Food Insecurity Contributes to Poorer Dietary Outcomes in Higher Education Students: A Systematic Review
Bibliographic record
Abstract
Tertiary education students have been found to experience a higher prevalence of food insecurity than the general population. This systematic review aims to examine the existing evidence on the association between food insecurity and dietary outcomes among higher education students. Nine electronic databases and gray literature were searched. Studies that reported dietary outcomes (e.g., nutritional intake and meal patterns) in students of differing food security status in tertiary education settings in any country were included. All primary study designs were eligible for inclusion, except for qualitative studies. Two reviewers completed the title/abstract and full-text screening, data extraction, and quality assessment independently. A total of 14 studies were included in the final qualitative synthesis of this review. The prevalence of food insecurity among higher education students ranged from 21% to 82% across the included studies from the United States, Canada, Australia and Greece. Lower intakes of healthy foods (e.g., fruits, vegetables, and whole grains) and higher intakes of unhealthy foods (e.g., fast foods, added sugars, and sugar-sweetened beverages) were observed in food-insecure students. Some students also consumed less breakfast and evening meal than food-secure students but the evidence was limited. The overall diet quality was not consistently measured in students with different food security status by using validated dietary assessment tools. Poorer dietary outcomes were found in higher education students with food insecurity compared with food-secure students. More policy interventions, effective nutrition education, and food assistance programs should be provided by tertiary education institutions and governments to target the nutritional needs of food-insecure students. This review received no specific funding.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".