Linking Canada’s health data to better understand pregnancy risks
Pregnancy outcomes are shaped by far more than medical care alone. Where someone lives, their income, stress levels, health behaviours, and environmental exposures can all influence the health of both parent and baby. Yet in Canada, researchers have long lacked a national dataset that brings these factors together in one place.
A new study published in the International Journal of Population Data Science (IJPDS) describes the creation of Canada’s first national that links clinical, social, and environmental data at the individual level. This resource gives researchers a powerful new tool to study pregnancy risks, health inequities, and opportunities for prevention across the country.
The cohort was built by linking data from the Canadian Community Health Survey (CCHS) with hospital delivery records from the Discharge Abstract Database, covering births between 2000 and 2017. The result is a nationally representative cohort of more than 13,000 singleton births among individuals aged 15 to 49.
What makes this dataset unique is its breadth. The survey data provide rich information about people’s lives before pregnancy, including income, education, immigration status, mental health, stress, health behaviours, and chronic conditions. These individual-level data are combined with clinically validated delivery outcomes from hospital records, allowing accurate identification of births and pregnancy complications.
Researchers further enriched the cohort by linking neighbourhood and environmental data, including measures of marginalisation, air pollution, green space, and walkability. Together, these linkages make it possible to examine how social and environmental conditions interact with individual health to shape pregnancy outcomes — something that has not previously been feasible at a national scale in Canada.
The dataset supports a wide range of research approaches, from descriptive epidemiology and health equity studies to causal inference, predictive modelling, and evaluation of population-level interventions. It can help identify groups at higher risk, reveal regional and neighbourhood differences, and inform policies aimed at prevention and reducing disparities.
Importantly, the cohort was designed with transparency and accessibility. Approved researchers can recreate the dataset within Statistics Canada’s secure Research Data Centres using reproducible R code that will be openly shared to encourage collaboration and future research.
This new cohort provides a powerful platform for equity-focused maternal health research and a more realistic picture of pregnancy risk by combining clinical information with the social and environmental conditions that shape health.
“As we move toward more precise and equitable public health approaches, it’s critical that we understand how social and environmental conditions shape pregnancy outcomes,” said lead author Sabrina Chiodo. “This cohort allows us to move beyond a purely clinical lens and better reflect the real-world factors that influence maternal and fetal health across Canada.”
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Sabrina Chiodo, MPH, PhD Epidemiology Candidate, Dalla Lana School of Public Health, Toronto, Canada