inhabitants of a lower socioeconomic position indicating hotspots of environmental inequalities. Suitable planning interventions mainly comprise transport planning and green space management. In the conclusions, we discuss how the analysis can be used to improve state of the art planning instruments, such as clean air action planning or noise reduction planning towards the consideration of the vulnerability of the population.

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BACKGROUND: Structural factors of neighbourhood environments in which children live have attracted increasing attention in epidemiological research. This study investigated whether neighbourhood socioeconomic position (SEP), public playground and park space, and perceived environmental exposures were independently associated with overweight in preschool aged children while simultaneously considering individual child and family factors. METHODS: Body-Mass-Index (BMI) data from 3499 children (53% boys and 47% girls) from three surveys between 2004 and 2007 from 18 school enrolment zones in the city of Munich, Germany, were analysed with hierarchical logistic regression models. An index of neighbourhood SEP was calculated with principal component analysis. Individual socioeconomic data, parental BMI, birth weight, housing characteristics, and perceived annoyance due to exposures to noise, air pollution, lack of greenspace, and traffic were collected with parental questionnaires. Measures of age-specific playground space and availability of park space derived from Geographic Information System were additionally weighted with age-specific population data. RESULTS: In bivariate analysis perceived annoyance due to exposures to noise or lack of greenspace, high frequency of lorries, traffic jam, living in a multiple dwelling or next to a main road, low neighbourhood SEP, and low playground space were significantly associated with overweight. However, in multivariate analysis only living in a multiple dwelling was independently associated with overweight. From the considered individual child and family factors low parental education, parental overweight or obesity, and a high birthweight showed an independent relation to overweight. CONCLUSIONS: Our study identified individual child and parental factors, and living in a multiple dwelling as the strongest predictors for overweight in preschool aged children. However, perceived annoyance to built environmental exposures additionally explained overweight variance between neighbourhoods. Based on our findings interventions and policies addressing overweight prevention in young children should focus on parental behaviours and the immediate home environment.

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BACKGROUND: The context of the close neighbourhood environment in which children live has gained increasing attention in epidemiological research. This study aimed to investigate if contextual neighbourhood socioeconomic position (SEP) was independently associated with overweight in young children aged 5-7 years while simultaneously considering a wide range of individual socioeconomic determinants and known risk factors for overweight. METHODS: Objectively measured body mass index (BMI) data from 3499 children (53 % boys and 47 % girls) from three surveys between 2004 and 2007 clustered in 18 school enrolment zones in the city of Munich, Germany, were analysed with hierarchical logistic regression models. An index of neighbourhood SEP was calculated with principal component analysis using aggregated data. Individual socioeconomic data, maternal BMI, and birth weight were collected with parental questionnaires. We analysed how much of the between neighbourhood variance of overweight was attributable to individual factors and how much was explained by neighbourhood SEP. RESULTS: The prevalence of overweight, including obesity, was 14.1 %. In the final adjusted model low neighbourhood SEP was independently associated with overweight (odds ratio (OR) = 1.42, 95 % confidence interval (CI) = 1.00-2.00) compared to high neighbourhood SEP. On the individual level low parental education (OR = 1.99, 95 % CI = 1.49-2.65) or middle parental education (OR = 1.50, 95 % CI = 1.16-1.95) compared to high parental education and nationality of the child other than German (OR = 1.53, 95 % CI = 1.17-1.99) compared to German nationality were independently associated with overweight. CONCLUSIONS: Whereas individual determinants were the main drivers in explaining between neighbourhood variance, neighbourhood SEP additionally explained differences in overweight between neighbourhoods. Thus, considering neighbourhood context in intervention planning could result in more effective strategies compared to measures only focusing on individual determinants of overweight.

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BACKGROUND: The research question how contextual factors of neighbourhood environments influence individual health has gained increasing attention in public health research. Both socioeconomic neighbourhood characteristics and factors of the built environment play an important role for health and health-related behaviours. However, their reciprocal relationships have not been systematically reviewed so far. This systematic review aims to identify studies applying a multilevel modelling approach which consider both neighbourhood socioeconomic position (SEP) and factors of the objective built environment simultaneously in order to disentangle their independent and interactive effects on individual health. METHODS: The three databases PubMed, PsycINFO, and Web of Science were systematically searched with terms for title and abstract screening. Grey literature was not included. Observational studies from USA, Canada, Australia, New Zealand, and Western European countries were considered which analysed simultaneously factors of neighbourhood SEP and the objective built environment with a multilevel modelling approach. Adjustment for individual SEP was a further inclusion criterion. RESULTS: Thirty-three studies were included in qualitative synthesis. Twenty-two studies showed an independent association between characteristics of neighbourhood SEP or the built environment and individual health outcomes or health-related behaviours. Twenty-one studies found cross-level or within-level interactions either between neighbourhood SEP and the built environment, or between neighbourhood SEP or the built environment and individual characteristics, such as sex, individual SEP or ethnicity. Due to the large variation of study design and heterogeneous reporting of results the identification of consistent findings was problematic and made quantitative analysis not possible. CONCLUSIONS: There is a need for studies considering multiple neighbourhood dimensions and applying multilevel modelling in order to clarify their causal relationship towards individual health. Especially, more studies using comparable characteristics of neighbourhood SEP and the objective built environment and analysing interactive effects are necessary to disentangle health impacts and identify vulnerable neighbourhoods and population groups.

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BACKGROUND: With one quarter of the world population infected, the intestinal nematode Ascaris lumbricoides is one of the most common infectious agents, especially in the tropics and sub-tropics. Infection is caused by oral intake of eggs and can cause respiratory and gastrointestinal problems. To identify high risk areas for intervention, it is necessary to understand the effects of climatic, environmental and socio-demographic conditions on A. lumbricoides infection. METHODOLOGY: Cross-sectional survey data of 6,366 study participants in the Mbeya region of South-Western Tanzania were used to analyze associations between remotely sensed environmental data and A. lumbricoides infection. Non-linear associations were accounted for by using fractional polynomial regression, and socio-demographic and sanitary data were included as potential confounders. PRINCIPAL FINDINGS: The overall prevalence of A. lumbricoides infection was 6.8%. Our final multivariable model revealed a significant non-linear association between rainfall and A. lumbricoides infection with peak prevalences at 1740 mm of mean annual rainfall. Mean annual land surface temperature during the day was linearly modeled and negatively associated with A. lumbricoides infection (odds ratio (OR) = 0.87, 95% confidence interval (CI) = 0.78-0.97). Furthermore, age, which also showed a significant non-linear association (infection maximum at 7.7 years), socio-economic status (OR = 0.82, CI = 0.68-0.97), and latrine coverage around the house (OR = 0.80, CI = 0.67-0.96) remained in the final model. CONCLUSIONS: A. lumbricoides infection was associated with environmental, socio-demographic and sanitary factors both in uni- and multivariable analysis. Non-linear analysis with fractional polynomials can improve model fit, resulting in a better understanding of the relationship between environmental conditions and helminth infection, and more precise predictions of high prevalence areas. However, socio-demographic determinants and sanitary conditions should also be considered, especially when planning public health interventions on a smaller scale, such as the community level.

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