Rasvaprosenttia voidaan mitata monilla eri tavoilla. Bioimpedanssimittaus on kiinnostava mm. siitä syystä, että markkinoilla on edullisia laitteita kotikäyttöön. Näyttäisivät olevan ihan hyödyllisiä laitteita.

http://www.ncbi.nlm....pubmed/22257993

RESULTS:

Metabolic syndrome was detected in 751 participants (520 women and 231 men with a mean age of 55 [12] years; 34% of the whole study population). Total body fat and visceral fat levels were higher in subjects with MetS.Correlation analyses showed that there were significant correlations between anthropometric and BIA measurements. Receiver operating curve characteristics of visceral adiposity revealed the best cutoff values as greater than 12% for men and greater than 9% for women.The diagnostic performance was good in both sexes (the sensitivity/specificity and area-under-the-curve values were 76%/75% and 0.83 for men and 83%/67% and 0.81 for women, respectively).

CONCLUSIONS:Visceral fat measured with BIA is an easily applicable and useful method for identifying people with MetS. The best cutoff values were higher than 12% for men and higher than 9% for women.

http://www.ncbi.nlm....pubmed/23239610

RESULTS:

Overall %BF was 33.5 ± 10.5% (Tanita SC-240) vs. 34.5 ± 8.7% (DXA). There was no significant difference between the two measures (P = 0.52, average error = -1.0%, average absolute error = 3.9%). The Tanita mean %BF estimates significantly differed from the DXA mean %BF in white boys (P = 0.001, Cohen's d = 0.40) and white girls (P = 0.006, Cohen's d = 0.48), but differences were of small effect. No differences in %BF estimates were found for African-American boys or girls.

CONCLUSIONS:In this sample, the Tanita SC-240 demonstrated acceptable accuracy for estimating %BF when compared with DXA, supporting its use in field studies.

http://www.ncbi.nlm....pubmed/15056180

In the present study, hand-to-hand bioelectrical impedance analysis (BIA), skinfold (SKF) thickness and height-weight (body mass index, BMI)-based equations and dual-energy X-ray absorptiometry (DEXA), as a criterion method, were compared with each other in the assessment of body fat percentage (BF%) in 17-18-year-old Estonian conscripts (n = 32). The Omron BF body fat monitor estimated that BF% was lower than that of the criterion method DEXA.

The difference between DEXA and Omron BF 300 (III) was higher (1.1 +/- 3.0%; P = 0.04) and that between DEXA and Omron BF 306 lower (0.2 +/- 3.0%; P>0.05). Omron BF 300 (I) and (II) (series 8) had intermediate difference (0.9 +/- 3.0 and 0.9 +/- 3.0; P>0.05) when compared with DEXA. Three anthropometric equations estimated a higher BF% than cthat of DEXA. The Durnin & Womersley SKF equation BF% (1.0 +/- 2.4; P = 0.03) was higher than that of the DEXA. Deurenberg et al. and Gallagher et al. BMI-based equations overestimation yielded 0.9 +/- 3.7 and 0.6 +/- 3.8 BF% (P>0.05). From the anthropometric equations, only the Deurenberg et al. SKF equation slightly underestimated 0.5 +/- 3.4 BF% (P>0.05). DEXA-assessed BF% had highest correlation with SKF equations (r = 0.93), less so with BIA (r = 0.88-0.89) and lowest with BMI equation-assessed BF% (r = 0.81-0.84). All values were significant at P<0.001.We can conclude that the Omron BF 306 body fat monitor and the anthropometric Deurenberg et al. SKF equation yielded results close to the DEXA BF%.

http://www.ncbi.nlm....pubmed/19893862

RESULTS:

The estimated fat mass, in men, by the anthropometrical method was 7 +/- 2.2 kg. The results by the BIA systems were: 7.4 +/- 3 kg; 5.6 +/- 2.2 kg; 5.7 +/- 2.5 kg, and 7.4 +/- 3 kg for Biospace Inbody 720, Tanita BC400, Tanita TBF521, and Omron BF300, respectively. In women, the results were 10.4 +/- 2.7 kg of fat mass by means of the anthropometrical method and 10.3 +/- 2.9 kg, 11 +/- 3.3 kg, 11.5 +/- 3.0 kg, and 10 +/- 2.9 kg for Biospace Inbody 720, Tanita BC400, Tanita TBF521, and Omron BF300, respectively.

CONCLUSIONS:

In the male group, the level of agreement between anthropometrics and BIA devices was moderate-poor, whereas in women there was a good correlation between both techniques for estimating the body fat when the Biospace Inbody 720 and Tanita BC400 devices were used.

http://www.ncbi.nlm....pubmed/11248873

RESULTS:

The 4-component model gave 0.6 (95% confidence interval for the mean, CI: 0.1 to 1.2) BF% higher results than UWW. Also the 3-component model with body density and total body water (+1.4 BF%, 95% CI: +0.3 to +2.6), deuterium dilution (+1.5 BF%, 95% CI: +0.7 to +2.3), DXA by Norland (+7.2 BF%, 95% CI: 2.6 to 11.8) andBIA by Lukaski et al. (+2.0 BF%, 95% CI: 0.2 to 3.8) overestimated BF%, whereas BIA by Valhalla Scientific (-2.6 BF%, 95% CI: -4.5 to -0.6) and skinfold equations by Jackson et al. (-1.20, 95% CI: -2.3 to -0.1) showed a relative underestimation. The mean bias for the skinfold equation by Durnin & Womersley, against UWW, was 0.0 BF% (95% CI: -1.3 to 1.3). The correlation between the size of measurement and the mean difference was significant for only NIR (r = -0.77, P = 0.003).

CONCLUSIONS:

The difference between any method and UWW is dependent on the study. However, some methods have a systematical tendency for relative over- or underestimation of BF%.

http://www.ncbi.nlm..../pubmed/9756243

RESULTS:

Mean %BF assessed by DEXA (%BF(DEXA)) was similar to that estimated by SKF (%BF(SKF)) in males, while %BF(DEXA) was slightly higher in females. %BF estimated by BIA (%BF(BIA)) was significantly lower than %BF(DEXA) in females, regardless of equations used for calculation, while the level of agreement between BIA and DEXA in estimating %BF in males was dependent on prediction equations used for calculation of %BF(BIA). A better agreement was obtained from the use on the prediction equations of Segal et al (1988), compared to other two sets of equations. The agreement between SKF or BIA and DEXA declined with increasing %BF.

CONCLUSIONS:

There was a good agreement between DEXA and SKF, and slightly less so between DEXA and BIA, in estimating %BF in an Anglo-Celtic adult population. The agreement in most cases, however, was dependent on the degree of body fatness.In comparison to DEXA, both SKF and BIA, with the use of the equations of Segal et al (1988), are applicable to estimate %BF in an Anglo-Celtic Australian population.

http://www.ncbi.nlm....pubmed/14618493

Childhood obesity increases the risk of morbidity whether or not obesity persists into adulthood. Measurement of body fat content using bioimpedance analysis (BIA) is a useful tool in epidemiologic studies. Both tricep skinfold thickness (TST, mm) and body mass index (BMI, kg/m(2)) are indirect, simple methods and easy to perform for assessing body composition. These methods are generally accepted as good clinical measures for defining childhood obesity. The aim of our study was to evaluate fat mass (FM, kg and %) measurements using TST and BIA (50 kHz) in a cohort of 6-year-old Italian children. A total of 228 southern Italian children (121 boys, 107 girls), randomly selected in nine local primary schools, were included in the study. The correlation between methods for measuring FM was calculated.

Linear regression analysis showed a significant positive correlation between FM measured with BIA and BMI ( r=0.92, p<0.001)and with TST ( r=0.79, p<0.001). We conclude that FM measurement using TST and BIA is comparable in different BMI ranges. However,BIA is a useful and alternative method for detecting body composition in children and may be a more precise tool than TST for measuring FM in epidemiological studies in pediatric populations.

http://www.ncbi.nlm....pubmed/18239555

RESULTS:

Compared to DXA, both BIA devices provided on average 2-6% lower values for FM% in normal BMI men, in women in all BMI categories, and in both genders in both HPA and LPA groups. In obese men, the differences were smaller. The two BIA devices provided similar means for groups. Differences between the two BIA devices with increasing FM% were a result of the InBody (720) not including age in their algorithm for estimating body composition.

DISCUSSION:BIA methods provided systematically lower values for FM than DXA. However, the differences depend on gender and body weight status pointing out the importance of considering these when identifying people with excess FM.

http://www.ncbi.nlm....pubmed/17936443

ESULTS:

MF-BIA estimates of body composition showed good absolute agreement with DXA, as evidenced by the small biases in the estimation of fat free mass (FFM), fat mass (FM) and percentage body fat (BF%); however, the limits of agreement for each variable were wide (bias +/-1.96 standard deviation; FFM -1.6+/-6.5 kg, FM 1.6+/-6.5 kg, BF% 1.4+/-6.3%). SF-BIA exhibited a larger bias with wide limits of agreement (FFM 3.8+/-9.1 kg, FM -3.8+/-9.1 kg, BF% -4.37+/-10.3%). During weight loss the values provided by MF-BIA and SF-BIA were not significantly different from DXA (p> or =0.89) due to small bias and the limits of agreement were narrow (MF-BIA: FFM -0.01+/-3.74 kg, FM 0.01+/-3.74 kg, BF% 0.22+/-3.40%; SF-BIA: FFM 0.40+/-3.92 kg, FM -0.40+/-3.92 kg, BF% 0.25+/-3.40%).

CONCLUSION:

Compared with DXA, both the MF-BIA and SF-BIA accurately assessed changes in body composition with weight loss but, compared with SF-BIA, MF-BIA provided superior cross-sectional estimates of body composition.