Validity of the international physical activity questionnaire and the Singapore prospective study program physical activity questionnaire in a multiethnic urban Asian population

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Validity of the international physical activity questionnaire and the Singapore prospective study program physical activity questionnaire in a multiethnic urban Asian population
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  RESEARCH ARTICLE Open Access Validity of the international physical activityquestionnaire and the Singapore prospectivestudy program physical activity questionnaire in amultiethnic urban Asian population Ei Ei Khaing Nang 1 , Susan Ayuko Gitau Ngunjiri 1 , Yi Wu 1 , Agus Salim 1 , E Shyong Tai 1,2 , Jeannette Lee 1 andRob M Van Dam 1,2,3* Abstract Background:  Physical activity patterns of a population remain mostly assessed by the questionnaires. However,few physical activity questionnaires have been validated in Asian populations. We previously utilized a combinationof different questionnaires to assess leisure time, transportation, occupational and household physical activity in theSingapore Prospective Study Program (SP2). The International Physical Activity Questionnaire (IPAQ) has beendeveloped for a similar purpose. In this study, we compared estimates from these two questionnaires with anobjective measure of physical activity in a multi-ethnic Asian population. Methods:  Physical activity was measured in 152 Chinese, Malay and Asian Indian adults using an accelerometerover five consecutive days, including a weekend. Participants completed both the physical activity questionnaire inSP2 (SP2PAQ) and IPAQ long form. 43subjects underwent a second set of measurements on average 6 monthslater to assess reproducibility of the questionnaires and the accelerometer measurements. Spearman correlationswere used to evaluate validity and reproducibility and correlations for validity were corrected for within-personvariation of accelerometer measurements. Agreement between the questionnaires and the accelerometermeasurements was also evaluated using Bland Altman plots. Results:  The corrected correlation with accelerometer estimates of energy expenditure from physical activity wasbetter for the SP2PAQ (vigorous activity: r = 0.73; moderate activity: r = 0.27) than for the IPAQ (vigorous activity: r= 0.31; moderate activity: r = 0.15). For moderate activity, the corrected correlation between SP2PAQ and theaccelerometer was higher for Chinese (r = 0.38) and Malays (r = 0.57) than for Indians (r = -0.09). Bothquestionnaires overestimated energy expenditure from physical activity to a greater extent at higher levels of physical activity than at lower levels of physical activity. The reproducibility for moderate activity (accelerometer: r= 0.68; IPAQ: r = 0.58; SP2PAQ: r = 0.55) and vigorous activity (accelerometer: 0.52; IPAQ: r = 0.38; SP2PAQ: r = 0.75)was moderate to high for all instruments. Conclusion:  The agreement between IPAQ and accelerometer measurements of energy expenditure from physicalactivity was poor in our Asian study population. The SP2PAQ showed good validity and reproducibility for vigorousactivity, but performed less well for moderate activity particularly in Indians. Further effort is needed to developquestionnaires that better capture moderate activity in Asian populations. * Correspondence: ephrmvd@nus.edu.sg 1 Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of SingaporeFull list of author information is available at the end of the article Nang  et al  .  BMC Medical Research Methodology   2011,  11 :141http://www.biomedcentral.com/1471-2288/11/141 © 2011 Khaing Nang et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the srcinal work is properly cited.  Background Globally, non communicable diseases (NCDs), consistingmainly of cardiovascular diseases, cancers, chronicrespiratory diseases and diabetes make up to 60% of alldeaths [1]. WHO projects that NCD deaths will increaseby 17% over the next ten years with the highest absolutenumber of deaths occurring in Asia [1]. Physical inactiv-ity has been identified as a modifiable shared risk factorfor NCDs [1]. Although the health benefits of physicalactivity in preventing cardiovascular diseases, type 2 dia-betes, several cancers, and even poor mental health hasbeen well established, the level of physical activity hasbeen declining in many countries [2]. This may be dueto several factors including increased reduced occupa-tional and household activity due to mechanization andreduced transport activity due to replacement of walkingand cycling by transport using -cars, trains and buses.Leisure time activity may have increased due to greaterpopularity of sports activities or decreased due to moretime spend on TV, computer games and the internet.However in order to describe, monitor and possibly implement effective interventions for physical activity itis important to measure activity levels accurately andacross multiple domains of physical activity (transporta-tion, leisure-time, occupational and household) withinthe population studied.There are different methods for assessing physicalactivity. These include criterion methods such as doubly labeled water, indirect calorimetry, and direct observa-tion; objective methods such as heart rate monitor, ped-ometer, accelerometer; and subjective methodsincluding questionnaires and activity diaries [3-6]. How- ever, the instrument used in large scale epidemiologicalstudies has generally been the questionnaire because of low cost, ease of administration and relative ease of cal-culating energy expenditure [7].The International Physical Activity Questionnaire(IPAQ) was designed to provide a set of well-developedinstruments that can be used internationally to obtainestimates of physical activity that can be comparedacross different populations [8]. In order to interpret thefindings from these questionnaire-based studies, it isimportant that the questionnaire is validated againstobjective assessments in the population of interest. TheIPAQ has been validated in multiple populations, butwithin Asia only the Japanese and Hong Kong Chinesepopulation have been studied [8-10]. In addition, the Japanese validation study only evaluated total physicalactivity and not the ability of IPAQ to differentiatebetween moderate and vigorous activity [8]. The two validation studies conducted in Hong Kong Chinesereported inconsistent results [9,10]. Thus, we would like to assess the measurement properties of IPAQ separately for moderate and vigorous activity in Singa-pore, a developed urban multi-ethnic Asian country.Between 2003 and 2007 we conducted a population-based study, the Singapore Prospective Study Program(SP2) [11], which collected data on physical activity. TheSP2 Physical Activity questionnaire (SP2PAQ) wasadapted from several established questionnaires devel-oped in Western nations [12-14] to assess transporta- tion, occupation, leisure time and household activities.The ability of the SP2PAQ and the IPAQ, whichassesses similar domains of physical activity, to assessphysical activity in Asian populations has not been eval-uated. This is important because the validity of otherphysical activity questionnaires used in Asian populationsuch as the questionnaire in the Shanghai physical activ-ity study had limited validity for moderate-to-vigorousintensity (spearman correlation of 0.17)[15].The aim of this study was to assess the validity of IPAQ long form in a multi-ethnic population of Chi-nese, Malays, and Indians living in Singapore and com-pares it against the SP2PAQ using accelerometermeasurements as the reference instrument. Methods Study population We studied 164 participants, aged above 21 years. Thesewere mainly students and staff from local university andhospital. Ethics approval was obtained from the NationalUniversity of Singapore Institutional Review Board (NUSIRB). Written informed consent was obtained from allparticipants. One participant withdrew from the study after 2 days. Hence, 163 participants completed the study. Procedures Anthropometric measurements were taken (height tothe nearest 0.1 cm and weight to the nearest kg). Parti-cipants then completed one of the two evaluated ques-tionnaires (SP2PAQ or IPAQ) before the physicalactivity monitoring period. Physical activity was moni-tored using an Actical accelerometer for five consecutivedays including 3 weekdays and 2 weekend days. Partici-pants were instructed to wear the accelerometer for allwaking hours except during water-based activities. Aftercompletion of the five- day monitoring period, partici-pants returned the accelerometer and completed theremaining questionnaire. The first 120 participantsanswered IPAQ before the monitoring period andSP2PAQ immediately after the monitoring period. Theorder of the questionnaires was reversed for the last 43participants to evaluate whether the order of question-naire assessment may have affected the results.Of the 163 participants, 52 participants were re-recruited to test reproducibility of the questionnaires Nang  et al  .  BMC Medical Research Methodology   2011,  11 :141http://www.biomedcentral.com/1471-2288/11/141Page 2 of 11  and the accelerometer. The reproducibility of the accel-erometer was evaluated at the same time as the ques-tionnaires were administered using the same device inboth periods. The mean interval between the two assess-ments was 175 days (SD = 64 days) with minimum 63days and maximum 308 days. Physical activity questionnaires The 8 versions of International physical activity ques-tionnaire (IPAQ) were developed by an InternationalConsensus Group between 1997 and 1998. These weredeveloped as an instrument for cross-national monitor-ing of physical activity with a recall period of 7 days. In2000, the reliability and validity of the questionnaireswere evaluated in 12 countries and the result was pub-lished in 2003, which showed acceptable reliability and validity [8,16]. Since its development, it has been vali- dated in different populations and also widely used inresearch studies [10,17-19]. The self-administered IPAQ  long form covers four domains of physical activity: jobrelated activity; transportation activity; housework,house maintenance, and caring for family; and recrea-tion, sports, and leisure-time physical activity. For eachdomain, the time spent on moderate and vigorous activ-ity per day and the numbers of days per week wererecorded. Walking time was asked in all domains excepthousehold activity. In addition, time spent sitting onweekday and weekend was also recorded.The physical activity questionnaire used in SingaporeProspective Study Program (SP2PAQ) is an interviewer-administered questionnaire with a recall period of theprevious 3 months. As mentioned before it was adaptedfrom several established questionnaires validated inother populations [12-14] and encompassed transporta- tion, occupation, leisure time and household activities.The questions on transportation activity were adaptedfrom National Health Survey 2004 questionnaire [20]which asked about walking or cycling for transport forat least 10 minutes. The duration, frequency and theintensity of the activity (light, moderate, or vigorous)were recorded. Questions on occupational activity werebased on the validated Modifiable Activity Question-naire [13,21]. Participants were asked to list all jobs held during the past 3 months. For each job entry, data wascollected for the job schedule and job activity was deter-mined by the number of hours spent sitting at work andthe most common physical activities performed whennot sitting. Leisure time activity was adapted from theMinnesota leisure time activity questionnaire covering atotal of 48 specific activities and open questions aboutpossible other activities which has been validated in var-ious populations [14,22-24]. For each activity, partici- pants identified the frequency and the average durationof participation in each activity. Household activity wasadapted from the Yale physical activity questionnairewhich covers housework, yard work and caretaking forelderly persons or children and has been validated indiverse populations [12,25,26]. Participants were asked about the type of activity performed and the frequency and duration of each activity. The SP2PAQ can befound in additional file 1. Actical physical activity monitor Objective measurement of physical activity was obtainedby using the Actical ® physical activity monitor (MiniMitter Co., Inc., Bend, OR) which is a water resistant,lightweight (17 g) and small (28 × 27 × 10 mm) device.The monitors are initialized and downloaded throughthe ActiReader PC serial port interface. According tomanufacturer, the Actical is an omnidirectional, piezo-electric accelerometer, which is able to detect move-ments in all directions. It is sensitive to movements inthe range of 0.5-3 Hz and its sensitivity allows for detec-tion of sedentary movement as well as high-energy movements. Its reduced frequency range also minimizesthe effect of undesirable noise impulses, which tend toskew energy expenditure [27]. The Actical accelerometerhas been validated previously showing good reliability and accuracy for estimating the energy expenditurefrom physical activity and the time spent in moderateand vigorous physical activity [28,29] and has been used in epidemiological studies [30]. The physical activity intensity prediction of the Actical accelerometer was validated with a room calorimeter. This showed that dif-ferences between the measurements of the Actical accel-erometer and the calorimeter for the time spent in eachmoderate and vigorous intensity activity was < 2%[31].Compared to ankle and wrist, hip was the best loca-tion for monitor placement to predict the energy expen-diture from physical activity when validated against withVmaxST portable metabolic system (R = 0.90)[32]. Forthis study, all participants wore the Actical acceler-ometer on the right hip, just anterior to iliac crest withelastic belt. The device was initialized using 15-s epochsand converted to 1-min epochs for data analysis of energy expenditure.The quality of the devices was monitored by checkingthe coefficient of variation (CV) of the devices monthly [33]. All the devices were placed on the mechanical sha-ker for 12 hours and the CV was calculated by dividingthe standard deviation of activity counts with the meanof activity counts captured by the devices. The CVs dur-ing the study period were acceptable, ranging from10.2% to 16.6%. Calculation of Energy Expenditure from Physical Activity For IPAQ, we used the IPAQ data processing rules [34]for our calculations. The data was truncated at 21 hours Nang  et al  .  BMC Medical Research Methodology   2011,  11 :141http://www.biomedcentral.com/1471-2288/11/141Page 3 of 11  per week for each of the following groups of activities:walking activity, other moderate activity, and vigorous[34]. Subsequently, walking activity and other moderateactivity were combined to derive total moderate activity.Metabolic equivalent task (MET) levels were obtainedfrom the IPAQ scoring protocol [34] for the IPAQ ques-tionnaire and from the compendium by Ainsworth et al[35] for the SP2PAQ questionnaire. One MET unit isdefined as the energy expenditure for sitting quietly,which for the average adult is approximately 3.5 ml of oxygen × kg bodyweight -1 × min -1 or 1 kcal × kg body weight -1 × h -1 [35]. For both questionnaires, minuteswere converted to hours and weekly energy expenditurefrom each physical activity (Kcal/week) was calculatedas follows: hours spent on activity per day × numbers of days per week × MET value × body weight in kg[36,37]. Then the energy expenditures from all the activ- ities under each intensity category were combined toobtain the total energy expenditure per week for eachmoderate and vigorous intensity category. Moderateintensity was defined as 3 to 6 METs and vigorousintensity was defined as more than 6 METs [38].The resulting measures from the two questionnairesexpressed in Kcal per week were divided by 7 and thetotal Kcal for each moderate and vigorous intensity cate-gory from accelerometer for 5-day wearing period wasdivided by 5, to derive average Kcal per day for allmethods.The Actical accelerometer recorded physical activity ina series of activity counts which were proportional tothe magnitude and duration of the sensed accelerations.The raw minute-by-minute activity counts were thentransformed into energy expenditure by the computerprogram using MET prediction algorithms of Klippel etal [32]. The output of the program included data of energy expenditure (Kcal/day) and time spent on light,moderate and vigorous activity with cutoff points of 3METs between light and moderate activity and 6 METsbetween moderate and vigorous activity. In this study,we used 2R regression to estimate energy expenditurefrom physical activity, which exhibits a decreased ten-dency to over predict energy expenditure [27]. Statistical Analysis The accelerometer data was considered valid only when10 or more hours of data per day were collected for fivedays. Thus, 8 participants were excluded because they did not meet this criterion. In addition, 3 participantswho reported the sum total of all walking, moderate and vigorous time more than 16 hours per day in IPAQ were treated as outliers and excluded from analysisaccording to IPAQ data processing rule [34]. As a result,152 participants were included in the analysis and 43participants for reproducibility analysis. The correlationsbetween estimates of energy expenditure from physicalactivity assessed by the accelerometer and estimatesassessed by questionnaires were obtained by the Spear-man rank correlation test. Because correlations betweenthe questionnaires and the reference instrument (i.e. theaccelerometer) are interpreted as measures of the accu-racy of the questionnaires, it is desirable to correct forlimitations of the reference instrument that reduce thesecorrelations. Thus we calculated correlation coefficientscorrected for within-person variation in the acceler-ometer measurements using the formula suggested by Beaton et al [39]. r  t   = r  0   1+  λ accelerometer naccelerometer  wherer t  =  “ true ”  correlation coefficientr 0  = observed correlation coefficient λ accelerometer = 1 − ICCaccelerometer ICCaccelerometer  where ICC accelerometer  = interclass correlation coeffi-cient of accelerometern accelerometer  = number of repeated accelerometer mea-surements within-subjectThe 95% and 99.99% confidence intervals for correc-tion correlations were calculated using the formulas sug-gested by Willett et al [40]. In addition, a Bland-Altmanplot was created for the agreement between the ques-tionnaires and the accelerometer measurement. Thereliability of the questionnaires was evaluated usingSpearman rank correlation coefficients. All statisticalanalyses were performed using Stata 10 for Windows(Stata Corporation, College station, Texas, USA). Results The study population (N = 152) had mean age of 38.3 years and mean BMI of 24.54 kg/m 2 . The majority of participants had a job, but there were also students,homemakers, retired and unemployed participants.Nearly 70% had a higher education while 21% achievedsecondary education and less than 10% had no educa-tion or primary level. There was a large variation inhousehold income among participants (Table 1).Additional file 2 shows the correlation between theIPAQ and SP2PAQ. The two questionnaires showedreasonable correlation with each other for moderateactivity (r = 0.55), but a low correlation for vigorousactivity (r = 0.27). Table 2 presents data on the Spear-man rank correlation between energy expenditure fromphysical activity assessed using questionnaires and theaccelerometer. In general, correlations were higher for vigorous activity than moderate activity and higher for Nang  et al  .  BMC Medical Research Methodology   2011,  11 :141http://www.biomedcentral.com/1471-2288/11/141Page 4 of 11  the SP2PAQ than for the IPAQ. The correlationsbetween the IPAQ and accelerometer were 0.13 formoderate activity, 0.18 for vigorous activity, and 0.19 formoderate and vigorous activity combined. These corre-lations remained low after correction for within-person variation in the accelerometer measurements; the cor-rected correlation was 0.15 for moderate activity wasand 0.31 for vigorous activity. The correlation for theSP2PAQ was 0.24 for moderate activity, 0.42 for vigor-ous activity, and 0.28 for moderate and vigorous activity combined. Correction of these correlation coefficientsfor within-person variation in the accelerometer mea-surements increased the correlation only slightly formoderate activity (r = 0.27), but substantially for vigor-ous activity (r = 0.73). No substantial difference in cor-relation between the questionnaires and accelerometerwas observed according to the order of the question-naire assessments (i.e. before or after the accelerometerassessment) (data not shown).The validity of the questionnaires was further assessedby stratifying the study population according to age,gender, and ethnic group. Compared with the youngerage group, the correlation between the energy expendi-ture from physical activity assessed by questionnaire andaccelerometer in the older group tended to be higherfor moderate activity, but lower for vigorous activity.This was observed for both questionnaires. The correla-tion was higher in men for both moderate and vigorousactivity when the IPAQ was used, whereas the correla-tion was higher in women than men for moderate activ-ity when the SP2PAQ was used.The performance of the SP2PAQ was similar in allthree ethnic groups for vigorous activity, but for moder-ate activity, Malays showed a higher correlation withaccelerometer measurements than Chinese and particu-larly Indians. For the IPAQ, reasonable correlationswere only observed with the accelerometer in Chinesefor moderate activity and Indians for vigorous activity.The agreement between the questionnaires and theaccelerometer was also evaluated using Bland-Altmanplots. Both IPAQ and SP2PAQ underestimated averageenergy expenditure from moderate activity, but overesti-mated average energy expenditure from vigorous activity as compared with the accelerometer. The mean differ-ence of daily energy expenditure between the measure-ments of IPAQ and accelerometer for moderate activity was -169 Kcal/day (95%CI: -236 to -90) and that of between SP2PAQ and accelerometer was -196 Kcal/day (95% CI: -295 to -97). SP2PAQ showed good agreementwith the accelerometer for moderate activity when theenergy expenditure was below approximately 1200 Kcalper day. However, it tended to overestimate energy expenditure when energy expenditure increased abovethat level (Figure 1). For vigorous activity, the mean dif-ference of daily energy expenditure between the mea-surements of the IPAQ and accelerometer was 139 Kcalper day (95% CI: 82 to 196) and that of betweenSP2PAQ and accelerometer was 81 Kcal per day (95%CI: 47 to 116). For vigorous activity, both questionnairesshowed good agreement with the accelerometer forenergy expenditure below approximately 400 Kcal perday. However, the higher the energy expenditure abovethat level, the greater was the degree of overestimationof the questionnaires (Figure 2).The reproducibility of the two questionnaires and theaccelerometer was also evaluated (Table 3). IPAQ hadhigher reproducibility for moderate activity, but lower Table 1 Socio-demographic characteristics of studypopulation N = 152 Age(years), mean ± SD 38.30 ± 12.86Body Mass Index(kg/m 2 ), mean ± SD 24.54 ± 4.64 Age group (N, %) ≤  40 years 87(57.24)> 40 years 65(42.76) Gender (N, %) Male 64(42.11)Female 88(57.89) Ethnicity (N, %) Chinese 66(43.42)Malay 34(22.37)Indian 52(34.21) Highest level of education (N, %) None/primary 13(8.55)Secondary 32(21.05) Technical school/diploma 42(27.63)University 65(42.76) Work status (N, %) Working 98(64.47)Student 33(21.71)Homemaker 17(11.18)Retired 3(1.97)Unemployed 1(0.66) Household income(S$/month) (N, %) Less than $2000 27(17.76)$2000 to $3999 40(26.32)$4000 to $5999 37(24.34)$6000 to $9999 27(17.76)More than $ 10 000 19(12.5)Decline to answer 2(1.32) Nang  et al  .  BMC Medical Research Methodology   2011,  11 :141http://www.biomedcentral.com/1471-2288/11/141Page 5 of 11
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