Journal of Physical Activity and Health, 2015, 12, 116 -123 http://dx.doi.org/10.1123/jpah.2013-0013 © 2015 Human Kinetics, Inc.
Official Journal of ISPAH www.JPAH-Journal.com ORIGINAL RESEARCH
Validity and Reliability of Question 8 of the Paffenbarger Physical Activity Questionnaire Among Healthy Adults Kathleen Simpson, Beth Parker, Jeffrey Capizzi, Paul Thompson, Priscilla Clarkson, Patty Freedson, and Linda Shannon Pescatello Background: Little information exists regarding the psychometric properties of question 8 (Q8) of the Paffenbarger Physical Activity Questionnaire (PPAQ) to assess exercise. Thus, we conducted 2 studies to assess the validity and test–retest reliability of Q8 among adults. Methods: Study 1 participants (n = 419) were 44.1 ± 16.1 years of age. Validity was determined by comparing self-reported hr∙d–1 in sedentary, light, moderate, and vigorous intensity physical activity (PA) and MET-hr·wk–1 on Q8 at baseline to accelerometer and health/fitness measurements using Spearman rank-order correlations. Study 2 participants (n = 217) were 44.7 ± 16.3 years of age and completed Q8 at baseline, 3 months, and 6 months. Test–retest reliability was determined using repeated measures analysis of covariance, intraclass correlations (ICCs), and standard error of the measurement (SEM). Results: Q8 displayed good criterion validity compared with accelerometer measurements (r = .102 to .200, P < .05) and predictive validity compared with health/fitness measurements (r = –.272 to .203, P < .05). No differences were observed in self-reported hr·d–1 in any of the PA categories at baseline, 3 months, and 6 months (ICC: 0.49 to 0.68; SEM: 1.0 to 2.0; P > .05), indicating good reliability. Conclusion: Q8 demonstrates adequate criterion validity, acceptable predictive validity, and satisfactory test–retest reliability and can be used in conjunction with other components of the PPAQ to provide a complete representation of exercise. Keywords: Actical accelerometer, body composition, Harvard Alumni Questionnaire, health, heart rate, maximum oxygen consumption, physical fitness Habitual participation in physical activity (PA) has many physical and mental health benefits for people of all ages.1 A physically active lifestyle is associated with a reduced risk of developing several chronic diseases and health conditions such as cardiovascular disease, type 2 diabetes mellitus, hypertension, dyslipidemia, obesity, and several forms of cancer.1–4 However, the dose-response relationships that exist among chronic disease risk and exercise participation are complex and not yet fully understood. Accurate quantification of PA habits is of utmost importance to increase the understanding of these relationships and ultimately devise even more effective PA interventions.5 Self-report questionnaires are currently one of the most practical and widely used methods for assessing PA because they are inexpensive, quick, and relatively easy to administer to large groups of people.6–10 However, using questionnaires can result in a greater misclassification of PA habits than objective PA measures because of difficulties with recalling PA, misunderstanding of questions, and social desirability biases.9,11 Additionally, questionnaires often differ in terms of the mode and length of administration and scoring methodology, all of which can have an impact on how effective and often the questionnaire is used.12
Simpson ([email protected]) is with the Dept of Kinesiology, University of Connecticut, Storrs, CT. Parker, Capizzi, and Thompson are with the Dept of Preventive Cardiology, Hartford Hospital, Hartford, CT. Clarkson and Freedson are with the Dept of Kinesiology, University of Massachusetts, Amherst, MA. Pescatello is with the School of Allied Health, University of Connecticut, Storrs, CT. 116
The Paffenbarger Physical Activity Questionnaire (PPAQ) is a short questionnaire designed to measure participation in leisure time PA among adults 18 years of age and above.13 The most recent version of the PPAQ consists of 8 questions. The first 4 questions on this version of the PPAQ are used to compute a PA index that provides an estimate of energy expenditure (MET-min·wk–1).14 Question 5 (Q5) asks subjects to choose which of these statements expresses their view: “I take enough exercise to keep healthy,” “I ought to take more exercise,” or “Don’t know.” Question 6 (Q6) of the PPAQ asks subjects to report the number of times per week they engage in PA long enough to work up a sweat, get their heart thumping or become out of breath. Question 7 (Q7) asks subjects to rate their level of exertion during PA on a scale of 0.5 to 10 with 0.5 being very weak and 10 being maximal. Both the PA index and Q6 of the PPAQ have been validated against measures of cardiorespiratory fitness (CRF) (eg, VO2max), accelerometers (eg, the caltrac accelerometer), daily PA logs, and various health outcomes (eg, heart rate [HR], body mass index [BMI], and lipids).7,8,15,16 These validation studies show the PA index and Q6 of the PPAQ are good measures of participation in moderate and vigorous intensity PA with correlation coefficients ranging from r = .13 to .69.7,8,15,16 Question 8 (Q8) of the newest version of the PPAQ asks respondents to report the time (hr·d–1) they spend on a typical day during the week and weekend sleeping and reclining, participating in sitting activities, and engaging in light, moderate, and vigorous intensity PA. Therefore, PPAQ Q8 not only provides researchers and clinicians with information regarding the duration of moderate and vigorous intensity PA people perform, but also can assess the duration of sedentary and light intensity PA performed. In addition,
Question 8 of the Paffenbarger Questionnaire 117
PPAQ Q8 can separately assess the duration of PA on weekdays and weekend days. Two studies have examined the validity of the PPAQ Q8.3,17 However, these studies examined subject populations consisting of postmenopausal women and individuals of low socioeconomic status, so the results may not be generalizable to the general population. In addition, to the best of our knowledge, no study has examined the test–retest reliability of Q8. Thus, the purpose of this study was to examine the criterion and predictive validity of the PPAQ Q8 compared with accelerometer and health/fitness measurements, as well as the test–retest reliability of the PPAQ Q8 in a sample of healthy men and women across the life span.
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Methods This study investigated the validity and test–retest reliability of the PPAQ Q8 using data from a larger U.S. National Institutes of Health–funded study entitled The Effects of Statins on Muscle Performance (STOMP; 1R01HL081893-01A2). STOMP was conducted by researchers at Hartford Hospital, Hartford, CT; the University of Massachusetts, Amherst, MA; and the University of Connecticut, Storrs, CT. The purpose of STOMP was to examine the incidence of statin-induced muscle symptoms or myalgia, as well as the effects of statins on exercise performance among healthy men and women taking either 80 mg of atorvastatin (Lipitor) or placebo daily for 6 months. The institutional review boards at all 3 study sites approved the experimental design of STOMP.18,19 The STOMP study consisted of 6 study visits over approximately a 6-month period of time. Study visits 1, 2, and 3 (V1, V2, and V3) occurred within approximately 1 week and consisted of strength and aerobic fitness testing, blood work, and questionnaires. Following V3, subjects were randomly assigned to receive either 80 mg of atorvastatin or a placebo. STOMP visit 4 (V4) took place 3 months following V3 and consisted of blood work and questionnaires. STOMP visits 5 (V5) and 6 (V6) took place 6 months following V3 and again consisted of strength and aerobic fitness testing, blood work, and questionnaires.18,19 In this STOMP substudy, subject responses on the PPAQ Q8 and health/fitness measurements obtained before atorvastatin or placebo were dispensed, that is, during V1, V2, and V3 of STOMP, were used to determine the validity of the PPAQ Q8. In addition, for subjects assigned to receive the placebo, responses on the PPAQ Q8 during V1, V4, and V5 were used to determine the test–retest reliability of the PPAQ Q8. Subjects for STOMP were recruited via study flyers, e-mail announcements, and radio/newspaper advertisements. Volunteers in STOMP included approximately equal numbers of men and women in the following age groups: 20 to 39 years old, 40 to 54 years old, and 55+ years old. Before participating, all participants signed an informed-consent document. Participants were excluded if they were presently being treated or had previously been treated with cholesterol-lowering medications or had been diagnosed with diabetes, hyper- or hypothyroidism, or any heart condition that required medication or a restriction of PA. Anyone unable to exercise vigorously on a treadmill or who had hepatic disease, renal disease, or occult cardiac ischemia documented during a physician-supervised treadmill test during STOMP V1 was also excluded from the study. Individuals using hypertensive medications were included if they had been on these medications for at least 3 months and their blood pressure (BP) was stable ( 6 METs). Physical Activity Measurements—Actical Accelerometer.
Subjects wore an Actical accelerometer (Mini Mitter Company, Bend, OR) securely fastened to their hip on the side of the dominant hand between V2 and V3. The device was set to record PA in 25-second epochs and was initialized to begin recording data immediately. To be included in the subsequent analysis, participants were required to wear the Actical for at least 4 consecutive days (96 h; 2 d during the week and 2 d over the weekend) and were asked to remove the Actical only when they were swimming, bathing, showering, or sleeping. Subjects were asked to inform the research assistant if they removed the Actical to go swimming at any point during the 4 days they were wearing the device. A valid day was defined as 8 consecutive hours of wear time. Data from the Actical were downloaded from the device using the Actical software developed by the Actical company (Mini Mitter Company, Bend, OR). The data were then exported into Microsoft Excel for further processing and analysis. Variables obtained from the Actical were time spent (min·d–1) in sedentary, light, moderate, and vigorous intensity PA, steps·day–1, activity counts·day–1, and energy expenditure (kcal·d–1). Cut points (in units of activity energy expenditure) used to define sedentary, light (< 3 METs), moderate (≥ 3 to < 6 METs), and vigorous (≥ 6 METs) intensity PA were as follows: sedentary and light intensity < 0.0310 kcal·kg–1·min–1; 0.0310 kcal·kg–1·min–1 £ moderate intensity < 0.0832 kcal·kg–1·min–1; and vigorous ≥ 0.0832 kcal·kg–1·min–1.20 Health/Fitness Measurements—Blood Lipid-Lipoprotein Profile. During V1, fasting blood samples were collected from the
antecubital space on the arm of each subject. These blood samples were allowed to sit at room temperature for at least 10 minutes and then centrifuged at 3400 rpm for 15 minutes (VanGuard V6500, Hamilton Bell Co., Inc., Montvale, NJ). After the blood samples were centrifuged, 1 mL aliquots of serum were obtained and analyzed for total cholesterol (TC), triglycerides (TG), and highdensity lipoprotein (HDL) cholesterol with oxidase assays using colorimetric enzymatic methods. Low-density lipoprotein (LDL) cholesterol was then calculated using the Friedewald equation.21 Health/Fitness Measurements—Body Composition. During V1,
height (in meters) and weight (in kilograms) were measured using a wall-mounted tape measure and a calibrated balance beam scale, and BMI was calculated (kg·m–2).
118 Simpson et al
Also during V1, waist circumference (WC) (in centimeters) was measured using a Gulick spring-loaded tape measure. With the subject standing, arms at their sides, feet together, and abdomen relaxed, a horizontal measure was taken at the narrowest part of the torso (above the umbilicus and below the xiphoid process). Health/Fitness Measurements—Resting Blood Pressure. During V1, resting BP (mmHg) was measured via auscultation using a mercury sphygmomanometer (Trimline, PyMaH Corp., Somerville, NJ), a Trimline BP cuff (Omni Kuff, Latex Free, Universally connection BALANCED design, Trimline Medical Products, Somerville, NJ), and a Cardiology stethoscope (3M Litmann Lightweight II SE, St. Paul, MN) while the subject sat with his or her back and arms supported and legs uncrossed. Mean arterial pressure (MAP) (mmHg) was calculated as [MAP = Diastolic BP + 1/3 (Systolic BP – Diastolic BP)].
covariance (ANCOVA) examined differences in self-reported time (hr·d–1) spent in each PA intensity category on the PPAQ Q8 at V1, V4, and V5 with gender and season during which subjects completed the PPAQ Q8 during V1 as fixed factors and age as a covariate. To further examine the test–retest reliability of the PPAQ Q8, intraclass correlation coefficients (ICCs) were calculated for 2 administrations of the PPAQ Q8 using a 2-way random effects model. Standard error of the measurement (SEM) for the 2 visits was calculated as the square root of the mean squared error term from the ANOVA table. All statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS) Base 14.0 for Windows (SPSS Inc., Chicago, IL) with P < .05 established as the level of statistical significance.
Results
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Health/Fitness Measurements—Cardiorespiratory Fitness. CRF
(VO2max) was measured during V2 using a modified Balke maximal treadmill test.22–25 VO2max (ml·mg–1·min–1) was determined by breath-by-breath analysis of expired gases via an open circuit respiratory apparatus (Parvomedics TrueOne 2400 metabolic cart, Parvo Medics, Sandy, UT). Treadmill test termination criteria included an overall rating of perceived exertion ≥ 18, a plateau in VO2max, a respiratory exchange ratio > 1.1, achievement of the age predicted maximum HR, and/or termination by the subject due to fatigue or discomfort.22 Statistical Analysis. Independent samples t tests were used to examine differences between men and women in terms of health characteristics. A Shapiro–Wilk test suggested the PA variables measured in this study are not normally distributed. Instead, they are positively skewed. Therefore, Spearman rank-order correlation coefficients were used to examine the relationships among subject responses on the PPAQ Q8 (eg, time spent [hr·d–1] in sedentary, light-, moderate-, and vigorous-intensity PA and MET-hr·wk–1) and the Actical accelerometer (eg, time spent [min·d–1] in sedentary, light-, moderate-, and vigorous-intensity PA, average daily steps, activity counts, and energy expenditure) and health/fitness measures (eg, HDL and LDL cholesterol, BMI, WC, BP, MAP, HR, and CRF) to determine criterion and predictive validity, respectively, of the PPAQ Q8. All statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS) Base 14.0 for Windows (SPSS Inc., Chicago, IL) with P < .05 established as the level of statistical significance.
Study 2: Test–Retest Reliability Subjects. Subjects (n = 130) who participated in the STOMP study and completed the V1 (baseline), V4 (3 mo), and V5 (6 mo) study visits and were randomized to receive the placebo participated in the reliability portion of this substudy. Paffenbarger Physical Activity Questionnaire. Subjects
completed the PPAQ Q8 at baseline during V1 and during V4 and V5, approximately 3 and 6 months following V1, respectively, as described previously.
Statistical Analysis. Independent samples t tests were used to examine differences between men and women in terms of health characteristics. Spearman rank-order correlation coefficients tested the relationship among self-reported time (hr·d–1) spent in each PA intensity category on the PPAQ Q8 between V1 and V4, V4 and V5, and V1 and V5. In addition, a repeated measures analysis of
Study 1: Validity Subject Characteristics. The sample for the validity portion of this substudy (n = 419) consisted of mostly young, healthy, Caucasian (93.8%) men (n = 49.2%) and women (n = 50.8%). Subjects were overweight with above optimal LDL cholesterol and normal BP, HDL cholesterol, TC, and TG. Men were heavier (P < .001) and had higher SBP (P < .001), DBP (P = .01), MAP (P = .001), WC (P < .001), VO2max (P < .001), and TG (P < .001) than women. Women had higher resting HR (P = .006) and HDL cholesterol (P < .001) than men (Table 1). Criterion Validity. As shown in Table 2, self-reported time spent
in sedentary activities on the PPAQ Q8 was positively correlated with time spent in sedentary activities (P < .001) measured by the Actical accelerometer. Self-reported time spent in light intensity PA on the PPAQ Q8 was not significantly correlated with light intensity PA (P = .63) measured by the Actical accelerometer. Self-reported time spent in moderate intensity PA reported on the PPAQ Q8 was positively correlated with time spent in moderate intensity PA (P < .001) measured by the Actical accelerometer. Self-reported time spent in vigorous intensity PA on the PPAQ Q8 was positively correlated with daily counts (P = .002) and time spent in vigorous intensity PA (P < .001) measured by the Actical accelerometer. Finally, MET-hr·wk–1 from the PPAQ Q8 was correlated negatively with time spent in sedentary activities (P < .001) and positively with moderate (P < .001) intensity PA measured by the Actical. MET-hr·wk–1 from the PPAQ Q8 was not significantly correlated with vigorous intensity PA (r = –.03, P = .59) measured by the Actical accelerometer. Age, gender, season, and testing site did not modulate any of the correlations among PA measures on the PPAQ and those measured by the Actical accelerometer (P > .05). Predictive Validity. Self-reported time spent in sedentary activities on the PPAQ Q8 was positively correlated with SBP (r = .13, P = .01, 95% CI [.02, .21]), MAP (r = .13, P = .009, 95% CI [.01, .20]), and TG (r = .13, P = .01, 95% CI [.02, .22]), and negatively correlated with HDL cholesterol (r = –.16, P < .001, 95% CI [–.27, –.08]) and TC (r = –.13, P = .01, 95% CI [–.16, .03]). Self-reported time spent in moderate intensity PA on the PPAQ Q8 was positively correlated with HDL cholesterol (r = .14, P = .006, 95% CI [.03, .23]) and negatively correlated with BMI (r = –.10, P = .02, 95% CI [–.14, .05]), SBP (r = –.11, P = .02, 95% CI [–.16, .03]), and WC (r = –.11, P = .03, 95% CI [–.18, .02]). Furthermore, self-reported time spent in vigorous intensity PA on the PPAQ Q8 was negatively correlated with BMI (r = –.12, P =
Question 8 of the Paffenbarger Questionnaire 119
Table 1 Subject Characteristics (Mean ± SD) of Studies 1 and 2
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Study 1: Validity
Study 2: Reliability
Characteristics
Men (n = 206)
Women (n = 213)
Men (n = 106)
Women (n = 111)
Age (y) Height (m) Weight (kg) BMI (kg·m–2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Mean arterial pressure (mmHg) Resting heart rate (b×min–1) Waist circumference (cm) VO2max (ml×kg–1×min–1) High-density lipoprotein cholesterol (mg×dL–1) Low-density lipoprotein cholesterol (mg×dL–1) Total cholesterol (mg×dL–1) Triglycerides (mg×dL–1)
43.8 ± 15.8 1.8 ± 0.1* 87.4 ± 16.0* 27.4 ± 4.5* 121.6 ± 12.7* 76.5 ± 9.3** 91.5 ± 9.3* 67.3 ± 11.8*** 92.8 ± 13.0* 38.0 ± 9.0* 50.6 ±13.0* 120.2 ± 29.6 194.3 ± 33.0 118.1 ± 63.4*
44.3 ± 16.5 1.6 ± 0.1 68.8 ± 12.9 25.4 ± 5.0 116.2 ± 13.3 74.1 ± 9.8 88.2 ± 10.2 70.2 ± 10.3 80.1 ± 11.9 30.0 ± 8.8 65.5 ± 17.3 114.8 ± 37.0 198.9 ± 42.7 95.6 ± 44.0
44.0 ± 15.8 1.8 ± 0.1* 87.7 ± 15.8* 27.5 ± 4.6*** 121.5 ± 11.5* 77.4 ± 9.5* 92.1 ± 9.2* 67.4 ± 11.1*** 93.8 ± 13.0* 37.5 ± 9.3* 50.9 ± 11.2* 119.0 ± 28.3 192.0 ± 33.1 111.3 ± 63.2**
45.3 ± 16.9 1.6 ± 0.1 69.4 ± 12.7 25.6 ± 5.0 115.2 ± 14.0 72.8 ± 9.7 86.9 ± 10.3 71.5 ± 10.1 80.8 ± 12.1 29.1 ± 8.7 66.1 ± 18.2 113.2 ± 34.7 197.5 ± 40.6 95.2 ± 45.8
Note. Men vs. women: *P < .001, ** P < .05, *** P < .01. Abbreviations: BMI, body mass index.
.02, 95% CI [–.21, –.02]), DBP (r = –.11, P = .03, 95% CI [–.18, .01]), MAP (r = –.11, P = .03, 95% CI [–.17, .02]), and WC (r = –.14, P = .005, 95% CI [–.21, –.01]) and positively correlated with VO2max (r = .18, P < .001, 95% CI [.04, .23]) and HDL cholesterol (r = .16, P < .001, 95% CI [.06, .25]). Finally, MET-hr·wk–1 on the PPAQ Q8 was negatively correlated with BMI (r = –.11, P = .03, 95% CI [–.20, –.01]), WC (r = –.12, P = .04, 95% CI [–.21, –.01]), SBP (r = –.13, P = .006, 95% CI [–.21, –.02]), DBP (r = –.12, P = .02, 95% CI [–.20, –.01]), MAP (r = –.14, P = .004, 95% CI [–.21, –.02]), and TG (r = –.14, P = .004, 95% CI [–.21, –.02]), and positively correlated with HDL cholesterol (r = .20, P < .001, 95% CI [.11, .30]).
Study 2: Test–Retest Reliability Subject Characteristics. Subjects’ (n = 130) characteristics in the reliability portion of this study did not differ from those of subjects in the validity portion of this substudy (Table 1) (P > .05). Similar to the subjects in the validity portion of this substudy, men were heavier (P < .001) and had a higher SBP (P < .001), DBP (P < .001), MAP (P < .001), WC (P < .001), and VO2max (P < .001) than women, and women had higher HDL cholesterol than men (P < .001). Test–Retest Reliability. Table 3 displays the correlations among
time (hr·d–1) spent in each PA intensity category as well as METhr·wk–1 reported on the PPAQ Q8 between V1 and V4, V4 and V5, and V1 and V5. The positive correlations among these 3 bivisit comparisons were moderately strong, ranging from .26 to .61, and highly significant (P < .001). Comparison of Self-Reported Responses to the PPAQ Q8 Completed During V1 (baseline), V4 (3 mo), and V5 (6 mo). The
self-reported hr·d–1 spent in each PA intensity category on the PPAQ Q8 during V1, V4, and V5 are shown in Table 4. Repeated measures ANCOVA revealed self-reported time spent engaging in sedentary activities (F = 1.45, P = .24) as well as light intensity PA (F = 0.82, P = .44), moderate intensity PA (F = 1.19, P = .31), and vigorous
intensity PA (F = 2.93, P = .05) did not differ among V1, V4, and V5. However, MET-hr·wk–1 from the PPAQ Q8 did differ among V1, V4, and V5 (F = 3.57, P = .03) such that MET-hr·wk–1 on V1 was lower than MET-hr·wk–1 onV4 (P = .009) and V5 (P = .001). Table 5 lists the ICC and SEM for subject responses on the PPAQ Q8 during V4 and V5. The ICC was .49 to .67 for each activity intensity category on the PPAQ Q8. Self-reported time spent in sedentary activities and in light, moderate, and vigorous intensity PA produced SEM values that were 1.0 to 2.0%.
Discussion To the best of our knowledge, this STOMP substudy was the first to examine the criterion and predictive validity and test–retest reliability of the PPAQ Q8 among healthy men and women across the life span. The results of this STOMP substudy revealed PA reported on Q8 was associated with numerous measurements from an Actical accelerometer, VO2max, and other health-related fitness outcomes, indicating good criterion and predictive validity. Furthermore, PA assessed by the PPAQ Q8 demonstrated acceptable test–retest reliability when measured 3 and 6 months from baseline.
Study 1: Validity Criterion Validity 1. In this STOMP substudy, significant positive
associations were observed among the intensity categories and MET-hr·wk–1 on the PPAQ Q8 and the Actical accelerometer (Table 2) measurements, ranging from r = .15 to .20. Although these correlations are relatively weak, they are consistent with the magnitude of the correlations reported in the existing literature examining the validity of other well-validated and popular questionnaires compared with accelerometer measurements.8,26–28 For instance, Strath et al reported correlations among self-reported PA on the PPAQ PA index and PA measured using the simultaneous HR motion sensor technique ranging from r = .20 to .47 among men and women 20 to 56 years of age.8 Similarly, Wolin et al found correlations ranging from r = .26 to .36 among self-reported PA on
120
* P < .05, ** P < .01.
Steps Counts (d–1) Energy expenditure (kcal×d–1) Sedentary (min×d–1) Light intensity (min×d–1) Moderate intensity (min×d–1) Vigorous intensity (min×d–1)
(d–1)
Actical measurement –.02 (–.15, .05) .04 (–.08, .12) –.03 (–.16, .04) .20** (.14, .33) –.24** (–.36, –.16) –.14* (–.25, –.06) .04 (–.04, .16)
Sedentary –.07 (–.17, .03) –.09 (–.17, .03) –.07 (–.17, .03) .03 (–.07, .13) .02 (–.09, .11) –.07 (–.17, .03) .01 (–.12, .08)
Light intensity .04 (.00, .20) –.03 (–.11, .09) .06 (–.00, .20) –.24** (.19, 3.77) .27** (.19, .34) .15** (.11, .30) –.11* (–.14, .05)
Moderate intensity
.10* (–.01, .19) .15** (.02, .22) .07 (.02, .22) –.09 (–.23, –.04) .03 (–.01, .19) .11* (.05, .24) .20** (–.01, .19)
Vigorous intensity
.07 (.02, .22) .01 (–.067, .13) .07 (.02, .22) –.24** (–.39, –.20) .26 (.20, .40) .17** (.13, .33) –.01 (–.13, .07)
MET· hr/wk
Table 2 Spearman Rank-Order Correlations (95% Confidence Intervals) Among Intensity Categories and MET-hr·wk–1 on the Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) and the Actical Accelerometer
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Question 8 of the Paffenbarger Questionnaire 121
Table 3 Spearman Rank-Order Correlations (95% Confidence Intervals) Among Subject Responses on the Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) Completed During Visit 1 and Visit 4, Visit 4 and Visit 5, and Visit 1 and Visit 5 PPAQ Q8 activity intensity category
Visit 1 vs. Visit 4*
Visit 4 vs. Visit 5*
Visit 1 vs. Visit 5*
.39 (.33, .51) .26 (.17, .36) .46 (.41, .59) .43 (.25, .43) .50 (.43, .60)
.49 (.36, .54) .34 (.23, .42) .46 (.35, .52) .54 (.41, .58) .61 (.52, .68)
.43 (.43, .60) .27 (.17, .36) .37 (.29, .47) .45 (.22, .40) .47 (.39, .56)
Sedentary Light intensity Moderate intensity Vigorous intensity MET-hr·wk–1 Note. For all variables, * P = .000.
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Table 4 Time (hr·d–1) (Mean ± SEM) Spent in Each Physical Activity Intensity Category Reported on Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) on Visit 1, Visit 4, and Visit 5 PPAQ Q8 physical activity intensity category
Visit 1 (hr·d–1)
Visit 4 (hr∙d–1)
Visit 5 (hr∙d–1)
Sedentary Light intensity Moderate intensity Vigorous intensity MET-hr·wk–1
13.4 ± 3.0 5.4 ± 2.5 3.8 ± 2.3 1.4 ± 1.2 343.9 ± 77.9*
13.1 ± 2.8 5.5 ± 2.5 3.8 ± 2.2 1.6 ± 1.5 354.2 ± 81.2
13.0 ± 2.7 5.6 ± 2.4 3.9 ± 2.3 1.5 ± 1.4 355.3 ± 80.3
* For MET-hr·wk–1, V1 vs. V4 and V1 vs. V5, P < .05.
Table 5 Reliability of Intensity Categories on the Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) Intraclass correlation (95% CI)a
SEM
.71 (.61, .74) .49 (.38, .59) .61 (.52, .68) .67 (.59, .72)
1.9 2.0 1.7 1.0
Sedentary Light intensity Moderate intensity Vigorous intensity
Abbreviations: CI, confidence interval; SEM, standard error of measurement. a Intraclass correlations calculated between V1, V2, and V3.
the short version of the International Physical Activity Questionnaire and PA measured with an Actical accelerometer among healthy African American men and women aged 24 to 70 years.27 Finally, Hagstromer et al and Boon et al reported fairly weak correlations among self-reported PA on the International Physical Activity Questionnaire and PA measured by the Actigraph accelerometer ranging from r = .14 to .27 and r = .19 to .30, respectively.26,28 Therefore, our results compare quite favorably to the existent literature and indicate adequate criterion validity of the PPAQ Q8 among healthy men and women over 20 years of age. It has been suggested that accelerometers worn on the hip may underestimate PA performed because of their inability to detect upper body motions and the inability of the subject to wear the device while swimming.20 This imperfect validity of accelerometers may have influenced our results by underestimating the real validity of Q8. In other words, if the Actical had perfect validity, the validity coefficients for Q8 reported in this study probably would have been higher. Predictive Validity. Significant correlations were also observed
among the intensity categories and MET-hr·wk–1 on the PPAQ Q8 and the various health/fitness measurements ranging from r = –.27 to .20. Although these correlations are weak, they are consistent
with the magnitude of correlations reported in the literature examining the validity of questionnaires compared with health/ fitness measurements.15,27 For instance, Washburn et al found weak but significant correlations among self-reported energy expenditure on the PPAQ PA index and HDL cholesterol (r = .14) and BMI (r = –.13) among men and women 25 to 65 years old.15 Graff-Iversen et al also reported weak, yet significant correlations among self-reported PA on the long version of the International Physical Activity Questionnaire and health-related fitness outcomes (eg, BMI, HDL cholesterol, waist/hip ratio, TG, diastolic BP, and glucose), ranging from r = –.14 to .12 among men and women 31 to 67 years old.27 Therefore, the results of this STOMP substudy are in agreement with previous studies in the literature and indicate acceptable predictive validity of the PPAQ Q8 among healthy men and women over 20 years old.
Study 2: Test–Retest Reliability Test–Retest Reliability. Medium strength, positive correlations ranging from r = .27 to .60 were observed among self-reported time (hr·d–1) spent in each exercise intensity category and MET hr·wk–1 reported on the PPAQ Q8 between V1 and V4, V4 and V5, and V1 and V5 (Table 4). In addition, ANCOVA revealed time (hr·d–1) spent
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122 Simpson et al
in each intensity category on PPAQ Q8 did not significantly differ among V1, V4, and V5 (P > .05). These findings are consistent with the results of other previously published studies.5,7 For instance, Ainsworth et al reported similar reliability over an 8- and 9-month time period for the PPAQ physical activity index (r = .34 and r = .43, P < .05) among healthy men and women of similar age to subjects in this STOMP substudy.7 Richardson et al reported similar observations regarding the 1-month test–retest reliability of the Stanford 7-day recall among 78 healthy men and women (r = .60 and r = .36, P < .05, respectively) 21 to 59 years of age.5 Therefore, the results of this STOMP substudy are consistent with the literature and indicate satisfactory test–retest reliability of the PPAQ Q8 over 3 and 6 months among healthy adults over 20 years old. The time period between test and retest (ie, between the first and second and first and third administrations of the PPAQ Q8) was relatively long (3 and 6 mo). Therefore, it is possible that some subjects actually changed their PA habits during test and retest periods, lowering the reliability coefficients. The PPAQ is a commonly used questionnaire in large, epidemiological studies examining the relationships between habitual PA and health. The results of this STOMP substudy provide novel evidence that, among healthy men and women over 20 years, the PPAQ Q8 has adequate criterion validity, acceptable predictive validity, and satisfactory test–retest reliability. The results of this substudy expand the PPAQ’s utility for researchers and health/fitness professionals to assess habitual participation in exercise among healthy men and women across the life span.
Study Limitations and Strengths This study is potentially limited by several factors. The data used in this study were collected at multiple test sites, increasing the chances of site and interpretation bias occurring during the data collection and entry processes. However, investigators at each of the 3 sites followed a strict standard protocol for collecting data as well as for interpreting subject responses on the PPAQ during data entry. These actions likely decreased the amount of site and interpretation bias that may have occurred. In addition, only individuals who were identified as “healthy,” according to the inclusion/exclusion criteria of the STOMP study, who could exercise vigorously on a treadmill, and who were willing to take either Lipitor or placebo for 6 months participated in STOMP. As a result, the sample used in this study was self-selected as opposed to a true random sample. This might have biased our findings. There are several strengths to this study. First, previously published studies assessing the ability of questionnaires to measure and assess participation in PA sometimes focus on only 1 dimension of validity. Moreover, questionnaire validation studies oftentimes neglect to examine the test–retest reliability of the questionnaire altogether. This study assessed concurrent and predictive validity as well as the test–retest reliability of the PPAQ Q8. Therefore, the results of this study provide more complete and accurate evidence that the PPAQ Q8 is indeed a valuable tool for assessing participation in PA. Second, this study used data collected from a large sample (n = 240) of healthy men and women. The sample used in this study was larger and covered a wider age range (20–81 y) than a number of other studies in the literature examining the validity and/or test–retest reliability of other PA questionnaires.3,17 The larger sample size and wider age range used in this study allows the findings/conclusions to be generalized to a larger group of people.
Acknowledgments This work was supported by a grant (R01HL081893-01A2) from the United States National Institutes of Health.
References 1. U.S. Department of Health and Human Services. Physical Activity Guidelines Advisory Guidelines Committee Report. Washington, DC: U.S. Department of Health and Human Services; 2008:A1–A10. 2. Department of Health, Physical Activity, Health Improvement, and Prevention. At Least Five a Week: Evidence on the Impact of Physical Activity and Its Relationship to Health. A report from the Chief Medical Officer. London, UK: Department of Health; 2004:1–9. 3. Mahabir S, Baer DJ, Giffen C, et al. Comparison of energy expenditure estimates from 4 physical activity questionnaires with doubly labeled water estimates in postmenopausal women. Am J Clin Nutr. 2006;84:230–236. PubMed 4. U.S. Department of Health and Human Services. Healthy People 2020, 2010. 5. Richardson MT, Ainsworth BE, Jacobs DR, Leon AS. Validation of the Stanford 7-Day Recall to Assess Habitual Physical Activity. Ann Epidemiol. 2001;11:145–153. PubMed doi:10.1016/S10472797(00)00190-3 6. Washburn RA, Goldfield SRW, Smith KW, McKinlay JB. The validity of self-reported exercise-induced sweating as a measure of physical activity. Am J Epidemiol. 1990;132:107–113. PubMed 7. Ainsworth BE, Leon AS, Richardson MT, Jacobs DR, Paffenbarger RS. Accuracy of the College Alumnus Physical Activity Questionnaire. J Clin Epidemiol. 1993;46(12):1403–1411. PubMed doi:10.1016/0895-4356(93)90140-V 8. Strath SJ, Bassett DR, Swartz AM. Comparison of the College Alumnus Questionnaire Physical Activity Index with objective monitoring. Ann Epidemiol. 2004;14:409–415. PubMed doi:10.1016/j.annepidem.2003.07.001 9. Aadahl M, Kjaer M, Kristensen JH, Mollerup B, Jorgensen T. Selfreported physical activity compared with maximal oxygen uptake in adults. Eur J Cardiovasc Prev Rehabil. 2007;14:422–428. PubMed doi:10.1097/HJR.0b013e3280128d00 10. Papathanasiou G, Georgoudis G, Georgakopoulos D, Katsouras C, Kalfakakou V, Evangelou A. Criterion-related validity of the Short International Physical Activity Questionnaire against exercise capacity in young adults. Eur J Cardiovasc Prev Rehabil. 2010;17(4):380–386. PubMed 11. Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations and future directions. Res Q Exerc Sport. 2000;71(2, Suppl):S1–S14. PubMed 12. Washburn RA, Montoye HJ. The assessment of physical activity by questionnaire. Am J Epidemiol. 1986;123:563–576. PubMed 13. Paffenbarger RS, Jr, Blair SN, Lee IM, Hyde RT. Measurement of physical activity to assess health effects in free-living populations. Med Sci Sports Exerc. 1993;25(1):60–70. PubMed doi:10.1249/00005768199301000-00010 14. Paffenbarger RS, Wing AL, Hyde RT. Physical activity as an index of heart attack risk in college alumni. Am J Epidemiol. 1978;108:161– 175. PubMed 15. Washburn RA, Smith KW, Goldfield SR, McKinlay JB. Reliability and physiologic correlates of the Harvard Alumni Activity Survey in a general population. J Clin Epidemiol. 1991;44(12):1319–1326. PubMed doi:10.1016/0895-4356(91)90093-O
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Question 8 of the Paffenbarger Questionnaire 123 16. Siconolfi SF, Lasater TM, Snow RCK, Carleton RA. Self-reported physical activity compared with maximal oxygen uptake. Am J Epidemiol. 1985;122:101–105. PubMed 17. Rundle A, Hagins M, Orjuela M, Mooney L, Kim M, Perera F. Traditional physical activity indexes derived from the Harvard Alumni Activity Survey have low construct validity in a lower income, urban population. J Urban Health. 2007;84(5):722–732. PubMed doi:10.1007/s11524-007-9212-4 18. Thompson PD, Parker BA, Clarkson PM, et al. A randomized clinical trial to assess the effect of statins on skeletal muscle function and performance: rationale and study design. Prev Cardiol. 2010;13(3):104– 111. PubMed 19. Parker BA, Capizzi JA, Grimaldi A, et al. The effect of statins on skeletal muscle function. J Am Coll Cardiol. 2012;59(13, Suppl):E1624. 20. Heil DP. Predicting activity energy expenditure using the Actical activity monitor. Res Q Exerc Sport. 2006;77(1):64–80. PubMed doi :10.1080/02701367.2006.10599333 21. Friedewald WT, Levy RT, Frederickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502. PubMed 22. Thompson WR, Gordon NF, Pescatello LS, American College of Sports Medicine. ACSM’s guidelines for exercise testing and prescription. 8th ed. Philadelphia, PA: Lippincott, Williams and Wilkins; 2009.
23. Balke B, Ware RW. An experimental study of physical fitness of Air Force personnel. U S Armed Forces Med J. 1959;10(6):675–688. PubMed 24. Martin Bland J, Altman DG. Statistical methods for assessing agreement between two methods of clinical assessment. Lancet. 1986;327(8476):307–310. PubMed doi:10.1016/S01406736(86)90837-8 25. Takken T, Blank AC, Hulzebos EH, Brussel MV, Groen WG, Helders PJ. Cardiopulmonary exercise testing in congenital heart disease: equipment and test protocols. Neth Heart J. 2009;17(9):339–344. PubMed doi:10.1007/BF03086280 26. Hagströmer M, Bergman P, De Bourdeaudhuij I, et al. Concurrent validity of a modified version of the International Physical Activity Questionnaire (IPAQ-A) in European adolescents: The HELENA Study. Int J Obes. 2008;32:S42–S48. doi:10.1038/ijo.2008.182 27. Wolin KY, Heil DP, Askew S, Matthews CE, Bennett GG. Validation of the International Physical Activity Questionnaire-Short among blacks. J Phys Act Health. 2008;5(5):746–760. PubMed 28. Boon RM, Hamlin MJ, Steel GD, Ross JJ. Validation of the New Zealand Physical Activity Questionnaire (NZPAQ-LF) and the International Physical Activity Questionnaire (IPAQ-LF) with accelerometer. Br J Sports Med. 2010;44:741–746. PubMed doi:10.1136/ bjsm.2008.052167
Official Journal of ISPAH www.JPAH-Journal.com ORIGINAL RESEARCH
Validity and Reliability of Question 8 of the Paffenbarger Physical Activity Questionnaire Among Healthy Adults Kathleen Simpson, Beth Parker, Jeffrey Capizzi, Paul Thompson, Priscilla Clarkson, Patty Freedson, and Linda Shannon Pescatello Background: Little information exists regarding the psychometric properties of question 8 (Q8) of the Paffenbarger Physical Activity Questionnaire (PPAQ) to assess exercise. Thus, we conducted 2 studies to assess the validity and test–retest reliability of Q8 among adults. Methods: Study 1 participants (n = 419) were 44.1 ± 16.1 years of age. Validity was determined by comparing self-reported hr∙d–1 in sedentary, light, moderate, and vigorous intensity physical activity (PA) and MET-hr·wk–1 on Q8 at baseline to accelerometer and health/fitness measurements using Spearman rank-order correlations. Study 2 participants (n = 217) were 44.7 ± 16.3 years of age and completed Q8 at baseline, 3 months, and 6 months. Test–retest reliability was determined using repeated measures analysis of covariance, intraclass correlations (ICCs), and standard error of the measurement (SEM). Results: Q8 displayed good criterion validity compared with accelerometer measurements (r = .102 to .200, P < .05) and predictive validity compared with health/fitness measurements (r = –.272 to .203, P < .05). No differences were observed in self-reported hr·d–1 in any of the PA categories at baseline, 3 months, and 6 months (ICC: 0.49 to 0.68; SEM: 1.0 to 2.0; P > .05), indicating good reliability. Conclusion: Q8 demonstrates adequate criterion validity, acceptable predictive validity, and satisfactory test–retest reliability and can be used in conjunction with other components of the PPAQ to provide a complete representation of exercise. Keywords: Actical accelerometer, body composition, Harvard Alumni Questionnaire, health, heart rate, maximum oxygen consumption, physical fitness Habitual participation in physical activity (PA) has many physical and mental health benefits for people of all ages.1 A physically active lifestyle is associated with a reduced risk of developing several chronic diseases and health conditions such as cardiovascular disease, type 2 diabetes mellitus, hypertension, dyslipidemia, obesity, and several forms of cancer.1–4 However, the dose-response relationships that exist among chronic disease risk and exercise participation are complex and not yet fully understood. Accurate quantification of PA habits is of utmost importance to increase the understanding of these relationships and ultimately devise even more effective PA interventions.5 Self-report questionnaires are currently one of the most practical and widely used methods for assessing PA because they are inexpensive, quick, and relatively easy to administer to large groups of people.6–10 However, using questionnaires can result in a greater misclassification of PA habits than objective PA measures because of difficulties with recalling PA, misunderstanding of questions, and social desirability biases.9,11 Additionally, questionnaires often differ in terms of the mode and length of administration and scoring methodology, all of which can have an impact on how effective and often the questionnaire is used.12
Simpson ([email protected]) is with the Dept of Kinesiology, University of Connecticut, Storrs, CT. Parker, Capizzi, and Thompson are with the Dept of Preventive Cardiology, Hartford Hospital, Hartford, CT. Clarkson and Freedson are with the Dept of Kinesiology, University of Massachusetts, Amherst, MA. Pescatello is with the School of Allied Health, University of Connecticut, Storrs, CT. 116
The Paffenbarger Physical Activity Questionnaire (PPAQ) is a short questionnaire designed to measure participation in leisure time PA among adults 18 years of age and above.13 The most recent version of the PPAQ consists of 8 questions. The first 4 questions on this version of the PPAQ are used to compute a PA index that provides an estimate of energy expenditure (MET-min·wk–1).14 Question 5 (Q5) asks subjects to choose which of these statements expresses their view: “I take enough exercise to keep healthy,” “I ought to take more exercise,” or “Don’t know.” Question 6 (Q6) of the PPAQ asks subjects to report the number of times per week they engage in PA long enough to work up a sweat, get their heart thumping or become out of breath. Question 7 (Q7) asks subjects to rate their level of exertion during PA on a scale of 0.5 to 10 with 0.5 being very weak and 10 being maximal. Both the PA index and Q6 of the PPAQ have been validated against measures of cardiorespiratory fitness (CRF) (eg, VO2max), accelerometers (eg, the caltrac accelerometer), daily PA logs, and various health outcomes (eg, heart rate [HR], body mass index [BMI], and lipids).7,8,15,16 These validation studies show the PA index and Q6 of the PPAQ are good measures of participation in moderate and vigorous intensity PA with correlation coefficients ranging from r = .13 to .69.7,8,15,16 Question 8 (Q8) of the newest version of the PPAQ asks respondents to report the time (hr·d–1) they spend on a typical day during the week and weekend sleeping and reclining, participating in sitting activities, and engaging in light, moderate, and vigorous intensity PA. Therefore, PPAQ Q8 not only provides researchers and clinicians with information regarding the duration of moderate and vigorous intensity PA people perform, but also can assess the duration of sedentary and light intensity PA performed. In addition,
Question 8 of the Paffenbarger Questionnaire 117
PPAQ Q8 can separately assess the duration of PA on weekdays and weekend days. Two studies have examined the validity of the PPAQ Q8.3,17 However, these studies examined subject populations consisting of postmenopausal women and individuals of low socioeconomic status, so the results may not be generalizable to the general population. In addition, to the best of our knowledge, no study has examined the test–retest reliability of Q8. Thus, the purpose of this study was to examine the criterion and predictive validity of the PPAQ Q8 compared with accelerometer and health/fitness measurements, as well as the test–retest reliability of the PPAQ Q8 in a sample of healthy men and women across the life span.
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Methods This study investigated the validity and test–retest reliability of the PPAQ Q8 using data from a larger U.S. National Institutes of Health–funded study entitled The Effects of Statins on Muscle Performance (STOMP; 1R01HL081893-01A2). STOMP was conducted by researchers at Hartford Hospital, Hartford, CT; the University of Massachusetts, Amherst, MA; and the University of Connecticut, Storrs, CT. The purpose of STOMP was to examine the incidence of statin-induced muscle symptoms or myalgia, as well as the effects of statins on exercise performance among healthy men and women taking either 80 mg of atorvastatin (Lipitor) or placebo daily for 6 months. The institutional review boards at all 3 study sites approved the experimental design of STOMP.18,19 The STOMP study consisted of 6 study visits over approximately a 6-month period of time. Study visits 1, 2, and 3 (V1, V2, and V3) occurred within approximately 1 week and consisted of strength and aerobic fitness testing, blood work, and questionnaires. Following V3, subjects were randomly assigned to receive either 80 mg of atorvastatin or a placebo. STOMP visit 4 (V4) took place 3 months following V3 and consisted of blood work and questionnaires. STOMP visits 5 (V5) and 6 (V6) took place 6 months following V3 and again consisted of strength and aerobic fitness testing, blood work, and questionnaires.18,19 In this STOMP substudy, subject responses on the PPAQ Q8 and health/fitness measurements obtained before atorvastatin or placebo were dispensed, that is, during V1, V2, and V3 of STOMP, were used to determine the validity of the PPAQ Q8. In addition, for subjects assigned to receive the placebo, responses on the PPAQ Q8 during V1, V4, and V5 were used to determine the test–retest reliability of the PPAQ Q8. Subjects for STOMP were recruited via study flyers, e-mail announcements, and radio/newspaper advertisements. Volunteers in STOMP included approximately equal numbers of men and women in the following age groups: 20 to 39 years old, 40 to 54 years old, and 55+ years old. Before participating, all participants signed an informed-consent document. Participants were excluded if they were presently being treated or had previously been treated with cholesterol-lowering medications or had been diagnosed with diabetes, hyper- or hypothyroidism, or any heart condition that required medication or a restriction of PA. Anyone unable to exercise vigorously on a treadmill or who had hepatic disease, renal disease, or occult cardiac ischemia documented during a physician-supervised treadmill test during STOMP V1 was also excluded from the study. Individuals using hypertensive medications were included if they had been on these medications for at least 3 months and their blood pressure (BP) was stable ( 6 METs). Physical Activity Measurements—Actical Accelerometer.
Subjects wore an Actical accelerometer (Mini Mitter Company, Bend, OR) securely fastened to their hip on the side of the dominant hand between V2 and V3. The device was set to record PA in 25-second epochs and was initialized to begin recording data immediately. To be included in the subsequent analysis, participants were required to wear the Actical for at least 4 consecutive days (96 h; 2 d during the week and 2 d over the weekend) and were asked to remove the Actical only when they were swimming, bathing, showering, or sleeping. Subjects were asked to inform the research assistant if they removed the Actical to go swimming at any point during the 4 days they were wearing the device. A valid day was defined as 8 consecutive hours of wear time. Data from the Actical were downloaded from the device using the Actical software developed by the Actical company (Mini Mitter Company, Bend, OR). The data were then exported into Microsoft Excel for further processing and analysis. Variables obtained from the Actical were time spent (min·d–1) in sedentary, light, moderate, and vigorous intensity PA, steps·day–1, activity counts·day–1, and energy expenditure (kcal·d–1). Cut points (in units of activity energy expenditure) used to define sedentary, light (< 3 METs), moderate (≥ 3 to < 6 METs), and vigorous (≥ 6 METs) intensity PA were as follows: sedentary and light intensity < 0.0310 kcal·kg–1·min–1; 0.0310 kcal·kg–1·min–1 £ moderate intensity < 0.0832 kcal·kg–1·min–1; and vigorous ≥ 0.0832 kcal·kg–1·min–1.20 Health/Fitness Measurements—Blood Lipid-Lipoprotein Profile. During V1, fasting blood samples were collected from the
antecubital space on the arm of each subject. These blood samples were allowed to sit at room temperature for at least 10 minutes and then centrifuged at 3400 rpm for 15 minutes (VanGuard V6500, Hamilton Bell Co., Inc., Montvale, NJ). After the blood samples were centrifuged, 1 mL aliquots of serum were obtained and analyzed for total cholesterol (TC), triglycerides (TG), and highdensity lipoprotein (HDL) cholesterol with oxidase assays using colorimetric enzymatic methods. Low-density lipoprotein (LDL) cholesterol was then calculated using the Friedewald equation.21 Health/Fitness Measurements—Body Composition. During V1,
height (in meters) and weight (in kilograms) were measured using a wall-mounted tape measure and a calibrated balance beam scale, and BMI was calculated (kg·m–2).
118 Simpson et al
Also during V1, waist circumference (WC) (in centimeters) was measured using a Gulick spring-loaded tape measure. With the subject standing, arms at their sides, feet together, and abdomen relaxed, a horizontal measure was taken at the narrowest part of the torso (above the umbilicus and below the xiphoid process). Health/Fitness Measurements—Resting Blood Pressure. During V1, resting BP (mmHg) was measured via auscultation using a mercury sphygmomanometer (Trimline, PyMaH Corp., Somerville, NJ), a Trimline BP cuff (Omni Kuff, Latex Free, Universally connection BALANCED design, Trimline Medical Products, Somerville, NJ), and a Cardiology stethoscope (3M Litmann Lightweight II SE, St. Paul, MN) while the subject sat with his or her back and arms supported and legs uncrossed. Mean arterial pressure (MAP) (mmHg) was calculated as [MAP = Diastolic BP + 1/3 (Systolic BP – Diastolic BP)].
covariance (ANCOVA) examined differences in self-reported time (hr·d–1) spent in each PA intensity category on the PPAQ Q8 at V1, V4, and V5 with gender and season during which subjects completed the PPAQ Q8 during V1 as fixed factors and age as a covariate. To further examine the test–retest reliability of the PPAQ Q8, intraclass correlation coefficients (ICCs) were calculated for 2 administrations of the PPAQ Q8 using a 2-way random effects model. Standard error of the measurement (SEM) for the 2 visits was calculated as the square root of the mean squared error term from the ANOVA table. All statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS) Base 14.0 for Windows (SPSS Inc., Chicago, IL) with P < .05 established as the level of statistical significance.
Results
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Health/Fitness Measurements—Cardiorespiratory Fitness. CRF
(VO2max) was measured during V2 using a modified Balke maximal treadmill test.22–25 VO2max (ml·mg–1·min–1) was determined by breath-by-breath analysis of expired gases via an open circuit respiratory apparatus (Parvomedics TrueOne 2400 metabolic cart, Parvo Medics, Sandy, UT). Treadmill test termination criteria included an overall rating of perceived exertion ≥ 18, a plateau in VO2max, a respiratory exchange ratio > 1.1, achievement of the age predicted maximum HR, and/or termination by the subject due to fatigue or discomfort.22 Statistical Analysis. Independent samples t tests were used to examine differences between men and women in terms of health characteristics. A Shapiro–Wilk test suggested the PA variables measured in this study are not normally distributed. Instead, they are positively skewed. Therefore, Spearman rank-order correlation coefficients were used to examine the relationships among subject responses on the PPAQ Q8 (eg, time spent [hr·d–1] in sedentary, light-, moderate-, and vigorous-intensity PA and MET-hr·wk–1) and the Actical accelerometer (eg, time spent [min·d–1] in sedentary, light-, moderate-, and vigorous-intensity PA, average daily steps, activity counts, and energy expenditure) and health/fitness measures (eg, HDL and LDL cholesterol, BMI, WC, BP, MAP, HR, and CRF) to determine criterion and predictive validity, respectively, of the PPAQ Q8. All statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS) Base 14.0 for Windows (SPSS Inc., Chicago, IL) with P < .05 established as the level of statistical significance.
Study 2: Test–Retest Reliability Subjects. Subjects (n = 130) who participated in the STOMP study and completed the V1 (baseline), V4 (3 mo), and V5 (6 mo) study visits and were randomized to receive the placebo participated in the reliability portion of this substudy. Paffenbarger Physical Activity Questionnaire. Subjects
completed the PPAQ Q8 at baseline during V1 and during V4 and V5, approximately 3 and 6 months following V1, respectively, as described previously.
Statistical Analysis. Independent samples t tests were used to examine differences between men and women in terms of health characteristics. Spearman rank-order correlation coefficients tested the relationship among self-reported time (hr·d–1) spent in each PA intensity category on the PPAQ Q8 between V1 and V4, V4 and V5, and V1 and V5. In addition, a repeated measures analysis of
Study 1: Validity Subject Characteristics. The sample for the validity portion of this substudy (n = 419) consisted of mostly young, healthy, Caucasian (93.8%) men (n = 49.2%) and women (n = 50.8%). Subjects were overweight with above optimal LDL cholesterol and normal BP, HDL cholesterol, TC, and TG. Men were heavier (P < .001) and had higher SBP (P < .001), DBP (P = .01), MAP (P = .001), WC (P < .001), VO2max (P < .001), and TG (P < .001) than women. Women had higher resting HR (P = .006) and HDL cholesterol (P < .001) than men (Table 1). Criterion Validity. As shown in Table 2, self-reported time spent
in sedentary activities on the PPAQ Q8 was positively correlated with time spent in sedentary activities (P < .001) measured by the Actical accelerometer. Self-reported time spent in light intensity PA on the PPAQ Q8 was not significantly correlated with light intensity PA (P = .63) measured by the Actical accelerometer. Self-reported time spent in moderate intensity PA reported on the PPAQ Q8 was positively correlated with time spent in moderate intensity PA (P < .001) measured by the Actical accelerometer. Self-reported time spent in vigorous intensity PA on the PPAQ Q8 was positively correlated with daily counts (P = .002) and time spent in vigorous intensity PA (P < .001) measured by the Actical accelerometer. Finally, MET-hr·wk–1 from the PPAQ Q8 was correlated negatively with time spent in sedentary activities (P < .001) and positively with moderate (P < .001) intensity PA measured by the Actical. MET-hr·wk–1 from the PPAQ Q8 was not significantly correlated with vigorous intensity PA (r = –.03, P = .59) measured by the Actical accelerometer. Age, gender, season, and testing site did not modulate any of the correlations among PA measures on the PPAQ and those measured by the Actical accelerometer (P > .05). Predictive Validity. Self-reported time spent in sedentary activities on the PPAQ Q8 was positively correlated with SBP (r = .13, P = .01, 95% CI [.02, .21]), MAP (r = .13, P = .009, 95% CI [.01, .20]), and TG (r = .13, P = .01, 95% CI [.02, .22]), and negatively correlated with HDL cholesterol (r = –.16, P < .001, 95% CI [–.27, –.08]) and TC (r = –.13, P = .01, 95% CI [–.16, .03]). Self-reported time spent in moderate intensity PA on the PPAQ Q8 was positively correlated with HDL cholesterol (r = .14, P = .006, 95% CI [.03, .23]) and negatively correlated with BMI (r = –.10, P = .02, 95% CI [–.14, .05]), SBP (r = –.11, P = .02, 95% CI [–.16, .03]), and WC (r = –.11, P = .03, 95% CI [–.18, .02]). Furthermore, self-reported time spent in vigorous intensity PA on the PPAQ Q8 was negatively correlated with BMI (r = –.12, P =
Question 8 of the Paffenbarger Questionnaire 119
Table 1 Subject Characteristics (Mean ± SD) of Studies 1 and 2
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Study 1: Validity
Study 2: Reliability
Characteristics
Men (n = 206)
Women (n = 213)
Men (n = 106)
Women (n = 111)
Age (y) Height (m) Weight (kg) BMI (kg·m–2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Mean arterial pressure (mmHg) Resting heart rate (b×min–1) Waist circumference (cm) VO2max (ml×kg–1×min–1) High-density lipoprotein cholesterol (mg×dL–1) Low-density lipoprotein cholesterol (mg×dL–1) Total cholesterol (mg×dL–1) Triglycerides (mg×dL–1)
43.8 ± 15.8 1.8 ± 0.1* 87.4 ± 16.0* 27.4 ± 4.5* 121.6 ± 12.7* 76.5 ± 9.3** 91.5 ± 9.3* 67.3 ± 11.8*** 92.8 ± 13.0* 38.0 ± 9.0* 50.6 ±13.0* 120.2 ± 29.6 194.3 ± 33.0 118.1 ± 63.4*
44.3 ± 16.5 1.6 ± 0.1 68.8 ± 12.9 25.4 ± 5.0 116.2 ± 13.3 74.1 ± 9.8 88.2 ± 10.2 70.2 ± 10.3 80.1 ± 11.9 30.0 ± 8.8 65.5 ± 17.3 114.8 ± 37.0 198.9 ± 42.7 95.6 ± 44.0
44.0 ± 15.8 1.8 ± 0.1* 87.7 ± 15.8* 27.5 ± 4.6*** 121.5 ± 11.5* 77.4 ± 9.5* 92.1 ± 9.2* 67.4 ± 11.1*** 93.8 ± 13.0* 37.5 ± 9.3* 50.9 ± 11.2* 119.0 ± 28.3 192.0 ± 33.1 111.3 ± 63.2**
45.3 ± 16.9 1.6 ± 0.1 69.4 ± 12.7 25.6 ± 5.0 115.2 ± 14.0 72.8 ± 9.7 86.9 ± 10.3 71.5 ± 10.1 80.8 ± 12.1 29.1 ± 8.7 66.1 ± 18.2 113.2 ± 34.7 197.5 ± 40.6 95.2 ± 45.8
Note. Men vs. women: *P < .001, ** P < .05, *** P < .01. Abbreviations: BMI, body mass index.
.02, 95% CI [–.21, –.02]), DBP (r = –.11, P = .03, 95% CI [–.18, .01]), MAP (r = –.11, P = .03, 95% CI [–.17, .02]), and WC (r = –.14, P = .005, 95% CI [–.21, –.01]) and positively correlated with VO2max (r = .18, P < .001, 95% CI [.04, .23]) and HDL cholesterol (r = .16, P < .001, 95% CI [.06, .25]). Finally, MET-hr·wk–1 on the PPAQ Q8 was negatively correlated with BMI (r = –.11, P = .03, 95% CI [–.20, –.01]), WC (r = –.12, P = .04, 95% CI [–.21, –.01]), SBP (r = –.13, P = .006, 95% CI [–.21, –.02]), DBP (r = –.12, P = .02, 95% CI [–.20, –.01]), MAP (r = –.14, P = .004, 95% CI [–.21, –.02]), and TG (r = –.14, P = .004, 95% CI [–.21, –.02]), and positively correlated with HDL cholesterol (r = .20, P < .001, 95% CI [.11, .30]).
Study 2: Test–Retest Reliability Subject Characteristics. Subjects’ (n = 130) characteristics in the reliability portion of this study did not differ from those of subjects in the validity portion of this substudy (Table 1) (P > .05). Similar to the subjects in the validity portion of this substudy, men were heavier (P < .001) and had a higher SBP (P < .001), DBP (P < .001), MAP (P < .001), WC (P < .001), and VO2max (P < .001) than women, and women had higher HDL cholesterol than men (P < .001). Test–Retest Reliability. Table 3 displays the correlations among
time (hr·d–1) spent in each PA intensity category as well as METhr·wk–1 reported on the PPAQ Q8 between V1 and V4, V4 and V5, and V1 and V5. The positive correlations among these 3 bivisit comparisons were moderately strong, ranging from .26 to .61, and highly significant (P < .001). Comparison of Self-Reported Responses to the PPAQ Q8 Completed During V1 (baseline), V4 (3 mo), and V5 (6 mo). The
self-reported hr·d–1 spent in each PA intensity category on the PPAQ Q8 during V1, V4, and V5 are shown in Table 4. Repeated measures ANCOVA revealed self-reported time spent engaging in sedentary activities (F = 1.45, P = .24) as well as light intensity PA (F = 0.82, P = .44), moderate intensity PA (F = 1.19, P = .31), and vigorous
intensity PA (F = 2.93, P = .05) did not differ among V1, V4, and V5. However, MET-hr·wk–1 from the PPAQ Q8 did differ among V1, V4, and V5 (F = 3.57, P = .03) such that MET-hr·wk–1 on V1 was lower than MET-hr·wk–1 onV4 (P = .009) and V5 (P = .001). Table 5 lists the ICC and SEM for subject responses on the PPAQ Q8 during V4 and V5. The ICC was .49 to .67 for each activity intensity category on the PPAQ Q8. Self-reported time spent in sedentary activities and in light, moderate, and vigorous intensity PA produced SEM values that were 1.0 to 2.0%.
Discussion To the best of our knowledge, this STOMP substudy was the first to examine the criterion and predictive validity and test–retest reliability of the PPAQ Q8 among healthy men and women across the life span. The results of this STOMP substudy revealed PA reported on Q8 was associated with numerous measurements from an Actical accelerometer, VO2max, and other health-related fitness outcomes, indicating good criterion and predictive validity. Furthermore, PA assessed by the PPAQ Q8 demonstrated acceptable test–retest reliability when measured 3 and 6 months from baseline.
Study 1: Validity Criterion Validity 1. In this STOMP substudy, significant positive
associations were observed among the intensity categories and MET-hr·wk–1 on the PPAQ Q8 and the Actical accelerometer (Table 2) measurements, ranging from r = .15 to .20. Although these correlations are relatively weak, they are consistent with the magnitude of the correlations reported in the existing literature examining the validity of other well-validated and popular questionnaires compared with accelerometer measurements.8,26–28 For instance, Strath et al reported correlations among self-reported PA on the PPAQ PA index and PA measured using the simultaneous HR motion sensor technique ranging from r = .20 to .47 among men and women 20 to 56 years of age.8 Similarly, Wolin et al found correlations ranging from r = .26 to .36 among self-reported PA on
120
* P < .05, ** P < .01.
Steps Counts (d–1) Energy expenditure (kcal×d–1) Sedentary (min×d–1) Light intensity (min×d–1) Moderate intensity (min×d–1) Vigorous intensity (min×d–1)
(d–1)
Actical measurement –.02 (–.15, .05) .04 (–.08, .12) –.03 (–.16, .04) .20** (.14, .33) –.24** (–.36, –.16) –.14* (–.25, –.06) .04 (–.04, .16)
Sedentary –.07 (–.17, .03) –.09 (–.17, .03) –.07 (–.17, .03) .03 (–.07, .13) .02 (–.09, .11) –.07 (–.17, .03) .01 (–.12, .08)
Light intensity .04 (.00, .20) –.03 (–.11, .09) .06 (–.00, .20) –.24** (.19, 3.77) .27** (.19, .34) .15** (.11, .30) –.11* (–.14, .05)
Moderate intensity
.10* (–.01, .19) .15** (.02, .22) .07 (.02, .22) –.09 (–.23, –.04) .03 (–.01, .19) .11* (.05, .24) .20** (–.01, .19)
Vigorous intensity
.07 (.02, .22) .01 (–.067, .13) .07 (.02, .22) –.24** (–.39, –.20) .26 (.20, .40) .17** (.13, .33) –.01 (–.13, .07)
MET· hr/wk
Table 2 Spearman Rank-Order Correlations (95% Confidence Intervals) Among Intensity Categories and MET-hr·wk–1 on the Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) and the Actical Accelerometer
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Question 8 of the Paffenbarger Questionnaire 121
Table 3 Spearman Rank-Order Correlations (95% Confidence Intervals) Among Subject Responses on the Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) Completed During Visit 1 and Visit 4, Visit 4 and Visit 5, and Visit 1 and Visit 5 PPAQ Q8 activity intensity category
Visit 1 vs. Visit 4*
Visit 4 vs. Visit 5*
Visit 1 vs. Visit 5*
.39 (.33, .51) .26 (.17, .36) .46 (.41, .59) .43 (.25, .43) .50 (.43, .60)
.49 (.36, .54) .34 (.23, .42) .46 (.35, .52) .54 (.41, .58) .61 (.52, .68)
.43 (.43, .60) .27 (.17, .36) .37 (.29, .47) .45 (.22, .40) .47 (.39, .56)
Sedentary Light intensity Moderate intensity Vigorous intensity MET-hr·wk–1 Note. For all variables, * P = .000.
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Table 4 Time (hr·d–1) (Mean ± SEM) Spent in Each Physical Activity Intensity Category Reported on Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) on Visit 1, Visit 4, and Visit 5 PPAQ Q8 physical activity intensity category
Visit 1 (hr·d–1)
Visit 4 (hr∙d–1)
Visit 5 (hr∙d–1)
Sedentary Light intensity Moderate intensity Vigorous intensity MET-hr·wk–1
13.4 ± 3.0 5.4 ± 2.5 3.8 ± 2.3 1.4 ± 1.2 343.9 ± 77.9*
13.1 ± 2.8 5.5 ± 2.5 3.8 ± 2.2 1.6 ± 1.5 354.2 ± 81.2
13.0 ± 2.7 5.6 ± 2.4 3.9 ± 2.3 1.5 ± 1.4 355.3 ± 80.3
* For MET-hr·wk–1, V1 vs. V4 and V1 vs. V5, P < .05.
Table 5 Reliability of Intensity Categories on the Paffenbarger Physical Activity Questionnaire Question 8 (PPAQ Q8) Intraclass correlation (95% CI)a
SEM
.71 (.61, .74) .49 (.38, .59) .61 (.52, .68) .67 (.59, .72)
1.9 2.0 1.7 1.0
Sedentary Light intensity Moderate intensity Vigorous intensity
Abbreviations: CI, confidence interval; SEM, standard error of measurement. a Intraclass correlations calculated between V1, V2, and V3.
the short version of the International Physical Activity Questionnaire and PA measured with an Actical accelerometer among healthy African American men and women aged 24 to 70 years.27 Finally, Hagstromer et al and Boon et al reported fairly weak correlations among self-reported PA on the International Physical Activity Questionnaire and PA measured by the Actigraph accelerometer ranging from r = .14 to .27 and r = .19 to .30, respectively.26,28 Therefore, our results compare quite favorably to the existent literature and indicate adequate criterion validity of the PPAQ Q8 among healthy men and women over 20 years of age. It has been suggested that accelerometers worn on the hip may underestimate PA performed because of their inability to detect upper body motions and the inability of the subject to wear the device while swimming.20 This imperfect validity of accelerometers may have influenced our results by underestimating the real validity of Q8. In other words, if the Actical had perfect validity, the validity coefficients for Q8 reported in this study probably would have been higher. Predictive Validity. Significant correlations were also observed
among the intensity categories and MET-hr·wk–1 on the PPAQ Q8 and the various health/fitness measurements ranging from r = –.27 to .20. Although these correlations are weak, they are consistent
with the magnitude of correlations reported in the literature examining the validity of questionnaires compared with health/ fitness measurements.15,27 For instance, Washburn et al found weak but significant correlations among self-reported energy expenditure on the PPAQ PA index and HDL cholesterol (r = .14) and BMI (r = –.13) among men and women 25 to 65 years old.15 Graff-Iversen et al also reported weak, yet significant correlations among self-reported PA on the long version of the International Physical Activity Questionnaire and health-related fitness outcomes (eg, BMI, HDL cholesterol, waist/hip ratio, TG, diastolic BP, and glucose), ranging from r = –.14 to .12 among men and women 31 to 67 years old.27 Therefore, the results of this STOMP substudy are in agreement with previous studies in the literature and indicate acceptable predictive validity of the PPAQ Q8 among healthy men and women over 20 years old.
Study 2: Test–Retest Reliability Test–Retest Reliability. Medium strength, positive correlations ranging from r = .27 to .60 were observed among self-reported time (hr·d–1) spent in each exercise intensity category and MET hr·wk–1 reported on the PPAQ Q8 between V1 and V4, V4 and V5, and V1 and V5 (Table 4). In addition, ANCOVA revealed time (hr·d–1) spent
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122 Simpson et al
in each intensity category on PPAQ Q8 did not significantly differ among V1, V4, and V5 (P > .05). These findings are consistent with the results of other previously published studies.5,7 For instance, Ainsworth et al reported similar reliability over an 8- and 9-month time period for the PPAQ physical activity index (r = .34 and r = .43, P < .05) among healthy men and women of similar age to subjects in this STOMP substudy.7 Richardson et al reported similar observations regarding the 1-month test–retest reliability of the Stanford 7-day recall among 78 healthy men and women (r = .60 and r = .36, P < .05, respectively) 21 to 59 years of age.5 Therefore, the results of this STOMP substudy are consistent with the literature and indicate satisfactory test–retest reliability of the PPAQ Q8 over 3 and 6 months among healthy adults over 20 years old. The time period between test and retest (ie, between the first and second and first and third administrations of the PPAQ Q8) was relatively long (3 and 6 mo). Therefore, it is possible that some subjects actually changed their PA habits during test and retest periods, lowering the reliability coefficients. The PPAQ is a commonly used questionnaire in large, epidemiological studies examining the relationships between habitual PA and health. The results of this STOMP substudy provide novel evidence that, among healthy men and women over 20 years, the PPAQ Q8 has adequate criterion validity, acceptable predictive validity, and satisfactory test–retest reliability. The results of this substudy expand the PPAQ’s utility for researchers and health/fitness professionals to assess habitual participation in exercise among healthy men and women across the life span.
Study Limitations and Strengths This study is potentially limited by several factors. The data used in this study were collected at multiple test sites, increasing the chances of site and interpretation bias occurring during the data collection and entry processes. However, investigators at each of the 3 sites followed a strict standard protocol for collecting data as well as for interpreting subject responses on the PPAQ during data entry. These actions likely decreased the amount of site and interpretation bias that may have occurred. In addition, only individuals who were identified as “healthy,” according to the inclusion/exclusion criteria of the STOMP study, who could exercise vigorously on a treadmill, and who were willing to take either Lipitor or placebo for 6 months participated in STOMP. As a result, the sample used in this study was self-selected as opposed to a true random sample. This might have biased our findings. There are several strengths to this study. First, previously published studies assessing the ability of questionnaires to measure and assess participation in PA sometimes focus on only 1 dimension of validity. Moreover, questionnaire validation studies oftentimes neglect to examine the test–retest reliability of the questionnaire altogether. This study assessed concurrent and predictive validity as well as the test–retest reliability of the PPAQ Q8. Therefore, the results of this study provide more complete and accurate evidence that the PPAQ Q8 is indeed a valuable tool for assessing participation in PA. Second, this study used data collected from a large sample (n = 240) of healthy men and women. The sample used in this study was larger and covered a wider age range (20–81 y) than a number of other studies in the literature examining the validity and/or test–retest reliability of other PA questionnaires.3,17 The larger sample size and wider age range used in this study allows the findings/conclusions to be generalized to a larger group of people.
Acknowledgments This work was supported by a grant (R01HL081893-01A2) from the United States National Institutes of Health.
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