Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling

Abstract

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Smartphones and wearable activity trackers present opportunties for large-scale physical activity surveillance that overcome some limitations of questionnaires or researcher-owned devices. However, it is unknown whether the current users of such technologies are representative of the UK population. Objective: To investigate potential socio-demographic biases in individuals using, or with the potential to use, smartphone applications and/or wearable activity trackers for physical activity surveillance in the UK. Methods: Data in adults (≥16 years) from two nationally representative surveys were used: the UK-wide 2018 Ofcom Technology Tracker (n=3,688) and the 2016 Health Survey for England (n=4,539). In the former, we derived mutually-adjusted odds ratios (95% confidence intervals) of personal use or household ownership of a smartwatch/fitness tracker, and personal use of a smartphone, by age, sex, social grade, activity/work limiting disability, urban/rural, and home nation. In the latter, the outcomes of interest were the use of wearable trackers or websites/smartphone applications for weight management. The explanatory variables were age, sex, physical activity, deprivation, and body mass index. We also carried out the Health Survey for England analyses stratified by body mass index, as these questions were asked in the context of weight management. Results: Smartphone use was the most prevalent of all outcomes with over 70% of most sub-groups responding affirmatively (exceptions were age ≥65 years and those with activity or work limiting disabilities). All other outcomes were <30% prevalent. Age ≥65 years was the strongest inverse correlate of all outcomes (e.g. 0.03 (0.02-0.05) for smartphone use compared to 16-44 year-olds). Lower social grade and activity/work limiting disability were also inversely associated with all Technology Tracker outcomes. Physical inactivity and male sex were inversely associated with both Health Survey for England outcomes; higher levels of deprivation were only inversely assocaited with websites/phone applications use for weight management. The conclusions did not differ meaningfully in the body mass index stratified analyses, except for deprivation which showed stronger inverse associations with websites/phone applications use in the obese. Conclusions: The sole use of physical activity data from personal trackers or smartphone apps for UK national surveillance is premature as those using these devices are more active, younger, and more affluent than those who do not.