{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T15:19:50Z","timestamp":1766157590929},"reference-count":36,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2012,11,7]],"date-time":"2012-11-07T00:00:00Z","timestamp":1352246400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["American J Hum Biol"],"published-print":{"date-parts":[[2013,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p><jats:bold>Objectives<\/jats:bold>: This study aimed to assess the accuracy and concordance of anthropometrically derived prediction equations for the estimation of regional fat mass (FM) distribution.<\/jats:p><jats:p><jats:bold>Methods<\/jats:bold>: Sixty\u2010two white males and 50 females with a large range of age (20\u221255 years) and BMI (16.6\u221233.4 kg\/m<jats:sup>2<\/jats:sup>) were included. Whole body dual energy X\u2010ray absorptiometry (DXA) scans were acquired and anthropometric prediction equations for regional FM were developed and cross\u2010validated. On the basis of the total sample two anthropometrically derived indices of FM distribution\n<jats:styled-content>$\\Big({{{\\rm FM}_{{\\rm trunk}} } \\over {{\\rm FM}_{{\\rm limbs}} }}$<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/tex2gif-ueqn-1.gif\" xlink:title=\"equation image\" \/><\/jats:styled-content>\nratio and <jats:styled-content>${{{\\rm \\%FM}_{{\\rm trunk}} } \\over {{\\rm \\%FM}_{{\\rm legs}} }} \\ {\\rm ratio}\\Big)$<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/tex2gif-ueqn-2.gif\" xlink:title=\"equation image\" \/><\/jats:styled-content>\nwere compared with their DXA analogues.<\/jats:p><jats:p><jats:bold>Results<\/jats:bold>: In both sexes multiple linear regression models predicted the regional DXA fat masses with good accuracy (<jats:italic>P<\/jats:italic> &lt; 0.001). In men mean bias (limits of agreement) were: \u22126.8 g (\u2212535,364) for FM<jats:sub>arms<\/jats:sub>, 65 g (\u22121921,2052) for FM<jats:sub>trunk<\/jats:sub>, \u221221 g (\u22121374,1332) for FM<jats:sub>legs<\/jats:sub>, \u22120.2% (\u22125.0,4.7) for %FM<jats:sub>trunk<\/jats:sub> and \u22120.5% (\u22126.8,5.8) for %FM<jats:sub>legs<\/jats:sub>. In women mean difference (limits of agreement) were: \u221286 g (\u2212463,450) for FM<jats:sub>arms<\/jats:sub>, 30 g (\u22121784,1844) for FM<jats:sub>trunk<\/jats:sub>, \u2212278 g (\u22121782,1227) for FM<jats:sub>legs<\/jats:sub>, 0.4% (\u22125.5,6.3) for %FM<jats:sub>trunk<\/jats:sub>, and 0.3% (\u22128.3,8.9) for %FM<jats:sub>legs<\/jats:sub>. No systematic (constant and proportional) differences between methods for the determination of FM distribution ratios were found, suggesting method interchangeability. The concordance for subject classification based on <jats:italic>t<\/jats:italic>\u2010scores according to the National Health and Nutrition Examination Survey (NHANES) was significant (<jats:italic>P<\/jats:italic> &lt; 0.001), with substantial agreement for\n<jats:styled-content>${{{\\rm FM}_{{\\rm trunk}} } \\over {{\\rm FM}_{{\\rm limbs}} }}$<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/tex2gif-ueqn-3.gif\" xlink:title=\"equation image\" \/><\/jats:styled-content>\nratio (\u03ba<jats:sub>w<\/jats:sub> = 0.80) and <jats:styled-content>${{{\\rm \\%FM}_{{\\rm trunk}} } \\over {{\\rm \\%FM}_{{\\rm legs}} }}$<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/tex2gif-ueqn-4.gif\" xlink:title=\"equation image\" \/><\/jats:styled-content>\nratio (\u03ba<jats:sub>w<\/jats:sub> = 0.75).<\/jats:p><jats:p><jats:bold>Conclusion<\/jats:bold>: Anthropometric variables offer promise to the development of simple, noninvasive, and inexpensive screening to identify individuals with abnormal FM distribution. The anthropometrically derived indices of FM distribution demonstrate sufficient accuracy for clinical use. Am. J. Hum. Biol., 2013. \u00a9 2012 Wiley Periodicals, Inc.<\/jats:p>","DOI":"10.1002\/ajhb.22342","type":"journal-article","created":{"date-parts":[[2012,11,7]],"date-time":"2012-11-07T10:57:20Z","timestamp":1352285840000},"page":"63-70","source":"Crossref","is-referenced-by-count":10,"title":["Accuracy and concordance of anthropometry for measuring regional fat distribution in adults aged 20\u201355 years"],"prefix":"10.1002","volume":"25","author":[{"given":"Aldo","family":"Scafoglieri","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Tresignie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven","family":"Provyn","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mike","family":"Marfell\u2010Jones","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keith","family":"George","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan Pieter","family":"Clarys","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivan","family":"Bautmans","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2012,11,7]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-2275(20)40090-2"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2008.11.021"},{"key":"e_1_2_7_4_1","first-page":"3","volume-title":"Kinanthropometry VIII: Proceedings of the 8th International conference of the International Society for the Advancement of Kinanthropometry (ISAK)","author":"Atkinson G","year":"2003"},{"key":"e_1_2_7_5_1","first-page":"111","article-title":"A canonical analysis of central and peripheral subcutaneous fat distribution and coronary heart disease risk factors in men and women aged 18\u201365 years","volume":"60","author":"Blair SN","year":"1988","journal-title":"Hum Biol"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1385\/JCD:8:3:287"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/ajcn\/52.5.946"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1520-6300(1999)11:2<167::AID-AJHB4>3.0.CO;2-G"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/oby.2009.447"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/ajhb.10165"},{"key":"e_1_2_7_11_1","first-page":"518","article-title":"Prediction of segmental percent fat using anthropometric variables","volume":"45","author":"Demura S","year":"2005","journal-title":"J Sports Med Phys Fitness"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0828-282X(08)71043-2"},{"key":"e_1_2_7_13_1","first-page":"237","article-title":"Emerging risk factors and risk markers for cardiovascular disease: looking beyond NCEP ATP III","volume":"44","author":"Hoffmann TK","year":"2009","journal-title":"Formulary"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1123\/jab.21.4.371"},{"key":"e_1_2_7_15_1","doi-asserted-by":"crossref","first-page":"e7038","DOI":"10.1371\/journal.pone.0007038","article-title":"Dual energy X\u2010ray absorptiometry body composition reference values from NHANES","volume":"4","author":"Kelley TL","year":"2009","journal-title":"PLoS One"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.1172\/JCI111040"},{"key":"e_1_2_7_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.arr.2009.06.001"},{"key":"e_1_2_7_18_1","doi-asserted-by":"publisher","DOI":"10.2307\/2529310"},{"key":"e_1_2_7_19_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.288.6428.1401"},{"key":"e_1_2_7_20_1","volume-title":"International Standards for Anthropometric Assessment. 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