A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina

Autores
Campero, Micaela Natalia; Scavuzzo, Carlos Matias; Andreoli, Veronica; Mileo, María Sol; Franzois, Micaela Belén; Oberto, María Georgina; Gonzalez Rodriguez, Carla; Defagó, María Daniela
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
New approaches to the study of cardiometabolic disease (CMD) distribution include analysis of built environment (BE), with spatial tools as suitable instruments. We aimed to characterize the spatial dissemination of CMD and the associated risk factors considering the BE for people attending the Non-Invasive Cardiology Service of Hospital Nacional de Clinicas in Córdoba City, Argentina during the period 2015-2020. We carried out an observational, descriptive, cross-sectional study performing non-probabilistic convenience sampling. The final sample included 345 people of both sexes older than 35 years. The CMD data were collected from medical records and validated techniques and BE information was extracted from Landsat-8 satellite products. A geographic information system (GIS) was constructed to assess the distribution of CMD and its risk factors in the area. Out of the people sampled, 41% showed the full metabolic syndrome and 22.6% only type-2 diabetes mellitus (DM2), a cluster of which was evidenced in north-western Córdoba. The risk of DM2 showed an association with high values of the normalized difference vegetation index (NDVI) (OR= 0.81; 95% CI:-0.30 to 1.66; p=0.05) and low normalized difference built index (NDBI) values that reduced the probability of occurrence of DM2 (OR=-1.39; 95% CI:-2.62 to-0.17; p=0.03). Considering that the results were found to be linked to the environmental indexes, the study of BE should include investigation of physical space as a fundamental part of the context in which people develop medically within society. The novel collection of satellite-generated information on BE proved efficient.
Fil: Campero, Micaela Natalia. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Scavuzzo, Carlos Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Andreoli, Veronica. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina
Fil: Mileo, María Sol. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina
Fil: Franzois, Micaela Belén. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina
Fil: Oberto, María Georgina. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina
Fil: Gonzalez Rodriguez, Carla. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Defagó, María Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; Argentina
Materia
ARGENTINA
BUILT ENVIRONMENT
DIABETES MELLITUS
METABOLIC SYNDROME
REMOTE SENSING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/218913
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in ArgentinaCampero, Micaela NataliaScavuzzo, Carlos MatiasAndreoli, VeronicaMileo, María SolFranzois, Micaela BelénOberto, María GeorginaGonzalez Rodriguez, CarlaDefagó, María DanielaARGENTINABUILT ENVIRONMENTDIABETES MELLITUSMETABOLIC SYNDROMEREMOTE SENSINGhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3New approaches to the study of cardiometabolic disease (CMD) distribution include analysis of built environment (BE), with spatial tools as suitable instruments. We aimed to characterize the spatial dissemination of CMD and the associated risk factors considering the BE for people attending the Non-Invasive Cardiology Service of Hospital Nacional de Clinicas in Córdoba City, Argentina during the period 2015-2020. We carried out an observational, descriptive, cross-sectional study performing non-probabilistic convenience sampling. The final sample included 345 people of both sexes older than 35 years. The CMD data were collected from medical records and validated techniques and BE information was extracted from Landsat-8 satellite products. A geographic information system (GIS) was constructed to assess the distribution of CMD and its risk factors in the area. Out of the people sampled, 41% showed the full metabolic syndrome and 22.6% only type-2 diabetes mellitus (DM2), a cluster of which was evidenced in north-western Córdoba. The risk of DM2 showed an association with high values of the normalized difference vegetation index (NDVI) (OR= 0.81; 95% CI:-0.30 to 1.66; p=0.05) and low normalized difference built index (NDBI) values that reduced the probability of occurrence of DM2 (OR=-1.39; 95% CI:-2.62 to-0.17; p=0.03). Considering that the results were found to be linked to the environmental indexes, the study of BE should include investigation of physical space as a fundamental part of the context in which people develop medically within society. The novel collection of satellite-generated information on BE proved efficient.Fil: Campero, Micaela Natalia. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Scavuzzo, Carlos Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Andreoli, Veronica. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; ArgentinaFil: Mileo, María Sol. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; ArgentinaFil: Franzois, Micaela Belén. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; ArgentinaFil: Oberto, María Georgina. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; ArgentinaFil: Gonzalez Rodriguez, Carla. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Defagó, María Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaUniv Naples Federico Ii2023-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/218913Campero, Micaela Natalia; Scavuzzo, Carlos Matias; Andreoli, Veronica; Mileo, María Sol; Franzois, Micaela Belén; et al.; A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina; Univ Naples Federico Ii; Geospatial Health; 18; 2; 10-2023; 1-101827-1987CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.geospatialhealth.net/index.php/gh/article/view/1212info:eu-repo/semantics/altIdentifier/doi/10.4081/gh.2023.1212info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:55:59Zoai:ri.conicet.gov.ar:11336/218913instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:55:59.532CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
title A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
spellingShingle A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
Campero, Micaela Natalia
ARGENTINA
BUILT ENVIRONMENT
DIABETES MELLITUS
METABOLIC SYNDROME
REMOTE SENSING
title_short A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
title_full A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
title_fullStr A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
title_full_unstemmed A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
title_sort A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina
dc.creator.none.fl_str_mv Campero, Micaela Natalia
Scavuzzo, Carlos Matias
Andreoli, Veronica
Mileo, María Sol
Franzois, Micaela Belén
Oberto, María Georgina
Gonzalez Rodriguez, Carla
Defagó, María Daniela
author Campero, Micaela Natalia
author_facet Campero, Micaela Natalia
Scavuzzo, Carlos Matias
Andreoli, Veronica
Mileo, María Sol
Franzois, Micaela Belén
Oberto, María Georgina
Gonzalez Rodriguez, Carla
Defagó, María Daniela
author_role author
author2 Scavuzzo, Carlos Matias
Andreoli, Veronica
Mileo, María Sol
Franzois, Micaela Belén
Oberto, María Georgina
Gonzalez Rodriguez, Carla
Defagó, María Daniela
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ARGENTINA
BUILT ENVIRONMENT
DIABETES MELLITUS
METABOLIC SYNDROME
REMOTE SENSING
topic ARGENTINA
BUILT ENVIRONMENT
DIABETES MELLITUS
METABOLIC SYNDROME
REMOTE SENSING
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv New approaches to the study of cardiometabolic disease (CMD) distribution include analysis of built environment (BE), with spatial tools as suitable instruments. We aimed to characterize the spatial dissemination of CMD and the associated risk factors considering the BE for people attending the Non-Invasive Cardiology Service of Hospital Nacional de Clinicas in Córdoba City, Argentina during the period 2015-2020. We carried out an observational, descriptive, cross-sectional study performing non-probabilistic convenience sampling. The final sample included 345 people of both sexes older than 35 years. The CMD data were collected from medical records and validated techniques and BE information was extracted from Landsat-8 satellite products. A geographic information system (GIS) was constructed to assess the distribution of CMD and its risk factors in the area. Out of the people sampled, 41% showed the full metabolic syndrome and 22.6% only type-2 diabetes mellitus (DM2), a cluster of which was evidenced in north-western Córdoba. The risk of DM2 showed an association with high values of the normalized difference vegetation index (NDVI) (OR= 0.81; 95% CI:-0.30 to 1.66; p=0.05) and low normalized difference built index (NDBI) values that reduced the probability of occurrence of DM2 (OR=-1.39; 95% CI:-2.62 to-0.17; p=0.03). Considering that the results were found to be linked to the environmental indexes, the study of BE should include investigation of physical space as a fundamental part of the context in which people develop medically within society. The novel collection of satellite-generated information on BE proved efficient.
Fil: Campero, Micaela Natalia. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Scavuzzo, Carlos Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Andreoli, Veronica. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina
Fil: Mileo, María Sol. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina
Fil: Franzois, Micaela Belén. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina
Fil: Oberto, María Georgina. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina
Fil: Gonzalez Rodriguez, Carla. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Defagó, María Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; Argentina
description New approaches to the study of cardiometabolic disease (CMD) distribution include analysis of built environment (BE), with spatial tools as suitable instruments. We aimed to characterize the spatial dissemination of CMD and the associated risk factors considering the BE for people attending the Non-Invasive Cardiology Service of Hospital Nacional de Clinicas in Córdoba City, Argentina during the period 2015-2020. We carried out an observational, descriptive, cross-sectional study performing non-probabilistic convenience sampling. The final sample included 345 people of both sexes older than 35 years. The CMD data were collected from medical records and validated techniques and BE information was extracted from Landsat-8 satellite products. A geographic information system (GIS) was constructed to assess the distribution of CMD and its risk factors in the area. Out of the people sampled, 41% showed the full metabolic syndrome and 22.6% only type-2 diabetes mellitus (DM2), a cluster of which was evidenced in north-western Córdoba. The risk of DM2 showed an association with high values of the normalized difference vegetation index (NDVI) (OR= 0.81; 95% CI:-0.30 to 1.66; p=0.05) and low normalized difference built index (NDBI) values that reduced the probability of occurrence of DM2 (OR=-1.39; 95% CI:-2.62 to-0.17; p=0.03). Considering that the results were found to be linked to the environmental indexes, the study of BE should include investigation of physical space as a fundamental part of the context in which people develop medically within society. The novel collection of satellite-generated information on BE proved efficient.
publishDate 2023
dc.date.none.fl_str_mv 2023-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/218913
Campero, Micaela Natalia; Scavuzzo, Carlos Matias; Andreoli, Veronica; Mileo, María Sol; Franzois, Micaela Belén; et al.; A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina; Univ Naples Federico Ii; Geospatial Health; 18; 2; 10-2023; 1-10
1827-1987
CONICET Digital
CONICET
url http://hdl.handle.net/11336/218913
identifier_str_mv Campero, Micaela Natalia; Scavuzzo, Carlos Matias; Andreoli, Veronica; Mileo, María Sol; Franzois, Micaela Belén; et al.; A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina; Univ Naples Federico Ii; Geospatial Health; 18; 2; 10-2023; 1-10
1827-1987
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.geospatialhealth.net/index.php/gh/article/view/1212
info:eu-repo/semantics/altIdentifier/doi/10.4081/gh.2023.1212
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Univ Naples Federico Ii
publisher.none.fl_str_mv Univ Naples Federico Ii
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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