Accuracy of two simple methods for the assessment of health-related physical fitness

A "Wearable" Test for Maximum Aerobic Power: Real-Time Analysis of a 60-m Sprint Performance and Heart Rate Off-Kinetics

Maximum aerobic power (V˙O2peak) as an indicator of body fitness is today a very well-known concept not just for athletes but also for the layman. Unfortunately, the accurate measurement of that variable has remained a complex and exhaustive laboratory procedure, which makes it inaccessible to many active people. In this paper we propose a quick estimate of it, mainly based on the heart rate off-kinetics immediately after an all-out 60-m sprint run. The design of this test took into account the recent availability of wrist wearable, heart band free, multi-sensor smart devices, which could also inertially detect the different phases of the sprint and check the distance run. 25 subjects undertook the 60-m test outdoor and a V˙O2peak test on the laboratory treadmill. Running average speed, HR excursion during the sprint and the time constant (τ) of HR exponential decay in the off-kinetics were fed into a multiple regression, with measured V˙O2peak as the dependent variable. Statistics revealed that within the investigated range (25–55 ml O₂/(kg min)), despite a tendency to overestimate low values and underestimate high values, the three predictors confidently estimate individual V˙O2peak (R² = 0.65, p < 0.001). The same analysis has been performed on a 5-s averaged time course of the same measured HR off-kinetics, as these are the most time resolved data for HR provided by many modern smart watches. Results indicate that despite of the substantial reduction in sample size, predicted V˙O2peak still explain 59% of the variability of the measured V˙O2peak.

Estimation of maximal oxygen uptake via submaximal exercise testing in sports, clinical, and home settings

Assessment of the functional capacity of the cardiovascular system is essential in sports medicine. For athletes, the maximal oxygen uptake [Formula: see text] provides valuable information about their aerobic power. In the clinical setting, the (VO(2max)) provides important diagnostic and prognostic information in several clinical populations, such as patients with coronary artery disease or heart failure. Likewise, VO(2max) assessment can be very important to evaluate fitness in asymptomatic adults. Although direct determination of [VO(2max) is the most accurate method, it requires a maximal level of exertion, which brings a higher risk of adverse events in individuals with an intermediate to high risk of cardiovascular problems. Estimation of VO(2max) during submaximal exercise testing can offer a precious alternative. Over the past decades, many protocols have been developed for this purpose. The present review gives an overview of these submaximal protocols and aims to facilitate appropriate test selection in sports, clinical, and home settings. Several factors must be considered when selecting a protocol: (i) The population being tested and its specific needs in terms of safety, supervision, and accuracy and repeatability of the VO(2max) estimation. (ii) The parameters upon which the prediction is based (e.g. heart rate, power output, rating of perceived exertion [RPE]), as well as the need for additional clinically relevant parameters (e.g. blood pressure, ECG). (iii) The appropriate test modality that should meet the above-mentioned requirements should also be in line with the functional mobility of the target population, and depends on the available equipment. In the sports setting, high repeatability is crucial to track training-induced seasonal changes. In the clinical setting, special attention must be paid to the test modality, because multiple physiological parameters often need to be measured during test execution. When estimating VO(2max), one has to be aware of the effects of medication on heart rate-based submaximal protocols. In the home setting, the submaximal protocols need to be accessible to users with a broad range of characteristics in terms of age, equipment, time available, and an absence of supervision. In this setting, the smart use of sensors such as accelerometers and heart rate monitors will result in protocol-free VO(2max) assessments. In conclusion, the need for a low-risk, low-cost, low-supervision, and objective evaluation of VO(2max) has brought about the development and the validation of a large number of submaximal exercise tests. It is of paramount importance to use these tests in the right context (sports, clinical, home), to consider the population in which they were developed, and to be aware of their limitations.

A simple assessment of physical activity is associated with obesity and motor fitness in pre-school children

OBJECTIVE

Physical activity is an important determinant of energy balance. However, its impact on overweight/obesity has proved difficult to measure in pre-school children and few studies have found significant associations. A set of simple questions was used to distinguish pre-school children with high and low physical activity, and the association of this classification with childhood overweight/obesity and performance in an established motor test was investigated.

DESIGN

Survey, cross-sectional.

SETTING AND SUBJECTS

Weight and height were measured in 12,556 children taking part in the obligatory school entrance health examination 2004-5 and 2005-6 in three urban and three rural Bavarian regions. Their parents were asked to answer a questionnaire with a set of questions on physical activity.

RESULTS

The mean age of the children evaluated was 5.78 (sd 0.43) years, 6535 (52.1 %) were boys. Physically active children were less likely to be overweight (OR = 0.786, 95 % CI 0.687, 0.898) or obese (OR = 0.655, 95 % CI 0.506, 0.849) and achieved 6.7 (95 % CI 5.8, 7.7) % more jumps per 30 s than less active children in a motor test, adjusted for a number of potentially confounding variables.

CONCLUSIONS

Classification of pre-school children as physically active or not, based on a small set of questions, revealed significant associations with overweight/obesity and a motor test. Once further validated, this classification might provide a valuable tool to assess the impact of physical activity on the risk of childhood overweight and obesity.