Regional Fat Distribution Research Articles

Establishing feasibility and reliability of subcutaneous fat measurements by ultrasound in very preterm infants.

Regional fat distribution may be a marker of metabolic health and brain growth in preterm infants. Point of care ultrasound has been used to assess regional fat in term infants but has not been used widely in preterm infants. To longitudinally quantify changes in body composition metrics using bedside ultrasound in very preterm infants. Very preterm infants (N = 69) were enrolled after birth and body composition assessments were done through 36 completed weeks' postmenstrual age (PMA). Linear mixed effects regression was used to model change in body composition assessments over time. There was an average increase across PMA for each body composition outcome. Biceps ultrasound subcutaneous fat (SQF) thickness increased by 0.11 mm (95% CI: 0.09, 0.13) each postmenstrual week. Triceps, subscapular, and abdominal ultrasound SQF remained constant through 28 weeks' PMA, then increased each week through 36 completed weeks' PMA. The inter-rater and intra-rater intraclass correlation coefficients for the ultrasound SQF measures ranged from 85.8 to 99.9. Use of ultrasound as a novel method to assess regional fat distribution in very preterm infants is feasible and reliable. Regional fat distribution may be a marker of metabolic health and brain growth in preterm infants. Gold standard body composition assessments may not be feasible in medically fragile very preterm infants. This study assesses longitudinally changes in regional adiposity development using bedside ultrasound techniques in a multicenter cohort of very preterm infants. Results of this study show that bedside ultrasound as a novel method to assess regional subcutaneous fat distribution and development in very preterm infants is both feasible and reliable.

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.

Associations of Plasma and Fecal Metabolites with Body Mass Index and Body Fat Distribution in Children.

Childhood obesity continues to be a critical public health concern with far-reaching implications for the well-being. This study aimed to investigate the association between metabolites in plasma and feces and indicators including body mass index (BMI), BMI for age Z score (BMIZ), and body fat distribution among children aged 6-9 years in China. This cross-sectional study enrolled 424 healthy children, including 186 girls and 238 boys. Dual-energy X-ray absorptiometry (DXA) was used to determine the body fat content and regional fat distribution. Plasma and fecal metabolites were analyzed using targeted metabolomic technologies. A total of 200 plasma metabolites and 212 fecal metabolites were accurately quantified via ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). By using Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) and random forest model, we discovered that 9 plasma metabolites and 11 fecal metabolites were associated with different weight statuses. After adjusting for potential covariates and false discovery rate (FDR) correction, multiple linear regression analyses revealed that plasma metabolites (fumaric acid, glycine, l-glutamine, methylmalonic acid, and succinic acid) and fecal metabolites (protocatechuic acid) were negatively associated (β: -1.373--0.016, pFDR: <0.001-0.031; β: -1.008--0.071, pFDR: 0.005-0.033), while plasma metabolites (isovaleric acid, isovalerylcarnitine, l-glutamic acid, and pyroglutamic acid) and fecal metabolites (3-aminoisobutanoic acid, butyric acid, N-acetylneuraminic acid, octanoylcarnitine, oleoylcarnitine, palmitoylcarnitine, stearoylcarnitine, taurochenodesoxycholic acid, and taurodeoxycholic acid) exhibited positive associations with BMI, BMIZ, and body fat distribution (β: 0.023-2.396, pFDR: <0.001; β: 0.014-1.736, pFDR: <0.001-0.049). Plasma and fecal metabolites such as glutamine may serve as a potential therapeutic target for the development of obesity.

Blood Glucose Fluctuation Is Indicative of Adiposity

Introduction: Continuous glucose monitoring (CGM) system is an effective tool for assessing a person’s glycemic control in real-time, in a “free living condition”. Poor glycemic control is strongly linked to cardiovascular disease, obesity, and the pernicious deposition of fat in the abdominal region. Emerging data show that surges in glucose levels after a meal (postprandial glucose excursions) are more tightly linked to cardiovascular disease, insulin resistance, and diabetic complications than the traditional clinical measure of glycemic control using glycated hemoglobin (HbA1c). Therefore, the purpose of this study is to determine if daily glycemic variability as measured by CGM is an indicator of total and regional body fat distribution and how CGM compares with HbA1c measurements. Methods: Twenty-seven volunteers participated in the study (Male: 11, Female: 16, Age: 32.15 ± 14.55 years, BMI: 28.43 ± 7.30 kg/m2). Total body and regional fat distribution (android, gynoid, android/gynoid) were determined using dual-energy x-ray absorptiometry. Fasting blood glucose and glycated hemoglobin (HbA1c) were measured from collected blood samples. Glycemic variability was measured by CGM attached to the abdomen. Results: CGM glycemic variability was positively correlated with total body fat% (r= 0.4278; p= 0.0329), android fat% (r= 0.5313; p= 0.0063), and android/gynoid ratio (r= 0.5981; p= 0.0016). HbA1c was only positively correlated with android/ gynoid ratio (r= 0.5534; p= 0.0041). Conclusion: Higher blood glucose variability/fluctuation measured by CGM was associated with greater body fat, android fat, android/gynoid fat ratio, which are indicators of cardiovascular disease risks. Blood glucose fluctuation monitoring should be considered in blood glucose management. This study was funded by The University of Texas, El Paso Dodson Fund and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) - R01DK132430. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Exploring the association between regional fat distribution and atrial fibrillation risks: a comprehensive cohort study.

The contribution of total fat mass and regional fat distribution to the risk of AF has rarely been studied. This prospective cohort study(N=494,063) evaluated the association of total fat mass measured by fat percentage (FP) and regional fat measured by arm fat percentage (AFP), trunk fat percentage (TFP), and leg fat percentage (LFP) with incident AF. A subgroup (N = 25,581) underwent MRI, which allowed us to further assess whether visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT) of the trunk fat exert different effects on AF incidence. Over, a median 12.9 ± 1.86 years of follow-up, 29,658 participants (cumulative rate: 6.0%) developed AF. Each 1-standard deviation (SD) increase in LFP was associated with a 16% lower risk of AF (HR: 0.84, 95% CI: 0.82, 0.85). The association between FP and AF was weaker than that between LFP and AF (HR: 0.90, 95% CI: 0.89, 0.92). AFP and TFP only had a marginal association with a lower incidence of AF. Both the VAT and ASAT showed a U-shaped relationship with incident AF. Fat mass, mainly leg fat mass, was associated with a lower risk of AF. ASAT did not exert protective effects.

Pattern of body fat distribution in patients of PCOS using DEXA-based indices

BackgroundConsidering the close link between polycystic ovary syndrome (PCOS) and metabolic syndrome considerable research has been devoted to studying the pattern of fat distribution in PCOS.ObjectivesThe study aims to assess the usefulness of dual-energy X-ray absorptiometry (DEXA) based regional fat distribution indices as a predictor of the development of PCOS.MethodsThis case–control study recruited diagnosed cases of PCOS using Rotterdam Criteria (cases n = 86) and healthy age-matched controls (n = 90). DEXA was performed in both groups for assessment of total and regional body fat distribution after undergoing ultrasonography (USG) and baseline/biochemical evaluation.ResultsThe study revealed a significant difference between cases and controls in trunk fat percentage (40.2% ± 9.1% vs 26.5% ± 9.1%; p < 0.001), android fat percentage (42.4% ± 41%vs 27.8% ± 1.51%; p < 0.001), total fat percentage (43.8% ± 8% vs28.5% ± 1.6%; p < 0.001), fat mass/ht2 (fat mass index) (8.82 ± 3% vs 4.8 ± 1.7%; p < 0.001), android/gynoid ratio (1.05 ± 0.1 vs 0.7 ± 0.2; p < 0.001), and trunk/limb fat mass ratio (1.06 ± 0.3 vs 0.69 ± 0.3; p 0.001). Multivariate analysis revealed a significant relation of trunk fat mass with android % fat, gynoid fat mass, and android-gynoid ratio.ConclusionsThe study demonstrates that there is a central pattern of fat distribution in patients with PCOS while the overall fat might not be increased which is well analyzed by DEXA. Hence, we suggest its use in the initial diagnostic workup and follow-up of PCOS patients for their body fat distribution and content.

Lean body mass positively associate with blood pressure in Chinese adults: the roles of ages and body fat distribution

BackgroundThe relationship between lean body mass (LBM) and blood pressure (BP) is controversial and limited. This study investigated the associations between LBM indexes and BP in adults of different ages and with varying body fat distribution.MethodsThe data for the present analysis was obtained from a cross-sectional survey of 1,465 adults (50.7% males) aged 18–70 years conducted in Beijing, China. Regional LBM and fat distribution, including fat mass (FM) and android to gynoid fat ratio (AOI), were assessed using a dual-energy X-ray bone densitometer. Generalized Liner Model (GLM) was employed. Confounders, including age, sex, height, weight, smoking, and alcohol use, were evaluated through questionnaires and physical examinations.ResultsMales had higher rates of hypertension (11.19% vs. 4.92%) and prehypertension (21.57% vs. 14.59%) than females. The mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) were 122.04 mmHg and 76.68 mmHg. There were no significant associations between LBM and DBP (p > 0.05). However, arms LBM (β = 1.86, 95% CI: 0.77, 2.94) and trunk LBM (β = 0.37, 95% CI: 0.01, 0.73) were significantly associated with SBP. The association of LBM on DBP was stronger with increasing ages, and stronger in females than in males (p < 0.001). The association between adults’ arms LBM and SBP was stronger in the high level FM group (β = 2.74 vs. β = 1.30) and high level AOI group (β = 1.80 vs. β = 2.08).ConclusionThe influence of LBM on SBP increases with age, particularly after the age twenty years in females. For adults with high FM or high AOI, LBM in the arms, showed a stronger positive predictive association with SBP. This suggests that, in addition to controlling fat content, future efforts to improve cardiovascular health in adults should include the management of LBM (especially in the upper body).

Differential sex associations of regional adiposity with cognition and brain pathology in Israeli older adults with Type II Diabetes

AbstractBackgroundAdiposity and Type II diabetes (T2D) are consistently associated with cognitive impairment and dementia. Body mass index (BMI) is the most common measure of global adiposity, but its associations with cognition in old age are inconsistent. BMI does not represent regional fat distribution, which might differ between the sexes. In this study, we examined sex differences in the relationships of regional adiposity with cognition and AD‐related brain volumes in older adults participating in the Israel Diabetes and Cognitive Decline study.MethodsRegional adiposity was measured by abdominal MRI in 89 participants (32.6% women), including hepatic and pancreatic fat, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). Participants were assessed for global cognition, episodic memory (EP), working memory (WM), executive function (EF), and language. A subsample (N = 50) underwent brain MRI assessing total gray matter [GM], hippocampus, inferior, middle, and superior frontal gyrus [IFG, MFG, and SFG, respectively]. Linear regressions examined associations of regional adiposity with cognition and AD‐related brain volumes adjusting for age, sex, education, and BMI (and intracranial volume for MRI measures).ResultsIn the whole sample, higher pancreatic fat was associated with lower EF (r = ‐0.369, p = 0.024). In men, high pancreatic fat was associated with lower global cognition (Men: r = ‐0.311; p = 0.048; Women: r = ‐0.122; p = 0.706), EF (Men: r = ‐0.384; p = 0.033; Women: r = ‐0.508; p = 0.661) and language (Men: r = ‐0.309; p = 0.049; Women: r = 0.082; p = 0.798). In the whole sample, no associations were found between pancreatic fat % and AD‐related brain volumes. Surprisingly, in men, higher pancreatic fat was associated with greater GM volume (Men: r = 0.411; p = 0.046; Women: r = ‐0.231; p = 0.521). In women, higher pancreatic fat was associated with smaller IFG (Men: r = ‐0.185, p = 0.386; Women: r = ‐0.642, p = 0.045). Hepatic fat %, VAT, and SAT did not associate with AD‐related brain volumes or cognitive measures.ConclusionIn Israeli older adults with T2D, different regional fat depots are linked to different cognitive and brain outcomes in men and women. Specifically, more pancreatic fat, but not other fat depots, is associated with poorer cognition. These findings highlight the value of examining distinct fat depots rather than global obesity concerning brain and cognition, and the need to account for sex differences in these associations.

A cohort study on the predictive capability of body composition for diabetes mellitus using machine learning.

We applied machine learning to study associations between regional body fat distribution and diabetes mellitus in a population of community adults in order to investigate the predictive capability. We retrospectively analyzed a subset of data from the published Fasa cohort study using individual standard classifiers as well as ensemble learning algorithms. We measured segmental body composition using the Tanita Analyzer BC-418 MA (Tanita Corp, Japan). The following features were input to our machine learning model: fat-free mass, fat percentage, basal metabolic rate, total body water, right arm fat-free mass, right leg fat-free mass, trunk fat-free mass, trunk fat percentage, sex, age, right leg fat percentage, and right arm fat percentage. We performed classification into diabetes vs. no diabetes classes using linear support vector machine, decision tree, stochastic gradient descent, logistic regression, Gaussian naïve Bayes, k-nearest neighbors (k = 3 and k = 4), and multi-layer perceptron, as well as ensemble learning using random forest, gradient boosting, adaptive boosting, XGBoost, and ensemble voting classifiers with Top3 and Top4 algorithms. 4661 subjects (mean age 47.64 ± 9.37 years, range 35 to 70 years; 2155 male, 2506 female) were analyzed and stratified into 571 and 4090 subjects with and without a self-declared history of diabetes, respectively. Age, fat mass, and fat percentages in the legs, arms, and trunk were positively associated with diabetes; fat-free mass in the legs, arms, and trunk, were negatively associated. Using XGBoost, our model attained the best excellent accuracy, precision, recall, and F1-score of 89.96%, 90.20%, 89.65%, and 89.91%, respectively. Our machine learning model showed that regional body fat compositions were predictive of diabetes status.

Body fat distribution, fat-free mass and cardiovascular function in the UK Biobank

Abstract Background Excess adiposity and high body mass index have been associated with cardiac dysfunction and heart failure. However, the role of whole body imaging and independent associations of regional fat and fat-free mass on left ventricular and vascular function is unclear. Purpose This study determined the cross-sectional associations of regional fat depots and fat-free mass on left ventricular function and arterial stiffness to explain obesity-related cardiac dysfunction. Methods Participants who underwent whole body magnetic resonance imaging (MRI) and dual energy X-ray absorptiometry (DXA) in an ongoing imaging study of 100,000 individuals in the UK were included in this analysis. Analyses exclude individuals with major cardiac and vascular diseases at initial baseline assessment. Regional fat distribution was quantified using MRI while body fat-free mass was quantified with DXA. Cardiac MRI was used to measure left ventricular (LV) ejection fraction and LV mass while pulse wave velocity from finger photo-plethysmography was used to measure arterial stiffness index. Associations of body fat distribution (visceral fat, abdominal subcutaneous fat, other body fat) and fat-free mass with each of LV ejection fraction, LV mass and arterial stiffness index, after mutual adjustment for one another and potential confounders were determined using multivariable linear regression. Results We included 31,088 individuals (mean age 63.4 years, 53% women). Among regional body fat measures, higher visceral fat was associated with lower LVEF (β=-0.43; 95% CI: -0.55, -0.31 per SD) and higher arterial stiffness index (β=0.44; 95% CI: 0.34, 0.54 per SD) while none of the regional fat and fat-free mass showed significant association with LV function or arterial stiffness. None of the fat or fat-free mass measures showed significant association with LV mass. These associations were not explained by inflammatory markers, blood pressure or glycaemic profile. Conclusion Visceral fat is the main driver of obesity-related cardiac and vascular dysfunction. There is need for further studies to understand the biological causal pathways of obesity-heart disease.Figure 1Figure 2

Sex-Specific Contribution of Cardiometabolic Index in Predicting Metabolic Dysfunction-Associated Fatty Liver Disease: Insights from a General Population.

Evidence suggests that cardiometabolic index (CMI) has been identified as a novel obesity-related index associated with diabetes, hypertension, and cardiovascular disease. Current evidence suggests that the differences in sex hormones and regional fat distribution in both sexes are directly correlated with metabolic dysfunction-associated fatty liver disease (MAFLD) risk. This study aimed to investigate the diagnostic value of CMI in MAFLD in both sexes. This retrospective study included 6107 subjects who underwent annual health check-ups from March 2021 to January 2022. CMI was calculated by multiplying the ratio of triglycerides and high-density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Multivariable logistic regression analysis and restricted cubic spline were used to investigate the association of CMI and MAFLD risk. Receiver operating characteristic curve analysis was conducted for the exploration of the diagnostic accuracies of obesity-related indicators. Areas under the curves (AUCs) with 95% CIs were calculated. Prevalence of MAFLD increased with elevated quartiles of CMI in both sexes. The median (IQR) age was 46.00 (18.00) years. Multivariate logistic regression analyses showed that higher CMI was independently associated with MAFLD, in which every additional standard deviation (SD) of CMI increased the risk of MAFLD (OR=2.72, 95% CI:2.35-3.15 for males; OR=3.26, 95% CI:2.36-4.51 for females). Subjects in the fourth quartile of CMI had the highest odds of MAFLD for males (OR=15.82, 95% CI:11.84-21.14) and females (OR=22.60, 95% CI:9.52-53.65)(all P for trend<0.001). Besides, CMI had a non-linearity association with MAFLD (all P for non-linearity<0.001). Furthermore, CMI exhibited the largest AUC compared to other obesity-related indexes in terms of discriminating MAFLD in males (AUC=0.796, 95% CI:0.782-0.810) and females (AUC=0.853, 95% CI:0.834-0.872). CMI was a convenient indicator for the screening of MAFLD among Chinese adults. Females with high CMI had a better diagnostic value for MAFLD than males.

The association of body composition and fat distribution with hypertension in community-dwelling older adults: the Bushehr Elderly Health (BEH) program

BackgroundA significant proportion of the global burden of disability and premature mortality has caused by hypertension. It seems that the relationship between obesity and hypertension is not only associated with excessive body fat mass (FM) but also with body adipose distribution patterns. The present study investigated the association between regional fat distribution using dual-energy X-ray absorptiometry and hypertension in older adults.MethodsThis cross-sectional study was performed using the data from Bushehr Elderly Health Program (BEH) on a total of 2419 participants aged 60 and over. Hypertension was defined as SBP of at least 140 mmHg and/or DBP of at least 90 mmHg. SBP between 120 and 139 mmHg and/or a DBP between 80 and 89 mmHg were considered prehypertension. Participants underwent body composition measurement by dual-energy x-ray absorptiometry to analyze FM, fat-free mass (FFM) in trunk and extremities composition.ResultsThe results showed that 460 (19.02%) of participants had prehypertension, and 1,818 (75.15% ) had hypertension. The odds of having prehypertension (OR: 1.06, 95%CI: 1.01–1.12) and hypertension (OR: 1.08, 95%CI: 1.03–1.13) increased with a rise in total body FM percentage. Moreover, people with a higher FM to FFM ratio had increased odds of being prehypertensive (OR: 9.93, 95%CI: 1.28–76.99) and hypertensive (OR: 16.15, 95%CI: 2.47-105.52). Having a higher android to gynoid FM ratio was related to increased odds of being prehypertensive and hypertensive.ConclusionsThis study showed that a higher body FM, particularly in the android region, is associated with higher odds of having hypertension in older adults.

Association Between Urinary Bisphenols and Body Composition Among American Adults: Cross-Sectional National Health and Nutrition Examination Survey Study.

Bisphenol A (BPA), bisphenol S (BPS), and bisphenol F (BPF) are widely used in various consumer products. They are environmental contaminants with estrogenic properties that have been linked to various health outcomes. Understanding their impact on body composition is crucial for identifying potential health risks and developing preventive strategies. However, most current studies have only focused on their relationship with BMI. This study aimed to investigate the association between urinary levels of BPA, BPS, and BPF and body composition, including BMI, lean mass, and fat mass, in a large population-based sample. We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey 2003-2016. Body composition data were assessed using dual-energy X-ray absorptiometry, which provided precise measurements of lean mass, fat mass, and other indicators. We used multivariate linear regression models to estimate the associations, adjusting for potential confounders such as age, gender, race, socioeconomic factors, and lifestyle variables. The results revealed significant associations between bisphenol exposure and body composition. After adjusting for covariates, BPS showed a positive association with BMI, with quartiles 3 and 4 having 0.91 (95% CI 0.34-1.48) and 1.15 (95% CI 0.55-1.74) higher BMI, respectively, compared with quartile 1 (P<.001). BPA was negatively associated with total lean mass (TLM) and appendicular lean mass, with quartiles 2, 3, and 4 having -7.85 (95% CI -11.44 to -4.25), -12.33 (95% CI -16.12 to -8.54), and -11.08 (95% CI -15.16 to -7.01) lower TLM, respectively, compared with quartile 1 (P<.001). BPS was negatively associated with TLM, with quartiles 3 (β=-10.53, 95% CI -16.98 to -4.08) and 4 (β=-11.14, 95% CI -17.83 to -4.45) having significantly lower TLM (P=.005). Both BPA and BPS showed a positive dose-response relationship with trunk fat (BPA: P=.002; BPS: P<.001) and total fat (BPA: P<.001; BPS: P=.01). No significant association was found between BPF and any body composition parameter. This large-sample study highlights the associations between urinary levels of BPA and BPS and alterations in body composition, including changes in lean mass, fat mass, and regional fat distribution. These findings underscore the importance of understanding the potential health risks associated with bisphenol exposure and emphasize the need for targeted interventions to mitigate adverse effects on body composition.

The association between regional adiposity, cognitive function, and dementia-related brain changes: a systematic review.

Adiposity has been previously associated with cognitive impairment and Alzheimer's disease and related disorders (ADRD). Body mass index (BMI) is the most common measure of global adiposity, but inconsistent results were found since it is a global measurement. BMI does not represent regional fat distribution which differs between sexes, race, and age. Regional fat distribution may contribute differently to cognitive decline and Alzheimer's disease (AD)-related brain changes. Fat-specific targeted therapies could lead to personalized improvement of cognition. The goal of this systematic review is to explore whether regional fat depots, rather than central obesity, should be used to understand the mechanism underlying the association between adiposity and brain. This systematic review included 33 studies in the English language, conducted in humans aged 18 years and over with assessment of regional adiposity, cognitive function, dementia, and brain measures. We included only studies that have assessed regional adiposity using imaging technics and excluded studies that were review articles, abstract only or letters to editor. Studies on children and adolescents, animal studies, and studies of patients with gastrointestinal diseases were excluded. PubMed, PsychInfo and web of science were used as electronic databases for literature search until November 2022. Based on the currently available literature, the findings suggest that different regional fat depots are likely associated with increased risk of cognitive impairment, brain changes and dementia, especially AD. However, different regional fat depots can have different cognitive outcomes and affect the brain differently. Visceral adipose tissue (VAT) was the most studied regional fat, along with liver fat through non-alcoholic fatty liver disease (NAFLD). Pancreatic fat was the least studied regional fat. Regional adiposity, which is modifiable, may explain discrepancies in associations of global adiposity, brain, and cognition. Specific regional fat depots lead to abnormal secretion of adipose factors which in turn may penetrate the blood brain barrier leading to brain damage and to cognitive decline.

Comparative Evaluation of Waist-to-Height Ratio and BMI in Predicting Adverse Cardiovascular Outcome in People With Diabetes: A Systematic Review.

Central obesity is strongly associated with cardiovascular risk in people with diabetes. BMI does not reflect a regional fat distribution. The other anthropometric indices, which are markers of central obesity, like waist circumference and waist-hip ratio, are subject to age, sex, and ethnic variations. An index like waist-to-height ratio (WHtR), which considers central obesity, outperforms BMI in predicting cardiometabolic risk. With a single cut-off of 0.5, irrespective of age, sex, and ethnic variations, WHtR has a wide application in screening obesity in population settings. Previous systematic analyses were conducted in the general population, assessing cardiometabolic risk. The current study is the first systematic analysis to compare the applicability of WHtR and BMI in predicting both cardiovascular risk and adverse cardiovascular outcomes in people with diabetes. It includes prospective cohort studies, cross-sectional studies, and randomized control trials to generate evidence. The summary scores indicate that WHtR is probably a better indicator than BMI to assess cardiovascular risk in people with diabetes. A future meta-analysis will pave the way for more robust evidence.

Ratio of visceral fat area to body fat mass (VBR) is a superior predictor of coronary heart disease.

Ratio of visceral fat area to body fat mass (VBR) is a superior predictor of coronary heart disease.

The gut microbiome and regional fat distribution: Findings from the Baltimore Longitudinal Study of Aging.

The aim of this study was to examine associations of gut microbiome diversity and composition with directly measured regional fat distribution, including central fat, in a large community-based cohort. A cross-sectional investigation was conducted in the Baltimore Longitudinal Study of Aging (N=815, 55.2% female, 65.9% White). The fecal microbiome was assessed using whole-genome shotgun metagenomic sequencing, and trunk and leg fat was measured using dual x-ray absorptiometry. Multivariable-adjusted associations of regional fat measures, BMI, or waist circumference with microbiome alpha diversity metrics, microbiome beta diversity metrics, and species differential abundance (verified using two compositional statistical approaches) were examined. Trunk fat, leg fat, BMI, and waist circumference all significantly explained similar amounts of variance in microbiome structure. Differential abundance testing identified 11 bacterial species significantly associated with at least one measure of body composition or anthropometry. Ruminococcus gnavus was strongly and consistently associated with trunk fat mass, which is congruentwith prior literature. Microbiome diversity and composition, in particular higher abundance of Ruminococcus gnavus, were associated with greater trunkfat, in addition to other measures of obesity. Longitudinal studies are needed to replicate these findings, and if replicated, randomized trials are needed to determine whether interventions targeting microbiome features such as abundance of Ruminococcus gnavuscan lead to reductions in trunk fat and its metabolic sequelae.

Relationship Between Regional Adiposity Distribution and Incident Heart Failure in General Populations without Cardiovascular Disease

BackgroundObesity is associated with a high risk of heart failure. However, the contribution of regional fat distribution evaluated using bioimpedance analysis toward heart failure risk in the general population without cardiovascular disease has rarely been studied. MethodsThis study included 483,316 participants without heart failure and cardiovascular disease from the UK Biobank study. The regional fat mass was determined by bioimpedance analysis and calculated by dividing the square of height in meters (kg/m2). This study evaluated the association of regional fat mass (arm fat index [AFI], trunk fat index [TFI], and leg fat index [LFI]) with the risk of incident heart failure and whether regional fat mass adds a further prognostic value for heart failure besides body mass index (BMI) in a large prospective cohort study. ResultsDuring the median 12.1 years, 3134 incident heart failure cases occurred. After adjustment for BMI and other confounding factors, each 1-standard deviation increase in LFI was associated with a 21% lower heart failure risk even after adjusting for BMI and other confounding factors (hazard ratio [HR] 0.79; 95% confidence interval [CI], 0.73-0.85). However, we did not observe heart failure-associated risks with AFI and TFI (HR 1.04; 95% CI, 0.99-1.09; HR 0.97, 95% CI, 0.91–1.04, respectively). Subgroup analysis demonstrated that the protective role of LFI was more prominent in the elderly and female participants (P < .01). ConclusionRegional fat measurement other than BMI can improve heart failure risk stratification; leg fat plays a protective role, yet arm and trunk fat do not, in the general population without cardiovascular disease.

Lean body mass but not body fat mass is related with leukocyte telomere length in children.

The aim of this study was to investigate the relationship between body composition and leukocyte telomere length (LTL) in healthy Chinese children aged 6-11 years. This cross-sectional study enrolled 406 healthy children (175 girls and 231 boys). The relative telomere length in their peripheral blood leukocytes was determined via quantitative polymerase chain reaction. Dual-energy X-ray absorptiometry was used to determine body fat content and regional fat distribution, appendicular skeletal muscle mass (ASM), bone mineral density (BMD) and bone mineral content (BMC) at the total body (TB) and total body less head (TBLH) levels, and total body lean mass (TBLM) was then determined. ASM/height2 (ASMI) was also calculated. After adjusting for potential covariates, multiple linear regression analyses revealed that neither body fat content nor regional body fat distribution were significantly associated with LTL (β = -8.48 × 10-6-1.44 × 10-1, p = 0.227-0.959). However, ASM, ASMI, TB BMC/TB BMD, TBLH BMC/TBLH BMD and TBLM were positively associated with LTL (β = 8.95 × 10-6-4.95 × 10-1, p = 0.005-0.035). Moreover, analysis of covariance revealed there was a statistically significant dose-dependent positive association between LTL and ASM, TB BMC/BMD, TBLH BMC/BMD, and TBLM (p-trend = 0.002-0.025). Skeletal muscle mass and bone mass but not body fat content or distribution were significantly associated with LTL in this pediatric population.

RF18 | PSAT146 Bone Quality in Lean Adults with Metabolic Syndrome

Abstract Purpose Metabolic syndrome (MetS) comprises a constellation of risk factors for cardiovascular disease, which are thought to be derived from truncal obesity. Adipose tissue can have positive effects on bone density through mechanical stimulation on weight bearing sites and can have hormonal influences which affect bone cells, however in obesity this relationship is inversed as the deleterious effects of excess fat mass predominate. It is unclear how MetS and the regional distribution of fat relate with bone density and bone quality in lean individuals who do not benefit from increased weight bearing. Methods We performed a cross sectional analysis of adults who underwent bone density and body composition by dual energy x-ray absorptiometry (DXA) at a university health system bone clinic, and had laboratory and demographic data available in the electronic medical record. We included adults with BMI below 24.9 kg/m2 in the analysis. Individuals were classified as being metabolically unhealthy lean (MUL) when they fulfilled at least 2 of the following criteria: blood pressure &amp;gt; 130/85, triglyceride &amp;gt;150 mg/dL, HDL &amp;lt; 50 mg/dL for women and &amp;lt; 40 mg/dL for men, fasting plasma glucose &amp;gt;100mg/dL (or HbA1c &amp;gt;=5.7), and metabolically healthy lean (MHL) when they did not fit the criteria. Linear regression was used to evaluate the association of body composition fat parameters with trabecular bone score (TBS), and bone mineral density (BMD) at the total hip (TH). Results Among the 119 (100%) lean adults, 50 (42%) were classified as being MUL. Mean age was 62 ±14 years old and mean BMI was 22 ±1.9kg/m2. The population was mostly white 105 (88%) and 70 (41%) were Hispanics. Additionally, 43 subjects (40%) had a history of a previous fracture. Total body fat was similar between the two groups (mean,%) MHL 33.5, MUL 34.1 (p=0.32), as were age (mean, years) MHL 62.3 vs MUL 62.5 (p=0.48), BMI (mean, kg/m2) MHL 22.2, MUH 22.2 (p=0.49), TH BMD (mean, g/cm2) MHL 0.74, MUL 0.72 (p=0.140) and TBS (mean, unitless) MHL 1.34, MUL 1.33 (p=0.308). However, visceral adipose tissue area (VAT) (mean, cm2) was statistically significantly different between the groups (MHL 69.0, MUL 86.7, p=0.004). In linear regression analyses total body fat had negative association with TBS (B=-0.44, p&amp;lt;0.001) and TH BMD (B= -0.37, p&amp;lt;0.001) while VAT had negative association with TBS (B=-0.26, p=0.02) but not TH BMD (B=-0.17, p=0.08). Conclusion In our sample of older lean individuals body fat distribution varied by classification of metabolic health. Total body fat amount was associated with decreasing bone density and quality, while higher truncal fat as measured by VAT area was associated with decreasing bone quality. Our findings suggest that excess body fat may have deleterious effects on bone health even in lean individuals Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m., Sunday, June 12, 2022 1:06 p.m. - 1:11 p.m.