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Ultrasound (US) provides the most accurate technique for thickness measurements of subcutaneous adipose tissue (SAT) layers. This US method was recently standardised using eight sites to capture SAT patterning and allows distinguishing between fat and embedded fibrous structures. These eight sites chosen for fat patterning studies do not represent the mean SAT thickness measured all over the body that is necessary for determining subcutaneous fat mass. This was obtained by SAT measurements at 216 sites distributed randomly all over the body. Ten participants with BMI below 28.5kgm −2 and SAT means (from eight sites) ranging from 3 mm to 10 mm were selected. The means from eight sites overestimated the means obtained from 216 sites (i.e. 2160 US measurements in the ten participants); the calibration factor of 0.65 corrects this; standard deviation (SD) was 0.05, i.e. 8%. The SD of the calibration factor transforms linearly when estimating the error range of the whole body’s SAT volume (body surface area times the calibrated mean SAT thickness). The SAT masses ranged from 3.2 to 12.4 kg in this group. The standard deviations resulting from solely the calibration factor uncertainty were ±0.3 and ±1.0 kg, respectively. For these examples, the SAT percentages were 4.9(±0.4)% and 13.3(±1.0)%.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures ( P  < 5 × 10 −8 ). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms. Genome-wide association meta-analyses of waist-to-hip ratio adjusted for body mass index in more than 224,000 individuals identify 49 loci, 33 of which are new and many showing significant sexual dimorphism with a stronger effect in women; pathway analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution. Cardiometabolic traits linked to body fat distribution In the first of a pair of Articles in this issue from the GIANT Consortium, genome-wide association meta-analyses of waist and hip circumference-related traits in more than 200,000 individuals have been used to identify 49 loci — 33 of them new — associated with waist-to-hip ratio adjusted for body mass index and an additional 19 loci associated with related waist and hip circumference measures. A subset of these loci shows significant sexual dimorphism, with many showing a stronger effect in women. Analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms and offer potential targets for interventions in the risks associated with abdominal fat accumulation.

Background: Adipokines are hormones secreted from adipose tissue (AT), and a number of them have been established as risk factors for chronic diseases. However, it is not clear whether and to what extent adiposity, gene expression, and other factors determine their circulating levels. Objectives: To assess to what extent adiposity, as measured by the amount of subcutaneous AT (SAT) and visceral AT (VAT) using magnetic resonance imaging, and gene expression levels in SAT determine plasma concentrations of the adipokines adiponectin, leptin, soluble leptin receptor, resistin, interleukin 6, and fatty acid-binding protein 4 (FABP4). Methods: We performed a cross-sectional analysis of 156 participants from the EPIC Potsdam cohort study and analyzed multiple regression models and partial correlation coefficients. Results: For leptin and FABP4 concentrations, 81 and 45% variance were explained by SAT mass, VAT mass, and gene expression in SAT in multivariable regression models. For the remaining adipokines, AT mass and gene expression explained <16% variance of plasma concentrations. Gene expression in SAT was a less important predictor compared to AT mass. SAT mass was a better predictor than VAT mass for leptin (partial correlation r = 0.81, 95% confidence interval 0.75–0.86, vs. r = 0.58, 95% confidence interval 0.46–0.67), while differences between AT compartments were small for the other adipokines. Conclusions: While plasma levels of leptin and FABP4 can be explained in a large and medium part by the amount of AT and SAT gene expression, surprisingly, these predictors explained only little variance for all other investigated adipokines.

Sedentary behavior (SB) has emerged as a new risk factor for cardiovascular accidents. We investigated whether physical activity levels or SB were related to percent body fat (%BF) in type 2 diabetes mellitus (T2DM). In this cross sectional study, we measured the duration of SB, light physical activity (LPA), moderate to vigorous physical activity (MVPA), total energy expenditure, and step counts using a wireless activity tracker (Fitbit HR; FB) for 7 days in free-living conditions, along with %BF using a bio impedance analyzer (Inbody; Biospace) in 120 smartphone users with T2DM. Subjects were divided into exercise (Exe, =68) and non-exercise (nonExe, =52) groups based on self-reports of whether the recommended exercises (30 min/day, 3 days/week for 3 months) were performed. SBt, LPAt, MVPAt were transformed from SB, LPA, MVPA for normally distributed variables. Participants were: female, 59.2%; age, 59.3±8.4 years; body mass index, 25.5±3.4 kg/m²; glycosylated hemoglobin (HbA1c), 7.6%±1.2%; %BF, 30.4%±7.1%. They performed SB for 15.7±3.7 hr/day, LPA for 4.4±1.7 hr/day, and MVPA for 0.9±0.8 hr/day. The %BF was related to SBt and LPAt, but not to MVPA after adjustments for age, gender, and HbA1c. VPA was significantly higher in the Exe group than in the nonExe group, but SB, LPA, and moderate physical activity were not different. Predicted %BF was 89.494 to 0.105 (age), -13.047 (gender), -0.507 (HbA1c), -7.655 (LPAt) (F[4, 64]=62.929, <0.001), with an ² of 0.785 in multiple linear regression analysis. Reduced body fat in elderly diabetic patients might be associated with reduced inactivity and increased LPA.

The aim of the study was to evaluate whether subject positioning would affect the measurement of raw body volume, thoracic gas volume, corrected body volume and the resulting percent body fat as assessed by air displacement plethysmography (ADP). Twenty-five young adult men (20.7±1.1 y, BMI = 22.5±1.4 kg/m(2)) were measured using the BOD POD® system using a measured thoracic gas volume sitting in a 'forward bent' position and sitting up in a straight position in random order. Raw body volume was 58±124 ml (p<0.05) higher in the 'straight' position compared to the 'bent' position. The mean difference in measured thoracic gas volume (bent-straight = -71±211 ml) was not statistically significant. Corrected body volume and percent body fat in the bent position consequently were on average 86±122 ml (p<0.05) and 0.5±0.7% (p<0.05) lower than in the straight position respectively. Although the differences reached statistical significance, absolute differences are rather small. Subject positioning should be viewed as a factor that may contribute to between-test variability and hence contribute to (in)precision in detecting small individual changes in body composition, rather than a potential source of systematic bias. It therefore may be advisable to pay attention to standardizing subject positioning when tracking small changes in PF are of interest. The cause of the differences is shown not to be related to changes in the volume of isothermal air in the lungs. It is hypothesized and calculated that the observed direction and magnitude of these differences may arise from the surface area artifact which does not take into account that a subject in the bent position exposes more skin to the air in the device therefore potentially creating a larger underestimation of the actual body volume due to the isothermal effect of air close to the skin.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes ( DNAH10 and PLXND1 ). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants. A transancestral exome-wide association study for body-fat distribution identifies protein-coding variants that are significantly associated with waist-to-hip ratio adjusted for body mass index.

Deposition of perirenal adipose tissue has been associated with adverse renal and cardiovascular events. We compared various methods to measure perirenal adipose tissue using computerized tomography (CT)-scan and performed correlations with anthropometric measures associated with renal and cardiovascular events. Voluntary overweight and obese subjects undergoing a CT-scan for diagnostic purposes were included in the study. Perirenal adipose tissue volume, adipose tissue area of the renal sinus and perirenal fat thickness were manually measured bilaterally. The intra- and inter-observer coefficient correlations and the correlation between the diverse measures of renal adipose tissue, subcutaneous (SC-)fat and anthropometrics measures were analyzed using Pearson's correlation tests. The forty included patients (24 men, 16 women) had a mean age of 57.6 ± 18.1 years and a mean body mass index of 28.9 ± 2.9 kg/m2. Despite comparable waist circumference, women had a greater SC-fat thickness compared to men, and therefore a smaller amount of visceral fat, as well as smaller perirenal fat volumes. Perirenal fat thickness was better correlated with perirenal fat volume than adipose area of the renal sinus (p <0.02). The adipose area of the renal sinus did not correlate with any anthropometric measures. In women, perirenal fat volume and thickness showed a negative correlation with SC-fat thickness and no correlation with waist circumference. In men, perirenal fat volume and thickness showed a positive correlation with waist circumference and no correlation with subcutaneous fat thickness. In conclusion, perirenal fat thickness measured with CT-scan at the level of the renal veins is a simple and reliable estimate of perirenal fat volume, that correlated negatively with SC-fat in women and positively with waist circumference in men. The adipose area of the renal sinus did not correlate with any anthropometric measure.

Background To investigate the joint associations between various body fat distribution parameters and high blood pressure (HBP) using the Bayesian Kernel Machine Regression (BKMR) model in school-aged children. Methods A diverse sample of 7 ∼ 17 years old ( N  = 1423; 50.25% boys) was recruited for this study. Fat distribution parameters for multiple body parts, including trunk, legs, android region, and gynoid region fat percentage were measured. HBP was defined as either systolic or diastolic blood pressure exceeded age-, sex- and height-specific 95th percentiles. The chi-square test was utilized to compare differences between groups. The BKMR model was employed to analyze the joint effects of body fat indicators on HBP while accounting for potential confounders. Weighted Quantile Sum (WQS) model was used to characterize the relative weights of each body fat distribution parameter for HBP. Additionally, stratified analyses were performed by sexes and overweight/non overweight groups. Results HBP prevalence was 46.86% and 35.10% for overweight and obese (OB) boys and girls, and was 17.96% and 17.28% for non-overweight and obese (non-OB) boys and girls, respectively. Increased fat percentages of trunk, android, and gynoid parts are associated with a higher risk of HBP, while increased fat percentage of the leg was associated with lower HBP risk. Android fat percentage contributed the most HBP risk in OB boys (weight = 0.34), OB girls (weight = 0.39), and non-OB girls (weight = 0.56). Leg fat percentage had significant protective effect on HBP for non-OB boys (weight=-0.22) and OB boys (weight=-0.44), while gynoid fat percentage had significant protective effect for OB girls (weight=-0.27). Conclusions Fat distribution of various body parts have inconsistent roles and directions in their association with HBP risk in children of different sex and weight status. We recommend that children of different sexes and weight statuses be provided with body-part-specific exercise recommendations for optimal chronic disease prevention and control benefits.

BackgroundVisceral fat has been shown to be associated with increased cardiometabolic risk, but the role of subcutaneous fat remains unclear, and evidence from diverse populations is lacking. We hypothesized that visceral fat, but not subcutaneous fat, would be independently associated with incident cardiovascular disease (CVD) and all-cause mortality.MethodsAmong 1910 participants from the Multi-Ethnic Study of Atherosclerosis with abdominal fat measurements from computed tomography scans and followed for an average of 9.3 years, we used multivariable Cox proportional hazards models to investigate the relationship of both visceral and subcutaneous fat tertiles with CVD and all-cause mortality. We tested for interaction and performed sensitivity analysis for subgroups and missing values of visceral fat.ResultsParticipants had mean age of 65 years, visceral fat 150 cm2, subcutaneous fat 263 cm2, and 50% were female, 21% African American, 13% Asian, and 26% Hispanic. In models adjusted for age, sex, race/ethnicity, income, education, smoking, and subcutaneous fat, there was a statistically significant positive association between visceral fat and CVD, but not mortality. The association for combined CVD may be driven by incident coronary heart disease [tertile 2: hazard ratio, 2.43 (1.38 to 4.28); tertile 3: hazard ratio, 3.00 (1.66 to 5.43)]. Additionally, we found no substantial associations between subcutaneous fat and CVD or mortality. There were no statistically significant interactions by age, sex, or race/ethnicity.ConclusionsVisceral fat, but not subcutaneous fat, is significantly associated with increased risk for CVD in a multiethnic cohort. These data support the need for effective strategies for lifestyle changes that prevent and reduce visceral fat.Using survival analysis, we found that visceral fat, but not subcutaneous fat, was associated with incident cardiovascular disease; these estimates were similar across age, sex, and race/ethnicity.

Objective: To develop bioelectrical impedance analysis (BIA) equations to predict total body water (TBW) and fat-free mass (FFM) of Sri Lankan children. Subjects/Methods: Data were collected from 5- to 15-year-old healthy children. They were randomly assigned to validation (M/F: 105/83) and cross-validation (M/F: 53/41) groups. Height, weight and BIA were measured. TBW was assessed using isotope dilution method (D2O). Multiple regression analysis was used to develop preliminary equations and cross-validated on an independent group. Final prediction equation was constructed combining the two groups and validated by PRESS (prediction of sum of squares) statistics. Impedance index (height2/impedance; cm2 omega), weight and sex code (male=1; female=0) were used as variables. Results: Independent variables of the final prediction equation for TBW were able to predict 86.3% of variance with root means-squared error (RMSE) of 2.1 l. PRESS statistics was 2.1 l with press residuals of 1.2 l. Independent variables were able to predict 86.9% of variance of FFM with RMSE of 2.7 kg. PRESS statistics was 2.8 kg with press residuals of 1.4 kg. Bland Altman technique showed that the majority of the residuals were within mean bias1.96 s.d. Conclusions: Results of this study provide BIA equation for the prediction of TBW and FFM in Sri Lankan children. To the best of our knowledge there are no published BIA prediction equations validated on South Asian populations. Results of this study need to be affirmed by more studies on other closely related populations by using multi-component body composition assessment.