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Loizeau, M, Buteau S, Chaix B, McElroy S, Counil E, Benmarhnia T.  2018.  Does the air pollution model influence the evidence of socio-economic disparities in exposure and susceptibility? Environmental Research. 167:650-661.   10.1016/j.envres.2018.08.002   AbstractWebsite

Studies assessing socio-economic disparities in air pollution exposure and susceptibility are usually based on a single air pollution model. A time stratified case-crossover study was designed to assess the impact of the type of model on differential exposure and on the differential susceptibility in the relationship between ozone exposure and daily mortality by socio-economic strata (SES) in Montreal. Non-accidental deaths along with deaths from cardiovascular and respiratory causes on the island of Montreal for the period 1991-2002 were included as cases. Daily ozone concentration estimates at partictaipants' residence were obtained from the five following air pollution models: Average value (AV), Nearest station model (NS), Inverse-distance weighting interpolation (IDW), Land-use regression model with back-extrapolation (LUR-BE) and Bayesian maximum entropy model combined with a land-use regression (BME-LUR). The prevalence of a low household income ( < 20,000/year) was used as socio-economic variable, divided into two categories as a proxy for deprivation. Multivariable conditional logistic regressions were used considering 3-day average concentrations. Multiplicative and additive interactions (using Relative Excess Risk due to Interaction) as well as Cochran's tests were calculated and results were compared across the different air pollution models. Heterogeneity of susceptibility and exposure according to socio-economic status (SES) were found. Ratio of exposure across SES groups means ranged from 0.75 [0.74-0.76] to 1.01 [1.00-1.02], respectively for the LUR-BE and the BME-LUR models. Ratio of mortality odds ratios ranged from 1.01 [0.96-1.05] to 1.02 [0.97-1.08], respectively for the IDW and LUR-BE models. Cochran's test of heterogeneity between the air pollution models showed important heterogeneity regarding the differential exposure by SES, but the air pollution model was not found to influence heterogeneity regarding the differential susceptibility. The study showed air pollution models can influence the assessment of disparities in exposure according to SES in Montreal but not that of disparities in susceptibility.

Deguen, S, Petit C, Delbarre A, Kihal W, Padilla C, Benmarhnia T, Lapostolle A, Chauvin P, Zmirou-Navier D.  2015.  Neighbourhood characteristics and long-term air pollution levels modify the association between the short-term nitrogen dioxide concentrations and all-cause mortality in Paris. Plos One. 10   ARTN e013146310.1371/journal.pone.0131463   AbstractWebsite

BackgroundWhile a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO2 ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO2 and all-cause mortality in Paris (France).MethodsA time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO2 variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO2 exposure. The data was estimated at the census block scale (n=866).ResultsThe mean of the NO2 concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95% CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95% CI=[1.4-14.90], p<0.001). Among these deprived census blocks, excess risk was even higher where long-term average NO2 concentrations were above 55.8 mu g/m(3) (the top tercile of distribution): ER=4.84%(95% CI=[1.56;8.24], p for interaction= 0.02).ConclusionOur results show that people living in census blocks characterized by low socioeconomic status are more vulnerable to air pollution episodes. There is also an indication that people living in these disadvantaged census blocks might experience even higher risk following short-term air pollution episodes, when they are also chronically exposed to higher NO2 levels.