Objectively and Subjectively Measured Physical Activity and Their Associations With Cardiometabolic Risk in the UK Biobank: Retrospective Cohort Study

Charlyne Bürki, Caiwei Tian, Kenneth Westerman, Chirag Patel

Abstract: Background: The association between physical activity behavior and cardiometabolic risk factors in longitudinal cohort studies has depended largely on questionnaire-based reporting. However, more studies are turning to mHealth device solutions, where physical activity (PA) can be directly measured with the promise of lower error than self-reported PA. While there are differences between self-reported activity levels and objectively measured accelerometer-based activity, how these differences manifest in disease risk is unknown. Objective: Here, to demonstrate the value of mHealth devices in the research setting, we sought to evaluate these differences and to model the impact in their association with cardiometabolic factors in a longitudinal cohort study which assessed PA using mHealth devices versus questionnaires. Our study provides a framework to assess the quality of relationships measured by mHealth technologies, which is generalizable to other sensors or activity-measuring devices. Methods: We assessed physical activity using both wrist-worn accelerometer data and self-reported questionnaires in 16K participants of the UK Biobank between 2013 and 2015, focusing on walking, sleeping, sedentary, and moderate-to-vigorous physical activity (MVPA). We compared the concordance between self-reported and objective measures of PA. We also compared the association between objective measured or self-reported PA and future clinical biomarker levels (e.g., body mass index, pulse rate, glucose control, cholesterol), controlling for lifestyle factors such as diet and disease. Results: Participants underestimated their weekly sedentary duration on average of 2.86 hours, and the correlation between subjective and objective activity were respectively r=0.12 for sedentary time, r=0.16 for moderate to vigorous physical activity, r=0.18 for walking, and r=0.13 for sleeping. We found an inverse association between objectively measured MVPA and cardiometabolic biomarkers such as BMI and pulse rate but found no association between subjectively reported activity and cardiometabolic biomarkers. We estimated that there is a 6% larger association between subjectively measured MVPA and BMI in healthy adults (versus the objective counterpart). We also estimated a 2 to 3% difference on a healthy adult heart beat (healthy range: 60 to 100 beats per minute [bpm]) if relying on subjectively-reported observations instead of measured physical activity. Conclusions: These findings provide evidence that the association of self-reported activity is likely overestimated and biased compared to objective physical activity acquired with mobile health (mHealth) devices. As such, care should be taken when assessing the effect of self-reported physical activity on key cardiometabolic factors, such as BMI and pulse rate, which are predictors of cardiometabolic disease (e.g., cardiovascular disease and diabetes), irrespective of the cohort population studied, and research cohorts should strive to incorporate mHealth devices in their studies to enhance physical activity guideline development. We emphasize that while the associations are biased when comparing physical activity modalities, we cannot conclude which method more closely reflected the daily activity load.

External IDs:doi:10.2196/54820