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Record W4387195479 · doi:10.1186/s13643-023-02312-3

Saturated fat, the estimated absolute risk and certainty of risk for mortality and major cancer and cardiometabolic outcomes: an overview of systematic reviews

2023· review· en· W4387195479 on OpenAlexaff
Jhalok Ronjan Talukdar, Jeremy Steen, Joshua Z. Goldenberg, Qian Zhang, Robin W.M. Vernooij, Long Ge, Dena Zeraatkar, Małgorzata M Bała, Geoff D.C. Ball, Lehana Thabane, Bradley C. Johnston

Bibliographic record

VenueSystematic Reviews · 2023
Typereview
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsSt. Joseph’s Healthcare HamiltonUniversity of AlbertaUniversity of OttawaMcMaster UniversityImpact
FundersCollege of Agriculture and Life Sciences, Texas A and M University
KeywordsMedicineAbsolute risk reductionCertaintyRisk assessmentCancerEnvironmental healthGerontologyInternal medicinePopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the impact of reducing saturated fat or fatty foods, or replacing saturated fat with unsaturated fat, carbohydrate or protein, on the risk of mortality and major cancer and cardiometabolic outcomes in adults. METHODS: We searched MEDLINE, EMBASE, CINAHL, and references of included studies for systematic reviews and meta-analyses (SRMAs) of randomized controlled trials (RCTs) and observational studies in adults published in the past 10 years. Eligible reviews investigated reducing saturated fat or fatty foods or replacing saturated fat with unsaturated fat, carbohydrate or protein, on the risk of cancer and cardiometabolic outcomes and assessed the certainty of evidence for each outcome using, for example, the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) approach. We assessed the quality of SRMAs using a modified version of AMSTAR-2. Results were summarized as absolute estimates of effect together with the certainty of effects using a narrative synthesis approach. RESULTS: We included 17 SRMAs (13 reviews of observational studies with follow-up 1 to 34 years; 4 reviews of RCTs with follow-up 1 to 17 years). The quality of two-thirds of the SRMAs was critically low to moderate; the main limitations included deficient reporting of study selection, absolute effect estimates, sources of funding, and a priori subgroups to explore heterogeneity. Our included reviews reported > 100 estimates of effect across 11 critically important cancer and cardiometabolic outcomes. High quality SRMAs consistently and predominantly reported low to very low certainty evidence that reducing or replacing saturated fat was associated with a very small risk reduction in cancer and cardiometabolic endpoints. The risk reductions where approximately divided, some being statistically significant and some being not statistically significant. However, based on 2 moderate to high quality reviews, we found moderate certainty evidence for a small but important effect that was statistically significant for two outcomes (total mortality events [20 fewer events per 1000 followed] and combined cardiovascular events [16 fewer per 1000 followed]). Conversely, 4 moderate to high quality reviews showed very small effects on total mortality, with 3 of these reviews showing non-statistically significant mortality effects. CONCLUSION: Systematic reviews investigating the impact of SFA on mortality and major cancer and cardiometabolic outcomes almost universally suggest very small absolute changes in risk, and the data is based primarily on low and very low certainty evidence. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020172141.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
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 score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0220.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.405
GPT teacher head0.486
Teacher spread0.080 · 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 teacher head, not a consensus.

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

Citations14
Published2023
Admission routes1
Has abstractyes

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