Evidence map›Paper›PMID 28701162›Full record

Trial reportNutrition journal2017

Does the ingestion of a 24 hour low glycaemic index Asian mixed meal diet improve glycaemic response and promote fat oxidation? A controlled, randomized cross-over study.

Stefan Gerardus Camps, Bhupinder Kaur, Rina Yu Chin Quek, Christiani Jeyakumar Henry

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Nutrition journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

12 citing papers in PubMed, 16 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 4 institutions in 1 country.

Stefan Gerardus CampsClinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Centre for Translational Medicine, Yong Loo Lin School of Medicine, 14 Medical Drive #07-02, MD 6 Building, Singapore, 117599, Singapore. Stefan_camps@sics.a-star.edu.sg.
Bhupinder KaurClinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Centre for Translational Medicine, Yong Loo Lin School of Medicine, 14 Medical Drive #07-02, MD 6 Building, Singapore, 117599, Singapore.
Rina Yu Chin QuekClinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Centre for Translational Medicine, Yong Loo Lin School of Medicine, 14 Medical Drive #07-02, MD 6 Building, Singapore, 117599, Singapore.
Christiani Jeyakumar HenryClinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Centre for Translational Medicine, Yong Loo Lin School of Medicine, 14 Medical Drive #07-02, MD 6 Building, Singapore, 117599, Singapore.
Agency for Science, Technology and Research · SGClinical Nutrition Research Centre · SGNational University Health System · SGNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe health benefits of consuming a low glycaemic index (GI) diet to reduce the risk of type 2 Diabetes are well recognized. In recent years the GI values of various foods have been determined. Their efficacy in constructing and consuming a low GI diet over 24 h in modulating glycaemic response has not been fully documented. The translation of using single-point GI values of foods to develop a 24 h mixed meal diet can provide valuable information to consumers, researchers and dietitians to optimize food choice for glycaemic control. By using GI values of foods to develop mixed meals, our study is the first to determine how both blood glucose and substrate oxidation may be modulated over 24 h.

methodsThe study included 11 Asian men with a BMI between 17-24 kg/m

resultsThe low GI diet resulted in lower 24 h glucose iAUC (860 ± 440 vs 1329 ± 614 mmol/L.min; p = 0.014) with lower postprandial glucose iAUC after breakfast (p < 0.001), lunch (p = 0.009), snack (p = 0.012) and dinner (p = 0.003). Moreover, 24 h mean amplitude of glycaemic excursion was lower during the low GI vs high GI diet (1.44 ± 0.63 vs 2.33 ± 0.82 mmol/L; p < 0.001). Simultaneously, decrease in 10 h fat oxidation was less during the low vs high GI diet (-0.033 ± 0.021 vs -0.050 ± 0.017 g/min; p < 0.001), specifically after breakfast (p < 0.001) and lunch (p < 0.001).

conclusionsOur study corroborates that using low GI local foods to construct a 24 h low GI diet, is able to reduce glycaemic response and variability as recorded by continuous glucose monitoring. Our observations also confirm that a low GI diet promotes fat oxidation over carbohydrate oxidation when compared to a high GI diet. These observations provide public health support for the encouragement of healthier nutrition choices by consuming low GI foods.

trial registrationNCT 02631083 (Clinicaltrials.gov).

Indexed as

DietGlycemic IndexLipid MetabolismAdultBlood GlucoseBody Mass IndexCross-Over StudiesDiabetes Mellitus, Type 2Dietary CarbohydratesEnergy MetabolismGlycated HemoglobinHumansInsulinMaleMealsOxidation-ReductionBlood GlucoseDietary CarbohydratesGlycated HemoglobinInsulin24 h dietContinuous glucose monitoringGlycaemic indexGlycaemic responseIndirect calorimetryMixed mealsSubstrate oxidationWhole body calorimeter

Identifiers

PMID28701162
PMCPMC5508658
OpenAlexW2736074622

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.