Genetic and environmental influences on eating behaviors in 2.5- and 9-year-old children: a longitudinal twin study
Bibliographic record
Abstract
BACKGROUND: Eating behaviors during childhood are related both to children's diet quality and to their weight status. A better understanding of the determinants of eating behavior during childhood is essential for carrying out effective dietary interventions. METHODS: We assessed the contribution of genetic and environmental factors to variations in selected eating behaviors in early and late childhood. Information on eating behaviors came from questionnaires administered to parents of children participating in the Quebec Newborn Twin Study when the twins were 2.5 and 9 years old (n = 692 children). Dichotomous variables were derived and analyzed using structural equation modeling, as part of a classic twin study design. We performed univariate and bivariate longitudinal analyses to quantify sources of variation and covariation across ages, for several eating behavior traits. RESULTS: We found moderate to strong heritability for traits related to appetite such as eating too much, not eating enough and eating too fast. Univariate analysis estimates varied from 0.71 (95% CI: 0.49, 0.87) to 0.89 (0.75, 0.96) in younger children and from 0.44 (0.18, 0.66) to 0.56 (0.28, 0.78) in older children. Bivariate longitudinal analyses indicated modest to moderate genetic correlations across ages (r(A) varying from 0.34 to 0.58). Common genetic influences explained 17% to 43% of the phenotypic correlation between 2.5 and 9 years for these appetite-related behaviors. In 9-year-old children, food acceptance traits, such as refusing to eat and being fussy about food, had high heritability estimates, 0.84 (0.63, 0.94) and 0.85 (0.59, 0.96) respectively, while in younger children, the shared environment (i.e., common to both twins) contributed most to phenotypic variance. Variances in meal-pattern-related behaviors were mostly explained by shared environmental influences. CONCLUSIONS: Genetic predispositions explain a large part of the variations in traits related to appetite during childhood, though our results suggest that as children get older, appetite-related behaviors become more sensitive to environmental influences outside the home. Still, for several traits environmental influences shared by twins appear to have the largest relative importance. This finding supports the notion that familial context has considerable potential to influence the development of healthy eating habits throughout childhood.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".