Relation between place of residence and postpartum depression
Bibliographic record
Abstract
BACKGROUND: The relation between place of residence and risk of postpartum depression is uncertain. We evaluated the relation between place of residence and risk of postpartum depression in a population-based sample of Canadian women. METHODS: Female postpartum respondents to the 2006 Canadian Maternity Experiences Survey (n=6126) were classified as living in rural (<1000 inhabitants or population density<400/km2), semirural (nonrural but <30,000 inhabitants), semiurban (30 000-499 999 inhabitants) or urban (≥500,000 inhabitants) areas. We further subdivided women living in rural areas based on the social and occupational connectivity of their community to larger urban centres. We compared the prevalence of postpartum depression (score of ≥13 on the Edinburgh Postnatal Depression Scale) across these groups and adjusted for the effect of known risk factors for postpartum depression. RESULTS: The prevalence of postpartum depression was higher among women living in urban areas than among those living in rural, semirural or semiurban areas. The difference between semiurban and urban areas could not be fully explained by other measured risk factors for postpartum depression (adjusted odds ratio 0.60, 95% confidence interval 0.42-0.84). In rural areas, there was a nonsignificant gradient of risk: women with less connection to larger urban centres were at greater risk of postpartum depression than women in areas with greater connection. INTERPRETATION: There are systematic differences in the distribution of risk factors for postpartum depression across geographic areas, resulting in an increased risk of depression among women living in large urban areas. Prevention programs directed at modifiable risk factors (e.g., social support) could specifically target women living in these areas to reduce the rates of postpartum depression.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".