A. Page Glave

Testing Postural Stability: Are the Star Excursion Balance Test and Biodex Balance System Limits of Stability Tests Consistent?

There are a variety of options to test postural stability; however many physical tests lack validity information. Two tests of postural stability - the Star Excursion Balance Test (SEBT) and Biodex Balance System Limits of Stability Test (LOS) - were examined to determine if similar components of balance were measured. Healthy adults (n=31) completed the LOS (levels 6 and 12) and SEBT (both legs). SEBT directions were offset by 180° to approximate LOS direction. Correlations and partial correlations controlling for height were analyzed. Correlations were significant for SEBT 45° and LOS back-left (6: r=-0.41; 12: r=-0.42; p<0.05), SEBT 90° and LOS 6 left (r=-0.51, p<0.05), SEBT 135(o) and LOS 6 front-left (r=-0.53, p<0.05), SEBT overall and LOS 6 overall (r=-0.43, p<0.05). Partial correlations were significant for SEBT 90° and LOS 6 left (rSEBT,LOS·H=-0.45, p<0.05) and SEBT 135° and LOS 6 front-left (rSEBT,LOS·H=-0.51, p<0.05), and SEBT overall and LOS 6 overall (rSEBT,LOS·H=-0.37, p<0.05). These findings indicate the tests seem to assess different components of balance. Research is needed to determine and define what specific components of balance are being assessed. Care must be taken when choosing balance tests to best match the test to the purpose of testing (fall risk, athletic performance, etc.).

The Effects of Two Different Arm Positions and Weight Status on Select Kinematic Variables During the Bodyweight Squat

Abstract Glave, AP, Olson, JM, Applegate, DK, and Di Brezzo, R. The effects of two different arm positions and weight status on select kinematic variables during the bodyweight squat. J Strength Cond Res 26(11): 3148–3154, 2012—The bodyweight squat is a common movement and is safe and effective. There are many variations and techniques, but little research has explored alterations of the movement. The purpose of this study was to examine the effects of 2 arm positions on select kinematic variables during the bodyweight squat. The participants were classified as normal-weight (NW: n = 17, height: 1.67 ± 0.06 m, weight: 61.25 ± 6.90 kg, body mass index [BMI]: 21.92 ± 1.68) or overweight (OW: n = 11, height: 1.68 ± 0.06 m, weight: 88.91 ± 16.86 kg, BMI: 31.64 ± 6.06) according to BMI. The participants completed a bodyweight squat with the arms held at the sides (AP1) followed by a bodyweight squat with the arms held at shoulder level (AP2). Reflective markers were placed on the shoulder, hip, knee, base of the fifth toe, and heel. Data were recorded and analyzed using Peak 9. Trunk and knee flexion was analyzed using separate repeated measures analyses of variance. Overweight participants exhibited reduced knee (OW: 75.56 ± 17.94°; NW: 83.73 ± 13.03°; p < 0.05) and trunk flexion (OW: –78.18 ± 17.72°; NW: –90.65 ± 17.57°; p = 0.05). Holding the arms at shoulder level resulted in greater knee flexion (AP1: 80.81 ± 15.17°; AP2: 86.31 ± 15.21°; p < 0.01). Both weight status and arm position affected the range of motion in the bodyweight squat. Using an arms-up position should be considered, especially for the OW population, to increase the benefits of the bodyweight squat by increasing the range of motion.

The relationship between body fat percentage and difference in caloric expenditure as measured by indirect calorimetry and estimated by an elliptical trainer

Objective: This study examined the effects of increased body fat percentage on the difference of estimated and measured caloric expenditure. Methods: Thirty-four adults participated in the study. Exercise was done on an elliptical machine for 30 minutes: 5 minute warm-up, 20 minute exercise at 64-76% of maximum estimated heart rate, and 5 minute cool-down. Indirect calorimetry was measured and recorded every 5 minutes along with ratings of perceived exertion. Heart rate was monitored throughout the exercise session. Body composition was measured using BodPod. Analysis was completed using SAS 9.4 to calculate correlation between the difference at each time point and body fat. Results: No significant relationship between body fat and difference in caloric estimate overall or at any time point (p=0.06 - 0.10). There was a consistent negative correlation between body fat and caloric estimate difference (-0.31 overall, -0.24 to -0.36 for the intermediate time points. No significant differences in caloric estimates based on obesity classification. Conclusions: Individuals with lower body fat percentage need to be cautious when relying on caloric estimates from exercise equipment, and those who near their weight goal will be less able to rely on the caloric estimates from exercise equipment. It is important that when using an exercise machine to enter as much information as possible for increased accuracy.