Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista da Sociedade Brasileira de Medicina Tropical |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822018000500638 |
Resumo: | Abstract INTRODUCTION: This study aimed to analyze social factors involved in the spatial distribution and under-reporting of tuberculosis (TB) in the city of Vitória, Espírito Santo State, Brazil. METHODS: This was an ecological study of the reported cases of TB between 2009 and 2011, according to census tracts. The outcome was TB incidence for the study period and the variables of exposure were proportions of literacy, inhabitants with an income of up to half the minimum monthly wage (MMW), and inhabitants associated with sewer mains or with access to safe drinking water. We used a zero-inflated process, zero-inflated negative binomial regression (ZINB), and selected an explanatory model based on the Akaike Information Criterion (AIC). RESULTS: A total of 588 cases of tuberculosis were reported in Vitória during the study period, distributed among 223 census tracts (38.6%), with 354 (61.4%) tracts presenting zero cases. In the ZINB model, the mean value of p i was 0.93, indicating that there is a 93% chance that an observed false zero could be due to sub-notification. CONCLUSIONS: It is important to prioritize areas exhibiting determinants that influence the occurrence of TB in the municipality of Vitória. The zero-inflated model can be useful to the public health sector since it identifies the percentage of false zeros, generating an estimate of the real epidemiological condition of TB in Vitória. |
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Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern BrazilTuberculosisEpidemiologySocial determinants of healthSpatial analysisStatistical modelNegative binomial distributionAbstract INTRODUCTION: This study aimed to analyze social factors involved in the spatial distribution and under-reporting of tuberculosis (TB) in the city of Vitória, Espírito Santo State, Brazil. METHODS: This was an ecological study of the reported cases of TB between 2009 and 2011, according to census tracts. The outcome was TB incidence for the study period and the variables of exposure were proportions of literacy, inhabitants with an income of up to half the minimum monthly wage (MMW), and inhabitants associated with sewer mains or with access to safe drinking water. We used a zero-inflated process, zero-inflated negative binomial regression (ZINB), and selected an explanatory model based on the Akaike Information Criterion (AIC). RESULTS: A total of 588 cases of tuberculosis were reported in Vitória during the study period, distributed among 223 census tracts (38.6%), with 354 (61.4%) tracts presenting zero cases. In the ZINB model, the mean value of p i was 0.93, indicating that there is a 93% chance that an observed false zero could be due to sub-notification. CONCLUSIONS: It is important to prioritize areas exhibiting determinants that influence the occurrence of TB in the municipality of Vitória. The zero-inflated model can be useful to the public health sector since it identifies the percentage of false zeros, generating an estimate of the real epidemiological condition of TB in Vitória.Sociedade Brasileira de Medicina Tropical - SBMT2018-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822018000500638Revista da Sociedade Brasileira de Medicina Tropical v.51 n.5 2018reponame:Revista da Sociedade Brasileira de Medicina Tropicalinstname:Sociedade Brasileira de Medicina Tropical (SBMT)instacron:SBMT10.1590/0037-8682-0015-2018info:eu-repo/semantics/openAccessSales,Carolina Maia MartinsSanchez,Mauro NiskierRamalho,WalterBertolde,Adelmo InácioMaciel,Ethel Leonor Noiaeng2019-07-29T00:00:00Zoai:scielo:S0037-86822018000500638Revistahttps://www.sbmt.org.br/portal/revista/ONGhttps://old.scielo.br/oai/scielo-oai.php||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br1678-98490037-8682opendoar:2019-07-29T00:00Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT)false |
dc.title.none.fl_str_mv |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil |
title |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil |
spellingShingle |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil Sales,Carolina Maia Martins Tuberculosis Epidemiology Social determinants of health Spatial analysis Statistical model Negative binomial distribution |
title_short |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil |
title_full |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil |
title_fullStr |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil |
title_full_unstemmed |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil |
title_sort |
Social determinants of tuberculosis via a zero-inflated model in small areas of a city in Southeastern Brazil |
author |
Sales,Carolina Maia Martins |
author_facet |
Sales,Carolina Maia Martins Sanchez,Mauro Niskier Ramalho,Walter Bertolde,Adelmo Inácio Maciel,Ethel Leonor Noia |
author_role |
author |
author2 |
Sanchez,Mauro Niskier Ramalho,Walter Bertolde,Adelmo Inácio Maciel,Ethel Leonor Noia |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Sales,Carolina Maia Martins Sanchez,Mauro Niskier Ramalho,Walter Bertolde,Adelmo Inácio Maciel,Ethel Leonor Noia |
dc.subject.por.fl_str_mv |
Tuberculosis Epidemiology Social determinants of health Spatial analysis Statistical model Negative binomial distribution |
topic |
Tuberculosis Epidemiology Social determinants of health Spatial analysis Statistical model Negative binomial distribution |
description |
Abstract INTRODUCTION: This study aimed to analyze social factors involved in the spatial distribution and under-reporting of tuberculosis (TB) in the city of Vitória, Espírito Santo State, Brazil. METHODS: This was an ecological study of the reported cases of TB between 2009 and 2011, according to census tracts. The outcome was TB incidence for the study period and the variables of exposure were proportions of literacy, inhabitants with an income of up to half the minimum monthly wage (MMW), and inhabitants associated with sewer mains or with access to safe drinking water. We used a zero-inflated process, zero-inflated negative binomial regression (ZINB), and selected an explanatory model based on the Akaike Information Criterion (AIC). RESULTS: A total of 588 cases of tuberculosis were reported in Vitória during the study period, distributed among 223 census tracts (38.6%), with 354 (61.4%) tracts presenting zero cases. In the ZINB model, the mean value of p i was 0.93, indicating that there is a 93% chance that an observed false zero could be due to sub-notification. CONCLUSIONS: It is important to prioritize areas exhibiting determinants that influence the occurrence of TB in the municipality of Vitória. The zero-inflated model can be useful to the public health sector since it identifies the percentage of false zeros, generating an estimate of the real epidemiological condition of TB in Vitória. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-10-01 |
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=S0037-86822018000500638 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822018000500638 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0037-8682-0015-2018 |
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 Medicina Tropical - SBMT |
publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina Tropical - SBMT |
dc.source.none.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical v.51 n.5 2018 reponame:Revista da Sociedade Brasileira de Medicina Tropical instname:Sociedade Brasileira de Medicina Tropical (SBMT) instacron:SBMT |
instname_str |
Sociedade Brasileira de Medicina Tropical (SBMT) |
instacron_str |
SBMT |
institution |
SBMT |
reponame_str |
Revista da Sociedade Brasileira de Medicina Tropical |
collection |
Revista da Sociedade Brasileira de Medicina Tropical |
repository.name.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT) |
repository.mail.fl_str_mv |
||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br |
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1752122161485578240 |