Association between depression and fruit and vegetable consumption among adults in South Asia
Bibliographic record
Abstract
BACKGROUND: In recent years there has been a growing research interest regarding the impact of dietary behaviour on mental health outcomes. The present study aimed to investigate the association between fruit and vegetable (F&V) consumption and depression in three south Asian countries- Bangladesh, India and Nepal. METHODS: Cross-sectional data were obtained from World Health Survey of WHO conducted during 2002-04. In total 14,133 adult subjects (Bangladesh 3262, India 7594, Nepal 3277) aged 18 years and above were included in the study. Outcome variables were Self-Reported Depression (SRD) during last 30 days and 12 months. Multivariable regression methods were used to explore the association between F&V consumption and depression. RESULTS: Prevalence of Self-Reported Depression during past 12 months were respectively 39%, 17.7%, and 49.9% for Bangladesh, India and Nepal. In India, those who consumed less than five servings of vegetables were respectively 41% [AOR = 1.41; 95%CI = 0.60-3.33] and 57% [AOR = 1.57; 95%CI = 0.93-2.64] more likely to report severe-extreme and mild-moderate depression during past 30 days compared to those who consumed five servings a day. Regarding fruit consumption, compared to those who consumed five servings a day, the odds of severe-extreme and mild-moderate SRD were respectively 3.5 times [AOR = 3.48; 95%CI = 1.216-10.01] and 45% [AOR = 1.44; 95%CI = 0.89-2.32] higher in Bangladesh, and 2.9 times [AOR = 2.92; 95%CI = 1.12-7.64] and 42% higher [AOR = 1.41; 95%CI = 0.89-2.24] in Nepal compared to those who consumed less than five servings a day during last 30 days. CONCLUSION: Daily intake of less than five servings of F&V was associated with higher odds of depression. Nutrition programs aimed at promoting F&V consumption might prove beneficial to reduce the prevalence of depression in south Asian population. Further studies are required to understand the factors limiting the adequate consumption of F&V.
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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 | 0.001 |
| 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".