We show that the oil sands industry releases the 13 elements considered priority pollutants (PPE) under the US Environmental Protection Agency's Clean Water Act, via air and water, to the Athabasca River and its watershed. In the 2008 snowpack, all PPE except selenium were greater near oil sands developments than at more remote sites. Bitumen upgraders and local oil sands development were sources of airborne emissions. Concentrations of mercury, nickel, and thallium in winter and all 13 PPE in summer were greater in tributaries with watersheds more disturbed by development than in less disturbed watersheds. In the Athabasca River during summer, concentrations of all PPE were greater near developed areas than upstream of development. At sites downstream of development and within the Athabasca Delta, concentrations of all PPE except beryllium and selenium remained greater than upstream of development. Concentrations of some PPE at one location in Lake Athabasca near Fort Chipewyan were also greater than concentration in the Athabasca River upstream of development. Canada's or Alberta's guidelines for the protection of aquatic life were exceeded for seven PPE—cadmium, copper, lead, mercury, nickel, silver, and zinc—in melted snow and/or water collected near or downstream of development.

The biodiversity hypothesis that contact with natural environments (e.g. native vegetation) and biodiversity, through the influence of environmental microbes, may be beneficial for human commensal microbiota has been insufficiently tested. We aimed to study the association between living near natural environments in the urban context, and gut microbiota diversity and composition in young infants. Based on data linkage between the unique Urban Primary Land and Vegetation Inventory (uPLVI) for the city of Edmonton and 355 infants in the CHILD Cohort Study, infant exposure to natural environments (any and specific types, yes/no) was determined within 500 m and 1000 m of their home residence. Gut microbiota composition and diversity at age 4 months was assessed in infant fecal samples. Adjusted for covariates, we observed a reduced odds of high microbial alpha-diversity in the gut of infants exposed to any natural environment within 500 m [Shannon index aOR (95%CI) = 0.63 (0.40, 0.98) and Simpson index = 0.63 (0.41, 0.98)]. In stratified analyses, these associations remained only among infants not breastfed or living with household pets. When doubly stratifying by these variables, the reduced likelihood of high alpha-diversity was present only among infants who were not breastfed and lived with household pets [9% of the study population, Shannon index = 0.07 (0.01, 0.49) and Simpson index = 0.11 (0.02, 0.66)]. Differences in beta-diversity was also seen (p = 0.04) with proximity to a nature space in not breastfed and pets-exposed infants. No associations were observed among infants who were fully formula-fed but without pets at home. When families and their pets had close access to a natural environment, Verrucomicrobiales colonization was reduced in the gut microbiota of formula-fed infants, the abundance of Clostridiales was depleted, whereas the abundance of Enterobacteriales was enriched. Our double-stratified results indicate that proximity to a natural environment plus pet ownership has the capacity to alter the gut microbiota of formula-fed infants. Further research is needed to replicate and better interpret these results, as well as to understand their health consequences.

Climate change impacts are felt unequally worldwide; populations that experience geographical vulnerability, those living in small island states and densely populated coastal areas, and children and women are affected disproportionately. This scoping review aims to synthesize evidence from relevant studies centred on South Asia, identify research gaps specifically focused on children and women's health, and contribute to knowledge about South Asia's existing mitigation and adaptation strategies. A research librarian executed the search on six databases using controlled vocabulary (e.g., MeSH, Emtree, etc.) and keywords representing the concepts “vulnerable populations” and “climate change” and “health impacts” and “South Asia.” Databases were searched from January 2010 to May 2020. Papers were screened independently by two researchers. Forty-two studies were included, of which 23 were based in India, 14 in Bangladesh, and five in other South Asian countries. Nineteen studies focused on meteorological factors as the primary exposure. In contrast, thirteen focused on extreme weather events, nine on air pollution, and one on salinity in coastal areas. Thirty-four studies focused on the health impacts on children related to extreme weather events, meteorological factors, and air pollution, while only eight studies looked at health impacts on women. Undernutrition, ARI (acute respiratory infection), diarrheal diseases, low birth weight, and premature mortality were the major health impacts attributed to extreme weather events, meteorological factors, and air pollution exposure in children and women in the region. Extreme weather events, meteorological factors and air pollution have affected the health of children and women in South Asia. However, the gap in the literature across the South Asian countries concerning relationships between exposure to extreme weather events, meteorological factors, air pollution and health effects, including mental health problems in children and women, are opportunities for future work.

Objective: Using a summary measure of health inequalities, this study evaluated the distribution of adverse birth outcomes (ABO) and related maternal risk factors across area-level socioeconomic status (SES) gradients in urban and rural Alberta, Canada. Design: Cross-sectional study using a validated perinatal clinical registry and an area-level SES. Setting: The study was conducted in Alberta, Canada. Data about ABO and related maternal risk factors were obtained from the Alberta Perinatal Health Program between 2006 and 2012. An area-level SES index derived from census data (2006) was linked to the postal code at delivery. Participants: Women (n=3 30 957) having singleton live births with gestational age ≥22 weeks. Primary and secondary outcome measures: We estimated concentration indexes to assess inequalities across SES gradients in both rural and urban areas (CIdx _R and CIdx _U , respectively) for spontaneous preterm birth (PTB), small for gestational age (SGA), large for gestational age (LGA), gestational hypertension, gestational diabetes, smoking and substance use during pregnancy and pre-pregnancy weight >91 kg. Results: The highest health inequalities disfavouring low SES groups were identified for substance abuse and smoking in rural areas (CIdx _R −0.38 and −0.23, respectively). Medium inequalities were identified for LGA (CIdx _R −0.08), pre-pregnancy weight >91 kg (CIdx _R −0.07), substance use (CIdx _U −0.15), smoking (CIdx _U −0.14), gestational diabetes (CIdx _U −0.10) and SGA (CIdx _U −0.07). Low inequalities were identified for PTB (CIdx _R −0.05; CIdx _U −0.05) and gestational diabetes (CIdx _R −0.04). Inequalities disfavouring high SES groups were identified for gestational hypertension (CIdx _R +0.04), SGA (CIdx _R +0.03) and LGA (CIdx _U +0.03). Conclusions: ABO and related maternal risk factors were unequally distributed across the socioeconomic gradient in urban–rural settings, with the greatest concentrations in lower SES groups of rural areas. Future research is needed on underlying mechanisms driving SES gradients in perinatal health across the rural–urban spectrum.

Adverse birth outcomes (ABO) such as prematurity and small for gestational age confer a high risk of mortality and morbidity. ABO have been linked to air pollution; however, relationships with mixtures of industrial emissions are poorly understood. The exploration of relationships between ABO and mixtures is complex when hundreds of chemicals are analyzed simultaneously, requiring the use of novel approaches. We aimed to generate robust hypotheses spatially linking mixtures and the occurrence of ABO using a spatial data mining algorithm and subsequent geographical and statistical analysis. The spatial data mining approach aimed to reduce data dimensionality and efficiently identify spatial associations between multiple chemicals and ABO. We discovered co-location patterns of mixtures and ABO in Alberta, Canada (2006-2012). An ad-hoc spatial data mining algorithm allowed the extraction of primary co-location patterns of 136 chemicals released into the air by 6279 industrial facilities (National Pollutant Release Inventory), wind-patterns from 182 stations, and 333,247 singleton live births at the maternal postal code at delivery (Alberta Perinatal Health Program), from which we identified cases of preterm birth, small for gestational age, and low birth weight at term. We selected secondary patterns using a lift ratio metric from ABO and non-ABO impacted by the same mixture. The relevance of the secondary patterns was estimated using logistic models (adjusted by socioeconomic status and ABO-related maternal factors) and a geographic-based assignment of maternal exposure to the mixtures as calculated by kernel density. From 136 chemicals and three ABO, spatial data mining identified 1700 primary patterns from which five secondary patterns of three-chemical mixtures, including particulate matter, methyl-ethyl-ketone, xylene, carbon monoxide, 2-butoxyethanol, and n-butyl alcohol, were subsequently analyzed. The significance of the associations (odds ratio > 1) between the five mixtures and ABO provided statistical support for a new set of hypotheses. This study demonstrated that, in complex research settings, spatial data mining followed by pattern selection and geographic and statistical analyses can catalyze future research on associations between air pollutant mixtures and adverse birth outcomes.