Background & Aims: Segmental body composition may be an important indicator of health and nutritional status in conditions where variations in fat and lean mass are frequently isolated to a particular body segment (e.g. paralysis, sarcopenia). Until recently, segment-specific body composition could only be assessed using invasive and expensive methods such as dual-energy x-ray absorptiometry (DXA), magnetic resonance imaging (MRI), or computed tomography (CT). Bioelectrical impedance analysis (BIA) may be a rapid, inexpensive alternative for assessing segmental composition, but it has not been fully validated for this purpose. The purpose of this study was to compare segmental estimates of lean and fat mass using BIA versus a criterion standard of DXA. Methods: A cross-sectional pilot study was conducted in n=30 healthy adults. Outcome measures included total mass, fat mass and lean mass of arm, leg and trunk. Pearson correlation coefficients (r) and paired-samples t-tests (t) were used to assess relationships between each outcome as measured by BIA and DXA. Results: Although the methods were strongly correlated for all measures, (r >.87 for all segments) BIA routinely overestimated lean mass for arm and trunk (mean difference arm: 0.97 kg, p=.008; trunk: 5.58 kg, p<.0001); and underestimated fat mass for arm and leg (mean difference arm: 0.42 kg, p<.0001; leg: 1.94 kg p<.0001). BIA overestimated total body lean mass in 93% of participants and underestimated total body fat mass in 90% of participants. Conclusions: Significant discrepancies were noted between DXA and BIA in all body segments. Further research is needed to refine BIA methods for segmental composition estimates in heterogeneous samples and disease-specific populations before this methods can be used reliably in a clinical setting.
Background Insulin resistance and accumulation of visceral adipose tissue (VAT) and intermuscular adipose tissue (IMAT) place aging adults with obesity at high risk of cardio-metabolic disease. A very low carbohydrate diet (VLCD) may be a means of promoting fat loss from the visceral cavity and skeletal muscle, without compromising lean mass, and improve insulin sensitivity in aging adults with obesity. Objective To determine if a VLCD promotes a greater loss of fat (total, visceral and intermuscular), preserves lean mass, and improves insulin sensitivity compared to a standard CHO-based/low-fat diet (LFD) in older adults with obesity. Design Thirty-four men and women aged 60–75 years with obesity (body mass index [BMI] 30-40 kg/m 2 ) were randomized to a diet prescription of either a VLCD (< 10:25:> 65% energy from CHO:protein:fat) or LFD diet (55:25:20) for 8 weeks. Body composition by dual-energy X-ray absorptiometry (DXA), fat distribution by magnetic resonance imaging (MRI), insulin sensitivity by euglycemic hyperinsulinemic clamp, and lipids by a fasting blood draw were assessed at baseline and after the intervention. Results Participants lost an average of 9.7 and 2.0% in total fat following the VLCD and LFD, respectively ( p < 0.01). The VLCD group experienced ~ 3-fold greater loss in VAT compared to the LFD group (− 22.8% vs − 1.0%, p < 0.001) and a greater decrease in thigh-IMAT (− 24.4% vs − 1.0%, p < 0.01). The VLCD group also had significantly greater thigh skeletal muscle (SM) at 8 weeks following adjustment for change in total fat mass. Finally, the VLCD had greater increases in insulin sensitivity and HDL-C and decreases in fasting insulin and triglycerides compared to the LFD group. Conclusions Weight loss resulting from consumption of a diet lower in CHO and higher in fat may be beneficial for older adults with obesity by depleting adipose tissue depots most strongly implicated in poor metabolic and functional outcomes and by improving insulin sensitivity and the lipid profile. Trial registration NCT02760641 . Registered 03 May 2016 - Retrospectively registered.
There is no difference in rates of large-for-gestational-age neonates with a one-step testing strategy compared with a two-step testing strategy for gestational diabetes mellitus.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.