Industrial air pollutant emissions and respiratory health effects in children

Asthma is a main chronic childhood disease. It has been associated with exposure to outdoor air pollutants from remote regional and traffic sources. Pollutant mixtures from industrial sources and their effects may not be the same as those from traffic and regional sources. Yet contrary to associations between pollutants from these sources and asthma in children, associations with community exposures to industrial air pollutant emissions have not been systematically assessed. Furthermore, although substantial reductions in industrial emissions of fine particles (PM2.5) and sulphur dioxide (SO2) have been noted in industrialized countries over the past decades, associations between the geographic and the temporal variations of industrial air pollutant emissions and the variation of asthma morbidity in children have been understudied.   In this dissertation, we aimed to investigate the association between asthma morbidity and industrial air pollutant emissions in children. We first assessed the association between exposure to industrial air pollutant emissions and asthma in children based on available evidence. We then assessed the associations between the spatial and the temporal variations in industrial air pollutant emissions and the spatial and temporal variations in asthma morbidity in Québec.   For the first objective, we searched bibliographic databases to identify studies on the association between children's exposure to air pollution from industrial point-sources and asthma-related outcomes, including: asthma, asthma-like symptoms, wheezing and bronchiolitis. Where possible, we performed random-effects meta-analyses of results. For the second and third objectives, we conducted spatial and temporal ecological analyses based on data for small geographic areas (n=1386) in the province of Québec. For the second objective, we related industrial emissions of PM2.5 and SO2 obtained from the National Pollutant Release Inventory and other variables such as regional levels of PM2.5, median annual household income and the percentage of the population of children exposed to Environmental Tobacco Smoke (ETS) to the total count of asthma hospital admissions in children younger than 13 years of age per small area (data from the database MED-ÉCHO: Maintenance et exploitation des données pour l'étude de la clientèle hospitalière), for the years 2002 to 2011, with negative binomial General Additive Models. For the third objective, we related industrial emissions of PM2.5 and SO2, as well as other environmental and sociodemographic variables mentioned above, to the yearly numbers of asthma onset cases in children aged <13 years from the database QICDSS (Québec Integrated Chronic Disease Surveillance system) over the years 2002 to 2011, with fixed effects negative binomial models (statistical models for panel data). In these models, regional PM2.5 levels were from satellite data, the median income from the census, ETS was from a pan Canadian survey and traffic related air pollution was estimated with kilometers of major roads in small areas.  The systematic review highlighted that half of the selected published studies used a cross sectional study design, ecological binary proximity was the main exposure method used in 15 out of 36 articles, while asthma outcomes were diverse but mainly collected by questionnaires and healthcare services. The pooled odds ratios (ORs) from the meta-analysis from case-crossover studies with hospitalisation for asthma and bronchiolitis in children younger than 5 years old was 1.02 (95%CI: 0.96-1.08; I2 = 56%) per 10 ppb increase in the daily mean concentration of SO2; for PM2.5, the pooled ORs was 1.02 (95%CI: 0.93-1.10; I2 = 56%) per 10 μg/m3 increase in the daily mean concentration. In cross-sectional studies on the prevalence of asthma and wheezing in children, pooled ORs in relation to residential proximity to industries were 1.98 (95%CI: 0.87-3.09; I2 =71%) and 1.33 (95%CI: 0.86-1.79; I2= 65%), respectively. Results of the spatial and temporal ecological analyses suggested that industrial emissions of PM2.5 and SO2 were not related to asthma morbidity. The relative risk (RR) for asthma hospital admissions from the multivariate spatial model was 1.0009, per increase of one ton of PM2.5 (95%CI: 0.9982-1.0037); the RR for SO2 per increase of one ton was 0.9999 (95%CI: 0.9997-1.0001). Additionally, the RR for new asthma onset cases in children from the multivariate temporal models were 0.99 per 1000 tons of SO2 (95%CI: 0.99-1.00) and also 0.99 per 100 tons of PM2.5 (95%CI: 0.98-1.00). Nonetheless, there was a 3.29% decrease in the rate of cases (95%CI: 2.44-4.14) per 1 ug/m3 decrease in the regional PM2.5 levels.  Overall, our results suggest that industrial air pollutant emissions have limited influence on asthma morbidity. This is in contrast with what would be expected based on the published literature that report effects of air pollution from sources other than industries. The results suggest that better exposure assessment and better study designs should be adopted in future studies to assess the association between asthma morbidity and industrial air pollutant emissions in children.

Keyphrases: Air pollution, Industries, Childhood asthma, Environmental and socioeconomic factors