Early introduction and cumulative consumption of sugar‐sweetened beverages during the pre‐school period and risk of obesity at 8–14 years of age
Bibliographic record
Abstract
BACKGROUND: Consumption of sugar-sweetened beverages (SSB) has been associated with risk of obesity, but little evidence exists to evaluate if age of introduction and cumulative SSB consumption increases risk in children. OBJECTIVES: The objective of the study was to estimate the relationship between age of introduction and cumulative SSB consumption with risk of obesity in 227 Mexican children. METHODS: SSB intake was measured every 6 months; age of introduction and cumulative consumption during the pre-school period were calculated. Height, weight, waist circumference, SSB intake and other relevant variables were measured at age 8-14 years and obesity defined using standard criteria. RESULTS: All participants were introduced to SSB before age 24 months and most (73%) before 12 months. Early SSB introduction (≤12 months) was not significantly associated with increased odds of obesity (odds ratio [OR] = 2.00, 95% confidence interval [CI]: 0.87, 4.59). However, children in the highest tertile of cumulative SSB consumption, compared with the lowest, had almost three times the odds of general (OR = 2.99, 95% CI: 1.27, 7.00) and abdominal (OR = 2.70, 95% CI: 1.03, 7.03) obesity at age 8-14 years. CONCLUSIONS: High SSB consumption increased the likelihood of obesity in 8-14-year-old children. Our results suggest that SSB intake should be delayed and excessive SSB consumption in pre-school period should be avoided.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".