Effect of Current Dietary Recommendations on Weight Loss and Cardiovascular Risk Factors
Bibliographic record
Abstract
BACKGROUND: Dietary recommendations emphasize increased consumption of fruit, vegetables, and whole grain cereals for prevention of chronic disease. OBJECTIVES: This study assessed the effect of dietary advice and/or food provision on body weight and cardiovascular disease risk factors. METHODS: , were randomized between November 2005 and August 2009 to receive Health Canada's food guide (control, n = 486) or 1 of 3 interventions: dietary advice consistent with both Dietary Approaches to Stop Hypertension (DASH) and dietary portfolio principles (n = 145); weekly food provision reflecting this advice (n = 148); or food delivery plus advice (n = 140). Interventions lasted 6 months with 12-month follow-up. Semiquantitative food frequency questionnaires and fasting blood, anthropometric and blood pressure measurements were obtained at baseline, 6 months, and 18 months. RESULTS: Participant retention at 6 and 18 months was 91% and 81%, respectively, after food provision compared to 67% and 57% when no food was provided (p < 0.0001). Test and control treatments showed small reductions in body weight (-0.8 to -1.2 kg), waist circumference (-1.1 to -1.9 cm), and mean arterial pressure (0.0 to -1.1 mm Hg) at 6 months and Framingham coronary heart disease risk score at 18 months (-0.19 to -0.42%), which were significant overall. Outcomes did not differ among test and control groups. CONCLUSIONS: Provision of foods increased retention but only modestly increased intake of recommended foods. Current dietary recommendations showed small overall benefits in coronary heart disease risk factors. Additional dietary strategies to maximize these benefits are required. (Fruits, Vegetables, and Whole Grains: A Community-based Intervention; NCT00516620).
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".