This study investigated sex and gender differences in cardinal symptoms of exposure to a mixture of ambient pollutants. A cross sectional population-based study design was utilized in Sarnia, ON, Canada. Stratified random sampling in census tracts of residents aged 18 and over recruited 804 respondents. Respondents completed a community health survey of chronic disease, general health, and socioeconomic indicators. Residential concentrations of NO₂, SO₂, benzene, toluene, ethylbenzene and o/m/p-xylene were estimated by land use regression on data collected through environmental monitoring. Classification and Regression Tree (CART) analysis was used to identify variables that interacted with sex and cardinal symptoms of exposure, and a series of logistic regression models were built to predict the reporting of five or more cardinal symptoms (5+ CS). Without controlling for confounders, higher pollution ranks increased the odds ratio (OR) of reporting 5+ CS by 28% (p < 0.01; Confidence Interval (CI): 1.07–1.54). Females were 1.52 (p < 0.05; CI: 1.03–2.26) times more likely more likely to report 5+ CS after controlling for income, age and chronic diseases. The CART analysis showed that allergies and occupational exposure classified the sample into the most homogenous groups of males and females. The likelihood of reporting 5+ CS among females was higher after stratifying the sample based on occupational exposure. However, stratifying by allergic disease resulted in no significant sex difference in symptom reporting. The results confirmed previous research that found pre-existing health conditions to increase susceptibility to ambient air pollution, but additionally indicated that stronger effects on females is partly due to autoimmune disorders. Furthermore, gender differences in occupational exposure confound the effect size of exposure in studies based on residential levels of air pollution. Full article

This study aimed at establishing the relationship between annoyance scores and modelled air pollution in “Chemical Valley”, Sarnia, Ontario (Canada). Annoyance scores were taken from a community health survey (N = 774); and respondents’ exposure to nitrogen dioxide (NO₂) and sulphur dioxide (SO₂) were estimated using land use regression (LUR) models. The associations were examined by univariate analysis while multivariate logistic regression was used to examine the determinants of odour annoyance. The results showed that odour annoyance was significantly correlated to modelled pollutants at the individual (NO₂, r = 0.15; SO₂, r = 0.13) and census tract (NO₂, r = 0.56; SO₂, r = 0.67) levels. The exposure-response relationships show that residents of Sarnia react to very low pollution concentrations levels even if they are within the Ontario ambient air quality criteria. The study found that exposure to high NO₂ and SO₂ concentrations, gender, and perception of health effects were significant determinants of individual odour annoyance reporting. The observed association between odour annoyance and modelled ambient pollution suggest that individual and census tract level annoyance scores may serve as proxies for air quality in exposed communities because they capture the within area spatial variability of pollution. However, questionnaire-based odour annoyance scores need to be validated longitudinally and across different scales if they are to be adopted for use at the national level. Full article