Evidence map›Paper›PMID 40781672›Full record

ArticleCardiovascular diabetology2025

Cardiometabolic risk stratification in pediatric obesity: evaluating the clinical utility of fasting insulin and BMI-SDS.

Rasmus Stenlid, Sami El Amrani, Sara Y Cerenius, Banu K Aydin, Hannes Manell, Katharina Mörwald, Julia Lischka, Julian Gomahr, Thomas Pixner, Iris Ciba and 4 more

Erratum issuedAbstract readMulticenter Study
In one paragraph

Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Rasmus StenlidDepartment of Medical Cell Biology, Uppsala University, Uppsala, Sweden.
Sami El AmraniDepartment of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
Sara Y CereniusDepartment of Medical Cell Biology, Uppsala University, Uppsala, Sweden.
Banu K AydinDepartment of Medical Cell Biology, Uppsala University, Uppsala, Sweden.
Hannes ManellDepartment of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
Katharina MörwaldDepartment of Pediatrics, Paracelsus Medical University, Salzburg, Austria.
Julia LischkaDepartment of Pediatrics, Paracelsus Medical University, Salzburg, Austria.
Julian GomahrDepartment of Pediatrics, Paracelsus Medical University, Salzburg, Austria.
Thomas PixnerObesity Research Unit, Paracelsus Medical University, Salzburg, Austria.
Iris CibaDepartment of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
Stefan K JamesUppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.
Anders ForslundDepartment of Medical Cell Biology, Uppsala University, Uppsala, Sweden.
Daniel WeghuberDepartment of Pediatrics, Paracelsus Medical University, Salzburg, Austria. d.weghuber@salk.at.
Peter BergstenDepartment of Medical Cell Biology, Uppsala University, Uppsala, Sweden.

Funding

Family Ernfors Foundation 160504Seventh Framework Programme 279153Sweden's Innovation Agency Vinnova 2020-02417Swedish Diabetes Association DIA 2016-146Swedish Diabetes Association DIA2023-781Swedish Foundation for Strategic Research CMP22-0014Swedish Research Council 2016-01040Swedish Research Council 2019-01456Uppsala-Örebro Regional Research Council RFR 158161, RFR 233041, RFR 309901
6 · The paper itself

Abstract

backgroundPatients with obesity during childhood have an increased risk of fatal and non-fatal cardiovascular events during adulthood. The severity of obesity is commonly determined by BMI. However, children with relatively low BMI may have high cardiometabolic risk. Indeed, BMI-based obesity classifications might miss children at high cardiometabolic risk. Insulin has been suggested as a marker of cardiometabolic risk. In this study, we therefore estimated and compared cardiometabolic risk using either the BMI standard deviation score (BMI-SDS) or fasting insulin in an international cohort of children and adolescents with obesity and lean controls.

methodsStudy participants (712 with obesity and 99 lean controls), aged 3 to 18 years, were categorized according to their BMI-SDS as lean or obesity class I, II, or III, or by their fasting insulin quartiles as quartile 1, 2, 3, or 4 with the lean subjects in a separate control group. Prevalence of cardiometabolic risk factors was assessed in each group. Sensitivity and specificity analyses for cardiometabolic risk were conducted for both BMI-SDS and fasting insulin. Multiple regression, logistic regression, and receiver operating characteristic (ROC) analyses were performed between fasting insulin, BMI-SDS and cardiometabolic risk factors.

resultsAn elevated prevalence of the cardiometabolic risk factors dyslipidemia, dysglycemia and hypertension was observed in both increasing BMI-SDS classes and increasing fasting insulin quartiles. Fasting insulin demonstrated higher areas under the curve (AUC) for detecting dyslipidemia, dysglycemia, and the combination of dyslipidemia, dysglycemia, and hypertension, compared to BMI-SDS. BMI-SDS demonstrated a higher AUC for detecting hypertension compared to fasting insulin. The same patterns were seen for the logistic regression. However, fasting insulin had an overall stronger association with the cardiometabolic risk factors studied compared to BMI-SDS.

conclusionsIn children and adolescents with obesity, fasting insulin provides complementary information to BMI-SDS in identifying those with elevated cardiometabolic risk factors. While neither marker alone offers strong predictive accuracy, incorporating fasting insulin into clinical assessment may help prioritize individuals who require more detailed evaluation. An elevated fasting insulin value may warrant further investigation among children and adolescents with obesity, independent of obesity class based on BMI-SDS.

Indexed as

Body Mass IndexCardiovascular DiseasesFastingInsulinPediatric ObesityAdolescentAge FactorsBiomarkersBlood GlucoseCardiometabolic Risk FactorsCase-Control StudiesChildChild, PreschoolDyslipidemiasFemaleHumansBiomarkersBlood GlucoseInsulinBMI-SDSCardiometabolic riskCardiovascular diseaseCardiovascular risk factorsDysglycemiaDyslipidemiaHypertensionInsulinObesityPediatric obesity

Identifiers

PMID40781672
PMCPMC12335099

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.