Eating behaviors, dietary patterns and weight status in emerging adulthood and longitudinal associations with eating behaviors in early childhood
Bibliographic record
Abstract
BACKGROUND: Eating behaviors may contribute to differences in body weight and diet over time. Our study aims to examine how eating behaviors of young adults relate to their current weight status and dietary patterns and to explore longitudinal associations with eating behaviors in early childhood. METHODS: Study participants are young adults (n = 698) taking part in the Quebec Longitudinal Study of Child Development. At age 22, eating behaviors were assessed using the Adult Eating Behavior Questionnaire. Dietary patterns were derived from information collected by food frequency questions. Weight status was based on self-reported data. Information on eating behaviors in childhood had been collected when participants were 2.5 to 6 years old. Pearson's correlations were used to determine associations between adult eating behaviors and body mass index. Simple and multivariate linear regression analyses were used to examine associations between eating behaviors and dietary patterns at age 22, and longitudinal associations with behaviors in early childhood. Ordinal logistic regression analyses were used to assess associations between overeating and fussy eating in childhood and weight status at age 22. RESULTS: Body mass index was positively correlated with Emotional overeating, Enjoyment of food, and Food responsiveness and negatively correlated with Satiety responsiveness, Emotional undereating, Slowness in eating and Hunger. A Healthy dietary pattern was positively associated with both Enjoyment of food and Hunger, and negatively associated with Food fussiness. Inversely, a Beverage-rich dietary pattern was negatively associated with Enjoyment of food and positively associated with Food fussiness. A Protein-rich pattern was positively associated with Enjoyment of food, while a High energy density pattern was positively associated with Food fussiness. Young adults with higher scores for fussy eating in early childhood were more likely to manifest Food fussiness and Emotional undereating, and less likely to adopt a Healthy dietary pattern. Young adults with higher scores for overeating in early childhood were less likely to show traits such as Slowness in eating and more likely to be overweight. CONCLUSIONS: Our findings suggest that eating behaviors in childhood have long-term influence on diet and weight status, thereby reinforcing the importance of early interventions that promote healthy eating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".