A 3-minute test of cardiorespiratory fitness for use in primary care clinics.

BACKGROUND: Cardiorespiratory fitness (CRF) is the only major risk factor that is not routinely assessed in the clinical setting, for preventive medicine. A valid and practical CRF test is needed for use in the clinics. The objective of this study is to demonstrate the validity of a 3-minute squat test to assess CRF in primary care. METHODS: A cross-sectional study in which the participants performed both the Ruffier squat test and the Balke maximal treadmill test. The study was conducted in a clinical setting from September 2016 to March 2017. We recruited a convenient sample of 40 adults between 18 and 64 years from the general U.S. population. Participants completed 30 squats in 45 seconds, paced by a metronome. Heart rate was measured at rest (P1), immediately after the test (P2), one minute after the test (P3). [Formula: see text] was measured using the Balke maximal treadmill fitness test. RESULTS: Of the 40 participants, there were 18 men and 22 women. Mean age was 31.2 years (SD = 9.9). We found that the best [Formula: see text] predictors were HR features P1/height and (P2-P3)/age3. Our best-performing model using these two features predicted individuals' CRF levels with an adjusted R2 of 0.637, sensitivity of 0.79, and specificity of 0.56. CONCLUSIONS: The study provided strong evidence for the validity of the squat test in the clinical setting. Further, the equation of our model along with [Formula: see text] normative tables provides an efficient and easy way to assess CRF in a primary care setting.

Running Mechanics and Metabolic Responses With Water Bottles and Bottle Belt Holders.

PURPOSE: To determine whether differential kinematics, kinetics, rates of energy use, and cardiopulmonary responses occur during running with water bottles and bottle belt holders compared with running only. METHODS: Trained runners (N = 42; age 27.2 [6.4] y) ran on an instrumented treadmill for 4 conditions in a randomized order: control run (CON), handheld full water bottle (FULL; 16.9 fluid oz; 454 g), handheld half-full water bottle (HALF; 8.4 fluid oz; 227 g), and waist-worn bottle belt holder (BELT; hydration belt; 676 g). Gas exchange was measured using a portable gas analyzer. Kinetic and kinematic responses were determined by standard 3-dimensional videographic techniques. Interactions of limb side (right and left) by study condition (CON, FULL, HALF, and BELT) were tested for rates of oxygen use and energy expenditure and kinematic and kinetic parameters. RESULTS: No significant limb-side × condition interactions existed for rates of oxygen use or energy expenditure. A significant interaction occurred with sagittal elbow flexion (P < .001). Transverse pelvic-rotation excursions differed on average 3.8° across conditions. The minimum sagittal hip-flexion moment was higher in the right leg in the HALF and BELT conditions compared with CON (P < .001). CONCLUSIONS: Carrying water by hand or on the waist does not significantly change the kinematics of running motion, rates of oxygen use and energy expenditure, or cardiopulmonary measures over short durations. Runners likely make adjustments to joint moments and powers that preserve balance and protect the lower-extremity joints while maintaining rates of oxygen use and energy expenditure.

Assessing the Quality of Mobile Exercise Apps Based on the American College of Sports Medicine Guidelines: A Reliable and Valid Scoring Instrument.

BACKGROUND: Regular physical activity can not only help with weight management, but also lower cardiovascular risks, cancer rates, and chronic disease burden. Yet, only approximately 20% of Americans currently meet the physical activity guidelines recommended by the US Department of Health and Human Services. With the rapid development of mobile technologies, mobile apps have the potential to improve participation rates in exercise programs, particularly if they are evidence-based and are of sufficient content quality. OBJECTIVE: The goal of this study was to develop and test an instrument, which was designed to score the content quality of exercise program apps with respect to the exercise guidelines set forth by the American College of Sports Medicine (ACSM). METHODS: We conducted two focus groups (N=14) to elicit input for developing a preliminary 27-item scoring instruments based on the ACSM exercise prescription guidelines. Three reviewers who were no sports medicine experts independently scored 28 exercise program apps using the instrument. Inter- and intra-rater reliability was assessed among the 3 reviewers. An expert reviewer, a Fellow of the ACSM, also scored the 28 apps to create criterion scores. Criterion validity was assessed by comparing nonexpert reviewers' scores to the criterion scores. RESULTS: Overall, inter- and intra-rater reliability was high with most coefficients being greater than .7. Inter-rater reliability coefficients ranged from .59 to .99, and intra-rater reliability coefficients ranged from .47 to 1.00. All reliability coefficients were statistically significant. Criterion validity was found to be excellent, with the weighted kappa statistics ranging from .67 to .99, indicating a substantial agreement between the scores of expert and nonexpert reviewers. Finally, all apps scored poorly against the ACSM exercise prescription guidelines. None of the apps received a score greater than 35, out of a possible maximal score of 70. CONCLUSIONS: We have developed and presented valid and reliable scoring instruments for exercise program apps. Our instrument may be useful for consumers and health care providers who are looking for apps that provide safe, progressive general exercise programs for health and fitness.

Real time noninvasive estimation of work of breathing using facemask leak-corrected tidal volume during noninvasive pressure support: validation study.

We describe a real time, noninvasive method of estimating work of breathing (esophageal balloon not required) during noninvasive pressure support (PS) that uses an artificial neural network (ANN) combined with a leak correction (LC) algorithm, programmed to ignore asynchronous breaths, that corrects for differences in inhaled and exhaled tidal volume (VT) from facemask leaks (WOBANN,LC/min). Validation studies of WOBANN,LC/min were performed. Using a dedicated and popular noninvasive ventilation ventilator (V60, Philips), in vitro studies using PS (5 and 10 cm H2O) at various inspiratory flow rate demands were simulated with a lung model. WOBANN,LC/min was compared with the actual work of breathing, determined under conditions of no facemask leaks and estimated using an ANN (WOBANN/min). Using the same ventilator, an in vivo study of healthy adults (n = 8) receiving combinations of PS (3-10 cm H2O) and expiratory positive airway pressure was done. WOBANN,LC/min was compared with physiologic work of breathing/min (WOBPHYS/min), determined from changes in esophageal pressure and VT applied to a Campbell diagram. For the in vitro studies, WOBANN,LC/min and WOBANN/min ranged from 2.4 to 11.9 J/min and there was an excellent relationship between WOBANN,LC/breath and WOBANN/breath, r = 0.99, r(2) = 0.98 (p < 0.01). There were essentially no differences between WOBANN,LC/min and WOBANN/min. For the in vivo study, WOBANN,LC/min and WOBPHYS/min ranged from 3 to 12 J/min and there was an excellent relationship between WOBANN,LC/breath and WOBPHYS/breath, r = 0.93, r(2) = 0.86 (p < 0.01). An ANN combined with a facemask LC algorithm provides noninvasive and valid estimates of work of breathing during noninvasive PS. WOBANN,LC/min, automatically and continuously estimated, may be useful for assessing inspiratory muscle loads and guiding noninvasive PS settings as in a decision support system to appropriately unload inspiratory muscles.

Low Quality of Free Coaching Apps With Respect to the American College of Sports Medicine Guidelines: A Review of Current Mobile Apps.

BACKGROUND: Low physical activity level is a significant contributor to chronic disease, weight dysregulation, and mortality. Nearly 70% of the American population is overweight, and 35% is obese. Obesity costs an estimated US$ 147 billion annually in health care, and as many as 95 million years of life. Although poor nutritional habits remain the major culprit, lack of physical activity significantly contributes to the obesity epidemic and related lifestyle diseases. OBJECTIVE: Over the past 10 years, mobile devices have become ubiquitous, and there is an ever-increasing number of mobile apps that are being developed to facilitate physical activity, particularly for active people. However, no systematic assessment has been performed about their quality with respect to following the parameters of sound fitness principles and scientific evidence, or suitability for a variety of fitness levels. The aim of this paper is to fill this gap and assess the quality of mobile coaching apps on iOS mobile devices. METHODS: A set of 30 popular mobile apps pertaining to physical activity programming was identified and reviewed on an iPhone device. These apps met the inclusion criteria and provided specific prescriptive fitness and exercise programming content. The content of these apps was compared against the current guidelines and fitness principles established by the American College of Sports Medicine (ACSM). A weighted scoring method based on the recommendations of the ACSM was developed to generate subscores for quality of programming content for aerobic (0-6 scale), resistance (0-6 scale), and flexibility (0-2 scale) components using the frequency, intensity, time, and type (FITT) principle. An overall score (0-14 scale) was generated from the subscores to represent the overall quality of a fitness coaching app. RESULTS: Only 3 apps scored above 50% on the aerobic component (mean 0.7514, SD 1.2150, maximum 4.1636), 4 scored above 50% on the resistance/strength component (mean 1.4525, SD 1.2101, maximum 4.1094), and no app scored above 50% on the flexibility component (mean 0.1118, SD 0.2679, maximum 0.9816). Finally, only 1 app had an overall score (64.3%) above 50% (mean 2.3158, SD 1.911, maximum 9.0072). CONCLUSIONS: There are over 100,000 health-related apps. When looking at popular free apps related to physical activity, we observe that very few of them are evidence based, and respect the guidelines for aerobic activity, strength/resistance training, and flexibility, set forth by the ACSM. Users should exercise caution when adopting a new app for physical activity purposes. This study also clearly identifies a gap in evidence-based apps that can be used safely and effectively to start a physical routine program, develop fitness, and lose weight. App developers have an exciting opportunity to improve mobile coaching app quality by addressing these gaps.