December 17 | 2018

The influence of social networks and the built environment on physical inactivity: A longitudinal study of urban-dwelling adults.

Josey MJ, Moore S.

Health Place. 2018 Nov;54:62-68. Epub 2018 Sep 21. DOI: 10.1016/j.healthplace.2018.08.016



Policies targeting the built environment to increase physical activity may be ineffective without considering personal social networks. Physical activity and social network data came from the Montreal Neighborhood Networks and Healthy Aging Panel; built environment measures were from geolocation data on Montreal parks and businesses. Using multilevel logistic regression with repeated physical inactivity measures, we showed that adults with more favorable social network characteristics had lower odds of physical inactivity. Having more physical activity facilities nearby also lowered physical inactivity, but not in socially-isolated adults. Community programs that address social isolation may also benefit efforts to increase physical activity.





Frances Sommerfreund Silverman was born in Shanghai, China after her physician parents fled Vienna in 1942, narrowly escaping Hilter’s tyranny. Frances lived in Wuhu, China to the age of 6 before emigrating to Canada where her family settled in Montreal.

Frances enrolled in a doctoral program in respiratory physiology at McGill University in 1968 under the late Professor David Bates, widely recognized one of the founding figures in the field of air pollution and health. After several years of study, Frances moved to Toronto to direct the Pulmonary Function Laboratory at the Gage Research Institute which was at the time, a joint Centre of the University of Toronto (Department of Medicine) and Toronto Western Hospital.

After completing her doctoral work at McGill in 1978, Frances was immediately appointed Assistant Professor in the Department of Medicine at the University of Toronto. Both then and throughout the rest of her career, Frances was proud to be one of a very small group of non-clinical appointees in an otherwise clinical Department.

Frances remained at the Gage Research Institute as an early faculty member in the fledgling discipline of Environmental Health where her research continued to focus on air contaminants, staying true to her first publication in the CMAJ in 1970 – “Problems in studies of human exposure to air pollutants”.

Over the years, her research activities expanded to include many health-relevant air contaminants that remain important today, including ozone, cigarette smoke, allergens and particulate matter arising from industry and motor vehicle emissions. Frances’s earliest work on the health consequences of ozone exposure in the 1970s was formative and continues to be cited regularly. From that and her other insights, she is widely regarded as one of the founding researchers in this area.

The health outcomes she considered also expanded beyond airways measurements to increasingly more sophisticated measures such as genetic and epigenetic markers, inflammatory mediators, and vascular measures. Elegant and highly cited work in the early 2000s by Frances and her colleagues first established a mechanistic link between air pollution exposure and acute cardiovascular events.

Frances held appointments in the Department of Medicine (Division of Respirology), the Dalla Lana School of Public Health (Division of Occupational and Environmental Health), The School of the Environment, the Faculty of Kinesiology and Physical Education, the Li Ka Shing Knowledge Institute, and the University Health Network. She was always most proud of her affiliation with the Gage Research Institute (later the Gage Occupational and Environmental Health Unit), where she served as Acting Director and a member of the Board of Directors.

Despite starting her career as a basic scientist, Frances rapidly understood that truly transformative and impactful research can only be achieved through collaboration. She focused her efforts at the poorly explored nexus that exists between the basic sciences, health sciences and engineering. There, she built a network of collaborators and developed a world-class research program to study air health effects in healthy human subjects as well as those with mild asthma, children and adolescents, and those with chronic obstructive lung disease and obesity using controlled exposure challenges. Using this approach, Frances and her group bridged a critical gap between basic laboratory science and population health, providing much essential evidence needed for policy setting in Canada and abroad in relation to a range of contaminants from environmental tobacco smoke to vehicle emissions. Her work on air contaminants continued well past her retirement in 2012, and she remained actively engaged in research and mentorship until her death. Her curiosity and enthusiasm were infectious, and her level of energy unmatched. “Not bad for an old lady,” she would often observe.

Frances was a networker before networking was a thing, she prioritized the mentorship of young scientists long before it became a trend, and had a preternatural ability to see connections and seed innovative thinking. In her final year, Frances became an advocate for the rights of the elderly to health care access, arising from her own experiences in later life as a caregiver, her deep knowledge of the health care system, her drive to help others, and her talent for building relationships. Despite retirement, she actively mentored students and kept up the schedule of an active faculty member until her last day where her final effort was to advocate tenaciously at a faculty retreat on the importance of the environment as a determinant of health.

Frances was a person of great goodness and integrity – a true Mensch in the Yiddish sense. She continually challenged all who knew her to be better and do better by example. Her spirit, her wisdom, and her generosity will be greatly missed.


December 10 | 2018

Residential green space and pathways to term birth weight in the Canadian Healthy Infant Longitudinal Development (CHILD) Study.

Cusack L, Sbihi H, Larkin A, Chow A, Brook JR, Moraes T, Mandhane PJ, Becker AB, Azad MB, Subbarao P, Kozyrskyj A, Takaro TK, Sears MR, Turvey SE, Hystad P; CHILD Study Investigators.

Int J Health Geogr. 2018 Dec 4;17(1):43. doi: 10.1186/s12942-018-0160-x



A growing number of studies observe associations between the amount of green space around a mother’s home and positive birth outcomes; however, the robustness of this association and potential pathways of action remain unclear.


To examine associations between mother’s residential green space and term birth weight within the Canadian Healthy Infant Longitudinal Development (CHILD) study and examine specific hypothesized pathways.


We examined 2510 births located in Vancouver, Edmonton, Winnipeg, and Toronto Canada. Green space was estimated around mother’s residences during pregnancy using Landsat 30 m normalized difference vegetation index (NDVI). We examined hypothesized pathways of: (1) reduction of environmental exposure; (2) built environment features promoting physical activity; (3) psychosocial conditions; and (4) psychological influences. Linear regression was used to assess associations between green space and term birth weight adjusting first for a comprehensive set of confounding factors and then incrementally for pathway variables.


Fully adjusted models showed non-statistically significant increases in term birth weight with increasing green space. For example, a 0.1 increase in NDVI within 500 m was associated with a 21.5 g (95% CI - 4.6, 47.7) increase in term birth weight. Associations varied by city and were most robust for high-density locations. For the two largest cities (Vancouver and Toronto), we observed an increase in birth weight of 41.2 g (95% CI 7.8, 74.6) for a 0.1 increase in NDVI within 500 m. We did not observe substantial reductions in the green space effect on birth weight when adjusting for pathway variables.


Our results highlight the need to further characterize the interactions between green space, urban density and climate related factors as well as the pathways linking residential green space to birth outcomes.

December 3 | 2018

A picture tells a thousand…exposures: Opportunities and challenges of deep learning image analyses in exposure science and environmental epidemiology.

Weichenthal S, Hatzopoulou M, Brauer M. 

Environ Int. 2018 Nov 22. pii: S0160-4120(18)32200-1. [Epub ahead of print] DOI:10.1016/j.envint.2018.11.042




Artificial intelligence (AI) is revolutionizing our world, with applications ranging from medicine to engineering.


Here we discuss the promise, challenges, and probable data sources needed to apply AI in the fields of exposure science and environmental health. In particular, we focus on the use of deep convolutional neural networks to estimate environmental exposures using images and other complementary data sources such as cell phone mobility and social media information.


Characterizing the health impacts of multiple spatially-correlated exposures remains a challenge in environmental epidemiology. A shift toward integrated measures that simultaneously capture multiple aspects of the urban built environment could improve efficiency and provide important insights into how our collective environments influence population health. The widespread adoption of AI in exposure science is on the frontier. This will likely result in new ways of understanding environmental impacts on health and may allow for analyses to be efficiently scaled for broad coverage. Image-based convolutional neural networks may also offer a cost-effective means of estimating local environmental exposures in low and middle-income countries where monitoring and surveillance infrastructure is limited. However, suitable databases must first be assembled to train and evaluate these models and these novel approaches should be complemented with traditional exposure metrics.


The promise of deep learning in environmental health is great and will complement existing measurements for data-rich settings and could enhance the resolution and accuracy of estimates in data poor scenarios. Interdisciplinary partnerships will be needed to fully realize this potential.