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Valid physical activity assessment in epidemiological studies is essential to study associations with various health outcomes.
To validate the Web-based physical activity questionnaire Active-Q by comparing results of time spent at different physical activity levels with results from the GENEA accelerometer and to assess the reproducibility of Active-Q by comparing two admissions of the questionnaire.
A total of 148 men (aged 33 to 86 years) responded to Active-Q twice and wore the accelerometer during seven consecutive days on two occasions. Time spent on six different physical activity levels including sedentary, light (LPA), moderate (MPA), and vigorous (VPA) as well as additional combined categories of sedentary-to-light and moderate-to-vigorous (MVPA) physical activity was assessed. Validity of Active-Q was determined using Spearman correlation coefficients with 95% confidence intervals (CI) and the Bland-Altman method. Reproducibility was assessed using intraclass correlation coefficients (ICCs) comparing two admissions of the questionnaire.
The validity correlation coefficients were statistically significant for time spent at all activity levels; sedentary (
More moderate and vigorous activities and less light activities were reported in Active-Q compared to accelerometer measurements. Active-Q shows comparable validity and reproducibility to other physical activity questionnaires used today.
Physical activity is a modifiable lifestyle factor, and while high activity levels are associated with decreased risks of non communicable diseases [
During the past decade, the use of Web-based instead of paper questionnaires has simplified data collection and improved data quality in large epidemiological studies [
Using accelerometers, movement can be objectively quantified and activities performed at different activity levels (eg light, moderate or vigorous) can be assessed. The devices are commonly worn around the waist or wrist, but wrist worn accelerometers have been shown to increase wear compliance and may thus decrease selection bias due to burden on study participants [
Study participants were recruited from a large ongoing cohort study of men who underwent PSA (Prostate Specific Antigen) testing in Stockholm County, Sweden, from 2010 to 2012. All study participants enrolled in the cohort between March and May 2012 who had agreed to be contacted regarding additional studies, were eligible for and invited to participate in the VALTER study (VALidation against acceleromeTER).
In September 2012, 1348 men were emailed an invitation to participate in the VALTER study. Of these, 31 emails did not reach the recipient due to an invalid email address. Men who replied to the invitation were sent more detailed information about the study and were scheduled for an introductory meeting at Karolinska Institutet, Stockholm, Sweden. In total, 167 men agreed to participate. All participants were given both written and oral information about the study and signed an informed consent prior to participation.
The study design is shown in
Among the 167 men who agreed to participate, only participants with complete data from both questionnaire and accelerometer measurements were included in analysis. Participants were excluded due to drop out of the study (n=2) or due to erroneous accelerometer data from the first (n=3) or second (n=3) week of measurements. Further, men who reported to be left handed (n=11) were excluded from analysis as the accelerometer was worn on the left wrist. In total, data from 148 men were included in further analyses. As an incentive, all participating men received feedback from their accelerometer measurements approximately one month after the data collection was finished.
A subgroup of participants (n=22) partook in a calibration of the accelerometers. There were no differences in age, weight, height or BMI (body mass index) (
The study was approved by the Research Ethics Committee at Karolinska Institutet, Stockholm, Sweden.
Timeline showing participants' responses to the first and second Active-Q questionnaire and when the first and second GENEA accelerometers were worn.
Active-Q is a Web-based, interactive physical activity questionnaire assessing habitual activity in adults (see
All activities in Active-Q are linked to a corresponding MET value [
The GENEA accelerometer was developed by Unilever discover, UK and is manufactured and distributed by Activinsights Ltd., UK. It is a small (36 mm long x 30 mm wide x 12mm high, 16 gram) tri-axial accelerometer measuring vertical, anteroposterior and mediolateral movement at a rate of up to 80 Hz with a dynamic range of ±6g [
Using the same methods as Esliger et al. [
Equation of GENEA output per minute using the post processing software. K is the number of samples per second (K=40 in our study), and x_ij, y_ij, and z_ij is the acceleration along the three dimensions, respectively, at the j:th sample of the i:th second of the particular minute. g is set to 1.00 by default.
Using data from the calibration of the accelerometers (
Mean GENEA SVMgs (g·min) output for the five activities included in the calibration study.
Activity | MET Value | SVMgs Meana (SD) |
Sitting | 1.5 | 105.2 (77.5) |
Standing | 1.8 | 167.1 (146.3) |
Walking 3.2 km/h | 2.5 | 826.0 (236.1) |
Walking 4.8 km/h | 3.3 | 1353.3 (246.2) |
Walking 6.4 km/h | 5.0 | 1875.3 (438.4) |
a Mean values are based on output from a total of 44 GENEA accelerometers.
Scatter plot displaying MET-values of activities performed during the calibration (x-axis) and average GENEA-output in SVMgs (y-axis) for each specific activity, n=22 (44 measuring points).
Characteristics of study participants are presented as numbers and percentage, median or mean values with specified standard deviation (SD), total range and interquartile range (IQR). Differences between groups with regards to continuous and categorical variables were tested for using t-tests and chi-square tests, respectively.
Spearman correlation coefficients were used to assess the degree of association between time spent at sedentary, light, sedentary-to-light, moderate, vigorous or moderate-to-vigorous activity levels assessed with Active-Q and the accelerometers. Confidence intervals (CIs) for correlation coefficients were obtained using the bootstrap method [
For the reproducibility of Active-Q and GENEA, comparing results from the first and second measurements, intraclass correlation coefficients (ICCs) were computed using the ANOVA estimator. ICCs >70 and >90 were considered as moderate and strong, respectively, in line with the definitions used in a recent review of physical activity questionnaires [
Among the 148 men included in analyses, the mean age was 65.4 (SD 8.7) years and the mean BMI 25.7 (SD 2.9) kg/m2. Characteristics of study participants are presented in
Time spent at different activity levels estimated from the GENEA and Active-Q measurements are summarized in
Spearman correlation coefficients with 95% confidence intervals (95% CI) for time at different activity levels are shown in
When dividing study participants into quartiles of time spent in MPA, VPA and MVPA assessed with GENEA and Active-Q, 32%, 46% and 33%, respectively, of participants were classified into the same quartile using both methods while 71%, 77% and 75%, respectively, were classified into the same or adjacent quartile. Results from weighted kappa statistics between the methods showed modest agreement, κ=0.16 (
ICCs comparing the first and second measurements of GENEA and Active-Q, respectively, are shown in
Characteristics of study participants (n=148).
|
Mean (SD) | Median | Min-Max | IQRa |
Height, cm | 179.2 (6.4) | 179 | 165-198 | 175-183 |
Weight, kg | 82.5 (11.0) | 82 | 58-122 | 75-89 |
Age, years | 65.4 (8.7) | 66 | 33-86 | 61-71 |
BMI, kg/m2 | 25.7 (2.9) | 25.4 | 19.6-35.6 | 23.5-27.5 |
aInterquartile range
Results of time in minutes per day spent at light (LPA, <3 MET), moderate (MPA, 3-6 MET), vigorous (VPA, >6 MET), and moderate-to-vigorous (MVPA, ≥3 MET) physical activity levels assessed by GENEA and Active-Q (n=148).
|
Mean (SD) | Median | Min-Max | IQRa | |
|
|
|
|
|
|
|
Sedentary | 773 (234) | 834 | 43-1107 | 708-926 |
|
LPA | 617 (234) | 540 | 299-1340 | 468-664 |
|
Sedentary + LPA | 1390 (29) | 1393 | 1269-1437 | 1379-1408 |
|
MPA | 47 (27) | 46 | 3-165 | 30-59 |
|
VPA | 3 (6) | 0 | 0-27 | 0-2 |
|
MVPA | 50 (29) | 47 | 3-171 | 32-62 |
|
|
|
|
|
|
|
Sedentary | 804 (236) | 853 | 83-1135 | 741-974 |
|
LPA | 589 (234) | 533 | 268-1347 | 436-630 |
|
Sedentary + LPA | 1394 (31) | 1399 | 1240-1438 | 1379-1415 |
|
MPA | 44 (29) | 40 | 3-198 | 26-56 |
|
VPA | 3 (7) | 0 | 0-61 | 0-3 |
|
MVPA | 47 (31) | 42 | 3-201 | 26-62 |
|
|
|
|
|
|
|
Sedentary | 789 (186) | 817 | 107-1116 | 676-941 |
|
LPA | 603 (185) | 566 | 297-1286 | 463-696 |
|
Sedentary + LPA | 1392 (28) | 1393 | 1255-1437 | 1380-1409 |
|
MPA | 46 (27) | 44 | 3-182 | 31-56 |
|
VPA | 3 (6) | 1 | 0-43 | 0-3 |
|
MVPA | 48 (28) | 47 | 3-186 | 32-60 |
|
|
|
|
|
|
|
Sedentary | 611 (143) | 579 | 360-1291 | 523-691 |
|
LPA | 690 (172) | 708 | 83-1028 | 582-807 |
|
Sedentary + LPA | 1301 (123) | 1339 | 849-1440 | 1281-1382 |
|
MPA | 121 (120) | 84 | 0-555 | 51-135 |
|
VPA | 18 (26) | 6 | 0-130 | 0-29 |
|
MVPA | 139 (123) | 101 | 0-591 | 58-159 |
|
|
|
|
|
|
|
Sedentary | 601 (142) | 582 | 213-1351 | 516-683 |
|
LPA | 700 (191) | 737 | 6-1109 | 596-826 |
|
Sedentary + LPA | 1301 (139) | 1355 | 680-1428 | 1275-1390 |
|
MPA | 116 (123) | 69 | 0-557 | 41-148 |
|
VPA | 22 (42) | 9 | 0-289 | 0-29 |
|
MVPA | 139 (139) | 85 | 12-760 | 50-165 |
|
|
|
|
|
|
|
Sedentary | 606 (136) | 578 | 338-1321 | 513-578 |
|
LPA | 695 (166) | 716 | 73-1003 | 613-810 |
|
Sedentary + LPA | 1301 (120) | 1346 | 872-1425 | 1265-1383 |
|
MPA | 119 (112) | 72 | 11-527 | 72-160 |
|
VPA | 20 (31) | 10 | 0-176 | 0-29 |
|
MVPA | 139 (120) | 94 | 15-568 | 57-175 |
aInterquartile range
Spearman correlation coefficients between time at different intensity levels and total MET-h in the first Active-Q questionnaire and time and total SVMgs from GENEA measurements during 12 days (n=148) and Intraclass correlation coefficients between the two Active-Q questionniares administered and between the two weeks of GENEA measurements (n=148).
|
Spearman correlations | Intraclass correlations | ||||
|
Active-Q vs GENEA | Active-Q | GENEA | |||
|
|
(95% CI) |
|
(95% CI) |
|
(95% CI) |
Minutes/Day Sedentary | .19 | (0.04-0.34) | .80 | (0.74-0.86) | .25 | (0.10-0.41) |
Minutes/Day LPA | .15 | (0.00-0.31) | .66 | (0.57-0.75) | .25 | (0.10-0.41) |
Minutes/Day Sedentary + LPA | .35 | (0.19-0.51) | .67 | (0.58-0.76) | .78 | (0.71-0.84) |
Minutes/Day MPA | .27 | (0.12-0.42) | .69 | (0.60-0.77) | .76 | (0.70-0.83) |
Minutes/Day VPA | .54 | (0.42-0.67) | .51 | (0.39-0.63) | .77 | (0.71-0.84) |
Minutes/Day MVPA | .35 | (0.21-0.48) | .67 | (0.58-0.76) | .78 | (0.71-0.84) |
Bland-Altman plots illustrating differences in time spent sedentary, in light (LPA), sedentary-to-light, moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) physical activity assessed with Active-Q and GENEA (y-axis) relative to the mean of the two methods (x-axis). Each point represents one study participant (n=148).
Our results from comparisons of Active-Q and the GENEA accelerometer show that Active-Q provides valid estimates of moderate and vigorous intensity activity although more time being active was reported in the questionnaire than assessed by the accelerometer. Active-Q showed acceptable reproducibility when comparing two admissions of the questionnaire.
Compared to accelerometer measurements, time spent at moderate and vigorous activity levels was overestimated in Active-Q. Over-reporting of physical activity is often due to misreporting of frequency, intensity and/or duration of activities [
A commonly used physical activity questionnaire is the IPAQ (International Physical Activity Questionnaire) [
In addition to comparisons of validity with other existing questionnaires, it is important to remember the population for which the questionnaire is developed. Active-Q was originally developed for adults 18-45 years for use in a large cohort study [
Results from the Bland-Altman plots, reflecting absolute differences between Active-Q and the GENEA accelerometer, showed that the difference between Active-Q and GENEA increased with increasing time spent in MPA, VPA and MVPA, similar to what has been seen in other studies [
While our results show moderate reproducibility of Active-Q, few previous studies have reported test-retest reliability of time spent at different intensity levels, making comparisons difficult [
Although considered to be one of the best methods to objectively assess free living physical activity, accelerometers are not without limitations [
In addition to the points of discussion raised in previous paragraphs, the present study has several strengths and limitations worth mentioning. First, the large sample size and the high compliance among participating men are important strengths. With some exceptions, most previous validation studies summarized in the review by Helmerhorst et al. [
The present study shows that more moderate and vigorous time and fewer light activities are reported in Active-Q compared to the accelerometer measurements. Nevertheless, the questionnaire shows good ranking ability, and validity and reproducibility comparable to other physical activity questionnaires.
The Active-Q physical activity questionnaire.
body mass index
gravity estimator of normal everyday activity
intraclass correlation coefficient
International Physical Activity Questionnaire
International Physical Activity Questionnaire (Short Form)
light physical activity
metabolic equivalent task
metabolic equivalent task x hours reported for each specific activity
moderate physical activity
moderate and vigorous physical activity
prostate specific antigen
Recent Physical Activity Questionnaire
signal vector magnitude (gravity subtracted)
VALidation against acceleromeTER
vigorous physical activity
We thank the devoted study participants and Erica Björnström, Camilla Sjörs and Yanina Taynard for their invaluable help during data collection. The present study was founded by the Swedish Research Council for Health, Working Life and Welfare and the regional agreement on medical training and clinical research between Stockholm County Council and Karolinska Institutet.
The authors declare no conflicts of interest.