Sources of variance in daily physical activity levels as measured by an accelerometer

To examine sources of variance in objective measures of physical activity in a group of healthy adults (N = 92) participating in a physical activity measurement study. Physical activity was assessed for up to 21 consecutive days using the Computer Science Applications (CSA) accelerometer. Day-of-the...

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Veröffentlicht in:Medicine and science in sports and exercise 2002-08, Vol.34 (8), p.1376-1381
Hauptverfasser: MATTHEWS, Charles E, AINSWORTH, Barbara E, THOMPSON, Raymond W, BASSETT, David R
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Sprache:eng
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Zusammenfassung:To examine sources of variance in objective measures of physical activity in a group of healthy adults (N = 92) participating in a physical activity measurement study. Physical activity was assessed for up to 21 consecutive days using the Computer Science Applications (CSA) accelerometer. Day-of-the-week effects were evaluated for activity counts (ct.min(-1).d(-1), ct.d(-1)) and time (min.d(-1)) spent in inactivity (0-499 ct), moderate-1 (500-1951 ct), and moderate-2-vigorous activity (> or =1952 ct). Random effects models were employed to estimate variance components for subject, day of the week, and residual error from which the number of days of assessment required to achieve 80% reliability were estimated. Physical inactivity was lower on weekend days, and Saturday was the least inactive day of the week for both men and women. Inter-individual variation, or differences between subjects, was proportionally the largest source of variance (55-60% of total) in accelerometer counts and time spent in moderate to vigorous activity. Differences within subjects (intra-individual variation) accounted for 30-45% of the overall variance, and day-of-the-week effects accounted for 1-8%. For activity counts, and time spent in moderate to vigorous activity, at least 3-4 d of monitoring were required to achieve 80% reliability. Reliable measures of physical inactivity required at least 7 d of monitoring. These findings provide insight for understanding the behavioral variability in the activity patterns of adults and suggest that reliable measures of activity behaviors require at least 7 d of monitoring.
ISSN:0195-9131
1530-0315
DOI:10.1097/00005768-200208000-00021