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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">nogr</journal-id><journal-title-group><journal-title xml:lang="ru">Экспериментальная и клиническая гастроэнтерология</journal-title><trans-title-group xml:lang="en"><trans-title>Experimental and Clinical Gastroenterology</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1682-8658</issn><publisher><publisher-name>«Global Media Technologies»</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.31146/1682-8658-ecg-222-2-89-100</article-id><article-id custom-type="elpub" pub-id-type="custom">nogr-2585</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОБЗОР</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>REVIEW</subject></subj-group></article-categories><title-group><article-title>Диагностика композиционного состава тела пожилого человека людей для оценки прогноза состояния его здоровья</article-title><trans-title-group xml:lang="en"><trans-title>Diagnostics of the body composition of an elderly person to assess the prognosis of his health</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0027-1786</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Булгакова</surname><given-names>С. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Bulgakova</surname><given-names>S. V.</given-names></name></name-alternatives><email xlink:type="simple">osteoporosis63@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-4114-5233</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Курмаев</surname><given-names>Д. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Kurmaev</surname><given-names>D. P.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0097-7252</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Тренева</surname><given-names>Е. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Treneva</surname><given-names>E. V.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Федеральное государственное бюджетное образовательное учреждение высшего образования «Самарский государственный медицинский университет» Министерства здравоохранения Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Samara State Medical University of the Ministry of Healthcare of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>26</day><month>03</month><year>2024</year></pub-date><volume>0</volume><issue>2</issue><fpage>89</fpage><lpage>100</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Булгакова С.В., Курмаев Д.П., Тренева Е.В., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Булгакова С.В., Курмаев Д.П., Тренева Е.В.</copyright-holder><copyright-holder xml:lang="en">Bulgakova S.V., Kurmaev D.P., Treneva E.V.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.nogr.org/jour/article/view/2585">https://www.nogr.org/jour/article/view/2585</self-uri><abstract><p>Старение ассоциировано с изменением состава тела, которое представляет собой увеличение доли жировой массы, как правило, на фоне уменьшения мышечной массы. Кроме того, ожирение часто ассоциировано с метаболическим синдромом, сахарным диабетом 2 типа (СД2), сердечно-сосудистыми заболеваниями. Висцеральное ожирение более опасно, чем избыточное накопление подкожного жира. Точная оценка состава тела может дать полезную информацию о здоровье и функциях организма. Однако бывает трудно определить точное содержание скелетно-мышечной и жировой ткани в организме гериатрических пациентов. Антропометрические методы простые в применении и не требуют сложного и дорогостоящего оборудования, однако они малоинформативны и обладают невысокой точностью. Актуальным является вопрос своевременной диагностики композиционного состава тела у людей старших возрастных групп, для прогноза риска развития хронических неинфекционных заболеваний, инвалидизации.</p></abstract><trans-abstract xml:lang="en"><p>Aging is associated with a change in body composition, which is an increase in the proportion of fat mass, usually against with decrease in muscle mass. In addition, obesity is often associated with metabolic syndrome, type 2 diabetes mellitus (DM2), and cardiovascular diseases. Visceral obesity is more dangerous than excessive accumulation of subcutaneous fat. An accurate assessment of body composition can provide useful information about the health and functions of the body. However, it can be difficult to determine the exact content of musculoskeletal and adipose tissue in the body of geriatric patients. Anthropometric methods are easy to use and do not require complex and expensive equipment, but they are uninformative and have low accuracy. The issue of timely diagnosis of the compositional composition of the body in older age groups is relevant for predicting the risk of developing chronic non-communicable diseases, disability.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>старение</kwd><kwd>полиморбидность</kwd><kwd>саркопения</kwd><kwd>ожирение</kwd><kwd>саркопеническое ожирение</kwd><kwd>состав тела</kwd><kwd>биоимпедансный анализ</kwd><kwd>компьютерная томография</kwd><kwd>двухэнергетическая рентгеновская абсорбциометрия</kwd><kwd>магнитно-резонансная томография</kwd></kwd-group><kwd-group xml:lang="en"><kwd>aging</kwd><kwd>polymorbidity</kwd><kwd>sarcopenia</kwd><kwd>obesity</kwd><kwd>sarcopenic obesity</kwd><kwd>body composition</kwd><kwd>bioimpedance analysis</kwd><kwd>computed tomography</kwd><kwd>dual-energy x-ray absorptiometry</kwd><kwd>magnetic resonance imaging</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Al-Sofiani M. E., Ganji S. S., Kalyani R. R. Body composition changes in diabetes and aging. J Diabetes Complications. 2019;33(6):451-459. doi:10.1016/j.jdiacomp.2019.03.007.</mixed-citation><mixed-citation xml:lang="en">Al-Sofiani M. E., Ganji S. S., Kalyani R. R. Body composition changes in diabetes and aging. J Diabetes Complications. 2019;33(6):451-459. doi:10.1016/j.jdiacomp.2019.03.007.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">World Health Organization. Obesity and Overweight. Geneva: World Health Organization; 2020. Available at: https://www.who.int/en/news-room/fact-sheets/detail/obesity-and-overweight Accecced: 2023 Aug 15.</mixed-citation><mixed-citation xml:lang="en">World Health Organization. Obesity and Overweight. Geneva: World Health Organization; 2020. Available at: https://www.who.int/en/news-room/fact-sheets/detail/obesity-and-overweight Accecced: 2023 Aug 15.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Flatt J. P. Use and storage of carbohydrate and fat. Am J Clin Nutr. 1995;61(4 Suppl):952S-959S. doi:10.1093/ajcn/61.4.952S.</mixed-citation><mixed-citation xml:lang="en">Flatt J. P. Use and storage of carbohydrate and fat. Am J Clin Nutr. 1995;61(4 Suppl):952S-959S. doi:10.1093/ajcn/61.4.952S.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Jozsa L. G. Obesity in the paleolithic era. Hormones (Athens). 2011;10(3):241-244. doi:10.14310/horm.2002.1315.</mixed-citation><mixed-citation xml:lang="en">Jozsa L. G. Obesity in the paleolithic era. Hormones (Athens). 2011;10(3):241-244. doi:10.14310/horm.2002.1315.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Williams R., Periasamy M. Genetic and Environmental Factors Contributing to Visceral Adiposity in Asian Populations. Endocrinol Metab (Seoul). 2020;35(4):681-695. doi:10.3803/EnM.2020.772.</mixed-citation><mixed-citation xml:lang="en">Williams R., Periasamy M. Genetic and Environmental Factors Contributing to Visceral Adiposity in Asian Populations. Endocrinol Metab (Seoul). 2020;35(4):681-695. doi:10.3803/EnM.2020.772.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Donini L. M., Busetto L., Bischoff S. C. et al. Definition and Diagnostic Criteria for Sarcopenic Obesity: ESPEN and EASO Consensus Statement. Obes Facts. 2022;15(3):321-335. doi:10.1159/000521241.</mixed-citation><mixed-citation xml:lang="en">Donini L. M., Busetto L., Bischoff S. C. et al. Definition and Diagnostic Criteria for Sarcopenic Obesity: ESPEN and EASO Consensus Statement. Obes Facts. 2022;15(3):321-335. doi:10.1159/000521241.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Boccara E., Golan S., Beeri M. S. The association between regional adiposity, cognitive function, and dementia-related brain changes: a systematic review. Front Med (Lausanne). 2023;10:1160426. doi:10.3389/fmed.2023.1160426.</mixed-citation><mixed-citation xml:lang="en">Boccara E., Golan S., Beeri M. S. The association between regional adiposity, cognitive function, and dementia-related brain changes: a systematic review. Front Med (Lausanne). 2023;10:1160426. doi:10.3389/fmed.2023.1160426.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Cruz-Jentoft A. J., Bahat G., Bauer J. et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(4):601. doi:10.1093/ageing/afz046.</mixed-citation><mixed-citation xml:lang="en">Cruz-Jentoft A. J., Bahat G., Bauer J. et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(4):601. doi:10.1093/ageing/afz046.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Jayasinghe S., Hills A. P. Sarcopenia, obesity, and diabetes - The metabolic conundrum trifecta. Diabetes Metab Syndr. 2022;16(11):102656. doi:10.1016/j.dsx.2022.102656.</mixed-citation><mixed-citation xml:lang="en">Jayasinghe S., Hills A. P. Sarcopenia, obesity, and diabetes - The metabolic conundrum trifecta. Diabetes Metab Syndr. 2022;16(11):102656. doi:10.1016/j.dsx.2022.102656.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Tutan D., Şen Uzeli Ü. A scientometric analysis of sarcopenic obesity: Future trends and new perspectives. Medicine (Baltimore). 2023;102(26): e34244. doi:10.1097/MD.0000000000034244</mixed-citation><mixed-citation xml:lang="en">Tutan D., Şen Uzeli Ü. A scientometric analysis of sarcopenic obesity: Future trends and new perspectives. Medicine (Baltimore). 2023;102(26): e34244. doi:10.1097/MD.0000000000034244</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Kuriyan R. Body composition techniques. Indian J Med Res. 2018 Nov;148(5):648-658. doi: 10.4103/ijmr.IJMR_1777_18.</mixed-citation><mixed-citation xml:lang="en">Kuriyan R. Body composition techniques. Indian J Med Res. 2018 Nov;148(5):648-658. doi: 10.4103/ijmr.IJMR_1777_18.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Thibault R., Genton L., Pichard C. Body composition: why, when and for who?. Clin Nutr. 2012;31(4):435-447. doi:10.1016/j.clnu.2011.12.011</mixed-citation><mixed-citation xml:lang="en">Thibault R., Genton L., Pichard C. Body composition: why, when and for who?. Clin Nutr. 2012;31(4):435-447. doi:10.1016/j.clnu.2011.12.011</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Andreoli A., Garaci F., Cafarelli F. P., Guglielmi G. Body composition in clinical practice. Eur J Radiol. 2016;85(8):1461-1468. doi:10.1016/j.ejrad.2016.02.005</mixed-citation><mixed-citation xml:lang="en">Andreoli A., Garaci F., Cafarelli F. P., Guglielmi G. Body composition in clinical practice. Eur J Radiol. 2016;85(8):1461-1468. doi:10.1016/j.ejrad.2016.02.005</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Cui L. H., Shin M. H., Kweon S. S. et al. Sex-related differences in the association between waist circumference and bone mineral density in a Korean population. BMC Musculoskelet Disord. 2014;15:326. doi:10.1186/1471-2474-15-326.</mixed-citation><mixed-citation xml:lang="en">Cui L. H., Shin M. H., Kweon S. S. et al. Sex-related differences in the association between waist circumference and bone mineral density in a Korean population. BMC Musculoskelet Disord. 2014;15:326. doi:10.1186/1471-2474-15-326.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Kawakami R., Murakami H., Sanada K. et al. Calf circumference as a surrogate marker of muscle mass for diagnosing sarcopenia in Japanese men and women. Geriatr Gerontol Int. 2015;15(8):969-976. doi:10.1111/ggi.12377.</mixed-citation><mixed-citation xml:lang="en">Kawakami R., Murakami H., Sanada K. et al. Calf circumference as a surrogate marker of muscle mass for diagnosing sarcopenia in Japanese men and women. Geriatr Gerontol Int. 2015;15(8):969-976. doi:10.1111/ggi.12377.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Troschel A. S., Troschel F. M., Best T. D. et al.Computed Tomography-based Body Composition Analysis and Its Role in Lung Cancer Care. J Thorac Imaging. 2020;35(2):91-100. doi:10.1097/RTI.0000000000000428.</mixed-citation><mixed-citation xml:lang="en">Troschel A. S., Troschel F. M., Best T. D. et al.Computed Tomography-based Body Composition Analysis and Its Role in Lung Cancer Care. J Thorac Imaging. 2020;35(2):91-100. doi:10.1097/RTI.0000000000000428.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Dabiri S., Popuri K., Cespedes Feliciano E. M. et al. Muscle segmentation in axial computed tomography (CT) images at the lumbar (L3) and thoracic (T4) levels for body composition analysis.Comput Med Imaging Graph. 2019;75:47-55. doi:10.1016/j.compmedimag.2019.04.007.</mixed-citation><mixed-citation xml:lang="en">Dabiri S., Popuri K., Cespedes Feliciano E. M. et al. Muscle segmentation in axial computed tomography (CT) images at the lumbar (L3) and thoracic (T4) levels for body composition analysis.Comput Med Imaging Graph. 2019;75:47-55. doi:10.1016/j.compmedimag.2019.04.007.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Gomez-Perez S. L., Haus J. M., Sheean P. et al. Measuring Abdominal Circumference and Skeletal Muscle From a Single Cross-Sectional Computed Tomography Image: A Step-by-Step Guide for Clinicians Using National Institutes of Health Image J. JPEN J Parenter Enteral Nutr. 2016;40(3):308-318. doi:10.1177/0148607115604149.</mixed-citation><mixed-citation xml:lang="en">Gomez-Perez S. L., Haus J. M., Sheean P. et al. Measuring Abdominal Circumference and Skeletal Muscle From a Single Cross-Sectional Computed Tomography Image: A Step-by-Step Guide for Clinicians Using National Institutes of Health Image J. JPEN J Parenter Enteral Nutr. 2016;40(3):308-318. doi:10.1177/0148607115604149.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Aroom K. R., Harting M. T., Cox C. S. Jr. et al. Bioimpedance analysis: a guide to simple design and implementation. J Surg Res. 2009;153(1):23-30. doi:10.1016/j.jss.2008.04.019.</mixed-citation><mixed-citation xml:lang="en">Aroom K. R., Harting M. T., Cox C. S. Jr. et al. Bioimpedance analysis: a guide to simple design and implementation. J Surg Res. 2009;153(1):23-30. doi:10.1016/j.jss.2008.04.019.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Sergi G., De Rui M., Stubbs B. et al. Measurement of lean body mass using bioelectrical impedance analysis: a consideration of the pros and cons. Aging Clin Exp Res. 2017;29(4):591-597. doi:10.1007/s40520-016-0622-6.</mixed-citation><mixed-citation xml:lang="en">Sergi G., De Rui M., Stubbs B. et al. Measurement of lean body mass using bioelectrical impedance analysis: a consideration of the pros and cons. Aging Clin Exp Res. 2017;29(4):591-597. doi:10.1007/s40520-016-0622-6.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Marra M., Sammarco R., De Lorenzo A. et al. Assessment of Body Composition in Health and Disease Using Bioelectrical Impedance Analysis (BIA) and Dual Energy X-Ray Absorptiometry (DXA): A Critical Overview. Contrast Media Mol Imaging. 2019;2019:3548284. doi:10.1155/2019/3548284.</mixed-citation><mixed-citation xml:lang="en">Marra M., Sammarco R., De Lorenzo A. et al. Assessment of Body Composition in Health and Disease Using Bioelectrical Impedance Analysis (BIA) and Dual Energy X-Ray Absorptiometry (DXA): A Critical Overview. Contrast Media Mol Imaging. 2019;2019:3548284. doi:10.1155/2019/3548284.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Guglielmi G., Ponti F., Agostini M. et al. The role of DXA in sarcopenia. Aging Clin Exp Res. 2016;28(6):1047-1060. doi:10.1007/s40520-016-0589-3.</mixed-citation><mixed-citation xml:lang="en">Guglielmi G., Ponti F., Agostini M. et al. The role of DXA in sarcopenia. Aging Clin Exp Res. 2016;28(6):1047-1060. doi:10.1007/s40520-016-0589-3.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Holmes C. J., Racette S. B. The Utility of Body Composition Assessment in Nutrition and Clinical Practice: An Overview of Current Methodology. Nutrients. 2021;13(8):2493. doi: 10.3390/nu13082493.</mixed-citation><mixed-citation xml:lang="en">Holmes C. J., Racette S. B. The Utility of Body Composition Assessment in Nutrition and Clinical Practice: An Overview of Current Methodology. Nutrients. 2021;13(8):2493. doi: 10.3390/nu13082493.</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995;854:1-452.</mixed-citation><mixed-citation xml:lang="en">Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995;854:1-452.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Lean M. E., Han T. S., Morrison C. E. Waist circumference as a measure for indicating need for weight management. BMJ. 1995;311(6998):158-161. doi:10.1136/bmj.311.6998.158.</mixed-citation><mixed-citation xml:lang="en">Lean M. E., Han T. S., Morrison C. E. Waist circumference as a measure for indicating need for weight management. BMJ. 1995;311(6998):158-161. doi:10.1136/bmj.311.6998.158.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Bawadi H., Abouwatfa M., Alsaeed S. et al. Body Shape Index is a Stronger Predictor of Diabetes. Nutrients. 2019;11:1018. doi: 10.3390/nu11051018.</mixed-citation><mixed-citation xml:lang="en">Bawadi H., Abouwatfa M., Alsaeed S. et al. Body Shape Index is a Stronger Predictor of Diabetes. Nutrients. 2019;11:1018. doi: 10.3390/nu11051018.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Britton K. A., Massaro J. M., Murabito J. M. et al. Body fat distribution, incident cardiovascular disease, cancer, and all-cause mortality. J Am Coll Cardiol. 2013;62(10):921-925. doi:10.1016/j.jacc.2013.06.027.</mixed-citation><mixed-citation xml:lang="en">Britton K. A., Massaro J. M., Murabito J. M. et al. Body fat distribution, incident cardiovascular disease, cancer, and all-cause mortality. J Am Coll Cardiol. 2013;62(10):921-925. doi:10.1016/j.jacc.2013.06.027.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Bibiloni M. D.M., Karam J., Bouzas C. et al. Association between Physical Condition and Body Composition, Nutrient Intake, Sociodemographic Characteristics, and Lifestyle Habits in Older Spanish Adults. Nutrients. 2018;10(11):1608. doi:10.3390/nu10111608.</mixed-citation><mixed-citation xml:lang="en">Bibiloni M. D.M., Karam J., Bouzas C. et al. Association between Physical Condition and Body Composition, Nutrient Intake, Sociodemographic Characteristics, and Lifestyle Habits in Older Spanish Adults. Nutrients. 2018;10(11):1608. doi:10.3390/nu10111608.</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Tur J. A., Bibiloni M. D.M. Anthropometry, Body Composition and Resting Energy Expenditure in Human. Nutrients. 2019;11(8):1891. doi:10.3390/nu11081891.</mixed-citation><mixed-citation xml:lang="en">Tur J. A., Bibiloni M. D.M. Anthropometry, Body Composition and Resting Energy Expenditure in Human. Nutrients. 2019;11(8):1891. doi:10.3390/nu11081891.</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Sun J. Y., Hua Y., Zou H. Y. et al. Association Between Waist Circumference and the Prevalence of (Pre) Hypertension Among 27,894 US Adults. Front Cardiovasc Med. 2021;8:717257. doi:10.3389/fcvm.2021.717257.</mixed-citation><mixed-citation xml:lang="en">Sun J. Y., Hua Y., Zou H. Y. et al. Association Between Waist Circumference and the Prevalence of (Pre) Hypertension Among 27,894 US Adults. Front Cardiovasc Med. 2021;8:717257. doi:10.3389/fcvm.2021.717257.</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Seyedhoseinpour A., Barzin M., Mahdavi M. et al. BMI category-specific waist circumference thresholds based on cardiovascular disease outcomes and all-cause mortality: Tehran lipid and glucose study (TLGS). BMC Public Health. 2023;23(1):1297. doi:10.1186/s12889-023-16190-w.</mixed-citation><mixed-citation xml:lang="en">Seyedhoseinpour A., Barzin M., Mahdavi M. et al. BMI category-specific waist circumference thresholds based on cardiovascular disease outcomes and all-cause mortality: Tehran lipid and glucose study (TLGS). BMC Public Health. 2023;23(1):1297. doi:10.1186/s12889-023-16190-w.</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Wang J., Thornton J. C., Kolesnik S., Pierson R. N. Jr. Anthropometry in body composition. An overview. Ann N Y Acad Sci. 2000;904:317-326. doi: 10.1111/j.1749-6632.2000.tb06474.x.</mixed-citation><mixed-citation xml:lang="en">Wang J., Thornton J. C., Kolesnik S., Pierson R. N. Jr. Anthropometry in body composition. An overview. Ann N Y Acad Sci. 2000;904:317-326. doi: 10.1111/j.1749-6632.2000.tb06474.x.</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Alberti K. G., Zimmet P. Z. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998;15(7):539-553. doi: 10.1002/(SICI)1096-9136(199807)15:7&lt;539:: AID-DIA668&gt;3.0.CO;2-S.</mixed-citation><mixed-citation xml:lang="en">Alberti K. G., Zimmet P. Z. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998;15(7):539-553. doi: 10.1002/(SICI)1096-9136(199807)15:7&lt;539:: AID-DIA668&gt;3.0.CO;2-S.</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Ludescher B., Machann J., Eschweiler G. W. et al. Correlation of fat distribution in whole body MRI with generally used anthropometric data. Invest Radiol. 2009;44(11):712-719. doi:10.1097/RLI.0b013e3181afbb1e.</mixed-citation><mixed-citation xml:lang="en">Ludescher B., Machann J., Eschweiler G. W. et al. Correlation of fat distribution in whole body MRI with generally used anthropometric data. Invest Radiol. 2009;44(11):712-719. doi:10.1097/RLI.0b013e3181afbb1e.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Romantsova T. I., Poluboyarinova I. V., Roik O. V. Dynamics of adipose tissue changes measured by MRI in obese patients during Reduxin treatment. Obesity and metabolism. 2012;9(4):39-43. (In Russ.) doi:10.14341/2071-8713-5128.@@ Романцова Т. И., Полубояринова И. В., Роик О. В. Динамика состояния жировой ткани по данным МР-томографии у больных ожирением на фоне лечения Редуксином. Ожирение и метаболизм. 2012;9(4):39-43. doi:10.14341/2071-8713-5128.</mixed-citation><mixed-citation xml:lang="en">Romantsova T. I., Poluboyarinova I. V., Roik O. V. Dynamics of adipose tissue changes measured by MRI in obese patients during Reduxin treatment. Obesity and metabolism. 2012;9(4):39-43. (In Russ.) doi:10.14341/2071-8713-5128.@@ Романцова Т. И., Полубояринова И. В., Роик О. В. Динамика состояния жировой ткани по данным МР-томографии у больных ожирением на фоне лечения Редуксином. Ожирение и метаболизм. 2012;9(4):39-43. doi:10.14341/2071-8713-5128.</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Brel N. K., Kokov A. N., Gruzdeva O. V. Advantages and disadvantages of different methods for diagnosis of visceral obesity. Obesity and metabolism. 2018;15(4):3-8. (In Russ.) doi:10.14341/omet9510.@@ Брель Н. К., Коков А. Н., Груздева О. В. Достоинства и ограничения различных методов диагностики висцерального ожирения. Ожирение и метаболизм. 2018;15(4):3-8. doi:10.14341/omet9510.</mixed-citation><mixed-citation xml:lang="en">Brel N. K., Kokov A. N., Gruzdeva O. V. Advantages and disadvantages of different methods for diagnosis of visceral obesity. Obesity and metabolism. 2018;15(4):3-8. (In Russ.) doi:10.14341/omet9510.@@ Брель Н. К., Коков А. Н., Груздева О. В. Достоинства и ограничения различных методов диагностики висцерального ожирения. Ожирение и метаболизм. 2018;15(4):3-8. doi:10.14341/omet9510.</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Kokov A. N., Brel N. K., Masenko V. L. et al. Quantitative assessment of visceral adipose depot in patients with ischemic heart disease by using of modern tomographic methods.Complex Issues of Cardiovascular Diseases. 2017;(3):113-119. (In Russ.) doi:10.17802/2306-1278-2017-6-3-113-119.@@ Коков А. Н., Брель Н. К., Масенко В. Л. и др. Количественная оценка висцерального жирового депо у больных ишемической болезнью сердца с использованием современных томографических методик. Комплексные проблемы сердечно-сосудистых заболеваний. 2017;(3):113-119. doi:10.17802/2306-1278-2017-6-3-113-119.</mixed-citation><mixed-citation xml:lang="en">Kokov A. N., Brel N. K., Masenko V. L. et al. Quantitative assessment of visceral adipose depot in patients with ischemic heart disease by using of modern tomographic methods.Complex Issues of Cardiovascular Diseases. 2017;(3):113-119. (In Russ.) doi:10.17802/2306-1278-2017-6-3-113-119.@@ Коков А. Н., Брель Н. К., Масенко В. Л. и др. Количественная оценка висцерального жирового депо у больных ишемической болезнью сердца с использованием современных томографических методик. Комплексные проблемы сердечно-сосудистых заболеваний. 2017;(3):113-119. doi:10.17802/2306-1278-2017-6-3-113-119.</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">Heymsfield S. B., Bourgeois B., Ng B. K. et al. Digital anthropometry: a critical review. Eur J Clin Nutr. 2018;72(5):680-687. doi:10.1038/s41430-018-0145-7.</mixed-citation><mixed-citation xml:lang="en">Heymsfield S. B., Bourgeois B., Ng B. K. et al. Digital anthropometry: a critical review. Eur J Clin Nutr. 2018;72(5):680-687. doi:10.1038/s41430-018-0145-7.</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Mocini E., Cammarota C., Frigerio F. et al. Digital Anthropometry: A Systematic Review on Precision, Reliability and Accuracy of Most Popular Existing Technologies. Nutrients. 2023;15(2):302. doi:10.3390/nu15020302.</mixed-citation><mixed-citation xml:lang="en">Mocini E., Cammarota C., Frigerio F. et al. Digital Anthropometry: A Systematic Review on Precision, Reliability and Accuracy of Most Popular Existing Technologies. Nutrients. 2023;15(2):302. doi:10.3390/nu15020302.</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Graybeal A. J., Brandner C. F., Tinsley G. M. Evaluation of automated anthropometrics produced by smartphone-based machine learning: a comparison with traditional anthropometric assessments. Br J Nutr. 2023;130(6):1077-1087. doi:10.1017/S0007114523000090.</mixed-citation><mixed-citation xml:lang="en">Graybeal A. J., Brandner C. F., Tinsley G. M. Evaluation of automated anthropometrics produced by smartphone-based machine learning: a comparison with traditional anthropometric assessments. Br J Nutr. 2023;130(6):1077-1087. doi:10.1017/S0007114523000090.</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">Demura S., Sato S., Nakada M. et al.Comparison of estimation accuracy of body density between different hydrostatics weighing methods without head submersion. J Physiol Anthropol Appl Human Sci. 2003;22(4):175-179. doi:10.2114/jpa.22.175.</mixed-citation><mixed-citation xml:lang="en">Demura S., Sato S., Nakada M. et al.Comparison of estimation accuracy of body density between different hydrostatics weighing methods without head submersion. J Physiol Anthropol Appl Human Sci. 2003;22(4):175-179. doi:10.2114/jpa.22.175.</mixed-citation></citation-alternatives></ref><ref id="cit42"><label>42</label><citation-alternatives><mixed-citation xml:lang="ru">Borga M., West J., Bell J. D. et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med. 2018;66(5):1-9. doi:10.1136/jim-2018-000722.</mixed-citation><mixed-citation xml:lang="en">Borga M., West J., Bell J. D. et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med. 2018;66(5):1-9. doi:10.1136/jim-2018-000722.</mixed-citation></citation-alternatives></ref><ref id="cit43"><label>43</label><citation-alternatives><mixed-citation xml:lang="ru">Smith-Ryan A. E., Mock M. G., Ryan E. D. et al. Validity and reliability of a 4-compartment body composition model using dual energy x-ray absorptiometry-derived body volume. Clin Nutr. 2017;36(3):825-830. doi:10.1016/j.clnu.2016.05.006</mixed-citation><mixed-citation xml:lang="en">Smith-Ryan A. E., Mock M. G., Ryan E. D. et al. Validity and reliability of a 4-compartment body composition model using dual energy x-ray absorptiometry-derived body volume. Clin Nutr. 2017;36(3):825-830. doi:10.1016/j.clnu.2016.05.006</mixed-citation></citation-alternatives></ref><ref id="cit44"><label>44</label><citation-alternatives><mixed-citation xml:lang="ru">Tagliafico A. S., Bignotti B., Torri L., Rossi F. Sarcopenia: how to measure, when and why. Radiol Med. 2022;127(3):228-237. doi:10.1007/s11547-022-01450-3.</mixed-citation><mixed-citation xml:lang="en">Tagliafico A. S., Bignotti B., Torri L., Rossi F. Sarcopenia: how to measure, when and why. Radiol Med. 2022;127(3):228-237. doi:10.1007/s11547-022-01450-3.</mixed-citation></citation-alternatives></ref><ref id="cit45"><label>45</label><citation-alternatives><mixed-citation xml:lang="ru">Elhakim T., Trinh K., Mansur A. et al. Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions. Diagnostics (Basel). 2023;13(5):968. doi: 10.3390/diagnostics13050968.</mixed-citation><mixed-citation xml:lang="en">Elhakim T., Trinh K., Mansur A. et al. Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions. Diagnostics (Basel). 2023;13(5):968. doi: 10.3390/diagnostics13050968.</mixed-citation></citation-alternatives></ref><ref id="cit46"><label>46</label><citation-alternatives><mixed-citation xml:lang="ru">Su H., Ruan J., Chen T. et al. CT-assessed sarcopenia is a predictive factor for both long-term and short-term outcomes in gastrointestinal oncology patients: a systematic review and meta-analysis. Cancer Imaging. 2019;19(1):82. doi:10.1186/s40644-019-0270-0.</mixed-citation><mixed-citation xml:lang="en">Su H., Ruan J., Chen T. et al. CT-assessed sarcopenia is a predictive factor for both long-term and short-term outcomes in gastrointestinal oncology patients: a systematic review and meta-analysis. Cancer Imaging. 2019;19(1):82. doi:10.1186/s40644-019-0270-0.</mixed-citation></citation-alternatives></ref><ref id="cit47"><label>47</label><citation-alternatives><mixed-citation xml:lang="ru">Palmas F., Ciudin A., Guerra R. et al.Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity. Front Endocrinol (Lausanne). 2023;14:1161116. doi:10.3389/fendo.2023.1161116.</mixed-citation><mixed-citation xml:lang="en">Palmas F., Ciudin A., Guerra R. et al.Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity. Front Endocrinol (Lausanne). 2023;14:1161116. doi:10.3389/fendo.2023.1161116.</mixed-citation></citation-alternatives></ref><ref id="cit48"><label>48</label><citation-alternatives><mixed-citation xml:lang="ru">Fischer M., Küstner T., Pappa S. et al. Identification of radiomic biomarkers in a set of four skeletal muscle groups on Dixon MRI of the NAKO MR study. BMC Med Imaging. 2023;23(1):104. doi:10.1186/s12880-023-01056.</mixed-citation><mixed-citation xml:lang="en">Fischer M., Küstner T., Pappa S. et al. Identification of radiomic biomarkers in a set of four skeletal muscle groups on Dixon MRI of the NAKO MR study. BMC Med Imaging. 2023;23(1):104. doi:10.1186/s12880-023-01056.</mixed-citation></citation-alternatives></ref><ref id="cit49"><label>49</label><citation-alternatives><mixed-citation xml:lang="ru">Foster K. R., Lukaski H. C. Whole-body impedance - what does it measure?. Am J Clin Nutr. 1996;64(3 Suppl):388S-396S. doi:10.1093/ajcn/64.3.388S.</mixed-citation><mixed-citation xml:lang="en">Foster K. R., Lukaski H. C. Whole-body impedance - what does it measure?. Am J Clin Nutr. 1996;64(3 Suppl):388S-396S. doi:10.1093/ajcn/64.3.388S.</mixed-citation></citation-alternatives></ref><ref id="cit50"><label>50</label><citation-alternatives><mixed-citation xml:lang="ru">Kyle U. G., Bosaeus I., De Lorenzo A. D. et al. Bioelectrical impedance analysis - part I: review of principles and methods. Clin Nutr. 2004;23(5):1226-1243. doi:10.1016/j.clnu.2004.06.004.</mixed-citation><mixed-citation xml:lang="en">Kyle U. G., Bosaeus I., De Lorenzo A. D. et al. Bioelectrical impedance analysis - part I: review of principles and methods. Clin Nutr. 2004;23(5):1226-1243. doi:10.1016/j.clnu.2004.06.004.</mixed-citation></citation-alternatives></ref><ref id="cit51"><label>51</label><citation-alternatives><mixed-citation xml:lang="ru">Gonzalez M. C., Barbosa-Silva T. G., Bielemann R. M. et al. Phase angle and its determinants in healthy subjects: influence of body composition. Am J Clin Nutr. 2016;103(3):712-716. doi:10.3945/ajcn.115.116772.</mixed-citation><mixed-citation xml:lang="en">Gonzalez M. C., Barbosa-Silva T. G., Bielemann R. M. et al. Phase angle and its determinants in healthy subjects: influence of body composition. Am J Clin Nutr. 2016;103(3):712-716. doi:10.3945/ajcn.115.116772.</mixed-citation></citation-alternatives></ref><ref id="cit52"><label>52</label><citation-alternatives><mixed-citation xml:lang="ru">Day K., Kwok A., Evans A. et al.Comparison of a Bioelectrical Impedance Device against the Reference Method Dual Energy X-Ray Absorptiometry and Anthropometry for the Evaluation of Body Composition in Adults. Nutrients. 2018;10(10):1469. doi:10.3390/nu10101469.</mixed-citation><mixed-citation xml:lang="en">Day K., Kwok A., Evans A. et al.Comparison of a Bioelectrical Impedance Device against the Reference Method Dual Energy X-Ray Absorptiometry and Anthropometry for the Evaluation of Body Composition in Adults. Nutrients. 2018;10(10):1469. doi:10.3390/nu10101469.</mixed-citation></citation-alternatives></ref><ref id="cit53"><label>53</label><citation-alternatives><mixed-citation xml:lang="ru">Earthman C., Traughber D., Dobratz J., Howell W. Bioimpedance spectroscopy for clinical assessment of fluid distribution and body cell mass. Nutr Clin Pract. 2007;22(4):389-405. doi:10.1177/0115426507022004389.</mixed-citation><mixed-citation xml:lang="en">Earthman C., Traughber D., Dobratz J., Howell W. Bioimpedance spectroscopy for clinical assessment of fluid distribution and body cell mass. Nutr Clin Pract. 2007;22(4):389-405. doi:10.1177/0115426507022004389.</mixed-citation></citation-alternatives></ref><ref id="cit54"><label>54</label><citation-alternatives><mixed-citation xml:lang="ru">Barrera Ortega S., Redondo Del Río P., Carreño Enciso L. et al. Phase Angle as a Prognostic Indicator of Survival in Institutionalized Psychogeriatric Patients. Nutrients. 2023;15(9):2139. doi:10.3390/nu15092139.</mixed-citation><mixed-citation xml:lang="en">Barrera Ortega S., Redondo Del Río P., Carreño Enciso L. et al. Phase Angle as a Prognostic Indicator of Survival in Institutionalized Psychogeriatric Patients. Nutrients. 2023;15(9):2139. doi:10.3390/nu15092139.</mixed-citation></citation-alternatives></ref><ref id="cit55"><label>55</label><citation-alternatives><mixed-citation xml:lang="ru">Merli P., Furnari R., Fadda M. et al. Role of Bioelectrical Impedance Analysis in the Evaluation of Patients with Upper Limb Lymphedema. Lymphat Res Biol. 2020;18(6):555-559. doi:10.1089/lrb.2019.0085.</mixed-citation><mixed-citation xml:lang="en">Merli P., Furnari R., Fadda M. et al. Role of Bioelectrical Impedance Analysis in the Evaluation of Patients with Upper Limb Lymphedema. Lymphat Res Biol. 2020;18(6):555-559. doi:10.1089/lrb.2019.0085.</mixed-citation></citation-alternatives></ref><ref id="cit56"><label>56</label><citation-alternatives><mixed-citation xml:lang="ru">Hernández-Ortega A., Osuna-Padilla I. A. Concordancia entre técnicas de composición corporal en niños y adolescentes: revisión narrativa de la literatura [Agreement between body composition techniques in children and adolescents: narrative review of the literature]. Rev Med Inst Mex Seguro Soc. 2020;58(2):181-196. doi:10.24875/RMIMSS.M20000016.</mixed-citation><mixed-citation xml:lang="en">Hernández-Ortega A., Osuna-Padilla I. A. Concordancia entre técnicas de composición corporal en niños y adolescentes: revisión narrativa de la literatura [Agreement between body composition techniques in children and adolescents: narrative review of the literature]. Rev Med Inst Mex Seguro Soc. 2020;58(2):181-196. doi:10.24875/RMIMSS.M20000016.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
