Predictors of Metabolic Syndrome in the Elderly: A Review

Detalhes bibliográficos
Autor(a) principal: Oliveira,Carolina Cunha de
Data de Publicação: 2017
Outros Autores: Costa,Emanuelle Dias da, Roriz,Anna Karla Carneiro, Ramos,Lilian Barbosa, Gomes Neto,Mansueto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: International Journal of Cardiovascular Sciences (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2359-56472017000400343
Resumo: Abstract The article aimed to critically analyse studies which evaluated the capacity of anthropometric and clinical indicators to predict MetS in the elderly. Bibliographical research was performed using the electronic databasese Medline/PubMed, LILACS e SciELO , references from selected articles and contact with several authors. Twenty one articles involving anthropometric and clinical indicators in the elderly were analysed, using different MS criteria. Fourteen studies report anthropometric indicators, being the waist circumference (WC) and waist-to-height ratio (WHtR), described as the best MS predictors, with the area under the ROC curve (AUC) over 0.70 (p < 0.05). The neck circumference was also described as an alternative indicator but with less discriminatory power. Lipid accumulation product (LAP) was the parameter with the best performance to identify MS, with an AUC over 0.85 and efficiency greater than 70%. The WC, WHtR and LAP indicators were the most sensitive for predicting MS. The use of these parameters may facilitate the early identification of MS, with good accuracy and low cost. In addition, it is important to determine specific cutoff points for the elderly, since obesity alone does not appear to be a strong predictor of MS in the elderly.
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spelling Predictors of Metabolic Syndrome in the Elderly: A ReviewAgedBody weights and MeasuresRisk FactorsAnthropometryObesityMetabolic SyndromeIndicatorsAbstract The article aimed to critically analyse studies which evaluated the capacity of anthropometric and clinical indicators to predict MetS in the elderly. Bibliographical research was performed using the electronic databasese Medline/PubMed, LILACS e SciELO , references from selected articles and contact with several authors. Twenty one articles involving anthropometric and clinical indicators in the elderly were analysed, using different MS criteria. Fourteen studies report anthropometric indicators, being the waist circumference (WC) and waist-to-height ratio (WHtR), described as the best MS predictors, with the area under the ROC curve (AUC) over 0.70 (p < 0.05). The neck circumference was also described as an alternative indicator but with less discriminatory power. Lipid accumulation product (LAP) was the parameter with the best performance to identify MS, with an AUC over 0.85 and efficiency greater than 70%. The WC, WHtR and LAP indicators were the most sensitive for predicting MS. The use of these parameters may facilitate the early identification of MS, with good accuracy and low cost. In addition, it is important to determine specific cutoff points for the elderly, since obesity alone does not appear to be a strong predictor of MS in the elderly.Sociedade Brasileira de Cardiologia2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2359-56472017000400343International Journal of Cardiovascular Sciences v.30 n.4 2017reponame:International Journal of Cardiovascular Sciences (Online)instname:Sociedade Brasileira de Cardiologia (SBC)instacron:SBC10.5935/2359-4802.20170059info:eu-repo/semantics/openAccessOliveira,Carolina Cunha deCosta,Emanuelle Dias daRoriz,Anna Karla CarneiroRamos,Lilian BarbosaGomes Neto,Mansuetoeng2017-07-25T00:00:00Zoai:scielo:S2359-56472017000400343Revistahttp://publicacoes.cardiol.br/portal/ijcshttps://old.scielo.br/oai/scielo-oai.phptailanerodrigues@cardiol.br||revistaijcs@cardiol.br2359-56472359-4802opendoar:2017-07-25T00:00International Journal of Cardiovascular Sciences (Online) - Sociedade Brasileira de Cardiologia (SBC)false
dc.title.none.fl_str_mv Predictors of Metabolic Syndrome in the Elderly: A Review
title Predictors of Metabolic Syndrome in the Elderly: A Review
spellingShingle Predictors of Metabolic Syndrome in the Elderly: A Review
Oliveira,Carolina Cunha de
Aged
Body weights and Measures
Risk Factors
Anthropometry
Obesity
Metabolic Syndrome
Indicators
title_short Predictors of Metabolic Syndrome in the Elderly: A Review
title_full Predictors of Metabolic Syndrome in the Elderly: A Review
title_fullStr Predictors of Metabolic Syndrome in the Elderly: A Review
title_full_unstemmed Predictors of Metabolic Syndrome in the Elderly: A Review
title_sort Predictors of Metabolic Syndrome in the Elderly: A Review
author Oliveira,Carolina Cunha de
author_facet Oliveira,Carolina Cunha de
Costa,Emanuelle Dias da
Roriz,Anna Karla Carneiro
Ramos,Lilian Barbosa
Gomes Neto,Mansueto
author_role author
author2 Costa,Emanuelle Dias da
Roriz,Anna Karla Carneiro
Ramos,Lilian Barbosa
Gomes Neto,Mansueto
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Oliveira,Carolina Cunha de
Costa,Emanuelle Dias da
Roriz,Anna Karla Carneiro
Ramos,Lilian Barbosa
Gomes Neto,Mansueto
dc.subject.por.fl_str_mv Aged
Body weights and Measures
Risk Factors
Anthropometry
Obesity
Metabolic Syndrome
Indicators
topic Aged
Body weights and Measures
Risk Factors
Anthropometry
Obesity
Metabolic Syndrome
Indicators
description Abstract The article aimed to critically analyse studies which evaluated the capacity of anthropometric and clinical indicators to predict MetS in the elderly. Bibliographical research was performed using the electronic databasese Medline/PubMed, LILACS e SciELO , references from selected articles and contact with several authors. Twenty one articles involving anthropometric and clinical indicators in the elderly were analysed, using different MS criteria. Fourteen studies report anthropometric indicators, being the waist circumference (WC) and waist-to-height ratio (WHtR), described as the best MS predictors, with the area under the ROC curve (AUC) over 0.70 (p < 0.05). The neck circumference was also described as an alternative indicator but with less discriminatory power. Lipid accumulation product (LAP) was the parameter with the best performance to identify MS, with an AUC over 0.85 and efficiency greater than 70%. The WC, WHtR and LAP indicators were the most sensitive for predicting MS. The use of these parameters may facilitate the early identification of MS, with good accuracy and low cost. In addition, it is important to determine specific cutoff points for the elderly, since obesity alone does not appear to be a strong predictor of MS in the elderly.
publishDate 2017
dc.date.none.fl_str_mv 2017-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2359-56472017000400343
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2359-56472017000400343
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5935/2359-4802.20170059
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Cardiologia
publisher.none.fl_str_mv Sociedade Brasileira de Cardiologia
dc.source.none.fl_str_mv International Journal of Cardiovascular Sciences v.30 n.4 2017
reponame:International Journal of Cardiovascular Sciences (Online)
instname:Sociedade Brasileira de Cardiologia (SBC)
instacron:SBC
instname_str Sociedade Brasileira de Cardiologia (SBC)
instacron_str SBC
institution SBC
reponame_str International Journal of Cardiovascular Sciences (Online)
collection International Journal of Cardiovascular Sciences (Online)
repository.name.fl_str_mv International Journal of Cardiovascular Sciences (Online) - Sociedade Brasileira de Cardiologia (SBC)
repository.mail.fl_str_mv tailanerodrigues@cardiol.br||revistaijcs@cardiol.br
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