Dietary Changes of Youth during the COVID-19 Pandemic: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has taken the lives of millions and disrupted countless more worldwide. Simply living through the pandemic has had drastic effects on the health of citizens. Diet, an important aspect of health, has been uniquely affected by the pandemic, although these changes have not been sufficiently studied among youth. OBJECTIVES: The objective of this systematic review was to investigate dietary changes of youth during COVID-19. METHODS: A prespecified literature review was conducted using MEDLINE, EMBASE, Scopus, and CINAHL to identify studies from January 2020 to May 2023 that assessed dietary changes among youth aged ≤20 y compared with before the pandemic. Only quantitative observational studies that were published in English were included. Two authors completed all screening/study selection independently, with disagreements being resolved via discussion. Data extraction was completed by 1 author. Dietary changes were categorized into food groups and habits for analysis purposes. RESULTS: In total, 67 studies met inclusion criteria. Most studies used recall to assess changes (48/67; 71.6%). Most studies found an increase in fruits and vegetables (24/46; 52.2%), grain products (6/11; 54.5%), meat, poultry, and eggs (4/8, 50.0%), diet quality indices and/or overall dietary assessments (7/13, 53.8%), and the frequency of snacking (9/12; 75.0%), whereas generally finding a decrease in ultraprocessed foods (32/53; 60.4%), compared with before the COVID-19 pandemic. Mixed findings or primarily no changes were found for fish and aquatic products, legumes, beans, seeds and nuts, milk and milk products, breakfast consumption, and nutrient intake. CONCLUSIONS: Mostly favorable dietary changes appear to have occurred among youth during COVID-19, although there were several mixed findings and unclear takeaways among the foods and habits under study. The heterogeneity of defining food groups was a noted limitation in the current review.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".