Poverty, Neighbourhood Characteristics and Trajectories of Maternal Depression
Bibliographic record
Abstract
Background: Income, education, being an immigrant and residential neighbourhood characteristics are linked to depressive symptoms. To our knowledge, no longitudinal study has examined the joint influence of demographic and neighbourhood characteristics on maternal depressive symptoms.\nObjective: To examine the influence of demographic and neighbourhood characteristics on trajectories of maternal depressive symptoms from child age 1.5 to 7 years, in Québec, Canada. METHODS: 1611 mothers from the Québec Longitudinal Study on Child Development, seen regularly since child birth (1998). Maternal depressive symptoms (CES-D), income, and residential neighbourhood characteristics (neighbourhood poverty, unemployment and quality of nearest park) were measured for mothers at child ages 1.5, 3.5, 5 and 7 years. Analyses of the influence of income and neighbourhood characteristics on depression scores (overall trajectory and at each time point) were performed with PROCTRAJ in SAS.\nResults: Over the 6-year period, 42.6% of mothers showed likelihood of a trajectory of low depressive symptoms, while 46.5% and 10.9% showed likelihood of trajectories of minor and elevated depressive symptoms respectively. Prior elevated maternal depressive symptoms at child age 5 months and being an immigrant mother were associated with a greater likelihood of minor (OR= 6.40 CI 3.40-12.37, p=0.001; OR=2.44 CI=1.09-5.48, p=0.01respectively) or elevated (OR=8.18, CI=1.88-22.88, p=0.005; OR=5.66 CI=1.41-22.65, p=0.01 respectively) depressive symptoms. High perception of neighbourhood safety (top quartile) was associated with lesser likelihood of a trajectory of elevated depressive symptoms (OR=0.12, CI=0.03-0.49, p=0.001). Living near a park with greater green space was associated with lesser likelihood of a trajectory of minor depressive symptoms (OR=0.38 CI=0.18-0.80, p=0.02).\nImplications: These results suggest that demographic and neighbourhood factors are associated with maternal depressive symptoms. Further research will evaluate the link between trajectories of maternal depressive symptoms and cortisol profiles as such relations vary according to individual and neighbourhood factors.\nDuring her doctoral studies, Mai Thanh Tu examined the influences of breastfeeding and low income on biological stress pathways in mothers of healthy infants. After studying stress regulation in preterm infants, Mai is now working on maternal mental health and social factors such as characteristics of the residential neighbourhood, living in poverty conditions and caring for a sick child. Mai is currently a postdoctoral research fellow at the Department of Social and Preventive Medicine at Universite de Montreal, and is funded by the Canadian Institutes for Health Research and the NARSAD foundation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".