Calibration of an Accelerometer Activity Index Among Older Women and Its Association With Cardiometabolic Risk Factors
Wang, 2022
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Last update: January 15, 2022. Updates will occur every 3 months.
Description
Description
Linear regression to predict METS and cut-points to classify activity intensity from accelerometer activity index (AAI) derived from a hip-worn ActiGraph monitor in older women. Sensitivity was 79-82%, specificity was 88-97%, and root mean square error was 0.482-0.503 METs.
Development/Validation
Development/Validation
Sample: 199 older women, 60-91 years of age
Setting: Laboratory
Activities: Activities of daily living, overground walking, stationary
Criterion: Oxycon Mobile (VO2)
Accelerometer(s): ActiGraph GT3X+ on right hip
Validation approach: Five-fold cross-validation
Instructions
Instructions
Calculate AAI using the relative equation described by Bai et al., 2016, then aggregate into AAI per 15-sec by taking the sum of AAI per second within the 15-sec epoch. The authors provided an overall model to predict METs from AAI, an age-specific model to predict METs from AAI, and cut-points to classify activity intensity based on AAI. AAI can also be calculated using the 'ActivityIndex' R package.
Source Information
Source Information
Reference:
Wang, G., Wu, S., Evenson, K. R., Kang, I., LaMonte, M. J., Bellettiere, J., ... & Di, C. (2022). Calibration of an Accelerometer Activity Index Among Older Women and Its Association With Cardiometabolic Risk Factors. Journal for the Measurement of Physical Behaviour, 5(3), 145-155. https://doi.org/10.1123/jmpb.2021-0031 Link to paper
Corresponding author: Chongzhi Di, cdi@fredhutch.org
Contact
Contact
Kimberly Clevenger at accelerometerrepository@gmail.com
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