Prevalence of sarcopenic obesity in brazilian elderly people: a systematic review with methanalysis
Notice bibliographique
Résumé
The interest in the study of aging has been growing due to the increase in the number of elderly and also because they are independent. During the aging process, there are several changes, including those related to body composition, which may cause an increase in adipose and visceral tissue leading to the onset of obesity and may also muscle mass reduction and strength, contributing to the development of sarcopenia. The simultaneous occurrence of sarcopenia and obesity in the elderly, the condition called sarcopenic obesity may develop which can be associated with health problems and decreased quality of life. The present study aimed to determine the prevalence of sarcopenic obesity in Brazilian elderly. This is a systematic review with meta-analysis. The databases PubMed, LILACS, Scopus, Scielo were consulted. As inclusion criteria we selected articles that investigated sarcopenic obesity, published in Portuguese, English and Spanish from 2010, involving Brazilian elderly aged 60 years and over of both sexes. Dissertations, theses, experimental animal studies, in vitro studies, recommendations, guidelines, reviews, protocols, letters, editorials, case reports, case series and duplicates were excluded. We used the descriptors, sarcopenic obesity, elderly, Brazilians and Brazil and their correlates in English and Spanish. In order to evaluate the quality of the studies, the Newcastle Ottawa Scale was used. Statistical analysis was performed using R Studio 3.6.0 software, heterogeneity through I² statistics and presented in forest plot graph. The total of 12 studies were included in this study. The prevalence of Brazilian elderly with sarcopenic obesity was 15% (95% CI: 10-23%), with the highest prevalence found in the Midwest. A high heterogeneity was found in the general prevalence analyzes and subgroups (regions and criteria and diagnostic methods). A sensitivity analysis was performed omitting the extreme prevalence values found in the included studies, where a 3% reduction in the overall prevalence of sarcopenic obesity was observed. In the Midwest regions and in the criteria and diagnostic methods there was also a reduction in their prevalence and heterogeneity. In methods that used an equation for diagnosis of sarcopenic obesity, heterogeneity reached 0%, indicating a low heterogeneity. It is concluded that a 15% prevalence of sarcopenic obesity was found in the Brazilian elderly. According to this study, it was possible to present important information on the conceptualization, epidemiology and how sarcopenic obesity can be diagnosed in the elderly. The criteria and methods used to diagnose sarcopenic obesity are different among studies regarding assessment, cutoff points and definitions, and may lead to different prevalences of sarcopence obesity, thus making it difficult to manage preventive measures of this condition, especially in the elderly population thus can interfere with the quality of life of this population.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,011 |
| Bibliométrie | 0,014 | 0,018 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».