Evidence map›Paper›PMID 33859227›Full record

ArticleScientific reports2021

Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance.

Katharina Lechner, Benjamin Lechner, Alexander Crispin, Peter E H Schwarz, Helene von Bibra

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
5.7field-weighted citation impact, top 3% 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

27 citing papers in PubMed, 46 citations in OpenAlex.

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  2. Muscle Ultrasound Echo Intensity Detects Insulin Resistance Before Changes in HbAJournal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2026
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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

5 authors at 3 institutions in 1 country.

Katharina LechnerKardiologie, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.
Benjamin LechnerDepartment of Internal Medicine IV, Ludwig-Maximilians-Universität München, Munich, Germany.
Alexander CrispinInstitute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.
Peter E H SchwarzCenter for Evidence-Based Healthcare, University Hospital Carl Gustav Carus, TU, Dresden, Germany.
Helene von BibraTechnical University of Munich, Stelznerstr. 7, 81479, Munich, Germany. vonbibra@gmx.de.
Ludwig-Maximilians-Universität München · DETechnical University of Munich · DEDeutsches Diabetes-Zentrum e.V. · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current screening algorithms for type 2 diabetes (T2D) rely on fasting plasma glucose (FPG) and/or HbA1c. This fails to identify a sizeable subgroup of individuals in early stages of metabolic dysregulation who are at high risk for developing diabetes or cardiovascular disease. The Matsuda index, a combination of parameters derived from a fasting and postprandial insulin assay, is an early biomarker for metabolic dysregulation (i.e. insulin resistance/compensatory hyperinsulinemia). The aim of this analysis was to compare four widely available anthropometric and biochemical markers indicative of this condition [waist-to-height ratio (WHtR), hypertriglyceridemic-waist phenotype (HTW), triglycerides-to-HDL-C ratio (TG/HDL-C) and FPG] to the Matsuda index. This cross-sectional analysis included 2231 individuals with normal fasting glucose (NFG, n = 1333), impaired fasting glucose (IFG, n = 599) and T2D (n = 299) from an outpatient diabetes clinic in Germany and thus extended a prior analysis from our group done on the first two subgroups. We analyzed correlations of the Matsuda index with WHtR, HTW, TG/HDL-C and FPG and their predictive accuracies by correlation and logistic regression analyses and receiver operating characteristics. In the entire group and in NFG, IFG and T2D, the best associations were observed between the Matsuda index and the WHtR (r = - 0.458), followed by HTW phenotype (r = - 0.438). As for prediction accuracy, WHtR was superior to HTW, TG/HDL-C and FPG in the entire group (AUC 0.801) and NFG, IFG and T2D. A multivariable risk score for the prediction of insulin resistance was tested and demonstrated an area under the ROC curve of 0.765 for WHtR and its interaction with sex as predictor controlled by age and sex. The predictive power increased to 0.845 when FPG and TG/HDL-C were included. Using as a comparator the Matsuda index, WHtR, compared to HTW, TG/HDL-C and FPG, showed the best predictive value for detecting metabolic dysregulation. We conclude that WHtR, a widely available anthropometric index, could refine phenotypic screening for insulin resistance/hyperinsulinemia. This may ameliorate early identification of individuals who are candidates for appropriate therapeutic interventions aimed at addressing the twin epidemic of metabolic and cardiovascular disease in settings where more extended testing such as insulin assays are not feasible.

Indexed as

Cardiometabolic Risk FactorsWaist-Height RatioAdultAgedAlgorithmsCardiovascular DiseasesCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleGermanyHealth Status IndicatorsHumansInsulin ResistanceMaleMetabolic SyndromeMiddle Aged

Identifiers

PMID33859227
PMCPMC8050044
OpenAlexW3156440939

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.