Family meals and body mass index among adolescents: effects of gender
Bibliographic record
Abstract
Family meals have been identified as a protective factor against obesity among youth. However, gender specificities with respect to the relationship between the frequency of family meals and body mass index (BMI) have not been investigated. The purpose of this study was to examine the relationship between the frequency of family meals and BMI in male and female adolescents, while controlling for potential confounding factors associated with BMI, such as parental education, adolescent's age, and snack-food eating. Research participants were 734 male and 1030 female students (mean age, 14.12 years, SD = 1.62) recruited from middle schools and high schools in the capital region of Canada. Participants completed validated, self-report measures to assess the frequency of family meals and the risk factors associated with increased BMI, which was derived from objective measures of height and weight. After controlling for proposed confounding variables, a higher frequency of family meals was associated with lower BMI in females, but not in males. A Z-transformation test of the homogeneity of adjusted correlation coefficients showed a significant trend (p = 0.06), indicating that the relationship between family meals and BMI is stronger in females than males, consistent with our regression analyses. Our findings suggest that eating together as a family may be a protective factor against obesity in female adolescents, but not in male adolescents. Findings from this study have important implications for parents and health care practitioners advocating for more frequent family meals as part of a comprehensive obesity prevention and treatment program for female adolescents.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".