Birth Weight, Postnatal Weight Gain, and Childhood Adiposity in Relation to Lipid Profile and Blood Pressure During Early Adolescence
Bibliographic record
Abstract
Background Different pathways likely underlie the association between early weight gain and cardiovascular disease risk. We examined whether birth weight for length relationship and weight gain up to 2 years of age are associated with lipid profiles and blood pressure ( BP ) in early adolescence and determined whether childhood adiposity mediates these associations. Methods and Results Data from QUALITY (Quebec Adipose and Lifestyle Investigation in Youth), a cohort of white children with parental history of obesity, were analyzed (n=395). Sex‐specific weight for length z scores from birth to 2 years were computed. Rate of postnatal weight gain was estimated using individual slopes of weight for length z ‐score measurements. Percentage of body fat was measured at 8 to 10 years. Fasting lipids and BP were measured at 10 to 12 years. Using path analysis, we found indirect effects of postnatal weight gain, through childhood adiposity, on all outcomes: Rate of postnatal weight for length gain was positively associated with childhood adiposity, which in turn was associated with unfavorable lipid and BP levels in early adolescence. In contrast, small beneficial direct effects on diastolic BP z scores, independent of weight at other time points, were found for birth weight for length (β=−0.05, 95% CI , −0.09 to −0.002) and for postnatal weight gain (β=−0.02, 95% CI , −0.03 to −0.002). Conclusions Among children with at least 1 obese parent, faster postnatal weight gain leads to cardiovascular risk factors in early adolescence through its effect on childhood adiposity. Although heavier newborns may have lower BP in early adolescence, this protective direct effect could be offset by a deleterious indirect effect linking birth weight to later adiposity.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".