AI Article Synopsis

  • Assessing physical activity in older adults is crucial for reducing disability and improving health, but existing monitors aren't validated for this demographic.
  • This study created prediction equations based on lower-limb accelerometer data to estimate activity levels in older adults.
  • The best equations showed strong correlations between accelerometer data and oxygen uptake during walking and stair-climbing, indicating effective prediction of physical activity.

Article Abstract

Assessing physical activity in older adults has proven to be difficult but important, because regular participation has a protective and rehabilitative effect against disability and morbidity. Commercially available physical activity monitors measure waist movements and have not been validated for older adults. This study developed a model for establishing prediction equations to estimate older adults physical activity levels based on lower-limb accelerometer measures. Oxygen uptake and lower-limb accelerometer data were simultaneously recorded from treadmill and stair-climbing exercises. The best stepwise regression equations were obtained when accelerometer and weight measures were regressed on oxygen uptake when subjects walked 1, 2, and 3 miles per hour (R = 0.69 with accelerometer on back of the heel) and for accelerometer measures and gender when subjects climbed stairs (R = 0.77 with accelerometer on mid-ankle). These findings illustrate that physical activity can be effectively predicted in older adults from lower-limb accelerometer measurements.

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Source
http://dx.doi.org/10.1682/jrrd.2003.12.0176DOI Listing

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