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dc.contributor.author | Piqueras Fiszman, Paola | es_ES |
dc.contributor.author | Ballester Fernandez, Alfredo | es_ES |
dc.contributor.author | DURÁ-GIL, JUAN V. | es_ES |
dc.contributor.author | Martinez-Hervas, Sergio | es_ES |
dc.contributor.author | Redón, Josep | es_ES |
dc.contributor.author | Real, José T. | es_ES |
dc.date.accessioned | 2022-06-16T18:05:50Z | |
dc.date.available | 2022-06-16T18:05:50Z | |
dc.date.issued | 2021-07-09 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/183410 | |
dc.description.abstract | [EN] Obesity is characterized by the accumulation of an excessive amount of fat mass (FM) in the adipose tissue, subcutaneous, or inside certain organs. The risk does not lie so much in the amount of fat accumulated as in its distribution. Abdominal obesity (central or visceral) is an important risk factor for cardiovascular diseases, diabetes, and cancer, having an important role in the so-called metabolic syndrome. Therefore, it is necessary to prevent, detect, and appropriately treat obesity. The diagnosis is based on anthropometric indices that have been associated with adiposity and its distribution. Indices themselves, or a combination of some of them, conform to a big picture with different values to establish risk. Anthropometric indices can be used for risk identification, intervention, or impact evaluation on nutritional status or health; therefore, they will be called anthropometric health indicators (AHIs). We have found 17 AHIs that can be obtained or estimated from 3D human shapes, being a noninvasive alternative compared to X-ray-based systems, and more accessible than high-cost equipment. A literature review has been conducted to analyze the following information for each indicator: definition; main calculation or obtaining methods used; health aspects associated with the indicator (among others, obesity, metabolic syndrome, or diabetes); criteria to classify the population by means of percentiles or cutoff points, and based on variables such as sex, age, ethnicity, or geographic area, and limitations. | es_ES |
dc.description.sponsorship | BODYPASS Project has received funding from the European Union's Horizon 2020 research and innovation program under Grant Agreement No. 779780. CIBER de Diabetes and Enfermedades Metabolicas Asociadas (CIBERDEM) is an Instituto de Salud Carlos III initiative. SM-H was an investigator in the Juan Rodes program (JR18/00051) financed by the Instituto de Salud Carlos III and the European Regional Development Fund (FEDER). Project (IMDEEA/2020/87) supported by Instituto Valenciano de Competitividad Empresarial (IVACE), call for proposals 2020 for Technology Centers of the Comunitat Valenciana, cofunded by ERDF Funds, EU Operational Program of the Comunitat Valenciana 2014-2020. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Frontiers Media SA | es_ES |
dc.relation.ispartof | Frontiers in Psychology | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Obesity | es_ES |
dc.subject | Anthropometric health indicators | es_ES |
dc.subject | Health | es_ES |
dc.subject | Risk identification | es_ES |
dc.subject | Fat distribution | es_ES |
dc.subject | 3D human shapes | es_ES |
dc.title | Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3389/fpsyg.2021.631179 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/779780/EU | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/IVACE//IMDEEA%2F2020%2F87//CUSTOM_DHM. Adaptación del modelo digital humano para su aplicación en el diseño de productos y aplicaciones digitales/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/ISCIII//JR18%2F00051//Juan Rodes program/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Piqueras Fiszman, P.; Ballester Fernandez, A.; Durá-Gil, JV.; Martinez-Hervas, S.; Redón, J.; Real, JT. (2021). Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review. Frontiers in Psychology. 12:1-19. https://doi.org/10.3389/fpsyg.2021.631179 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3389/fpsyg.2021.631179 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 19 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 12 | es_ES |
dc.identifier.eissn | 1664-1078 | es_ES |
dc.identifier.pmid | 34305707 | es_ES |
dc.identifier.pmcid | PMC8299753 | es_ES |
dc.relation.pasarela | S\464989 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Instituto de Salud Carlos III | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Institut Valencià de Competitivitat Empresarial | es_ES |