Measures Of Fat Distribution Research Articles

Sex Differences in Protein Biomarkers and Measures of Fat Distribution.

Sex differences in obesity and fat distribution may in part explain differences in cardiovascular risk in men versus women. We sought to examine sex differences in the associations of obesity and adiposity measures with cardiovascular disease-related protein biomarkers. In a cross-sectional observational cohort study, we examined whether the association of obesity (body mass index [BMI] and waist circumference) and adiposity measures (visceral adipose tissue) with biomarkers demonstrates effect modification by sex using multiplicative interaction terms in multivariable linear regression models. Among 3143 participants (mean age, 50 years; 49% women), sex modified the association of BMI, waist circumference, and visceral adipose tissue with cardiovascular disease-related protein biomarkers (7 for BMI, 3 for waist circumference, and 23 for visceral adipose tissue, false discovery rate [FDR]-qint<0.05 for all). For example, higher BMI was associated with lower α1-microglobulin levels in men but not in women (ß, -0.113; SE, 0.028; P<0.001 in men versus ß, -0.007; SE, 0.024; P=0.78 in women). By contrast, higher BMI was associated with higher adipsin levels in men and women, but the association was more pronounced in women (ß, 0.287; SE, 0.023; P<0.001 in women versus ß, 0.189; SE, 0.026; P<0.001 in men). The associations of higher visceral adipose tissue with biomarkers representing adiposity, inflammation, and fibrosis were more pronounced in women versus men. We found that sex modified the associations of obesity and adipose traits with cardiovascular risk ascertained by cardiovascular disease-related biomarkers including markers of adiposity, inflammation, and fibrosis. These findings highlight potential biological pathways that may underlie some of the observed differences in obesity-related cardiovascular disease between women and men.

The association between food insecurity and obesity, a body shape index and body roundness index among US adults

Research has established a positive association between food insecurity and obesity, typically assessed by body mass index (BMI); However, studies examining the relationship between food insecurity and measures of body fat content and distribution are lacking. The aim of this study was to examine the association between food insecurity and obesity ([BMI] ≥ 30 kg/m2) and body fat indicators assessed by body roundness index ([BRI] > 6.72) and a body shape index ([ABSI] > 0.08). This is a cross-sectional study using NHANES data 2007–2020. Household food security was assessed by U.S. Food Security Survey Module questionnaire. Multivariable-adjusted binary logistic regression analyses were used to calculate odds ratios and 95% CIs. Compared to those with full food security, the adjusted ORs for obesity were 1.28 (95% CI:1.18, 1.39), 1.40 (95% CI:1.28, 1.53), and 1.43 (95% CI:1.30, 1.57) for those with marginal, low and very low food security, respectively. The corresponding ORs for high BRI were, respectively, 1.39 (95% CI:1.26, 1.52), 1.50 (95% CI:1.36, 1.66), and 1.60 (95% CI:1.43, 1.78). Similar results were observed for ABSI. The analyses of BMI suggested a potential sex difference, as significant associations were found in women, but not in men. This study confirms previous evidence of the positive association between food insecurity and obesity among US adults.

Association between body fat distribution and asthma in adults: results from the cross-sectional and bidirectional Mendelian randomization study.

Many studies define obesity based on body mass index (BMI) and explore its relationship with adult asthma. However, BMI only considers height and weight, ignoring other factors such as body fat, which may have a greater impact on health. We investigated the relationship between body fat distribution and adult asthma using both a cross-sectional study and bidirectional Mendelian randomization (MR) analysis. Weighted logistic regression models were used to examine the relationship between body fat distribution measurements and adult asthma in the cross-sectional study from National Health and Nutrition Examination Survey (NHANES) 2011-2018. Restricted cubic spline (RCS) curves were employed to explore the dose-response relationship between them. The inverse-variance weighted (IVW) method was used as the main method of MR analysis to explore the causal effect of exposure on outcome. After adjusting for all covariates, weighted logistic regression analysis indicated that fat mass in the left arm, left leg, right arm, right leg, trunk, and total body is associated with an increased risk of developing adult asthma (p < 0.05). RCS curves showed that all six fat mass indicators exhibit a J-shaped relationship with adult asthma. Forward MR analysis found a causal effect of six fat mass indicators on the increased risk of adult asthma (p < 0.05). However, reverse MR did not reveal any causal effect of adult asthma on these six fat mass indicators (p > 0.05). Our study supports a positive correlation and a unidirectional causality between body fat distribution measurements and the risk of adult asthma. Further studies are needed to validate our findings.

Surrogate Biomarker to Identify Obesity and Predict Cardiovascular Disease Risk: A Systematic Review

The study investigates the relationship between obesity and cardiovascular disease (CVD) risk, comparing the use of body mass index (BMI) versus other biomarkers in predicting CVD risk among obese individuals. It conducts a systematic literature review following the PRISMA guidelines, searching databases for relevant articles published from 2017-2022. The review analyzes 12 eligible articles and finds that factors beyond just BMI, such as genetics, physical activity, metabolic disorders, previous heart disease history, nutrition, fat distribution, and changes in BMI, can significantly impact the prognosis of heart disease in obese individuals. Importantly, the study shows that measures of fat distribution, like waist-to-height ratio, waist circumference, log-transformed body shape index (LBSIZ), and the ratio of visceral adipose tissue (VAT) to subcutaneous adipose tissue (SAT), are superior to BMI in predicting CVD risk among those with obesity. The key takeaway is that while obesity is strongly linked to CVD risk, BMI alone often fails to predict that risk accurately. Fat distribution measures may be a more effective tool for identifying obesity status and predicting associated CVD risk compared to relying solely on BMI.

Regional fat distribution and hepatic fibrosis and steatosis severity in patients with nonalcoholic fatty liver disease and type 2 diabetes.

Epidemiologic findings suggest that measures of body fat distribution predict health outcomes independent of the overall body fat assessed by body mass index (BMI). This study aimed to evaluate the associations of overall and regional body fat with the severity of hepatic steatosis and fibrosis in type 2 diabetic patients with non-alcoholic fatty liver disease. Bioelectric impedance analysis and two newly developed anthropometric indices, namely, A Body Shape Index (ABSI) and Body Roundness Index (BRI), were used to estimate the body fat. Based on fibroscan parameters, significant hepatic fibrosis and severe steatosis were defined as ≥F2 and >66%, respectively. Higher total body fat (odds ratio [OR] 1.107, 95% confidence intervals (CI) 1.038-1.182, p=0.002), trunk fat (OR 1.136, 95% CI 1.034-1.248, p=0.008) and leg fat (OR 1.381, 95% CI 1.139-1.674, p=0.001) were associated with liver fibrosis. However, in contrast to the total body fat (OR 1.088, 95% CI 1.017-1.164, p=0.014) and leg fat (OR 1.317, 95% CI 1.066-1.628, p=0.011), the trunk fat was not associated with severe hepatic steatosis. BRI performed better than trunk, leg and total body fat in predicting hepatic steatosis (OR 2.186, 95% CI 1.370-3.487, p=0.001) and fibrosis (OR 2.132, 95% CI 1.419-3.204, p<0.001). Moreover, the trunk to leg fat ratio and ABSI were not independent predictors of either steatosis or fibrosis (p>0.05). BRI revealed a superior predictive ability for identifying the degree of hepatic steatosis and stiffness than other obesity indices. Additionally, higher levels of adiposity in the trunk, legs, and overall body were linked to an increased risk of developing liver fibrosis. Although trunk fat did not show an association with severe hepatic steatosis, an increase in leg and total fat was related to liver steatosis.

Genetic Evidence for Distinct Biological Mechanisms That Link Adiposity to Type 2 Diabetes: Toward Precision Medicine.

We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We employed MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity). We then characterized each cluster based on various biomarkers, metabolites and Magnetic Resonance Imaging-based measures of fat distribution and muscle quality. Analyzing the metabolic signatures of these clusters revealed two primary mechanisms connecting higher adiposity to reduced type 2 diabetes risk. The first involves higher adiposity in subcutaneous tissues (abdomen and thigh), lower liver fat, improved insulin sensitivity, and decreased risk of cardiometabolic diseases and diabetes complications. The second mechanism is characterized by increased body size, enhanced muscle quality, with no impact on cardiometabolic outcomes. Furthermore, our findings unveil diverse mechanisms linking higher adiposity to higher disease risk, such as cholesterol pathways or inflammation. These results reinforce the existence of adiposity-related mechanisms that may act as protective factors against type 2 diabetes and its complications, especially when accompanied by reduced ectopic liver fat.

The causal association between body fat distribution and risk of abdominal wall hernia: a two-sample Mendelian randomization study.

Obesity and a high body mass index (BMI) are considered as risk factors for abdominal wall hernia (AWH). However, anthropometric measures of body fat distribution (BFD) seem to be better indicators in the hernia field. This Mendelian randomization analysis aimed to generate more robust evidence for the impact of waist circumstance (WC), body, trunk, arm, and leg fat percentages (BFP, TFP, AFP, LFP) on AWH. A univariable MR design was employed and the summary statistics allowing for assessment were obtained from the genome-wide association studies (GWASs). An inverse variance weighted (IVW) method was applied as the primary analysis, and the odds ratio value was used to evaluate the causal relationship between BFD and AWH. None of the MR-Egger regression intercepts deviated from null, indicating no evidence of horizontal pleiotropy (p > 0.05). The Cochran Q test showed heterogeneity between the genetic IVs for WC (p = 0.005; p = 0.005), TFP (p < 0.001; p < 0.001), AFP-L (p = 0.016; p = 0.015), LFP-R (p = 0.012; p = 0.009), and LFP-L (p < 0.001; p < 0.001). Taking the IVW random-effects model as gold standard, each standard deviation increment in genetically determined WC, BFP, TFP, AFP-R, AFP-L, LFP-R, and LFP-L raised the risk of AWH by 70.9%, 70.7%, 56.5%, 69.7%, 78.3%, 87.7%, and 72.5%, respectively. This study proves the causal relationship between AWH and BFD, attracting more attention from BMI to BFD. It provides evidence-based medical evidence that healthy figure management can prevent AWH.

Central Body Fat Distribution and Kidney Function after Living Kidney Donation.

In most screening guidelines, high body mass index (BMI) is considered a contraindication for kidney donation. New insights suggest that central body fat distribution might provide greater power in assessing kidney risk. This study aimed to determine whether BMI and central body fat distribution measures are associated with long-term kidney function after donor nephrectomy. We hypothesized that higher BMI, waist circumference (WC), and waist-to-height ratio (WHtR) were associated with lower kidney function long term after donation. The study population consisted of living kidney donors. BMI, WC, and WHtR were measured during donor screening. The outcome postdonation kidney function was assessed using measured GFR (mGFR) (mGFR, 125 I-iothalamate infusion) at 3 months ( n =1042), 5 years ( n =556), and 10 years ( n =210) of follow-up. Primary multivariable linear regression analyses were performed with BMI and WC and secondary analyses with WHtR. Linear mixed models were performed to investigate change in postdonation eGFR. The donor age was 52±11 years, and 48% were male. The mean BMI was 26.1±3.6 kg/m 2 , and WC was 91±11 cm. Higher predonation BMI was associated with lower mGFR throughout follow-up: -1.35 (95% confidence interval [CI], -1.95 to -0.80), -1.55 (95% CI, -2.50 to -0.65), and -2.35 (95% CI, -4.10 to -0.60) ml/min per m 2 per 5 kg/m 2 higher BMI at 3 months, 5, and 10 years after donation, respectively, adjusted for sex, age, and predonation GFR. For WC, differences in mGFR were -1.30 (95% CI, -1.70 to -0.90), -1.50 (95% CI, -2.20 to -0.80), and -1.70 (95% CI, -3.00 to -0.50) ml/min per m 2 per 10 cm higher WC at 3 months, 5, and 10 years after donation, respectively. In male donors, BMI and WC were significantly associated with a negative postdonation change in eGFR. Higher BMI and WC were independently associated with lower GFR (long term) after living kidney donation.

Associations of infant feeding practices with abdominal and hepatic fat measures in childhood in the longitudinal Healthy Start Study

BackgroundInfant feeding patterns have been linked with obesity risk in childhood, but associations with precise measures of body fat distribution are unclear. ObjectiveWe examined associations of infant feeding practices with abdominal fat and hepatic fat trajectories in childhood. MethodsThis study included 356 children in the Healthy Start Study, a prospective prebirth cohort in Colorado. Infant feeding practices were assessed by postnatal interviews and categorized as any human milk <6 mo compared with ≥6 mo; complementary foods introduced ≤4 mo compared with >4 mo; soda introduced ≤18 mo compared with >18 mo. Abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) areas and hepatic fat (%) were assessed by magnetic resonance imaging in early and middle childhood (median 5 and 9 y old, respectively). We examined associations of infant feeding with adiposity trajectories across childhood using linear mixed models. ResultsIn the sample of children, 67% consumed human milk ≥6 mo, 75% were introduced to complementary foods at >4 mo, and 81% were introduced to soda at >18 mo. We did not find any associations between duration of any human milk consumption and childhood adiposity trajectories. Early introduction to complementary foods (≤4 mo) was associated with faster rates of change for SAT and VAT during childhood (Slope [95% CI]: 15.1 [10.7,19.4] cm2/y for SAT; 2.5 [1.9,2.9] cm2/y for VAT), compared with introduction at >4 mo (5.5 [3.0,8.0] cm2/y and 1.6 [1.3,1.9] cm2/y, respectively). Similarly, early introduction to soda (≤18 mo) was associated with faster rates of change for all 3 outcomes during childhood (Slope [95% CI]: 20.6 [15.0,26.1] cm2/y for SAT, 2.7 [2.0,3.3] cm2/y for VAT, 0.3 [0.1,0.5] %/year for hepatic fat) compared with delayed introduction (5.4 [2.8,8.0] cm2/y, 1.7 [1.3, 2.0] cm2/y, -0.1 [-0.2,0.0] %/y, respectively). ConclusionsThe timing of introduction and quality of complementary foods in infancy was associated with rates of abdominal and hepatic fat accrual during childhood. Experimental studies are needed to assess underlying mechanisms.

Abstract 14613: Sex Differences in Protein Biomarkers and Measures of Fat Distribution

Background: Sex differences in obesity and fat distribution have been well described and may explain differences in subsequent cardiovascular risk in men vs women. Underlying mechanisms are not fully elucidated and warrant further investigation. Objective: This study aims to examine sex differences in the associations of obesity and fat distribution measures with cardiovascular disease (CVD) protein biomarkers reflecting key pathways including inflammation, adiposity, fibrosis, and neurohormonal regulation. Methods: We measured 71 circulating protein biomarkers in 3,143 participants with available computed tomography measures of adiposity in the Framingham Heart Study. We examined whether sex modified the association of obesity (body mass index [BMI] and waist circumference [WC]) and fat distribution measures (visceral adipose tissue [VAT]) with protein biomarkers using multiplicative interaction terms in multivariable linear regression models. Sex-stratified analyses were performed as appropriate. Results: Among 3,143 participants (mean age 50 years, 48.7% women), we found that sex modified the association of BMI with 8 protein biomarkers including AGP-1, adipsin, IGFBP-1, IGFBP-2, ADM, KLKB1, MCP-1, and ucMGP (FDR-q int &lt; 0.05 for all, Figure 1 ). For example, BMI was associated with higher MCP-1 levels in women, but not in men (ß 0.132, SE 0.025, p &lt; 0.0001 in women vs ß 0.036, SE 0.028, p = 0.20 in men, FDR-q int 0.03). We found that sex also modified the association of WC and VAT with key CVD protein biomarkers including AGP-1 and A1M. Conclusions: We found that sex modified the association of obesity and adipose traits with cardiovascular risk as ascertained using biomarkers of CVD. These findings highlight potential biological pathways that may contribute to obesity-related cardiometabolic disease uniquely in men versus women.

Independent relevance of adiposity measures to coronary heart disease risk among 0.5 million adults in UK Biobank.

Evidence on body fat distribution shows opposing effects of waist circumference (WC) and hip circumference (HC) for coronary heart disease (CHD). We aimed to investigate the causality and the shape of such associations. UK Biobank is a prospective cohort study of 0.5million adults aged 40-69years recruited between 2006 and 2010. Adjusted hazard ratios (HRs) for the associations of measured and genetically predicted body mass index (BMI), WC, HC and waist-to-hip ratio with incident CHD were obtained from Cox models. Mendelian randomization (MR) was used to assess causality. The analysis included 456 495 participants (26 225 first-ever CHD events) without prior CHD. All measures of adiposity demonstrated strong, positive and approximately log-linear associations with CHD risk over a median follow-up of 12.7 years. For HC, however, the association became inverse given the BMI and WC (HR per usual SD 0.95, 95% CI 0.93-0.97). Associations for BMI and WC remained independently positive after adjustment for other adiposity measures and were similar (1.14, 1.13-1.16 and 1.18, 1.15-1.20, respectively), with WC displaying stronger associations among women. Blood pressure, plasma lipids and dysglycaemia accounted for much of the observed excess risk. MR results were generally consistent with the observational, implying causality. Body fat distribution measures displayed similar associations with CHD risk as BMI except for HC, which was inversely associated with CHD risk (given WC and BMI). These findings suggest that different measures of body fat distribution likely influence CHD risk through both overlapping and independent mechanisms.

Body Fat Distribution, Diabetes Mellitus, and Cardiovascular Disease: an Update.

Specific measures of body fat distribution may have particular value in the development and treatment of cardiometabolic conditions, such as cardiovascular disease (CVD) and diabetes mellitus (DM). Here, we review the pathophysiology, epidemiology, and recent advances in the identification and management of body fat distribution as it relates to DM and CVD risk. Accumulation of visceral and ectopic fat is a major contributor to CVD and DM risk above and beyond the body mass index (BMI), yet implementation of fat distribution assessment into clinical practice remains a challenge. Newer imaging-based methods offer improved sensitivity and specificity for measuring specific fat depots. Lifestyle, pharmacological, and surgical interventions allow a multidisciplinary approach to reduce visceral and ectopic fat. A focus on implementation of body fat distribution measurements into clinical practice should be a priority over the next 5 to 10 years, and clinical assessment of fat distribution can be considered to refine risk evaluation and to develop improved and effective preventive and therapeutic strategies for high-risk obesity.

Deep Learning-Based Fully Automated Segmentation of Regional Muscle Volume and Spatial Intermuscular Fat Using CT

Rationale and ObjectivesWe aim to develop a CT-based deep learning (DL) system for fully automatic segmentation of regional muscle volume and measurement of the spatial intermuscular fat distribution of the gluteus maximus muscle. Materials and MethodsA total of 472 subjects were enrolled and randomly assigned to one of three groups: a training set, test set 1, and test set 2. For each subject in the training set and test set 1, we selected six slices of the CT images as the region of interest for manual segmentation by a radiologist. For each subject in test set 2, we selected all slices of the gluteus maximus muscle on the CT images for manual segmentation. The DL system was constructed using Attention U-Net and the Otsu binary thresholding method to segment the muscle and measure the fat fraction of the gluteus maximus muscle. The segmentation results of the DL system were evaluated using the Dice similarity coefficient (DSC), Hausdorff distance (HD), and the average surface distance (ASD) as metrics. Intraclass correlation coefficients (ICCs) and Bland-Altman plots were used to assess agreement in the measurements of fat fraction between the radiologist and the DL system. ResultsThe DL system showed good segmentation performance on the two test sets, with DSCs of 0.930 and 0.873, respectively. The fat fraction of the gluteus maximus muscle measured by the DL system was in agreement with the radiologist (ICC=0.748). ConclusionThe proposed DL system showed accurate, fully automated segmentation performance and good agreement with the radiologist at fat fraction evaluation, and can be further used for muscle evaluation.

Fat distribution measurements by chemical shift-encoded transition region extraction predict the risk of hyperglycaemia, dyslipidaemia and metabolic syndrome in mice.

Metabolically healthy or unhealthy obesity is closely related to metabolic syndrome (MetS). To validate a more accurate diagnostic method for obesity that reflects the risk of metabolic disorders in a pre-clinical mouse model, C57BL/6J mice were fed high-sucrose-high-fat and chow diets for 12 weeks to induce obesity. MRI was performed and analysed by chemical shift-encoded fat-water separation based on the transition region extraction method. Abdominal fat was divided into upper and lower abdominal regions at the horizontal lower border of the liver. Blood samples were collected, and the glucose level, lipid profile, liver function, HbA1c and insulin were tested. k-means clustering and stepwise logistic regression were applied to validate the diagnosis of hyperglycaemia, dyslipidaemia and MetS, and to ascertain the predictive effect of MRI-derived parameters to the metabolic disorders. Pearson or Spearman correlation was used to assess the relationship between MRI-derived parameters and metabolic traits. The receiver-operating characteristic curve was used to evaluate the diagnostic effect of each logistic regression model. A two-sided p value less than 0.05 was considered to indicate statistical significance for all tests. We made the precise diagnosis of obesity, dyslipidaemia, hyperglycaemia and MetS in mice. In all, 14 mice could be diagnosed as having MetS, and the levels of body weight, HbA1c, triglyceride, total cholesterol and low-density lipoprotein cholesterol were significantly higher than in the normal group. Upper abdominal fat better predicted dyslipidaemia (odds ratio, OR = 2.673; area under the receiver-operating characteristic curve, AUCROC = 0.9153) and hyperglycaemia (OR = 2.456; AUCROC = 0.9454), and the abdominal visceral adipose tissue (VAT) was better for predicting MetS risk (OR = 1.187; AUCROC = 0.9619). We identified the predictive effect of fat volume and distribution in dyslipidaemia, hyperglycaemia and MetS. The upper abdominal fat played a better predictive role for the risk of dyslipidaemia and hyperglycaemia, and the abdominal VAT played a better predictive role for the risk of MetS.

Patient-Centered Approaches to Using BMI to Evaluate Gender-Affirming Surgery Eligibility.

Body mass index (BMI) cutoffs are routinely used to assess eligibility for gender-affirming surgeries (GAS), yet they are not empirically based. The transgender population is disproportionately affected by overweight and obesity due to clinical and psychosocial influences on body size. Strict BMI requirements for GAS are likely to cause harm by delaying care or denying patients the benefits of GAS. A patient-centered approach to assessing GAS eligibility with respect to BMI would utilize reliable predictors of surgical outcomes specific to each gender-affirming surgery, include measures of body composition and body fat distribution rather than BMI alone, center on the patient's desired body size, and emphasize collaboration and support if the patient genuinely desires weight loss.

Comparison of CT and Dixon MR Abdominal Adipose Tissue Quantification Using a Unified Computer-Assisted Software Framework.

Reliable and objective measures of abdominal fat distribution across imaging modalities are essential for various clinical and research scenarios, such as assessing cardiometabolic disease risk due to obesity. We aimed to compare quantitative measures of subcutaneous (SAT) and visceral (VAT) adipose tissues in the abdomen between computed tomography (CT) and Dixon-based magnetic resonance (MR) images using a unified computer-assisted software framework. This study included 21 subjects who underwent abdominal CT and Dixon MR imaging on the same day. For each subject, two matched axial CT and fat-only MR images at the L2-L3 and the L4-L5 intervertebral levels were selected for fat quantification. For each image, an outer and an inner abdominal wall regions as well as SAT and VAT pixel masks were automatically generated by our software. The computer-generated results were then inspected and corrected by an expert reader. There were excellent agreements for both abdominal wall segmentation and adipose tissue quantification between matched CT and MR images. Pearson coefficients were 0.97 for both outer and inner region segmentation, 0.99 for SAT, and 0.97 for VAT quantification. Bland-Altman analyses indicated minimum biases in all comparisons. We showed that abdominal adipose tissue can be reliably quantified from both CT and Dixon MR images using a unified computer-assisted software framework. This flexible framework has a simple-to-use workflow to measure SAT and VAT from both modalities to support various clinical research applications.

Ultrasound Calculation of Fat Volume for Liposuction: A Clinical Software Validation.

Fat manipulation procedures such as liposuction contain a degree of subjectivity primarily guided by the surgeon's visual or tactile perception of the underlying fat. Currently, there is no cost-effective, direct method to objectively measure fat depth and volume in real time. Utilizing innovative ultrasound-based software, the authors aimed to validate fat tissue volume and distribution measurements in the preoperative setting. Eighteen participants were recruited to evaluate the accuracy of the new software. Recruited participants underwent ultrasound scans within the preoperative markings of the study area before surgery. Ultrasound-estimated fat profiles were generated with the in-house software and compared directly with the intraoperative aspirated fat recorded after gravity separation. Participants' mean age and BMI were 47.6 (11.3) years and 25.6 (2.3) kg/m2, respectively. Evaluation of trial data showed promising results following the use of a Bland Altman agreement analysis. For the 18 patients and 44 volumes estimated, 43 of 44 measurements fell within a confidence interval of 95% when compared with the clinical lipoaspirate (dry) volumes collected postsurgery. The bias was estimated at 9.15 mL with a standard deviation of 17.08 mL and 95% confidence interval between -24.34 mL and 42.63 mL. Preoperative fat assessment measurements agreed significantly with intraoperative lipoaspirate volumes. The pilot study demonstrates, for the first time, a novel companion tool with the prospect of supporting surgeons in surgical planning, measuring, and executing the transfer of adipose tissues.

Impact of Abdominal Fat Distribution on Mortality and Its Changes Over Time in Patients Undergoing Hemodialysis: A Prospective Cohort Study

Measures of fat distribution and visceral fat accumulation maintain a direct association with mortality in the general population. However, among patients undergoing hemodialysis (HD), there are few reports of this association. This study aimed to investigate the impact of computed tomography (CT)-measured abdominal fat levels, including the visceral fat area (VFA) and subcutaneous fat area (SFA), on all-cause mortality in patients undergoing HD and investigate whether there are sex-specific particularities regarding the associations between the abovementioned parameters. A total of 258 participants were selected from the population of patients undergoing stable HD. The baseline characteristics were collected by records and interviews. The following variables were assessed at baseline and every year: body mass index, abdominal circumference, VFA, and SFA. Abdominal circumference and body fat distribution were assessed at the level of the umbilicus via CT. All CT scans were performed on a nondialysis day with the subject in a supine position. The primary end point was the 5-year all-cause mortality. This prospective cohort study revealed that age, cardiothoracic ratio, %VFA (VFA/[VFA+SFA]), and albumin were independent predictors of death via multivariable analyses. Regarding the %VFA, its area under the curve (0.599), which did not suffice to predict mortality, was higher than that of VFA, SFA, and body mass index. Also, the effect was recognized mainly in male patients. The %VFA of patients who survived for 60months increased over time. These data suggest that patients (especially men) with a high VFA-to-abdominal fat ratio have a high risk of death. Thus, more attention should be paid to such patients.

Inferior Nutritional Status Significantly Differentiates Dialysis Patients with Type 1 and Type 2 Diabetes.

Diabetes mellitus is currently the leading cause of end-stage renal disease. Assessing nutritional status is an important component of care in this group. This prospective observational study aimed to assess the nutritional status of type 1 and type 2 diabetes patients on hemodialysis or peritoneal dialysis and its relationship with hospitalizations and all-cause death. Adult patients with end-stage renal disease, treated with dialysis, and suffering from type 1 or type 2 diabetes, being treated with insulin, were included in the study. Exclusion criteria comprised other types of diabetes, the patient's refusal to participate in the study, and severe disorders impacting verbal-logical communication. The nutritional status based on the Nutritional Risk Index, the Geriatric Nutritional Risk Index, fat distribution measures, and the Charlson Comorbidity Index was estimated for 95 Caucasian dialysis patients with type 1 (n = 25) or type 2 (n = 70) diabetes. Patients with type 1 diabetes exhibited significantly inferior nutritional status and increased nutritional risk than those with type 2 diabetes. Lower values of nutritional indices significantly differentiated patients with type 1 from those with type 2 diabetes, with ≥84% sensitivity and specificity. Inferior nutritional status was related to all-cause hospitalizations, whereas higher comorbidity was associated with a greater likelihood of cardiovascular hospitalizations and all-cause death. The significant difference between patients with type 1 and type 2 diabetes being treated with dialysis indicates that these patients should not be considered as a homogeneous group, while also considering the greater age of patients with type 2 diabetes.

Abstract WMP105: Gluteofemoral Fat Distribution Is Associated With Decreased Stroke Risk: A Mendelian Randomization Study

Introduction: Previous studies have suggested that increased body fat is associated with stroke risk. Advances in imaging-based fat distribution measurements have uncovered distinct biological underpinnings of local fat depots. Here, we explored associations between biologically relevant local adiposity profiles and stroke risk, aiming to refine the association between body fat distribution and stroke. Methods: Utilizing data from Genome-Wide Association Studies of MRI-derived visceral (VAT), abdominal subcutaneous (ASAT) and gluteofemoral (GFAT) adipose tissue volumes in the UK Biobank (n= 37,750), we selected genome-wide (p&lt;5x10 -8 ), independent (r 2 &lt;0.01), BMI- and height-adjusted variants associated with each trait. We performed Mendelian Randomization (MR) analyses of each trait on ischemic stroke (n=34,217) and subtypes (large artery (LAS)=4,373; cardioembolic (CES)=7,193; small vessel (SVS)=5,386) in MEGASTROKE. We performed multivariable MR, adjusting for relevant cardiometabolic factors (low-density lipoprotein, systolic blood pressure, type 2 diabetes, coronary artery disease). Estimates were expressed as per liter increase in fat volume. Results: GFAT distribution was associated with an overall decreased risk of ischemic stroke (OR 0.89; 95% CI: 0.82-96; p=0.04), mainly driven by SVS risk (OR 0.76; 95% CI: 0.64-0.88; p&lt;0.001) (Figure 1A). Associations were largely consistent in weighted-median and MR-Egger analyses. After adjusting for cardiometabolic factors, only the association between GFAT and SVS remained significant (Figure 1B) . Neither VAT nor ASAT volumes were associated with ischemic stroke risk (both p&gt;0.05). Conclusions: GFAT distribution is associated with a favorable stroke risk profile, suggesting that increases in stroke risk in the setting of an unhealthy body fat distribution may potentially primarily be driven by relative decreases in GFAT rather than increases in VAT or ASAT.