Significance Of Using BIA Technology To Measure Body Fat Percentage On The Studies Of Obesity And Its Relative Diseases

Objective To analyze the correlation of % body fat with ahthropometic and metabolic variables, further more, to explore the significance of % body fat on the studies of obesity and its relative diseases.Methods (1) The common informations of 86 persons who wanted to examine themselves by oral glucose tolerance test were invesgated. % Body fat, stature, weight, fasting total cholesterol, fasting triglyceride and blood pressure and other indexes were measured. Some indexes reflecting the function of pancreas island were calculated. Relative analysis, stepwise multiple regression analysis and ANOVA were used to study the relationship between % body fat and other indexes. (2) The common informations of 44 persons who wanted to examine themselves by oral glucose tolerance test were invesgated. % Body fat, stature, weight, waist circumference, hip circumference, thickness of fatty mass on shoulder, abdomen and below kidney were all measured. Principal component analysis was used to study the significance of each index about obesity.Results (1) %BF was significantly correlated with BMI, FINS, ESTS2h, AIC, WC, PG2h, HDL, Sex(P<0.05), especially with BMI and AIC (r>0. 5). And %BF had weak correlations with FINS and PG2h. On the other hand, %BF had no correlation with Age, DBF, FPG, HC, IAI, IR, LDL, SBP, TC, TG and WHR (P^O.05) . Furthermore, two multiple stepwise models were made, which were:AIC=1. 1316INS2K+253. 056(%BF)-2. 295FPG+1. 361FINS+1. 205%BF=(1. 17E-2)BMI+0. HSex+(l. 881E-2)AIC+0. 23WC-0. 275 (2) One linear Regression model was made: %BF=(1.795E-2)BMI-0.146. The selected subjects with DM were divided into two groups according to %BF>0.3 or <0.3. ANOVA showed that levels of PG2h were different in two groups (P<0.05) , but FPG, SBP, HDL, DBP, TC, TG and LDL were not different (PX).05) . (3) CV of OD was much higher than that of other indexes (>130%) . And CV of BMI, WC, HC and WHR was Iow(<20%). There were significant correlations among almost all indexes. OD was correlated with the other indexes except for WHR. WHR was correlated with WC, but had weak correlation with other indexes. Three factors were selected through principal component analysis, whose effection was above 85% (86.733%)?Conclusions (1) %BF was strongly correlated with AIC, Sex, WC and BMI. (2) OD, BMI and WHR contributed to obesity more than the other indexes while %BF was not better than others.