The validity of predicted body fat percentage from body mass index and from impedance in samples of five European populations

OBJECTIVES: To test and compare the validity of a body mass index (BMI)-based prediction equation and an impedance-based prediction equation for body fat percentage among various European population groups. DESIGN: Cross-sectional observational study. SETTINGS: The study was performed in five different European centres: Maastricht and Wageningen (The Netherlands), Milan and Rome (Italy) and Tampere (Finland), where body composition studies are routinely performed. SUBJECTS: A total of 234 females and 182 males, aged 18-70 y, BMI 17.0-41.9 kg/m(2). METHODS: The reference method for body fat percentage (BF%(REF)) was either dual-energy X-ray absorptiometry (DXA) or densitometry (underwater weighing). Body fat percentage (BF%) was also predicted from BMI, age and sex (BF%(BMI)) or with a hand-held impedance analyser that uses in addition to arm impedance weight, height, age and sex as predictors (BF%(IMP)). RESULTS: The overall mean (+/-s.e.) bias (measured minus predicted) for BF%(BMI) was 0.2+/-0.3 (NS) and-0.7+/-0.3 (NS) in females and males, respectively. The bias of BF%(IMP) was 0.2+/-0.2 (NS) and 1.0+/-0.4 (P<0.01) for females and males, respectively. There were significant differences in biases among the centres. The biases were correlated with level of BF% and with age. After correction for differences in age and BF% between the centres the bias of BF%(BMI) was not significantly different from zero in each centre and was not different among the centres anymore. The bias of BF%(IMP) decreased after correction and was significant from zero and significant from the other centres only in males from Tampere. Generally, individual biases can be high, leading to a considerable misclassification of obesity. The individual misclassification was generally higher with the BMI-based prediction. CONCLUSIONS: The prediction formulas give generally good estimates of BF% on a group level in the five population samples, except for the males from Tampere. More comparative studies should be conducted to get better insight in the generalisation of prediction methods and formulas. Individual results and classifications have to be interpreted with caution.     

生物电阻抗法测量肥胖者体脂含量的应用方程

生物电阻抗是近年来被广泛应用的一种快速、简便、安全测量体成分的方法。本研究采用水下称重测量 1 96名 (男性 :66名 ;女性 :1 30名 ) 1 8～ 67岁肥胖受试者的体脂含量 ,并用生物电阻抗方法测定生物电阻抗值。结果表明用水下称重法测量的体脂含量和去脂体重的测量结果与文献中不同国家生物电阻抗推算方程的推算结果有显著的统计学差异 (P <0 0 1 )。本文通过用多元线性逐步回归和方差分析方法建立了适合我国肥胖人群特点的体成分推算方程 :BF =0 846 Wt- 0 1 85 Ht2 z - 2 361 Sex - 2 4 977。Ht:身高(cm) ,Wt:体重 (kg) ,Z :生物电阻抗 (Ω) ,Sex :性别 (男性 =1 ,女性 =0 )。方程的相关系数 :r =0 92 3 ,标准误 :S x=3 43 ,方差分析 (ANOVA)具有统计学意义 (F =365 73 ,P <0 0 0 1 )。     

Analysis of body composition methods in a community sample of African American women

The purposes of the authors in this study were: (1) to determine whether published body mass index and bioelectrical impedance analysis equations agreed with dual energy x-ray absorptiometry body fat percentage measures and (2) to estimate new body mass index and bioelectrical impedance analysis equations in a sample of African American women. Linear regression was used to determine how well 10 body mass index and bioelectrical impedance analysis equations reflected dual energy x-ray absorptiometry body fat percentage measures in this sample of 74 African American women; new body mass index and bioelectrical impedance analysis equations were created using dual energy x-ray absorptiometry body fat percentage measures as the dependent variable. Participants (M = 47.6 years, SD = 7.7) were classified as overweight or obese (BMI Mean BF% = 35.4, SD = 8.2; BIA Mean BF% = 43.3, SD = 6.9; DXA Mean BF% = 41.5, SD = 6.1). R(2) and SEE values indicated that all body mass index and bioelectrical impedance analysis equations were a poorer fit with less precision, and the new bioelectrical impedance analysis equation discussed in this article was a better fit and was more precise. All 10 body mass index and bioelectrical analysis equations inaccurately estimated dual energy x-ray absorptiometry body fat percentage measures in our sample. The new body mass index equation discussed in this article had less estimation bias and more precision than the published body mass index equations and may be a more accurate equation in African American women.     

Analysis of Body Composition Methods in a Community Sample of African American Women

The purposes of the authors in this study were: (1) to determine whether published body mass index and bioelectrical impedance analysis equations agreed with dual energy x-ray absorptiometry body fat percentage measures and (2) to estimate new body mass index and bioelectrical impedance analysis equations in a sample of African American women. Linear regression was used to determine how well 10 body mass index and bioelectrical impedance analysis equations reflected dual energy x-ray absorptiometry body fat percentage measures in this sample of 74 African American women; new body mass index and bioelectrical impedance analysis equations were created using dual energy x-ray absorptiometry body fat percentage measures as the dependent variable. Participants (M = 47.6 years, SD = 7.7) were classified as overweight or obese (BMI Mean BF% = 35.4, SD = 8.2; BIA Mean BF% = 43.3, SD = 6.9; DXA Mean BF% = 41.5, SD = 6.1). R² and SEE values indicated that all body mass index and bioelectrical impedance analysis equations were a poorer fit with less precision, and the new bioelectrical impedance analysis equation discussed in this article was a better fit and was more precise. All 10 body mass index and bioelectrical analysis equations inaccurately estimated dual energy x-ray absorptiometry body fat percentage measures in our sample. The new body mass index equation discussed in this article had less estimation bias and more precision than the published body mass index equations and may be a more accurate equation in African American women.     

Comparison of body compositional indices assessed by underwater weighing, bioelectrical impedance and anthropometry in Indonesian adolescent girls

OBJECTIVE: To investigate the accuracy of bioelectric impedance analysis and anthropometry to assess percentage body fat (BF %) against underwater weighing (UW). DESIGN AND METHODS: A cross sectional study, 102 girls, aged 11-15, were recruited from two Junior High Schools in Jakarta. MEASUREMENTS: Measurements of percent-age body fat (BF%) using underwater weighing (UW), bioelectrical impedance analysis (BIA), Tanita BIA, body mass index (BMI) and skinfold equations. RESULTS: Correlation between different methods was significant (p < 0.001). The mean difference of BF % from BIA, Tanita, BMI and skinfold compared to UW were 1.87 +/- 3.14, -3.46 +/- 3.28, 1.57 +/- 2.90 and -0.360 +/- 3.09, respectively. Assessments between UW and other methods were significantly different (p < 0.0001) except for skinfolds (p = 0.3031). CONCLUSION: The results between UW and other methods was significantly different, except for skinfolds. There was overestimation and underestimation of BF%. The agreement between skinfold measurement and underwater weighing was also influenced by menarche status.     

Evaluation of body fat estimated from body mass index, skinfolds and impedance. A comparative study

The purpose of the study was to cross-validate three different methods used in field studies for estimating body fat in a group of Danes (n = 139) aged 35-65 years with a wide range in body fat. On the first two-thirds of the participants (n = 93) multiple regressions equations were developed for body fat by means of height, weight, sex and age and either BMI, or by sum of four skinfolds or electrical impedance. A four-compartment-model based on measurements of both total body water (TBW) and potassium (TBK) was used as reference. On the remaining one-third of the subjects (n = 46) cross-validation of the developed equations was carried out. The multiple regression equation for impedance had higher R-square (R2 = 0.89) and lower residual error (SEE = 3.32 kg) than the multiple regression equations for skinfolds (R2 = 0.81, SEE = 3.91 kg) or body mass index (R2 = 0.85, SEE = 3.94 kg). The cross-validation study showed that all three simple methods give reliable average body fat estimates. The difference in estimates of body fat between the reference method and impedance, BMI and skinfolds was 0.76 kg, -0.64 kg and -0.21 kg respectively, none of these differences being different from zero. However, the variance of body fat estimated from BMI (4.84 kg) was higher than body fat estimated from impedance (4.36 kg) (P = 0.013). The multiple regression analysis further showed that measurements of skinfold do not seem to add significantly to the prediction of body fat if height and weight are included.(ABSTRACT TRUNCATED AT 250 WORDS)     

Body mass index as a measure of body fatness: age- and sex-specific prediction formulas

In 1229 subjects, 521 males and 708 females, with a wide range in body mass index (BMI; 13.9-40.9 kg/m2), and an age range of 7-83 years, body composition was determined by densitometry and anthropometry. The relationship between densitometrically-determined body fat percentage (BF%) and BMI, taking age and sex (males = 1, females = 0) into account, was analysed. For children aged 15 years and younger, the relationship differed from that in adults, due to the height-related increase in BMI in children. In children the BF% could be predicted by the formula BF% = 1.51 x BMI-0.70 x age - 3.6 x sex + 1.4 (R2 0.38, SE of estimate (SEE) 4.4% BF%). In adults the prediction formula was: BF% = 1.20 x BMI + 0.23 x age - 10.8 x sex - 5.4 (R2 0.79, SEE = 4.1% BF%). Internal and external cross-validation of the prediction formulas showed that they gave valid estimates of body fat in males and females at all ages. In obese subjects however, the prediction formulas slightly overestimated the BF%. The prediction error is comparable to the prediction error obtained with other methods of estimating BF%, such as skinfold thickness measurements or bioelectrical impedance.     

Evaluation of the novel Tanita body-fat analyser to measure body composition by comparison with a four-compartment model

The Tanita body-fat analyser is a novel device to estimate body fat, based on the principles of bioelectrical impedance. It differs from other impedance systems which use surface electrodes in that the subjects stand bare-footed on a metal sole-plate which incorporates the electrodes, hence impedance is measured through the legs and lower trunk. In 104 men and 101 women (16-78 years and BMI 16-41 kg/m2) the mean bias in body-fat mass measured using the Tanita body-fat analyser was 0.8 (2SD 7.9) kg relative to a four-compartment model. This is comparable to the other prediction techniques tested (conventional tetrapolar impedance -1.3 (2SD 6.9) kg, skinfold thicknesses 0.3 (2SD 7.4) kg, and BMI-based formulas -0.2 (2SD 9.0) kg and -0.6 (2SD 8.5) kg), but the agreement was poorer than for 'reference' methods to measure body fat (density 0.2 (2SD 3.7) kg, total body water -0.9 (2SD 3.4) kg and dual-energy X-ray absorptiometry 0.1 (2SD 5.0) kg). The present paper also describes the derivation of a new prediction equation for the calculation of body composition from the Tanita body-fat analyser. The equation incorporates sex, age, and a log-transformation of height, weight and the measured impedance to predict body fat measured by a four-compartment model. This approach is recommended in the derivation of other prediction equations in body composition analysis. Using this novel prediction equation the residual standard deviations were 4.8% for men and 3.3% for women. A similar analysis using data collected with a conventional tetrapolar system yielded residual standard deviations of 4.3% for men and 3.1% for women. This demonstrates that the practical simplicity of the novel Tanita method is not associated with a clinically significant decrement in performance relative to a traditional impedance device.     

The validity of the World Health Organisation's obesity body mass index criteria in a Turkish population: a hospital-based study

Our aim was to determine the relationship between body fat percentage (BF%) and body mass index (BMI) and to evaluate the validity of World Health Organisation's BMI cut-off values for obesity. Adult out-patients (n=909, 249 men, 660 women), mean age; 40.5 +/- 14.1 years were included. According to WHO's BMI criteria, 440 subjects were obese (79 men, 361 women). The BF% of participants were measured using a bioelectrical impedance analysis (BIA) system (TANITA). Randomly selected 30 patients were also subjected to the dual-energy X-ray absorptiometry (DEXA) procedure for evaluation of the validity of TANITA measurements. The BF% results obtained by DEXA and TANITA revealed good correlation (r =0.952, p= 0.382). There was a positive correlation between BF% and BMI (p<0.001) for both methods. Cut-off values for BMI were calculated as 28.0 kg/m2 for women, 28.2 kg/m2 for men, if obesity was defined as BF >= 25% in men, >= 35% in women according to WHOfs criteria. Using the new cut-off values, the frequency of obesity increased up to 33.9% in our group. The increase was more pronounced in men (67.1% vs. 26.6%).The WHO cut-off values underestimated the frequency of obesity in this population. Further studies are warranted for different ethnic groups.     

Association between body composition and body mass index in young Japanese women

The National Nutrition Survey of Japan indicated a trend toward a decreasing body mass index (BMI; kg/m2) among young Japanese women. Current studies suggest that not-high BMI often does not correlate with not-high body fat percentage. Recently, the classification of BMI in adult Asians was proposed by the International Obesity Task Force. The addition of an "at risk of overweight" category, BMI as 23.0-24.9, was intended to prevent chronic diseases. We investigated the association between body fat percentage (BF%) and BMI to evaluate the screening performance of BMI focused on individual preventive medicine. The subjects consisted of 605 female college students. The subjects' ages (y), heights (cm), body weights (kg), BMIs, and BF percents with underwater weighing expressed as the means +/- SD were 19.6 +/- 0.5, 158.7 +/- 5.6, 53.8 +/- 7.2, 21.3 +/- 2.4, and 24.9 +/- 4.9, respectively. We defined high BF% as +/- 85th percentile of BF% (29.8%). High-BF% individuals are often not classified into BMI > or = 23.0 because their BMI readings are very broad (18.4-31.7). In comparison to the screening performances (specificity and sensitivity), BMI > or = 23.0 (85.3% and 52.1%, respectively), rather than BMI > or = 25.0 (96.7% and 29.8%, respectively), is recommended for the mass evaluation of fatness. For this reason, the BMI "at risk of overweight" category is characterized as the threshold of increasing the appearance ratio of high-BF% individuals. In conclusion, the BMI > or = 25.0 kg/m2 category is determined as high BF%, regardless of body composition measurement for mass evaluation as a result of quite high specificity. Even so, body composition measurement is necessitated by the individual evaluation of fatness focused on preventive medicine because BMI performed a poor representation of body composition, especially BMI < 25.0 kg/m2 individuals.     

Percentage fat in overweight and obese children: comparison of DXA and air displacement plethysmography

OBJECTIVE: To compare percentage body fat (percentage fat) estimates from DXA and air displacement plethysmography (ADP) in overweight and obese children. RESEARCH METHODS AND PROCEDURES: Sixty-nine children (49 boys and 20 girls) 14.0+/-1.65 years of age, with a BMI of 31.3+/-5.6 kg/m2 and a percentage fat (DXA) of 42.5+/-8.4%, participated in the study. ADP body fat content was estimated from body density (Db) using equations devised by Siri (ADP(Siri)) and Lohman (ADP(Loh)). RESULTS: ADP estimates of percentage fat were highly correlated with those of DXA in both male and female subjects (r=0.90 to 0.93, all p<0.001; standard error of estimate=2.50% to 3.39%). Compared with DXA estimates, ADP(Siri) and ADP(Loh) produced significantly (p<0.01) lower estimates of mean body fat content in boys (-2.85% and -4.64%, respectively) and girls (-2.95% and -5.15%, respectively). Agreement between ADP and DXA methods was further examined using the total error and methods of Bland and Altman. Total error ranged from 4.46% to 6.38% in both male and female subjects. The 95% limits of agreement were relatively similar for all percentage fat estimates, ranging from +/-6.73% to +/-7.94%. DISCUSSION: In this study, conversion of Db using the Siri equation led to mean percentage fat estimates that agreed better with those determined by DXA compared with the Lohman equations. However, relatively high limits of agreement using either equation resulted in percentage fat estimates that were not interchangeable with percentage fat determined by DXA.     

Differences in the relationship between body fat and body mass index between two different Indonesian ethnic groups: the effect of body build.

OBJECTIVE: To study the relationship between body fat percent (BF%) and body mass index (BMI) in two different Indonesian ethnic groups (Malays and Chinese) and to relate differences in the relationship to differences in body build and slenderness. DESIGN: Cross-sectional study. SUBJECTS: Except for ethnicity, not specially selected populations living on Java (Depok, south of Jakarta: Malay Indonesians, n = 117) and on Sulawesi (Makale, north of Ujung Pandang: Chinese Indonesians, n = 109). MEASUREMENTS: Weight, height, sitting height, waist and hip circumferences and skeletal widths were measured. BMI was calculated and BF% was predicted from BMI, age and sex using a (Dutch) Caucasian prediction formula. Slenderness was expressed as the ratio of weight: sum of knee and wrist width. BF% assessed by deuterium oxide dilution was used as a reference. RESULTS: BF% in the male and female Malay Indonesians was 24.6+/-7.0 and 35.6+/-5.6% respectively which was not significantly different from the values in the male and female Chinese Indonesians (24.0+/-4.3 and 33.8+/-6.9%). BMI and age were significantly lower in the Malay Indonesians. Malay Indonesians had a more slender body build in terms of skeletal widths compared to the Chinese Indonesians, and they had a higher slenderness index. BF% predicted from BMI using a Caucasian prediction formula was underestimated by 5.8+/-4.8% and 7.7+/-3.8% in the male and female Malay Indonesians but only by 1.3+/-3.0% and 1.7+/-3.7% in the male and female Chinese Indonesians. After correction for differences in age, sex and BF% the Malay Indonesians had a 1.7+/-0.3 kg/m2 (P < 0.0001) lower BMI than the Chinese Indonesians. After correcting for body build and relative sitting height the difference lowered to 0.9+/-0.4 kg/m2 (P < 0.02). CONCLUSIONS: The study confirmed the results of an earlier study that Indonesians have a higher BF% at the same BMI compared to Caucasians, but that there are apparently also differences among Indonesian subgroups. These differences are at least partly related to differences in body build.     

Comparison of body composition methods: a literature analysis

OBJECTIVE: To examine the comparability of different methods to assess percentage body fat (BF%) against underwater weighing (UWW). DESIGN: A meta-analysis on 54 papers, published in 1985-96, on healthy, adult Caucasians. METHODS: The mean BF% from different studies were treated as single data points. In addition to UWW, the studies included one or more of the following methods: 3- or 4-component model, dual-energy X-ray absorptiometry (DXA), dual-energy photon absorptiometry, isotope dilution, bioimpedance (BIA), skinfolds or near-infrared interactance (NIR). Within each of the methods, the analyses were done separately for different mathematical functions, techniques or instruments. MAIN OUTCOME MEASURES: Bias (mean difference) and error (s.d. of difference) between BF% measured by UWW and the other methods. 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) and BIA 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%.     

Correlation between forearm bone mineral density and body composition in Japanese females aged 18–40 years

Objective The purpose of this study was to clarify the relationship between forearm bone mineral density (BMD), body mass index (BMI), and body composition focusing on body fat percentage (BF%) in Japanese females 18 to 40 years old. Methods Subjects were 2,280 females 18–40 years old. Anthropometric measurements were taken, and a medical history was obtained by questionnaire, including age at the time of the study and age at menarche. BF% was measured by bioelectrical impedance analysis. Forearm BMD was measured using dual-energy X-ray absorptiometry (DXA). The correlations of BMD with BMI and BF% were analyzed using a structural equation model. Results The standardized regression coefficients for the path from BMI to BMD and the path from BF% to BMD were 0.538 and −0.184 respectively. The squared multiple correlation of BMD was 0.146. In addition, the standardized regression coefficient for the path from BMI to BF% was 0.896. Conclusion The results showed a positive correlation between BMD and BMI and an inverse correlation between BMD and BF%. At the same time, it was noted that BF% increased with BMI. This indicated that BMD is dependant on BF% in subjects who have a similar BMI. Therefore, this study concluded that it is necessary to take body composition measurements into account when examining the relationship between BMI and BMD, especially in young females.     

Validation of skinfold thickness and hand-held impedance measurements for estimation of body fat percentage among Singaporean Chinese, Malay and Indian subjects

Body fat percentage (BF%) was measured in 298 Singaporean Chinese, Malay and Indian men and women using a chemical four-compartment model consisting of fat, water, protein and mineral (BF%4C). In addition, weight, height, skinfold thickness and segmental impedance (from hand to hand) was measured. Body fat percentage was predicted using prediction equations from the literature (for skinfolds BF%SKFD) and using the manufacturer's software for the hand-held impedance analyser (BF%IMP). The subjects ranged in age from 18-70 years and in body mass index from 16.0 to 40.2 kg/m2. Body fat ranged from 6.5 to 53.3%. The biases for skinfold prediction (BF%4C-BF%SKFD, mean +/- SD) were -0.4+/-3.9, 2.3+/-4.1 and 3.1+/-4.2 in Chinese, Malay and Indian women, respectively, the Chinese being different from the Malays and Indians. The differences were significant from zero (P < 0.05) in the Malays and Indians. For the men, the biases were 0.5+/-3.8, 0.0+/-4.8 and 0.9+/-4.0 in Chinese, Malays and Indians, respectively. These biases were not significantly different from zero and not different among the ethnic groups. The biases for hand-held impedance BF% were -0.7+/-4.5, 1.5+/-4.4 and 0.4+/-3.8 in Chinese, Malay and Indian women. These biases were not significantly different from zero but the bias in the Chinese was significantly different from the biases in the Malays and Indians. In the Chinese, Malay and Indian men, the biases of BF%IMP were 0.7+/-4.6, 1.9+/-4.8 and 2.0+/-4.4, respectively. These biases in Malay and Indian men were significantly different from zero and significantly different from the bias in Chinese men. The biases were correlated with level of body fat and age, and also with relative arm span (arm span/height) for impedance. After correction, the differences in bias among the ethnic groups disappeared. The study shows that the biases in predicted BF% differ between ethnic groups, differences that can be explained by differences in body composition and differences in body build. This information is important and should be taken into account when comparing body composition across ethnic groups using predictive methods.     

Body composition predicted from skinfolds in African women: a cross-validation study using air-displacement plethysmography and a black-specific equation

Skinfold thickness (SF) measurements are commonly used for the indirect assessment of body composition. It is necessary to know how large the bias is when using Caucasian SF-based prediction equations Africans, as no specific equations exist. Our first aim was to test the validity of the equation of Durnin & Womersley for predicting body density from SF in Africans. The second aim was to determine the effect of calculating percentage body fat (%BF) from body density using a black-specific formula rather than the Siri equation, thus taking into account the higher fat-free mass (FFM) density in blacks than in whites. A total of 196 African women volunteered. Mean age was 29.5 (sd 8.7) years and mean BMI was 22.5 (sd 4.6) kg/m2. We compared body density values predicted from SF with those measured by air-displacement plethysmography, and %BF values obtained from body density using the Siri equation or the black-specific calculation. The bias (reference minus prediction) was 0.0100 kg/cm3 in body density (P<10(-4)) and 6.5 % BF (P<10(-4)), and the error (sd of the bias) 0.0097 kg/l and 4.5 % BF. With the black-specific equation, the bias was reduced by 1.9 % BF, while error remained similar. As the %BF prediction required an SF-based equation followed by a body density-based calculation, the lack of validity we observed in Africans may be due to known differences between blacks and whites in the distribution of subcutaneous adipose tissue and, as demonstrated, in the FFM density. Equations thus need to be established using SF values specific to Africans.     

Interchangeability among the percentages of body fat estimated by mid-arm adipose area,triceps skinfold thickness and arm-to-arm segmental bioimpedance analysis

BACKGROUND: Assessing nutritional status based on the upper limbs is useful at the clinical level. The aim of this study is to evaluate the agreement degree of the body fat percentages (%BF) estimated by the mid-arm adipose area (%BFARM), the Siri triceps skin-fold equation (%BFTRICEPS) and the arm-to-arm segmental bioimpedance analysis (%BFBIA), as well as the Siri four-skinfold equation (%BFSIRI), assessing their interchangeability. METHODS: A cross-sectional study. Body fat assessments were made on a total of 145 subjects (83 males, 62 females) anthropometrically and by bioelectrical impedance analysis (Omron BF 300). The agreement between methods were analyzed using the interclass correlation coefficient (ICC) and the Bland-Altman method. RESULTS: The ICC between %BFARM and %BFTRICEPS was 0.8322 (CI .95% 0.7672-0.8791); between %BFARM-%BFBIA 0.7337 (0.6305-0.8080) and between %BFTRICEPS-%BFBIA 0.9290 (0.9015; 0.9488). For the Bland-Altman method, the agreement interval between %BFARM-%BFTRICEPS (-11.2; 16.96) and between %BFARM-%BFBIA (-13.04; 21.76) exceeded the cutoff point (+/- 10%), but not between %BFTRICEPS-%BFBIA (-6.64; 9.6), %BFSIRI-%BFTRICEPS (-5.27; 4.52) and %BFSIRI-%BFBIA (-6.31; 8.52). The BMI has no bearing on the results. CONCLUSIONS: The method utilized influences the nutritional assessment made based on the upper limbs. The mid-arm adipose area method overestimated the %BF with relationship to the Siri triceps skinfold or four-skinfold equation and to the bioelectrical impedance analysis, and although this result suggests that mid-arm adipose area may not be a good indicator of global adiposity, this must be confirmed against a gold standard.     

Bioelectrical impedance analysis: population reference values for phase angle by age and sex

BACKGROUND: Phase angle is an indicator based on reactance and resistance obtained from bioelectrical impedance analysis (BIA). Although its biological meaning is still not clear, phase angle appears to have an important prognostic role. OBJECTIVE: The aim of this study was to estimate population averages and SDs of phase angle that can be used as reference values. DESIGN: BIA and other methods used to evaluate body composition, including hydrodensitometry and total body water, were completed in 1967 healthy adults aged 18-94 y. Phase angle was calculated directly from body resistance and reactance, and fat mass (FM) was estimated from the combination of weight, hydrodensitometry, and total body water by using the 3-compartment Siri equation. Phase angle values were compared across categories of sex, age, body mass index (BMI), and percentage FM. RESULTS: Phase angle was significantly (P < 0.001) smaller in women than in men and was lower with greater age (P < 0.001). Phase angle increased with an increase in BMI and was significantly inversely associated with percentage fat in men. Phase angle was significantly predicted from sex, age, BMI, and percentage FM in multiple regression models. CONCLUSIONS: Phase angle differs across categories of sex, age, BMI, and percentage fat. These reference values can serve as a basis for phase angle evaluations in the clinical setting.     

Differences in body composition between Singapore Chinese,Beijing Chinese and Dutch children

OBJECTIVES: To compare the relationship between body mass index (BMI) and body fat percentage (BF%) in children of different ethnic background. DESIGN: Cross-sectional observational study. SETTINGS: The study was performed in three different locations, Singapore, Beijing and Wageningen (The Netherlands). SUBJECTS: In each centre 25 boys and 25 girls, aged 7-12 y, were selected. They were matched on age, sex and body height. METHODS: Body weight and body height was measured following standardized procedures. The body mass index (BMI) was calculated as weight/height squared (kg/m(2)). Body fat was measured by densitometry in Beijing and Wageningen and by dual energy X-ray absorptiometry (DXA) in Singapore. The DXA measurements in Singapore were validated against densitometry. RESULTS: There were no significant differences in BF% or BMI within each gender group across the three study sites. However, after controlling for (non-significant) differences in age and BF%, the Singapore children had a lower (mean+/-s.e.) BMI (15.6+/-0.3) than the Beijing 17.6+/-0.3) and Wageningen (16.9+/-0.3) children. For the same BMI, age and sex the Singapore children had a significant higher BF% (24.6+/-0.7) than the Beijing (19.2+/-0.8) and Wageningen (20.3+/-0.7) children. CONCLUSIONS: The study strongly suggests that the relationship between BF% and BMI (or weight and height) is different among children of different ethnic background. Consequently growth charts and BMI cut-off points for underweight, overweight and obesity in children may have to be ethnic-specific.     

广州市不同年龄儿童青少年体脂含量检测结果分析

目的了解不同年龄儿童青少年体脂情况,为制定我国儿童青少年肥胖诊断标准提供依据。方法选定广州市本地生源为主的中、小学各1所,采用生物电阻抗法(BIA)对1305名7~18岁儿童青少年进行体脂含量测定。结果男生体脂百分比(BF%)7岁组为13.2%,8~18岁基本稳定在15%左右,没有随年龄而上升;女生BF%7岁组较低,为12.2%,以后逐渐升高,在10~11岁与男生形成交叉并超越男生。男女生的BF%与BMI相关分析r值分别为0.722和0.954,P值均小于0.001。结论BF%可作为儿童青少年的肥胖诊断标准,但在不同性别和年龄中变化较大,应根据我国人种特点进行大样本的基础调查。