Accelerometer-assessed Physical Activity in Epidemiology: Are Monitors Equivalent?

ABSTRACTPurposeAccelerometers are increasingly being used to assess physical activity in large-scale surveys. Establishing whether key physical activity outcomes can be considered equivalent between three widely used accelerometer brands would be a significant step toward capitalizing on the increasing availability of accelerometry data for epidemiological research.MethodsTwenty participants wore a GENEActiv, an Axivity AX3, and an ActiGraph GT9X on their nondominant wrist and were observed for 2 h in a simulated living space. Participants undertook a series of seated and upright light/active behaviors at their own pace. All accelerometer data were processed identically using open-source software (GGIR) to generate physical activity outcomes (including average dynamic acceleration (ACC) and time within intensity cut points). Data were analyzed using pairwise 95% equivalence tests (±10% equivalence zone), intraclass correlation coefficients (ICC) and limits of agreement.ResultsThe GENEActiv and Axivity could be considered equivalent for ACC (ICC = 0.95, 95% confidence interval (CI), 0.87–0.98), but ACC measured by the ActiGraph was approximately 10% lower (GENEActiv/ActiGraph: ICC = 0.86; 95% CI, 0.56–0.95; Axivity/ActiGraph: ICC = 0.82; 95% CI, 0.50–0.94). For time spent within intensity cut points, all three accelerometers could be considered equivalent to each other for more than 85% of outcomes (ICC ≥0.69, lower 95% CI ≥0.36), with the GENEActiv and Axivity equivalent for 100% of outcomes (ICC ≥0.95, lower 95% CI ≥0.86).ConclusionsGENEActiv and Axivity data processed in GGIR are largely equivalent. If GENEActiv or Axivity is compared with the ActiGraph, time spent within intensity cut points has good agreement. These findings can be used to inform selection of appropriate outcomes if outputs from these accelerometer brands are compared. Purpose Accelerometers are increasingly being used to assess physical activity in large-scale surveys. Establishing whether key physical activity outcomes can be considered equivalent between three widely used accelerometer brands would be a significant step toward capitalizing on the increasing availability of accelerometry data for epidemiological research. Methods Twenty participants wore a GENEActiv, an Axivity AX3, and an ActiGraph GT9X on their nondominant wrist and were observed for 2 h in a simulated living space. Participants undertook a series of seated and upright light/active behaviors at their own pace. All accelerometer data were processed identically using open-source software (GGIR) to generate physical activity outcomes (including average dynamic acceleration (ACC) and time within intensity cut points). Data were analyzed using pairwise 95% equivalence tests (±10% equivalence zone), intraclass correlation coefficients (ICC) and limits of agreement. Results The GENEActiv and Axivity could be considered equivalent for ACC (ICC = 0.95, 95% confidence interval (CI), 0.87–0.98), but ACC measured by the ActiGraph was approximately 10% lower (GENEActiv/ActiGraph: ICC = 0.86; 95% CI, 0.56–0.95; Axivity/ActiGraph: ICC = 0.82; 95% CI, 0.50–0.94). For time spent within intensity cut points, all three accelerometers could be considered equivalent to each other for more than 85% of outcomes (ICC ≥0.69, lower 95% CI ≥0.36), with the GENEActiv and Axivity equivalent for 100% of outcomes (ICC ≥0.95, lower 95% CI ≥0.86). Conclusions GENEActiv and Axivity data processed in GGIR are largely equivalent. If GENEActiv or Axivity is compared with the ActiGraph, time spent within intensity cut points has good agreement. These findings can be used to inform selection of appropriate outcomes if outputs from these accelerometer brands are compared.

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