Trunk Fat Research Articles

Relationship of Fat Mass Ratio, a Biomarker for Lipodystrophy, With Cardiometabolic Traits.

Familial partial lipodystrophy (FPLD) is a heterogenous group of syndromes associated with a high prevalence of cardiometabolic diseases. Prior work has proposed DEXA-derived fat mass ratio (FMR) - defined as trunk fat percentage (trunk fat %) divided by leg fat percentage (leg fat %) - as a biomarker of FPLD, but this metric has not previously been characterized in large cohort studies. We set out to (1) understand the cardiometabolic burden of individuals with high FMR in up to 40,796 participants in the UK Biobank and 9,408 participants in the Fenland study, (2) characterize the common variant genetic underpinnings of FMR, and (3) build and test a polygenic predictor for FMR. Participants with high FMR were at higher risk for type 2 diabetes (OR = 2.30, p = 3.5 × 10-41) and MASLD/MASH (OR = 2.55, p = 4.9 × 10-7) in UK Biobank, and had higher fasting insulin (difference = +19.8 pmol/L, p = 5.7 × 10-36) and fasting triglycerides (difference = +36.1 mg/dL, p = 2.5 × 10-28) in the Fenland Study. Across FMR and its component traits, 61 conditionally independent variant-trait pairs were discovered, including 13 newly-identified pairs. A polygenic score for FMR was associated with increased risk of cardiometabolic diseases. This work establishes the cardiometabolic significance of high FMR - a biomarker for FPLD - in two large cohort studies and may prove useful in increasing diagnosis rates of patients with metabolically unhealthy fat distribution to enable treatment or a preventive therapy.

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.

Body composition and metabolic syndrome in patients with type 1 diabetes.

In recent years, the prevalence of obesity and metabolic syndrome in type 1 diabetes (T1DM) patients has gradually increased. Insulin resistance in T1DM deserves attention. It is necessary to clarify the relationship between body composition, metabolic syndrome and insulin resistance in T1DM to guide clinical treatment and intervention. To assess body composition (BC) in T1DM patients and evaluate the relationship between BC, metabolic syndrome (MS), and insulin resistance in these indi-viduals. A total of 101 subjects with T1DM, aged 10 years or older, and with a disease duration of over 1 year were included. Bioelectrical impedance analysis using the Tsinghua-Tongfang BC Analyzer BCA-1B was employed to measure various BC parameters. Clinical and laboratory data were collected, and insulin resistance was calculated using the estimated glucose disposal rate (eGDR). MS was diagnosed in 16/101 patients (15.84%), overweight in 16/101 patients (15.84%), obesity in 4/101 (3.96%), hypertension in 34/101 (33.66%%) and dyslipidemia in 16/101 patients (15.84%). Visceral fat index (VFI) and trunk fat mass were significantly and negatively correlated with eGDR (both P < 0.001). Female patients exhibited higher body fat percentage and visceral fat ratio compared to male patients. Binary logistic regression analysis revealed that significant factors for MS included eGDR [P = 0.017, odds ratio (OR) = 0.109], VFI (P = 0.030, OR = 3.529), and a family history of diabetes (P = 0.004, OR = 0.228). Significant factors for hypertension included eGDR (P < 0.001, OR = 0.488) and skeletal muscle mass (P = 0.003, OR = 1.111). Significant factors for dyslipidemia included trunk fat mass (P = 0.033, OR = 1.202) and eGDR (P = 0.037, OR = 0.708). Visceral fat was found to be a superior predictor of MS compared to conventional measures such as body mass index and waist-to-hip ratio in Chinese individuals with T1DM. BC analysis, specifically identifying visceral fat (trunk fat), may play an important role in identifying the increased risk of MS in non-obese patients with T1DM.

Connections between body composition and dysregulation of islet α- and β-cells in type 2 diabetes

BackgroundAccompanying islet α- and β-cell dysregulation in type 2 diabetes (T2D) at the microscopic scale, alterations in body composition at the macroscopic scale may affect the pathogenesis of T2D. However, the connections between body composition and islet α-cell and β-cell functions in T2D have not been thoroughly explored.MethodsFor this cross-sectional study, we recruited a total of 729 Chinese Han patients with T2D in a consecutive manner. Dual-energy X-ray absorptiometry (DXA) was used to measure body composition, which included total bone-free mass, total fat and lean mass, trunk fat and lean mass and limb fat and lean mass. Every patient underwent an oral glucose tolerance test to simultaneously detect glucose, C-peptide and glucagon. The indices of islet α-cell function included fasting glucagon levels and the area under the curve of glucagon after a challenge (AUCglucagon), while the indices of β-cell function included the insulin sensitivity index derived from C-peptide (ISIC-peptide) and the area under the curve of C-peptide after a challenge (AUCC-peptide).ResultsAmong all patients, fat mass, especially trunk fat mass, was significantly correlated with ISIC-peptide and AUCC-peptide levels (r = − 0.330 and 0.317, respectively, p < 0.001), while lean mass, especially limb lean mass, was significantly correlated with fasting glucagon and AUCglucagon levels (r = − 0.196 and − 0.214, respectively, p < 0.001). Moreover, after adjusting for other relevant variables via multivariate linear regression analysis, increased trunk fat mass was independently associated with decreased ISIC-peptide (β = − 0.247, t = − 3.628, p < 0.001, partial R2 = 10.9%) and increased AUCC-peptide (β = 0.229, t = 3.581, p < 0.001, partial R2 = 8.2%), while decreased limb lean mass was independently associated with increased fasting glucagon (β = − 0.226, t = − 2.127, p = 0.034, partial R2 = 3.8%) and increased AUCglucagon (β = − 0.218, t = − 2.050, p = 0.041, partial R2 = 2.3%). Additionally, when separate analyses were performed with the same concept for both sexes, we found that increased trunk fat mass was still independently associated with decreased ISIC-peptide and increased AUCC-peptide, while decreased limb lean mass was still independently associated with increased fasting glucagon and AUCglucagon.ConclusionsIncreased trunk fat mass may partly account for decreased insulin sensitivity and increased insulin secretion, while decreased limb lean mass may be connected to increased fasting glucagon and postprandial glucagon secretion.

Prevalence and influencing factors of muscle mass loss in adults with diabetes and a high body fat percentage: A cross-sectional study.

In adults with type 2 diabetes (T2DM), sarcopenia and obesity are two common body composition issues. We investigated the associated influencing factors of muscle mass loss in obese adults with T2DM, to provide a theoretical basis for the prevention of sarcopenic obesity in patients with T2DM. We recruited 315 participants in this study. The participants underwent body composition assessment and clinical information was collected. Dual-energy X-ray absorptiometry was used to verify the accuracy of the body composition data. Based on their body fat percentage, 189 patients with T2DM were classified as obese. Patients with T2DM and obesity were grouped into the muscle mass loss group and non-muscle mass loss group based on gender. We collected demographic and clinical information about patients with T2DM who were obese, including their age, gender, body mass index (BMI), appendicular skeletal muscle index (ASMI), and body fat percentage (PBF). Among the participants who were obese and had T2DM, 56.61% (107/189) experienced muscle mass loss, with a detection rate of 43.42% (33/76) among females and 65.49% (74/113) among males. Body mass index, fat index, Android fat, Gynoid fat, limb fat, trunk fat, and total body bone mineral content were all lower in the muscle mass loss group compared to the non-muscle mass loss group, regardless of gender (all P< 0.001). Muscle mass loss in obese adults with T2DM was affected by BMI, body fat index, and limb fat. Muscle mass loss is more prevalent in adults with T2DM and a high PBF. Body mass index, body fat index, and limb fat are the protective factors of muscle mass loss in adult patients with T2DM and obesity.

DXA-based Fat Mass With Risk of Worsening Insulin Resistance in Adolescents: A 9-Year Temporal and Mediation Study.

Surrogate measures of childhood and adolescent obesity have impaired the understanding of the relationship of body composition with insulin resistance in the young population. We aim to examine the longitudinal associations of directly measured total fat mass, trunk fat mass, and lean mass with the risk of hyperglycemia, hyperinsulinemia, and insulin resistance from ages 15 to 24 years, the mediation path through which lipids and inflammation influence insulin resistance, and whether increased fat mass temporally precede insulin resistance. We studied 3160 adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC), UK birth cohort, who had complete dual-energy x-ray absorptiometry measure and fasting blood samples at age 15 years and repeated measures at ages 17- and 24-years clinic visit. Fasting glucose greater than 6.1 mmol/L, insulin greater than 11.78 mU/L, and homeostatic model assessment for insulin resistance (HOMA-IR) greater than or equal to the 75th percentile were categorized as hyperglycemia, hyperinsulinemia, and high insulin resistance, respectively. Longitudinal associations were examined with generalized logit-mixed-effect models, while mediation and temporal path analyses were examined using structural equation models, adjusting for cardiometabolic and lifestyle factors. Among 3160 participants (51% female), fat mass and lean mass increased linearly both in males and females, while glucose, insulin, and HOMA-IR had a U-shaped course from age 15 through 24 years. After full adjustment, each 1-kg cumulative increase in total fat mass (odds ratio 1.12 [95% CI, 1.11-1.13]) and trunk fat mass (1.21 [1.19-1.23]) from ages 15 through 24 years were associated with a progressively worsening risk of high insulin resistance as well as hyperglycemia and hyperinsulinemia. The association of increased total fat mass with increased insulin resistance was partly mediated by triglycerides (9% mediation). In the temporal path analysis, higher total fat mass at age 15 years was associated with higher insulin resistance at age 17 years, but not vice versa. Higher total fat mass at age 17 years was bidirectionally associated with higher insulin resistance at 24 years. Mid-adolescence may be an optimal time for interrupting the worsening fat mass-insulin resistance pathologic cycle and attenuating the risk of progressively worsening metabolic dysfunction before young adulthood.

Associations of Serum Uric Acid to High-Density Lipoprotein Cholesterol Ratio with Trunk Fat Mass and Visceral Fat Accumulation.

It has been reported recently that the ratio of uric acid to high-density lipoprotein cholesterol (UHR) is correlated with several metabolic disorders. The present study aimed to investigate the associations of UHR with body fat content and distribution. This study enrolled 300 participants (58 men and 242 women) aged 18 to 65 years. The levels of serum uric acid and high-density lipoprotein cholesterol were measured by standard enzymatic methods. The overall fat content and segmental fat distribution were assessed with an automatic bioelectrical impedance analyzer. In the population with obesity, the visceral fat area (VFA) and subcutaneous fat area (SFA) were measured using magnetic resonance imaging. Among the study population, 219 individuals (73.0%) were with obesity. The median level of UHR in individuals with obesity was 33.7% (26.2% - 45.9%), which was significantly higher than that in those without obesity [22.6% (17.0% - 34.4%), P < 0.01]. UHR was positively associated with overall fat content and segmental fat distribution parameters (all P < 0.01). In multivariate linear regression analysis, compared with body mass index, waist circumference was more closely associated with UHR (standardized β = 0.427, P < 0.001) after adjusting for confounding factors. Additionally, total fat mass (standardized β = 0.225, P = 0.002) and trunk fat mass (standardized β = 0.296, P = 0.036) were more closely linked to UHR than total fat-free mass and leg fat mass, respectively. In the population with obesity, VFA was independently correlated with UHR (P < 0.01), while SFA was not associated with UHR. UHR was significantly associated with overall fat content and trunk fat accumulation. In the population with obesity, UHR was positively associated with VFA. Attention should be paid to the role of excessive trunk fat mass in the relationship between UHR and metabolic disorders.

Bifidobacterium lactis IDCC 4301 (B. lactis Fit™) supplementation effects on body fat, serum triglyceride, and adipokine ratio in obese women: a randomized clinical trial.

Obesity is a common metabolic disease characterized by abnormal fat accumulation. It contributes to health issues, such as type 2 diabetes, cardiovascular disease, and dyslipidemia, necessitating continuous management through diet and physical activity. Probiotics, particularly Bifidobacterium lactis IDCC 4301 (B. lactis Fit™), have shown promise in positively regulating the gut microbiota. Therefore, this study aimed to evaluate the anti-obesity effect of B. lactis IDCC 4301 (B. lactis Fit™) in obese women. A randomized, double-blind, placebo-controlled, parallel-arm study was performed in 99 volunteers with a body mass index (BMI) of 25-30 kg m-2. The participants were randomly assigned to probiotics (n = 49, >5.0 × 109 CFU day-1) or placebo (n = 50) groups. Body fat, lipid profiles, and adipokine levels were assessed at baseline and at 12 weeks. After 12 weeks, changes in total fat (placebo -0.16 ± 0.83 kg; probiotics -0.45 ± 0.83 kg; p = 0.0407), trunk fat (placebo -0.03 ± 0.50 kg; probiotics -0.22 ± 0.51 kg; p = 0.0200), and serum triglyceride concentration (placebo 13 ± 60 mg dL-1; probiotics -15 ± 62 mg dL-1; p = 0.0088) were significantly different between the groups. The difference in total fat mass change between groups among postmenopausal women was greater than that of all women. A significant positive correlation was found between the change in total fat mass and log leptin/adiponectin ratio (R = 0.371, p = 0.0112) in the probiotics group. In addition, BMI (26.6 ± 1.9 kg m-2 to 26.4 ± 2.0 kg m-2, p = 0.0009) and leg fat (42 ± 5% to 41 ± 5%, p = 0.0006) significantly decreased in the probiotics group after 12 weeks, but there was no difference in the placebo group. In conclusion, B. lactis IDCC 4301 (B. lactis Fit™) may be associated with body fat loss through changes in metabolic health parameters, such as serum triglyceride and adipokine levels. The clinical trial registry number is KCT0007425 (https://cris.nih.go.kr).

Body Composition Changes Impact Islet β-Cell Function in Patients With Type 2 Diabetes Mellitus.

Background: Identifying β-cells dysregulation in type 2 diabetes mellitus (T2DM) is crucial. Weight fluctuations are frequently observed during diabetes treatment. However, the relationship between body composition changes and islet β-cell function in individuals with T2DM remains insufficiently investigated. Methods: This retrospective longitudinal study encompassed a cohort of 775 T2DM patients, who underwent body composition measuring using dual-energy X-ray absorptiometry (DEXA) and followed up for a median of 2.29 years. Key metrics included body mass index (BMI), fat mass index (FMI), trunk fat mass index (TFMI), muscle mass index (MMI), appendicular skeletal muscle mass index (ASMI), muscle/fat mass ratio (M/F), and the appendicular skeletal muscle mass/trunk fat mass ratio (A/T) were then categorized and grouped. Insulin, C-peptide, and glucose levels were assessed concurrently following a glucose load. β-cell function included insulin resistance (HOMA-IR), insulin sensitivity (Matsuda index (MI)), and insulin secretion evaluated by HOMA-β and C-peptidogenic index (CGI). Results: Although no significant changes in BMI were observed, patients with T2DM at readmission exhibited higher FMI, TFMI, and ASMI, as well as elevated levels of HOMA-IR, MI, and CGI compared to baseline measurements. And lower MI, higher levels of CGI, and HOMA-IR were observed in BMI increased group. Univariate correlation analysis revealed a negative association between changes in BMI (ΔBMI) and ΔMI, while positive associations were observed in both ΔHOMA-IR and ΔCGI. Among body composition indexes, ΔFMI exhibited the strongest correlation with ΔHOMA-IR (r = 0.255, p < 0.001), and ΔASMI was positively associated with ΔMI and ΔCGI (r = 0.131 and 0.194, respectively). Moreover, increased levels of BMI and FMI were associated with a greater risk of progressive insulin resistance compared to the decreased, whereas the trend was converse in ASMI and A/T. Conclusions: Increased FMI may partially contribute to the deterioration of insulin resistance, while increased ASMI is associated with improved insulin sensitivity and secretion. Maintaining an appropriate BMI and muscle/fat ratio is conductive to prevent the progression of insulin resistance in patients with T2DM.

Development and cross-validation of prediction equations for body composition in adult cancer survivors from the Korean National Health and Nutrition Examination Survey (KNHANES).

Epidemiological studies frequently use indices of adiposity related to mortality. However, no studies have validated prediction equations for body composition in adult cancer survivors. We aimed to develop and cross-validate prediction equations for body fat mass (BFM), lean body mass (LBM), trunk fat mass (TFM), and appendicular lean mass (ALM) in adult cancer survivors using sociodemographic, anthropometric, and laboratory test data. This study included adult cancer survivors from the Korean National Health and Nutrition Examination Survey 2008-2011 with complete data on Dual-energy X-ray absorptiometry (DXA) measurements. A total of 310 participants were randomly divided into development and cross-validation groups (5:5 ratio). Age, height, weight, waist circumference, serum creatinine levels, and lifestyle factors were included as independent variables The predictive equations were developed using a multiple linear regression and their predictive performances were primarily evaluated with R2 and Concordance Correlation Coefficient (CCC). The initial equations, which included age, height, weight, and waist circumference, showed different predictive abilities based on sex for BFM (total: R2 = 0.810, standard error of estimate [SEE] = 3.072 kg, CCC = 0.897; men: R2 = 0.848, SEE = 2.217 kg CCC = 0.855; women: R2 = 0.791, SEE = 2.194 kg, CCC = 0.840), LBM (total: R2 = 0.736, SEE = 3.321 kg, CCC = 0.838; men: R2 = 0.703, SEE = 2.450 kg, CCC = 0.774; women: R2 = 0.854, SEE = 2.234 kg, CCC = 0.902), TFM (total: R2 = 0.758, SEE = 1.932 kg, CCC = 0.844; men: R2 = 0.650, SEE = 1.745 kg, CCC = 0.794; women: R2 = 0.852, SEE = 1.504 kg, CCC = 0.890), and ALM (total: R2 = 0.775, SEE = 1.726 kg, CCC = 0.876; men: R2 = 0.805, SEE = 1.320 kg, CCC = 0.817; women: R2 = 0.726, SEE = 1.198 kg, CCC = 0.802). When additional factors, such as creatinine, smoking, alcohol consumption, and physically inactive were included in the initial equations the predictive performance of the equations were generally improved. The prediction equations for body composition derived from this study suggest a potential application in epidemiological investigations on adult cancer survivors.

Impaired Sensitivity to Thyroid Hormones is Associatedwith Central Obesity in Euthyroid Type 2 Diabetes Mellitus Patients with Overweight and Obesity.

Thyroid hormone levels are associated with the distribution of body components in humans. This study aimed to investigate the associations between thyroid hormone (TH) levels, central sensitivity to THs, and body composition in overweight and obese patients with euthyroid type 2 diabetes mellitus (T2DM). This cross-sectional study included 1215 euthyroid T2DM patients (721 men and 494 women) aged 20-80 years. The thyroid hormone sensitivity indices included the thyroid feedback quartile-based index (TFQI), thyrotroph T3 resistance index (TT3RI), thyrotroph T4 resistance index (TT4RI), and thyroid-stimulating hormone index (TSHI). The appendicular fat ratio, trunk fat ratio, android fat ratio, gynoid fat ratio, and appendicular skeletal muscle mass (ASM) were measured via dual-energy X-ray absorptiometry. The data revealed a greater proportion of subjects with impaired central sensitivity to THs in the obese group. TFQIFT4 and TFQIFT3 levels were positively correlated with the upper limb fat ratio, lower limb fat ratio, gynoid fat ratio, and total fat ratio. TSHI was positively correlated with body mass index (BMI), upper limb fat ratio, lower limb fat ratio, trunk fat ratio, android fat ratio, gynoid fat ratio, total fat ratio, and appendicular skeletal muscle mass index (ASMI) in women. In men, TSHI was only positively correlated with upper limb fat ratio, lower limb fat ratio, and total fat ratio. Logistic regression analysis indicated that TT3RI and TFQIFT3 were independently and positively associated with central obesity and low muscle mass in overweight and obese men. No significant differences were found among the women. THs central sensitivity is related to the body composition of euthyroid T2DM patients. Specifically, high levels of TT3RI and TFQIFT3 are associated with central obesity and low muscle mass in T2DM men with overweight and obesity.

Comparison of coronary artery lesion complexity and body component parameters measured by TANITA.

Obesity is one of the main reversible causes of coronary artery disease. To investigate the relationship between body component measurements calculated with TANITA and SYNTAX score (SXscore), which indicates coronary complexity. 200 acute subendocardial myocardial infarction patients were included in our study. Body component measurements were made with the TANITA BC-601 device. After coronary angiography, patients were divided into two groups: high SXscore (≥ 22) and low-medium SXscore (< 22). When the high SXscore group (50 patients) was compared with the low medium SXscore group (150 patients); for waist height ratio (p = 0.001), total fat weight (p = 0.001), total fat percentage (p = 0.006), total water percentage (p = 0.001), trunk fat percentage (p = 0.001), internal fat (p = 0.001) and metabolic age (p < 0.001), a statistical difference was found. In the correlation analysis, a correlation was detected between high SXscore and the waist height ratio (p = 0.042), trunk fat percentage (p = 0.047), internal fat (p < 0.001) and metabolic age (p = 0.009). ROC curve analysis for prediction of high SXscore detection; the cut-off value for internal fat and metabolic age was found to be 13.5-60.5 with 60-64% sensitivity and 61.3-62.7% specificity. We demonstrated the relationship between parameters such as internal fat, trunk fat percentage and metabolic age calculated by TANITA and SXscore, which is the coronary complexity score. We recommend that patients with high values detected during TANITA measurements be followed more carefully in terms of primary preventive medicine.

Association of Questionnaire-Based Physical Activity Analysis and Body Composition Dynamics in Type 2 Diabetes: A Cross-Sectional Study.

Physical activity (PA) exerts an important influence on glycemic control in type 2 diabetes (T2D) patients. Alterations in body composition in patients with T2D may be involved in the overall pathophysiologic process, but PAs and alterations in body composition have been poorly studied. A total of 615 patients with T2D were selected by convenient sampling. The patients were investigated with the International Physical Activity Questionnaire (IPAQ-S). Moreover, biochemical indices were collected, and the progression of the body composition of the subjects was determined via dual-energy X-ray absorptiometry (DXA). The variables included lumbar bone mineral density (LSBMD), femoral neck bone mineral density (FNBMD), hip bone mineral density (HBMD), whole-body bone mineral density (TBMD), limb skeletal muscle mass index (ASMI), whole-body fat percentage (B-FAT) and trunk fat percentage (T-FAT). Moreover, the levels of physical activity (high level of physical activity [H-PA], medium level of physical activity [M-PA] and low level of physical activity [L-PA]) were divided into three groups to analyze the changes in patient body composition with changes in physical activity level. One-way analysis of variance showed that β-CTX, TP1NP, HbA1c, B-FAT and T-FAT increased significantly (p<0.05), while 25(OH)D, LSBMD, FNBMD, HBMD, TBMD and ASMI decreased significantly (p<0.001) with the decrease of physical activity. However, there was no significant difference in serum lipids between lnHOMA-ir and lnHOMA-β (p>0.05). Multiple linear regression model was established to gradually adjust for clinical confounding factors. It was found that physical activity level was independently positively correlated with LSBMD, FNBMD, HBMD, TBMD, and ASMI, and was independently negatively correlated with B-FAT and T-FAT in patients with type 2 diabetes. A lack of physical activity is an independent risk factor for decreased bone mineral density, decreased skeletal muscle content and increased fat content in patients with T2D.

Increased legs-to-total fat percentage ratio in females with a normal body mass index: A change in lifestyle or the adaptation process of the body

Monitoring the prevalence of obesity is of great importance for assessing lifestyle interventions aimed at preventing or reducing the health and economic burden of obesity. A sedentary Westerntype lifestyle results in an increase in the incidence of normal-weight (e.g., thin fat) obesity. In the present cross-sectional study, the regional body composition status (using a multifrequency, medically approved electrical bioimpedance monitor) of 844 Slovene adults was examined. The primary aim was to compare the leg fat percentage to total body fat percentage (LEGFAT%-toTOTFAT%) and to trunk fat percentage (TRUFAT%) (LEGFAT%-to-TRUFAT%) ratios of participants in the normal and obese body mass index (BMI) and categories according to the BMI and obesity classifications of the World Health Organization. In addition, examined how correlated with, sex, and age, according to obesity classification cut-offs. Results showed, for the whole sample, that increases by an average of 0.13% each year (ceteris paribus). However, females in the normal BMI and TOTFAT% categories, but not males, had significantly higher LEGFAT%-to-TOTFAT% and LEGFAT%-to-TRUFAT% ratios than those in the obese category. Furthermore, adjusted R2 (linear regression) showed that 82.5% of the variation in LEGFAT% was explained by variations in TOTFAT%, sex, and age. The present results indicated the increasing importance of studying the regional body composition status, especially of TRUFAT% and LEGFAT% compared with TOTFAT% (beyond the known sex differences). The clinical relevance of the increasing disproportionality in the regional body composition status of females with normal BMI and TOTFAT% needs to be further clarified.

Physiological and Morphometric Differences in Resident Moderate-Altitude vs. Sea-Level Mice.

INTRODUCTION: High-altitude [>2400 m (7874 ft)] acclimatization has been well studied with physiological adaptations like reductions in body weight and exercise capacity. However, despite the significance of moderate altitude [MA, 1524-2438 m (5000-8000 ft)], acclimatization at this elevation is not well described. We aimed to investigate differences in mice reared at MA compared to sea level (SL). We hypothesized that MA mice would be smaller and leaner and voluntarily run less than SL mice.METHODS: C57BL/6 mice reared for at least three generations in Laramie, WY [2194 m (7198 ft), MA], were compared to C57BL/6J mice from Bar Harbor, ME [20 m (66 ft), SL]. We quantified body composition and exercise outputs as well as cardiopulmonary morphometrics. Subsets of MA and SL mice were analyzed to determine differences in neuronal activation after exercise.RESULTS: When body weight was normalized to tibia length, SL animals weighed 1.30 g ⋅ mm-1 while MA mice weighed 1.13 g · mm-1. Total fat % and trunk fat % were higher in MA mice with values of 41% and 39%, respectively, compared to SL mice with values of 28% and 26%, respectively. However, no differences were noted in leg fat %. MA animals had higher heart mass (119 mg) and lower lung mass (160 mg) compared to SL mice heart mass (100 mg) and lung mass (177 mg). MA mice engaged in about 40% less voluntary wheel-running activity than SL animals.DISCUSSION: Physiological differences are apparent between MA and SL mice, prompting a need to further understand larger scale implications of residence at moderate altitude.O'Connor AE, Hatzenbiler DM, Flom LT, Bobadilla A-C, Bruns DR, Schmitt EE. Physiological and morphometric differences in resident moderate-altitude vs. sea-level mice. Aerosp Med Hum Perform. 2023; 94(12):887-893.

1984. Effects of Semaglutide on Adipose Tissue in HIV-Associated Lipohypertrophy

Abstract Background Lipohypertrophy (central adipose tissue (AT) accumulation) is a common and significant problem in people with HIV (PWH). Pathogenesis remains elusive; yet, AT abnormalities are key drivers of cardiometabolic co-morbidities in HIV. We aimed to assess effects of semaglutide, a glucagon-like peptide-1 receptor agonist, on AT in PWH with lipohypertrophy. Methods We conducted a randomized, double-blinded, placebo-controlled trial of virologically-suppressed, non-diabetic PWH ≥ 18 years of age on stable antiretroviral therapy (ART) with body mass index (BMI) ≥ 25 kg/m2, increased waist circumference/waist-to-hip ratio, and subjective increased abdominal girth after ART initiation. Participants were randomized 1:1 to 32 weeks semaglutide (8-week titration + 24 weeks 1.0 mg weekly subcutaneous injection) or matching placebo. Computed tomography and whole-body dual-energy X-ray absorptiometry were used to measure area/density in abdominal AT [total (TAT), visceral (TAT), and subcutaneous (SAT)] and body composition [lean body mass (LBM), limb/trunk/total body fat (TBF)], resp. Semaglutide effects were estimated using generalized estimating equations or simultaneous quantile regressions on outcome variables. Results 108 participants were enrolled (N = 54 semaglutide: median age = 52 years, 70% male, 61% Black, 83% integrase inhibitor). Groups were well-matched at baseline. In unadjusted models, semaglutide group had greater reductions (P &amp;lt; 0.05) in BMI, homeostatic model of insulin resistance (HOMA-IR), trunk fat, TBF (at quantile ≥ 75th), TAT, and SAT with trends (P &amp;lt; 0.1) for limb fat and VAT (Fig 1/Table 1). Semaglutide effects remained significant for BMI, HOMA-IR, trunk fat, TAT, and VAT after adjusting for age, sex, CD4, and ART duration (Table 2); caloric intake was also significant at ≤ 50th quantile. No differences were seen in LBM, AT density, or VAT/TAT ratio. Semaglutide was well-tolerated; serious adverse events were rare. Conclusion Semaglutide significantly decreased central fat in PWH with lipohypertrophy, primarily driven by reductions in VAT. Semaglutide may offer an effective treatment to decrease visceral adiposity and reduce co-morbidity risk. Further investigation is needed to determine mechanisms by which reductions in visceral adiposity occur. Disclosures Grace A. McComsey, MD, Gilead Sciences: Advisor/Consultant|Gilead Sciences: Grant/Research Support|Janssen: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|ViiV Healthcare: Advisor/Consultant|ViiV Healthcare: Grant/Research Support

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.

Sex differences in the associations between relative fat mass and all-cause and cardiovascular mortality: A population-based prospective cohort study

Background and aimsThe novel sex-specific anthropometric equation relative fat mass (RFM) is a new estimator of whole-body fat %. The study aimed to investigate the predictive role of RFM in cardiometabolic abnormalities, cardiovascular disease (CVD), all-cause and cardiovascular mortality, and explored potential sex differences. Methods and resultsThe study analyzed data from 26,754 adults in NHANES 1999–2010, with a median follow-up of 13.8 years. The correlation between RFM and body composition as well as fat distribution assessed by dual-energy X-ray absorptiometry was investigated. Weighted multivariable generalized linear models, Cox proportional hazards models and restricted cubic spline were applied to investigate the predictive role of RFM in metabolic markers, cardiovascular risk factors, CVD, all-cause and cardiovascular mortality. RFM exhibited a robust correlation with both whole-body fat % and trunk fat %. Higher RFM exhibited a stronger association with impaired glucose homeostasis, serum lipids, the incidence of hypertension, and coronary heart disease in males, while a stronger association with C-reactive protein in females. A U-shaped association between RFM and all-cause mortality was observed only in males. The hazard ratio (HR) of all-cause and cardiovascular mortality in males increased rapidly when RFM exceeded 30. However, in females, the HR of all-cause and cardiovascular mortality fluctuated until RFM exceeded 45, after which it increased rapidly. ConclusionRFM was a sex-specific estimator for both general and central obesity, sex-specific differences in predicting cardiometabolic abnormalities and adverse events using RFM might be partially attributed to differences in body composition and fat distribution between sexes.

Higher childhood weight gain, lower skeletal muscle mass, and higher cereal consumption in normal-weight Japanese women with high-percentage trunk fat: a subanalysis study.

Normal-weight but high-percentage trunk fat phenotype was characterized in a setting where adiposity is not associated with educational and socioeconomic status. Body size trajectory since birth, current body composition measured using whole-body dual-energy X-ray absorptiometry, cardiometabolic traits, serum adipokines, and dietary intake were measured cross-sectionally in 251 normal weight Japanese female university students whose fasting triglyceride and homeostasis model assessment-insulin resistance (HOMA-IR) averaged 56mg/dL and 1.2, respectively. They were grouped according to tertile of percentage trunk fat. Although HOMA-IR did not differ among three groups, high-percentage trunk fat was associated with higher triglyceride and apolipoprotein B, and lower HDL cholesterol and apolipoprotein A1. In multivariate logistic regression analyses, weight-adjusted skeletal muscle mass (OR: 0.13, 95% CI: 0.04-0.38, p < 0.001), weight gain from birth to age 12years (OR: 1.214、95% CI: 1.008-1.463、p = 0.04), and cereal consumption (OR:1.008, 95% CI: 1.000-1.016, p = 0.04) were associated with high-percentage trunk fat independent of birthweight, HOMA-IR, adipose tissue-insulin resistance index (the product of fasting insulin and free fatty acid), triglyceride, HDL cholesterol, apolipoprotein A1 and B, leptin, adiponectin, blood pressure, and high-sensitivity C-reactive protein. Early childhood growth, lower skeletal muscle mass, and higher cereal consumption may be associated with normal-weight but high-percentage trunk fat phenotype in Japanese female university students in this subanalysis study. Atherogenic profile of lipids and apolipoproteins may be directly related to abdominal fat accumulation.

Abdominal aerobic endurance exercise reveals spot reduction exists: A randomized controlled trial.

The existence of spot reduction, exercise-induced local body fat reduction, has been debated for half a century. Although the evidence is equivocal, no study has applied aerobic endurance training closely matching interventions for energy expenditure. Sixteen overweight (BMI: 29.8 ± 3.3(SD) kg m-2 ) males (43 ± 9 years) were randomized to: (1) abdominal endurance exercise (AG), combining treadmill running at 70% HRmax (27 min) with 4 × 4 min (30%-40% maximal strength, 1RM) of torso rotation and abdominal crunches (57 min), 4 days⋅week-1 for 10 weeks; or (2) control group (CG) performing only treadmill running (45 min) at 70% HRmax . Local fat mass was measured by dual-energy x-ray absorptiometry (DEXA), along with 1RM, and pulmonary oxygen uptake (to control energy expenditure during training). Trunk fat mass decreased more (697 g, 3%, p < 0.05) in AG (1170 ± 1093 g, 7%; p < 0.05) than in CG (no change). Total fat mass (AG: 1705 ± 1179 g, 6%; CG: 1134 ± 731 g, 5%; both p < 0.01) and body weight (AG: 1.2 ± 1.2 kg, 1%, p < 0.05; CG: 2.3 ± 0.9 kg, 3%, p < 0.01) decreased similarly in AG/CG. Torso rotation (AG: 32 ± 16 kg, 39%, p < 0.01; CG: no change) and abdominal crunch 1RM (AG: 35 ± 16 kg, 36%, p < 0.01; CG: 13 ± 12 kg, 17%, p < 0.05) increased more (p < 0.05/0.01) in AG than CG. Abdominal endurance exercise utilized more local fat than treadmill running, indicating that spot reduction exists in adult males.