ArticleInternational journal of population data science2023
Data resource profile: a nationally representative linked pregnancy cohort in Canada integrating clinical, social, and environmental data.
Article in International journal of population data science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Perinatal outcomes are shaped by clinical, social, and environmental factors, yet Canada lacks a nationally representative pregnancy cohort capturing these influences at the individual-level. This gap has limited the ability to address multifactorial drivers of maternal and fetal health. To fill this need, we established a linked cohort integrating survey, clinical, and contextual data to support equity-focused, precision public health research in maternal health. Methods: We linked the Canadian Community Health Survey (CCHS; 2000-2017) to the Discharge Abstract Database (DAD) using Statistics Canada's Social Data Linkage Environment. Eligible participants were female (as defined by the binary CCHS sex variable), aged 15-49 years, with a hospital delivery within two years of their CCHS interview. We excluded multifetal gestations and retained only the first delivery per individual. Area-level and environmental exposures (i.e., neighbourhood inequity, pollution, greenspace, neighbourhood walkability, etc.) were appended via residential postal codes using the Postal Code Conversion File Plus (PCCF+). Results: The cohort includes 13,360 singleton births. Pre-pregnancy data include sociodemographics, health behaviours, chronic conditions, psychosocial factors, and reproductive history. Contextual measures capture neighbourhood marginalization, air pollution, greenness, and built environment characteristics. In the CCHS, individuals who reported being pregnant at interview and those who did not (but later delivered) had similar characteristics (SMDs < 0.1), except for age and marital status. Data quality is supported by Statistics Canada's survey protocols, CIHI's hospital validation processes, and standardised geocoding. Conclusion: Approved researchers can recreate this dataset within Statistics Canada's Research Data Centres using reproducible R code, which will become openly available on GitHub. The cohort enables research across descriptive epidemiology, causal inference, predictive modelling, and health equity evaluation, supporting investigations into multilevel determinants of maternal health. Future work should prioritise national mother-child linkages to expand life course research.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.