Relationship between eating behaviours and food and drink consumption in healthy postmenopausal women in a real-life context
Bibliographic record
Abstract
Associations between eating behaviours and dietary variables have not been thoroughly investigated in healthy postmenopausal women in a real life uncontrolled context. To investigate how eating behaviours (cognitive dietary restraint, disinhibition and susceptibility to hunger) were associated with food and drink consumption, energy density and meal pattern in 112 healthy postmenopausal women (age 56.8 (SD 4.4) years) not on.hormonal therapy. Women completed a 3 d weighed food record and filled out the Three-Factor Eating Questionnaire. The sample was divided according to the median of the distribution of cognitive dietary restraint and disinhibition (9 and 6 respectively). Both subgroups of women with high restraint level (presenting either high or low disinhibition) consumed a diet with a lower energy density than subgroups of women with lower restraint level. Women with high restraint-low disinhibition had a lower consumption of red meat and processed meat and a lower consumption of diet soft drinks than women with low restraint-high disinhibition. They were also characterised by a higher intake of whole grains than women with high restraint-high disinhibition and than women with lower restraint level (with either high or low disinhibition). Women with high restraint-high disinhibition levels showed differences in dietary variables when compared with subgroups of women with lower restraint level, namely for refined grains and diet soft drinks. We conclude that in healthy postmenopausal women, dietary consumption of specific food and drink may be related to particular eating behaviours. Women with high restraint and low disinhibition levels generally showed the most healthy dietary pattern.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".