Supplementation of Olive Oil and Flaxseed Oil on Blood Pressure and Inflammation in Healthy and At-Risk Adults: A Systematic Literature Review and Meta-Analysis
Bibliographic record
Abstract
Background: Adding olive oil (OO) and flaxseed oil (FLO) to the diet has been reported to improve endothelial function and reduce inflammation. However, the efficacy of supplementing OO and FLO on blood pressure (BP) in normo-, pre-, and hypertensive stage 1 adults is uncertain. Objective: This study aimed to systematically review the literature on OO and FLO supplementation on BP and select inflammatory markers in healthy adults and adults at risk of hypertension. Methods: Four databases, PubMed, CINHAL, Web of Science, and Medline (Ovid), were searched from inception until October 2023 for randomized control trials (RCTs) comparing OO and FLO supplementation in normotensive or adults at risk of hypertension. The outcomes included were systolic blood pressure (SBP) and/or diastolic blood pressure (DBP) and at least one inflammatory marker, C-reactive protein (CRP), interleukin6 (IL6), or tumor necrosis factor alpha (TNFα). The risk of bias was assessed using version 2 of the Cochrane risk of bias tool for RCTs, publication bias visualization was performed using funnel plots, and meta-analysis was completed to generate average estimates of effects in 2024. Results: Seventeen RCTs, comprising 14 studies on OO and 3 on FLO, met the inclusion criteria. Meta-analysis using a random-effects model reported no significant effect on SBP n=17 mean difference (MD) -0.48; 95% CI: -1.76, 0.80; p=0.65, I2=0%) and DBP (n=16, MD -0.47; 95% CI: -1.33, 0.39; p=0.65, I2=0%) or inflammatory markers, CRP (n=8, MD 0.11; 95% CI: -1.18, 0.40; p=0.98, I2=0%), IL6 (n=3, MD -0.15; 95% CI: -0.57, 0.27; p=0.87, I2=0%), and TNFα (n=3, MD-0.08; 95% CI: -0.12, -0.03; p=0.98, I2=0%). Conclusion: Longer-duration, higher-dose, and larger-scale RCTs are needed to better understand the efficacy of OO and FLO supplementation on BP. Further insight will better inform dietary supplement use for preventing hypertension.
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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.031 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".