The purpose of this study was to develop a regression equation to predict maximal oxygen uptake (VO₂max) based on nonexercise (N-EX) data. All participants (N= 100), ages 18–65 years, successfully completed a maximal graded exercise test (GXT) to assess VO₂max (M= 39.96 mL·kg ^-1· min ^-1 , SD = 9.54). The N-EX data collected just before the maximal GXT included the participant's age; gender; body mass index (BMI); perceived functional ability (PFA) to walk, jog, or run given distances; and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL·kg ^-1· min ^-1 , %SEE= 8.62): VO₂max (mL·kg ^-1· min ^-1 ) = 48.0730 + (6.1779 x gender; women = 0, men = 1) – (0.2463 x age) – (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R _p = .91 and SEE _p = 3.63 mL·kg ^-1· min ^-1 ); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (ages 18–-65 years) with a similar cardiorespiratory fitness level. Based on standardized β-weights, the PFA variable (0.41) was the most effective at predicting VO₂max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO₂max in adult men and women.

The purpose of this study was to evaluate the validity and reliability of standing posture assessments in asymptomatic men using the PostureScreen Mobile (PSM) iOS application. The standing posture of 50 asymptomatic male participants (24.04 ± 1.81 years) was measured during 3 trials on the same day. The following 10 measurements using the PSM app were compared to the criterion VICON 3-dimensional analysis: from the frontal plane, shift and tilt of the head, shoulders, and hips; and from the sagittal plane, shift of the head, shoulders, hips, and knees. We used Bayesian methods to analyze the data. Compared with the VICON measurements, PSM assessments of head tilt, shoulder tilt and shift, and hip tilt and shift in the frontal plane were biased. In the sagittal plane, PSM measurements of shoulder, hip, and knee shift were biased. Only head shift in the frontal and sagittal planes were comparable between the VICON and the PSM. The VICON and PSM had similar intraclass correlations in 6 of 10 measurements. The PSM assessments of head shift and tilt and shoulder tilt in the sagittal plane were significantly less reliable than with VICON. The use of the PSM app introduced significant bias in postural measurements in the frontal and sagittal plane. Until further research reports additional validity and reliability data of the PSM app, we suggest caution in the use of PSM app when highly accurate postural assessments are necessary.

The Functional Movement Screen (FMS™) has become increasingly popular for identifying functional limitations in basic functional movements. This exploratory and descriptive study was undertaken to confirm feasibility of performing the FMS™ in older active adults, assess prevalence of asymmetries and to evaluate the relationship between functional movement ability, age, physical activity levels and body mass index (BMI). This is an observational study; 97 men (n = 53) and women (n = 44) between the ages of 52 and 83 participated. BMI was computed and self-reported physical activity levels were obtained. Subjects were grouped by age (5-year intervals), BMI (normal, over-weight, and obese) and sex. Each participant's performance on the FMS™ was digitally recorded for later analysis. The youngest age group (50-54 years) scored highest in all seven tests and the oldest age group (75+) scored lowest in most of the tests compared to all other age groups. The subjects in the "normal weight" group performed no different than those who were in the "overweight" group; both groups performed better than the "obese" group. Of the 97 participants 54 had at least one asymmetry. The pairwise correlations between the total FMS™ score and age (r = -0.531), BMI (r = -0.270), and the measure of activity level (r = 0.287) were significant (p < 0.01 for all). FMS™ scores decline with increased BMI, increased age, and decreased activity level. The screen identifies range of motion- and strength-related asymmetries. The FMS™ can be used to assess functional limitations and asymmetries. Future research should evaluate if a higher total FMS™ score is related to fewer falls or injuries in the older population.

This study was designed to develop a single-stage submaximal treadmill jogging (TMJ) test to predict VO₂max in fit adults. Participants (N = 400; men = 250 and women = 150), ages 18 to 40 years, successfully completed a maximal graded exercise test (GXT) at 1 of 3 laboratories to determine VO₂max. The TMJ test was completed during the first 2 stages of the GXT. Following 3 min of walking (Stage 1), participants achieved a steady-state heart rate (HR) while exercising at a comfortable self-selected submaximal jogging speed at level grade (Stage 2). Gender, age, body mass, steady-state HR, and jogging speed (mph) were included as independent variables in the following multiple linear regression model to predict VO₂max (R = 0.91, standard error of estimate [SEE] = 2.52 mL · kg⁻¹ · min⁻¹): VO₂max (mL · kg⁻¹ · min⁻¹) = 58.687 + (7.520 × Gender; 0 = woman and 1 = man) + (4.334 × mph) − (0.211 × kg) − (0.148 × HR) − (0.107 × Age). Based on the predicted residual sum of squares (PRESS) statistics (R_PRESS = 0.91, SEE _PRESS = 2.54 mL · kg⁻¹ · min⁻¹) and small total error (TE; 2.50 mL · kg⁻¹ · min⁻¹; 5.3% of VO₂max) and constant error (CE; −0.008 mL · kg⁻¹ · min⁻¹) terms, this new prediction equation displays minimal shrinkage. It should also demonstrate similar accuracy when it is applied to other samples that include participants of comparable age, body mass, and aerobic fitness level. This simple TMJ test and its corresponding regression model provides a relatively safe, convenient, and accurate way to predict VO₂max in fit adults, ages 18 to 40 years.

This study sought to develop a regression model to predict maximal oxygen uptake (VO_2max) based on submaximal treadmill exercise (EX) and non-exercise (N-EX) data involving 116 participants, ages 18–65 years. The EX data included the participants' self-selected treadmill speed (at a level grade) when exercise heart rate first reached at least 70% of predicted maximum heart rate (HR_max; 220 – age) by the end of any one of three 4-min consecutive stages involving walking (3.0–4.0 mph; Stage 1), jogging (4.1–6.0 mph; Stage 2), and running (> 6.0 mph; Stage 3). The N-EX data included various demographic (age, gender), biometric (body mass), and questionnaire (participants' perceived functional ability [PFA] to walk, jog, or run given distances, and their self-reported level of physical activity [PA-R]) information. All participants (n = 100) who completed the study requirements and successfully achieved a maximal level of exertion during a graded exercise test (GXT) to assess VO_2max (mean ± SD; 41.39 ± 9.15 ml · kg⁻¹ · min⁻¹) were included in the data analysis. Stepwise regression was used to generate the following prediction equation (R = .94, SEE = 3.09 ml · kg⁻¹ · min⁻¹): VO_2max (ml · kg⁻¹ · min⁻¹) = 30.04 + (6.37 × gender; females = 0, males = 1) – (0.243 × age) – (0.122 × body mass) + (3.263 × ending self-selected treadmill speed; mph) + (0.391 × PFA) + (0.669 × PA-R). Each of the predictor variables were statistically significant (p < .001) and cross-validation procedures using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R_p = .92 and SEE _p = 3.29 ml · kg⁻¹ · min⁻¹). In summary, this submaximal treadmill test and accompanying regression model yields relatively accurate VO_2max estimates in healthy men and women (ages 18–65 years) using both EX and N-EX data.

To assess test-retest reliability scores on 16 balance tests of 21 individuals with Down syndrome whose ages ranged from 5 to 31 yr., participants performed a standing test on firm and soft surfaces with the eyes open and closed, the balance subset of the Bruininks-Oseretsky test, full turn, timed-up-and-go test, forward reach, and sit-to-stand. Each participant completed all 16 tests twice in one day and then again on a subsequent day for a total of 4 sessions. The interclass reliability correlation coefficients (ICC) value for each measure of balance varied considerably by age and sex. Based on having an ICC > .50, only 3 tests were reliable in young males and young females, whereas 5 tests could reliably be used in adult females and 9 tests could reliably be used in adult males. The results of this study raise suspicions as to the reliability of tests commonly used to assess balance and differences in reliability due to age and sex. Results of balance tests should be interpreted with caution in males and females with Down syndrome across the age span.