Application Of Bioelectrical Impedance Analysis Research Articles

Application of Bioelectrical Impedance Analysis in Weight Management of Children with Spina Bifida.

Children with spina bifida (SB) face an elevated risk of obesity, which necessitates precise methods for assessing body composition to ensure effective weight management. Conventional measures like BMI are inadequate for this population because of variations in growth patterns and skeletal structure. Bioelectrical impedance analysis (BIA) is a method that offers a clearer picture of body composition, yet its use in children with SB remains underexplored. Conducted on 57 children with SB and 28 healthy controls, with a median age of 11 years, this study evaluated anthropometrics, including BMI and BIA-derived metrics. The Hoffer's scale to assess physical activity was applied in SB children. Results showed that while 32% of SB patients were classified as overweight or obese based on BMI, 62% exhibited high body fat percentage via BIA. Fat-free mass, muscle and fat mass, and fat-to-muscle ratio (FMR) differed significantly compared to the reference group. Non-ambulators showed a higher median body fat mass percentage (25.9% vs. 17.8%, p = 0.01) and FMR (0.92 vs. 0.44, p = 0.003) in comparison to the community walkers. In SB children, BIA-measured fat mass is a better obesity indicator than BMI. Non-ambulatory, SB patients with obesity had the highest FMR values, indicating a higher risk for metabolic syndrome.

Application of bioelectrical impedance analysis to assess body composition of male and female broiler chickens from 2 different strains throughout the growth period

Bioelectrical impedance analysis (BIA) was performed in males and females of 2 different broiler strains from 0 to 42 d of age to develop and validate equations to predict body composition (BC). A total of 528 birds, 132 birds per sex and strain (Ross 308 and Cobb 500) were used in the experiment. Birds were fed ad libitum following CVB recommendations with a common starter (0-14 d), grower (15-29 d), and finisher diet (30-42 d). Bioelectrical impedance analysis was measured weekly from 0 to 42 d. Birds were euthanized, frozen and ground for sample collection. Each sample was analyzed through proximate analysis for dry matter (DM), protein, fat, ash, and energy content. Water (%), protein and ash (% DM) decreased with age (77.5-67.5, 69.1-52.2, and 8.12-7.29, respectively; P < 0.0001); whereas fat (% DM) and energy (cal/g DM) increased with the age (20.7-36.4 and 5,421-6151, respectively; P < 0.0001). Males had significantly higher water (%) and protein (% DM) contents, and lower lipid (% DM) deposits than females (70.5, 55.5, and 32.6 vs. 69.6, 54.6, and 33.7, respectively; P < 0.0001). Cobb 500 had a higher fat and lower protein (% DM) and water (%) content than Ross (34.6, 54.0, and 69.7 vs. 31.7, 56.1, and 70.4, respectively; P < 0.0001). A multiple linear regression analysis was carried out to select the equation model to predict BC using the relative mean prediction error (RMPE, %) to evaluate the accuracy. The coefficients of determination (R2) to estimate water (%), protein, fat, ash (% DM) and energy content (cal/g DM) were 0.909, 0.825, 0.795, 0.493, and 0.838, respectively, and the RMPE were 1.26, 3.46, 7.73, 8.85, and 1.86%, respectively. A t test analysis was run, observing no differences in any of the parameters under study between the analyzed and estimated values. Based on these results, we can conclude that BIA can be used as a valid non-invasive technique to estimate in vivo BC in broilers.

Application of Bioelectrical Impedance Analysis in Nutritional Management of Patients with Chronic Kidney Disease.

Body composition measurement plays an important role in the nutritional diagnosis and treatment of diseases. In the past 30 years, the detection of body composition based on bioelectrical impedance analysis (BIA) has been widely used and explored in a variety of diseases. With the development of technology, bioelectrical impedance analysis has gradually developed from single-frequency BIA (SF-BIA) to multi-frequency BIA (multi-frequency BIA, MF-BIA) and over a range of frequencies (bioimpedance spectroscopy, BIS). As the clinical significance of nutrition management in chronic kidney disease has gradually become prominent, body composition measurement by BIA has been favored by nephrologists and nutritionists. In the past 20 years, there have been many studies on the application of BIA in patients with CKD. This review describes and summarizes the latest research results of BIA in nutritional management of patients with CKD including pre-dialysis, hemodialysis, peritoneal dialysis and kidney transplantation, in order to provide reference for the application and research of BIA in nutritional management of chronic kidney disease in the future.

Can Bioelectrical Impedance Analysis (BIA) Be Used to Predict Pig’s Meat Quality In Vivo?

The aim of the current study was to evaluate the possibility of application of bioelectrical impedance analysis (BIA) in order to estimate pork quality. The BIA measurements were tested on 18 living animals for the prediction of the meat quality. The absolute resultant electrical resistance (Rz) and reactance (Xc) of the body was measured with a set of disposable surface electrodes at the frequency of 50 kHz and the current intensity of 400 µA. The characteristics of meat quality, pH measured 1 h and 24 h after slaughter, meat color parameters represented in CIE L*a*b* system, glycolytic potential, intramuscular fat, and natural drip loss, were assessed on the samples of the Longissimus dorsi (LD) muscle. The slaughter value of pigs was characterized on the basis of hot carcass weight (HCW) and percent of meat in carcass. The results showed a significant Pearson correlation between bioelectrical impedance parameter Rz and pH1 (r = 0.48*, p &lt; 0.05). A significant Spearman correlation was showed between color b* value and the Rz/Xc/HCW ratio (r = −0.62*, p &lt; 0.05) and Xc (r = −0.51*, p &lt; 0.05), as well as between the Rz/Xc ratio with pH1 (r = 0.48*, p &lt; 0.05). The multivariate statistical method (principal component analysis and cluster analysis) showed that bioimpedance measurements combined with meat quality traits make it possible to distinguish groups with different quality parameters. However, the relationships between them are complex and still require analysis.

Application of Bioelectrical Impedance Analysis (BIA) to Assess Carcass Composition and Nutrient Retention in Rabbits from 25 to 77 Days of Age.

The aim of this study was to assess and validate, using independent data, the prediction equations obtained to estimate in vivo carcass composition using bioelectrical impedance analysis (BIA) to determine the nutrient retention and overall energy and nitrogen retention efficiencies of growing rabbits. Seventy-five rabbits grouped into five different ages (25, 35, 49, 63 and 77 days) were used in the study. A four-terminal body-composition analyzer was applied to obtain resistance (Rs, Ω) and reactance (Xc, Ω) values. All the animals were stunned and bled at each selected age, and the chilled carcasses were analyzed to determine water, fat, crude protein (CP), ash and gross energy (GE). Multiple linear regression analysis was conducted to determine the equations, using body weight, length and impedance data as independent variables. The coefficients of determination (R2) to estimate the content of water, protein, fat and ash in grams, and energy in Mega Jules(MJ), were: 0.99, 0.99, 0.95, 0.96 and 0.98, respectively, and the relative mean prediction errors (RMPE) were: 4.20, 5.48, 21.9, 9.10 and 6.77%, respectively. Carcass yield (%) estimation had values of 0.50 and 10.0 for R2 and RMPE, respectively. When water content was expressed as a percentage, the R2 and RMPE were 0.79 and 1.62%, respectively. When the protein, fat and ash were expressed as a percentage of dry matter (%DM) and the energy content as kJ/100 g DM, the R2 values were 0.68, 0.76, 0.66 and 0.82, respectively, and the RMPEs were 3.22, 10.5, 5.82 and 2.54%, respectively. Energy Retention Efficiency was 20.4 ± 7.29%, 21.0 ± 4.18% and 20.8 ± 2.79% from 35 to 49, from 49 to 63 and from 35 to 63 d, respectively. Nitrogen Retention Efficiency was 46.9 ± 11.7%, 34.5 ± 7.32% and 39.1 ± 3.23% for the same periods. Energy was retained in body tissues for growth with an efficiency of approximately 52.5%, and the energy efficiency for protein and fat retention was 33.3 and 69.9%, respectively. This work shows that BIA is a non-invasive and good method to estimate in vivo carcass composition and to determine the nutrient retention of growing rabbits from 25 to 77 days of age.

The Possibility of Using Bioelectrical Impedance Analysis in Pregnant and Postpartum Women.

Pregnancy is a time of significant changes occurring in the composition of a woman’s body in order to provide support for the growth and development of the foetus. Bioelectrical impedance analysis (BIA) is used to assess the body composition and hydration status. This technique represents a non-invasive, reliable, and fast clinical approach, which is well tolerated by patients. A segmental impedance measurement might be advantageous in pregnant women, particularly in late pregnancy. The purpose of this paper is to provide a review of different applications of BIA in pregnant and postpartum women. It seems that BIA has a better prognostic potential for gestational and post-partum outcomes than body mass index. The BIA method can be successfully used to study the effect of excessive gestational weight gain in pregnancy on the development of obstetric complications. Studying the mother’s body composition and correlating it with her energy balance could facilitate the development of dietary recommendations for women. Evaluation of the body composition can provide important clues for diagnosis of gestational diabetes mellitus in pregnant women with a low risk of this disease. BIA is also used as one of the additional tests in assessing the risk of developing gestational hypertension and preeclampsia.

Applications of Bioelectrical Impedance Analysis in Diagnosis of Diseases: A Systematic Review

Introduction: Bioelectrical Impedance Analysis (BIA) is a safe, non-invasive, painless, portable, and inexpensive technology that has the prospect to provide information related to the dynamic performance of the human body. Body Composition (BC) assessment is widely accepted as a clinical method to diagnose and evaluate disease status. Aim: To predict and validate the applicability of BIA in diagnosis of diseases such as Chronic Kidney Disease (CKD), Chronic Obstructive Pulmonary Disease (COPD), Heart Failure (HF), Pregnancy and Spinal Cord Injury (SCI). Materials and Methods: A systematic clinical review was conducted following the PRISMA guidelines {PubMed, The Cochrane Archive, Web of Research, Medline, and SPORTDiscus with complete text (EBSCO)}. A literature review was carried out randomly, from 2000 to 2018, published in English; the keyword combinations were evaluated using Boolean operators “OR” and “AND” for BIA, CKD, COPD, HF, Pregnancy, SCI. Results: A total of 1156 search terms, 1139 citations were excluded, and 17 potentially qualifying articles were shortlisted. Hence, as per the inclusion criteria, three articles on COPD, three articles on CKD, three articles on pregnancy, four articles on HF, and four SCI articles were shortlisted. Conclusion: The calculated BIA parameters showed that the patient’s actual health could be analysed quickly to monitor the disease progression and provide significant advances in developing therapies for the diseases. However, this paper recommends further study on BIA to improve a clinical assessment of BC.

Application of Bioelectrical Impedance Analysis to Detect Broiler Breast Filets Affected With Woody Breast Myopathy.

Woody breast (WB) myopathy in modern broilers is causing major meat quality issues and consumer complaints. The poultry industry is sorting out WB filets through the inconsistent manual hand-palpation method. Bioelectrical impedance analysis (BIA) method was evaluated as a rapid and objective WB detection method. Freshly deboned broiler breast filets (15 filets × 2 categories × 3 trials) were sorted (hand-palpation) into severe woody (SW) and normal (N) categories were analyzed for BIA values, cook loss, texture (BMORS) method. SW filets had significantly (P < 0.05) higher resistance and reactance compared to N indicating BIA can be used to detect WB filets. In another experiment, we determined the ability of the BIA to differentiate between four WB severity levels using the whole filet. Significant differences were observed in resistance and reactance of normal and other WB categories, however, there were no significant differences among mild, moderate and severe WB categories. Segmental BIA of those filets indicated that BIA can be used to separate cranial, medial and caudal region of the breast filet based on the presence of WB myopathy. Accidental discovery of spaghetti breast in the samples demonstrated the significance of compounding different factors in analyzing WB meat using BIA.

Identifying early abdominal obesity risk in adolescents by telemedicine: A cross-sectional study in Greece

Obesity and thus, lipotoxicity, is a major health risk factor. Modern exposure to environmental chemicals has contributed significantly to the obesity epidemic. The purpose of this study was to assess, via telemedicine and using bioelectrical impedance analysis (BIA) in schools, the levels of adiposity and other body composition parameters of Greek adolescents in relation with their metabolic syndrome (MetS) characteristics.A representative sample (1575 adolescents, 14.4 ± 1.7 years-old) of the Attica region population, underwent body composition assessment of fat mass (FM), fat-free mass (FFM), and total body water (TBW) and was evaluated for anthropometric and MetS characteristics.Males demonstrated higher FFM% and TBW% but lower FM% than females. Adolescents with abdominal obesity/MetS (n = 149/n = 40) demonstrated significantly (P < 0.001) higher body mass index (BMI 27.8 ± 3.8 kg/m2/30.2 ± 4.2 kg/m2) and FM (33.6 ± 9.7%/35.0 ± 10.5%) but significantly (P < 0.001) lower FFM (34.2 ± 5.7%/33.8 ± 6.2%) and TBW (45.6 ± 6.7%/44.6 ± 7.2%) than adolescents without abdominal obesity/MetS (BMI 20.9 ± 2.8 kg/m2/21.3 ± 3.2 kg/m2; FM 19.2 ± 6.9%/20.2 ± 8.0%; FFM 41.3 ± 4.4%/40.8 ± 4.8%; TBW 55.5 ± 4.8%/54.8 ± 5.5%).Findings suggest that early “osteosarcopenic” elements of abdominal obesity/MetS may exist even in adolescence. The application of BIA, incorporated in the new approach methodology of telemedicine in schools, identified adolescents at risk for obesity complications.

Application of bioelectrical impedance analysis in nutritional assessment of patients with hemodialysis

Objective To explore the effect and related influencing factors of body composition measurement based on bioelectrical impedance analysis(BIA)in evaluating the nutritional status of patients with maintenance hemodialysis(MHD). Methods A total of 54 patients with MHD were selected as research objects. The nutritional status of MHD patients was evaluated by BIA, anthropometric indexes and laboratory indexes. The related influencing factors of skeletal muscle loss in MHD patients were analyzed by multiple linear regression analysis. Results The results of BIA showed that the incidence of skeletal muscle deficiency was 40.74%, and the detection rate was high. Pearson correlation analysis showed that skeletal muscle was significantly correlated with body mass index, high-density lipoprotein, transferrin, serum phosphorus, body cell volume, bone mineral content, basic metabolism, upper arm muscle circumference, upper arm circumference, body fat percentage, protein and inorganic salt(P<0.05). Multiple linear regression analysis showed that serum phosphorus and protein were the influencing factors of skeletal muscle(P<0.05). Conclusion The incidence of malnutrition in MHD patients is high, and the problem of skeletal muscle reduction is prominent. Serum phosphorus and protein levels are the influencing factors of skeletal muscle content in MHD patients. It is necessary to strengthen the control of serum phosphorus level in patients with MHD in order to slow down the process of skeletal muscle atrophy. BIA technology combined with laboratory index detection is recommended for comprehensive evaluation and regular follow-up of nutritional status of MHD patients.

The Efficacy of Body Mass Index and Total Body Fat Percent in Diagnosis Obesity according to Menopausal Status.

ObjectivesBody mass index (BMI) is commonly used in epidemiological study or clinical center. However, it is not exactly correlated with body fat composition and does not reflect sex, age, or race. The aim of this article is to evaluate the validity of BMI standards relative to total body fat (TBF) and to estimate new BMI criteria that correspond to TBF for obesity, especially for Asian postmenopausal women.MethodsA total 3,936 patients were included in this cross-sectional study, including 1,565 premenopausal and 2,371 postmenopausal women. At the time of visit, demographic data were collected. We demonstrated the validity of BMI cut-point of 25 kg/m2 by using area under the curve (AUC), and presented the empirical optimal BMI cut-point by using Youden's index and overall accuracy in both premenopausal and postmenopausal women.ResultsBMI-defined obesity (≥ 25 kg/m2) represents high AUC values (> 0.9) for each TBF. In premenopausal women, TBF ≥ 38% and corresponding BMI value was 29.45 kg/m2 indicated the highest both Youden's index and overall accuracy. In comparison, postmenopausal women who were TBF ≥ 38% showed the highest Youden's index and overall accuracy, and corresponding BMI value was 26.45 kg/m2.ConclusionsWe proposed new BMI criteria for obesity by using TBF reference. With application of bioelectrical impedance analysis, the diagnosis of obesity using BMI criteria may differ between premenopausal and postmenopausal women.

Application of bioelectrical impedance analysis in prediction of light kid carcass and muscle chemical composition

Carcass data were collected from 24 kids (average live weight of 12.5±5.5 kg; range 4.5 to 22.4 kg) of Jarmelista Portuguese native breed, to evaluate bioelectrical impedance analysis (BIA) as a technique for prediction of light kid carcass and muscle chemical composition. Resistance (Rs, Ω) and reactance (Xc, Ω), were measured in the cold carcasses with a single frequency bioelectrical impedance analyzer and, together with impedance (Z, Ω), two electrical volume measurements (VolA and VolB, cm2/Ω), carcass cold weight (CCW), carcass compactness and several carcass linear measurements were fitted as independent variables to predict carcass composition by stepwise regression analysis. The amount of variation explained by VolA and VolB only reached a significant level (P<0.01 and P<0.05, respectively) for muscle weight, moisture, protein and fat-free soft tissue content, even so with low accuracy, with VolA providing the best results (0.326⩽R2⩽0.366). Quite differently, individual BIA parameters (Rs, Xc and Z) explained a very large amount of variation in dissectible carcass fat weight (0.814⩽R2⩽0.862; P<0.01). These individual BIA parameters also explained a large amount of variation in subcutaneous and intermuscular fat weights (respectively 0.749⩽R2⩽0.793 and 0.718⩽R2⩽0.760; P<0.01), and in muscle chemical fat weight (0.663⩽R2⩽0.684; P<0.01). Still significant but much lower was the variation in muscle, moisture, protein and fat-free soft tissue weights (0.344⩽R2⩽0.393; P<0.01) explained by BIA parameters. Still, the best models for estimation of muscle, moisture, protein and fat-free soft tissue weights included Rs in addition to CCW, and accounted for 97.1% to 99.8% (P<0.01) of the variation observed, with CCW by itself accounting for 97.0% to 99.6% (P<0.01) of that variation. Resistance was the only independent variable selected for the best model predicting subcutaneous fat weight. It was also selected for the best models predicting carcass fat weight (combined with carcass length, CL; R2=0.943; P<0.01) and intermuscular fat weight (combined with CCW; R2=0.945; P<0.01). The best model predicting muscle chemical fat weight combined CCW and Z, explaining 85.6% (P<0.01) of the variation observed. These results indicate BIA as a useful tool for prediction of light kids’ carcass composition.

Application of bioelectrical impedance analysis to assess rabbit's body composition from 25 to 77 days of age.

The aim of the study was to develop prediction equations for assessing, in vivo, the whole body composition of growing rabbits. The accuracy of the models obtained was externally validated with independent data sets. One hundred fifty rabbits grouped at 5 different ages (25, 35, 49, 63, and 77 d) were used. A body composition analyzer with 4 terminals was used to obtain resistance (Rs; Ω) and reactance (Xc; Ω) values. The distance between internal electrodes (D; cm), body length (Len; cm), and live BW (g) were also registered. Average values of Rs, Xc, impedance (Z), Len, D, and BW were 83.5 ± 23.1 Ω, 18.2 ± 3.8 Ω, 85.6 ± 22.9 Ω, 30.6 ± 6.9 cm, 10.8 ± 3.1 cm, and 1,454 ± 845 g, respectively. At each selected age, animals were slaughtered, ground, and frozen (-20°C) for determining water, fat, CP, ash, and GE (70.5 ± 3.36%, 27.7 ± 7.61% DM, 54.9 ± 5.41% DM, 11.1 ± 1.55% DM, and 2,267 ± 183 kJ/100 g DM, on average, respectively). Fat and GE contents increased with the age, whereas CP, ash, and water contents decreased. A multiple linear regression analysis was used to determine the prediction equations, using BW, Len, and Z data as independent variables. Equations obtained to estimate water (g), CP (g), fat (g), ash (g), and GE (MJ) had coefficient of determination () values of 0.99, 0.99, 0.97, 0.98, and 0.99, respectively, and the relative mean prediction error (RMPE) was 2.79, 6.15, 24.3, 15.2, and 10.6%, respectively. When water was expressed as a percentage, the and RMPE were 0.85 and 2.30%, respectively. When prediction of the content of protein (% DM), fat (% DM), ash (% DM), and energy (kJ/100 g DM) was done, values of 0.79, 0.83, 0.71, and 0.86, respectively, for and 5.04, 18.9, 12.0, and 3.19%, respectively, for RMPE were obtained. It could be concluded that bioelectrical impedance analysis is a good, noninvasive method to estimate, in vivo, whole body composition of growing rabbits from 25 to 77 d of age.

Application of bioelectrical impedance analysis to assess rabbit’s body composition from 25 to 77 days of age

Application of bioelectrical impedance analysis to assess rabbit’s body composition from 25 to 77 days of age

Clinical Application of Bioelectrical Impedance Analysis and its Phase Angle for Nutritional Assessment of Critically Ill Patients

Clinical Application of Bioelectrical Impedance Analysis and its Phase Angle for Nutritional Assessment of Critically Ill Patients

The application of bioelectrical impedance analysis in live tropical hair sheep as a predictor of body composition upon slaughter

Animal management for breeding and marketing can be improved by precise measurement of desirable traits. Live animal body composition analysis facilitates the selection of animals that are best suited for the intended purpose. This study was designed to assess the accuracy of bioelectrical impedance analysis (BIA) predicted live body tissue composition, as a proxy for the estimation of carcass quality in Barbados Black Belly lambs. Thirty-four Barbados Black Belly lambs were placed on an 8-week feeding regime and then slaughtered. A randomized experimental design was used to allocate diets to animals, which had been stratified into eight groups by initial live weight. The lambs were fed a basal diet of Brachiaria arrecta fresh forage ad libitum and subjected to one of four diets; NS-non-supplemented diet, TG-Trichantera gigantea-supplemented, C100-concentrate supplemented for maintenance, and C400-concentrate supplemented for growth. Diets NS, TG, C100, and C400 had 7, 9, 11, and 7 animals, respectively. The average age and weight at the time of slaughter were 206days and 23.7kg, respectively. A 4-terminal impedance analyzer (RJL Systems®) was used to generate BIA data from live animals immediately before slaughter. The chilled carcasses were then subject to chemical analysis for crude fat, crude protein, and dry matter. Live animal and carcass traits predicted by BIA included fat and fat-free mass, crude fat, crude protein, protein to fat ratio, and tissue distribution. Regression equations were developed from BIA data obtained from the live animal to predict all carcass composition traits measured. Bioelectrical impedance analysis generated favorable results as a practical application to carcass composition evaluation in live tropical hair sheep.

New Application of Bioelectrical Impedance Analysis by the Back Propagation Artificial Neural Network Mathematically Predictive Model of Tissue Composition in the Lower Limbs of Elderly People

The accurate evaluation of muscle mass by a non–invasive and easy method is the first step to help prevent falling events in elderly people. To develop greater predictive accuracy and precision in the measurement of body composition in lower limbs by bioelectrical impedance analysis (BIA), the Back Propagation Artificial Neural Network (BP–ANN) was used to calculate predictive results and was compared with data from dual–energy X–ray absorptiometry (DXA) in 22 male and 16 female elderly people in Taiwan. Fat–free mass (FFM), tissue weight, and fat mass (FM) of the lower limbs were directly measured by DXA, and the BIA values (Z) of left side hand to right side foot in the standing position were measured by BIA. The parameters of height, weight, age, gender and BIA values were combined to create the BP–ANN mathematical model, which was developed to predict the FFM and FM in lower limbs in elderly. A relatively lower correlation coefficient ( r 2 ) of 0.964 and standard deviation (2SD) of 0.01 ± 3.64% were obtained for the prediction of FFM and FM by BIA with the BP–ANN mathematical model, whereas the linear regression analyzing model had an r 2 value of 0.845 and 2SD of 0.12 ± 7.68%, respectively. The performance of the BP–ANN mathematical model at BIA measurement was superior to that of the current linear regression model. In summary, the greater predictive accuracy and precision made the application of BIA with the BP–ANN mathematical model more feasible for the clinical measurement of FM and FFM in the lower limbs of elderly people.

Application of bioelectrical impedance analysis as a method for estimating composition and metabolic condition of southern bluefin tuna ( Thunnus maccoyii) during conventional tagging

Tagging fish without gathering physiological information may be a wasted opportunity. We tested bioelectrical impedance analysis (BIA) for measurement of relative condition of southern bluefin tuna ( Thunnus maccoyii) during conventional tagging at sea. We refined the equipment and method by measurement of 360 fish during conventional and acoustic tagging. Our results demonstrate that BIA is an accurate measure of condition for southern bluefin tuna in the same way it has been shown to be for metabolic condition and composition in other vertebrates including humans. Further, there is sufficient variation in BIA measures of the natural population to give meaningful measures of both metabolic condition and composition between groups at different times and developmental stages. Condition of tuna in this study may be related to the ocean environment just prior to measurement. BIA meets the necessary objectives for measuring fish condition during tagging as it is shown to be harmless, reliable, quick, and effective and does not disrupt conventional tagging operations. In the light of these results this type of condition measurement should be taken wherever possible in future tagging operations for this and other similar species, which will generate new insight into the ecological challenges faced by pelagic fishes. The ability to relate recent ocean environments and subsequent patterns in fish survival may lead to changes in the way tagging data is interpreted.

Prediction of visceral fat area in Japanese adults: proposal of prediction method applicable in a field setting

This study aimed to develop a prediction equation for the visceral fat area at the umbilical level (VFA(L4-5)) in Japanese adults, using internal fat mass (IFM) estimated from a few anthropometric variables. Subjects were 112 adults aged from 25 to 82 years (body mass index (BMI)=24.2+/-3.1 kg/m(2), ranged from 15.7 to 31.2 kg/m(2)). Another 60 adults aged from 21 to 71 years were recruited for the crossvalidation group (BMI=24.5+/-4.0 kg/m(2), ranged from 17.1 to 34.6 kg/m(2)). We examined (1) the prediction of IFM based on a small number of skinfold thicknesses; (2) the prediction of VFA(L4-5) using IFM and (3) the application of bioelectrical impedance analysis (BIA) measurement. VFA(L4-5) was measured by computed tomography (reference value). Total fat mass was measured by dual-energy X-ray absorptiometry (DXA) and single-frequency BIA with 8-point tactile electrodes. Three skinfolds at the abdomen, side chest and suprailiac were selected to estimate IFM. From IFM estimated using these three skinfolds, waist-to-hip ratio (WHR), sex and age, about 75% of the variance of VFA(L4-5) could be explained (Eq(VFA)1: R=863, R(2)=0.745, standard error of estimate (s.e.e.)=20.483 cm(2)). When substituting IFM based on BIA measurement (IFM(BIA)) into Eq(VFA)1, there were no significant mean differences from the reference in both equations, and high correlations were found (r=0.860, s.e.e.=20.902 cm(2)), although a significant mean difference in total fat mass was found between DXA and BIA measurements. The prediction equation using IFM(BIA) (Eq(VFA)2) could have prediction accuracy comparable with that of Eq(VFA)1 (Eq(VFA)2: R=879, R(2)=0.773, s.e.e.=20.324 cm(2)). Furthermore, when applying these equations to the crossvalidation group, there were cross-validity in both equations. This study proposed a prediction equation for VFA(L4-5) from WHR and IFM based on three skinfolds, and the validity of BIA measurement in Japanese adults. We can propose the procedure for a field setting.

Limitations and validation of bioelectrical impedance analysis in morbidly obese patients

Several factors limit the use of bioelectrical impedance analysis as a valid predictor of the amount of body fat in morbidly obese individuals. The purpose of this review is to examine the theory and assumptions that may limit the use of bioelectrical impedance analysis in such individuals. There is currently insufficient validation of bioelectrical impedance analysis equations in obese individuals with body mass indices greater than 34 kg/m. Several factors limit the application of bioelectrical impedance analysis in morbidly obese individuals. Obese individuals have a relatively high amount of extracellular water and total body water, which may overestimate fat-free mass and underestimate fat mass. Central body fat will generally overestimate the percentage of fat-free mass and underestimate the percentage of fat mass in overweight and obese adults with the use of prediction formulas developed in normal weight individuals. A relatively increased amount of total body water and a relative increase in extracellular water will result in an underestimation of the percentage of body fat and an overestimation of fat-free mass in the morbid obesity state. A different body build disposition (mainly in those with severe abdominal obesity) will result in an overestimation of the percentage of body fat. New equations are needed to validate bioelectrical impedance analysis in morbidly obese patients.