Nutrient intake and dietary quality changes within a personalized lifestyle intervention program for metabolic syndrome in primary care
Bibliographic record
Abstract
A team-based 12-month lifestyle program for the treatment of metabolic syndrome (MetS) (involving physicians, registered dietitians (RDs), and kinesiologists) was previously shown to reverse MetS in 19% of patients (95% confidence interval, 14% to 24%). This work evaluates changes in nutrient intake and diet quality over 12 months (n = 205). Individualized diet counselling was provided by 14 RDs at 3 centres. Two 24-h recalls, the Canadian Healthy Eating Index (HEI-C), and the Mediterranean Diet Score (MDS) were completed at each time point. Total energy intake decreased by 145 ± 586 kcal (mean ± SD) over 3 months with an additional 76 ± 452 kcal decrease over 3–12 months. HEI-C improved from 58 ± 15 to 69 ± 12 at 3 months and was maintained at 12 months. Similarly, MDS (n = 144) improved from 4.8 ± 1.2 to 6.2 ± 1.9 at 3 months and was maintained at 12 months. Changes were specific to certain food groups, with increased intake of fruits, vegetables, and nuts and decreased intake of “other foods” and “commercial baked goods” being the most prominent changes. There was limited change in intake of olive oil, fish, and legumes. Exploratory analysis suggested that poorer diet quality at baseline was associated with greater dietary changes as assessed by HEI-C. Novelty Multiple dietary assessment tools provided rich information on food intake changes in an intervention for metabolic syndrome. Improvements in diet were achieved by 3 months and maintained to 12 months. The results provide a basis for further dietary change implementation studies in the Canadian context.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".