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Relation of Total Sugars and Fructose‐Containing Sugars with Risk of Cardiovascular Disease: A Systematic Review and Meta‐Analysis of Prospective Cohort Studies

2016· review· en· W2891687421 on OpenAlexaffabout
Tauseef Khan, Sonia Blanco Mejía, Russell J. de Souza, Cyril W.C. Kendall, John L. Sievenpiper

Bibliographic record

VenueThe FASEB Journal · 2016
Typereview
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsMcMaster UniversityUniversity of TorontoUniversity of SaskatchewanSt. Michael's Hospital
Fundersnot available
KeywordsMedicineProspective cohort studyRelative riskMeta-analysisCochrane LibraryCohort studyConfidence intervalFructoseCohortInternal medicineFood scienceChemistry

Abstract

fetched live from OpenAlex

Objective Intake of sugars‐sweetened beverages has been associated with weight gain and risk of cardiovascular disease in adults, though, it is not known if the intake of total sugars and particularly fructose‐containing sugars is associated with cardiovascular disease (CVD). We undertook a systematic review and meta‐analysis of cohort studies to quantify the relation of total sugars, sucrose, and fructose with incident CVD. Methods MEDLINE, EMBASE and Cochrane Library (through October 31, 2015) were searched for relevant studies. We included prospective cohort studies in humans investigating the association between total and individual fructose‐containing sugars and incident CVD. Two independent reviewers reviewed and extracted the relevant data and assessed study quality (Newcastle‐Ottawa Scale). Risk estimates of extreme comparisons (lowest versus highest quantile) were pooled using inverse variance random effects models and expressed as risk ratios (RR) with 95% confidence intervals (CIs). Inter‐study heterogeneity was assessed with Cochran Q statistic and quantified with the I 2 statistic. Results Eight prospective cohort comparisons (n = 512,343) involving 14,035 cases of CVD observed over an average of 11.9 years of follow‐up were eligible. Median total sugar intake was 55 g and 115 g in the lowest and highest quantile respectively. Total sugars intake was weakly associated with increased CVD risk (RR, 1.08 [95% CIs, 1.01 to 1.14]) with no evidence of heterogeneity (I 2 = 0%, p= 0.99). There was a weak positive association with total fructose intake (RR, 1.08 [95% CIs, 1.00 to 1.15]) but not total sucrose intake (RR, 0.95 [95% CIs, 0.87 to 1.04]) with no evidence of significant heterogeneity (I 2 <29%, P>0.24). Effect estimates were similar when stratified by sex. Limitations As the observed associations were weak and the 95% CIs for sucrose included potentially important benefit, measured and unmeasured residual confounding cannot be excluded. Conclusions Total sugars and fructose were weakly associated with increased CVD risk in eight large prospective cohort comparisons. Additional studies looking at important food sources of sugars other than sugars‐sweetened beverages may be helpful in better explaining the relationship between dietary sugars and CVD risk. Support or Funding Information Canadian Diabetes Association and PSI Foundation. https://clinicaltrials.gov/ct2/show/NCT01608620

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)0.016
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.036
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.039
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.313
Teacher spread0.277 · 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.

Study designMeta-analysis
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

Citations0
Published2016
Admission routes2
Has abstractyes

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