Publications

Export 3 results:
Sort by: Author Title Type [ Year  (Desc)]
2018
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.

Benmarhnia, T, Delpla I, Schwarz L, Rodriguez MJ, Levallois P.  2018.  Heterogeneity in the relationship between disinfection by-products in drinking water and cancer: A systematic review. International Journal of Environmental Research and Public Health. 15   10.3390/ijerph15050979   AbstractWebsite

The epidemiological evidence demonstrating the effect of disinfection by-products (DBPs) from drinking water on colon and rectal cancers is well documented. However, no systematic assessment has been conducted to assess the potential effect measure modification (EMM) in the relationship between DBPs and cancer. The objective of this paper is to conduct a systematic literature review to determine the extent to which EMM has been assessed in the relationship between DBPs in drinking water in past epidemiological studies. Selected articles (n = 19) were reviewed, and effect estimates and covariates that could have been used in an EMM assessment were gathered. Approximately half of the studies assess EMM (n = 10), but the majority of studies only estimate it relative to sex subgroups (n = 6 for bladder cancer and n = 2 both for rectal and colon cancers). Although EMM is rarely assessed, several variables that could have a potential modification effect are routinely collected in these studies, such as socioeconomic status or age. The role of environmental exposures through drinking water can play an important role and contribute to cancer disparities. We encourage a systematic use of subgroup analysis to understand which populations or territories are more vulnerable to the health impacts of DBPs.

Schinasi, LH, Benmarhnia T, De Roos AJ.  2018.  Modification of the association between high ambient temperature and health by urban microclimate indicators: A systematic review and meta-analysis. Environmental Research. 161:168-180.   10.1016/j.envres.2017.11.004   AbstractWebsite

Background: Landscape characteristics, including vegetation and impervious surfaces, influence urban micro climates and may lead to within-city differences in the adverse health effects of high ambient temperatures. Objective: Our objective was to quantitatively summarize the epidemiologic literature that assessed microclimate indicators as effect measure modifiers (EMM) of the association between ambient temperature and mortality or morbidity. Methods: We systematically identified papers and abstracted relative risk estimates for hot and cool micro climate indicator strata. We calculated the ratio of the relative risks (RRR) and 95% confidence intervals (95% CI) to assess differences in health effects across strata, and pooled the RRR estimates using random effects meta analyses. Results: Eleven papers were retained. In the pooled analyses, people living in hotter areas within cities (based on land surface temperature or modeled estimates of air temperature) had 6% higher risk of mortality/morbidity compared to those in cooler areas (95% CI: 1.03-1.09). Those living in less vegetated areas had 5% higher risk compared to those living in more vegetated areas (95% CI: 1.00-1.11). Discussion: There is epidemiologic evidence that those living in hotter, and less vegetated areas of cities have higher risk of morbidity or mortality from higher ambient temperature. Further research with improved assessment of landscape characteristics and investigation of the joint effects of physiologic adaptation and landscape will advance the current understanding. Conclusion: This review provides quantitative evidence that intra-urban differences in landscape characteristics and micro-urban heat islands contribute to within-city variability in the health effects of high ambient temperatures.