Bioimpedance Analysis Method Research Articles

BCAA was more closely associated with visceral fat area than subcutaneous fat area in patients of type 2 diabetes mellitus: a cross-sectional study

BackgroundBranched-chain amino acid (BCAA) has been reported to be associated with obesity, the association of BCAA with visceral fat area (VFA) and subcutaneous fat area (SFA) remained unclear in patients with type 2 diabetes.MethodsThis cross-sectional study was conducted in 284 patients with type 2 diabetes mellitus. Enzyme-linked immunospecific assay was used to measure levels of serum BCAA and branched-chain keto acid (BCKA). VFA and SFA were measured with bio-impedance analysis method. The association between BCAA and VFA was calculated using Pearson correlation and multivariable linear regression analysis.ResultsThere were significant differences in the means of body mass index, waist circumstance, SFA and VFA among the three groups divided by total BCAA tertiles (all p < 0.05). Compared to patients with lower levels of serum BCAA (the lower tertile group), the means of VFA and SFA were significantly larger in the middle and upper tertile groups (all p < 0.05). However, the differences in above obesity parameters were nonsignificant according to various BCKA tertiles. Pearson correlation analysis also demonstrated that BCAA levels were positive associated with each obesity parameter (p < 0.05). Nevertheless, multivariable linear regression analysis showed that levels of serum BCAA were correlated with VFA, BMI and WC (all p < 0.05) rather than SFA after adjusted for other confounders.Conclusionslevels of serum BCAA were more closely correlated with VFA than SFA, prospective studies should be warranted to further explore the mechanism mediating BCAA and visceral fat accumulation in Human beings.Clinical trial numberNot applicable.

Accurate prediction of three-dimensional humanoid avatars for anthropometric modeling.

To evaluate the hypothesis that anthropometric dimensions derived from a person's manifold-regression predicted three-dimensional (3D) humanoid avatar are accurate when compared to their actual circumference, volume, and surface area measurements acquired with a ground-truth 3D optical imaging method. Avatars predicted using this approach, if accurate with respect to anthropometric dimensions, can serve multiple purposes including patient body composition analysis and metabolic disease risk stratification in clinical settings. Manifold regression 3D avatar prediction equations were developed on a sample of 570 adults who completed 3D optical scans, dual-energy X-ray absorptiometry (DXA), and bioimpedance analysis (BIA) evaluations. A new prospective sample of 84 adults had ground-truth measurements of 6 body circumferences, 7 volumes, and 7 surface areas with a 20-camera 3D reference scanner. 3D humanoid avatars were generated on these participants with manifold regression including age, weight, height, DXA %fat, and BIA impedances as potential predictor variables. Ground-truth and predicted avatar anthropometric dimensions were quantified with the same software. Following exploratory studies, one manifold prediction model was moved forward for presentation that included age, weight, height, and %fat as covariates. Predicted and ground-truth avatars had similar visual appearances; correlations between predicted and ground-truth anthropometric estimates were all high (R2s, 0.75-0.99; all p < 0.001) with non-significant mean differences except for arm circumferences (%Δ ~ 5%; p < 0.05). Concordance correlation coefficients ranged from 0.80-0.99 and small but significant bias (p < 0.05-0.01) was present with Bland-Altman plots in 13 of 20 total anthropometric measurements. The mean waist to hip circumference ratio predicted by manifold regression was non-significantly different from ground-truth scanner measurements. 3D avatars predicted from demographic, physical, and other accessible characteristics can produce body representations with accurate anthropometric dimensions without a 3D scanner. Combining manifold regression algorithms into established body composition methods such as DXA, BIA, and other accessible methods provides new research and clinical opportunities.

Accurate Prediction of Three-Dimensional Humanoid Avatars for Anthropometric Modeling.

To evaluate the hypothesis that anthropometric dimensions derived from a person's manifold-regression predicted three-dimensional (3D) humanoid avatar are accurate when compared to their actual circumference, volume, and surface area measurements acquired with a ground-truth 3D optical imaging method. Avatars predicted using this approach, if accurate with respect to anthropometric dimensions, can serve multiple purposes including patient metabolic disease risk stratification in clinical settings. Manifold regression 3D avatar prediction equations were developed on a sample of 570 adults who completed 3D optical scans, dual-energy X-ray absorptiometry (DXA), and bioimpedance analysis (BIA) evaluations. A new prospective sample of 84 adults had ground-truth measurements of 6 body circumferences, 7 volumes, and 7 surface areas with a 20-camera 3D reference scanner. 3D humanoid avatars were generated on these participants with manifold regression including age, weight, height, DXA %fat, and BIA impedances as potential predictor variables. Ground-truth and predicted avatar anthropometric dimensions were quantified with the same software. Following exploratory studies, one manifold prediction model was moved forward for presentation that included age, weight, height, and %fat as covariates. Predicted and ground-truth avatars had similar visual appearances; correlations between predicted and ground-truth anthropometric estimates were all high (R2s, 0.75-0.99; all p < 0.001) with non-significant mean differences except for arm circumferences (%D ~ 5%; p < 0.05). Concordance correlation coefficients ranged from 0.80-0.99 and small but significant bias (p < 0.05 - 0.01) was present with Bland-Altman plots in 13 of 20 total anthropometric measurements. The mean waist to hip circumference ratio predicted by manifold regression was non-significantly different from ground-truth scanner measurements. 3D avatars predicted from demographic, physical, and other accessible characteristics can produce body representations with accurate anthropometric dimensions without a 3D scanner. Combining manifold regression algorithms into established body composition methods such as DXA, BIA, and other accessible methods provides new research and clinical opportunities.

AN OVERVIEW OF OBESITY RISK FACTORS IN THE STUDENTS OF POLTEKKES KEMENKES TASIKMALAYA

The risk factors of adolescent obesity are caused by macronutrient intake, diet and eating habits, physical activity, genetics, knowledge, attitudes, and psychological. This study aimed to determine obesity risk factors for students of Poltekkes Kemenkes Tasikmalaya. This descriptive research studied on 100 students. Obesity is determined by BMI, while body fat composition is determined by the bioimpedance analysis method. Intake and diet were measured through interviews, using a 24-hour recall form, an FFQ questionnaire, and a PGS instrument. Physical activity was measured using the IPAQ form. Knowledge and attitudes are determined by interviews, using knowledge and attitudes instruments. The data were analyzed descriptively. Food intake data were processed using Nutrisurvey 2007 for Windows. BMI showed 64% belong to the obesity 1. The average of body weight was 73.96 Kg ± 11.89. The incidence of obesity occurs a lot during adolescence and college (70%), 48% have obese parents, and 42% have obese siblings. The average body fat was 32.84% ± 5.59 and the average visceral fat was 9.57 ± 4.72. Fat and carbohydrate intake and energy were 100% less than DV, while protein intake was 85% less than DV. The diet of carbohydrate and vegetable sources was less than normal, while protein and fruit sources tend to be normal. Physical activity was low with 46%. The average knowledge score was 75.1% ± 12.98, and the average attitude score was 78.2% ± 14.17.&#x0D; Keywords: Physical Activity; Intake; Obesity; Knowledge; Diet

Comparison of anthropometric, BIA measures and serum leptin with genotypes of Q223R leptin receptor single nucleotide polymorphism and association with obesity and serum leptin

BackgroundLiterature provides evidence for the association of Q223R Leptin Receptor Single Nucleotide Polymorphism (LEPR SNP) with obesity. Genetics in the development of obesity is hardly studied in Sri Lanka. Aim of the studyThe aim of the present study was to compare measures of body composition assessed by anthropometric and bio-impedance analysis (BIA) methods and selected biochemical parameters between individuals with the 3 genotypes of Q223R polymorphism; (QQ-Homozygous Q allele, QR-heterozygous, RR-homozygous R allele) and the association of Q223R polymorphism with obesity and serum leptin levels. MethodsHealthy 347 young adult volunteers residing in Colombo district, Sri Lanka were recruited. Written informed consent was taken from each of the volunteer participants. Anthropometric and BIA methods were used to assess body composition. Serum leptin, insulin and fasting blood glucose levels were measured. Homeostatic Model Assessment-Insulin Resistance (HOMA-IR) was calculated. Polymerase Chain Reaction- Restriction Fragment Length Polymorphism (PCR-RFLP) was used for genotyping. Independent sample t-test, ANOVA and binary logistic regression were used for statistical analysis. ResultsThe mean age of the female and male groups was 26 (±4) and 27 (±5) years respectively. Most of the measured parameters did not show significant differences between genotypes. Q223R polymorphism was not associated with the obesity defined by either BMI or body fat percentage. In the female population, R allele (OR = 2.253, 95% CI = 1.015–4.999, p = 0.046) was significantly associated with elevated serum leptin. ConclusionsBody composition measures, serum leptin and IR are not significantly higher among individuals with the R allele of Q223R polymorphism. Allele R was not associated with obesity and associated with serum leptin levels only in the female population.

Smartphone camera based assessment of adiposity: a validation study

Body composition is a key component of health in both individuals and populations, and excess adiposity is associated with an increased risk of developing chronic diseases. Body mass index (BMI) and other clinical or commercially available tools for quantifying body fat (BF) such as DXA, MRI, CT, and photonic scanners (3DPS) are often inaccurate, cost prohibitive, or cumbersome to use. The aim of the current study was to evaluate the performance of a novel automated computer vision method, visual body composition (VBC), that uses two-dimensional photographs captured via a conventional smartphone camera to estimate percentage total body fat (%BF). The VBC algorithm is based on a state-of-the-art convolutional neural network (CNN). The hypothesis is that VBC yields better accuracy than other consumer-grade fat measurements devices. 134 healthy adults ranging in age (21–76 years), sex (61.2% women), race (60.4% White; 23.9% Black), and body mass index (BMI, 18.5–51.6 kg/m2) were evaluated at two clinical sites (N = 64 at MGH, N = 70 at PBRC). Each participant had %BF measured with VBC, three consumer and two professional bioimpedance analysis (BIA) systems. The PBRC participants also had air displacement plethysmography (ADP) measured. %BF measured by dual-energy x-ray absorptiometry (DXA) was set as the reference against which all other %BF measurements were compared. To test our scientific hypothesis we run multiple, pair-wise Wilcoxon signed rank tests where we compare each competing measurement tool (VBC, BIA, …) with respect to the same ground-truth (DXA). Relative to DXA, VBC had the lowest mean absolute error and standard deviation (2.16 ± 1.54%) compared to all of the other evaluated methods (p < 0.05 for all comparisons). %BF measured by VBC also had good concordance with DXA (Lin’s concordance correlation coefficient, CCC: all 0.96; women 0.93; men 0.94), whereas BMI had very poor concordance (CCC: all 0.45; women 0.40; men 0.74). Bland-Altman analysis of VBC revealed the tightest limits of agreement (LOA) and absence of significant bias relative to DXA (bias −0.42%, R2 = 0.03; p = 0.062; LOA −5.5% to +4.7%), whereas all other evaluated methods had significant (p < 0.01) bias and wider limits of agreement. Bias in Bland-Altman analyses is defined as the discordance between the y = 0 axis and the regressed line computed from the data in the plot. In this first validation study of a novel, accessible, and easy-to-use system, VBC body fat estimates were accurate and without significant bias compared to DXA as the reference; VBC performance exceeded those of all other BIA and ADP methods evaluated. The wide availability of smartphones suggests that the VBC method for evaluating %BF could play an important role in quantifying adiposity levels in a wide range of settings.Trial registration: ClinicalTrials.gov Identifier: NCT04854421.

Left Heart Failure Caused by Capacity Overload in Peritoneal Dialysis Patients.

Background This study sets out to investigate the incidence of acute left ventricular failure in peritoneal dialysis patients with different volume loads and to analyze the related risk factors for LVF in these patients. Methods This study involved patients who received peritoneal dialysis in our hospital between September 2018 and January 2021. The demographic data and biochemical indicators of the patients were collected. The bioimpedance analysis method was used to determine the volume overload [overhydration (OH)] level of patients, and cardiac color Doppler ultrasound was used to detect changes in their cardiac structure. According to the LVF diagnostic criteria of symptoms and laboratory tests, the patients were divided into the LVF and non-LVF groups and then divided according to their OH level into the normal volume (OH ≤1.1 L) and volume overload (OH >1.1 L) groups. The incidence of LVF in was analyzed in patients with different volume loads, and logistic regression was used to identify the risk factors for LVF. Results Among the 226 peritoneal dialysis patients enrolled in this study, 125 patients (55.3%) had LVF. The normal volume group (n = 68, 30.1%) included 22 patients (32.4%) with LVF, and the volume overload group (n = 158, 69.9%) included 84 patients (53.2%) with LVF. In the volume overload group, 74 patients (46.8%) had subclinical volume overload, including 35 patients (47.3%) with LVF, and 84 patients (53.2%) had clinical volume overload, including 65 patients (77.4%) LVF. Multivariate logistic regression analysis revealed a high OH level (OR = 1.862, 95% CI: 1.353–2.668, P < 0.001) and low hemoglobin level (OR = 0.845, 95% CI: 0.721–0.980, P = 0.008) to be independent risk factors for LVF. Conclusions LVF has a high incidence in peritoneal dialysis patients, especially those with volume overload. A high OH level and low hemoglobin level are independent risk factors for LVF.

Preventive effect of rehabilitation training therapy on muscle quality in patients with stroke: A retrospective study

A retrospective analysis was conducted in 45 patients with stroke. All patients received three weeks of rehabilitation training. Body composition was examined using Bio-impedance analysis methods before and after training. Barthel index was used to evaluate activities of daily living before and after the intervention. After rehabilitation training, total body water, muscle mass, protein content, inorganic salt content, and skeletal muscle content were increased while body fat content and body fat percentage were significantly decreased. Barthel Index scores showed that the ability of daily living was improved after rehabilitation. In conclusion, rehabilitation training therapy may have protective effects on sarcopenia in patients with stroke. Keywords: Stroke, sarcopenia, rehabilitation training

Anthropometric Profile Assessed by Bioimpedance and Anthropometry Measures of Male and Female Rugby Players Competing in the Spanish National League

Different rugby positions make different demands on players. It therefore follows that optimum body composition may vary according to the position played. Using anthropometry and bioimpedance analysis (BIA) to assess body composition, the present study aimed to compare the effect of sex and position on body composition variables using anthropometry and BIA methods. A total of 100 competitive rugby players (35 women and 65 men) competing in the First Spanish National League were recruited voluntarily and for convenience for this study. In the laboratory, body composition was assessed by anthropometry, following the recommendations established by the International Society for the Advancement of Kinanthropometry (ISAK), and by direct segmental multi-frequency BIA, following the guidelines established by the Spanish Group of Kinanthropometry (GREC) of the Spanish Federation of Sports Medicine (FEMEDE). We found sex-related differences in height, weight, body mass index and body fat (%) by anthropometry and in body lean mass (%) by DSM-BIA, in 4 of the 6 skinfolds assessed (p &lt; 0.05). We also observed position-related differences in all the variables assessed (p &lt; 0.05) except for lean body mass, as measured by both methods of determining body composition, and front thigh skinfold. Body composition and ∑6skinfolds differs according to sex and playing position, backs (16.6 ± 3.8% and 92.3 ± 33.9 mm,) vs. forwards (20.0 ± 6.7 and 115.3 ± 37.6 mm), and the muscle-adipose (meso-endomorphic somatotype) development predominated in both sexes. Thus, forwards of both sexes are taller, heavier and fatter, possibly due to the specific demands of this position. In addition, body composition measurements vary according to the method used (DSM-BIA vs. anthropometry), indicating that anthropometry is probably the best body composition assessment method.

A Bio-Impedance Analysis Method Based on Human Hand Anatomy for Hand Gesture Recognition

In this article, we presented a bio-impedance analysis method (BIAM) based on the human hand anatomy and propose a feasible and flexible BIAM system to obtain the bio-impedance signals for different gestures to achieve a high classification accuracy in hand gesture recognition with flexibility in electrode arrangement and fewer electrodes. To verify the proposed method, 11 gestures, including two sets: hand gestures and pinch gestures, were selected for the experiment. Based on the functional structure of the human hand, we identified appropriate electrode positions and placed five electrodes on the hand surface for bio-impedance signal measurement. Compared with the electrical impedance tomography (EIT) method, which uses a band with the same number of electrodes wrapped around the wrist, the proposed method achieved 98.7% recognition accuracies on the hand gesture set and 97.8% on the pinch gesture set, while the EIT achieved only 97.1% and 86.3%, respectively. In particular, the proposed method demonstrated the advantage of distinguishing gestures with similar muscle contractions.

Uric acid distribution volume calculated by kinetic modeling and extracellular volume predicted by bioimpedance method.

Several reports indicate that extracellular volume predicted by bioimpedance analysis method is associated with hydration status of hemodialysis patients. Fundamentally, uric acid does not cross cell membranes by simple diffusion, either by facilitated diffusion or by active transport. In addition, uric acid cannot move through cell membranes in most tissues other than those involved in uric acid excretion. These facts support the interpretation that uric acid distribution volume would therefore correlate with extracellular volume. We examined correlation between uric acid distribution volume calculated by uric acid mass-balance modeling from regular blood test results and extracellular volume predicted by bioimpedance analysis predicted by BCM (Fresenius Medical Care) in 53 patients. There was a significant correlation between uric acid distribution volume (x) and extracellular volume predicted by bioimpedance analysis (y): y = 0.69x + 3.39, r2 = 0.61, p < 0.0001. Bland-Altman analysis showed systematic error for uric acid distribution volume versus extracellular volume predicted by bioimpedance analysis (mean difference between uric acid distribution volume and extracellular volume predicted by bioimpedance analysis was 0.94 L, 95% confidence interval of difference was -3.29 to 5.17 L). Uric acid distribution volume calculated by uric acid mass-balance modeling from regular blood test results may be an alternative marker of extracellular volume predicted by bioimpedance analysis.

Anthropometric, body composition and behavioural predictors of bioelectrical impedance phase angle in Polish young adults - preliminary results.

Bioimpedance analysis (BIA) phase angle (PhA) is an index of the integrity of cells and cellular membranes. The aim of the study was identification of behavioural and anthropometric predictors of PhA in a group of young adults. A cross-sectional observational study of health behaviours, anthropometric indicators and body composition assessed by the BIA method was conducted in a group of Polish young adults (n=92) aged 18 - 24 (mean - 19.33, STD - 0.915). Behavioural variables included: level of physical activity, eating behaviours and nutritional knowledge. Body composition was analysed by means of BIA phase-sensitive 8-electrode medical SECA mBCA 525 device. The mean PhA value in the examined cohort was 6.38±0.75 (males - 7.22±0.72; females - 6.13±0.57). Males also showed higher statistically significant other body composition indices, excluding fat mass. The multiple regression model, including anthropometric variables and gender, which explained the effect of these variables on PhA, occurred to be significant (p<0.0000) and allowed explanation of the 82.49% of PhA variability. PhA was significantly predicted from body mass index (BMI), absolute fat mass, visceral adipose tissue value, skeletal muscle mass value and gender. The regression model, including behavioural predictors and gender, allowed explanation of the lower percentage of PhA variability (42.75%; p<0.0000) and included general intensity of health behaviours, level of nutritional knowledge, and gender. A regression model which would consider simultaneously anthropometric and behavioural variables could not be constructed. In the examined cohort, anthropometric and body composition variables showed a stronger predictive value with respect to PhA, compared to behavioural variables.

Arm Skeletal Muscle Mass Is Associated With the Prognosis of Patients With Cirrhosis.

This study aimed to assess the clinical significance of measuring the arm skeletal muscle mass in patients with cirrhosis. Using body composition data measured with the bioimpedance analysis (BIA) method, the skeletal muscle mass index (SMI) values of the arm (arm skeletal muscle mass/height2) and leg (leg skeletal mass muscle/height2) were calculated for 353 patients with cirrhosis, and the relationships of these indices to their prognosis were assessed. In addition, overhydration of the upper and lower limbs was compared. Arm SMI was significantly positively associated with the prognosis of patients with cirrhosis (p=0.0002) but leg SMI was not (p=0.0829). The rate of overhydration in the lower limbs was significantly higher than that in the upper limbs (p<0.0001). Arm SMI measured with the BIA method was suggested to be minimally affected by water retention, and might be clinically useful for patients with cirrhosis.

The Anthropometric Assessment With the Bioimpedance Method Is Associated With the Prognosis of Cirrhotic Patients.

The bioimpedance analysis (BIA) can provide anthropometric data on patients. The aim of the study is to evaluate the clinical relevance of these automatically obtained values. We studied the arm circumference (AC) and arm muscle circumference (AMC) of 197 histologically proven cirrhotic patients. The BIA-based anthropometric data were compared to the manually measured data. In addition, we evaluated whether or not the BIA-based anthropometric data were associated with the prognosis of the patients. The data of %AC and %AMC obtained using the two methods were well correlated (p<0.001) with relatively inconspicuous differences (approximately 6.0% for %AC and 16.0% for %AMC). The data of %AC and %AMC obtained from the BIA method were significantly associated with the prognosis of the patients. The BIA-based anthropometric data were associated with the direct measurement data and related to the prognosis of cirrhotic patients.

Relationship between diabetic neuropathy and sarcopenia

ObjectiveThe present study was designed to examine the prevalence of sarcopenia in patients who have Diabetic Neuropathy (DN); and to determine the relation between DN and sarcopenia. Material and methodsA total of 602 diabetic patients (mean age 60.2 ± 10.6 years; 40.5% male) were included in the study, which was designed as a cross-sectional study. The body composition was measured with the bioimpedance analysis method, and the muscle strength was measured by evaluating the hand grip strength. Those who showed only reduced handgrip strength were categorized in the s-presarcopenia group, whereas patients with only muscle volume loss were categorized in the v-presarcopenia group, those who had them together were defined as sarcopenia; and sarcopenia that was accompanied by obesity was defined as sarcopenic obesity. DN consisted of Diabetic Sensorimotor Polyneuropathy (DSPN) and Diabetic Autonomic Neuropathies (DAN) as two large groups. DAN consisted of its sub-groups of Cardiovascular Autonomic Neuropathy (CV-AN), Gastrointestinal Autonomic Neuropathy (GI-AN), Genitourinary Autonomic Neuropathy (GU-AN), Sudomotor Autonomic Neuropathy (SM-AN), which were identified with their own methods. Logistic regression analyzes were carried out to determine the relations of DN and its subgroups with sarcopenia and its components. ResultsThe DN prevalence was determined to be 85% in the entire patient population; and it was 80.2% in those who had normal muscle mass and strength, 84.4% in s-presarcopenic patients, 82.1% in v-presarcopenic patients, and 94.1% in sarcopenic patients. On the other hand, DN prevalence was 89.2% in non-obese sarcopenics; however, it was determined as 95,9% in sarcopenic obese patients. Similarly, the DN prevalence of non-sarcopenic patients was determined to be 76.7% in non-obese patients; and 88.5% in those who were obese. The sarcopenia incidence in patients who had DN was higher at a significant level than in those without DN (24.7%–8.9%). In the multivariate logistic regression analyzes, DN was determined to be associated with sarcopenia, independently from age and gender, even from accompanying concomitant diseases, BMI, Ha1c and GFR levels (OR: 2.38, 95% CI: 1.02–5.54). ConclusionsThe present study revealed the relation of sarcopenia with DN, especially with GI-AN and GU-AN.

The interplay of adiposity, metabolic factors, and tumor infiltrating lymphocytes in an East Asian breast cancer cohort.

e14207 Background: Breast cancer is rapidly emerging in East Asian countries in recent 2 decades. Unlike western countries in which obesity are quite prevalent and contributes to BC patients, the body mass index (BMI) of BC patients in East Asian countries are usually normal to no more than overweight. In our previous study, we noticed a 30% incidence of crown-like structure of breast (CLS-B) in our BC patients. Despite a lower BMI in this East Asian cohort than the US cohort, the body fat percentage (BF%) is significantly higher in the East Asian The roles of tumor infiltrating lymphocytes (TILs) in BC are inconslusive in different disease contexts. This study aims to decipher the interplay of adiposity, metabolic factors, and TILs in a BC cohort from an East Asian country. Methods: Breast cancer patients from National Taiwan University Hospital were prospectively enrolled into the protocol. Clinicopathologic factors were collected from electronic medical records. Fasting serum collected prior to surgery was used to quantify metabolic factors, including lipid and glucose profiles. Adiposity, including BF% and BMI were quantified by bioimpedance analysis method prior to surgery. Immunohistochemical staining from formalin-fixed, paraffin-embedded BC tumor samples were done to profile TILs by pathologist. CLS-B was stained and interpreted by pathologists. The correlation of TILs with different clinicopathologic factors, adiposity, or relapse-free survival (RFS) were analyzed. Results: 72 BC patients were included in this analysis. The density of CLS-B positively correlates with tumor infiltrating lymphocyte (TIL) percentage ( p = .042), higher BF% correlates with higher regulatory T cells ( p = .026) and tumor associated macrophages (TAM, p = .010), high glucose level is associated with higher CD56 ( p = .040) and higher TAMs ( p &lt; 0.0001). Higher BMI is also associated with higher TAMs ( p= .005). In multivariate analysis, TAMx M2 macrophage is an independent predictor for RFS. Higher TAM level is associated with shorter RFS. Conclusions: Higher TAMs are associated with metabolic alterations such as higher adiposity, higher glucose level, and higher BMI. This result suggests a potential interplay between higher TAMs, altered metabolic factors, and worse RFS.

Assessment of hydration status in a large population.

Both acute and chronic dehydration can have important implications for human behaviour and health. Young children, non-autonomous individuals and the elderly are at a greater risk of dehydration. Mild hypertonic dehydration could be related to less efficient cognitive and physical performance and has been reported to be associated with frequently occurring pathological conditions, especially nephrolithiasis. The assessment of hydration status in a large sample appears to be of interest for conducting epidemiological and large clinical studies aimed at improving preventive and curative care. Especially in large-population studies, methods that are used have to be accurate, cheap, quick and require no technical expertise. Body weight change is widely used to determine acute hydration changes, but seems to be insufficiently accurate in longitudinal studies. Bioimpedance analysis methods enable the assessment of total body water content, but their use is still under debate. Because plasma osmolality directly reflects intracellular osmolality, it constitutes a good marker to assess acute hydration changes, but not chronic hydration status because it changes constantly. Moreover, venepuncture is considered to be invasive and is not suitable for a large-sample study, especially in children. Urinary markers appear to be good alternatives for assessing hydration status in large populations. Collection of urine samples is non-invasive and cheap. High technical expertise is not required to perform urinary marker measurements and these measurements can be carried out quickly. Thus, methods based on urinary markers are very well suited for field studies. Urine colour is probably the least sensitive marker despite its high specificity. Urine osmolality and especially urine specific gravity could be easily used for determining hydration status in large-sample studies.

Assessing skeletal muscle mass: historical overview and state of the art

BackgroundEven though skeletal muscle (SM) is the largest body compartment in most adults and a key phenotypic marker of sarcopenia and cachexia, SM mass was until recently difficult and often impractical to quantify in vivo. This review traces the historical development of SM mass measurement methods and their evolution to advances that now promise to provide in-depth noninvasive measures of SM composition.MethodsKey steps in the advancement of SM measurement methods and their application were obtained from historical records and widely cited publications over the past two centuries. Recent advances were established by collecting information on notable studies presented at scientific meetings and their related publications.ResultsThe year 1835 marks the discovery of creatine in meat by Chevreul, a finding that still resonates today in the D3-creatine method of measuring SM mass. Matiegka introduced an anthropometric approach for estimating SM mass in 1921 with the vision of creating a human “capacity” marker. The 1940s saw technological advances eventually leading up to the development of ultrasound and bioimpedance analysis methods of quantifying SM mass in vivo. Continuing to seek an elusive SM mass “reference” method, Burkinshaw and Cohn introduced the whole-body counting-neutron activation analysis method and provided some of the first detailed reports of cancer cachexia in the late 1970s. Three transformative breakthroughs leading to the current SM mass reference methods appeared in the 1970s and early 1980s as follows: the introduction of computed tomography (CT), photon absorptiometry, and magnetic resonance (MR) imaging. Each is advanced as an accurate and/or practical approach to quantifying whole-body and regional SM mass across the lifespan. These advances have led to a new understanding of fundamental body size-SM mass relationships that are now widely applied in the evaluation and monitoring of patients with sarcopenia and cachexia. An intermediate link between SM mass and function is SM composition. Advances in water-fat MR imaging, diffusion tensor imaging, MR elastography, imaging of connective tissue structures by ultra-short echo time MR, and other new MR approaches promise to close the gap that now exists between SM anatomy and function.ConclusionsThe global efforts of scientists over the past two centuries provides us with highly accurate means by which to measure SM mass across the lifespan with new advances promising to extend these efforts to noninvasive methods for quantifying SM composition.

Increase in maternal adiposity and poor lipid profile is associated with oxidative stress markers during pregnancy

ObjectiveThis study aimed to evaluate changes in maternal adiposity and lipid profile and to correlate these parameters with Deoxyribonucleic acid (DNA) damage and total antioxidant capacity (TAC) levels among pregnant women. MethodThis was a longitudinal study which took place in Kelantan state, Malaysia. Fasting blood samples of 159 healthy pregnant women were collected in second and third trimesters from April 2010 until October 2011. Maternal total body fat was assessed using bioimpedance analysis method. ResultsWhen compared to data in second trimester, pregnant women in third trimester showed significantly higher levels of total body fat (p<0.001), total cholesterol (p<0.001), triglyceride (p<0.001), LDL-C (p=0.001), DNA damage (p<0.001) and TAC (p<0.001) but a lower level of HDL-C (p<0.001). Maternal adiposity and lipid profile were positively and consistently correlated with DNA damage in second and third trimesters. Significant and positive correlations of triglyceride with TAC levels were noted in both periods indicating compensatory action against increased oxidative stress. ConclusionNormal pregnancy is associated with marked changes in lipid metabolism, prooxidant and antioxidant status. Dyslipidemia-associated oxidative stress was demonstrated with advancing gestational age. Appropriate preventive and compensatory measures should be practiced to minimize the effect of oxidative stress throughout pregnancy.

Visceral adipose tissue level, as estimated by the bioimpedance analysis method, is associated with impaired lung function.

Aims/Introduction: It has been reported that metabolic syndrome is associated with impaired lung function, and abdominal obesity is regarded as the most important determinant of this association. We evaluated the association between a component of metabolic syndrome, indices of body composition, including the total adipose tissue content, lean bodyweight and visceral adipose tissue content, as assessed by bioimpedance analysis, and lung function. A total of 516 participants responded to our questionnaire to determine the smoking status and history of past diseases. Waist circumference, height, bodyweight, percent forced expiratory volume in 1 s (%FEV1) and percent forced vital capacity (%FVC) were measured. Fasting blood samples were obtained to determine the serum levels of high-density lipoprotein and triglyceride, and also the blood glucose. The body composition, including the total adipose tissue content and lean bodyweight, was measured, and the visceral adipose tissue content was estimated as the visceral adipose tissue level, by the bioimpedance analysis method. Waist circumference, estimated visceral adipose tissue level and blood pressure were significantly associated with the %FEV1, and the serum high-density lipoprotein cholesterol was significantly associated with the %FVC in men, after adjustment for age, smoking history, and past histories of bronchial asthma and ischemic heart disease. However, this association was not detected in women. We found an association between the visceral adipose tissue level as estimated by the bioimpedance analysis method and lung function. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2011.00189.x, 2011).