Physical activity has not been objectively measured in prospective cohorts with sufficiently large numbers to reliably detect associations with multiple health outcomes. Technological advances now make this possible. We describe the methods used to collect and analyse accelerometer measured physical activity in over 100,000 participants of the UK Biobank study, and report variation by age, sex, day, time of day, and season. Participants were approached by email to wear a wrist-worn accelerometer for seven days that was posted to them. Physical activity information was extracted from 100Hz raw triaxial acceleration data after calibration, removal of gravity and sensor noise, and identification of wear / non-wear episodes. We report age- and sex-specific wear-time compliance and accelerometer measured physical activity, overall and by hour-of-day, week-weekend day and season. 103,712 datasets were received (44.8% response), with a median wear-time of 6.9 days (IQR:6.5–7.0). 96,600 participants (93.3%) provided valid data for physical activity analyses. Vector magnitude, a proxy for overall physical activity, was 7.5% (2.35mg) lower per decade of age (Cohen’s d = 0.9). Women had a higher vector magnitude than men, apart from those aged 45-54yrs. There were major differences in vector magnitude by time of day (d = 0.66). Vector magnitude differences between week and weekend days (d = 0.12 for men, d = 0.09 for women) and between seasons (d = 0.27 for men, d = 0.15 for women) were small. It is feasible to collect and analyse objective physical activity data in large studies. The summary measure of overall physical activity is lower in older participants and age-related differences in activity are most prominent in the afternoon and evening. This work lays the foundation for studies of physical activity and its health consequences. Our summary variables are part of the UK Biobank dataset and can be used by researchers as exposures, confounding factors or outcome variables in future analyses.

Background: Accurate measurement of physical activity patterns can be used to identify sedentary behaviour and may facilitate interventions aimed at reducing inactivity. Objective: To evaluate the activPAL physical activity monitor as a measure of posture and motion in everyday activities using observational analysis as the criterion standard. Methods: Wearing three activPAL monitors, 10 healthy participants performed a range of randomly assigned everyday tasks incorporating walking, standing and sitting. Each trial was captured on a digital camera and the recordings were synchronised with the activPAL. The time spent in different postures was visually classified and this was compared with the activPAL output. Results: Intraclass correlation coefficients (ICC 2,1) for interdevice reliability ranged from 0.79 to 0.99. Using the Bland and Altman method, the mean percentage difference between the activPAL monitor and observation for total time spent sitting was 0.19% (limits of agreement −0.68% to 1.06%) and for total time spent upright was −0.27% (limits of agreement −1.38% to 0.84%). The mean difference for total time spent standing was 1.4% (limits of agreement −6.2% to 9.1%) and for total time spent walking was −2.0% (limits of agreement −16.1% to 12.1%). A second-by-second analysis between observer and monitor found an overall agreement of 95.9%. Conclusion: The activPAL activity monitor is a valid and reliable measure of posture and motion during everyday physical activities.

Background:The accurate measurement of physical activity is crucial to understanding the relationship between physical activity and disease prevention and treatment.Objective:The primary purpose of this study was to investigate the validity and reliability of theactivPAL physical activity monitor in measuring step number and cadence.Methods:The ability of theactivPAL monitor to measure step number and cadence in 20 healthy adults (age 34.5±6.9 years; BMI 26.8±4.8 (mean±SD)) was evaluated against video observation. Concurrently, the accuracy of two commonly used pedometers, the Yamax Digi-Walker SW-200 and the Omron HJ-109-E, was compared to observation for measuring step number. Participants walked on a treadmill at five different speeds (0.90, 1.12, 1.33, 1.56, and 1.78 m/s) and outdoors at three self selected speeds (slow, normal, and fast).Results:At all speeds, inter device reliability was excellent for theactivPAL (ICC (2,1)⩾0.99) for both step number and cadence. The absolute percentage error for theactivPAL was <1.11% for step number and cadence regardless of walking speed. The accuracy of the pedometers was adversely affected by slow walking speeds.Conclusion:TheactivPAL monitor is a valid and reliable measure of walking in healthy adults. Its accuracy is not influenced by walking speed. TheactivPAL may be a useful device in sports medicine.

This study investigated the possibility of using uni-axial gyroscopes to develop a simple portable gait analysis system. Gyroscopes were attached on the skin surface of the shank and thigh segments and the angular velocity for each segment was recorded in each segment. Segment inclinations and knee angle were derived from segment angular velocities. The angular signals from a motion analysis system were used to evaluate the angular velocities and the derived signals from the gyroscopes. There was a good correlation between these signals. When performing a turn the signals of segment inclination and knee angle drifted. Two methods were used to solve this: automatically resetting the system to re-initialise the angle in each gait cycle, and high-pass filtering. They both successfully corrected this drift. A single gyroscope on the shank segment could provide information on segment inclination range, cadence, number of steps, and an estimation of stride length and walking speed.

This study aimed to describe the scope of accelerometry data collected internationally in adults and to obtain a consensus from measurement experts regarding the optimal strategies to harmonize international accelerometry data. In March 2014, a comprehensive review was undertaken to identify studies that collected accelerometry data in adults (sample size, n ≥ 400). In addition, 20 physical activity experts were invited to participate in a two-phase Delphi process to obtain consensus on the following: unique research opportunities available with such data, additional data required to address these opportunities, strategies for enabling comparisons between studies/countries, requirements for implementing/progressing such strategies, and value of a global repository of accelerometry data. The review identified accelerometry data from more than 275,000 adults from 76 studies across 36 countries. Consensus was achieved after two rounds of the Delphi process; 18 experts participated in one or both rounds. The key opportunities highlighted were the ability for cross-country/cross-population comparisons and the analytic options available with the larger heterogeneity and greater statistical power. Basic sociodemographic and anthropometric data were considered a prerequisite for this. Disclosure of monitor specifications and protocols for data collection and processing were deemed essential to enable comparison and data harmonization. There was strong consensus that standardization of data collection, processing, and analytical procedures was needed. To implement these strategies, communication and consensus among researchers, development of an online infrastructure, and methodological comparison work were required. There was consensus that a global accelerometry data repository would be beneficial and worthwhile. This foundational resource can lead to implementation of key priority areas and identification of future directions in physical activity epidemiology, population monitoring, and burden of disease estimates.