MétaCan
Menu
Back to cohort
Record W4289225774 · doi:10.1093/nutrit/nuac040

Walnut consumption and health outcomes with public health relevance—a systematic review of cohort studies and randomized controlled trials published from 2017 to present

2022· review· en· W4289225774 on OpenAlexaboutno aff
S. Lockyer, Anne de la Hunty, Simon Steenson, A. Spiro, Sara Stanner

Bibliographic record

VenueNutrition Reviews · 2022
Typereview
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsnot available
FundersAston UniversityKing's College LondonCalifornia Walnut Commission
KeywordsMedicineCohortRandomized controlled trialCohort studyDiseasePublic healthMEDLINEEnvironmental healthObesityGerontologyInternal medicinePhysical therapyPathology

Abstract

fetched live from OpenAlex

CONTEXT: Considering the accumulation of recent studies investigating the health effects of walnut consumption, both including and beyond cardiovascular health effects, a systematic review of this literature to investigate the strength of the evidence is warranted. OBJECTIVE: To investigate associations between walnut consumption and outcomes with public health relevance (specifically all-cause mortality, type 2 diabetes, CVD, metabolic syndrome, obesity, cancer, neurological and mental health, musculoskeletal, gastrointestinal, and maternal disorders) and the effect on associated disease risk markers, reported in studies published from 2017 to present. DATA SOURCES: MEDLINE, FSTA, CENTRAL, and Scopus were searched from 1 January 2017 to 5 May 2021. DATA EXTRACTION: Human studies (cohort studies and RCTs) ≥3 weeks in duration comparing consumption of walnuts (whole, pieces, or 100% butter) to a control and measuring associations with relevant public health outcomes and disease risk markers were assessed. Key study characteristics were extracted independently by 2 investigators using a standardized table. The quality of the studies was assessed using the Cochrane Risk-of-Bias tool 2.0 and the Newcastle-Ottawa Scale. DATA ANALYSIS: Only 1 RCT was considered to be at low risk of bias for any of its outcomes. The cohort studies were considered to be of moderate or high quality. The results were synthesized using vote counting, based on the direction of effect. Thirty-three articles, 23 describing RCTs (walnut dose ∼10-99 g/day, 1,948 subjects) and 10 describing cohort studies (∼675,928 subjects), were included. Vote counting could be performed for the blood lipids, cardiovascular function, inflammation- and hemostatic-related factors, markers of glucose metabolism, and body weight and composition outcome groupings. The results are presented in effect direction plots. With respect to blood lipids, results from 8/8 RCTs favoured walnuts, in accordance with associations with a reduced risk of CVD suggested by cohort studies; results from 6/6 RCTs favoured control with respect to body weight and composition, although most of these effects were small. This was contrary to cohort study results suggesting small benefits of walnut consumption on body weight. There was no overall consistent direction of effect for cardiovascular function, markers of glucose metabolism, or inflammation- and hemostatic-related factors. CONCLUSIONS: Evidence published since 2017 is consistent with previous research suggesting that walnut consumption improves lipid profiles and is associated with reduced CVD risk. Evidence is accumulating in other areas, such as cognitive health, although more research is needed to draw firm conclusions. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD4202122.

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 imitation

Not 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.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.119
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.033
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.119
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.012
Bibliometrics0.0160.018
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.266
GPT teacher head0.470
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations19
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueNutrition ReviewsSame topicNuts composition and effectsFrench-language works237,207