A target trial emulation of adherence to Canada’s Food Guide 2019 recommendations in older adults
Bibliographic record
Abstract
Abstract The 2019 Canada’s Food Guide (CFG) may not be tailored for older adults, since it provides universal recommendations. In community-dwelling adults aged 67-84 years and compared with habitual diet and physical activity, our objective was to estimate the 3-year difference in muscle strength, physical function, cardiometabolic health and cognitive health score according to adherence to CFG recommendations (CFG), enhancements with additional protein foods (CFG-PRO), physical activity (PA) and both (CFG-PLUS). Longitudinal non-experimental data from the NuAge study (2003-2008 in Québec, Canada) were used to emulate a 3-year target trial. Data was collected at annual in-person follow-up visits. The hypothetical interventions were modelled using the parametric g-formula assuming no unmeasured confounding, no measurement error and correct models. 1561 participants were eligible. Compared with no intervention, adherence to the CFG intervention would have increased quadriceps strength by 0.8 kg (95%CI: 0.0, 1.7), walking speed by 0.03 m/s (95%CI: 0.00, 0.05) and reduced waist circumference by 1.0 cm (95%CI: -1.7, -0.3). Estimates were similar for the CFG-PRO intervention. Compared with CFG alone, the CFG-PLUS intervention improved to a greater extent walking speed (vs. CFG, +0.06 m/s; 95%CI: 0.03, 0.08) and waist circumference (vs. CFG, -0.8 cm; 95%CI: -1.5, -0.2). Under strong assumptions, compared with no intervention leading to declines in most outcomes, adherence to CFG recommendations over 3 years would have attenuated declines in strength and walking speed in older adults. Greater benefits were achieved when protein food intake and physical activity were increased in addition to CFG adherence.
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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".