Increased consumption of fruit and vegetables for the primary prevention of cardiovascular diseases
Bibliographic record
Abstract
Editorial note: This Cochrane Review has been superseded by a review entitled Vegan dietary pattern for the primary and secondary prevention of cardiovascular diseases (https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD013501.pub2/full) https://pubmed.ncbi.nlm.nih.gov/33629376/ BACKGROUND: There is increasing evidence that high consumption of fruit and vegetables is beneficial for cardiovascular disease (CVD) prevention. OBJECTIVES: The primary objective is to determine the effectiveness of i) advice to increase fruit and vegetable consumption ii) the provision of fruit and vegetables to increase consumption, for the primary prevention of CVD. SEARCH METHODS: We searched the following electronic databases: The Cochrane Library (2012, issue 9-CENTRAL, HTA, DARE, NEED), MEDLINE (1946 to week 3 September 2012); EMBASE (1980 to 2012 week 39) and the Conference Proceedings Citation Index - Science on ISI Web of Science (5 October 2012). We searched trial registers, screened reference lists and contacted authors for additional information where necessary. No language restrictions were applied. SELECTION CRITERIA: Randomised controlled trials with at least three months follow-up (follow-up was considered to be the time elapsed since the start of the intervention) involving healthy adults or those at high risk of CVD. Trials investigated either advice to increase fruit and vegetable intake (via any source or modality) or the provision of fruit and vegetables to increase intake. The comparison group was no intervention or minimal intervention. Outcomes of interest were CVD clinical events (mortality (CVD and all-cause), myocardial infarction (MI), coronary artery bypass grafting (CABG) or percutaneous transluminal coronary angioplasty (PTCA), angiographically-defined angina pectoris, stroke, carotid endarterectomy, peripheral arterial disease (PAD)) and major CVD risk factors (blood pressure, blood lipids, type 2 diabetes). Trials involving multifactorial lifestyle interventions (including different dietary patterns, exercise) or where the focus was weight loss were excluded to avoid confounding. DATA COLLECTION AND ANALYSIS: Two review authors independently selected trials for inclusion, extracted data and assessed the risk of bias. Trials of provision of fruit and vegetables were analysed separately from trials of dietary advice. MAIN RESULTS: We identified 10 trials with a total of 1730 participants randomised, and one ongoing trial. Six trials investigated the provision of fruit and vegetables, and four trials examined advice to increase fruit and vegetable consumption.The ongoing trial is examining the provision of an avocado-rich diet.The number and type of intervention components for provision, and the dietary advice provided differed between trials.None of the trials reported clinical events as they were all relatively short term. There was no strong evidence for effects of individual trials of provision of fruit and vegetables on cardiovascular risk factors, but trials were heterogeneous and short term. Furthermore, five of the six trials only provided one fruit or vegetable. Dietary advice showed some favourable effects on blood pressure (systolic blood pressure (SBP): mean difference (MD) -3.0 mmHg (95% confidence interval (CI) -4.92 to -1.09), diastolic blood pressure (DBP): MD -0.90 mmHg (95% CI -2.03 to 0.24)) and low-density lipoprotein (LDL) cholesterol but analyses were based on only two trials. Three of the 10 included trials examined adverse effects, which included increased bowel movements, bad breath and body odour. AUTHORS' CONCLUSIONS: There are very few studies to date examining provision of, or advice to increase the consumption of, fruit and vegetables in the absence of additional dietary interventions or other lifestyle interventions for the primary prevention of CVD. The limited evidence suggests advice to increase fruit and vegetables as a single intervention has favourable effects on CVD risk factors but more trials are needed to confirm this.
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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 | 0.014 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".