CHAP-Adult: A Reliable and Valid Algorithm to Classify Sitting and Measure Sitting Patterns Using Data From Hip-Worn Accelerometers in Adults Aged 35

• Published in: Journal for the measurement of physical behaviour Vol. 5; no. 4; p. 215
• Main Authors: Bellettiere, John, Nakandala, Supun, Tuz-Zahra, Fatima, Winkler, Elisabeth A H, Hibbing, Paul R, Healy, Genevieve N, Dunstan, David W, Owen, Neville, Greenwood-Hickman, Mikael Anne, Rosenberg, Dori E, Zou, Jingjing, Carlson, Jordan A, Di, Chongzhi, Dillon, Lindsay W, Jankowska, Marta M, LaCroix, Andrea Z, Ridgers, Nicola D, Zablocki, Rong, Kumar, Arun, Natarajan, Loki
• Format: Journal Article
• Language: English
• Published: United States 01.12.2022
• Subjects: computational methods; activity classification; machine learning; sedentary behavior; validation; neural networks
• ISSN: 2575-6613; 2575-6605; 2575-6613
• DOI: 10.1123/jmpb.2021-0062

Hip-worn accelerometers are commonly used, but data processed using the 100 counts per minute cut point do not accurately measure sitting patterns. We developed and validated a model to accurately classify sitting and sitting patterns using hip-worn accelerometer data from a wide age range of older adults. Deep learning models were trained with 30-Hz triaxial hip-worn accelerometer data as inputs and activPAL sitting/nonsitting events as ground truth. Data from 981 adults aged 35-99 years from cohorts in two continents were used to train the model, which we call CHAP-Adult (Convolutional Neural Network Hip Accelerometer Posture-Adult). Validation was conducted among 419 randomly selected adults not included in model training. Mean errors (activPAL - CHAP-Adult) and 95% limits of agreement were: sedentary time -10.5 (-63.0, 42.0) min/day, breaks in sedentary time 1.9 (-9.2, 12.9) breaks/day, mean bout duration -0.6 (-4.0, 2.7) min, usual bout duration -1.4 (-8.3, 5.4) min, alpha .00 (-.04, .04), and time in ≥30-min bouts -15.1 (-84.3, 54.1) min/day. Respective mean (and absolute) percent errors were: -2.0% (4.0%), -4.7% (12.2%), 4.1% (11.6%), -4.4% (9.6%), 0.0% (1.4%), and 5.4% (9.6%). Pearson's correlations were: .96, .92, .86, .92, .78, and .96. Error was generally consistent across age, gender, and body mass index groups with the largest deviations observed for those with body mass index ≥30 kg/m . Overall, these strong validation results indicate CHAP-Adult represents a significant advancement in the ambulatory measurement of sitting and sitting patterns using hip-worn accelerometers. Pending external validation, it could be widely applied to data from around the world to extend understanding of the epidemiology and health consequences of sitting.