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Air Pollution: Actions to be taken
Abstract
To overcome problems related to air pollution, and for protection against its negative effects on health, a number of actions are required at the individual, local, national, and international levels. The role of prevention is crucial, as the effects of pollution on health are still largely unknown; some of them could show up years after exposure. For this reason, international bodies and experts are needed to foster proper environmental administration, to coordinate research, and to promote healthy behaviors that could reduce the risk of exposure for communities and individuals.
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Background:
Nitrogen dioxide (NO₂) is a marker for traffic-related air pollution, which exhibits strong spatial gradients in large cities. Previous studies have shown that in Canadian cities, exposure to ambient NO₂ is greater in neighbourhoods of low socioeconomic status (SES). As a result of these differences in exposure, air pollution-related health problems may be more prevalent among children in lower SES urban neighbourhoods.
Data and methods:
Children younger than age 18 enumerated in the 2006 Census who lived in Toronto, Montreal or Vancouver were linked to published air pollution exposure land use regression models to assign exposure at the Dissemination Area (DA) level. Associations between both socioeconomic and visible minority status and exposure to ambient NO₂ among children in these three cities were examined in a series of regression models (OLS and simultaneous autoregressive models that account for spatial autocorrelation).
Results:
Children in lower income DAs in all three cities were exposed to higher NO₂ concentrations than were children in higher income DAs (mean difference of 2 ppb between lowest and highest income quintiles). In some cities, DAs with larger percentages of children in lone-parent families and visible minority children were characterized by greater NO₂ exposure.
Interpretation:
The relatively high incidence of air pollution-related diseases (for example, asthma) among children in lower SES neighbourhoods may be attributable, at least in part, to variations in NO₂ air pollution exposure within the same city.
Air quality is known to be a key factor in affecting the wellbeing and quality of life of the general populous and there is a large body of knowledge indicating that certain underrepresented groups may be overexposed to air pollution. Therefore, a more precise understanding of air pollution exposure as a driving cause of health disparities between and among ethnic and racial groups is necessary. Utilizing 52,613 urban census tracts across the United States, this study investigates age, racial, educational attainment and income differences in exposure to benzene pollution in 1999 as a case. The study examines spatial clustering patterns of these inequities using logistic regression modeling and spatial autocorrelation methods such as the Global Moran's I index and the Anselin Local Moran's I index. Results show that the age groups of 0 to 14 and those over 60 years old, individuals with less than 12 years of education, racial minorities including Blacks, American Indians, Asians, some other races, and those with low income were exposed to higher levels of benzene pollution in some census tracts. Clustering analyses stratified by age, education, and race revealed a clear case of disparities in spatial distribution of exposure to benzene pollution across the entire United States. For example, people aged less than 4 years from the western south and the Pacific coastal areas exhibit statistically significant clusters. The findings confirmed that there are geographical-location based disproportionate pattern of exposures to benzene air pollution by various socio-demographic factors across the United States and this type of disproportionate exposure pattern can be effectively detected by a spatial autocorrelation based cluster analysis method. It is suggested that there is a clear and present need for programs and services that will reduce inequities and ultimately improve environmental conditions for all underrepresented groups in the United States.
To study respiratory health effects of long-term exposure to ambient air pollutant mixture, we observed 7058 school children 5-16 years of age living in the four Chinese cities of Lanzhou, Chongqing, Wuhan, and Guangzhou. These children were enrolled from elementary schools located in eight districts, one urban district and one suburban district in each of the above cities. Ambient levels of PM(2.5), PM(10-2.5), total suspended particles (TSP), SO(2), and NO(x) were measured in these districts from 1993 to 1996. Based on a cluster analysis of arithmetic mean concentrations of PM(2.5), PM(10-2.5), (TSP-PM(10)), SO(2), and NO(x), we classified these children into four ordinal categories of exposure to ambient air pollutant mixtures. We tested for exposure-response relationships using logistic regression models, controlling for relevant covariates. We observed monotonic, positive relationships of exposure to the pollutant mixture with prevalence rates of cough with phlegm and wheeze. Other outcomes were not associated with the exposure in a monotonic exposure-response pattern. Even so, odds ratios for cough, phlegm, bronchitis, and asthma in the higher exposure district clusters were all higher than in the lowest exposure district cluster. We found evidence that exposure to the pollutant mixtures had adverse effects on children living in the four Chinese cities.
Background
A broad literature base provides evidence of association between air pollution and paediatric asthma. Socioeconomic status (SES) may modify these associations; however, previous studies have found inconsistent evidence regarding the role of SES.
Methods
Effect modification of air pollution–paediatric asthma morbidity by multiple indicators of neighbourhood SES was examined in Atlanta, Georgia. Emergency department (ED) visit data were obtained for 5–18 years old with a diagnosis of asthma in 20-county Atlanta during 2002–2008. Daily ZIP Code Tabulation Area (ZCTA)-level concentrations of ozone, nitrogen dioxide, fine particulate matter and elemental carbon were estimated using ambient monitoring data and emissions-based chemical transport model simulations. Pollutant–asthma associations were estimated using a case-crossover approach, controlling for temporal trends and meteorology. Effect modification by ZCTA-level (neighbourhood) SES was examined via stratification.
Results
We observed stronger air pollution–paediatric asthma associations in ‘deprivation areas’ (eg, ≥20% of the ZCTA population living in poverty) compared with ‘non-deprivation areas’. When stratifying analyses by quartiles of neighbourhood SES, ORs indicated stronger associations in the highest and lowest SES quartiles and weaker associations among the middle quartiles.
Conclusions
Our results suggest that neighbourhood-level SES is a factor contributing vulnerability to air pollution-related paediatric asthma morbidity in Atlanta. Children living in low SES environments appear to be especially vulnerable given positive ORs and high underlying asthma ED rates. Inconsistent findings of effect modification among previous studies may be partially explained by choice of SES stratification criteria, and the use of multiplicative models combined with differing baseline risk across SES populations.
The authors evaluated whether the effects of air pollution on asthma in children differed by the regional socioeconomic status (SES) associated with the area in which children resided. They analyzed data on air pollution, asthma-related hospitalization, weather conditions, and SES collected from 25 subregions in Seoul from January 1 to December 31, 2002. The National Health Insurance Cooperation provided data for children aged younger than 15 years who were living in Seoul and hospitalized for asthma-related health conditions (ICD-10 codes J45-J46). Exposure to interquartile range increase of airborne particles < or = 10 microm in aerodynamic diameter, sulfur dioxide, and nitrogen dioxide in districts associated with a lower SES, the estimated percent increase of hospitalization for asthma among children was 31% (95% confidence interval [CI] = 14%-51%), 29% (95% CI = 8%-53%), and 29% (95% CI = 5%-58%), respectively. This suggests that not only biological sensitivity markers, but also the SES of subjects, should be considered as potentially confounding factors.