Duration of lack of money for basic needs and growth delay in the Quebec Longitudinal Study of Child Development birth cohort
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between duration of lack of money for basic needs and growth delay in a birth cohort. METHODOLOGY: Mothers of children (n = 1929) from the Quebec Longitudinal Study of Child Development (QLSCD) participating when the children were ages 2(1/2) and 4 years were interviewed at home and data were extracted from birth records. Children's height at 4 years old was transformed into an age- and sex-adjusted z-score. A z-score under the 10th percentile of the Centers for Disease Control and Prevention population growth curve was equated with growth delay. Lack of money for basic needs (paying for rent, electricity and/or heating, clothing, medications or other needs) when the children were ages 2(1/2) and 4 years was reported by the mother. RESULTS: Only 2.5% of children experienced two episodes of lack of money for basic needs. Logistic regression analyses showed that, after adjusting for confounding variables, the probability of growth delay at 4 years among children whose families experienced two episodes of lack of money was higher than for their peers who had not lacked money (OR 3.43; 95% CI 1.54 to 7.66). Experiencing lack of money only at 2(1/2) years showed higher but not significant odds of growth delay at 4 years (OR 1.51; 95% CI 0.84 to 2.72), whereas the likelihood of growth delay was similar for children who experienced lack of money only at 4 years and for their counterparts who never lacked money (OR 0.74; 95% CI 0.26 to 2.11). CONCLUSION: In an industrialised country toddlers whose families experienced persistent lack of money for basic needs are more likely to have growth delay even after controlling for neonatal conditions and their mothers' characteristics.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| 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".