A influência do estilo de vida no estado nutricional de idosos: uma revisão sistemática da literatura
Bibliographic record
Abstract
Introduction: Lifestyle is described as a pattern of behavior that can have effects on health and is related to aspects that reflect attitudes, values, and opportunities. Goal: To conduct a systematic review of published articles on the influence of lifestyle on the nutritional status of elderly people. Materials and Methods: Published articles found in three research databases, namely, Lilacs, PubMed, and SciELO, were analyzed. After searching for descriptors, abstracts were peer-selected in two phases, by two readers each. Bias analysis was conducted using a validated protocol (Newcastle-Ottawa), which has been adapted for cross-sectional studies. Results: Eight articles were identified in the systematic review. Most of the papers were published in 2013. From the analyzed articles, four lifestyle factors were found to be significantly associated with the nutritional status of elderly people. The studies included in the review employed the Mini Nutritional Assessment, the Mini Nutritional Assessment-Short Form, and the criterion of the European Working Group on Sarcopenia in Older People to assess nutritional status. Discussion: Some of the lifestyle factors found to be significant protectors of nutritional status were regular consumption of alcohol, habitual physical activity, and leisure. Factors with a negative influence were smoking and sedentarism. Conclusion: The study identified the influence of lifestyle factors (physical activity, alcohol, smoking, and leisure) on the nutritional status of elderly people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.025 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".