Diagnosis of metabolic syndrome in nursing professionals: An accuracy study
Metabolic Syndrome (MetS) represents a group of cardiovascular risk factors. This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essentia...
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| creator | Gomes, Érica Velasco Dias Vasconcelos, Rebeca de Souza Coelho, Natália Maria Freitas Almeida, Lorena de Carvalho Silva, Dandara Almeida Reis da Cerqueira, Monique Magnavita Borba da Fonseca Cerqueira, Jeane Magnavita da Fonseca Conceição, Sarah Dos Santos Soares, Johelle de Santana Passos Magalhães, Lucélia Batista Neves Cunha Lua, Iracema Figueredo, Ana Claúdia Morais Godoy Brito, Vitória Cézar Santos Gonçalves Fernandes, Sandra Lúcia Viana, Dayanne de Aguiar Freitas, Ruan Pablo Duarte Requião, Gabriella Moreira Lima, Luiz Alberto da Silva Hayes, Barbara Kraychete Pinheiro, Isabelle Matos Monção, Maurício Mitsuo Souza, Antônio Carlos Dos Santos Cruz, Simone Seixas da Gomes, Antônio Marcos Tosoli Pimentel, Rodrigo Fernandes Weyll Nardes, Barbara Oliveira Lopes, Letícia Costa Bastos, Neiva Sueli Santana Gonçalves D'Oliveira, Júnior, Argemiro Mercês, Magno Conceição das Coelho, Julita Maria Freitas |
| description | Metabolic Syndrome (MetS) represents a group of cardiovascular risk factors. This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essential health information for the diagnostic of MetS. For MetS diagnostic, we used EGIR, NCEP-ATPIII, AACE, IDF, Barbosa et al. (2006), and IDF/AHA/NHLBI (defined as gold standard) definition. Sensitivity, specificity, predictive values, and likelihood ratio were estimated for each diagnostic tool and compared with the gold standard. Kappa statistic was used to determine the agreement between the diagnostic methods. One thousand one hundred and eleven nursing professionals were included in this study. Sensitivity varied from 15% to 95.1%, and specificity varied between 99.5% and 100%. IDF and Barbosa et al. (2006) definitions were more sensitive (95.1% and 92.8%, respectively), and EGIR, NCEP, ATP III, and IDF showed 100% specificity. IDF and Barbosa et al. (2006) use suitable metabolic syndrome identification and confirmation criteria. The highest agreement was found in the definition of the IDF, Barbosa et al. (2006) and the NCEP ATP III. Defining metabolic syndrome with a higher diagnostic accuracy could contribute to the screening and the early identification of nursing professionals with cardiovascular disease risk factors, which provide opportunities for appropriate prevention and treatment. |
| doi_str_mv | 10.1371/journal.pone.0295985 |
| format | Article |
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This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essential health information for the diagnostic of MetS. For MetS diagnostic, we used EGIR, NCEP-ATPIII, AACE, IDF, Barbosa et al. (2006), and IDF/AHA/NHLBI (defined as gold standard) definition. Sensitivity, specificity, predictive values, and likelihood ratio were estimated for each diagnostic tool and compared with the gold standard. Kappa statistic was used to determine the agreement between the diagnostic methods. One thousand one hundred and eleven nursing professionals were included in this study. Sensitivity varied from 15% to 95.1%, and specificity varied between 99.5% and 100%. IDF and Barbosa et al. (2006) definitions were more sensitive (95.1% and 92.8%, respectively), and EGIR, NCEP, ATP III, and IDF showed 100% specificity. IDF and Barbosa et al. (2006) use suitable metabolic syndrome identification and confirmation criteria. The highest agreement was found in the definition of the IDF, Barbosa et al. (2006) and the NCEP ATP III. Defining metabolic syndrome with a higher diagnostic accuracy could contribute to the screening and the early identification of nursing professionals with cardiovascular disease risk factors, which provide opportunities for appropriate prevention and treatment.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0295985</identifier><identifier>PMID: 38857224</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Accuracy ; Adult ; Biology and Life Sciences ; Blood pressure ; Brazil - epidemiology ; Cardiovascular diseases ; Comparative analysis ; Cross-Sectional Studies ; Data collection ; Diabetes ; Diagnosis ; Female ; Health risks ; Humans ; Hypertension ; Likelihood ratio ; Liver diseases ; Male ; Medical care ; Medical diagnosis ; Medicine and Health Sciences ; Metabolic disorders ; Metabolic syndrome ; Metabolic Syndrome - diagnosis ; Metabolic Syndrome - epidemiology ; Middle Aged ; Nurses ; Nursing ; Obesity ; Ovaries ; People and places ; Pilot projects ; Population ; Professionals ; Quality management ; Risk Factors ; Sensitivity ; Sensitivity and Specificity ; Type 2 diabetes ; Womens health ; Working conditions</subject><ispartof>PloS one, 2024-06, Vol.19 (6), p.e0295985-e0295985</ispartof><rights>Copyright: © 2024 Gomes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Gomes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Gomes et al 2024 Gomes et al</rights><rights>2024 Gomes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c576t-fa1867e6b82ac67978c96076fcdfeaa557ac9c7ca6bade14179bc2539c6d1c9d3</cites><orcidid>0000-0003-0643-4355 ; 0000-0001-9881-7016 ; 0000-0003-1674-3952 ; 0009-0005-1521-3644</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11164393/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11164393/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38857224$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Tsima, Billy Morara</contributor><creatorcontrib>Gomes, Érica Velasco Dias</creatorcontrib><creatorcontrib>Vasconcelos, Rebeca de Souza</creatorcontrib><creatorcontrib>Coelho, Natália Maria Freitas</creatorcontrib><creatorcontrib>Almeida, Lorena de Carvalho</creatorcontrib><creatorcontrib>Silva, Dandara Almeida Reis da</creatorcontrib><creatorcontrib>Cerqueira, Monique Magnavita Borba da Fonseca</creatorcontrib><creatorcontrib>Cerqueira, Jeane Magnavita da Fonseca</creatorcontrib><creatorcontrib>Conceição, Sarah Dos Santos</creatorcontrib><creatorcontrib>Soares, Johelle de Santana Passos</creatorcontrib><creatorcontrib>Magalhães, Lucélia Batista Neves Cunha</creatorcontrib><creatorcontrib>Lua, Iracema</creatorcontrib><creatorcontrib>Figueredo, Ana Claúdia Morais Godoy</creatorcontrib><creatorcontrib>Brito, Vitória Cézar Santos Gonçalves</creatorcontrib><creatorcontrib>Fernandes, Sandra Lúcia</creatorcontrib><creatorcontrib>Viana, Dayanne de Aguiar</creatorcontrib><creatorcontrib>Freitas, Ruan Pablo Duarte</creatorcontrib><creatorcontrib>Requião, Gabriella Moreira</creatorcontrib><creatorcontrib>Lima, Luiz Alberto da Silva</creatorcontrib><creatorcontrib>Hayes, Barbara Kraychete</creatorcontrib><creatorcontrib>Pinheiro, Isabelle Matos</creatorcontrib><creatorcontrib>Monção, Maurício Mitsuo</creatorcontrib><creatorcontrib>Souza, Antônio Carlos Dos Santos</creatorcontrib><creatorcontrib>Cruz, Simone Seixas da</creatorcontrib><creatorcontrib>Gomes, Antônio Marcos Tosoli</creatorcontrib><creatorcontrib>Pimentel, Rodrigo Fernandes Weyll</creatorcontrib><creatorcontrib>Nardes, Barbara Oliveira</creatorcontrib><creatorcontrib>Lopes, Letícia Costa</creatorcontrib><creatorcontrib>Bastos, Neiva Sueli Santana Gonçalves</creatorcontrib><creatorcontrib>D'Oliveira, Júnior, Argemiro</creatorcontrib><creatorcontrib>Mercês, Magno Conceição das</creatorcontrib><creatorcontrib>Coelho, Julita Maria Freitas</creatorcontrib><title>Diagnosis of metabolic syndrome in nursing professionals: An accuracy study</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Metabolic Syndrome (MetS) represents a group of cardiovascular risk factors. This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essential health information for the diagnostic of MetS. For MetS diagnostic, we used EGIR, NCEP-ATPIII, AACE, IDF, Barbosa et al. (2006), and IDF/AHA/NHLBI (defined as gold standard) definition. Sensitivity, specificity, predictive values, and likelihood ratio were estimated for each diagnostic tool and compared with the gold standard. Kappa statistic was used to determine the agreement between the diagnostic methods. One thousand one hundred and eleven nursing professionals were included in this study. Sensitivity varied from 15% to 95.1%, and specificity varied between 99.5% and 100%. IDF and Barbosa et al. (2006) definitions were more sensitive (95.1% and 92.8%, respectively), and EGIR, NCEP, ATP III, and IDF showed 100% specificity. IDF and Barbosa et al. (2006) use suitable metabolic syndrome identification and confirmation criteria. The highest agreement was found in the definition of the IDF, Barbosa et al. (2006) and the NCEP ATP III. Defining metabolic syndrome with a higher diagnostic accuracy could contribute to the screening and the early identification of nursing professionals with cardiovascular disease risk factors, which provide opportunities for appropriate prevention and treatment.</description><subject>Accuracy</subject><subject>Adult</subject><subject>Biology and Life Sciences</subject><subject>Blood pressure</subject><subject>Brazil - epidemiology</subject><subject>Cardiovascular diseases</subject><subject>Comparative analysis</subject><subject>Cross-Sectional Studies</subject><subject>Data collection</subject><subject>Diabetes</subject><subject>Diagnosis</subject><subject>Female</subject><subject>Health risks</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Likelihood ratio</subject><subject>Liver diseases</subject><subject>Male</subject><subject>Medical care</subject><subject>Medical diagnosis</subject><subject>Medicine and Health Sciences</subject><subject>Metabolic 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of metabolic syndrome in nursing professionals: An accuracy study</title><author>Gomes, Érica Velasco Dias ; Vasconcelos, Rebeca de Souza ; Coelho, Natália Maria Freitas ; Almeida, Lorena de Carvalho ; Silva, Dandara Almeida Reis da ; Cerqueira, Monique Magnavita Borba da Fonseca ; Cerqueira, Jeane Magnavita da Fonseca ; Conceição, Sarah Dos Santos ; Soares, Johelle de Santana Passos ; Magalhães, Lucélia Batista Neves Cunha ; Lua, Iracema ; Figueredo, Ana Claúdia Morais Godoy ; Brito, Vitória Cézar Santos Gonçalves ; Fernandes, Sandra Lúcia ; Viana, Dayanne de Aguiar ; Freitas, Ruan Pablo Duarte ; Requião, Gabriella Moreira ; Lima, Luiz Alberto da Silva ; Hayes, Barbara Kraychete ; Pinheiro, Isabelle Matos ; Monção, Maurício Mitsuo ; Souza, Antônio Carlos Dos Santos ; Cruz, Simone Seixas da ; Gomes, Antônio Marcos Tosoli ; Pimentel, Rodrigo Fernandes Weyll ; Nardes, Barbara Oliveira ; Lopes, Letícia Costa ; Bastos, Neiva Sueli Santana Gonçalves ; D'Oliveira, Júnior, Argemiro ; Mercês, 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syndrome</topic><topic>Metabolic Syndrome - diagnosis</topic><topic>Metabolic Syndrome - epidemiology</topic><topic>Middle Aged</topic><topic>Nurses</topic><topic>Nursing</topic><topic>Obesity</topic><topic>Ovaries</topic><topic>People and places</topic><topic>Pilot projects</topic><topic>Population</topic><topic>Professionals</topic><topic>Quality management</topic><topic>Risk Factors</topic><topic>Sensitivity</topic><topic>Sensitivity and Specificity</topic><topic>Type 2 diabetes</topic><topic>Womens health</topic><topic>Working conditions</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gomes, Érica Velasco Dias</creatorcontrib><creatorcontrib>Vasconcelos, Rebeca de Souza</creatorcontrib><creatorcontrib>Coelho, Natália Maria Freitas</creatorcontrib><creatorcontrib>Almeida, Lorena de Carvalho</creatorcontrib><creatorcontrib>Silva, Dandara Almeida Reis da</creatorcontrib><creatorcontrib>Cerqueira, Monique Magnavita Borba da 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Santos</creatorcontrib><creatorcontrib>Cruz, Simone Seixas da</creatorcontrib><creatorcontrib>Gomes, Antônio Marcos Tosoli</creatorcontrib><creatorcontrib>Pimentel, Rodrigo Fernandes Weyll</creatorcontrib><creatorcontrib>Nardes, Barbara Oliveira</creatorcontrib><creatorcontrib>Lopes, Letícia Costa</creatorcontrib><creatorcontrib>Bastos, Neiva Sueli Santana Gonçalves</creatorcontrib><creatorcontrib>D'Oliveira, Júnior, Argemiro</creatorcontrib><creatorcontrib>Mercês, Magno Conceição das</creatorcontrib><creatorcontrib>Coelho, Julita Maria Freitas</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints in Context (Gale)</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior 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Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community 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Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gomes, Érica Velasco Dias</au><au>Vasconcelos, Rebeca de Souza</au><au>Coelho, Natália Maria Freitas</au><au>Almeida, Lorena de Carvalho</au><au>Silva, Dandara Almeida Reis da</au><au>Cerqueira, Monique Magnavita Borba da Fonseca</au><au>Cerqueira, Jeane Magnavita da Fonseca</au><au>Conceição, Sarah Dos Santos</au><au>Soares, Johelle de Santana Passos</au><au>Magalhães, Lucélia Batista Neves Cunha</au><au>Lua, Iracema</au><au>Figueredo, Ana Claúdia Morais Godoy</au><au>Brito, Vitória Cézar Santos Gonçalves</au><au>Fernandes, Sandra Lúcia</au><au>Viana, Dayanne de Aguiar</au><au>Freitas, Ruan Pablo Duarte</au><au>Requião, Gabriella Moreira</au><au>Lima, Luiz Alberto da Silva</au><au>Hayes, Barbara Kraychete</au><au>Pinheiro, Isabelle Matos</au><au>Monção, Maurício Mitsuo</au><au>Souza, Antônio Carlos Dos Santos</au><au>Cruz, Simone Seixas da</au><au>Gomes, Antônio Marcos Tosoli</au><au>Pimentel, Rodrigo Fernandes Weyll</au><au>Nardes, Barbara Oliveira</au><au>Lopes, Letícia Costa</au><au>Bastos, Neiva Sueli Santana Gonçalves</au><au>D'Oliveira, Júnior, Argemiro</au><au>Mercês, Magno Conceição das</au><au>Coelho, Julita Maria Freitas</au><au>Tsima, Billy Morara</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diagnosis of metabolic syndrome in nursing professionals: An accuracy study</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-06-10</date><risdate>2024</risdate><volume>19</volume><issue>6</issue><spage>e0295985</spage><epage>e0295985</epage><pages>e0295985-e0295985</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Metabolic Syndrome (MetS) represents a group of cardiovascular risk factors. This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essential health information for the diagnostic of MetS. For MetS diagnostic, we used EGIR, NCEP-ATPIII, AACE, IDF, Barbosa et al. (2006), and IDF/AHA/NHLBI (defined as gold standard) definition. Sensitivity, specificity, predictive values, and likelihood ratio were estimated for each diagnostic tool and compared with the gold standard. Kappa statistic was used to determine the agreement between the diagnostic methods. One thousand one hundred and eleven nursing professionals were included in this study. Sensitivity varied from 15% to 95.1%, and specificity varied between 99.5% and 100%. IDF and Barbosa et al. (2006) definitions were more sensitive (95.1% and 92.8%, respectively), and EGIR, NCEP, ATP III, and IDF showed 100% specificity. IDF and Barbosa et al. (2006) use suitable metabolic syndrome identification and confirmation criteria. The highest agreement was found in the definition of the IDF, Barbosa et al. (2006) and the NCEP ATP III. Defining metabolic syndrome with a higher diagnostic accuracy could contribute to the screening and the early identification of nursing professionals with cardiovascular disease risk factors, which provide opportunities for appropriate prevention and treatment.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>38857224</pmid><doi>10.1371/journal.pone.0295985</doi><tpages>e0295985</tpages><orcidid>https://orcid.org/0000-0003-0643-4355</orcidid><orcidid>https://orcid.org/0000-0001-9881-7016</orcidid><orcidid>https://orcid.org/0000-0003-1674-3952</orcidid><orcidid>https://orcid.org/0009-0005-1521-3644</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2024-06, Vol.19 (6), p.e0295985-e0295985 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_3069265260 |
| source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Accuracy Adult Biology and Life Sciences Blood pressure Brazil - epidemiology Cardiovascular diseases Comparative analysis Cross-Sectional Studies Data collection Diabetes Diagnosis Female Health risks Humans Hypertension Likelihood ratio Liver diseases Male Medical care Medical diagnosis Medicine and Health Sciences Metabolic disorders Metabolic syndrome Metabolic Syndrome - diagnosis Metabolic Syndrome - epidemiology Middle Aged Nurses Nursing Obesity Ovaries People and places Pilot projects Population Professionals Quality management Risk Factors Sensitivity Sensitivity and Specificity Type 2 diabetes Womens health Working conditions |
| title | Diagnosis of metabolic syndrome in nursing professionals: An accuracy study |
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