Issues Related to Measuring and Interpreting Objectively Measured Sedentary Behavior Data

Abstract

1The use of objective measures of sedentary behavior has increased over the past decade. However, as 2 is the case for objectively measured physical activity, methodological decision before and after data 3 collection are likely to influence the outcomes. The aim of this paper is to review the evidence on 4 different methodological decisions made by researchers when examining sedentary behavior. The 5 different issues researchers may encounter when measuring sedentary behavior have been divided 6 into: 1) activity monitor placement; 2) epochs, cut points and non-wear time definitions; 3) criteria for 7 sedentary behavior bouts and breaks; and 4) combining motion and posture data. This paper 8 recommends that 1) activity monitors should be placed on the thigh and combined with a data 9 reduction approach that estimates inclination, especially in children and adults; and 2) researchers 10 should clearly report their data processing decisions to enhance the ability to evaluate and compare 11 studies in the future. However, the paper also highlights a dearth of methodological evidence to 12 inform the use of objective measures of sedentary behavior. Based on the gaps in the literature, 13 research recommendations, which require addressing to develop a best practice protocol when 14 measuring sedentary behavior objectively, have been made. 15 16

Validity of an Integrative Method for Processing Physical Activity Data

“…It is notable that the SIP method, which is designed to better distinguish sitting from standing through the inclusion of postural data from the AP, improved on the SOJ method even for vigorous upright activities. This can only have been caused by the insertion of candidate bout boundaries, as there was no standing or sedentary time to reclassify, and indeed we observed several instances in our data in which the SOJ method failed to separate a rest period from an adjacent active bout, causing SOJ to underestimate the intensity of the active bout (see Figure The inherent challenges in processing and interpreting accelerometry-based physical activity data have been well chronicled (3,20). The need to simultaneously examine physical activity and sedentary behaviors further compounds these challenges.…”

“…These monitors offer multiple options for processing methods that provide varying levels of precision and accuracy for both estimating energy expenditure (EE) as well as classifying activities into different intensity categories. For example, data from the ActiGraph (AG) accelerometer, one of the most commonly used monitors, has been processed in a variety of ways including differences in intensity cut-points, wear-time algorithms, and bout durations, as well as utilizing data from the vertical axis only vs. data from all 3 axes (11,20,24,29,32).…”

Objectively measured sedentary behaviour and health and development in children and adolescents: systematic review and meta‐analysis

“…Considering the evidence from numerous studies among adults indicating that overall sedentary time (3,4,6,65) and patterns of sedentary behaviour (2,3,5) are adversely associated with health outcomes, particularly cardio-metabolic health, explaining the contrasting findings among studies in children and adolescents is challenging. There are a number of measurement issues to consider when objectively measuring sedentary behaviour (66)(67)(68)(69), which could influence the ability to detect associations. Specifically, the validity of cut-point-based approaches to estimate sedentary time from hip-mounted accelerometers is limited because of the potential to misclassify standing still as sedentary behaviour (69,70).…”

Volume and correlates of objectively measured physical activity and sedentary time in non‐Hodgkin lymphoma survivors

“…The cutoff points we used to differentiate different levels of activity intensity were created using data from young adults , so it is possible that they underestimated the actual intensity of the activity performed by the NHL survivors in this study. Other accelerometer data reduction‐related decisions, such as epoch length, the definition of non‐wear time, the definitions of sedentary and activity bouts, and minimum cutoffs for valid daily hours of wear time and valid days of wear time, are also all likely to influence accelerometer‐derived estimates of time spent sedentary and time spent in different levels of physical activity intensity .…”