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Background: Evidence from studies of air pollutants and birth outcomes suggests an association, but uncertainties around geographical variability and modifying factors still remain. As neighborhood-level social characteristics are associated with birth outcomes, we assess whether neighborhood deprivation level is an effect measure modifier on the association between air pollution and birth outcomes in a North Carolina birth cohort. Methods: Using birth certificate data, all North Carolina residential singleton live births from 1 January 2011 to 31 December 2015 with gestational ages of 20–44 weeks (n = 566,799) were examined for birth defect diagnoses and preterm birth. Exposures were daily average fine particulate matter (PM2.5), daily 8-h maximum nitrogen dioxide (NO2), and daily 8-h maximum ozone (O3) modeled concentrations, and the modifier of interest was the neighborhood deprivation index (NDI). Linear binomial models were used to estimate the prevalence differences and 95% confidence intervals (CI) for the association between ambient air pollution and birth defect diagnoses. Modified Poisson regression models were used to estimate risk differences (RDs) and 95% CIs for air pollution and preterm birth. Models were stratified by the neighborhood deprivation index group (low, medium, or high) to assess potential modification by NDI. Results: Approximately 3.1% of the study population had at least one birth defect and 8.18% were born preterm. For preterm birth, associations with PM2.5 and O3 did not follow a conclusive pattern and there was no evidence of modification by NDI. The associations between NO2 and preterm birth were generally negative across exposure windows except for a positive association with NO2 and preterm birth for high NDI [RD: 34.70 (95% CI 4.84–64.56)] for entire pregnancy exposure. There was no evidence of associations between pollutants examined and birth defects Conclusions: There may be differences in the association between NO2 exposure and preterm birth by NDI but we did not observe any evidence of associations for birth defects. Our results support the public health protection afforded by reductions in air pollution, even in areas of neighborhood deprivation, but future research conducted in areas with higher levels of air pollution and evaluating the potential for modification by neighborhood deprivation level would be informative [ABSTRACT FROM AUTHOR]

Background Analyses of coronavirus disease 19 suggest specific risk factors make communities more or less vulnerable to pandemic-related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics. Methods We applied a two-stage Bayesian model to quantify inequalities in excess mortality in people aged 40 years and older at the community level in England, Italy and Sweden during the first year of the pandemic (March 2020–February 2021). We used community characteristics measuring deprivation, air pollution, living conditions, population density and movement of people as covariates to quantify their associations with excess mortality. Results We found just under half of communities in England (48.1%) and Italy (45.8%) had an excess mortality of over 300 per 100 000 males over the age of 40, while for Sweden that covered 23.1% of communities. We showed that deprivation is a strong predictor of excess mortality across the three countries, and communities with high levels of overcrowding were associated with higher excess mortality in England and Sweden. Conclusion These results highlight some international similarities in factors affecting mortality that will help policy makers target public health measures to increase resilience to the mortality impacts of this and future pandemics. [ABSTRACT FROM AUTHOR]

Background A number of factors contribute to attention deficit hyperactivity disorder (ADHD) and although they are not fully known, the occurrence of ADHD seems to be a consequence of an interaction between multiple genetic and environmental factors. However, apart from pesticides, the evidence is inadequate and inconsistent as it differs not only in the population and time period analysed, but also in the type of study, the control of the confounding variables and the statistical methods used. In the latter case, the studies also differ in the adjustment of spatial and temporal variability. Our objective here, is to provide evidence on an association between environmental factors and ADHD. Methods In our study, we used a population-based retrospective cohort in which we matched cases and controls (children free of the disease) by sex and year of birth (n = 5193, 78.9% boys). The cases were children born between 1998 and 2012 and diagnosed with ADHD (n = 116). To evaluate whether there was a geographical pattern in the incidence of ADHD, we first represented the smoothed standardized incidence rates on a map of the region being studied. We then estimated the probability of being a case by using a generalized liner mixed model with a binomial link. As explanatory variables of interest, we included the following environmental variables: distance to agricultural areas, distance to roads (stratified into three categories according to traffic density and intensity), distance to petrol stations, distance to industrial estates, and land use. We control for both observed (individual and family specific variables and deprivation index) and unobserved confounders (in particular, individual and familial heterogeneity). In addition, we adjusted for spatial extra variability. Results We found a north-south pattern containing two clusters (one in the centre of the study region and another in the south) in relation to the risk of developing ADHD. The results from the multivariate model suggest that these clusters could be related to some of the environmental variables. Specifically, living within 100 m from an agricultural area or a residential street and/or living fewer than 300 m from a motorway, dual carriageway or one of the industrial estates analysed was associated (statistically significant) with an increased risk of ADHD. Conclusion Our results indicate that some environmental factors could be associated with ADHD occurring, particularly those associated with exposure to pesticides, organochlorine compounds and air pollutants because of traffic. [ABSTRACT FROM AUTHOR]

Background: Social factors may enhance health effects of air pollution, yet empirical support is inconsistent. The interaction of social and environmental factors may only be evident with long-term exposures and outcomes that reflect long-term disease development.Methods: We used cardiac magnetic resonance imaging data from the Multi-Ethnic Study of Atherosclerosis to assess left-ventricular mass index (LVMI) and left-ventricular ejection fraction (LVEF). We assigned residential concentrations of fine particulate matter (PM2.5), oxides of nitrogen, and nitrogen dioxide in the year 2000 to each participant in 2000 using prediction models. We examined modifying roles of four measures of adversity: race/ethnicity, racial/ethnic residential segregation, and socioeconomic status and psychosocial adversity as composite indices on the association between air pollution and LVMI or LVEF.Results: Compared with whites, blacks showed a stronger adjusted association between air pollution and LVMI. For example, for each 5 µg/m greater PM2.5 level, whites showed a 1.0 g/m greater LVMI (95% confidence interval = -1.3, 3.1), while blacks showed an additional 4.0 g/m greater LVMI (95% confidence interval = 0.3, 8.2). Results were similar for oxides of nitrogen and nitrogen dioxide with regard to black race and LVMI. However, we found no evidence of a modifying role of other social factors or ethnic groups. Furthermore, we found no evidence of a modifying role for any social factors or racial/ethnic groups on the association between air pollution and LVEF.Conclusions: Our results suggest that racial group membership may modify the association between air pollution and cardiovascular disease. [ABSTRACT FROM AUTHOR]

Several studies have documented that more deprived populations tend to live in areas characterized by higher levels of environmental pollution. Yet, time trends and geographic patterns of this disproportionate distribution of environmental burden remain poorly assessed, especially in Europe. We investigated the spatial and temporal relationship between ambient air nitrogen dioxide (NO 2 ) concentrations and socioeconomic and demographic data in four French metropolitan areas (Lille in the North, Lyon in the center, Marseille in the South, and Paris) during two different time periods. The geographical unit used was the census block. The dependent variable was the NO 2 annual average concentration (μg/m 3 ) per census block, and the explanatory variables were a neighborhood deprivation index and socioeconomic and demographic data derived from the national census. Generalized additive models were used to account for spatial autocorrelation. We found that the strength and direction of the association between deprivation and NO 2 estimates varied between cities. In Paris, census blocks with the higher social categories are exposed to higher mean concentrations of NO 2 . However, in Lille and Marseille, the most deprived census blocks are the most exposed to NO 2 . In Lyon, the census blocks in the middle social categories were more likely to have higher concentrations than in the lower social categories. Despite a general reduction in NO 2 concentrations over the study period in the four metropolitan areas, we found contrasting results in the temporal trend of environmental inequalities. There is clear evidence of city-specific spatial and temporal environmental inequalities that relate to the historical socioeconomic make-up of the cities and its evolution. Hence, general statements about environmental and social inequalities can be made. [ABSTRACT FROM AUTHOR]