Association of housing tenure and unaffordable housing with preterm birth and other adverse birth outcomes in Canada: a population-based study
Bibliographic record
Abstract
BACKGROUND: Socioeconomic risk factors are known drivers of adverse birth outcomes. Housing is a key target for policy interventions. OBJECTIVE: To estimate the associations of housing tenure (renting vs owning) and unaffordable housing with preterm birth and other adverse birth outcomes. METHODS: We used 2014-2016 Canadian birth registration data linked with the 2016 long-form census and included singleton births among homeowners and renters. Unaffordable housing was defined at the family level as the proportion of pre-tax income spent on shelter, using a 30% cut-off. The primary outcome was preterm birth. Secondary outcomes were stillbirth and infant death. Log-binomial regression estimated the association of housing tenure and unaffordability with outcomes adjusting for sociodemographic risk factors and parity. RESULTS: Among 162 700 live births and stillbirths (52 740 renters, 109 960 owners), 31% of renters and 17% of owners experienced unaffordable housing. Renting was associated with an increased risk of preterm birth (7.5% vs 6.1%; adjusted risk ratio (aRR) 1.13; 95% CI 1.08 to 1.17), stillbirth (9.5 vs 6.6 per 1000; aRR 1.33, 95% CI 1.14 to 1.56) and infant death (4.2 vs 3.0 per 1000; aRR 1.52, 95% CI 1.26 to 1.82). There was no association of housing unaffordability with preterm birth or other adverse birth outcomes among owners or renters. CONCLUSIONS: This nationally representative study in Canada found associations between renting versus owning and preterm birth, stillbirth and infant death, as well as a high burden of unaffordable housing, particularly among renters. This study suggests that home tenure itself is a social determinant of adverse birth outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".