Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review
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 fact...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-07-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2021.631179/full |
| _version_ | 1818871738342047744 |
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| author | Paola Piqueras Alfredo Ballester Juan V. Durá-Gil Sergio Martinez-Hervas Sergio Martinez-Hervas Sergio Martinez-Hervas Sergio Martinez-Hervas Josep Redón Josep Redón Josep Redón José T. Real José T. Real José T. Real José T. Real |
| author_facet | Paola Piqueras Alfredo Ballester Juan V. Durá-Gil Sergio Martinez-Hervas Sergio Martinez-Hervas Sergio Martinez-Hervas Sergio Martinez-Hervas Josep Redón Josep Redón Josep Redón José T. Real José T. Real José T. Real José T. Real |
| author_sort | Paola Piqueras |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T12:27:41Z |
| format | Article |
| id | doaj.art-89983a4f11544307890ab9e3456641cf |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-12-19T12:27:41Z |
| publishDate | 2021-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-89983a4f11544307890ab9e3456641cf2022-12-21T20:21:30ZengFrontiers Media S.A.Frontiers in Psychology1664-10782021-07-011210.3389/fpsyg.2021.631179631179Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature ReviewPaola Piqueras0Alfredo Ballester1Juan V. Durá-Gil2Sergio Martinez-Hervas3Sergio Martinez-Hervas4Sergio Martinez-Hervas5Sergio Martinez-Hervas6Josep Redón7Josep Redón8Josep Redón9José T. Real10José T. Real11José T. Real12José T. Real13Instituto de Biomecánica de Valencia, Universitat Politècnica de Valencia, Valencia, SpainInstituto de Biomecánica de Valencia, Universitat Politècnica de Valencia, Valencia, SpainInstituto de Biomecánica de Valencia, Universitat Politècnica de Valencia, Valencia, SpainService of Endocrinology and Nutrition, Hospital Clínico Universitario de Valencia, Valencia, SpainInstitute of Health Research of the Hospital Clinico Universitario de Valencia (INCLIVA), Valencia, SpainDepartment of Medicine, University of Valencia, Valencia, SpainCIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, SpainDepartment of Internal Medicine, Hospital Clínico de Valencia, University of Valencia, Valencia, SpainCIBER Fisiopatología Obesidad y Nutrición (CB06/03), Instituto de Salud Carlos III, Madrid, SpainCardiovascular and Renal Risk Research Group, Institute of Health Research of the Hospital Clinico Universitario de Valencia (INCLIVA), University of Valencia, Valencia, SpainService of Endocrinology and Nutrition, Hospital Clínico Universitario de Valencia, Valencia, SpainInstitute of Health Research of the Hospital Clinico Universitario de Valencia (INCLIVA), Valencia, SpainDepartment of Medicine, University of Valencia, Valencia, SpainCIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, SpainObesity 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.https://www.frontiersin.org/articles/10.3389/fpsyg.2021.631179/fullobesityanthropometric health indicatorshealthrisk identificationfat distribution3D human shapes |
| spellingShingle | Paola Piqueras Alfredo Ballester Juan V. Durá-Gil Sergio Martinez-Hervas Sergio Martinez-Hervas Sergio Martinez-Hervas Sergio Martinez-Hervas Josep Redón Josep Redón Josep Redón José T. Real José T. Real José T. Real José T. Real Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review Frontiers in Psychology obesity anthropometric health indicators health risk identification fat distribution 3D human shapes |
| title | Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review |
| title_full | Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review |
| title_fullStr | Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review |
| title_full_unstemmed | Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review |
| title_short | Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review |
| title_sort | anthropometric indicators as a tool for diagnosis of obesity and other health risk factors a literature review |
| topic | obesity anthropometric health indicators health risk identification fat distribution 3D human shapes |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2021.631179/full |
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