Abstract
BackgroundEpidemiological studies on physical activity often lack inexpensive, objective, valid, and reproducible tools for measuring physical activity levels of participants. Novel sensing technologies built into smartphones offer the potential to fill this gap.ObjectiveWe sought to validate estimates of physical activity and determine the usability for large population-based studies of the smartphone-based CalFit software.MethodsA sample of 36 participants from Barcelona, Spain, wore a smartphone with CalFit software and an Actigraph GT3X accelerometer for 5 days. The ease of use (usability) and physical activity measures from both devices were compared, including vertical axis counts (VT) and duration and energy expenditure predictions for light, moderate, and vigorous intensity from Freedson’s algorithm. Statistical analyses included (1) Kruskal-Wallis rank sum test for usability measures, (2) Spearman correlation and linear regression for VT counts, (3) concordance correlation coefficient (CCC), and (4) Bland-Altman plots for duration and energy expenditure measures.ResultsApproximately 64% (23/36) of participants were women. Mean age was 31 years (SD 8) and mean body mass index was 22 kg/m2 (SD 2). In total, 25/36 (69%) participants recorded at least 3 days with at least 10 recorded hours of physical activity using CalFit. The linear association and correlations for VT counts were high (adjusted R 2=0.85; correlation coefficient .932, 95% CI 0.931-0.933). CCCs showed high agreement for duration and energy expenditure measures (from 0.83 to 0.91).ConclusionsThe CalFit system had lower usability than the Actigraph GT3X because the application lacked a means to turn itself on each time the smartphone was powered on. The CalFit system may provide valid estimates to quantify and classify physical activity. CalFit may prove to be more cost-effective and easily deployed for large-scale population health studies than other specialized instruments because cell phones are already carried by many people.
Highlights
1.2 Understanding the nature of health risks1.1 Purpose of this reportA description of diseases and injuries and the risk factors that cause them is vital for health decisionmaking and planning
Health risks are in transition: populations are ageing owing to successes against infectious diseases; at the same time, patterns of physical activity and food, alcohol and tobacco consumption are changing
The 24 risk factors described in this report are responsible for 44% of global deaths and 34% of disability-adjusted life years (DALYs); the 10 leading risk factors account for 33% of deaths
Summary
1.2 Understanding the nature of health risks. A description of diseases and injuries and the risk factors that cause them is vital for health decisionmaking and planning. Understanding the risks to health is key to preventing disease and injuries. A particular disease or injury is often caused by more than one risk factor, which means that multiple interventions are available to target each of these risks. The infectious agent Mycobacterium tuberculosis is the direct cause of tuberculosis; crowded housing and poor nutrition increase the risk, which presents multiple paths for preventing the disease. Most risk factors are associated with more than one disease, and targeting those factors can reduce multiple causes of disease. By quantifying the impact of risk factors on diseases, evidence-based choices can be made about the most effective interventions to improve global health
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