Evidence map›Paper›PMID 39635953›Full record

ArticleObesity (Silver Spring, Md.)2025

Associations of body size and morphology with cardiometabolic health in children: the contribution of genetic factors.

Karri Silventoinen, José Maia, Reijo Sund, Élvio R Gouveia, António Antunes, Gonçalo Marques, Martine Thomis, Aline Jelenkovic, Jaakko Kaprio, Duarte Freitas

Abstract readTwin Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Obesity (Silver Spring, Md.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Karri SilventoinenHelsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland.ORCID https://orcid.org/0000-0003-1759-3079
José MaiaCentre of Research, Education, Innovation, and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, Porto, Portugal.
Reijo SundInstitute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.
Élvio R GouveiaDepartment of Physical Education and Sport, University of Madeira, Funchal, Portugal.
António AntunesDepartment of Physical Education and Sport, University of Madeira, Funchal, Portugal.
Gonçalo MarquesDepartment of Physical Education and Sport, University of Madeira, Funchal, Portugal.
Martine ThomisPhysical Activity, Sports & Health Research Group, Department of Movement Sciences, Faculty of Movement and Rehabilitation Sciences, KU Leuven, Leuven, Belgium.
Aline JelenkovicDepartment of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Bilbao, Spain.
Jaakko KaprioInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
Duarte FreitasCentre of Research, Education, Innovation, and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, Porto, Portugal.

Funding

Basque Government IT1693-22European Union's Horizon Europe Research and Innovation programme 101080117Portuguese National Funding Agency for Science, Research and Technology POCI/DES/56834/2004Research Council of Finland 352792
6 · The paper itself

Abstract

objectiveWe analyzed how anthropometric measures predict cardiometabolic health and how genetic and environmental factors contribute to these associations.

methodsData on 8 indicators of cardiometabolic health, 21 anthropometric measures, and 11 anthropometric indices were available for 216 twin pairs of individuals age 3 to 18 years living in the Autonomous Region of Madeira, Portugal (51% girls). Genetic twin modeling was used to estimate genetic and environmental correlations between the cardiometabolic and anthropometric indicators.

resultsAnthropometric indicators were positively associated with blood pressure and triglycerides and inversely associated with high-density lipoprotein cholesterol. The associations with glucose, low-density lipoprotein cholesterol, total cholesterol, and heart rate were close to zero. BMI and waist circumference showed similar or slightly higher absolute correlations with cardiometabolic health indicators compared with other anthropometric indices. Additive genetic and unique environmental correlations were at the same level as trait correlations.

conclusionsBMI and waist circumference provide information on cardiometabolic health that is not less accurate than that provided by more comprehensive anthropometric indices. These associations reflect causal associations between obesity and cardiometabolic disorders rather than only shared genetic associations. Measuring obesity is important for monitoring cardiometabolic risks and can be accomplished using simple indicators at the population level.

Indexed as

Blood PressureBody Mass IndexBody SizeCardiovascular DiseasesTriglyceridesWaist CircumferenceAdolescentAnthropometryBlood GlucoseCardiometabolic Risk FactorsChildChild, PreschoolCholesterol, HDLCholesterol, LDLFemaleHumansBlood GlucoseCholesterol, HDLCholesterol, LDLTriglycerides

Identifiers

PMID39635953
PMCPMC11664301

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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.