Association between Appendicular Fat Mass and Metabolic Risk Factors

Abstract

BackgroundDifferent 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).MethodsA 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.ResultsOne 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.ConclusionIn 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.

Specific characterization of regional storage fat in upper and lower limbs of young healthy adults

“…Pathophysiological relevance to assess appendicular regional fat and muscle distribution would be revealed in the fact that greater fat mass distributed in appendicular sites, such as lower limbs, appears to be beneficial or protective against cardiovascular disease and/or metabolic risk factors as compared with central obesity (Hu et al 2011 ; Park et al 2014 ; Snijder et al 2009 ). These protective effects of appendicular fat might be mostly attributed to the leg, especially thigh (Hunter et al 2010 ; Park et al 2014 ; Snijder et al 2005 ). On the other hand, the study using DEXA to evaluate percentage of fat has shown less impact of upper limbs on diagnosing metabolic disease compared to lower limbs (Park et al 2014 ).…”

“…These protective effects of appendicular fat might be mostly attributed to the leg, especially thigh (Hunter et al 2010 ; Park et al 2014 ; Snijder et al 2005 ). On the other hand, the study using DEXA to evaluate percentage of fat has shown less impact of upper limbs on diagnosing metabolic disease compared to lower limbs (Park et al 2014 ). It is possible, however, that DEXA- or BIA-derived percentage of fat does not reflect site-specific fat and muscle distribution, thereby missing the association between regional limb composition and diagnostic criterion.…”

Relationship between fat distribution and cardiometabolic risk in Hispanic girls

“…Fat within the abdominal region, in adults, is more strongly related with metabolic complications than total excess body fat (Despres & Lemieux, 2006). In contrast, adipose tissue located at peripheral sites, such as the thigh and legs, appears to be protective against metabolic syndrome (Park et al, 2014). Moreover, in adults, subcutaneous fat appears to be less metabolically deleterious than fat distributed within visceral depots or within muscle (Bastien et al, 2014).…”

“…Inconsistent findings could be due to multiple factors such as the fat depot studied, the metabolic biomarkers assessed, variation in total body fat, and the ethnicity of the population being studied. It has been suggested that the amount and location of fat depots may have differential relationships with different risk factors (Park et al, 2014; Sanchez-Lopez et al, 2013). For example, Samouda et al found that visceral adipose tissue had significant positive correlations with triglycerides (TG) and high density lipoprotein cholesterol (HDL-C), whereas leg fat mass did not have a significant correlation with TG, but had a significant positive correlation with HDL-C in overweight and obese children (Samouda et al, 2016).…”

Comments on Statistical Issues in September 2014

“…In this section, we explain the assumptions in the analysis of covariance and the relationship between the magnitudes of correlation coefficient and P-value, which appeared in the articles titled, "Association between nutrition label reading and nutrient Intake in Korean adults: Korea National Health and Nutritional Examination Survey, 2007-2009 (KNHANES IV)," by Kim et al 1) and "Association between appendicular fat mass and metabolic risk factors," by Park et al 2) published in July 2014.…”