Infant hospitalization and maternal depression, poverty and single parenthood – a population‐based study
Bibliographic record
Abstract
OBJECTIVES: There is variation in rates of hospitalization for young children which is unexplained by differences in health. We used population-based survey data to examine the contribution of family sociodemographic and psychodynamic factors to the risk of hospitalization in children under the age of 2 years in Canada. METHODS: Baseline data from the National Longitudinal Survey of Children and Youth (a population-based study of child health and well-being) were used. A weighted sample of 332 697 (unweighted n = 2184) children between the age of 12 and 24 months, whose biological mother reported data on hospitalization over the past year, were included. Logistic regression analyses were conducted to estimate the risk of hospitalization by sociodemographic and psychodynamic factors controlling for important biological covariates. RESULTS: The overall proportion of children who were hospitalized was 11.2%. After adjusting for prematurity, the only statistically significant biological factor associated with the risk of hospitalization was reported present health [odds ratio (OR) 4.04, 95% confidence intervals (CI): 2.93, 5.58]. However, three family variables were significantly associated with hospitalization: low income adequacy (OR 1.66, 95% CI: 1.15, 2.40), single parenthood (OR 1.55, 95% CI: 1.03, 2.34) and maternal depression (OR 1.81, 95% CI: 1.22, 2.69). Having a parent who is a recent immigrant to Canada is associated with a reduced risk of hospitalization (OR 0.53, 95% CI: 0.35, 0.78). CONCLUSIONS: Most of the significant associations with hospitalization in the first 2 years of life in the Canadian population relate to the overall family's social and mental health. Maternal depression is a treatable disorder which if recognized might prevent some infant morbidity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".