Estimation of population exposure is a main component of human health risk assessment for environmental contaminants. Population-level exposure assessments require time-activity pattern distributions in relation to microenvironments where people spend their time. Societal trends may have influenced time-activity patterns since previous Canadian data were collected 15 years ago. The Canadian Human Activity Pattern Survey 2 (CHAPS 2) was a national survey conducted in 2010–2011 to collect time-activity information from Canadians of all ages. Five urban and two rural locations were sampled using telephone surveys. Infants and children, key groups in risk assessment activities, were over-sampled. Survey participants (n = 5,011) provided time-activity information in 24-hour recall diaries and responded to supplemental questionnaires concerning potential exposures to specific pollutants, dwelling characteristics, and socio-economic factors. Results indicated that a majority of the time was spent indoors (88.9%), most of which was indoors at home, with limited time spent outdoors (5.8%) or in a vehicle (5.3%). Season, age, gender and rurality were significant predictors of time activity patterns. Compared to earlier data, adults reported spending more time indoors at home and adolescents reported spending less time outdoors, which could be indicative of broader societal trends. These findings have potentially important implications for assessment of exposure and risk. The CHAPS 2 data also provide much larger sample sizes to allow for improved precision and are more representative of infants, children and rural residents.

BackgroundThere is evidence that rural residents experience a health disadvantage compared to urban residents, associated with a greater prevalence of health risk factors and socioeconomic differences. We examined differences between urban and rural Canadians using data from the Canadian Human Activity Pattern Survey (CHAPS) 2.MethodsData were collected from 1460 respondents in two rural areas (Haldimand-Norfolk, Ontario and Annapolis Valley-Kings County, Nova Scotia) and 3551 respondents in five urban areas (Vancouver, Edmonton, Toronto, Montreal, and Halifax) using a 24-h recall diary and supplementary questionnaires administered using computer-assisted telephone interviews. We evaluated differences in time-activity patterns, occupational activity, and housing characteristics between rural and urban populations using multivariable linear and logistic regression models adjusted for design as well as demographic and socioeconomic covariates. Taylor linearization method and design-adjusted Wald tests were used to test statistical significance.ResultsAfter adjustment for demographic and socioeconomic covariates, rural children, adults and seniors spent on average 0.7 (p < 0.05), 1.2 (p < 0.001), and 0.9 (p < 0.001) more hours outdoors per day respectively than urban counterparts. 23.1 % (95 % CI: 19.0–27.2 %) of urban and 37.8 % (95 % CI: 31.2–44.4 %) of rural employed populations reported working outdoors and the distributions of job skill level and industry differed significantly (p < 0.001) between urban and rural residents. In particular, 11.4 % of rural residents vs. 4.9 % of urban residents were employed in unskilled jobs, and 11.5 % of rural residents vs. <0.5 % of urban residents were employ in primary industry. Rural residents were also more likely than urban residents to report spending time near gas or diesel powered equipment other than vehicles (16.9 % vs. 5.2 %, p < 0.001), more likely to report wood as a heating fuel (9.8 % vs. <0.1 %; p < 0.001 for difference in distribution of heating fuels), less likely to have an air conditioner (43.0 % vs. 57.2 %, p < 0.001), and more likely to smoke (29.1 % vs. 19.0 %, p < 0.001). Private wells were the main water source in rural areas (68.6 %) in contrast to public water systems (97.6 %) in urban areas (p < 0.001). Despite these differences, no differences in self-reported health status were observed between urban and rural residents.ConclusionsWe identified a number of differences between urban and rural residents, which provide evidence pertinent to the urban–rural health disparity.

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Objective To determine whether long term exposure to outdoor nitrogen dioxide (NO2) is associated with all-cause or cause-specific mortality. Methods MEDLINE, Embase, CENTRAL, Global Health and Toxline databases were searched using terms developed by a librarian. Screening, data extraction and risk of bias assessment were completed independently by two reviewers. Conflicts were resolved through consensus and/or involvement of a third reviewer. Pooling of results across studies was conducted using random effects models, heterogeneity among included studies was assessed using Cochran’s Q and I2 measures, and sources of heterogeneity were evaluated using meta-regression. Sensitivity of pooled estimates to individual studies was examined and publication bias was evaluated using Funnel plots, Begg’s and Egger’s tests, and trim and fill. Results Seventy-nine studies based on 47 cohorts, plus one set of pooled analyses of multiple European cohorts, met inclusion criteria. There was a consistently high degree of heterogeneity. After excluding studies with probably high or high risk of bias in the confounding domain (n = 12), pooled hazard ratios (HR) indicated that long term exposure to NO2 was significantly associated with mortality from all/ natural causes (pooled HR 1.047, 95% confidence interval (CI), 1.023–1.072 per 10 ppb), cardiovascular disease (pooled HR 1.058, 95%CI 1.026–1.091), lung cancer (pooled HR 1.083, 95%CI 1.041–1.126), respiratory disease (pooled HR 1.062, 95%CI1.035–1.089), and ischemic heart disease (pooled HR 1.111, 95%CI 1.079–1.144). Pooled estimates based on multi-pollutant models were consistently smaller than those from single pollutant models and mostly non-significant. Conclusions For all causes of death other than cerebrovascular disease, the overall quality of the evidence is moderate, and the strength of evidence is limited, while for cerebrovascular disease, overall quality is low and strength of evidence is inadequate. Important uncertainties remain, including potential confounding by co-pollutants or other concomitant exposures, and limited supporting mechanistic evidence. (PROSPERO registration number CRD42018084497)