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Increased use of the Internet provides new opportunities for collecting data in large studies. The aim of our new Web-based questionnaire, Active-Q, is to assess total physical activity and inactivity in adults. Active-Q assesses habitual activity during the past year via questions in four different domains: (1) daily occupation, (2) transportation to and from daily occupation, (3) leisure time activities, and (4) sporting activities.
The objective of our study is to validate Active-Q’s energy expenditure estimates using the doubly labeled water (DLW) method, and to assess the reproducibility of Active-Q by comparing the results of the questionnaire completed by the same group on two occasions.
The validity and reproducibility of Active-Q were assessed in a group of 37 individuals, aged 20 to 65 years. Active-Q was distributed via email to the participants. The total energy expenditure of the participants was assessed using DLW for 11 consecutive days.
The median time to complete Active-Q was 6.1 minutes. The majority of participants (27/37, 73%) reported that the questionnaire was “easy” or “very easy” to answer. On average, Active-Q overestimated the total daily energy expenditure by 440 kJ compared with the DLW. The Spearman correlation between the two methods was r = 0.52 (P < .001). The intraclass correlation coefficient for total energy expenditure between the results of Active-Q completed on two occasions was 0.83 (95% CI 0.73-0.93).
Active-Q is a valid and reproducible method of assessing total energy expenditure. It is also a user-friendly method and suitable for Web-based data collection in large epidemiological studies.
Increased use of the Internet over the past decade provides new opportunities to use Web-based questionnaires in epidemiological studies. Compared to traditional paper-based questionnaires, Web-based alternatives may simplify data collection and improve the quality of data [
At present, there are few physical activity questionnaires available specifically developed for the Web. To the best of our knowledge, only one Web-based questionnaire (that assessed lifetime physical activity) has been validated and showed acceptable results [
The primary aim of this study was to test the validity of Active-Q against the doubly labeled water (DLW) method, the criterion standard for measuring energy expenditure [
Study participants of both sexes, aged 20 to 65 years, were recruited in April of 2009 through public advertisements (including advertisements on the campuses of three universities) around Stockholm, Sweden. Participants were required to have an email address and access to the Internet. Exclusion criteria were any form of weight alteration diet, pregnancy, or having given birth during the ten months prior to the start of the study. Participants were provided with written and verbal information about the study. All participants gave their written informed consent prior to entering the study.
In total, 40 individuals were recruited. Data from three participants were excluded from the analysis because of illness during data collection, incomplete data from the first Active-Q questionnaire (ie, < 1 hour of leisure time activities per day reported), and unreliable DLW data, respectively. After exclusions, data from 37 participants remained for analysis.
The study was approved by the Research Ethics Committee at the Karolinska Institutet, Stockholm, Sweden.
Timeline of study showing days that participants took doubly labeled water (DLW), provided urine samples, took the first questionnaire (Active-Q-I), and the second questionnaire (Active-Q-II).
Active-Q is a Web-based questionnaire designed to assess physical activity and inactivity in adults older than 18 years. Respondents are asked to report their habitual activity during the past year. Active-Q covers four different domains: (1) daily occupation, (2) transportation to and from daily occupation, (3) leisure time activities, and (4) regular sporting activities (see
In total, Active-Q includes 35 questions with all activities linked to a corresponding Metabolic Equivalent Task (MET) value [
Energy expenditure (EE) was estimated based on the assumption that 1 MET equals 1 kcal ∙ kg-1 ∙ h-1 [
EEactivity (kJ/day) = METactivity ∙ Weight (kg) ∙ Durationactivity (h/d) ∙ 4.184
Total energy expenditure was expressed in terms of the crude total energy expenditure and the total energy expenditure per 24 hours. The crude total energy expenditure was obtained by summing the contributions of energy from each activity in Active-Q. The total energy expenditure over a 24-hour period was calculated by adding eight hours of sleep to the crude results from Active-Q. If the resulting time differed from 24 hours, time was added or subtracted to obtain the adjusted total energy expenditure per 24 hours. A MET value of 2.0 was assumed for the time added and subtracted [
Screenshot of Active-Q screening question regarding mode of transportation to and from daily activities.
Screenshot of follow-up question for activities selected in screening question regarding transportation showing an example of possible answers.
Questions included in Active-Qa and corresponding MET values.
Activity category | MET value | |
|
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Mostly sitting | 1.5 | |
A combination of sitting and standing up | 2.3 | |
Mostly standing up | 3.0 | |
Some physical activity | 4.5 | |
Heavy manual labor | 6.0 | |
|
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Walking | 4.0 | |
Bicycling | 4.0 | |
By motorcycle or scooter | 2.5 | |
By car or taxi | 1.0 | |
By bus, train, subway, or boat | 1.0 | |
|
||
Watching TV/DVDs | 1.0 | |
Using the computer | 1.0 | |
Sitting listening to music, sewing, etc | 1.0 | |
Playing a musical instrument or active computer games | 2.0 | |
Doing household chores | 3.0 | |
Shopping or other errands | 2.3 | |
Dancing | 3.0 | |
Walking | 3.4 | |
Bicycling | 8.0 | |
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Aerobics | 6.5 | |
Weight lifting | 6.0 | |
Jogging or running | 8.0 | |
Athletics | 6.0 | |
Spinning | 8.5 | |
Swimming | 6.0 | |
Soccer, basketball, volleyball, or floorball (floor hockey) | 6.0 | |
Golf | 4.5 | |
Dance class | 4.5 | |
Horseback riding | 4.0 | |
Ice skating, ice hockey, or bandy | 7.0 | |
Skiing (downhill or cross country) | 7.0 | |
Martial arts | 10.0 | |
Boxing or wrestling | 6.0 | |
Tennis, badminton, or squash | 7.0 | |
Table tennis | 4.0 | |
Rowing, canoeing, surfing, or sailing | 3.0 | |
Motor sports | 4.0 | |
Rock climbing | 8.0 | |
Other | 2.5 |
a All domain activities (ie, daily occupation, transportation, leisure time, and sporting activities), including frequency and duration, were assessed via an initial screening questionnaire.
b Participants ranked their overall effort in this category on a scale from 1 to 5.
Doubly labeled water was used as the criterion measure of total energy expenditure [
The principles for the slightly modified analyses of the isotopic enrichment in the samples have been described in detail in previous studies [
Measurements of the18O/16O ratios were made using an AP2003 continuous-flow isotope ratio mass spectrometer (Analytical Precision Ltd, Northwich, Cheshire, UK). Urine samples of 0.5 ml were placed in 10 ml Vacutainers (Labco Ltd, High Wycombe, UK), flush-filled with 5% CO2 in nitrogen and then equilibrated on blood tube rotators overnight at room temperature before analysis. In all cases, analytical standards prepared in-house and traceable to the international standards, Vienna Standard Mean Ocean Water (VSMOW) and Standard Light Arctic Precipitation (SLAP), were included in each batch of samples analyzed.
Total energy expenditure was calculated as described by Schoeller et al [
Descriptive statistics were used to present the characteristics of the participants. Results are reported as mean values and standard deviations (SD), with the exception of time to respond to the questionnaire, which is presented as the median response time, and results of user-friendliness, which is presented in absolute numbers. For categorical variables or variables with a skewed distribution, Fisher’s exact test was performed to assess potential differences between men and women, and participants < 30 and ≥ 30 years of age. For those continuous variables typically normally distributed (eg, height, weight, and BMI),
The degree of association between the total energy expenditure obtained from Active-Q-I, both crude and adjusted to reflect a 24-hour day, and the DLW method, was assessed using Spearman correlation coefficients. Because Spearman correlation coefficients do not detect systematic differences between the methods, we used the Bland-Altman technique [
The median time required to fill out the Active-Q questionnaire on the first occasion was 6 minutes and 6 seconds. On average, the activities reported corresponded to 11 hours and 24 minutes of a typical day (excluding time spent sleeping). In the evaluation of the user-friendliness of the questionnaire, the majority of respondents (27/37, 73%) graded the questionnaire as “easy” or “very easy” to answer. Respondents were also asked to give the questionnaire an overall grade on a scale from 1 (worst) to 5 (best). The majority of respondents (21/37, 57%) graded the questionnaire a 4. An equal number of participants (7/37, 19%), graded the questionnaire a 3 or a 5. The remainder of participants (2/37, 5%) gave the questionnaire a 2. No respondents gave the questionnaire a 1, the worst possible grade. The mean overall grade for Active-Q-I was 3.9 ±0.8. Participants ≥ 30 years graded the questionnaire higher than younger participants (
The mean total daily energy expenditure measured with DLW was 11,229 kJ (SD 2256), while the mean energy expenditure from Active-Q-I and Active-Q-II, adjusted to reflect a 24-hour period, was 11,667 kJ (SD 3212) and 11,529 kJ (SD 2758), respectively. The mean crude energy expenditure assessed with Active-Q-I was 7008 kJ (SD 3854). The crude energy expenditure for each domain of Active-Q-I was 2971 kJ (SD 1736) for daily occupation, 434 kJ (SD 388) for transportation, 2243 kJ (SD 1550) for leisure time activities, and 1360 kJ (SD 3044) for regular sporting activities. The mean crude energy expenditure from Active-Q-II was 6439 kJ (SD 2614). The crude energy expenditure for each domain of Active-Q-II was 3005 kJ (SD 1537) for daily occupation, 365 kJ (SD 296) for transportation, 2254 kJ (SD 1880) for leisure time activities, and 815 kJ (SD 761) for regular sporting activities.
The Spearman correlation coefficient between the crude total daily energy expenditure assessed with Active-Q-I and DLW was
The intraclass correlation coefficient for the crude total energy expenditure assessed from the questionnaire on two occasions was 0.66 (95% CI 0.47-0.84). After adjustments to a 24-hour day, the value increased to 0.83 (95% CI 0.73-0.93).
Bland-Altman plot illustrating the difference in total daily energy expenditure (TEE) between Active-Q-I (adjusted to reflect a 24-hour day) and the DLW method. The absolute difference in TEE between Active-Q-I and DLW is plotted on the y-axis and the mean of the two assessments on the x-axis. Each data point represents one participant (n= 37).
Baseline characteristics of the study population (n = 37).
n | (%) | |
|
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Female | 30 | (81) |
Male | 7 | (19) |
|
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< 30 | 22 | (59) |
30-39 | 5 | (14) |
40-49 | 5 | (14) |
50-59 | 4 | (11) |
> 60 | 1 | (3) |
|
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< 20 | 3 | (8) |
20-25 | 28 | (76) |
> 25 | 6 | (16) |
|
||
9-12 | 7 | (19) |
> 12 | 30 | (81) |
|
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Current | 2 | (5) |
Previous | 8 | (22) |
Never | 25 | (68) |
|
||
Current | 4 | (11) |
Previous | 6 | (16) |
Never | 26 | (70) |
|
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< 1 | 25 | (68) |
1-3 | 10 | (27) |
≥ 3 | 2 | (5) |
|
||
< 1 | 23 | (62) |
1-3 | 8 | (22) |
≥ 3 | 6 | (16) |
|
||
0 | 5 | (14) |
< 1 | 26 | (70) |
1-3 | 5 | (14) |
≥ 3 | 1 | (3) |
a Percentages do not equal 100 because of missing data
b Reported in Active-Q-I
c During leisure time
The results of this study demonstrate that Active-Q is a user-friendly questionnaire that provides valid and reproducible estimates of total energy expenditure when compared with objective DLW measurements, the criterion standard [
The validity and reproducibility of many paper-based physical activity questionnaires in use today are low [
Important factors in making a questionnaire user-friendly are the length and the level of details in a questionnaire, plus the way in which questions are structured and the order in which they are presented [
Today, more than 90% of the population in Sweden between 16 and 74 years of age have access to the Internet at home [
Among Swedish individuals between 16 and 44 years of age, over 97% reported to be frequent users of the Internet compared to 90% for individuals between 45 and 54 years, and 70% for individuals between 55 and 74 years [
Ideally, in validation studies, the reference method should reflect the same period of time as the new method being validated. However, habitual physical activity was assessed over a one-year period with Active-Q, while that measured with the DLW method reflects physical activity over 11 days. Repeated reference measures of DLW over a longer period of time would have been preferable, but this was neither practical nor possible in our study setting. Another drawback of this study is that we were only able to validate measures of total energy expenditure. Because the DLW method does not discriminate between different levels of intensity in activity, we were not able to validate Active-Q in this respect. Since different aspects of activity may affect health-related outcomes differently, the ability of Active-Q to accurately assess this needs to be validated in future studies using, for example, accelerometers.
When estimating the total daily energy expenditure with Active-Q, we assumed that all participants slept for eight hours [
The use of published MET values [
While the point estimate of the intraclass correlation for the adjusted total energy expenditure assessed with Active-Q is high, the point estimate for the assessed crude total energy expenditure is lower, and the confidence intervals around both estimates are rather wide. The wide confidence intervals, and the rather low point estimate obtained for the crude total energy expenditure, might be explained by our small sample size and sampling variability. To obtain more certain measures of reproducibility, we need to conduct a larger study to assess reproducibility of both assessments of total energy expenditure, as well as energy expenditure within each individual domain of Active-Q.
Our study population was recruited from the Stockholm area, including the campuses of three universities, and the participants were young and predominantly female. This may limit the generalizability of our results. The overall level of education among the participants was high, with more than 80% having an education longer than 12 years, compared with 36% in the general Swedish population aged 16-64 years [
To the best of our knowledge, Active-Q is one of the first validated physical activity questionnaires specifically designed for Web-based use. Despite the limitations mentioned previously, we believe Active-Q to be a good assessment method in studies collecting Web-based data. Active-Q is currently in use in three large ongoing cohort studies in Sweden, aimed at recruiting hundreds of thousands of people [
An increasing number of studies are relying on the collection of data via the Web, and there is a need for valid Web-based methods of assessing physical activity. We have demonstrated that Active-Q is a valid method for estimating total energy expenditure. Furthermore, Active-Q is also a reproducible and user-friendly method. We conclude that Active-Q is a suitable method for collecting Web-based data on physical activity and inactivity in large epidemiological studies.
The Active-Q Physical Activity Questionnniare.
body mass index
doubly labeled water
energy expenditure
metabolic equivalent task
standard light arctic precipitation
Vienna standard mean ocean water
This work was supported by grants from the Swedish Cancer Foundation as well as grants to LifeGene from AFA Insurance, Torsten and Ragnar Söderbergs Foundation, Karolinska Institutet, Stockholm's County Council, and the Swedish Research Council.
The authors thank MRC Human Nutrition Research for their cooperation and performing the DLW analyses, in particular Marilena Leventi for her help in analyzing samples and Dr. Les Bluck for his help with the analysis and interpretation of the results.
SEB, YTL, SEC, EM, and KB contributed significantly to the concept and design of the study, and SEB, SEC, EM, AW, and KB participated in the data acquisition. AW conducted doubly labeled water analyses while SEB conducted data analyses (in collaboration with AS who provided significant statistical expertise). SEB, YTL, AW, AS, and KB contributed to the interpretation of results. SEB together with YTL and KB prepared the manuscript, which was subsequently reviewed by SEC, EM, AW, and AS. All authors have approved the final manuscript.