Associations between sensor-based physical activity behaviour features and health-related parameters

Abstract

ObjectivesWearable actimetry devices are used increasingly in cohort and cross-sectional studies to assess physical activity (PA) behaviour objectively. Thus far, the medical relevance of distinct PA groups, as identified by using new methods of sensor data analysis, remains unclear. The objective of this research paper is to evaluate whether such PA groups differ in commonly accepted health risk parameters. MethodsPA sensor data and corresponding outcome data of the NHANES 2005–06 study were obtained. Data pre-processing included elimination of potential outliers, data splitting and the computation of PA parameters, including a novel regularity measure. PA groups were identified using the x-Means clustering algorithm, and groups were evaluated for differences in CRP, BMI and HDL. ResultsData sets of 7334 NHANES participants were analysed, and four distinct PA groups were identified. Statistically significant group differences were found for CRP and BMI (p<0.001), but not for HDL (p=0.67). ConclusionsPA groups derived from objective accelerometer mass data differ in exemplary health-related outcome parameters. The novel PA regularity measure is of particular interest and may become part of future PA assessments, especially when regarding low-intensity, short-lived PA events. Further research in pattern recognition methods and analytic algorithms for PA data from current multi-sensing devices is necessary.