Comparative Analysis Between ActiGraph And ActivPAL Measured Moderate To Vigorous Physical Activity For People With COPD
ActiGraph (AG) accelerometers are commonly used to measure sedentary behavior (SB) and moderate-to-vigorous physical activity (MVPA), but there are compliance issues with waist-worn devices that lead to problems with missing data. ActivPAL (AP) devices are worn 24 hours/day on the thigh, and there is minimal missing data, but PAL software does not estimate MVPA. PURPOSE: We estimated MVPA from AP data using 5 data processing methods and assessed their agreement with AG-measured MVPA among older adults with chronic obstructive pulmonary disease (COPD) to determine whether AP devices can be used to measure MVPA. METHODS: This is a secondary data analysis of data collected from 148 inactive adults (aged ≥50) with COPD. Participants wore ActivPAL3 on the thigh and ActiGraph GT9X on the waist concurrently for 7 days. ActivPAL data was processed using the following methods: 1) metabolic equivalents (METs), 2) ≥75 steps/min, 3) ≥100 steps/min, 4) vector magnitude (VM) acceleration counts, and 5) vertical axis counts. ActiGraph data was processed using Freedson (2011) and Evenson (2023) VM cut points, 60s epochs, and normal filters. The Bland-Altman plots and concordance correlation coefficient (CCC) were used to assess the agreement between AP and AG MVPA using individual day-level data. RESULTS: Compared to AG MVPA using Freedson VM cut points, CCC ranged from 0.62 to 0.64 for all AP MVPA, except for 100 steps/min (CCC = 0.44). Compared to AG MVPA using Evenson VM cut points, CCC ranged from 0.08 to 0.18 for all AP MVPA. CONCLUSION: Most AP-derived estimates of MVPA showed moderate agreement and low bias and were reasonably accurate when compared to AG-derived MVPA with Freedson VM cut points. Further research is needed to further validate this approach. Table 1. - Comparing AG and AP Data Processing Methods for Measruing MVPA in Older Adults with COPD (n = 148) ActiGraph (60 second epochs, Normal Filter) Freedson VM cut points Evenson VM cut points ActivPAL Data Reduction Techniques Mean difference AG-AP (95%CI) Concordance Correlation(95%CI) Mean difference AG-AP (95%CI) Concordance Correlation(95%CI) METs (≥3 METs) 3.65 (-22.41, 29.72) 0.63 (0.58, 0.66) 33.50 (-32.27, 99.28) 0.18 (0.16, 0.21) Steps (≥75 steps/min) 3.93 (-22.16, 30.02) 0.62 (0.57, 0.66) 33.78 (-32.35, 99.90) 0.18 (0.15, 0.20) Steps (≥100 steps/min) 8.23 (-18.20, 34.66) 0.44 (0.40, 0.48) 38.08 (-32.14, 108.29) 0.08 (0.06, 0.09) VM acceleration counts (≥35492) 5.28 (-20.00, 30.56) 0.62 (0.57, 0.65) 35.13 (-31.54, 101.80) 0.16 (0.14, 0.19) Vertical axis counts (≥20492) 5.55 (-18.82, 29.91) 0.64 (0.60, 0.67) 35.39 (-31.43, 102.22) 0.16 (0.13, 0.18) Note. VM = Vector Magnitude; AG = ActiGraph; AP = ActivPAL; METs = Metabolic Equivalents Supported by: J.Y.S. is supported by NIH T32 NR016914.
Authors
- Katelyn Webster (ORCID: https://orcid.org/0000-0002-8443-3115)
- Sandra K. Tucker (ORCID: https://orcid.org/0009-0004-2172-7847)
- Janet L. Larson (ORCID: https://orcid.org/0000-0002-3920-8998)
- Jung Yoen Son (ORCID: https://orcid.org/0000-0003-0909-2688)
- Deanna J. Marriott (ORCID: https://orcid.org/0000-0002-7104-5682)
- Nathan Kaduk
Institutions
- University of Michigan (US)
Publication Details
- Journal
- Medicine & Science in Sports & Exercise
- Published
- 2025-09-16
- DOI
- https://doi.org/10.1249/01.mss.0001160180.84626.8b
- Primary Topic
- Stroke Rehabilitation and Recovery
- Type
- article
- Field-Weighted Citation Impact
- 0.00