Gender differences in dietary intakes: what is the contribution of motivational variables?
Bibliographic record
Abstract
BACKGROUND: Differences between men and women with respect to dietary intakes and eating behaviours have been reported and could be explained by gender differences in motivational variables associated with the regulation of food intake. The main objectives of the present study were to identify gender differences in dietary intakes, eating behaviours and motivational variables and to determine how motivational variables were associated with dietary intakes and eating behaviours in men and women. METHODS: Sixty-four men and 59 premenopausal women were included in the present study and presented cardiovascular risk factors. The Regulation of Eating Behaviours scale was completed to assess motivational variables. A validated food frequency questionnaire was administered to evaluate dietary intakes and subjects completed the Three-Factor Eating questionnaire to assess eating behaviours. RESULTS: Men had higher energy intake, energy density and percentage of energy from lipids and lower percentage of energy from carbohydrates than women (P ≤ 0.04). Men also had a lower emotional susceptibility to disinhibition than women (P = 0.0001). Women reported a higher score for eating-related self-determined motivation [i.e., eating-related self-determination index (SDI)] than men (P = 0.002). The most notable gender difference in the pattern of associations was that eating-related SDI was negatively associated with energy density (r = -0.30; P = 0.02), only in women. CONCLUSIONS: Women had a better dietary profile and higher eating-related SDI than men. However, gender differences in dietary variables might be explained by a potential gender-specific pattern of association of eating-related SDI with dietary intakes and eating behaviours.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".