Using Activity Monitors to Measure Sit-to-Stand Transitions in Overweight/Obese Youth

Abstract

Introduction Reducing sedentary behavior has emerged as an important health intervention strategy. Although hip-worn, and more recently wrist-worn, accelerometers are commonly used for measuring physical activity and sedentary behavior, they may not provide accurate measures of postural changes. The current study examined the validity of commonly used hip- and wrist-worn accelerometer cut points and the thigh-worn activPAL activity monitor for measuring sit-to-stand transitions as compared to direct observation in youth with overweight and obesity. Methods Nine children wore three activity monitors while being directly observed. The monitors included a hip- and wrist-worn ActiGraph and thigh-worn activPAL. The hip-worn ActiGraph was processed with the normal and low frequency filters and the inclinometer function. Cut points of ≤25 counts per 15-second epoch for the hip, and ≤105 counts per 15-second epoch for the wrist were applied to the vertical axis to identify sit-to-stand transitions. Epoch-level absolute agreement, Bland-Altman plots, mixed-effects linear regression, and Intraclass Correlation Coefficients (ICCs) were investigated. Results The hip and wrist accelerometer cut points and hip inclinometer function overestimated the number of hourly sit-to-stand transitions by approximately triple as compared to direct observation. ICCs between the ActiGraph methods and direct observation were all <0.12. Sit-to-stand transitions assessed from ActivPAL were within 17% of direct observation; ICC was 0.26. Conclusion Despite the common use of the 100 count hip-worn accelerometer cut point for assessing sedentary time, these processing decisions should be used with caution for assessing sit-to-stand transitions. Future research should investigate other processing methods for ActiGraph data, and studies investigating postural changes should consider including devices such as activPALs.

Improving Hip-Worn Accelerometer Estimates of Sitting Using Machine Learning Methods

“…Compared with a thigh-worn inclinometer, the hip-worn 100-count threshold has been shown to underestimate standing time and overestimate the number of sit-to-stand transitions ( 9 ). Some studies have suggested new cut points for the hip accelerometer, ranging from 25 to 300 counts per minute ( 10 ), but such absolute cut points may not always distinguish between sitting still and standing still or moving while sitting and moving while standing ( 11 ). Cut points also do not make full use of differences in patterns in the accelerometer signal (beyond counts) across activities, for example, that can be seen in vehicle travel.…”

Neighborhood built environment associations with adolescents' location-specific sedentary and screen time

“…Future studies should use newer GPS devices that measure signal strength to support identification of indoor vs. outdoor time (Lam et al, 2013). The use of hip-worn accelerometer cut points for the purposes of this study is potentially limited because they do not specifically differentiate sitting from standing behavior (Mitchell et al, 2017). However, these methods have good validity for accurately assessing an individual's volume of sedentary time in minutes (Evenson et al, 2008;Trost et al, 2011;Carlson et al, 2019), as was done in the present study.…”

Assessing sitting and standing in college students using height-adjustable desks

“…Others have used accelerometers to assess sedentary behaviour in a laboratory setting, but only a limited range of activities were assessed that may not reflect free-living conditions (Berninger et al, 2018). Recent evidence indicates that some accelerometer cut-points to assess sit-to-stand transitions have poor acceptability (Mitchell et al, 2017). Some studies have only used stand-biased desks (Benden et al, 2011(Benden et al, , 2014, which are set at a fixed height and may provide a different experience from adjustable standing desks.…”