Blood Lipid Levels in Response to Almond Consumption: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Background/Objectives: While the benefits of almond consumption in reducing levels of TC and LDL-C are well established, the effects on additional lipids that have emerged as important predictors of cardiovascular disease, such as ApoB and the ratio of ApoB:ApoA, are not well characterized. In this systematic review and meta-analysis, the effects of almond consumption on blood lipids were comprehensively assessed. Methods: On 12 May 2025, ProQuest Dialog™ was used to search ten literature databases (AdisInsight: Trials; Allied & Complementary Medicine™; BIOSIS Previews®; CAB ABSTRACTS; Embase®; Embase Preprints; Foodline®: SCIENCE; FSTA®; MEDLINE®; National Technical Information Service). Randomized controlled trials at least 4 weeks in duration were included if the investigational product was almonds; the control was void of nuts/tree nuts; the subjects were adults without CVD; and blood lipid levels were assessed. Health Canada’s Quality Appraisal Tool for Intervention Studies was used to assess each study’s risk of bias. The mean difference in the effect for each parameter was pooled across studies in a random effects model, using the inverse of the variance as the weighting factor. Results: 36 publications (48 almond–control datasets) representing 2485 participants were included. Almond consumption significantly reduced LDL-C (−0.132 mmol/L; 95% CI: −0.190, −0.075 mmol/L; p < 0.001), TC (−0.160 mmol/L; 95% CI: −0.218, −0.101 mmol/L; p < 0.001), non-HDL-C (−0.204 mmol/L; 95% CI: −0.281, −0.127 mmol/L; p < 0.001), TC:HDL-C (−0.154; 95% CI: −0.246, −0.063; p = 0.001), LDL-C:HDL-C (−0.112; 95% CI: −0.199, −0.026; p = 0.011), ApoB (−4.552 mg/dL; 95% CI: −6.460, −2.645 mg/dL; p < 0.001), and ApoB:ApoA (−0.027; 95% CI: −0.046, −0.008; p = 0.006), with a borderline significant reduction in TG (−0.037 mmol/L; 95% CI: −0.079, 0.005; p = 0.085) and no effects on HDL-C, ApoA, or Lp[a]. The effects persisted when the analyses were limited to higher quality studies, except for the reduction in TG. Conclusions: Almond consumption improves levels of LDL-C, TC, non-HDL-C, TC:HDL-C, LDL-C:HDL-C, ApoB, and ApoB:ApoA, though dedicated clinical trials are needed to better understand effects on TG levels.
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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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".