Thigh-worn accelerometry for measuring movement and posture across the 24-hour cycle: a scoping review and expert statement

Abstract

IntroductionThe Prospective Physical Activity Sitting and Sleep consortium (ProPASS) is an international collaboration platform committed to harmonise thigh-worn accelerometry data. The aim of this paper is to (1) outline observational thigh-worn accelerometry studies and (2) summarise key strategic directions arising from the inaugural ProPASS meeting.Methods(1) We performed a systematic scoping review for observational studies of thigh-worn triaxial accelerometers in free-living adults (n≥100, 24 hours monitoring protocols). (2)Attendees of the inaugural ProPASS meeting were sent a survey focused on areas related to developing ProPASS: important terminology (Q1); accelerometry constructs (Q2); advantages and distinct contribution of the consortium (Q3); data pooling and harmonisation (Q4); data access and sharing (Q5 and Q6).Results(1) Eighty eligible articles were identified (22 primary studies; n~17 685). The accelerometers used most often were the ActivPAL3 and ActiGraph GT3X. The most commonly collected health outcomes were cardiometabolic and musculoskeletal. (2) None of the survey questions elicited the predefined 60% agreement. Survey responses recommended that ProPASS: use the term physical behaviour or movement behaviour rather than ‘physical activity’ for the data we are collecting (Q1); make only minor changes to ProPASS’s accelerometry construct (Q2); prioritise developing standardised protocols/tools (Q4); facilitate flexible methods of data sharing and access (Q5 and Q6).ConclusionsThigh-worn accelerometry is an emerging method of capturing movement and posture across the 24 hours cycle. In 2020, the literature is limited to 22 primary studies from high-income western countries. This work identified ProPASS’s strategic directions—indicating areas where ProPASS can most benefit the field of research: use of clear terminology, refinement of the measured construct, standardised protocols/tools and flexible data sharing.

Effect of physical activity and exercise on telomere length: Systematic review with meta‐analysis

“…Such studies would ideally utilize both self‐reported and device‐based measures of PA (e.g., accelerometers) so that we better understand the influence of each complex dimension of physical activity (domain, frequency, total volume, etc. ) 87 on TL.…”

A Machine Learning Classifier for Detection of Physical Activity Types and Postures During Free-Living

“…However, depending on the research questions, it may be enough to apply a single accelerometer on the thigh or lower back to record most key physical activity types. If the primary research question is related to assessment of "time-on-feet" (standing) and physical activity (walking, running, and cycling), applying a single thighworn accelerometer can be enough (Crowley et al, 2019;Stevens et al, 2020). However, if the main purpose is to study sedentary behaviors and a necessity of differentiating between lying down and sitting, a back-worn accelerometer is recommended.…”

Associations of neighborhood walkability with moderate to vigorous physical activity: an application of compositional data analysis comparing compositional and non-compositional approaches

“…Intensity zones (sleep, SP, LPA, MVPA) represent only one dimension of 24-hour movement behaviour [ 47 ]. Other dimensions include posture/activity type (reclining, sitting, standing, walking, running, cycling, and walking stairs), bout duration (short, moderate, or long), domain (sleep, work/school, and non-work), and biological state (awake or asleep) [ 40 ].…”