Background: Retatrutide (RETA) is a single peptide with agonist activity at GIR, GLP-1, and glucagon receptors, which demonstrated clinically meaningful glucose- and body weight-lowering efficacy in ...participants with type 2 diabetes (T2D). Quality of weight loss is an important consideration in this setting. Here, we analyze the change in body composition (BC) and the ratio of absolute fat mass loss (FML) to absolute total body mass loss (TBML) after 36 weeks treatment with RETA. Methods: The phase 2, randomized double-blind study included adults with T2D. Participants received once weekly RETA 0.5, 4, 8, or 12 mg, dulaglutide 1.5 mg (DULA) or PBO. Change from baseline in TBM and BC at week 36 was assessed. The ratio of FML to TBML was assessed in treatment groups with mean TBML >5 kg (RETA 4, 8, 12 mg). On treatment data prior to discontinuation of study drug and regression methods were used for analysis. Results: 189 subjects were enrolled in the dual X-ray absorptiometry (DXA) sub-study and 103 had baseline and postbaseline DXA data with 13-22 in all the treatment arms. Overall baseline characteristics (55.6% female, mean age 56.0 years, BMI 35.2 kg/m2, TBM 97.0 kg, HbAlc 8.3%) were similar to those of the main study as was weight loss across the study arms. The percent reduction from baseline in TBM was 2.6%, 9.7%, 17.1%, 16.0%, 1.0%, 2.4% with RETA 0.5, 4, 8, 12 mg, DULA and PBO respectively. There was 4.9%, 15.2%, 26.1%, 23.2%, 2.6%, 4.5% percent reduction in fat mass in RETA 0.5, 4, 8, 12 mg, DULA and PBO respectively. There was 0.9%, 6.0%, 12.5%, 11.7%, -0.7%, 1.3% percent reduction in lean mass in RETA 0.5, 4, 8, 12 mg, DULA and PBO respectively. The percent body fat was significantly decreased only in the RETA arms. The ratio of FML to TBML was 0.67 in a pooled analysis of the RETA 4 mg, 8 mg, and 12 mg arms. Conclusions: In adults with T2D, RETA treatment led to improvements in body composition. The ratio of fat mass loss to total body mass loss was consistent with other weight loss regimens.
Background: Three-dimensional optical (3DO) body composition (BC) from statistical shape models have been developed and vali- dated on cross-sectional data. This technique has shown to be ac- curate ...and precise in respect to dual-energy X-ray absorptiometry (DXA). However, it is unknown if 3DO is sensitive enough to detect change in BC. Therefore, our objective was to evaluate the accuracy of the previously developed cross-sectional models for detecting change and the need for new longitudinal models. Methods: Data from participants in the longitudinal arm of the Shape Up! Adults, FB4 Study, and Louisiana State University Athlete's Study were used in this analysis. Measures on all partici- pants included 3DO and DXA scans at baseline and follow-up using similar make and model systems. Healthy participants went through study-specific interventions that included either dietary or physical activity modifications. Fat mass (FM) and visceral adipose tissue (VAT) were estimated from 3DO scans using previously-developed statistical shape models. Changes in these estimates were compared to criterion changes in DXA. Further, fundamental studies relating change in shape and demographics to DXA were performed using step-forward linear regression with 5-fold cross-validation. Results: For this analysis, 107 participants completed the study (males = 67). Of the models created, 3DO estimates of FM from the previ- ously developed cross-sectional model performed the best for females (R2 = 0.88, RMSE = 1.29 kg) while fundamental models of change in shape were best for males (R2 = 0.88, RMSE = 1.8 kg). Change in DXA VAT for both males and females was best predicted by change in shape models (R2 = 0.57 and 0.49, RMSE = 85 g and 76 g, respectively). Conclusions: Using a diverse population of healthy males and females, various 3DO models accurately estimated changes in DXA FM and VAT over time.
Background: Bariatric surgery remains the most effective method for weight loss and mitigation of comorbid conditions for obese patients. Early post-operative weight loss is rapid and slowly levels ...off, creating characteristic asymptotic weight loss curves. Little is known with regard tto the relative degrees of fat free mass (FFM) loss versus fat mass (FM) loss in this early period. Ideally, weight loss methods including bariatric surgery will provide FM loss that is much greater than FFM loss, thus preserving lean body mass. We sought to better characterize the patterns of early weight loss after bariatric surgery. Methods: Retrospective chart review of patients who had bariatric surgery at our institution between March 2019 and November 2022 was performed. A total of 184 patients underwent sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB) or Biliopancreatic Diversion with Duodenal Switch (BPD/DS). Body composition analysis was performed using bioimpedance methods with a medical body composition analyzer. The following values were obtained for each patient: fat free mass (FFM), fat mass (FM) and total weight (WT). Data was collected pre-surgery and in post-surgery follow up at 2 weeks-1 month, 2-4 months and 5-7 months. Results: The highest rates of FFM loss were found in the first 2 weeks post-bariatric surgery (p < 10e-7, 95%CI 10.5-17.9). FFM and FM loss showed no significant difference within the initial 2 weeks postsurgery (p = 0.74). Following the initial 2 months post-surgery, FFM rates slowed down significantly. FM loss rates continued to progress after the initial 2 weeks compared to FFM loss. Significant differences between FFM and FM loss were seen at 2-4 months (p = 1.0e-09, 95% Cl5.8-9.1) and 5-7 months post-surgery (p = 5.1e-08, 95% Cl 1.6-5.5). The RYGB procedure showed significantly more mean FFM loss within the first 2 weeks compared to patients who underwent SG (RYGB = 7.54, SG = 5.82, p = 0.04678, 95%CI 0.03-3.4). No difference was seen after this. No other significant differences were seen based on surgical procedure. Long term weight loss is not impacted by early excessive FFM. Conclusions: FFM loss is highest in the first 2 weeks post-surgery. FM loss predominated subsequently. Overall weight loss is not significantly impacted by excessive FFM loss. FFM loss is short-term. Type of procedure only affects early FFM loss.
Background: Measuring body composition in a seated position would be advantageous in clinical practice because patients are already seated while waiting in patient rooms. This allows sufficient time ...for fluid shifts to occur that can affect bioelectrical impedance analysis (BIA). However, BIA's assumption of a uniform cylindrical shape may be violated in the seated position if the trunk contacts the limbs, such as in people with a high waist circumference (WC). The aims of this research are to determine whether posture (supine, standing, and seated) and WC affect agreement of fat-free mass (FFM) as measured by BIA and DXA. Methods: Data were collected from 28 adults (mean = 61.2 ± 6.9 years, 64.3% female) with obesity (BMI 38.6 ± 5.0 kg/m2). FFM was measured by BIA in the supine, standing, and seated positions and by DXA while supine. Interclass correlation coefficient (ICC) analyses with two-way mixed effects and absolute agreement were performed to determine agreement. Results: Point estimates of agreement between BIA and DXA FFM measures were excellent in supine (ICC = 0.93, 0.75-0.97 95% Cl), and good in standing (ICC = 0.89, 0.31-0.97) and seated (ICC = 0.77, 0.12-0.92) positions. Better agreement was observed across all positions in participants with a WC below the median (118.3 cm) compared to above the median (supine: 0.97 0.90-0.99 vs. 0.87 0.780.96, standing: 0.92 0.20-0.98 vs. 0.83 0.16-0.95, seated: 0.86 -0.02-0.97 vs. 0.65 0.00-0.89). Regardless of WC, measuring FFM by BIA in the supine position resulted in the narrowest 95% confidence intervals. Conclusions: Despite the potential pragmatic value of measuring BIA in a seated position, results of this analysis demonstrate the poorest DXA-BIA agreement with that method that was accentuated in people with high WC. The observed excellent agreement and narrow confidence intervals-regardless of WC-indicate that a supine position should be recommended when using BIA to measure body composition.
Background: Nutrition bars are perceived by consumers as a convenient and healthy snack option; yet there is little research examining health outcomes associated with snack bar ingestion. This ...research examined the impact of the daily ingestion of commercial high protein nutrition bars (with or without added fiber) on 24-h energy intake and body composition after one week among young, free-living healthy adults. Methods: In a 4-week double-blind, randomized crossover trial, 21 nonsmoking, non-athlete adults (15 females; 21.9±2.6 y; 23.9±2.7 kg/m2) were randomly assigned to HP (high protein: 21 g protein, 15 g carbohydrate, 5 g fat) or HPHF (high protein high fiber: 20g protein, 14 g fiber, 10 g carbohydrate, 7 g fat) groups. Bars were consumed daily during trial weeks 2 and 4 (crossover fashion) within an hour of waking. Body composition was measured using bioelectrical impedance at baseline and the end of each feeding period. Dietary data (using the MyfitnessPal app) was measured on three nonconsecutive days each week of the trial. Results: The mean energy intakes for the weeks the bars were consumed were significantly elevated versus the baseline or washout weeks (+126-220 kcal, p = 0.022, repeated measures ANOVA). Mean fat mass following one week of HP or HPHF bar consumption was elevated versus baseline value (18.8+6.8, 18.8+6.8 and 18.3 ± 6.7 kg respectively; p = 0.039). Physical activity level at baseline was weakly related to energy intake on the weeks the protein bars were consumed (r>0.330). Macronutrient intakes differed significantly between timepoints mirroring the nutrient profile for each bar. Conclusions: Sales of nutrition bars show rapid growth year after year in the U.S. and may represent an efficient source of specific nutrients. However, ingestion of nutrition bars may increase total daily energy intake and the risk of gaining fat mass and eventual body mass over time.
Background: Temporal increases in energy intake over time have been implicated as the cause of the worsening epidemic of obesity but are difficult to examine due to limitations in energy intake ...assessments. In an ad libitum energy intake model, we examined longitudinal and seasonal differences in energy intake over 20 years. Methods: Participants (n=292; 59% Indigenous Americans; 61% male; BMI (mean ± SD) 31.6 ± 8 kg.m2) were admitted for a 10 day inpatient stay during which measurements such as body composition (by DXA), 24 hour energy expenditure including spontaneous physical activity (SPAVS(1 ) otherwise known as fidgeting, and ad libitum energy intake over 3 days using a validated vending machine paradigm were collected. General linear models (GLM) were used for secular and seasonal trends adjusting for sex, age, FFM-index, FMindex, and race. FFM-index and FM-index consider height to normalize body composition. SPA was also added to these models in later analysis. Results: Total energy intake (kcal) (B= -411), percent weight maintaining energy needs (%WMEN) (B= -15), and fat kcals (B= -197) were lower (p<0.05) in the summer compared to winter but these differences were attenuated after adjustment for SPA (all p>0.11). KJ (1 As expected FFM-index was positively associated with all food intake measures (all p<0.05) while FM-index was negatively associated (all p<0.05). Adjusted models of secular trends, expressed in years, indicated total kcals (B= -55), %WMEN (B= -2), protein kcals (B= -10), fat kcals (B= -27), and carb kcals (B= -22) all decreased over time. SPA was positively associated with total energy intake (partial R: 0.21, p<0.0036), %WMEN (partial R: 0.18, p<0.01), protein kcals (partial R: 0.21, p<0.0032), fat kcals (partial R: 0.016, p<0.021), and carb kcals (partial R: 0.0020, p<0.0043) when included in above models. Secular trends in body composition measures revealed decreased FFM-index (partial R: -0.39, p<0.0001), but increased FM-index (partial R: 0.34, p<0.0001) with no changes in weight, BMI, and percent body fat (all p>0.20). Conclusions: Ad libitum intake and FFM-index are decreasing with time. FFM-index is the major determinant of energy demand, so its decline may play a role in overall reduction in intake.
