822. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study
Commentary by Dr Paul Kelly, The University of Edinburgh, UK
The paper by Doherty et al., is a descriptive epidemiology study that reports accelerometer estimated physical activity in almost 100,000 participants of the UK Biobank Study. The UK Biobank is a large prospective study with 500,000 participants aged 40±69 years when they were recruited between 2006 and 2010.
The researchers asked participants to wear the wrist worn Axivity AX3 triaxial accelerometer for 7 days. Devices were delivered and returned by post. A total of 236,519 UK Biobank participants were approached, of whom 106,053 (44.8%) agreed to wear a device. After data processing and cleaning 96,600 (40.8% of those invited) were included in analysis.
This is the largest accelerometer based physical activity data collection the writer is aware of and represents a remarkable dataset. Additionally, the wrist worn nature of the device is likely to have contributed to higher compliance and wear time than is possible with waist or belt worn devices. However, potential biases in who consented and complied were not reported, and this remains an issue for investigation.
The longitudinal nature of this dataset opens the opportunity to assess the relationship between objective physical activity patterns and long term health outcomes. Ultimately we may see the generation of “objective physical activity guidelines” to complement our existing guidelines of 150 minutes of moderate or 75 minutes of vigorous that were derived from self-reported physical activity behaviour. This will hopefully prevent the mistaken attempts to assess 150 minutes of MVPA by accelerometer. However, it should be noted that while this is relevant to aerobic activity, the contribution to muscle strengthening and balance and coordination guidelines and surveillance is unclear.
Physical activity was estimated by computing an output termed "vector magnitude". Men registered higher vector magnitude than women in those aged 45-54 years. However, women registered higher vector magnitude in 55-64 years, 65-74 years and 75-79 years. This perhaps challenges current understanding of physical activity and sex in the UK. Vector magnitude decreased with age in both genders, which is consistent with current understanding. It is worth noting that the vector magnitude method is a move away from “cut-points” and the associated issues and challenges of that approach.
A particularly exciting aspect of these data is the ability to objectively assess patterns by time of day and by day of week. These patterns may prove important in predicting health outcomes, and highlighting if frequency and bout duration as well as total volume of activity are important.
In conclusion, this study represents a potential shift in how physical activity patterns and related health outcomes are understood. The hopefully forthcoming papers from this dataset may profoundly change how we understand physical activity’s impact on health.
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