Association between Appendicular Fat Mass and Metabolic Risk Factors.
10.4082/kjfm.2014.35.4.182
- Author:
Si Young PARK
1
;
Kil Young KWON
;
Jung Hwan KIM
;
Hyung Hwa CHOI
;
Kun Hee HAN
;
Jee Hye HAN
Author Information
1. Department of Family Medicine, Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea. hnjh66@daum.net
- Publication Type:Original Article
- Keywords:
Metabolic Syndrome;
Body Fat Distribution;
Android Fat;
Appendicular Fat;
Dual-Energy X-ray Absorptiometry
- MeSH:
Absorptiometry, Photon;
Anthropometry;
Arm;
Blood Pressure;
Body Composition;
Body Fat Distribution;
Cholesterol;
Cholesterol, HDL;
Cholesterol, LDL;
Glucose;
Hematologic Tests;
Humans;
Insulin;
Leg;
Lipoproteins;
Male;
Metabolism;
Risk Factors*;
Triglycerides;
Waist Circumference
- From:Korean Journal of Family Medicine
2014;35(4):182-189
- CountryRepublic of Korea
- Language:English
-
Abstract:
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.
