BackgroundLow 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.ObjectiveOver 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.MethodsA 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.ResultsOnly 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).ConclusionsThere 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.

BackgroundCardiorespiratory 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.MethodsA 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). was measured using the Balke maximal treadmill fitness test.ResultsOf the 40 participants, there were 18 men and 22 women. Mean age was 31.2 years (SD = 9.9). We found that the best 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.ConclusionsThe study provided strong evidence for the validity of the squat test in the clinical setting. Further, the equation of our model along with normative tables provides an efficient and easy way to assess CRF in a primary care setting.

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.

No abstract