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Association between Appendicular Fat Mass and Metabolic Risk Factors

BACKGROUND: Different regional fat depots have different effects on lipid and glucose metabolism. The purpose of this study is to examine the relationship between body fat distribution as measured by dual-energy X-ray absorptiometry (DEXA) and metabolic risk factors and to disclose whether there is...

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Autores principales: Park, Si Young, Kwon, Kil Young, Kim, Jung Hwan, Choi, Hyung Hwa, Han, Kun Hee, Han, Jee Hye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Family Medicine 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4129245/
https://www.ncbi.nlm.nih.gov/pubmed/25120889
http://dx.doi.org/10.4082/kjfm.2014.35.4.182
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author Park, Si Young
Kwon, Kil Young
Kim, Jung Hwan
Choi, Hyung Hwa
Han, Kun Hee
Han, Jee Hye
author_facet Park, Si Young
Kwon, Kil Young
Kim, Jung Hwan
Choi, Hyung Hwa
Han, Kun Hee
Han, Jee Hye
author_sort Park, Si Young
collection PubMed
description BACKGROUND: Different regional fat depots have different effects on lipid and glucose metabolism. The purpose of this study is to examine the relationship between body fat distribution as measured by dual-energy X-ray absorptiometry (DEXA) and metabolic risk factors and to disclose whether there is any difference between groups with and without metabolic syndrome (MS). METHODS: A total of 292 participants (98 men, 194 women) over 19 years old underwent whole-body DEXA to evaluate body composition with respect to the whole body, leg, arm, and android regions. Anthropometry and blood tests for metabolic risks were measured. RESULTS: One hundred and seven participants were diagnosed with MS. The MS group had significantly higher android fat (%) and had lower leg fat (%), arm fat (%), and appendicular (arms + legs) fat (%) than the non-MS group. Android fat (%) had a positive correlation with waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, log insulin, hemoglobin A1c (HbA1c), triglyceride (TG), and low density lipoprotein cholesterol, and had a negative correlation with high density lipoprotein (HDL) cholesterol. Appendicular fat (%) had a negative correlation with WC, SBP, DBP, glucose, log insulin, HbA1c, and TG, and had a positive correlation with HDL cholesterol. The association of appendicular fat with metabolic risk was consistently observed in non-MS, but the association was not observed except for SBP, glucose and log insulin in MS. CONCLUSION: In contrast with the adverse effects of android fat, appendicular fat distribution was associated with decreased risks of MS. The protective effect of appendicular fat against metabolic risk factors in non-MS was less characteristic in MS.
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spelling pubmed-41292452014-08-12 Association between Appendicular Fat Mass and Metabolic Risk Factors Park, Si Young Kwon, Kil Young Kim, Jung Hwan Choi, Hyung Hwa Han, Kun Hee Han, Jee Hye Korean J Fam Med Original Article BACKGROUND: Different regional fat depots have different effects on lipid and glucose metabolism. The purpose of this study is to examine the relationship between body fat distribution as measured by dual-energy X-ray absorptiometry (DEXA) and metabolic risk factors and to disclose whether there is any difference between groups with and without metabolic syndrome (MS). METHODS: A total of 292 participants (98 men, 194 women) over 19 years old underwent whole-body DEXA to evaluate body composition with respect to the whole body, leg, arm, and android regions. Anthropometry and blood tests for metabolic risks were measured. RESULTS: One hundred and seven participants were diagnosed with MS. The MS group had significantly higher android fat (%) and had lower leg fat (%), arm fat (%), and appendicular (arms + legs) fat (%) than the non-MS group. Android fat (%) had a positive correlation with waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, log insulin, hemoglobin A1c (HbA1c), triglyceride (TG), and low density lipoprotein cholesterol, and had a negative correlation with high density lipoprotein (HDL) cholesterol. Appendicular fat (%) had a negative correlation with WC, SBP, DBP, glucose, log insulin, HbA1c, and TG, and had a positive correlation with HDL cholesterol. The association of appendicular fat with metabolic risk was consistently observed in non-MS, but the association was not observed except for SBP, glucose and log insulin in MS. CONCLUSION: In contrast with the adverse effects of android fat, appendicular fat distribution was associated with decreased risks of MS. The protective effect of appendicular fat against metabolic risk factors in non-MS was less characteristic in MS. The Korean Academy of Family Medicine 2014-07 2014-07-25 /pmc/articles/PMC4129245/ /pubmed/25120889 http://dx.doi.org/10.4082/kjfm.2014.35.4.182 Text en Copyright © 2014 The Korean Academy of Family Medicine http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Park, Si Young
Kwon, Kil Young
Kim, Jung Hwan
Choi, Hyung Hwa
Han, Kun Hee
Han, Jee Hye
Association between Appendicular Fat Mass and Metabolic Risk Factors
title Association between Appendicular Fat Mass and Metabolic Risk Factors
title_full Association between Appendicular Fat Mass and Metabolic Risk Factors
title_fullStr Association between Appendicular Fat Mass and Metabolic Risk Factors
title_full_unstemmed Association between Appendicular Fat Mass and Metabolic Risk Factors
title_short Association between Appendicular Fat Mass and Metabolic Risk Factors
title_sort association between appendicular fat mass and metabolic risk factors
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4129245/
https://www.ncbi.nlm.nih.gov/pubmed/25120889
http://dx.doi.org/10.4082/kjfm.2014.35.4.182
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