The socioecological correlates of meal skipping in community-dwelling older adults: a systematic review
Bibliographic record
Abstract
CONTEXT: Meal skipping may contribute to nutrient deficiency across the lifespan. Multiple socioecological factors have been identified as correlates of meal skipping in adolescents and adults, but evidence in older adults is limited. OBJECTIVE: To determine the socioecological correlates of meal skipping in community-dwelling older adults. DATA SOURCE: Embase, PsycINFO, CINAHL, and MEDLINE electronic databases were systematically searched from inception to March 2021. DATA EXTRACTION: A total of 473 original research studies on socioecological factors and meal skipping among community-dwelling adults aged ≥65 years were identified. Title, abstract, and full-text review was performed by 2 reviewers independently, and a third reviewer resolved disagreements. A total of 23 studies met our inclusion criteria. Data were extracted by 1 reviewer from these studies and independently verified by another. The Newcastle-Ottawa Scale was used to assess methodological quality. DATA ANALYSIS: The frequency of meal skipping in included studies ranged between 2.1% and 61%. This review identified 5 domains of socioecological correlates associated with meal skipping in older adults: sociodemographic, behavioral, biomedical, psychological, and social. CONCLUSION: Understanding the factors associated with meal skipping in older adults can inform the development of targeted interventions to improve nutrition and health. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42021249338.
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".