How many days of pedometer monitoring predict monthly ambulatory activity in adults?
OBJECTIVE
To determine how many days of pedometer monitoring are necessary to estimate monthly ambulatory activity in adults.


METHODS
Two hundred and twelve adults (64% female; age = 38.3 +/- 13.3 yr; body mass index = 27.9 +/- 5.3 kg x m(-2)) wore a pedometer (SW-200) for 28 consecutive days. About 76.4% were randomly allocated to a reliability group, whereas the remainder (n = 50) comprised a confirmation group. Mean step counts calculated over the 28-d period served as the criterion. Using the reliability group, intraclass correlations (ICC) were computed for the entire 4-wk period, for 3, 2, and 1 wk, and for different combinations of any 6, 5, 4, 3, and 2 d. The reliability of the recommended time frame was tested in the confirmation group using regression analysis.


RESULTS
In the reliability group, the ICC for any single given day was 0.41. All combinations including 6 d or more had ICC above 0.80. The inclusion of participant characteristics into a regression, alongside mean steps reported during 1 wk of monitoring, failed to strengthen the prediction. When tested in the confirmation group, there was a significant relationship between mean step counts calculated from the first week of monitoring and the criterion (adjusted R2 = 0.91, P< 0.001).


CONCLUSIONS
It is recommended that researchers collect pedometer data over a 7-d period for a reliable estimate of monthly activity in adults. A 7-d period is recommended, as opposed to 6 d (where ICC > 0.80) because: 1) step counts are characteristically lower on a Sunday; thus, for a reliable estimate of habitual activity, Sunday activity should always be included; and 2) in the event of missing data (1 d), data collected on 6 d will remain sufficiently reliable to estimate mean monthly activity.
Clemes
Stacy A
SA
Department of Human Sciences, Loughborough University, Leicestershire, United Kingdom. S.A.Clemes@lboro.ac.uk
Griffiths
Paula L
PL
D000328:Adult; D004739:England; D015444:Exercise; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D015203:Reproducibility of Results; D012107:Research Design; D013997:Time Factors