Evidence map›Paper›PMID 35119682›Full record

SynthesisCurrent cardiology reports2022

Associations of Glycemic Index and Glycemic Load with Cardiovascular Disease: Updated Evidence from Meta-analysis and Cohort Studies.

Alok Kumar Dwivedi, Pallavi Dubey, Sireesha Y Reddy, Deborah J Clegg

Abstract readMeta-AnalysisReview
PubMed Publisher
In one paragraph

Synthesis in Current cardiology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
10.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Alok Kumar DwivediDivision of Biostatistics & Epidemiology, Department of Molecular and Translational Medicine, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, 5001 El Paso Drive, TX, 79905, USA. alok.dwivedi@ttuhsc.edu.ORCID 0000-0003-4574-1761
Pallavi DubeyDepartment of Obstetrics & Gynecology, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, 4800 Alberta Avenue, El Paso, TX, 79905, USA.
Sireesha Y ReddyDepartment of Obstetrics & Gynecology, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, 4800 Alberta Avenue, El Paso, TX, 79905, USA.
Deborah J CleggDepartment of Internal Medicine, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, 4800 Alberta Avenue, El Paso, TX, 79905, USA.
Texas Tech University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewDiet and lifestyle patterns are considered major contributory factors for cardiovascular disease (CVD) and mortality. In particular, consuming a diet higher in carbohydrates (not inclusive of fruits and vegetables, but more processed carbohydrates) has been associated with metabolic abnormalities that subsequently may increase the risk of CVD and related mortality. Glycemic index (GI) and glycemic load (GL) are values given to foods based on how fast the body converts carbohydrates into glucose also referred to as the glycemic burden of carbohydrates from foods. Conflicting associations of how high GI and GL influence CVDs have been observed even in high-quality meta-analysis studies. We synthesize and report the associations of high GI and GL with various CVDs by sex, obesity, and geographical locations using an updated review of meta-analysis and observational studies. RECENT

findingsWe identified high GI or high GL is associated with an increased risk of CVD events including diabetes (DM), metabolic syndrome (MS), coronary heart disease (CHD), stroke, and stroke mortality in the general population, and the risk of CVD outcomes appears to be stratified by sex, obesity status, and preexisting CVD. Both high GI and GL are associated with DM and CHD in the general population. However, high GI is strongly associated with DM/MS, while high GL is strongly associated with an increased risk of CHD in females. In addition, high GL is also associated with incident stroke, and appears to be associated with CVD mortality in subjects with preexisting CVD or high BMI and all-cause mortality in non-obese DM subjects. However, high GI appears to be associated with CVD or all-cause mortality only in females without CVD. High GI/GL is an important risk factor for CVD outcomes in the general population. High GI seems to be markedly associated with DM/MS, and it may enhance the risk of CVD or all-cause mortality in both sexes and predominately females. Although both high GI and high GL are risk factors for CHD in females, high GL is associated with CVD outcomes in at-risk populations for CVD. These data suggest that while high GI increases the propensity of CVD risk factors and mortality in healthy individuals, high GL contributes to the risk of severe heart diseases including CVD or all-cause mortality, particularly in at-risk populations. These data indicate dietary interventions designed for focusing carbohydrate quality by lowering both GI and GL are recommended for preventing CVD outcomes across all populations.

Indexed as

Cardiovascular DiseasesCoronary DiseaseGlycemic LoadStrokeBlood GlucoseCohort StudiesDietDietary CarbohydratesFemaleGlycemic IndexHumansMaleObesityRisk FactorsBlood GlucoseDietary CarbohydratesAll-cause mortalityBody mass indexCardiovascular diseaseDiabetesGlycemic indexGlycemic loadHeart diseaseObesityStroke

Identifiers

PMID35119682
OpenAlexW4210785595

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.