Parental childhood growth and offspring birthweight: Pooled analyses from four birth cohorts in low and middle income countries
Bibliographic record
Abstract
OBJECTIVE: Associations between parental and offspring size at birth are well established, but the relative importance of parental growth at different ages as predictors of offspring birthweight is less certain. Here we model parental birthweight and postnatal conditional growth in specific age periods as predictors of offspring birthweight. METHODS: We analyzed data from 3,392 adults participating in four prospective birth cohorts and 5,506 of their offspring. RESULTS: There was no significant heterogeneity by study site or offspring sex. 1SD increase in maternal birthweight was associated with offspring birthweight increases of 102 g, 1SD in maternal length growth 0-2 year with 46 g, and 1SD in maternal height growth Mid-childhood (MC)-adulthood with 27 g. Maternal relative weight measures were associated with 24 g offspring birth weight increases (2 year- MC) and 49 g for MC-adulthood period but not with earlier relative weight 0-2 year. For fathers, birthweight, and linear/length growth from 0-2 year were associated with increases of 57 and 56 g in offspring birthweight, respectively but not thereafter. CONCLUSIONS: Maternal and paternal birthweight and growth from birth to 2 year each predict offspring birthweight. Maternal growth from MC-adulthood, relative weight from 2-MC and MC-adulthood also predict offspring birthweight. These findings suggest that shared genes and/or adequate nutrition during early life for both parents may confer benefits to the next generation, and highlight the importance of maternal height and weight prior to conception. The stronger matrilineal than patrilineal relationships with offspring birth weight are consistent with the hypothesis that improving the early growth conditions of young females can improve birth outcomes in the next generation.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".