Understanding healthy eating/nutrition interventions for people living with dementia: A systematic review
Bibliographic record
Abstract
BACKGROUND: There is limited research focused on lifestyle interventions for people living with dementia and recent systematic reviews primarily focus on the impact of exercise on cognition. However, functional abilities and quality of life (QoL) are the outcomes most consistently prioritized by people living with dementia, care partners, and healthcare professionals. We conducted a systematic review to understand the impact of two lifestyle interventions (physical activity, nutrition) on the functional abilities, quality of life, and nutritional status (nutrition interventions only) of people living with dementia living in the community. The results presented here focus on the effects of nutrition interventions. METHOD: Systematic literature searches for peer-reviewed intervention studies were conducted in four databases (MEDLINE, EMBASE, Scopus, CINAHL). Articles were exported to Covidence, where duplicates were removed and two independent reviewers performed study selection, data extraction, and risk of bias assessments. A narrative synthesis was conducted. RESULT: Six studies met the inclusion criteria. Five studies compared nutrition interventions to usual care. Interventions included education/counselling on nutrition through various delivery modes; one study also included coaching to reduce care partner stress and encourage protein supplementation. Sample sizes (n = 12 - 946) and follow-up periods varied substantially across studies (3 weeks - 12 months). Five studies assessed nutritional status, all of which used the Mini-Nutritional Assessment. The two largest studies, a cluster-randomized trial with 946 participants (intervention = 448; control=498) and a non-randomized controlled trial with 225 participants (intervention = 151; control=74) found significantly better nutritional status in the intervention compared to control groups. Results showed no change for two studies and data collection was incomplete for one study. Other outcomes measures included: QoL (n = 2 studies), activities of daily living (ADL)/instrumental ADL (n = 3 studies), falls (n = 1 study), grip strength (n = 1 study), timed up and go test (n = 1 study), lower body strength (n = 1 study), and step test (n = 1 study). CONCLUSION: Existing literature suggests that nutritional status can be improved through nutrition interventions, supporting a role for nutrition risk screening and intervention among people living with dementia. Additional large-scale studies are needed to understand the impact of these interventions on nutritional status, QoL, and functional abilities while considering barriers to access.
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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 | 0.016 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".