Socioeconomic Deprivation Status and Air Pollution by PM(10) and NO(2): An Assessment at Municipal Level of 11 Years in Italy

The aim of this observational study was to assess the relationship between environmental risk factors and some aspects of social economic status (SES) of the population in different Italian municipalities. Nitrogen dioxide (NO(2)) and particulate matter (PM(10)) annual means were extracted from ISPRA-BRACE (environmental information system of 483 Italian municipalities, 6% of the total amount of administrative units) from 2002 to 2012. As an indicator of sociodemographic and SES data, we collected the following: resident population, foreign nationality, low level of education, unemployment, nonhome ownership, single-parent family, and overcrowding. Low educational level, unemployment, and lack of home ownership were indirectly associated with the higher mean values of NO(2) at the statistically significant level (p < 0.05). Major resident population and rental housing percentage determined higher levels of PM(10). Northern regions showed similar results compared to the national level, with the exception of foreign residency that showed direct correlation with the increase of PM(10). The central regions showed a direct relationship between NO(2) and PM(10) levels and higher educational levels and between NO(2) levels and percentage of single-parent family. In the southern areas, higher NO(2) levels were correlated with a higher rental housing percentage, as well as higher PM(10) levels with a higher percentage of unemployment and lower housing density. The study shows high heterogeneity in the findings but confirms the relationship between high educational level and employment with the increased concentration of pollutants. The higher rental housing percentage may increase the pollutants' levels too. The housing density does not seem to be in relationship with NO(2) and PM(10) at the national level. The analysis stratified by geographical areas showed that the direction of the correlations was different over time as the analysis was at a national level. The study represents an example of how data from national information systems can provide a preliminary evaluation and be a comparative tool for policy-makers to assess environmental risk factors and social inequalities.