Food insecurity is associated with poor mental health outcomes among a diverse sample of young adults
Bibliographic record
Abstract
Abstract Objective: Young adulthood is a transitional period between childhood and adulthood characterised by unique stressors that increase the risk of food insecurity and poor mental health. This study examined the association between food insecurity and mental health outcomes among U.S. young adults aged 18–25. Design: A cross-sectional survey was completed by young adults between the ages of 18 and 25 years between January and April 2022. Key measures included food insecurity, perceived stress, anxiety, depressive symptoms and insomnia. Descriptive statistics and linear regression analyses were used to determine the prevalence of and associations between food insecurity and mental health outcomes, controlling for key demographic and social factors. Setting: Online survey. Participants: 1630 U.S. young adults. Results: Among the analytic sample of 1041 young adults, nearly 70 % of participants identified as being food insecure in the last year. Participants reported moderate to high levels of perceived stress, anxiety, depressive symptoms and insomnia. Food insecurity was positively associated with each mental health outcome including perceived stress (β = 2·28, P< 0·01), anxiety (β = 2·84, P< 0·01), depressive symptoms (β = 2·74, P< 0·01) and insomnia (β = 1·28, P< 0·01) after controlling for all other factors. Conclusion: Food insecurity is associated with mental health problems among young adults. Future efforts should explore the directionality of this relationship to determine if food insecurity initiates or exacerbates poor mental health outcomes or if poor mental health contributes to food insecurity. Interventions to improve food security status may also help support mental health among young adults.
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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 | 0.001 |
| 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".