No abstract

: 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.

With few exceptions, studies of short-term health effects of air pollution use pollutant concentrations that are averaged citywide as exposure indicators. They are thus prone to exposure misclassification and consequently to bias. Measurement of the relations between air pollution and health, generally and in specific populations, could be improved by employing more geographically precise exposure estimates. The authors investigated short-term relations between ambient air pollution estimated in small geographic areas (French census blocks) and asthma attacks in Strasbourg, France, in 2000-2005--in the general population and in populations with contrasting levels of socioeconomic deprivation. Emergency health-care networks provided data on 4,683 telephone calls made for asthma attacks. Deprivation was estimated using a block-level index constructed from census data. Hourly concentrations of particulate matter less than 10 microm in aerodynamic diameter (PM(10)), sulfur dioxide, nitrogen dioxide, and ozone were modeled by block with ADMS-Urban software. Adjusted case-crossover analyses showed that asthma calls were positively but not significantly associated with PM(10) (for a 10-microg x m(-3) increase, odds ratio (OR) = 1.035, 95% confidence interval (CI): 0.997, 1.075), sulfur dioxide (OR = 1.056, 95% CI: 0.979, 1.139), and nitrogen dioxide (OR = 1.025, 95% CI: 0.990, 1.062). No association was observed for ozone (OR = 0.998, 95% CI: 0.965, 1.032). Socioeconomic deprivation had no significant influence on these relations.

No abstract

Background and ObjectivesExposure to traffic is an established risk factor for the triggering of myocardial infarction (MI). Particulate matter, mainly emitted by diesel vehicles, appears to be the most important stressor. However, the possible influence of benzene from gasoline-fueled cars has not been explored so far.Methods and ResultsWe conducted a case-crossover study from 2,134 MI cases recorded by the local Coronary Heart Disease Registry (2000–2007) in the Strasbourg Metropolitan Area (France). Available individual data were age, gender, previous history of ischemic heart disease and address of residence at the time of the event. Nitrogen dioxide, particles of median aerodynamic diameter <10 µm (PM10), ozone, carbon monoxide and benzene air concentrations were modeled on an hourly basis at the census block level over the study period using the deterministic ADMS-Urban air dispersion model. Model input data were emissions inventories, background pollution measurements, and meteorological data. We have found a positive, statistically significant association between concentrations of benzene and the onset of MI: per cent increase in risk for a 1 µg/m3 increase in benzene concentration in the previous 0, 0–1 and 1 day was 10.4 (95% confidence interval 3–18.2), 10.7 (2.7–19.2) and 7.2 (0.3–14.5), respectively. The associations between the other pollutants and outcome were much lower and in accordance with the literature.ConclusionWe have observed that benzene in ambient air is strongly associated with the triggering of MI. This novel finding needs confirmation. If so, this would mean that not only diesel vehicles, the main particulate matter emitters, but also gasoline-fueled cars –main benzene emitters–, should be taken into account for public health action.