Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/128839
Campo DC | Valor | idioma |
---|---|---|
dc.contributor.author | Martín, V | en_US |
dc.contributor.author | Dávila Batista, Verónica | en_US |
dc.contributor.author | Castilla, J | en_US |
dc.contributor.author | Godoy, P | en_US |
dc.contributor.author | Delgado-Rodríguez, M | en_US |
dc.contributor.author | Soldevila, N | en_US |
dc.contributor.author | Molina, AJ | en_US |
dc.contributor.author | Fernandez-Villa, T | en_US |
dc.contributor.author | Astray, J | en_US |
dc.contributor.author | Castro, A | en_US |
dc.contributor.author | González-Candelas, F | en_US |
dc.contributor.author | Mayoral, JM | en_US |
dc.contributor.author | Quintana, JM | en_US |
dc.contributor.author | Domínguez, Angela | en_US |
dc.contributor.author | CIBERESP Cases and Controls in Pandemic Influenza Working Group in Spain | en_US |
dc.date.accessioned | 2024-02-07T17:48:49Z | - |
dc.date.available | 2024-02-07T17:48:49Z | - |
dc.date.issued | 2016 | en_US |
dc.identifier.issn | 1471-2458 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/128839 | - |
dc.description.abstract | Background: Obesity is a world-wide epidemic whose prevalence is underestimated by BMI measurements, but CUN-BAE (Clínica Universidad de Navarra - Body Adiposity Estimator) estimates the percentage of body fat (BF) while incorporating information on sex and age, thus giving a better match. Our aim is to compare the BMI and CUN-BAE in determining the population attributable fraction (AFp) for obesity as a cause of chronic diseases. Methods: We calculated the Pearson correlation coefficient between BMI and CUN-BAE, the Kappa index and the internal validity of the BMI. The risks of arterial hypertension (AHT) and diabetes mellitus (DM) and the AFp for obesity were assessed using both the BMI and CUN-BAE. Results: 3888 white subjects were investigated. The overall correlation between BMI and CUN-BAE was R2 = 0.48, which improved when sex and age were taken into account (R2 > 0.90). The Kappa coefficient for diagnosis of obesity was low (28.7 %). The AFp was 50 % higher for DM and double for AHT when CUN-BAE was used. Conclusions: The overall correlation between BMI and CUN-BAE was not good. The AFp of obesity for AHT and DM may be underestimated if assessed using the BMI, as may the prevalence of obesity when estimated from the percentage of BF. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | BMC Public Health | en_US |
dc.source | BMC Public Health [1471-2458], v. 16:82 (Enero 2016) | en_US |
dc.subject | 32 Ciencias médicas | en_US |
dc.subject | 3206 Ciencias de la nutrición | en_US |
dc.subject.other | Obesity | en_US |
dc.subject.other | Body mass index | en_US |
dc.subject.other | Body fat | en_US |
dc.subject.other | CUN-BAE | en_US |
dc.subject.other | Population attributable fraction | en_US |
dc.subject.other | Hypertension | en_US |
dc.subject.other | Diabetes mellitus | en_US |
dc.title | Comparison of body mass index (BMI) with the CUN-BAE body adiposity estimator in the prediction of hypertension and type 2 diabetes | en_US |
dc.type | info:eu-repo/semantics/article | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1186/s12889-016-2728-3 | en_US |
dc.identifier.pmid | 26817835 | - |
dc.identifier.scopus | 2-s2.0-84955257587 | - |
dc.identifier.isi | WOS:000369475800001 | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.identifier.issue | 1 | - |
dc.relation.volume | 16 | en_US |
dc.investigacion | Ciencias de la Salud | en_US |
dc.type2 | Artículo | en_US |
dc.description.notas | Con la participación de: CIBERESP Cases and Controls in Pandemic Influenza Working Group in Spain | en_US |
dc.description.numberofpages | 8 | en_US |
dc.utils.revision | Sí | en_US |
dc.date.coverdate | Enero 2016 | en_US |
dc.identifier.ulpgc | Sí | en_US |
dc.contributor.buulpgc | BU-MED | en_US |
dc.description.sjr | 1,328 | |
dc.description.jcr | 2,265 | |
dc.description.sjrq | Q1 | |
dc.description.jcrq | Q2 | |
dc.description.scie | SCIE | |
item.grantfulltext | open | - |
item.fulltext | Con texto completo | - |
crisitem.author.dept | GIR IUIBS: Diabetes y endocrinología aplicada | - |
crisitem.author.dept | IU de Investigaciones Biomédicas y Sanitarias | - |
crisitem.author.dept | Departamento de Ciencias Clínicas | - |
crisitem.author.dept | GIR IUSA-ONEHEALTH 3: Histología y Patología Veterinaria y Forense (Terrestre y Marina) | - |
crisitem.author.dept | IU de Sanidad Animal y Seguridad Alimentaria | - |
crisitem.author.dept | Departamento de Morfología | - |
crisitem.author.dept | GIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional | - |
crisitem.author.dept | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.orcid | 0000-0001-8888-395X | - |
crisitem.author.orcid | 0000-0002-2243-5449 | - |
crisitem.author.orcid | 0000-0002-3252-5683 | - |
crisitem.author.parentorg | IU de Investigaciones Biomédicas y Sanitarias | - |
crisitem.author.parentorg | IU de Sanidad Animal y Seguridad Alimentaria | - |
crisitem.author.parentorg | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.fullName | Dávila Batista, Verónica | - |
crisitem.author.fullName | Castro Alonso, Ayoze | - |
crisitem.author.fullName | Domínguez Brito, Antonio Carlos | - |
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