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dc.contributor.authorHetherington-Rauth, Megan
dc.contributor.authorBea, Jennifer W.
dc.contributor.authorLee, Vinson R.
dc.contributor.authorBlew, Robert M.
dc.contributor.authorFunk, Janet
dc.contributor.authorLohman, Timothy G.
dc.contributor.authorGoing, Scott B.
dc.date.accessioned2017-04-12T18:08:27Z
dc.date.available2017-04-12T18:08:27Z
dc.date.issued2017-02-23
dc.identifier.citationComparison of direct measures of adiposity with indirect measures for assessing cardiometabolic risk factors in preadolescent girls 2017, 16 (1) Nutrition Journalen
dc.identifier.issn1475-2891
dc.identifier.pmid28231807
dc.identifier.doi10.1186/s12937-017-0236-7
dc.identifier.urihttp://hdl.handle.net/10150/623119
dc.description.abstractBackground: Childhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages. It is unclear which measures of adiposity serve as the best proxies for identifying children at metabolic risk. This study assessed whether DXA-derived direct measures of adiposity are more strongly related to cardiometabolic risk factors in children than indirect measures. Methods: Anthropometric and DXA measures of adiposity and a comprehensive assessment of cardiometabolic risk factors were obtained in 288, 9-12 year old girls, most being of Hispanic ethnicity. Multiple regression models for each metabolic parameter were run against each adiposity measure while controlling for maturation and ethnicity. In addition, regression models including both indirect and direct measures were developed to assess whether using direct measures of adiposity could provide a better prediction of the cardiometabolic risk factors beyond that of using indirect measures alone. Results: Measures of adiposity were significantly correlated with cardiometabolic risk factors (p < 0.05) except fasting glucose. After adjusting for maturation and ethnicity, indirect measures of adiposity accounted for 29-34% in HOMA-IR, 10-13% in TG, 14-17% in HDL-C, and 5-8% in LDL-C while direct measures accounted for 29-34% in HOMA-IR, 10-12% in TG, 13-16% in HDL-C, and 5-6% in LDL-C. The addition of direct measures of adiposity to indirect measures added significantly to the variance explained for HOMA-IR (p = 0.04). Conclusion: Anthropometric measures may perform as well as the more precise direct DXA-derived measures of adiposity for assessing most CVD risk factors in preadolescent girls. The use of DXA-derived adiposity measures together with indirect measures may be advantageous for predicting insulin resistance risk.
dc.description.sponsorshipNational Institute of Child Health and Human Development [HD074565]en
dc.language.isoenen
dc.publisherBIOMED CENTRAL LTDen
dc.relation.urlhttp://nutritionj.biomedcentral.com/articles/10.1186/s12937-017-0236-7en
dc.rights© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License.en
dc.subjectBody compositionen
dc.subjectCardiovascular diseaseen
dc.subjectGirlsen
dc.titleComparison of direct measures of adiposity with indirect measures for assessing cardiometabolic risk factors in preadolescent girlsen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Dept Nutr Scien
dc.contributor.departmentUniv Arizona, Dept Meden
dc.contributor.departmentUniv Arizona, Ctr Cancen
dc.contributor.departmentUniv Arizona, Dept Physiolen
dc.contributor.departmentUniv Arizona, Coll Agr & Life Sci, Dept Nutr Scien
dc.identifier.journalNutrition Journalen
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-06-28T23:30:15Z
html.description.abstractBackground: Childhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages. It is unclear which measures of adiposity serve as the best proxies for identifying children at metabolic risk. This study assessed whether DXA-derived direct measures of adiposity are more strongly related to cardiometabolic risk factors in children than indirect measures. Methods: Anthropometric and DXA measures of adiposity and a comprehensive assessment of cardiometabolic risk factors were obtained in 288, 9-12 year old girls, most being of Hispanic ethnicity. Multiple regression models for each metabolic parameter were run against each adiposity measure while controlling for maturation and ethnicity. In addition, regression models including both indirect and direct measures were developed to assess whether using direct measures of adiposity could provide a better prediction of the cardiometabolic risk factors beyond that of using indirect measures alone. Results: Measures of adiposity were significantly correlated with cardiometabolic risk factors (p < 0.05) except fasting glucose. After adjusting for maturation and ethnicity, indirect measures of adiposity accounted for 29-34% in HOMA-IR, 10-13% in TG, 14-17% in HDL-C, and 5-8% in LDL-C while direct measures accounted for 29-34% in HOMA-IR, 10-12% in TG, 13-16% in HDL-C, and 5-6% in LDL-C. The addition of direct measures of adiposity to indirect measures added significantly to the variance explained for HOMA-IR (p = 0.04). Conclusion: Anthropometric measures may perform as well as the more precise direct DXA-derived measures of adiposity for assessing most CVD risk factors in preadolescent girls. The use of DXA-derived adiposity measures together with indirect measures may be advantageous for predicting insulin resistance risk.


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