Children's exposure to nitrogen dioxide in Sweden: investigating environmental injustice in an egalitarian country

Maternal exposure to air pollution and birth outcomes

BACKGROUND

The knowledge about air pollution effects on birth weight, prematurity, and small for gestational age (SGA) in low-exposure areas is insufficient.

OBJECTIVES

The aim of this birth cohort study was to investigate whether low-level exposure to air pollution was associated with prematurity and fetal growth and whether there are sex-specific effects.

METHOD

We combined high-quality registry information on 81,110 births with individually modeled exposure data at residence for nitrogen oxides (NO(x)) and proximity to roads with differing traffic density. The data were analyzed by logistic and linear regression with and without potential confounders.

RESULTS

We observed an increased risk for babies being SGA when we compared highest and lowest NO(x) quartiles, adjusting for maternal age, smoking, sex, and year of birth. After additional adjustment for maternal country of origin and parity (which were highly intercorrelated), the increase was no longer statistically significant. However, in subgroup analyses when we compared highest and lowest NO(x) quartiles we still observed an increased risk for SGA for girls [odds ratio (OR)=1.12; 95% confidence interval (CI), 1.01-1.24); we also observed increased risk among mothers who had not changed residency during pregnancy (OR=1.09; 95% CI, 1.01-1.18). The confounders with the greatest impact on SGA were parity and country of origin. Concerning prematurity, the prevalence was lower in the three higher NO(x) exposure quartiles compared with the lowest category.

CONCLUSION

For future studies on air pollution effects on birth outcomes, careful control of confounding is crucial.

Does exposure to air pollution in urban parks have socioeconomic, racial or ethnic gradients?

Little is known about the levels of air pollution at public parks where regular exercise takes place or in park-adjacent neighborhoods where people have easy access to parks. In this study we investigated the ambient concentrations of criteria pollutants nitrogen dioxide (NO(2)), fine particulate (PM(2.5)) and ozone (O(3)) at public parks and in park-adjacent neighborhoods for metropolitan Los Angeles. Socioeconomic and racial-ethnic inequalities in exposure to the three criteria pollutants were also investigated using multiple linear regression models. In addition, differences in inhalation doses from breathing the three +criteria pollutants were investigated for the top and bottom quartile racial composition in the parks and neighborhoods. Our research showed that although public parks had on average the lowest pollutant concentrations of NO(2) and PM(2.5), they had relatively high O(3) concentrations. Park-adjacent neighborhoods, by contrast, had the highest NO(2) and PM(2.5) concentrations, but the lowest O(3) concentrations. Higher exposures to NO(2) and PM(2.5) were systematically identified for the lower socioeconomic position or higher minority population neighborhoods. For children and adolescents aged 6-15 engaging in high and moderate intensity activities in and around public parks, those from the top quartile of primarily Hispanic neighborhoods had much higher (63%) inhaled doses of NO(2) compared to the bottom quartile counterpart. PM(2.5) showed a similar but less pronounced pattern of inhalation doses. Evidence of socioeconomic and racial-ethnic gradients was found in air pollution exposure and inhalation doses in and around the urban parks in Los Angeles. This suggests that patterns of exposure inequality found in other environmental justice research are present in exposures in and around urban parks.

Social factors associated with nitrogen dioxide (NO2) exposure during pregnancy: the INMA-Valencia project in Spain

Numerous studies have focused on the effects of exposure to air pollution on health; however, certain subsets of the population tend to be more exposed to such pollutants depending on their social or demographic characteristics. In addition, exposure to toxicants during pregnancy may play a deleterious role in fetal development as fetuses are especially vulnerable to external insults. The present study was carried out within the framework of the INMA (Infancia y Medio Ambiente or Childhood and the Environment) multicenter cohort study with the objective of identifying the social, demographic, and life-style factors associated with nitrogen dioxide (NO(2)) exposure in the subjects in the cohort. The study comprised 785 pregnant women who formed part of the INMA cohort in Valencia, Spain. Outdoor levels of NO(2) were measured at 93 sampling sites spread over the study area during four different sampling periods lasting 7 days each. Multiple regression models were used for mapping outdoor NO(2) throughout the area. Individual exposure was assigned as: 1) the estimated outdoor NO(2) levels at home, and 2) the average of estimated outdoor NO(2) levels at home and work, weighted according to the time spent in each environment. The subjects' socio-demographic and life-style information was obtained through a questionnaire. In the multiple linear analyses, the outdoor NO(2) levels assigned to each home were taken to be the dependent variable. Other variables included in the model were: age, country of origin, smoking during pregnancy, parity, season of the year, and social class. These same variables remained in the model when the dependent variable was changed to the NO(2) levels adjusted for the subjects' time-activity patterns. We found that younger women, those coming from Latin American countries, and those belonging to the lower social strata were exposed to higher NO(2) levels, both as measured outside their homes as well as when time-activity patterns were taken into account. These subgroups also have a higher probability of being exposed to NO(2) levels over 40 μg/m(3), which is the annual limit for maximum safe exposure, as established by European Directive 2008/50/EC.

Environmental justice in a French industrial region: are polluting industrial facilities equally distributed?

Recent studies have suggested that minority or deprived groups are subject to the additional burden of a polluted living environment. Our goal is to determine whether such environmental inequalities occur in France's leading industrial region, using detailed socio-economic data and advanced Bayesian methods. Associations between proximity to hazardous facilities (i.e., within a 2 km radius) and the socio-economic characteristics of populations are analyzed at fine geographical scales. Noxious facilities are disproportionately located in higher foreign-born communities after controlling for deprivation (Townsend score), population density and rural/urban status. High deprivation also appears as a predictive factor, although less strongly and less consistently.

Indoor and outdoor concentrations and determinants of NO2 in a cohort of 1-year-old children in Valencia, Spain

Nitrogen dioxide (NO2) is produced from the exhausts of vehicles and gas appliances and is known to pose certain health risks. In this study, we characterize the exposure to this substance during the first year of life, which is an important period of development. To this end, we used passive samplers to measure indoor and outdoor NO2 levels for 2 weeks in the homes of 352 children. To compensate for the fact that NO2 levels were measured only once in each home, a correction factor was calculated to assign each child an outdoor NO2 exposure value for the first year of life. The outdoor NO2 concentrations were 26.1 microg/m(3) while those measured indoors averaged 18.0 microg/m(3). A multivariate linear regression analysis showed that the main determinants of outdoor NO2 levels were the degree of urbanization and the frequency of vehicle traffic at the location of the residence while for indoor NO2 levels the principal determinants were the type of cooking range and water heater present in the home, the season of the year, and both the country of origin and educational level of the mother.

PRACTICAL IMPLICATIONS

Exposure to NO2 has been related to respiratory and other health problems among children. Precise identification of the main sources of both indoor and outdoor NO2 should shed light on appropriate intervention periods and methods. Our results indicate that while population density and traffic-related variables are the main determinants of outdoor NO2 levels, the use of gas appliances have the greatest impact on indoor levels. Strategies should thus be developed to reduce such exposure, especially with regard to reducing emissions from vehicle traffic.

Social inequalities resulting from health risks related to ambient air quality--A European review

BACKGROUND

Environmental nuisances, including ambient air pollution, are thought to contribute to social inequalities in health. There are two major mechanisms, which may act independently or synergistically, through which air pollution may play this role. Disadvantaged groups are recognized as being more often exposed to air pollution (differential exposure) and may also be more susceptible to the resultant health effects (differential susceptibility).

METHOD

European research articles were obtained through a literature search in the Medline database using keywords 'Socioeconomic Factors, Air Pollution, Health' and synonymous expressions.

RESULTS

Some studies found that poorer people were more exposed to air pollution whereas the reverse was observed in other papers. A general pattern, however, is that, irrespective of exposure, subjects of low socio-economic status experience greater health effects of air pollution. So far as we are aware, no European study has explored this relationship among children.

CONCLUSION

The housing market biases land use decisions and may explain why some subgroups suffer from both a low socio-economic status and high exposure to air pollution. Some data may be based on inaccurate exposure assessment. Cumulative exposures should be taken into account to explore health problems more accurately. The issue of exposure and health inequalities in relation to ambient air quality is complex and calls for global appraisal. There is no single pattern. Policies aimed at reducing the root causes of these inequalities could be based on urban multipolarity and diversity, two attributes that require long-term urban planning.

Traffic-related air pollution and socioeconomic status: a spatial autocorrelation study to assess environmental equity on a small-area scale

BACKGROUND

: Most ecologic studies of environmental equity show that groups with lower socioeconomic status (SES) are more likely to be exposed to higher air pollution levels than groups of higher SES. However, these studies rarely consider spatial autocorrelation in the data. We investigated the associations between traffic-related air pollution and SES on a small-area level in Strasbourg (France) and assessed the impact of spatial autocorrelation on the results.

METHODS

: We used a deprivation index, constructed from census data, to estimate SES at the block level. Average ambient nitrogen dioxide (NO2) levels during year 2000, modeled at the block level by a dispersion model, served as a marker of traffic exhaust. We estimated the association between exposure to NO2 and the deprivation index by using an ordinary least squares model and a simultaneous autoregressive model that controls for the spatial autocorrelation of data.

RESULTS

: The association between the deprivation index and NO2 levels was positive and nonlinear with both regression models; the midlevel deprivation areas were the most exposed. Control of spatial autocorrelation strongly reduced the strength of the association but clearly improved the model's goodness-of-fit; the most pronounced reduction was observed for the midlevel deprivation areas (regression coefficients decreased by 67%).

CONCLUSIONS

: This study confirms the need to take spatial autocorrelation into account in ecologic studies and shows that failure to do so may lead to biased and unreliable estimates and thus to erroneous conclusions. This may be especially important in studying the role of air pollution on social inequalities in health.

Children at risk: measuring racial/ethnic disparities in potential exposure to air pollution at school and home

STUDY OBJECTIVE

This paper addresses the environmental justice implications of children's health by exploring racial/ethnic disparities in potential exposure to air pollution, based on both school and home locations of children and three different types of pollution sources, in Orange County, Florida, USA.

METHODS

Using geocoded school and residence locations of 151 709 children enrolled in the public school system, distribution functions of proximity to the nearest source are generated for each type of air pollution source in order to compare the exposure potential of white, Hispanic, and black children. Discrete buffer distances are utilised to provide quantitative comparisons for statistical testing.

MAIN RESULTS

At any given distance from each type of pollution source, the cumulative proportion of Hispanic or black children significantly exceeds the corresponding proportion of white children, for both school and home locations. Regardless of race, however, a larger proportion of children are potentially exposed to air pollution at home than at school.

CONCLUSIONS

This study addresses the growing need to consider both daytime and nighttime activity patterns in the assessment of children's exposure to environmental hazards and related health risks. The results indicate a consistent pattern of racial inequity in the spatial distribution of all types of air pollution sources examined, with black children facing the highest relative levels of potential exposure at both school and home locations.

Investigating the relationship between air pollution, health and social deprivation in Leeds, UK

This study examines the relationship between air pollution, social deprivation and health in the city of Leeds, UK under a baseline and three distance-based road user charging (RUC) scenarios set at 2 pence, 10 pence and 20 pence/km. Through application of a series of linked models of traffic, emission and pollutant dispersion, air quality was modelled in response to RUC scenarios. The pollutant modelled were NO(2), PM(10), CO, benzene and 1,3-butadiene, though results of NO(2) are used in this study. The RUC scenarios were compared with the 'base' scenario, all set for the year 2005. The RUC initiatives result in the differences in ambient concentrations of NO(2). The study correlates NO(2) concentrations with derived indices of social deprivation and health. The study concludes that positive but weak relationship exists between air quality and social deprivation, and indicates that deprived population groups are disproportionately exposed to higher NO(2) levels. The relationship between air quality and health status of the population is weak. There is a strong relationship between social deprivation and health status of the population. The study concludes that RUC scenarios result in reducing disparity between affluent and deprived populations.

Epidemiologic evidence of relationships between reproductive and child health outcomes and environmental chemical contaminants

This review summarizes the level of epidemiologic evidence for relationships between prenatal and/or early life exposure to environmental chemical contaminants and fetal, child, and adult health. Discussion focuses on fetal loss, intrauterine growth restriction, preterm birth, birth defects, respiratory and other childhood diseases, neuropsychological deficits, premature or delayed sexual maturation, and certain adult cancers linked to fetal or childhood exposures. Environmental exposures considered here include chemical toxicants in air, water, soil/house dust and foods (including human breast milk), and consumer products. Reports reviewed here included original epidemiologic studies (with at least basic descriptions of methods and results), literature reviews, expert group reports, meta-analyses, and pooled analyses. Levels of evidence for causal relationships were categorized as sufficient, limited, or inadequate according to predefined criteria. There was sufficient epidemiological evidence for causal relationships between several adverse pregnancy or child health outcomes and prenatal or childhood exposure to environmental chemical contaminants. These included prenatal high-level methylmercury (CH(3)Hg) exposure (delayed developmental milestones and cognitive, motor, auditory, and visual deficits), high-level prenatal exposure to polychlorinated biphenyls (PCBs), polychlorinated dibenzofurans (PCDFs), and related toxicants (neonatal tooth abnormalities, cognitive and motor deficits), maternal active smoking (delayed conception, preterm birth, fetal growth deficit [FGD] and sudden infant death syndrome [SIDS]) and prenatal environmental tobacco smoke (ETS) exposure (preterm birth), low-level childhood lead exposure (cognitive deficits and renal tubular damage), high-level childhood CH(3)Hg exposure (visual deficits), high-level childhood exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (chloracne), childhood ETS exposure (SIDS, new-onset asthma, increased asthma severity, lung and middle ear infections, and adult breast and lung cancer), childhood exposure to biomass smoke (lung infections), and childhood exposure to outdoor air pollutants (increased asthma severity). Evidence for some proven relationships came from investigation of relatively small numbers of children with high-dose prenatal or early childhood exposures, e.g., CH(3)Hg poisoning episodes in Japan and Iraq. In contrast, consensus on a causal relationship between incident asthma and ETS exposure came only recently after many studies and prolonged debate. There were many relationships supported by limited epidemiologic evidence, ranging from several studies with fairly consistent findings and evidence of dose-response relationships to those where 20 or more studies provided inconsistent or otherwise less than convincing evidence of an association. The latter included childhood cancer and parental or childhood exposures to pesticides. In most cases, relationships supported by inadequate epidemiologic evidence reflect scarcity of evidence as opposed to strong evidence of no effect. This summary points to three main needs: (1) Where relationships between child health and environmental exposures are supported by sufficient evidence of causal relationships, there is a need for (a) policies and programs to minimize population exposures and (b) population-based biomonitoring to track exposure levels, i.e., through ongoing or periodic surveys with measurements of contaminant levels in blood, urine and other samples. (2) For relationships supported by limited evidence, there is a need for targeted research and policy options ranging from ongoing evaluation of evidence to proactive actions. (3) There is a great need for population-based, multidisciplinary and collaborative research on the many relationships supported by inadequate evidence, as these represent major knowledge gaps. Expert groups faced with evaluating epidemiologic evidence of potential causal relationships repeatedly encounter problems in summarizing the available data. A major driver for undertaking such summaries is the need to compensate for the limited sample sizes of individual epidemiologic studies. Sample size limitations are major obstacles to exploration of prenatal, paternal, and childhood exposures during specific time windows, exposure intensity, exposure-exposure or exposure-gene interactions, and relatively rare health outcomes such as childhood cancer. Such research needs call for investments in research infrastructure, including human resources and methods development (standardized protocols, biomarker research, validated exposure metrics, reference analytic laboratories). These are needed to generate research findings that can be compared and subjected to pooled analyses aimed at knowledge synthesis.

The relationship between diabetes mellitus and traffic-related air pollution

OBJECTIVE

Air pollution is associated with an increased risk for cardiovascular events. Many of the biological pathways involved could also promote diabetes mellitus (DM). We therefore investigated the association between DM prevalence and exposure to traffic-related air pollution (nitrogen dioxide [NO 2]).

METHODS

Study participants were patients who attended two respiratory clinics in Hamilton (n = 5228) and Toronto (n = 2406). The diagnosis of DM was ascertained by linkage to administrative databases of the Ontario universal Health Insurance Plan for patients aged 40 years and above. Geographic Information systems methodology was used to assign individual estimates of NO2 based on a network of samplers in each city. Logistic regression was used to estimate the relations between NO2 exposures and the odds of DM diagnosis.

RESULTS

After adjusting for age, body mass index, and neighborhood income there were positive effects in women on the odds ratio for DM for each 1 ppb NO2 exposure in Toronto (OR 1.055, 95% CI: 0.99 to 1.11) and Hamilton (OR 1.029, 95% CI: 0.98 to 1.08). In a meta-analytic model including both cities, there was a significant effect in women (OR = 1.04; 95% CI: 1.00 to 1.08). Across the inter-quartile range (approximately 4 ppb NO2) there was nearly a 17% increase in the odds of DM for women. There were no positive associations among men.

CONCLUSIONS

Exposure to NO2, a marker of traffic-related air pollutants, was associated with DM prevalence among women. Exposure estimate errors in men may explain the apparent gender difference. These results suggest that common air pollutants are associated with DM and warrant more investigation to determine if this is a cause-and-effect relationship.

Assessing uncertainty in spatial exposure models for air pollution health effects assessment

BACKGROUND

Although numerous epidemiologic studies now use models of intraurban exposure, there has been little systematic evaluation of the performance of different models.

OBJECTIVES

In this present article we proposed a modeling framework for assessing exposure model performance and the role of spatial autocorrelation in the estimation of health effects.

METHODS

We obtained data from an exposure measurement substudy of subjects from the Southern California Children's Health Study. We examined how the addition of spatial correlations to a previously described unified exposure and health outcome modeling framework affects estimates of exposure-response relationships using the substudy data. The methods proposed build upon the previous work, which developed measurement-error techniques to estimate long-term nitrogen dioxide exposure and its effect on lung function in children. In this present article, we further develop these methods by introducing between- and within-community spatial autocorrelation error terms to evaluate effects of air pollution on forced vital capacity. The analytical methods developed are set in a Bayesian framework where multistage models are fitted jointly, properly incorporating parameter estimation uncertainty at all levels of the modeling process.

RESULTS

Results suggest that the inclusion of residual spatial error terms improves the prediction of adverse health effects. These findings also demonstrate how residual spatial error may be used as a diagnostic for comparing exposure model performance.

Assessment of the magnitude of geographical variations and socioeconomic contextual effects on ischaemic heart disease mortality: a multilevel survival analysis of a large Swedish cohort

BACKGROUND

In a public health perspective, it is of interest to assess the magnitude of geographical variations in ischaemic heart disease (IHD) mortality and quantify the strength of contextual effects on IHD.

OBJECTIVE

To investigate whether area effects vary according to the individual and contextual characteristics of the population, socioeconomic contextual influences were assessed in different age groups and within territories of differing population densities.

DESIGN

Multilevel survival analysis of a 28-year longitudinal database.

PARTICIPANTS

341 048 residents of the Scania region in Sweden, reaching age 50-79 years in 1996, followed up over 7 years.

RESULTS

After adjustment for several individual socioeconomic indicators over the adult age, Cox multilevel models indicated geographical variations in IHD mortality and socioeconomic contextual effects on the mortality risk. However, the magnitude of geographical variations and strength of contextual effects were modified by the age of individuals and the population density of their residential area: socioeconomic contextual effects were much stronger among non-elderly than among elderly adults, and much larger within urban territories than within rural ones. As a consequence, among non-elderly residents of urban territories, the socioeconomic contextual effect was almost as large as the effect of individual 20-year cumulated income.

CONCLUSIONS

Non-elderly residents of deprived urban neighbourhoods constitute a major target for both contextual epidemiology of coronary disease and public health interventions aimed at reducing the detrimental effects of the social environment on IHD.

A study of spatial resolution in pollution exposure modelling

Background

This study is part of several ongoing projects concerning epidemiological research into the effects on health of exposure to air pollutants in the region of Scania, southern Sweden. The aim is to investigate the optimal spatial resolution, with respect to temporal resolution, for a pollutant database of NO_x-values which will be used mainly for epidemiological studies with durations of days, weeks or longer periods. The fact that a pollutant database has a fixed spatial resolution makes the choice critical for the future use of the database.

Results

The results from the study showed that the accuracy between the modelled concentrations of the reference grid with high spatial resolution (100 m), denoted the fine grid, and the coarser grids (200, 400, 800 and 1600 meters) improved with increasing spatial resolution. When the pollutant values were aggregated in time (from hours to days and weeks) the disagreement between the fine grid and the coarser grids were significantly reduced. The results also illustrate a considerable difference in optimal spatial resolution depending on the characteristic of the study area (rural or urban areas). To estimate the accuracy of the modelled values comparison were made with measured NO_x values. The mean difference between the modelled and the measured value were 0.6 μg/m³ and the standard deviation 5.9 μg/m³ for the daily difference.

Conclusion

The choice of spatial resolution should not considerably deteriorate the accuracy of the modelled NO_x values. Considering the comparison between modelled and measured values we estimate that an error due to coarse resolution greater than 1 μg/m³ is inadvisable if a time resolution of one day is used. Based on the study of different spatial resolutions we conclude that for urban areas a spatial resolution of 200–400 m is suitable; and for rural areas the spatial resolution could be coarser (about 1600 m). This implies that we should develop a pollutant database that allows different spatial resolution for urban and rural areas.

Influence of geocoding quality on environmental exposure assessment of children living near high traffic roads

Background

The widespread availability of powerful geocoding tools in commercial GIS software and the interest in spatial analysis at the individual level have made address geocoding a widely employed technique in epidemiological studies. This study determined the effect of the positional error in street geocoding on the analysis of traffic-related air pollution on children.

Methods

For a case-study of a large sample of school children in Orange County, Florida (n = 104,865) the positional error of street geocoding was determined through comparison with a parcel database. The effect of this error was evaluated by analyzing the proximity of street and parcel geocoded locations to road segments with high traffic volume and determining the accuracy of the classification using the results of street geocoding. Of the original sample of 163,886 addresses 36% were not used in the final analysis because they could not be reliably geocoded using either street or parcel geocoding. The estimates of positional error can therefore be considered conservative underestimates.

Results

Street geocoding was found to have a median error of 41 meters, a 90^th percentile of 100 meters, a 95^th percentile of 137 meters and a 99^th percentile of 273 meters. These positional errors were found to be non-random in nature and introduced substantial bias and error in the estimates of potential exposure to traffic-related air pollution. Street geocoding was found to consistently over-estimate the number of potentially exposed children at small distances up to 250 meters. False positives and negatives were also found to be very common at these small distances.

Conclusion

Results of the case-study presented here strongly suggest that typical street geocoding is insufficient for fine-scale analysis and more accurate alternatives need to be considered.

Neighborhood socioeconomic deprivation and residential instability: effects on incidence of ischemic heart disease and survival after myocardial infarction

BACKGROUND

Previous literature has shown that neighborhood socioeconomic position influences the risk of ischemic heart disease, but little is known about the mechanisms linking the residential context to ischemic heart disease incidence and mortality. We examined whether neighborhood socioeconomic position and neighborhood residential stability (as a determinant of social interaction patterns) have an influence on ischemic heart disease risk. Moreover, we investigated whether dissimilar contextual influences operate at different stages of the disease process, ie, on incidence, 1-day case-fatality, and long-term survival after acute myocardial infarction (MI).

METHODS

Using a large 27-year longitudinal cohort (baseline: 1 January 1996) defined in the Scania region, Sweden, we estimated multilevel survival models adjusted for individual sociodemographic factors and previous diseases of the persons.

RESULTS

After adjustment, multilevel survival models indicated that the incidence of ischemic heart disease increased with neighborhood socioeconomic deprivation but was only weakly associated with neighborhood residential instability (for high vs low residential instability, hazard ratio = 1.2; 95% credible interval = 1.0-1.4). Conversely, beyond effects of individual and contextual socioeconomic circumstances and distance to the hospital, we saw a markedly higher 1-day case-fatality (4.9; 1.8-15) and shorter survival time after MI among individuals still alive 28 days after MI (4.3; 1.2-17) in neighborhoods with a high versus low residential instability.

CONCLUSIONS

Effects of residential instability on post-MI survival may be mediated by the lower availability of social support in residentially unstable neighborhoods, suggesting a new class of intermediate processes that should be taken into account when investigating contextual influences on ischemic heart disease. Moreover, dissimilar contextual effects may operate at various stages of the disease process (ie, on incidence, case-fatality, and survival after MI).

Children's environmental health: why should social disparities be considered?

BACKGROUND/METHODS

The aim of workpackage 5 'Environmental exposures and children's health: impact of socioeconomic factors' in the EU-funded network PINCHE (Policy Interpretation Network on Children's Health and Environment) was to review and interpret the current knowledge of social inequalities in environmental exposures and children's health. Socioeconomic factors may impact on children's environmental health in two ways: 1) environmental exposures may differ according to socioeconomic status; 2) given a certain level of harmful environmental exposure, socioeconomic factors may modify the health effects by influencing the susceptibility characteristics of children.

RESULTS

There is a lack of information to evaluate and quantify the effect of socioeconomic factors on environmental exposures and children's health in Europe. In most circumstances there seems to be an inverse social gradient with increased burden concerning exposures and health outcomes in children of lower social status.

CONCLUSIONS

There is a need to improve research on social inequalities in children's health and environment. Because of the complexity, integrated approaches and a combination of different intervention measures and policies are necessary to reduce environmental exposure and adverse health effects in children. Paediatricians may contribute to improvement of children's environmental health by risk communication and health advocacy at community and governmental level.

Improving environmental exposure analysis using cumulative distribution functions and individual geocoding

Background

Assessments of environmental exposure and health risks that utilize Geographic Information Systems (GIS) often make simplifying assumptions when using: (a) one or more discrete buffer distances to define the spatial extent of impacted regions, and (b) aggregated demographic data at the level of census enumeration units to derive the characteristics of the potentially exposed population. A case-study of school children in Orange County, Florida, is used to demonstrate how these limitations can be overcome by the application of cumulative distribution functions (CDFs) and individual geocoded locations. Exposure potential for 159,923 school children was determined at the childrens' home residences and at school locations by determining the distance to the nearest gasoline station, stationary air pollution source, and industrial facility listed in the Toxic Release Inventory (TRI). Errors and biases introduced by the use of discrete buffer distances and data aggregation were examined.

Results

The use of discrete buffers distances in proximity-based exposure analysis introduced substantial bias in terms of determining the potentially exposed population, and the results are strongly dependent on the choice of buffer distance(s). Comparisons of exposure potential between home and school locations indicated that different buffer distances yield different results and contradictory conclusions. The use of a CDF provided a much more meaningful representation and is not based on the a-priori assumption that any particular distance is more relevant than another. The use of individual geocoded locations also provided a more accurate characterization of the exposed population and allowed for more reliable comparisons among sub-groups. In the comparison of children's home residences and school locations, the use of data aggregated at the census block group and tract level introduced variability as well as bias, leading to incorrect conclusions as to whether exposure potential was higher at school or at home.

Conclusion

The use of CDFs in distance-based environmental exposure assessment provides more robust results than the use of discrete buffer distances. Unless specific circumstances warrant the use of discrete buffer distances, their applcation should be discouraged in favor of CDFs. The use of aggregated data at the census tract or block group level introduces substantial bias in environmental exposure assessment, which can be reduced through individual geocoding. The use of aggregation should be minimized when individual-level data are available. Existing GIS analysis techniques are well suited to determine CDFs as well as reliably geocode large datasets, and computational issues do not present a barrier for their more widespread use in environmental exposure and risk assessment.

Are associations between socio-economic characteristics and exposure to air pollution a question of study area size? An example from Scania, Sweden

BACKGROUND

Numerous studies have shown that exposure to air pollutants in the area of residence and the socio-economic status of an individual may be related. Therefore, when conducting an epidemiological study on the health effect of air pollution, socio-economy may act as a confounding factor. In this paper we examine to what extent socio-economic status and concentrations of NO2 in the county/region of Scania, southern Sweden, are associated and if such associations between these factors differ when studying them at county or city level. To perform this study we used high-resolution census data and modelled the annual exposure to NO2 using an emission database, a dispersion modelling program and a geographical information system (GIS).

RESULTS

The results from this study confirm that socio-economic status and the levels of NO2 in the area of residence are associated in some cities. The associations vary considerably between cities within the same county (Scania). Even for cities of similar sizes and population bases the associations observed are different. Studying the cities together or separately yields contradictory results, especially when education is used as a socio-economic indicator.

CONCLUSION

Four conclusions have been drawn from the results of this study. 1) Adjusting for socio-economy is important when investigating the health effects of air pollution. 2) The county of Scania seems to be heterogeneous regarding the association between air pollution and socio-economy. 3) The relationship between air pollution and socio-economy differs in the five cities included in our study, depending on whether they are analysed separately or together. It is therefore inadvisable to determine and analyse associations between socio-economy and exposure to air pollutants on county level. This study indicates that the size and choice of study area is of great importance. 4) The selection of socio-economic indices (in this study: country of birth and education level) is important.