Sarcopenic obesity and health outcomes: An umbrella review of systematic reviews with meta‐analysis

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Many studies support the idea that sarcopenic obesity (SO) could be considered a potential risk factor for negative health outcomes. These results have been inconsistent, and no umbrella reviews exist regarding this topic. Several databases until November 2023 were searched for systematic reviews with meta‐analysis of observational studies (cross‐sectional, case–control and prospective). For each association, random‐effects summary effect sizes with correspondent 95% confidence intervals (CIs) were evaluated using the GRADE tool. Among the 213 papers initially screened, nine systematic reviews with meta‐analysis were included, for a total of 384 710 participants. In cross‐sectional and case–control studies, 30 different outcomes were analysed, and 18 were statistically significant. In any population addressed in cross‐sectional and case–control studies, compared with non‐SO, SO increased the prevalence of cognitive impairment ( k = 3; odds ratio [OR] = 3.46; 95% CI: 2.24–5.32; high certainty of evidence), coronary artery disease ( k = 2; OR = 2.48; 95% CI: 1.85–3.31) and dyslipidaemia ( k = 3; OR = 2.50; 95% CI: 1.51–4.15). When compared with sarcopenia or obesity, the results were conflicting. In prospective studies, the association between SO—compared with non‐SO—and other negative outcomes was supported by low/very low certainty of evidence and limited to a few conditions. Besides, no comparison with sarcopenia or obesity was provided. Finally, only a few studies have considered muscle function/physical performance in the diagnostic workup. SO could be considered a risk factor only for a few conditions, with the literature mainly based on cross‐sectional and case–control studies. Future studies with clear definitions of SO are needed for quantifying the importance of SO—particularly when compared with the presence of only sarcopenia or obesity—and the weight of muscle function/physical performance in its definition.

Related collections

Most cited references 34

Record: found
Abstract: found
Article: not found

Quantifying heterogeneity in a meta-analysis.

Julian P T Higgins, Simon G Thompson (2002)

The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.

0 comments Cited 6905 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Rayyan—a web and mobile app for systematic reviews

Mourad Ouzzani, Hossam Hammady, Zbys Fedorowicz … (2017)

Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.

0 comments Cited 5899 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

GRADE: an emerging consensus on rating quality of evidence and strength of recommendations.

Gordon H Guyatt, Andrew D Oxman, Gunn E Vist … (2008)

0 comments Cited 4637 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Emanuele Cereda:

ORCID: https://orcid.org/0000-0002-0747-1951

e.cereda@smatteo.pv.it

Journal

Journal ID (nlm-ta): J Cachexia Sarcopenia Muscle

Journal ID (iso-abbrev): J Cachexia Sarcopenia Muscle

Journal ID (doi): 10.1007/13539.2190-6009

Journal ID (publisher-id): JCSM

Title: Journal of Cachexia, Sarcopenia and Muscle

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Print): 2190-5991

ISSN (Electronic): 2190-6009

Publication date (Electronic): 19 June 2024

Publication date Collection: August 2024

Volume: 15

Issue: 4 ( doiID: 10.1002/jcsm.v15.4 )

Pages: 1264-1274

Affiliations

[ ¹ ] Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties University of Palermo Palermo Italy

[ ² ] Dipartimento di Scienze per la Qualità della Vita‐QUVI Università di Bologna Rimini Italy

[ ³ ] Faculty of Medicine and Surgery “Kore” University of Enna Enna Italy

[ ⁴ ] Geriatric Clinic Maggiore Hospital of Trieste, Azienda Sanitaria Universitaria Integrata Giuliano Isontina Trieste Italy

[ ⁵ ] Department of Medical, Surgical and Health Sciences University of Trieste Trieste Italy

[ ⁶ ] Clinical Nutrition and Dietetics Unit Fondazione IRCCS Policlinico San Matteo Pavia Italy

Author notes

[*] [* ]Correspondence to: Emanuele Cereda, Clinical Nutrition and Dietetics Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. Email: e.cereda@ 123456smatteo.pv.it

Author information

Emanuele Cereda https://orcid.org/0000-0002-0747-1951

Article

Publisher ID: JCSM13502 Other ID: JCSM-D-23-01088

DOI: 10.1002/jcsm.13502

PMC ID: 11294015

PubMed ID: 38897937

SO-VID: 77ca0197-1bf3-40d5-873b-4cc255c2d77c

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

History

Date revision received : 03 April 2024

Date received : 12 December 2023

Date accepted : 16 April 2024

Page count

Figures: 1, Tables: 4, Pages: 11, Words: 3604

Custom metadata

source-schema-version-number 2.0

cover-date August 2024

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.6 mode:remove_FC converted:01.08.2024

ScienceOpen disciplines: Orthopedics

Keywords: meta‐analysis,obesity,sarcopenia,sarcopenic obesity,umbrella review

Data availability:

ScienceOpen disciplines: Orthopedics

Keywords: meta‐analysis, obesity, sarcopenia, sarcopenic obesity, umbrella review

Comments

Comment on this article

scite_

Smart Citations

Citing PublicationsSupportingMentioningContrasting

View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.