The Influence of Monitoring Interval on Data Measurement: An Analysis of Step Counts of University Students

Abstract

The pedometer is a widely used research tool for measuring the level and extent of physical activity (PA) within population subgroups. The sample used in this study was drawn from a population of university students to examine the influence of the monitoring interval and alternate starting days on step-count activity patterns. The study was part of a national project during 2008–2010. Eligible subjects (641) were selected from a sample of 906 university students. The students wore pedometers continuously for 7 days excluding time for sleep and personal hygiene. Steps per day were logged on record sheets by each student. Data gathering spanned an entire week, and the results were sorted by alternate starting days, by activity for an entire week, by activity for only the weekdays of the one-week monitoring interval and for the two-day weekend. The statistical analysis included ANOVA, intra-class correlation (ICC) analysis, and regression analysis. The ICC analysis suggested that monitoring starting on Monday (ICC = 0.71; 95%CI (0.61–0.79)), Tuesday (ICC = 0.67; 95%CI (0.59–0.75)) or Thursday (ICC = 0.68; 95%CI (0.55–0.79)) improved reliability. The results of regression analysis also indicated that any starting day except Sunday is satisfactory as long as a minimum of four days of monitoring are used.

Relationship between Czech Parent and Child Pedometer-assessed Weekday and Weekend Physical Activity and Screen Time

“…The data analysis included only records when the pedometer was worn for at least 10 h a day during at least 4 weekdays/school days and 2 weekend days. Monitoring of at least 4 weekdays and 2 weekend days is suitable for predicting weekly physical activity in children and young adults (31,32). Incomplete records of daily step counts or an omission of the age, body height and body weight variables constituted a reason for excluding 5.37% (n = 20) of daughters, 6.04% (n = 21) of sons, 1.97% (n = 7) of mothers, and 4.3% (n = 13) of fathers ( Table 1).…”

Statistical methods to model and evaluate physical activity programs, using step counts: A systematic review

“…Similarly maximum oxygen usage during high intensity exercise was predicted using a linear regression model based on step counts and other related body composition measures [ 87 ]. Other studies examined the influence of monitoring interval and alternative starting days for step count interventions in order to reliably assess and predict the participants’ physical activity [ 31 , 88 ]. ANOVA, inter class correlation and linear regression methods were used to model the collected data.…”

“…ANOVA, inter class correlation and linear regression methods were used to model the collected data. One study reported that a minimum of four days need to be monitored starting from Sunday [ 31 ]. Another study [ 88 ] also claimed that four days were required for a pedometer based intervention, with different monitoring periods for different step count collecting devices.…”

How Many Days are Necessary to Represent Typical Daily Leg Movement Behavior for Infants at Risk of Developmental Disabilities?

“…In the previous adult literature, at-risk groups have less day-to-day variability and require less days to represent their typical physical activity level than healthy groups. For example, 3–5 days (using an accelerometer) or 4–7 days (using a pedometer) are needed to measure the typical physical activity level for a healthy adult group [ 45 , 46 , 47 , 48 , 49 ]. A group of adults with a spinal cord injury only needed 2 days of activity monitoring to sufficiently represent their daily behavior [ 50 ].…”