Research Article: Convergent validity of ActiGraph and Actical accelerometers for estimating physical activity in adults

Date Published: June 12, 2018

Publisher: Public Library of Science

Author(s): Scott Duncan, Tom Stewart, Mikkel Bo Schneller, Suneeta Godbole, Kelli Cain, Jacqueline Kerr, Rebecca A. Krukowski.


The aim of the present study was to examine the convergent validity of two commonly-used accelerometers for estimating time spent in various physical activity intensities in adults.

The sample comprised 37 adults (26 males) with a mean (SD) age of 37.6 (12.2) years from San Diego, USA. Participants wore ActiGraph GT3X+ and Actical accelerometers for three consecutive days. Percent agreement was used to compare time spent within four physical activity intensity categories under three counts per minute (CPM) threshold protocols: (1) using thresholds developed specifically for each accelerometer, (2) applying ActiGraph thresholds to regression-rectified Actical CPM data, and (3) developing new ‘optimal’ Actical thresholds.

Using Protocol 1, the Actical estimated significantly less time spent in light (-16.3%), moderate (-2.8%), and vigorous (-0.4%) activity than the ActiGraph, but greater time spent sedentary (+20.5%). Differences were slightly more pronounced when the low frequency extension filter on the ActiGraph was enabled. The two adjustment methods (Protocols 2 and 3) improved agreement in this sample.

Our findings show that ActiGraph and Actical accelerometers provide significantly different estimates of time spent in various physical activity intensities. Regression and threshold adjustment were able to reduce these differences, although some level of non-agreement persisted. Researchers should be aware of the inherent limitations of count-based physical activity assessment when reporting and interpreting study findings.

Partial Text

Physical inactivity has become a prominent area of research because of its known associations with chronic disease [1]. Indeed, increasing the proportion of the population who meet physical activity guidelines is a public health priority in many countries [2]. Accurate assessment of physical activity is therefore crucial for identifying important dose-response relationships with health outcomes, and understanding current physical activity patterns and practices. This information is necessary for the development of physical activity guidelines, interventions, and policy recommendations to promote physical activity and improve population health [3].

The descriptive characteristics of the sample are presented in Table 1. Differences in height and weight were observed between males and females. The mean wear time per day was 11.2 ± 2.1 hours. The average CPM was higher for the AGNORM (596 ± 203) and AGLFE (662 ± 219) than AC (236 ± 94). Between-device variation was consistent in both males and females.

The ability to compare physical activity outcomes measured from different accelerometer-based motion sensors is vital for the assimilation of physical activity information, understanding health outcomes, and developing supportive policy. In this study, we assessed the convergent validity of two popular accelerometers by developing three CPM threshold conditions. Although newer devices featuring wearable technology are regularly being released, many large studies have utilized the AC and AG accelerometers and continue to do so prospectively. Knowing how to adjust these analyses appropriately will facilitate a consistent evidence base.

Identifying small differences in physical activity outcomes is important for evaluating the effectiveness of physical activity interventions. Accelerometers have become an integral part of physical activity research, yet data comparability between devices is not without complication. We demonstrated that regression models developed to rectify differences between the Actical and ActiGraph accelerometers improved data agreement. In practice, this means that application of the regression equations in Protocol 2 or the cut-point adjustments in Protocol 3 should result in better alignment of existing AC and AG datasets. However, the outcomes of this study may not be consistent across all populations. Researchers should therefore continue to be aware of the inherent limitations of count-based physical activity assessment when reporting and interpreting study findings.




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