Evidence map›Paper›PMID 39557762›Full record

ArticleAging clinical and experimental research2024

Can simple measures from clinical practice serve as a proxy for sarcopenic obesity and identify mortality risk?

Valdete Regina Guandalini, Patrícia Silva Tofani, Sara Souza Lima, Letícia Coelho Silveira, Natália Cochar-Soares, Thais Barros Pereira da Silva, Thales Batista de Souza, Mariane Marques Luiz, Paula Camila Ramírez, Roberta de Oliveira Máximo and 3 more

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In one paragraph

Article in Aging clinical and experimental research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Valdete Regina GuandaliniNutrition and Health Postgraduate Program, Federal University of Vitoria, Vitoria, Brazil.
Patrícia Silva TofaniGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Sara Souza LimaGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Letícia Coelho SilveiraPhysical Therapy Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Natália Cochar-SoaresGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Thais Barros Pereira da SilvaGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Thales Batista de SouzaGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Mariane Marques LuizGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Paula Camila RamírezEscuela de Fisioterapia, Universidad Industrial de Santander, Bucaramanga, Colombia.
Roberta de Oliveira MáximoGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil.
Andrew SteptoeDepartment of Epidemiology and Public Health, University College London, London, UK.
Cesar de OliveiraDepartment of Epidemiology and Public Health, University College London, London, UK.
Tiago da Silva AlexandreGerontology Postgraduate Program, Federal University of Sao Carlos, Sao Carlos, Brazil. tiagoalexandre@ufscar.br.

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88887.570076/2020-00Fundação de Amparo à Pesquisa do Estado de São Paulo 18/13917-3NIA NIH HHS R01 AG017644NIA NIH HHS R01AG017644
6 · The paper itself

Abstract

backgroundSarcopenic obesity is a condition where loss of muscle mass occurs alongside fat gain, and it is considered a risk factor for mortality. However, the use of various definitions for this condition has led to conflicting results.

aimTo investigate whether the coexistence of low muscle mass and abdominal obesity, defined using two simple measures employed in clinical practice, is a risk factor for mortality in individuals aged 50 or older.

methodsA longitudinal study with a 14-year follow-up was conducted involving 5,440 participants of the English Longitudinal Study of Ageing. Abdominal obesity and low muscle mass were respectively defined based on high waist circumference and low skeletal muscle mass index (SMMI) determined by an equation. The sample was divided into four groups: non-low muscle mass/non-abdominal obesity (NLMM/NAO), non-low muscle mass/abdominal obesity (NLMM/AO), low muscle mass/non-abdominal obesity (LMM/NAO), and low muscle mass/abdominal obesity (LMM/AO). Cox regression models were used to estimate the mortality risk as a function of muscle mass and abdominal obesity status.

resultsLMM/AO increased the risk of death by 83% (HR:1.83; 95%CI: 1.35-2.66) compared to those in the NLMM/NAO group. AO alone was not associated with a greater risk of mortality (HR:1.09; 95%CI: 0.93-1.27), whereas LMM alone increased the risk by 40% (HR:1.40; 95%CI:1.18-1.66).

conclusionsIdentifying LMM/AO in individuals aged 50 or older can be crucial for predicting the risk of mortality. Simple and easily applicable measures can serve as a proxy for sarcopenic obesity and aid in implementing the necessary interventions.

Indexed as

Obesity, AbdominalSarcopeniaAgedAged, 80 and overFemaleHumansLongitudinal StudiesMaleMiddle AgedMuscle, SkeletalObesityRisk FactorsWaist CircumferenceMortalityMuscle massOlder adultsSarcopeniaVisceral obesity

Identifiers

PMID39557762
PMCPMC11573834

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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.