Depressive Symptoms and Food Intake among Weight-Preoccupied Women: Do Eating Behaviors and Attitudes or BMI Mediate This Association?
Bibliographic record
Abstract
Associations between depressive symptoms, dysfunctional eating behaviors and attitudes, higher food intake and body mass index (BMI) have been previously observed. However, few studies have assessed these variables in the same study. The first objective is to compare, in a natural setting environment, the profile of women reporting lower or higher levels of depressive symptoms in terms of food intake, eating behaviors and attitudes, and BMI. The second objective is to test mediational models for which the link between depressive symptoms and food intake would be mediated by eating behaviors and attitudes or BMI. Weight-preoccupied women were recruited (n = 323), and their level of depressive symptoms was assessed using the Beck Depression Inventory. The median score was used to create two groups (lower ≤ 13; higher > 13). A web-based food-frequency questionnaire, the Three-Factor Eating Questionnaire, and the Intuitive Eating Scale were completed. BMI was calculated from reported body weight and height. Compared to women with a lower level of depressive symptoms, those with a higher level of depressive symptoms reported a higher energy intake (p = 0.02), and a higher consumption of savoury foods (p = 0.02). These women also had higher scores of disinhibition (p p = 0.0002), ate less intuitively (p p = 0.005). Association between depressive symptoms and energy intake was mediated by disinhibition, susceptibility to hunger and eating for physical rather than emotional reasons, while the role of BMI was less clear. Regarding another component of food intake, association between depressive symptoms and consumption of savoury foods was mediated by disinhibition and eating for physical rather than emotional reasons. In summary, it seems essential to be aware of the presence of depressive symptoms and to pay attention to eating behaviors and attitudes in interventions among weight-preoccupied women.
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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 | 0.002 |
| 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".