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• W4220741226 abstract "Abstract Background Given the evolution of processing and analyzing accelerometry data over the past decade, it is of utmost importance that we as a field understand how newer (e.g., MIMS) summary measures compare to long-established ones (e.g., ActiGraph activity counts). Objective Our study aims to compare and harmonize accelerometry-based measures of physical activity (PA) to increase the comparability, generalizability, and translation of findings across studies using objective measures of PA. Methods High resolution accelerometry data were collected from 655 participants in the Baltimore Longitudinal Study on Aging who wore an ActiGraph GT9X device at wrist continuously for a week. Data were summarized at the minute-level as activity counts (AC; measure obtained from ActiGraph’s ActiLife software) and MIMS, ENMO, MAD, and AI (open-source measures implemented in R). The correlation between AC and other measures was quantified both marginally and conditionally on age, sex and BMI. Next, each pair of measures were harmonized using nonparametric regression of minute-level measurements. Results The study sample had the following characteristics: mean (sd) age of 69.8 (14.2), BMI of 27.3 (5.0) kg/m 2 , 54.5% females, and 67.9% white. The marginal participant-specific correlation between AC and MIMS, ENMO, MAD, and AI were 0.988, 0.867, 0.913 and 0.970, respectively. After harmonization, the mean absolute percentage error for predicting total AC from MIMS, ENMO, MAD, and AI was 2.5, 14.3, 11.3 and 6.3, respectively. The accuracy for predicting sedentary minutes based on AC (AC > 1853) using MIMS, ENMO, MAD and AI was 0.981, 0.928, 0.904, and 0.960, respectively. An R software with a unified interface for computation of the open-source measures from raw accelerometry data was developed and published as SummarizedActigraphy R package. Conclusions Our comparison of accelerometry-based measures of PA enables researchers to extend the knowledge from the thousands of manuscripts that have been published using ActiGraph AC to MIMS and other measures by demonstrating their high correlation and providing a harmonization mapping." @default.
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• W4220741226 date "2022-03-18" @default.
• W4220741226 modified "2023-10-18" @default.
• W4220741226 title "Comparison of Accelerometry-based Measures of Physical Activity" @default.
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• W4220741226 doi "https://doi.org/10.1101/2022.03.16.22272518" @default.
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