Association between children’s caregivers time preferences and childhood overweight and obesity in Mexico
Bibliographic record
Abstract
BACKGROUND: Parents or children's primary caregivers are a key influence on child weight as both decision makers and role models for eating patterns, physical activity, and other social behaviors. It is unknown whether caregivers' time preferences are associated with overweight or obesity in children. The primary objective was to estimate the association between parents' or caregivers' time preferences and children having overweight or obesity in Mexico. METHODS: A cross-sectional study was conducted using a representative survey of the Mexican population. A multinomial logistic model was used to examine the association between parents' or caregivers' time preferences (patience and time consistency) and child overweight or obesity, adjusting for potential confounders. RESULTS: The study included 9,102 children (mean age 10, 43% female) and 5,842 caregivers (mean age 37; 95% female). Intertemporal preference was strongly associated with increased odds of overweight or obesity in children. A medium patient caregiver had higher odds of having overweight (adjusted OR: 1.73; 95% CI: 1.19, 2.52). Similarly, having a caregiver with a present (OR: 2.52; 95% CI: 1.72, 3.70) or future bias (OR: 1.48; 95% CI: 1.11, 1.98) was associated with higher odds of obesity. CONCLUSION: Caregivers' time preferences were associated with having overweight and obesity in children and should be considered when developing policies to reduce children's obesity status.
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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 | 0.001 | 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) | 0.002 | 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".