Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging

Detalhes bibliográficos
Autor(a) principal: Salvador, Catharina Cavasin
Data de Publicação: 2023
Outros Autores: Lopes, Adalberto Aparecido dos Santos, Resendes, Danilo, Demarco, Fernanda Faccio, Justina, Marcelo Dutra Della, Saboya, Renato Tibiriçá de, Rech, Cassiano Ricardo, d’Orsi, Eleonora
Tipo de documento: Artigo
Idioma: por
eng
Título da fonte: Revista de Saúde Pública
Texto Completo: https://www.revistas.usp.br/rsp/article/view/220477
Resumo: OBJECTIVE: To describe the process and epidemiological implications of georeferencing in EpiFloripa Aging samples (2009–2019). METHOD: The EpiFloripa Aging Cohort Study sought to investigate and monitor the living and health conditions of the older adult population (≥ 60) of Florianópolis in three study waves (2009/2010, 2013/2014, 2017/2019). With an automatic geocoding tool, the residential addresses were spatialized, allowing to investigate the effect of the georeferencing sample losses regarding 19 variables, evaluated in the three waves. The influence of different neighborhood definitions (census tracts, Euclidean buffers, and buffers across the street network) was examined in the results of seven variables: area, income, residential density, mixed land use, connectivity, health unit count, and public open space count. Pearson’s correlation coefficients were calculated to evaluate the differences between neighborhood definitions according to three variables: contextual income, residential density, and land use diversity. RESULT: The losses imposed by geocoding (6%, n = 240) caused no statistically significant difference between the total sample and the geocoded sample. The analysis of the study variables suggests that the geocoding process may have included a higher proportion of participants with better income, education, and living conditions. The correlation coefficients showed little correspondence between measures calculated by the three neighborhood definitions (r = 0.37–0.54). The statistical difference between the variables calculated by buffers and census tracts highlights limitations in their use in the description of geospatial attributes. CONCLUSION: Despite the challenges related to geocoding, such as inconsistencies in addresses, adequate correction and verification mechanisms provided a high rate of assignment of geographic coordinates, the findings suggest that adopting buffers, favored by geocoding, represents a potential for spatial epidemiological analyses by improving the representation of environmental attributes and the understanding of health outcomes.
id USP-23_12e197685cde148c1f5854b57c337da4
oai_identifier_str oai:revistas.usp.br:article/220477
network_acronym_str USP-23
network_name_str Revista de Saúde Pública
repository_id_str
spelling Geocoding processes in cohort studies: methods applied in the EpiFloripa AgingProcessos de geocodificação em estudos de coorte: métodos aplicados no EpiFloripa IdosoHealth of Aged PersonsEnvironment and Public HealthHealth Surveys Geographic Mapping Geographic Information SystemsSpatial AnalysisSaúde do IdosoMeio Ambiente e Saúde PúblicaInquéritos EpidemiológicosMapeamento GeográficoSistemas de Informação GeográficaAnálise EspacialOBJECTIVE: To describe the process and epidemiological implications of georeferencing in EpiFloripa Aging samples (2009–2019). METHOD: The EpiFloripa Aging Cohort Study sought to investigate and monitor the living and health conditions of the older adult population (≥ 60) of Florianópolis in three study waves (2009/2010, 2013/2014, 2017/2019). With an automatic geocoding tool, the residential addresses were spatialized, allowing to investigate the effect of the georeferencing sample losses regarding 19 variables, evaluated in the three waves. The influence of different neighborhood definitions (census tracts, Euclidean buffers, and buffers across the street network) was examined in the results of seven variables: area, income, residential density, mixed land use, connectivity, health unit count, and public open space count. Pearson’s correlation coefficients were calculated to evaluate the differences between neighborhood definitions according to three variables: contextual income, residential density, and land use diversity. RESULT: The losses imposed by geocoding (6%, n = 240) caused no statistically significant difference between the total sample and the geocoded sample. The analysis of the study variables suggests that the geocoding process may have included a higher proportion of participants with better income, education, and living conditions. The correlation coefficients showed little correspondence between measures calculated by the three neighborhood definitions (r = 0.37–0.54). The statistical difference between the variables calculated by buffers and census tracts highlights limitations in their use in the description of geospatial attributes. CONCLUSION: Despite the challenges related to geocoding, such as inconsistencies in addresses, adequate correction and verification mechanisms provided a high rate of assignment of geographic coordinates, the findings suggest that adopting buffers, favored by geocoding, represents a potential for spatial epidemiological analyses by improving the representation of environmental attributes and the understanding of health outcomes.OBJETIVO: Descrever o processo e as implicações epidemiológicas do georreferenciamento nas amostras do EpiFloripa Idoso (2009–2019). MÉTODO: O estudo de coorte EpiFloripa Idoso buscou investigar e acompanhar as condições de vida e saúde da população idosa (≥ 60) de Florianópolis em três ondas de estudo (2009/2010, 2013/2014, 2017/2019). Com uma ferramenta de geocodificação automática, os endereços residenciais foram espacializados, permitindo a investigação do efeito das perdas amostrais do georreferenciamento em relação a 19 variáveis, avaliadas nas três ondas. A influência de diferentes definições de vizinhança (setores censitários, buffers euclidianos e buffers pela rede de ruas) foi examinada nos resultados de sete variáveis: área, renda, densidade residencial, uso misto do solo, conectividade, contagem de unidades de saúde, e contagem de espaços livres públicos. Coeficientes de correlação de Pearson foram calculados para avaliar as diferenças entre as definições de vizinhança de acordo com três variáveis: renda contextual, densidade residencial e diversidade de uso do solo. RESULTADO: As perdas impostas pela geocodificação (6%, n = 240) não ocasionaram diferença estatística significativa entre a amostra total e a georreferenciada. A análise das variáveis do estudo sugere que o processo de geocodificação pode ter incluído uma maior proporção de participantes com melhor nível de renda, escolaridade e condições de vida. Os coeficientes de correlação evidenciaram pouca correspondência entre medidas calculadas pelas três definições de vizinhança (r = 0,37–0,54). A diferença estatística entre as variáveis calculadas por buffers e setores censitários ressalta limitações no uso destes na descrição dos atributos geoespaciais. CONCLUSÃO: Apesar dos desafios relacionados à geocodificação, como inconsistências nos endereços, adequados mecanismos de correção e verificação propiciaram elevada taxa de atribuição de coordenadas geográficas. Os achados sugerem que a adoção de buffers, favorecida pela geocodificação, representa uma potencialidade para análises epidemiológicas espaciais ao aprimorar a representação dos atributos do ambiente e a compreensão dos desfechos de saúde.Universidade de São Paulo. Faculdade de Saúde Pública2023-11-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdftext/xmlhttps://www.revistas.usp.br/rsp/article/view/22047710.11606/s1518-8787.2023057004976Revista de Saúde Pública; Vol. 57 No. 1 (2023); 88Revista de Saúde Pública; Vol. 57 Núm. 1 (2023); 88Revista de Saúde Pública; v. 57 n. 1 (2023); 881518-87870034-8910reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USPporenghttps://www.revistas.usp.br/rsp/article/view/220477/201391https://www.revistas.usp.br/rsp/article/view/220477/201390https://www.revistas.usp.br/rsp/article/view/220477/201389Copyright (c) 2023 Catharina Cavasin Salvador, Adalberto Aparecido dos Santos Lopes, Danilo Resendes, Fernanda Faccio Demarco, Marcelo Dutra Della Justina, Renato Tibiriçá de Saboya, Cassiano Ricardo Rech, Eleonora d’Orsihttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSalvador, Catharina CavasinLopes, Adalberto Aparecido dos SantosResendes, DaniloDemarco, Fernanda FaccioJustina, Marcelo Dutra DellaSaboya, Renato Tibiriçá deRech, Cassiano Ricardod’Orsi, Eleonora2023-12-18T19:30:20Zoai:revistas.usp.br:article/220477Revistahttps://www.revistas.usp.br/rsp/indexONGhttps://www.revistas.usp.br/rsp/oairevsp@org.usp.br||revsp1@usp.br1518-87870034-8910opendoar:2023-12-18T19:30:20Revista de Saúde Pública - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
Processos de geocodificação em estudos de coorte: métodos aplicados no EpiFloripa Idoso
title Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
spellingShingle Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
Salvador, Catharina Cavasin
Health of Aged Persons
Environment and Public Health
Health Surveys
Geographic Mapping
Geographic Information Systems
Spatial Analysis
Saúde do Idoso
Meio Ambiente e Saúde Pública
Inquéritos Epidemiológicos
Mapeamento Geográfico
Sistemas de Informação Geográfica
Análise Espacial
title_short Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
title_full Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
title_fullStr Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
title_full_unstemmed Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
title_sort Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging
author Salvador, Catharina Cavasin
author_facet Salvador, Catharina Cavasin
Lopes, Adalberto Aparecido dos Santos
Resendes, Danilo
Demarco, Fernanda Faccio
Justina, Marcelo Dutra Della
Saboya, Renato Tibiriçá de
Rech, Cassiano Ricardo
d’Orsi, Eleonora
author_role author
author2 Lopes, Adalberto Aparecido dos Santos
Resendes, Danilo
Demarco, Fernanda Faccio
Justina, Marcelo Dutra Della
Saboya, Renato Tibiriçá de
Rech, Cassiano Ricardo
d’Orsi, Eleonora
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Salvador, Catharina Cavasin
Lopes, Adalberto Aparecido dos Santos
Resendes, Danilo
Demarco, Fernanda Faccio
Justina, Marcelo Dutra Della
Saboya, Renato Tibiriçá de
Rech, Cassiano Ricardo
d’Orsi, Eleonora
dc.subject.por.fl_str_mv Health of Aged Persons
Environment and Public Health
Health Surveys
Geographic Mapping
Geographic Information Systems
Spatial Analysis
Saúde do Idoso
Meio Ambiente e Saúde Pública
Inquéritos Epidemiológicos
Mapeamento Geográfico
Sistemas de Informação Geográfica
Análise Espacial
topic Health of Aged Persons
Environment and Public Health
Health Surveys
Geographic Mapping
Geographic Information Systems
Spatial Analysis
Saúde do Idoso
Meio Ambiente e Saúde Pública
Inquéritos Epidemiológicos
Mapeamento Geográfico
Sistemas de Informação Geográfica
Análise Espacial
description OBJECTIVE: To describe the process and epidemiological implications of georeferencing in EpiFloripa Aging samples (2009–2019). METHOD: The EpiFloripa Aging Cohort Study sought to investigate and monitor the living and health conditions of the older adult population (≥ 60) of Florianópolis in three study waves (2009/2010, 2013/2014, 2017/2019). With an automatic geocoding tool, the residential addresses were spatialized, allowing to investigate the effect of the georeferencing sample losses regarding 19 variables, evaluated in the three waves. The influence of different neighborhood definitions (census tracts, Euclidean buffers, and buffers across the street network) was examined in the results of seven variables: area, income, residential density, mixed land use, connectivity, health unit count, and public open space count. Pearson’s correlation coefficients were calculated to evaluate the differences between neighborhood definitions according to three variables: contextual income, residential density, and land use diversity. RESULT: The losses imposed by geocoding (6%, n = 240) caused no statistically significant difference between the total sample and the geocoded sample. The analysis of the study variables suggests that the geocoding process may have included a higher proportion of participants with better income, education, and living conditions. The correlation coefficients showed little correspondence between measures calculated by the three neighborhood definitions (r = 0.37–0.54). The statistical difference between the variables calculated by buffers and census tracts highlights limitations in their use in the description of geospatial attributes. CONCLUSION: Despite the challenges related to geocoding, such as inconsistencies in addresses, adequate correction and verification mechanisms provided a high rate of assignment of geographic coordinates, the findings suggest that adopting buffers, favored by geocoding, represents a potential for spatial epidemiological analyses by improving the representation of environmental attributes and the understanding of health outcomes.
publishDate 2023
dc.date.none.fl_str_mv 2023-11-13
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/220477
10.11606/s1518-8787.2023057004976
url https://www.revistas.usp.br/rsp/article/view/220477
identifier_str_mv 10.11606/s1518-8787.2023057004976
dc.language.iso.fl_str_mv por
eng
language por
eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/rsp/article/view/220477/201391
https://www.revistas.usp.br/rsp/article/view/220477/201390
https://www.revistas.usp.br/rsp/article/view/220477/201389
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
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; Vol. 57 No. 1 (2023); 88
Revista de Saúde Pública; Vol. 57 Núm. 1 (2023); 88
Revista de Saúde Pública; v. 57 n. 1 (2023); 88
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_ 1800221804075155456