Multimorbidity patterns and associated factors in a megacity: a cross-sectional study
Autor(a) principal: | |
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Data de Publicação: | 2024 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista de Saúde Pública |
Texto Completo: | https://www.revistas.usp.br/rsp/article/view/227879 |
Resumo: | OBJECTIVE: To identify empirical patterns of multimorbidity and quantify their associations with socioeconomic, behavioral characteristics, and health outcomes in the megacity of São Paulo. METHODS: This was a cross-sectional study conducted through household interviews with residents aged 20 years or older in urban areas (n = 3,184). Latent class analysis was used to identify patterns among the co-existence of 22 health conditions. Age-adjusted prevalence ratios were estimated using Poisson regression. RESULTS: The analysis of latent classes showed 4 patterns of multimorbidity, whereas 58.6% of individuals were classified in the low disease probability group, followed by participants presenting cardiovascular conditions (15.9%), respiratory conditions (12.8%), and rheumatic, musculoskeletal, and emotional conditions (12.8%). Older individuals, with lower schooling and lower household income, presented higher multimorbidity prevalence in cardiovascular, respiratory, rheumatic, musculoskeletal, and emotional conditions patterns compared with the low disease probability pattern. CONCLUSION: The results showed four distinct patterns of multimorbidity in the megacity population, and these patterns are clinically recognizable and theoretically plausible. The identification of trends between patterns would make it feasible to estimate the magnitude of the challenge for the organization of health care policies. |
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Multimorbidity patterns and associated factors in a megacity: a cross-sectional studyMultimorbidity patterns and associated factors in a megacityMultimorbidityComorbidityLatent Class AnalysisOBJECTIVE: To identify empirical patterns of multimorbidity and quantify their associations with socioeconomic, behavioral characteristics, and health outcomes in the megacity of São Paulo. METHODS: This was a cross-sectional study conducted through household interviews with residents aged 20 years or older in urban areas (n = 3,184). Latent class analysis was used to identify patterns among the co-existence of 22 health conditions. Age-adjusted prevalence ratios were estimated using Poisson regression. RESULTS: The analysis of latent classes showed 4 patterns of multimorbidity, whereas 58.6% of individuals were classified in the low disease probability group, followed by participants presenting cardiovascular conditions (15.9%), respiratory conditions (12.8%), and rheumatic, musculoskeletal, and emotional conditions (12.8%). Older individuals, with lower schooling and lower household income, presented higher multimorbidity prevalence in cardiovascular, respiratory, rheumatic, musculoskeletal, and emotional conditions patterns compared with the low disease probability pattern. CONCLUSION: The results showed four distinct patterns of multimorbidity in the megacity population, and these patterns are clinically recognizable and theoretically plausible. The identification of trends between patterns would make it feasible to estimate the magnitude of the challenge for the organization of health care policies.Universidade de São Paulo. Faculdade de Saúde Pública2024-07-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/xmlhttps://www.revistas.usp.br/rsp/article/view/22787910.11606/s1518-8787.2024058006058Revista de Saúde Pública; v. 58 n. 1 (2024); 26Revista de Saúde Pública; Vol. 58 Núm. 1 (2024); 26Revista de Saúde Pública; Vol. 58 No. 1 (2024); 261518-87870034-8910reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/rsp/article/view/227879/206301https://www.revistas.usp.br/rsp/article/view/227879/206302Copyright (c) 2024 Ricardo Goes de Aguiar, Daniela Simões, Shamyr Sulyvan Castro, Moises Goldbaum, Chester Luiz Galvão Cesar, Raquel Lucashttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessAguiar, Ricardo Goes deSimões, DanielaCastro, Shamyr SulyvanGoldbaum, MoisesCesar, Chester Luiz GalvãoLucas, Raquel2025-02-03T19:30:29Zoai:revistas.usp.br:article/227879Revistahttps://www.revistas.usp.br/rsp/indexONGhttps://www.revistas.usp.br/rsp/oairevsp@org.usp.br||revsp1@usp.br1518-87870034-8910opendoar:2025-02-03T19:30:29Revista de Saúde Pública - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study Multimorbidity patterns and associated factors in a megacity |
title |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study |
spellingShingle |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study Aguiar, Ricardo Goes de Multimorbidity Comorbidity Latent Class Analysis |
title_short |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study |
title_full |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study |
title_fullStr |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study |
title_full_unstemmed |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study |
title_sort |
Multimorbidity patterns and associated factors in a megacity: a cross-sectional study |
author |
Aguiar, Ricardo Goes de |
author_facet |
Aguiar, Ricardo Goes de Simões, Daniela Castro, Shamyr Sulyvan Goldbaum, Moises Cesar, Chester Luiz Galvão Lucas, Raquel |
author_role |
author |
author2 |
Simões, Daniela Castro, Shamyr Sulyvan Goldbaum, Moises Cesar, Chester Luiz Galvão Lucas, Raquel |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Aguiar, Ricardo Goes de Simões, Daniela Castro, Shamyr Sulyvan Goldbaum, Moises Cesar, Chester Luiz Galvão Lucas, Raquel |
dc.subject.por.fl_str_mv |
Multimorbidity Comorbidity Latent Class Analysis |
topic |
Multimorbidity Comorbidity Latent Class Analysis |
description |
OBJECTIVE: To identify empirical patterns of multimorbidity and quantify their associations with socioeconomic, behavioral characteristics, and health outcomes in the megacity of São Paulo. METHODS: This was a cross-sectional study conducted through household interviews with residents aged 20 years or older in urban areas (n = 3,184). Latent class analysis was used to identify patterns among the co-existence of 22 health conditions. Age-adjusted prevalence ratios were estimated using Poisson regression. RESULTS: The analysis of latent classes showed 4 patterns of multimorbidity, whereas 58.6% of individuals were classified in the low disease probability group, followed by participants presenting cardiovascular conditions (15.9%), respiratory conditions (12.8%), and rheumatic, musculoskeletal, and emotional conditions (12.8%). Older individuals, with lower schooling and lower household income, presented higher multimorbidity prevalence in cardiovascular, respiratory, rheumatic, musculoskeletal, and emotional conditions patterns compared with the low disease probability pattern. CONCLUSION: The results showed four distinct patterns of multimorbidity in the megacity population, and these patterns are clinically recognizable and theoretically plausible. The identification of trends between patterns would make it feasible to estimate the magnitude of the challenge for the organization of health care policies. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-07-10 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/rsp/article/view/227879 10.11606/s1518-8787.2024058006058 |
url |
https://www.revistas.usp.br/rsp/article/view/227879 |
identifier_str_mv |
10.11606/s1518-8787.2024058006058 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/rsp/article/view/227879/206301 https://www.revistas.usp.br/rsp/article/view/227879/206302 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf text/xml |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Faculdade de Saúde Pública |
publisher.none.fl_str_mv |
Universidade de São Paulo. Faculdade de Saúde Pública |
dc.source.none.fl_str_mv |
Revista de Saúde Pública; v. 58 n. 1 (2024); 26 Revista de Saúde Pública; Vol. 58 Núm. 1 (2024); 26 Revista de Saúde Pública; Vol. 58 No. 1 (2024); 26 1518-8787 0034-8910 reponame:Revista de Saúde Pública instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Revista de Saúde Pública |
collection |
Revista de Saúde Pública |
repository.name.fl_str_mv |
Revista de Saúde Pública - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
revsp@org.usp.br||revsp1@usp.br |
_version_ |
1824325145812008960 |