Evaluation of Automated Anthropometrics Produced By Smartphone-Based Machine Learning: A Comparison With Traditional Anthropometric Assessments

Automated visual anthropometrics produced by mobile applications are accessible and cost-effective with the potential to assess clinically relevant anthropometrics without a trained technician present. Thus, the aim of this study was to evaluate the precision and agreement of smartphone-based automated anthropometrics against reference tape measurements. Waist and hip circumference (WC; HC), waist-to-hip ratio (WHR), and waist-to-height ratio (W:HT), were collected from 115 participants (69 F) using a tape measure and two smartphone applications (MeThreeSixty®, myBVI®) across multiple smartphone types. Precision metrics were used to assess test-retest precision of the automated measures. Agreement between the circumferences produced by each mobile application and the reference were assessed using equivalence testing and other validity metrics. All mobile applications across smartphone types produced reliable estimates for each variable with ICCs ≥0.93 (all

Time-restricted Feeding Plus Resistance Training in Active Females: A Randomized Trial

Background A very limited amount of research has examined intermittent fasting (IF) programs, such as time-restricted feeding (TRF), in active populations. Objective Our objective was to examine the effects of TRF, with or without β-hydroxy β-methylbutyrate (HMB) supplementation, during resistance training (RT). Methods This study employed a randomized, placebo-controlled, reduced factorial design and was double-blind with respect to supplementation in TRF groups. Resistance-trained females were randomly assigned to a control diet (CD), TRF, or TRF plus 3 g/d HMB (TRFHMB). TRF groups consumed all calories between 1200 h and 2000 h, whereas the CD group ate regularly from breakfast until the end of the day. All groups completed 8 wk of supervised RT and consumed supplemental whey protein. Body composition, muscular performance, dietary intake, physical activity, and physiological variables were assessed. Data were analyzed prior to unblinding using mixed models and both intention-to-treat (ITT) and per protocol (PP) frameworks. Results Forty participants were included in ITT, and 24 were included in PP. Energy and protein intake (1.6 g/kg/d) did not differ between groups despite different feeding durations (TRF and TRFHMB: ∼7.5 h/d; CD: ∼13 h/d). Comparable fat-free mass (FFM) accretion (+2% to 3% relative to baseline) and skeletal muscle hypertrophy occurred in all groups. Differential effects on fat mass (CD: +2%; TRF: −2% to −4%; TRFHMB: −4% to −7%) were statistically significant in the PP analysis, but not ITT. Muscular performance improved without differences between groups. No changes in physiological variables occurred in any group, and minimal side effects were reported. Conclusions IF, in the form of TRF, did not attenuate RT adaptations in resistance-trained females. Similar FFM accretion, skeletal muscle hypertrophy, and muscular performance improvements can be achieved with dramatically different feeding programs that contain similar energy and protein content during RT. Supplemental HMB during fasting periods of TRF did not definitively improve outcomes. This study was prospectively registered at clinicaltrials.gov as NCT03404271

Differential Effects of Oral vs. Intravenous Fluid Administration on Bioelectrical Impedance During Dehydration Induced by Exercise and Heat

There is continued debate regarding optimal evaluation of hydration. Bioimpedance analysis has been utilized to evaluate hydration status, but there is limited information regarding the ability of this technology to detect physiological changes occurring during acute dehydration. PURPOSE: To evaluate whether bioimpedance spectroscopy (BIS) detects changes in bioelectrical resistance (R) in response to dehydration induced by exercising in the heat, assess whether these changes are related to body mass changes, and determine if the route of fluid administration during the dehydration protocol influences these observations. METHODS: Twelve males (mean ± SD; age: 28.6 ± 12.4 y; body mass: 74.7 ± 7.9 kg; height: 179.4 ± 7.0 cm; VO2max: 49.8 ± 6.6 mL/kg/min) completed two randomized experimental trials, each consisting of 90 minutes of continuous cycling exercise at 55% VO2maxfollowed by a 12 km time trial in the heat (ambient temperature: 34.9 ± 0.6 °C; relative humidity: 30.3 ± 0.9 %; wind speed: 3.4 mile×h-1). During each trial, fluid was administered either orally (DRINK) or intravenously (IV). During the DRINK trial, participants drank 25 mL of water every 5 minutes. During the IV trial, participants received 25 mL of isotonic saline solution through their IV catheter every 5 minutes. Nude body mass and BIS data were collected before and after trials to assess hydration status. Data were analyzed using Pearson’s correlations and paired t-tests with p-values corrected via false discovery rate. RESULTS: Body mass decreased, without differences between conditions (IV: -2.3 ± 0.5%; DRINK: -2.4 ± 0.9%; p=0.85). However, significant differences were observed for changes in predicted R at zero frequency (R0; IV: -3.6 ± 4.6%; DRINK: 1.3 ± 5.6%; p=0.02) and R at 50 kHz (R50; IV: -3.2 ± 4.1%; DRINK: -0.2 ± 4.1%; p=0.04), without differences in predicted R at infinite frequency (R∞; IV: -2.4 ± 6.1%; DRINK: -1.1 ± 3.7%; p=0.45). In the IV condition, significant correlations between body mass changes and R changes were observed for R0 (r=-0.80; p=0.002), R50 (r=-0.85; p\u3c0.001), and R∞ (r=-0.84; p\u3c0.001); however, no correlations were observed in the DRINK condition (r=-0.06 to 0.13; p≥0.69 for each). CONCLUSION: Differences between oral and intravenous fluid administration were seemingly detected by bioelectrical resistance at low-to-moderate, but not high, frequencies. With intravenous administration, negative correlations between changes in body mass and changes in R at all frequencies were observed, unlike with oral fluid administration. These findings suggest a potential sensitivity of bioimpedance technologies for monitoring intravenous fluid administration in the context of acute dehydration. However, additional investigation is needed to confirm their utility during distinct fluid loss scenarios and to confirm if these technologies are useful in the context of oral intake of fluids varying in composition

Impact of Acute Dietary Manipulations on Dual-Energy X-ray Absorptiometry Estimates of Visceral Adipose Tissue

Dual-energy x-ray absorptiometry (DXA) is viewed as a superior method of body composition assessment, but whole-body DXA scans are impacted by variation in pre-assessment activities, such as eating and drinking. DXA software now allows for estimation of visceral adipose tissue (VAT), which has been implicated in a number of diseases. It is unknown to what extent food and fluid intake affect VAT estimates. PURPOSE: determine the effects of acute high-carbohydrate (HC) and very low-carbohydrate (VLC) diets on DXA estimates of VAT. METHODS: Male and female adults completed two one-day dietary conditions in random order: a VLC diet (1 – 1.5 g CHO/kg) and a HC diet (9 g CHO/kg). The diets were isocaloric to each other, and all food items were provided to participants. DXA scans were conducted in the morning after an overnight fast and in the afternoon soon after the third standardized meal. VAT volume, mass, and area were obtained, and paired samples t-tests were performed to compare the changes in VAT measures between diets. RESULTS: Fifteen males (age 22 ± 3, BF% 21 ± 5%) and eighteen females (age 21 ± 2, BF% 31 ± 5%) were included in the analysis. The change in VAT volume between the fasted and fed visits was different between diets (HC: +1.6%; VLC: -9.2%, p= 0.047). There were also trends for differences in VAT mass (p= 0.089) and area (p= 0.096) changes between diets. CONCLUSIONS: Within a single day, VAT estimates are differentially affected by isocaloric HC and VLC diets, with VLC consumption leading to reductions in VAT estimates. The content of the diet on the day of a DXA scan can affect estimates of VAT, which could spuriously influence the categorization of an individual’s health risk by DXA VAT estimates. Standardization of food intake prior to scans, preferably in the form of an overnight fast, should be employed to eliminate this important source of error

Associations Between Visceral Adipose Tissue Estimates Produced By Near-Infrared Spectroscopy, Mobile Anthropometrics, and Traditional Body Composition Assessments and Estimates Derived From Dual-Energy X-Ray Absorptiometry

Assessments of visceral adipose tissue (VAT) are critical in preventing metabolic disorders; however, there are limited measurement methods that are accurate and accessible for VAT. The purpose of this cross-sectional study was to evaluate the association between VAT estimates from consumer-grade devices and traditional anthropometrics and VAT and subcutaneous adipose tissue (SAT) from dual-energy X-ray absorptiometry (DXA). Data were collected from 182 participants (female = 114; White = 127; Black/African-American (BAA) = 48) which included anthropometrics and indices of VAT produced by near-infrared reactance spectroscopy (NIRS), visual body composition (VBC) and multifrequency BIA (MFBIA). VAT and SAT were collected using DXA. Bivariate and partial correlations were calculated between DXAVAT and DXASAT and other VAT estimates. All VAT indices had positive moderate–strong correlations with VAT (all P \u3c 0·001) and SAT (all P \u3c 0·001). Only waist:hip (r = 0·69), VATVBC (r = 0·84), and VATMFBIA (r = 0·86) had stronger associations with VAT than SAT (P \u3c 0·001). Partial associations between VATVBC and VATMFBIA were only stronger for VAT than SAT in White participants (r = 0·67, P \u3c 0·001) but not female, male, or BAA participants individually. Partial correlations for waist:hip were stronger for VAT than SAT, but only for male (r = 0·40, P \u3c 0·010) or White participants (r = 0·48, P \u3c 0·001). NIRS was amongst the weakest predictors of VAT which was highest in male participants (r = 0·39, P \u3c 0·010) but non-existent in BAA participants (r = –0·02, P \u3e 0·050) after adjusting for SAT. Both anthropometric and consumer-grade VAT indices are consistently better predictors of SAT than VAT. These data highlight the need for a standardised, but convenient, VAT estimation protocol that can account for the relationship between SAT and VAT that differs by sex/race

Validity of Body Volume Estimates from Infrared 3-dimensional Scanning and Dual-energy X-ray Absorptiometry as Compared to Air Displacement Plethysmography

Traditional methods of estimating body volume (BV) such as hydrostatic weighing and air-displacement plethysmography (ADP) could theoretically be replaced using BV estimates obtained by dual-energy x-ray absorptiometry (DXA) or infrared 3-dimensional (3D) scanning devices. Multiple 3D scanning technologies have recently become popularized, including scanners that acquire data through pattern deformations caused by the projected light over the 3D object (i.e., structured light [SL] scanners) or by calculating depth from the time it takes reflected photons to reach the scanner’s image sensor (i.e. time of flight [ToF] scanners). While these 3D scanning technologies currently predict body composition based primarily on circumference estimates, the BV estimates obtained by this technology could be used to predict body composition if the BV estimates are validated. PURPOSE: The purpose of this analysis was to examine the validity of BV estimates obtained from DXA-derived formulas and multiple types of 3D scanners as compared to ADP. METHODS: At a single research visit, BV estimates were obtained via ADP, prediction from DXA output, and three infrared 3D scanners in a sample of 102 adults (64 F, 38 M; age: 29.2 ± 13.4 y; BMI: 24.3 ± 3.9 kg/m2; BF%: 24.6 ± 8.3%). The 3D scanners included a SL scanner with a static configuration (SL-S) in which the scanner and participant are stationary during assessments, a SL scanner with a dynamic configuration (SL-D) in which the participant is rotated during the scan, and a ToF scanner with a dynamic configuration. ADP was designated as the criterion method, and BV estimates were compared using one-way ANOVA and post hoc testing with Bonferroni correction. Additional evaluations were conducted using the coefficient of determination (R2), constant error (CE), total error (TE), and 95% limits of agreement (LOA). RESULTS: DXA-derived BV estimates were valid and produced the lowest error of all methods (p \u3e 0.05; R2: 1.00; CE: 0 – 1.4 L; TE: 0.8 – 1.5 L; LOA: 1.0 – 1.8 L). BVSL-D did not differ from BVADP (p \u3e 0.05; R2: 1.00; CE: -3.9 L; TE: 4.0 L; LOA: 2.5 L), although errors were higher than the DXA-derived equations. The SL-S and ToF scanners did not produce valid estimates, although they differed in the direction and magnitude of errors. The SL-S scanner overestimated BV relative to BVADP (p=0.01; R2: 0.94; CE: 7.0 L; TE: 8.0 L; LOA: 7.3 L), while the ToF scanner underestimated BV relative to BVADP (p \u3c 0.001; R2: 0.99; CE: -9.7 L; TE: 9.9 L; LOA: 4.6 L). CONCLUSION: The present results add to the growing research indicating that DXA-derived BV may be an acceptable replacement to traditional methods of BV assessment. Although the SL-D 3D scanner exhibited better validity of BV estimates as compared to the other scanners, improvements in the validity of BV estimates obtained from 3D scanners are necessary before this technology can be viewed as a viable alternative to traditional methods of BV assessment

New Equations for Hydrostatic Weighing without Head Submersion

New equations were derived to predict the density of the body (DB) by hydrostatic weighing with the head above water (HWHAW). Hydrostatic weighing with the head below water (HWHBW) was the criterion for DB measurement in 90 subjects (44 M, 46 F). Head volume by immersion (HVIMM) was determined by subtracting the mass in water with the head below water (MWHBW) from the mass in water with the head above water (MWHAW), with subjects at residual lung volume. Equations were derived for head volume prediction (HVPRED) from head measurements and used to correct DB by HWHAW. Equations were also derived for HWHAW using direct regression of DB from uncorrected density (with MWHAW in place of MWHBW). Prediction equations were validated in 45 additional subjects (21 M, 24 F). Results were evaluated using equivalence testing, linear regression, Bland–Altman plots, and paired t-tests. Head girth, face girth, and body mass produced the smallest errors for HVPRED. In both M and F validation groups, equivalence (±2% fat by weight) was demonstrated between body fat percent (BF%) by HWHBW and BF% by HWHAW with HVPRED. Variance in computer-averaged samples of MWHAW was significantly less (p \u3c 0.05) than MWHBW. Prediction error was smaller for BF% by HWHAW with HVPRED than for alternative methods. Conclusions: Equivalence between BF% by HWHBW and BF% by HWHAW with HVPRED was demonstrated and differences were not statistically significant. Weight fluctuations were smaller for HWHAW than HWHBW