Caesarean birth and adiposity parameters in 6‐ to 8‐year‐old urban Maya children from two cities of Yucatan, Mexico
Bibliographic record
Abstract
Abstract Objectives The purpose of this study was to analyze the association between birth mode and fat mass index (FMI = fat mass [kg]/height [m]2), and z‐score values of waist circumference (WCZ) and sum of triceps and subscapular skinfolds (SumSkfZ) in a sample of 256 6‐ to 8‐year‐old urban Maya children from the cities of Merida and Motul in Yucatan, Mexico. Methods From September 2011 to January 2014, we measured height, weight, waist circumference and skinfolds in children, and height and weight in their mothers. Body composition was estimated in both generations through bioelectrical impedance analysis. Data on children's birth mode and birth weight were obtained from birth certificates. A pre‐validated questionnaire for mothers was used regarding household living conditions. Multiple regression models were used to analyze the association between birth mode and adiposity parameters, adjusting for the effect of place of residence, household crowding index, children's birth weight, and maternal fat mass. Separate regression models were run for boys and girls. Results Caesarean‐born children comprised 43% of the entire sample. Caesarean section (CS) was found to be associated with higher values of body adiposity in girls, but not in boys. Specifically, our models predicted that girls born by CS had an increased value of 0.817 kg/m2 in FMI and showed higher SDs values for WCZ and SumskfZ (0.29 and 0.32 SD, respectively) than girls who were delivered vaginally. Discussion Our results support the hypothesis that CS is associated with increased levels of adiposity in childhood, but only in girls.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".