Associations between mental health conditions in pregnancy and maternal socioeconomic status: a population-based retrospective cohort study in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: The World Health Organization has recognized maternal mental illness as an emerging issue. Previous studies have indicated that maternal mental illness is associated with socioeconomic status (SES). However, there is a lack of research concerning the mental health of pregnant people with low SES in Ontario, Canada. In this study, we examined associations between mental health conditions during pregnancy and two SES indicators: the pregnant person's residential neighbourhood income and education level. METHODS: A population-based retrospective cohort study was conducted, consisting of all singleton pregnancies resulting in stillbirths or live births in Ontario hospitals from April 1, 2012, to March 31, 2021. Data were linked from the BORN Information System database, Canadian Institute for Health Information Discharge Abstract Database, and Canadian Census. Poisson regression with robust error variance models was performed to estimate the relative risks of anxiety, depression, anxiety and/or depression, or any mental health condition during pregnancy, by SES indicator. We adjusted for maternal age, obesity status in pre-pregnancy, certain pre-existing maternal health conditions, substance use during pregnancy, race, and rural or urban residence. RESULTS: Within the cohort (n = 1,202,292), 10.5% (126,076) and 8.1% (97,135) of pregnant individuals experienced anxiety and depression, respectively, and 15.8% (189,616) had at least one mental health condition during pregnancy. The trend test (p < 0.0001) showed a significant downward trend in the total rates of mental health conditions by increasing SES quintiles. Pregnant individuals in the lowest neighbourhood income quintile tended to have a higher risk of anxiety (aRR: 1.24, 95%CI: 1.22-1.27), depression (aRR: 1.56, 95%CI: 1.52-1.59), anxiety and/or depression (aRR: 1.13, 95%CI: 1.11-1.15), or any mental health condition (aRR: 1.18, 95%CI: 1.16-1.19). Similarly, pregnant people living in the lowest education level neighbourhoods had higher likelihoods of anxiety (aRR: 1.66, 95%CI: 1.62-1.69), depression (aRR: 2.09, 95%CI: 2.04-2.14), anxiety and/or depression (aRR: 1.42, 95%CI: 1.39-1.44), and any mental health condition (aRR: 1.41, 95%CI: 1.38-1.43). CONCLUSIONS: Despite a universal healthcare system, the variations in mental health prevalence and risk during pregnancy based on SES suggest health inequity in Ontario, Canada. Future studies are needed to examine the mechanisms of this health inequity to guide policy makers in reducing disparities in Ontario.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".