This review examined the literature on physical activity measurement among individuals with disabilities utilizing Yun and Ulrich’s (2002) view on measurement validity. Specific inclusion criteria were identified. The search produced 115 articles; however, only 28 met all specified criteria. Findings revealed that self-reports and accelerometers were the most common approaches to measuring physical activity, and individuals with orthopedic impairments, those with mental retardation, and those with other health impairments received the most attention. Of the 28 articles, 17 (61%) reported validity and reliability evidence. Among those studies reporting validity, criterion-related evidence was the most common; however, a number of methodological limitations relative to validity were observed. Given the importance of using multiple physical activity measures, only five (18%) studies reported the use of multiple measures. Findings are discussed relative to conducting future physical activity research on persons with disabilities.
Carlos M. Cervantes and David L. Porretta
Nurdiana Zainol Abidin, Wendy J. Brown, Bronwyn Clark, Ahmad Munir Che Muhamed, and Rabindarjeet Singh
We evaluated feasibility of physical activity measurement by accelerometry among older Malay adults living in semi-rural areas in Malaysia. Results showed that 95% of 146 participants (aged [SD] 67.6 [6.4] years) were compliant in wearing the accelerometer for at least five days. Fifteen participants were asked for re-wear the accelerometer because they did not have enough valid days during the first assessment. Participants wore the accelerometer an average of 15.3 hr in a 24-hr day, with 6.5 (1.2) valid wear days. No significant difference in valid wear day and time was found between men and women. Participants who are single provide more valid wear days compared with married participants (p < .05), and participants with higher levels of education provide longer periods of accelerometer wearing hours (p < .01). Eighty-seven percent of participants reported ‘no issues’ with wearing the meter. This study suggests that accelerometry is a feasible method to assess the physical activity level among older Malay adults living in semi-rural areas.
Sarah J. Parker, Scott J. Strath, and Ann M. Swartz
This study examined the relationship between physical activity (PA) and mental health among older adults as measured by objective and subjective PA-assessment instruments. Pedometers (PED), accelerometers (ACC), and the Physical Activity Scale for the Elderly (PASE) were administered to measure 1 week of PA among 84 adults age 55–87 (mean = 71) years. General mental health was measured using the Positive and Negative Affect Scale (PANAS) and the Satisfaction With Life Scale (SWL). Linear regressions revealed that PA estimated by PED significantly predicted 18.1%, 8.3%, and 12.3% of variance in SWL and positive and negative affect, respectively, whereas PA estimated by the PASE did not predict any mental health variables. Results from ACC data were mixed. Hotelling–William tests between correlation coefficients revealed that the relationship between PED and SWL was significantly stronger than the relationship between PASE and SWL. Relationships between PA and mental health might depend on the PA measure used.
Susana Vale, Rute Santos, Pedro Silva, Luísa Soares-Miranda, and Jorge Mota
The purpose of this study was twofold: first to document the gender differences in Moderate to Vigorous Physical Activity (MVPA) according to two epoch systems (5 vs. 60 s) in preschoolers, and, second to document the differences in physical activity (PA) patterns according to two different epoch choices. The sample comprised 59 preschoolers (31 girls) aged 2–5 years old. PA was assessed by accelerometer during school hours. The time spent in MVPA was significantly higher (p < .001) when a 5-s epoch was considered compared to the 60-s epoch, regardless gender. Further, it was found a difference of ?17 min difference between the 2 epoch systems for MVPA. Different epoch times might affect the time spent in MVPA among preschool children.
Ruth Miller and Wendy Brown
The aims of this study were to investigate the relationships and agreement between average number of steps taken per day and compliance with Australian physical activity guidelines in a sample of working Australian adults.
One hundred-eighty-five adults wore a pedometer and recorded the number of steps taken each day for 7 d. On the 8th day, they completed a self-report survey that asked about frequency and duration of different activities during the previous week.
The average number of steps per day was 8543 (standard deviation = 2466) for men (n = 74) and 9093 (2926) for women (n = 111; no significant difference). Just over half the men (53%) and 45% of the women met the current national physical activity guidelines (no significant difference). Average number of steps per day was higher in those who met the guidelines [9547 (2655), n = 89] than in those who did not [8220 (2702), n = 96; P < 0.0001]. In general, the level of agreement between the 2 measures was only moderate. There was, however, better agreement between the 2 measures in women (Spearman’s ρ = 0.35; % agreement 67.5%; κ = 0.33, P < 0.0001) than in men (ρ = 0.21; % agreement 52.7%; κ = 0.08, NS).
This study provides an indication of average daily step counts among adults who do and do not meet physical activity guidelines and some evidence on which to base appropriate “step targets” that might be recommended for health benefits for adults.
Kate Lyden, Natalia Petruski, Stephanie Mix, John Staudenmayer, and Patty Freedson
Physical activity and sedentary behavior measurement tools need to be validated in free-living settings. Direct observation (DO) may be an appropriate criterion for these studies. However, it is not known if trained observers can correctly judge the absolute intensity of free-living activities.
To compare DO estimates of total MET-hours and time in activity intensity categories to a criterion measure from indirect calorimetry (IC).
Fifteen participants were directly observed on three separate days for two hours each day. During this time participants wore an Oxycon Mobile indirect calorimeter and performed any activity of their choice within the reception area of the wireless metabolic equipment. Participants were provided with a desk for sedentary activities (writing, reading, computer use) and had access to exercise equipment (treadmill, bike).
DO accurately and precisely estimated MET-hours [% bias (95% CI) = –12.7% (–16.4, –7.3), ICC = 0.98], time in low intensity activity [% bias (95% CI) = 2.1% (1.1, 3.2), ICC = 1.00] and time in moderate to vigorous intensity activity [% bias (95% CI) –4.9% (–7.4, –2.5), ICC = 1.00].
This study provides evidence that DO can be used as a criterion measure of absolute intensity in free-living validation studies.
Steven P. Hooker, Janet Fulton, and Lanay M. Mudd
Hotaka Maeda, Chris C. Cho, Young Cho, and Scott J. Strath
When processing free-living accelerometer data, invalid days are typically discarded, potentially resulting in loss of valuable information. The purpose of this semi-simulation study was to compare the accuracy of the conventional method of calculating free-living physical activity (PA) in average counts per day to three methods that can utilize all accelerometer data, including the invalid days (<10 hours per day). National Health and Nutrition Examination Survey data from 2003 to 2006 were used. Age and sample size were included as study conditions. Artificial missing data were created among the participants with 7 days of valid accelerometer data by imposing missing data patterns from a donor matched on age and gender. Results showed that the conventional method of calculating PA levels discarded 26.0% to 28.6% of the data. In most conditions, the within-minute average and day-level imputation method were able to recover the artificially deleted accelerometer counts better than the conventional method. As an exception, the within-minute average method overestimated PA among young people with ≥3 valid days. In conclusion, practitioners are suggested to use the within-minute average method for adults ≥18 years of age, and the day-level imputation method for children and teenagers. To note, the day-level imputation method may be unstable for sample sizes of <50. These methods are particularly useful when the number of valid days is ≤3. Potentially, these methods can allow some participants with insufficient number of valid days to be included in the final analysis.
Craig Donnachie, Kate Hunt, Nanette Mutrie, Jason M.R. Gill, and Paul Kelly
.53, p = 0.011, median difference = 56 MET-minutes/day), and vigorous MET-minutes ( Z = –2.58, p = 0.010, median difference = 80 MET-minutes/day). Table 2 Device-Based (activPAL3 ™ ) and Self-Report (IPAQ) Physical Activity Measurements at T0 and T1 and Changes Between T0 and T1 ( n = 30) T0 T1
Aaron Beighle and Robert P. Pangrazi
The primary purpose of this study was to describe the association between activity time and step counts in children.
Subjects were 590 students (334 girls, 256 boys) with each gender having a mean age of 9.2 ± 1.8 y. All subjects wore the Walk4Life 2505 pedometer for four consecutive weekdays. This pedometer simultaneously measures both step counts and activity time.
Boys accumulated significantly more minutes of activity time/day (140.9 ± 39.6 vs. 126.3 ± 38.1), steps/day (13,348 ± 4131 vs. 11,702 ± 3923), and steps per min (93.99 ± 5.8 vs. 91.85 ± 5.8) than girls (P < 0.001) Steps/day was a significant predictor of activity time/day (P < 0.0001).
Boys accumulate more steps per day and more activity time per day than girls. There is a strong association between steps per day and activity time in children. Daily steps per minute as a measure of free living physical activity in children is explored