Food and Mood: An Investigation Into the Association Between Diet Quality and Depressive Symptoms
Bibliographic record
Abstract
Research has suggested that there may be an association between diet and depressive symptoms. This association has not been well examined among emerging adults, who are at increased risk of developing both depression and unhealthy lifestyle habits. Research objectives were to examine the cross-sectional association between depressive symptoms and each of diet quality, fruits and vegetable intake, omega-3 fatty acids, protein, “other foods”, and glycemic index/glycemic load in emerging adult females. One hundred and forty-one female subjects from two undergraduate nutrition courses at the University of Guelph were recruited in Fall 2012 and Winter 2013. Measures of diet (Healthy Eating Index - Canadian Adaptation; HEI-C), depressive symptoms (Center for Epidemiologic Studies Depression Scale; CES-D), and other health behaviours (e.g., physical activity) were collected. Descriptive statistics and age-adjusted linear regressions were performed to test for associations between depressive symptoms and diet. Independent t-tests examined differences in dietary intake between reporters of high vs. low levels of depressive symptoms. Depressive symptoms were inversely associated with diet quality (r = 0.21, p = 0.043). There was no association between depressive symptoms and other dietary variables (p > .05). Independent t-tests revealed no differences in dietary variables between reporters of high vs. low depressive symptoms (p > .05). The inverse association between diet quality and depressive symptoms indicates that those with higher levels of depressive symptoms are consuming diets of poorer nutritional quality than those with lower levels of depressive symptoms, but given the cross-sectional nature of this research, the temporal order of this association is not known. The association between diet and depressive symptoms is likely bi-directional, and thus dietary intervention could eventually be used as an adjunctive treatment for depression.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".