A pulse-based diet is effective for reducing total and LDL-cholesterol in older adults
Bibliographic record
Abstract
Our purpose was to determine the effects of a pulse-based diet in individuals 50 years or older for reducing CVD risk factors. A total of 108 participants were randomised to receive pulse-based foods (two servings daily of beans, chickpeas, peas or lentils; about 150 g/d dry weight) or their regular diet for 2 months, followed by a washout of 1 month and a cross-over to the other diet for 2 months. Anthropometric measures, body composition and biochemical markers (i.e. serum LDL-cholesterol (LDL-C), as the primary outcome, and other lipids, glucose, insulin and C-reactive protein) were assessed before and after each diet phase. A total of eighty-seven participants (thirty males and fifty-seven females; 59·7 (sd 6·3) years, body mass 76 (sd 16) kg) completed the study. Compared with the regular diet, the pulse-based diet decreased total cholesterol by 8·3 % (pulse, 4·57 (sd 0·93) to 4·11 (sd 0·91) mmol/l; regular, 4·47 (sd 0·94) to 4·39 (sd 0·97) mmol/l; P < 0·001) and LDL-C by 7·9 % (pulse, 2·93 (sd 0·84) to 2·55 (sd 0·75) mmol/l; regular, 2·96 (sd 0·86) to 2·81 (sd 0·83) mmol/l; P = 0·01). In a sub-analysis of individuals with high lipid levels at baseline (twenty individuals with high cholesterol), the pulse-based diet reduced cholesterol by 6 % compared with the regular diet (pulse, 5·62 (sd 0·78) to 5·26 (sd 0·68) mmol/l; regular, 5·60 (sd 0·91) to 5·57 (sd 0·85) mmol/l; P = 0·05). A pulse-based diet is effective for reducing total cholesterol and LDL-C in older adults and therefore reduces the risk of CVD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".