Maternal and Early Childhood Risk Factors for Overweight and Obesity among Low-Income Predominantly Black Children at Age Five Years: A Prospective Cohort Study
Bibliographic record
Abstract
Objective. To identify maternal and early childhood risk factors for obesity and overweight among children at age 5 in the state of Alabama. Methods. We recruited 740 mothers during early pregnancy from University of Alabama Prenatal Clinics in a prospective cohort study and followed them throughout pregnancy. We followed their children from birth until 5 years of age. The main outcome measure was obesity (BMI for age and sex ≥ 95th percentile) at 5 years of age. We used poisson regression with robust variance estimation to compute risk ratio (RR). Results. At the 5th year of followup, 71 (9.6%) of the children were obese and 85 (11.5%) were overweight (BMI ≥ 85th-<95th percentile). In multivariable analysis, maternal prepregnancy overweight (RR: 2.30, 95% CI: 1.29-4.11) and obesity (RR: 2.53, 95% CI: 1.49-4.31), and child's birth weight >85th percentile (RR: 2.04, 95% CI: 1.13-3.68) were associated with childhood obesity. Maternal prepregnancy BMI, birth weight, and maternal smoking were associated with the child being overweight 1-12 cigarettes/day versus 0 cigarettes/day (RR: 1.40, 95% CI: 1.02-1.91). Conclusion. Children of overweight and obese mothers, and children with higher birth weight, are more likely to be obese and overweight at age 5. Maternal smoking 1-12 cigarettes per day is associated with the child being overweight.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".