Determinants of birthweight inequalities: Population‐based study
Bibliographic record
Abstract
BACKGROUND: The aim of this paper is to study the whole spectrum of birthweight in a population-based birth cohort in order to document the role played by social factors, which complement physiological and behavioural factors, in the development of birthweight inequalities at the population level. METHODS: The analyses were performed with data from the 'Quebec Longitudinal Study of Child Development 1998-2002 (QLSCD)'. The study follows a representative sample (n = 2103) of the children born in 1998 in the Canadian province of Québec. RESULTS: Multivariate analyses adjusted for gestational age and mother's age indicate that mean birthweight was higher for boys than girls; improved with birth rank, mother's body mass index (BMI), and family socioeconomic status; and was lower for children of smoking mothers. Compared with children born to non-smoking mothers of higher socioeconomic status, the odds of having a low birthweight were between 6 and 12 times higher for children born to smoking mothers of lower or middle socioeconomic status. When maternal smoking status and mother's BMI are combined, socioeconomic status could still be seen to have a positive effect on mean birthweight except for overweight or obese smoking mothers, among whom the relationship between socioeconomic status and mean birthweight was reversed. In families of lower socioeconomic status, maternal smoking was the most important factor in birthweight inequalities, and in families of higher socioeconomic status, mother's BMI was the most important factor in birthweight inequalities. CONCLUSION: This research is not only important for children in developed nations, but also for those in developing countries, where high birthweight and obesity are becoming more prevalent.
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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 | 0.001 |
| 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 | 0.000 |
| 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".