Open Access

A systematic review of reliability and objective criterion-related validity of physical activity questionnaires

  • Hendrik Hendrik JF Helmerhorst1, 2,
  • Søren Brage1,
  • Janet Warren3, 4,
  • Herve Besson1 and
  • Ulf Ekelund1, 5Email author
International Journal of Behavioral Nutrition and Physical Activity20129:103

DOI: 10.1186/1479-5868-9-103

Received: 19 February 2012

Accepted: 15 August 2012

Published: 31 August 2012

Abstract

Physical inactivity is one of the four leading risk factors for global mortality. Accurate measurement of physical activity (PA) and in particular by physical activity questionnaires (PAQs) remains a challenge. The aim of this paper is to provide an updated systematic review of the reliability and validity characteristics of existing and more recently developed PAQs and to quantitatively compare the performance between existing and newly developed PAQs.

A literature search of electronic databases was performed for studies assessing reliability and validity data of PAQs using an objective criterion measurement of PA between January 1997 and December 2011. Articles meeting the inclusion criteria were screened and data were extracted to provide a systematic overview of measurement properties. Due to differences in reported outcomes and criterion methods a quantitative meta-analysis was not possible.

In total, 31 studies testing 34 newly developed PAQs, and 65 studies examining 96 existing PAQs were included. Very few PAQs showed good results on both reliability and validity. Median reliability correlation coefficients were 0.62–0.71 for existing, and 0.74–0.76 for new PAQs. Median validity coefficients ranged from 0.30–0.39 for existing, and from 0.25–0.41 for new PAQs.

Although the majority of PAQs appear to have acceptable reliability, the validity is moderate at best. Newly developed PAQs do not appear to perform substantially better than existing PAQs in terms of reliability and validity. Future PAQ studies should include measures of absolute validity and the error structure of the instrument.

Keywords

Systematic review Physical activity Self-report Accelerometry Validity Reliability

Background

Physical inactivity is considered to be one of the four leading risk factors for global mortality [1]. The measurement of physical activity is a challenging and complex procedure. Valid and reliable measures of physical activity (PA) are required to: document the frequency, duration and distribution of PA in defined populations; evaluate the prevalence of individuals meeting health recommendations; examine the effect of various intensities of physical activity on specific health parameters; make cross-cultural comparisons and evaluate the effects of interventions [2].

Physical activity questionnaires (PAQs) are often the most feasible method when assessing PA in large-scale studies, likely because of their low cost and convenience but these instruments have limitations and should be selected and used judiciously. PAQs are prone to measurement error and bias due to misreporting, either deliberate (social desirability bias) or because of cognitive limitations related to recall or comprehension [3, 4]. Cognitive immaturity or degeneration can make self-report of physical activity particularly difficult in the young and elderly [5, 6]. Despite more frequent use of objective assessment methods to measure physical activity, PAQs still provide a practical method for PA assessment in surveillance systems, for risk stratification and when examining etiology of disease in large observational studies. Most PAQs are designed to be able to measure multiple dimensions of PA by reporting type, location, domain and context of the activity, provide estimates of time spent in activities of various levels of intensity, and may be able to rank individuals according to intensity levels of reported activity [7, 8]. However, results from studies aimed at evaluating the validity of PAQs assessed in one population cannot be systematically extrapolated to other populations, ethnic groups, or other geographical regions. Consequently, a great variety of PAQs have been developed and tested for reliability and validity in recent years.

A comprehensive review of PAQs for use in adults was published in 1997 [9]. Since then, reviews summarizing the validity and reliability of PAQs have been carried out in children [1012] and preschoolers [13]. Recently, specific reviews were published assessing the quality of PAQs available for children [11], adults [14] and the elderly [15]. The aim of the present study was to systematically review the literature on reliability of PAQs as well as their validity evaluated against objective criterion methods, for use in all age groups, published between January 1997 and December 2011 to quantitatively compare the performance between existing and newly developed PAQs.

Methods

Inclusion criteria

Studies meeting all of the following inclusion criteria were included: (i) published in the English language between January 1997 and December 2011; (ii) self- or interviewer-administered PAQs or parental proxy reports reporting both reliability and validity results; (iii) PAQs reporting validity results only, when the reliability data has been published previously; (iv) PAQs developed for a healthy general population and for observational surveillance studies; (v) PAQs tested in its original form or in an adapted version if results were reported for validity and reliability or validity only, when reliability results were published before; (vi) validity tested against an objective criterion measure of PA (i.e. accelerometry, heart rate, combined heart rate and accelerometry, doubly labeled water (DLW)); (vii) results on validity obtained by pedometer where the questionnaire was specifically developed to assess walking only.

Exclusion criteria

We excluded studies that reported: (i) reliability and validity results in groups with specific clinical or medical conditions (except pregnancy); (ii) results from PAQs that were designed for specific intervention studies; (iii) results where the validity of the PAQ was tested against another self-report method (i.e. diaries, logs); (iv); results on validity using pedometers (except if walking only was tested) and indirect measures of physical activity (e.g. VO2max and body composition); (v) results on essential adaptations of original PAQs, without any published results on both reliability and validity.

Literature search

The PubMed, Medline and Web of Science databases were systematically searched using the following lists and terms:

List A: (physical activity AND health survey OR population survey OR question*)

List B: List B: measure* (i.e. measures, measurement), assess* (i.e. assessment, assessed), self-report, exercise, valid* (i.e. valid, validation, validity), reliab* (i.e. reliable, reliability), reproducible, accelerometer, heart rate, doubly labelled water, doubly labeled water. The search included titles, abstracts, key words and full texts.

Key search terms in List A were combined with each of the terms in List B.

The literature search was undertaken in two stages. The original literature search (1997–2008) was undertaken by two of the authors (JW, HB) independently and search results were compared and verified. The literature search was then updated to include studies up to December 2011 using exactly the same search criteria (HH). A second search strategy included screening references lists of publications that matched the inclusion criteria and any other publications of which the authors were aware but did not show up during the original literature search. Figure 1 displays an overview of the literature search.
https://static-content.springer.com/image/art%3A10.1186%2F1479-5868-9-103/MediaObjects/12966_2012_Article_635_Fig1_HTML.jpg
Figure 1

Overview of the literature search.

Data collection and extraction

Data were extracted using a standardized pro-forma which included sample characteristics, questionnaire details, methods of validity and reliability testing, test results and authors’ conclusions. We retrieved full text of articles of all abstracts that met our inclusion criteria. Any queries about the inclusion of papers were resolved by one of the authors (UE).

Reliability

Reliability in all studies was tested through a test-retest procedure to measure consistency of the PAQs. Reliability results from included studies were reported as: intraclass correlation coefficients (ICC); Pearson and Spearman correlation coefficients; and agreement measures using Cohen’s weighted kappa (κ) and mean differences. Reliability was considered poor, moderate (acceptable), or strong when correlation coefficients or kappa statistics were <0.4, 0.4–0.8 or >0.8, respectively [16]. Similarly, an ICC > 0.70 or >0.90 was considered as acceptable and strong, respectively, in those studies reporting this measure [17].

Medians of reliability correlation coefficients across studies were calculated and included in the tables when possible.

Validity

Correlation coefficients were the most commonly used measures of validity, although the Bland-Altman technique [18] which determines absolute agreement between two measures expressed in the same units, was also frequently used. The Bland-Altman method estimates the mean bias and the 95 % limits of agreement (± 2SD of the difference) and is usually plotted as the difference between the methods against the mean of the methods for visual inspection of the error pattern throughout the measurement range; the dependence of error with the underlying level can be summarised in the error correlation coefficient but this was only seldom reported.

Medians of included validity correlation coefficients were calculated and included in the tables when possible. When calculating the medians, we excluded those studies reporting correlation coefficients for the associations of self-reported sedentary time. The medians for sedentary time are reported separately and associations of sedentary time with measures of total physical activity (i.e. total energy expenditure [TEE], physical activity level [PAL] and total activity from accelerometry [mean counts]) from the criterion method were excluded in these analyses as these measures are expected to be inversely related.

Classification

Questionnaires were classified as new or existing (i.e. previously published test results) PAQ. Existing questionnaires were subdivided into those which reported new reliability and validity results, and those which reported new results on validity only but had previously reported results on reliability. Questionnaires were classified as new, when the concerning study was the first to publish reliability and objective validity data on the PAQ. Hereafter, studies were further stratified for age group of the sample. Study populations with a mean age lower than 18 years were categorised as youth, 18 – 65 years were classified as adults, and elderly above 65 years.

PAQs included

PAQ abbreviations are listed in Table 1, with their respective timeframe. The details of these studies are shown in Tables 2 (new PAQs) and 5 (existing PAQs). A range of tests were used to assess reliability and validity with some studies reporting results for a total questionnaire summary score, and others assessing reliability and validity for various aspects, intensities, or domains of the questionnaire and/or by subgroups within the test population. The total score or index for the PAQ was reported, if available. In the absence of a total score, correlation coefficients by intensity category or group are reported. Where multiple results were reported, a decision was made about the data that constituted the main results based on the stated objectives for the study or questionnaire. Several studies compared results to another questionnaire concurrently but if this was a secondary aim of the specific study, the results were not included.
Table 1

List of questionnaire abbreviations and the corresponding definitions

Acronym

Definition

Timeframe

1WPAR

One-week Physical Activity Recall

Last 7 days

7DPAR

7-Day Physical Activity Recall

Last 7 days

7DR

7-Day Recall

Last 7 days

7DR-O

7-Day Recall (occupational activity)

Last 7 days

AAFQ

Arizona Activity Frequency Questionnaire

Last 28 days

AAS

Active Australian Survey (modified version)

Last 7 days, usual week

Activitygram

Activitygram

Last 3 days

AQuAA

Activity Questionnaire for Adolescents and Adults

Last 7 days

AWAS

Australian Women's Activity Survey

Typical week last month

BAD

Bouchard Activity Diary

Last 3 days

BAQ

Baecke Activity Questionnaire

Usual activity

BAQ-mod

Baecke Activity Questionnaire (modified version)

Last year

BONES PAS

Beat Osteoporosis: Nourish and Exercise Skeletons Physical Activity Survey

Last 2 days

BRFSS PAQ

Behavioral Risk Factor Surveillance System Physical Activity Questionnaire (2001 version)

Typical week

CAPS-4WR

Cross-Cultural Activity Participation Study – 4 Weeks activity Recall

4 weeks

CAPS-TWR

Cross-Cultural Activity Participation Study – Typical Week activity Recall

Typical week

CAQ

College Alumnus Questionnaire

Last 7 days

CAQ-PAI

College Alumnus Questionnaire – Physical Activity Index

Last 7 days

CDPAQ

Computer Delivered Physical Activity Questionnaire

Previous day

CHAMPS

Community Healthy Activities Model Program for Seniors

Typical week last month

CHAMPS-MMSCV

Community Healthy Activities Model Program for Seniors (Modified Mailed Self-Complete Version)

Last 7 days

CHASE

Child Heart and Health Study in England questionnaire

Typical week

CLASS

Children's Leisure Activity Study Survey questionnaire

Typical week

CPAQ

Children's Physical Activity Questionnaire

Last 7 days

DQ-mod

Dallosso Questionnaire (modified version)

Typical day last week, typical week

EPAQ

EPIC Physical Activity Questionnaire

Last year

EPAQ-s

EPIC Physical Activity Questionnaire (short version)

Last year

EPAQ2

EPIC Physical Activity Questionnaire (second version)

Last year

FCPQ

Five City Project Questionnaire

Typical week

Fels PAQ

Fels Physical Activity Questionnaire for children

Last year

FPACQ

Flemish Physical Activity Computerized Questionnaire

Typical week

GAQ

GEMS (Girls Health Enrichment Multi-site Studies) Activity Questionnaire

Previous day, usual activity

GLTEQ

Godin Leisure-Time Exercise Questionnaire

Typical week

GPAQ

Global Physical Activity Questionnaire

Typical week

GSQ

Godin-Shephard Questionnaire

Typical week

HAQ

Harvard Alumni Questionnaire

Typical week

HBSC

Health Behaviour in School Children Questionnaire

Typical week

HEPA99

Swiss Health Enhancing Physical Activity Survey 1999

Typical week

HUNT1

Nord-Trøndelag Health Study questionnaire (version 1)

Last 7 days

HUNT2

Nord-Trøndelag Health Study questionnaire (version 2)

Last year

IPAQ

International Physical Activity Questionnaire

Last 7 days, typical week

IPAQ-A

International Physical Activity Questionnaire (modified for Adolescents)

Last 7 days

IPAQ-E

International Physical Activity Questionnaire (short version modified for Elderly)

Last 7 days

IPAQ-LC

International Physical Activity Questionnaire (Long version in Chinese)

Last 7 days

IPAQ-s

International Physical Activity Questionnaire (short version)

Last 7 days

IPAQ-SALVCF

International Physical Activity Questionnaire (Self-Administered Long Version in Canadian French)

Last 7 days

JPAC

Jackson heart Physical Activity Cohort (i.e. modified KPAS)

Last year

KPAS

Kaiser Physical Activity Survey

Last year

KPAS-mod

Kaiser Physical Activity Survey (modified version)

Current trimester

LRC

Lipid Research Clinics questionnaire

Usual activity

MAQ

Modifiable Activity Questionnaire

Last year

MARCA

Multimedia Activity Recall for Children and Adolescents

Previous day

MLTPAQ

Minnesota Leisure Time Physical Activity Questionnaire

Last year

MRPARQ

Many Rivers Physical Activity Recall Questionnaire

Typical week

NHS-PAQ

Nurses' Health Study II – Physical Activity Questionnaire

Last 7 days

OIMQ

Office In Motion Questionnaire

Last 7 days

OPAQ

Occupational Physical Activity Questionnaire

Typical week

PAAT

Physical Activity Assessment Tool

Last 7 days

PAQ-A

Physical Activity Questionnaire for Adolescents

Last 7 days

PAQ-C

Physical Activity Questionnaire for older Children

Last 7 days

PAQ-EJ

Physical Activity Questionnaire for Elderly Japanese

Typical week last month

PASE

Physical Activity Scale for the Elderly

Last 7 days

PDPAR

Previous Day Physical Activity Recall

Previous day

PMMAQ

Past Month – Modifiable Activity Questionnaire

Last month

PPAQ

Pregnancy Physical Activity Questionnaire

Current trimester

Pre-PAQ

Preschool-age Children's Physical Activity Questionnaire

Last 3 days (1 week, 2 weekend days)

PWMAQ

Past Week – Modifiable Activity Questionnaire

Last 7 days

PYTPAQ

Past Year Total Physical Activity Questionnaire

Last year

QAPSE

Questionnaire d'Activité Physique Saint-Etienne

Typical week last year

RPAQ

Recent Physical Activity Questionnaire (i.e. EPAQ2 redesigned)

Last month

RPAR

Recess Physical Activity Recall

Last recess

S7DR

Stanford 7-Day Recall

Last 7 days

SAPAC

Self-Administered Physical Activity Checklist (modified version)

Last 3 days

SBQ

Sedentary Behavior Questionnaire

Typical week

SHAPES

School Health Action, Planning Evaluation System

Last 7 days

SHS97

Swiss Health Survey 1997

Typical week

SP2PAQ

Singapore Prospective Study Program Physical Activity Questionnaire

Last 3 months

SPAQ

Scottish Physical Activity Questionnaire

Last 7 days

SSAAQ

Sub-Saharan Africa Activity Questionnaire

Last year

SUA

Stanford Usual Activity

Usual activity, last 3 months

SWAPAQ

Swedish Adolescent Physical Activity Questionnaire

Last 7 days

TCQ

Tecumseh Community Questionnaire

Last year

TOQ

Tecumseh Occupational Questionnaire

Last 7 days

WAC

Weekly Activity Checklist

Last 7 days

WHI-PAQ

Women's Health Initiative – Physical Activity Questionnaire

Last 7 days

YMCLS

Youth Media Campaign Longitudinal Survey

Last 7 days

YPAQ

Youth Physical Activity Questionnaire

Last 7 days, previous day

YPAS

Yale Physical Activity Scale

Typical week last month

YRBS

Youth Risk Behavior Survey

Last 7 days

PAEE

Physical Activity Energy Expenditure

 

TEE

Total Energy Expenditure

 

MPA

Moderate intensity Physical Activity

 

VPA

Vigorous intensity Physical Activity

 

MVPA

Moderate and Vigorous intensity Physical Activity

 

PAL

Physical Activity Level

 

MET

Metabolic Equivalent of Task

 

Acc

Accelerometry

 

HR

Heart Rate monitoring

 

DLW

Doubly Labeled Water

 

Ped

Pedometer

 

ML

Mini-Logger

 

Frequently used acronyms also included at the bottom of the table.

Table 2

Descriptive characteristics of new PAQs

Age group

Reference

Name questionnaire

Country

Domains of activity

Population

Primary outcome

     

Size

Age (years)

Sex

Ethnicity

 

Youth

Dwyer (2011)[19]

Pre-PAQ

Australia

Habitual and sedentary activities in home environment

103 reliability, 67 validity

3 - 5.9

M/F

Mainly Caucasian

Min/day

Youth

Economos (2010)[20]

BONES PAS

United States

Common activities for children

41 reliability, 40 validity

6 - 9

M/F

METs, WBF score

Youth

Martinez-Gomez (2010)[21]

RPAR

Spain

Sedentary, leisure, transportation, sports/exercise

125

12 - 14

M/F

MET-min, minutes

Youth

Philippaerts (2006)[22]

FPACQ

Belgium

Sedentary, leisure, occupation, transportation

33

12 - 18

M/F

Mainly Caucasian

Total hr/week, METs

Youth

Ridley (2001)[23]

CDPAQ

Australia

Type, duration, intensity, organization of activities before, during and after school

30

11.96 ± 0.53

M/F

METs, minutes

Youth

Ridley (2006)[24]

MARCA

Australia

Sedentary, leisure, household, occupation, transportation, sports/exercise during a school day or another day

32 reliability, 66 validity

9 - 15

M/F

PAL, EE, total time in any activity

Youth

Telford (2004)[25]

CLASS

Australia

30 physical activities over weekdays and weekends

280

5 - 6, 10 - 12

M/F

Mainly Australian born

Total min/week

Youth

Treuth (2003)[26]

GAQ, Activitygram

United States

GAQ: 28 physical, 7 sedentary usual activities. Activitygram: log of all activities in light, moderate, vigorous intensity

68

8 - 9

F

African-American

GAQ score, Activitygram score

Youth

Treuth (2005)[27]

Fels PAQ

United States

Leisure, occupation, sports/exercise

229

7 - 19

M/F

Fels PAQ scores

Youth

Welk (2007)[28]

YMCLS

United States

Free time activity, organized activity, any outside school activity

192

9 - 13

M/F

Mixed

Frequency/week, min/day

Youth

Wong (2006)[29]

SHAPES

Canada

Moderate and vigorous activity and participation in physical, sedentary activities

1636 reliability, 67 validity

Grades 6 - 12

M/F

Mixed

Min/day, EE

Adults

Ainsworth (2000)[30]

KPAS

United States

Household, occupation, sports/exercise, active living habits

50

20 - 60

F

Mainly white

KPAS activity indexes

Adults

Besson (2010)[31]

RPAQ

United Kingdom

Sedentary, leisure, household, occupation, transportation

131 reliability, 50 validity

21 - 55

M/F

MET-hr/day, PAEE (kJ/day), TEE (kJ/day)

Adults

Chasan-Taber (2004)[32]

PPAQ

United States

Sedentary, household, occupation, transportation, sports/exercise

63

16 - 40

F

Mixed

MET-hr/week

Adults

Chinapaw (2009)[33]

AQuAA

Netherlands

Sedentary, leisure, household, occupation, transportation, sports/exercise

111 reliability, 89 validity

12 - 38

M/F

MET-min/week, AQuAA score

Adults

Craig (2003)[34]

IPAQ

12 countries

Short form: sitting, walking, moderate and vigorous intensity. Long form: sedentary, leisure, household, occupation, transportation

Long form: 1880 reliability, 744 validityShort form: 1974 reliability, 781 validity.

18 - 65

M/F

Mixed

Weighted MET-min/week

Adults

Fjeldsoe (2009)[35]

AWAS

Australia

Sedentary, household, occupation, transportation, planned activities

40 reliability, 75 validity

32 ± 5

F

Total min/week for each intensity level

Adults

Friedenreich (2006)[36]

PYTPAQ

Canada

Leisure, household, occupation

154

35 - 65

M/F

MET-hr/week, total hours/week

Adults

Kurtze (2007)[37]

HUNT2

Norway

Leisure, occupation in light and hard intensity

108

20 - 39

M

Light, hard PA summary score

Adults

Kurtze (2008)[38]

HUNT1

Norway

Leisure

108

20 - 39

M

Summary index of weekly PA

Adults

Lowther (1999)[39]

SPAQ

Scotland

Leisure, occupation in moderate, hard, very hard intensity

34 reliability, 30 validity

33 ± 12, 33 ± 11 (reliability); 37 ± 11, 35 ± 14 (validity)

M/F

Total min/week

Adults

Mäder (2006)[40]

SHS97, HEPA99, IPAQ, OIMQ

Switzerland

Sedentary, leisure, household, occupation, transportation

178 reliability, 35 validity

15 - 75

M/F

Mainly Caucasian

MET-min/week, days/week, combined variable

Adults

Meriwether (2006)[41]

PAAT

United States

Leisure, household, occupation, transportation

68 reliability, 63 validity

20 - 61

M/F

Mainly white

Total min/week

Adults

Reis (2005)[42]

OPAQ

United States

Occupational sitting/standing, walking, heavy labour

41

20 - 63

M/F

MET-min/week

Adults

Rosenberg (2010)[43]

SBQ

United States

9 sedentary activities

49 reliability, 842 validity

20.4 ± 1.3 (reliability); ♀41.2 ± 8.7, ♂43.9 ± 8.0 (validity)

M/F

Mainly white

Total hr/week

Adults

Sobngwi (2001)[44]

SSAAQ

Cameroon

Leisure, occupation, walking/cycling

89 reliability, 54 acc, 89 HR

19 - 68

M/F

African

Total hr/day, MET-hr/day

Adults

Timperio (2003)[45]

1WPAR

Australia

All activities in walking, moderate, vigorous intensity

118 reliability, 122 validity

25 - 47

M/F

MET-min/day

Adults

Wareham (2002)[46]

EPAQ2

United Kingdom

Sedentary, leisure, household, occupation, transportation

399 reliability, 173 validity

40 - 74

M/F

Mixed

MET-hr/week

Adults

Wareham (2003)[47]

EPAQ-s

United Kingdom

Leisure, household, occupation, transportation

2271 reliability, 173 validity

40 - 74

M/F

Mixed

PA index, mean day PAR

Adults

Yore (2007)[48]

BRFSS PAQ (2001 version)

United States

Leisure, household, occupation, transportation

60

44.5 ± 15.7

M/F

Mixed

MPA and VPA min/week

Elderly

Yasunaga (2007)[49]

PAQ-EJ

Japan

Household, occupation, transportation, sports/exercise

147

65 - 85

M/F

Japanese

PAQ-EJ score (MET-hr/week)

Domains named in paper were reclassified, unless the activities were very different from categories used, according to the following system: Occupation: work, school, labour. Transportation: travel, commuting, employment. Household: home/life, housework, caregiving, domestic life, child/elder/self care, cooking, chores, gardening, stair climbing. Leisure: leisure, recreation time. Sports/exercise: play, sports, exercise, workout. Sedentary: sedentary behaviours, e.g. sitting, TV viewing activities, eating, sleeping, bathing, inactivity. "– = not stated, M = Male, F = Female.

Results were reported for both total score and other aspects (e.g. domain, intensity) when this substantially added to the information for the specific study, for example when total PA was tested against a different validation method than PA intensities [31]. Some questionnaires assessed sedentary behaviour and these results are specifically reported in the tables or text. Sedentary behaviour has recently been suggested to be considered distinctively from physical activity in associations with health outcomes [50].

Results

The search string (JW and HH) resulted in a total of 11098 hits. The first literature search resulted in 125 papers being retrieved for data extraction. The update of the literature review to December 2011 resulted in a further 75 papers being retrieved for data extraction (Figure 1). More than half of the papers retrieved were excluded (n = 104). The main reasons for exclusion were inappropriate criterion measures, generally a measure of aerobic fitness (n = 48), and lack of information on reliability (n = 26) or validity (n = 17) (Figure 1).

New PAQs

The description of newly developed PAQs is summarized in Table 2. The literature search found 31 articles, reporting results from 34 newly developed PAQs of which 10 were from the United States, 10 from Europe, six from Australia, two from Canada, and one study from Japan and Sub-Saharan Africa, respectively. Of note was a 12–country international study testing the International Physical Activity Questionnaire (IPAQ) [34]. This questionnaire is available in a short form for surveillance and in a longer form when more detailed physical activity information is collected. Both forms are available in a number of languages. IPAQ has been rigorously tested for reliability and validity and this has been replicated in a number of countries.

Nineteen studies tested the reliability and validity in adults, an additional 11 studies focused on youth [1929] and one study was performed in Japanese elderly (n = 1) [49]. Most studies (n = 25) included men and women, four studies [26, 30, 32, 35] reported data in women and two studies [37, 38] in men only. The number of participants varied from 30 to 2271, and several studies [19, 20, 29, 31, 3335, 3941, 4347] performed reliability testing in a larger sample than their test of criterion validity. The most common response timeframe was the last seven days, with seven studies [27, 30, 36, 37, 44, 46, 47] using a timeframe covering the last year (Table 1). All PAQs captured some elements of leisure time and recreational activity, although most questionnaires also addressed multiple domains of activity. Sedentary time is also a commonly captured behaviour from the newly developed questionnaires and has been given some extra attention in recent publications and in the current results. Several recent PAQs, such as the EPIC Physical Activity Questionnaire (EPAQ2) and the Recent Physical Activity Questionnaire (RPAQ), aim to measure the totality of physical activity by domains [31, 46, 47, 51]. The final outcome of the majority of PAQs was reported as time-integrated MET values, e.g. MET-min/week.

Reliability

All reliability results for new PAQs are listed in Table 3.
Table 3

Reliability results of new PAQs

Age Group

Reference

Test-retest period

PAQ

Variables tested

Reliability results

     

Correlation coefficients

Agreement

Youth

Dwyer (2011)[19]

1 - 2 weeks

Pre-PAQ

Level 5 min/day(Q1) – level 5

min/day(Q2)

ICC = 0.64

    

Level 4 min/day(Q1) – level 4 min/day(Q2)

ICC = 0.44

    

Level 3 min/day(Q1) – level 3 min/day(Q2)

ICC = 0.53

    

Levels 1–2 min/day(Q1) – levels 1–2 min/day(Q2)

ICC = 0.44

Youth

Economos (2010)[20]

1 - 2 hours

BONES PAS

High METs(Q1) – high METs(Q2)

Spearman r (95 % CI) = 0.57 (0.32;0.75), P < 0.001

    

Moderate-high METs(Q1) – moderate-high METs(Q2)

Spearman r (95 % CI) = 0.74 (0.56;0.85), P < 0.001

    

WBF score(Q1) – WBF score(Q2)

Spearman r (95 % CI) = 0.71 (0.51;0.83), P < 0.001

Youth

Martinez-Gomez (2010)[21]

1 hour

RPAR

Total MET-min(Q1) – total MET-min(Q2)

ICC = 0.87

Youth

Philippaerts (2006)[22]

9 days

FPACQ

Total hr/week(Q1) – total hr/week(Q2)

ICC = 0.68

κ = 0.50

    

Total EE(Q1) – total EE(Q2)

ICC = 0.80

κ = 0.53

    

Inactivity(Q1) – inactivity(Q2)

ICC = 0.83

κ = 0.61

Youth

Ridley (2001)[23]

7 days

CDPAQ

Total METs(Q1) – total METs(Q2)

ICC = 0.98 (P < 0.05)

    

Total min(Q1) – total min(Q2)

ICC = 0.91 (P < 0.05)

   

CDPAQ-HC

Total METs(Q1) – total METs(Q2)

ICC = 0.98 (P < 0.05)

    

Total min(Q1) – total min(Q2)

ICC = 0.96 (P < 0.05)

Youth

Ridley (2006)[24]

Within 24 hours

MARCA

PAL(Q1) – PAL(Q2)

ICC = 0.93

95 % LoA = −0.30 – 0.30

Youth

Telford (2004)[25]

> 14 days

CLASS-parental report

5-6 yrs: frequency(Q1) – frequency(Q2)

ICC = 0.83 (P < 0.001)

    

10-12 yrs: frequency(Q1) – frequency(Q2)

ICC = 0.69 (P < 0.001)

    

5-6 yrs: duration(Q1) – duration(Q2)

ICC = 0.76 (P < 0.001)

    

10-12 yrs: duration(Q1) – duration(Q2)

ICC = 0.74 (P < 0.001)

   

CLASS-self

10-12 yrs: frequency(Q1) – frequency(Q2)

ICC = 0.36 (P < 0.01)

    

10-12 yrs: duration(Q1) – duration(Q2)

ICC = 0.24

Youth

Treuth (2003)[26]

4 days

GAQ

Yesterday: GAQ score(Q1) – GAQ score(Q2)

Pearson r = 0.7833 (P < 0.0001)

    

Usual: GAQ score(Q1) – GAQ score(Q2)

Pearson r = 0.8187 (P < 0.0001)

    

Yesterday: TV watching(Q1) – TV watching(Q2)

Pearson r = 0.3454 (P = 0.0043)

    

Usual: TV watching(Q1) – TV watching(Q2)

Pearson r = 0.3827 (P = 0.0015)

    

Yesterday: other sedentary(Q1) – other sedentary(Q2)

Pearson r = 0.4695 (P < 0.0001)

    

Usual: other sedentary(Q1) – other sedentary(Q2)

Pearson r = 0.4837 (P < 0.0001)

  

3 days

Activitygram

Activitygram score(Q1) – activitygram score(Q2)

ICC = 0.24 (P = 0.005)

Youth

Treuth (2005)[27]

6 days

Fels PAQ

Girls: Fels PAQ score(Q1) – Fels PAQ score(Q2)

ICC = 0.67

    

Boys: Fels PAQ score(Q1) – Fels PAQ score(Q2)

ICC = 0.65

Youth

Welk (2007)[28]

7 days

YMCLS

Total activity(Q1) – total activity(Q2)

ICC (95 % CI) = 0.60 (0.47;0.70)

Youth

Wong (2006)[29]

7 days

SHAPES

Combined activity(Q1) – combined activity(Q2)

κ (±SD) = 0.58 ± 0.17

    

Sedentary activity(Q1) – sedentary activity(Q2)

κ (±SD) = 0.55 ± 0.01

Adults

Ainsworth (2000)[30]

1 month

KPAS

3-point summary index(Q1) – 3-point summary index(Q2)

ICC = 0.82 (P < 0.0001)

    

4-point summary index(Q1) – 4-point summary index(Q2)

ICC = 0.83 (P < 0.0001)

Adults

Besson (2010)[31]

± 2 weeks

RPAQ

PAEE(Q1) – PAEE(Q2)

ICC = 0.76 (P < 0.001)

    

Sedentary time(Q1) – sedentary time(Q2)

ICC = 0.76 (P < 0.001)

Adults

Chasan-Taber (2004)[32]

7 days

PPAQ

Total activity(Q1) – total activity(Q2)

ICC = 0.78

    

Sedentary(Q1) – sedentary(Q2)

ICC = 0.79

Adults

Chinapaw (2009)[33]

2 weeks

AQuAA

Adolescents: AQuAA score(Q1) – AQuAA score(Q2)

ICC (95 % CI) = 0.44 (0.16;0.65)

    

Adults: AQuAA score(Q1) – AQuAA score(Q2)

ICC (95 % CI) = 0.22 (−0.04;0.46)

    

Adolescents: sedentary(Q1) – sedentary(Q2)

ICC (95 % CI) = 0.57 (0.34;0.73)

    

Adults: sedentary(Q1) – sedentary(Q2)

ICC (95 % CI) = 0.60 (0.40;0.74)

Adults

Craig (2003)[34]

3 - 7 days

IPAQ

Long form: total PA(Q1) – total PA(Q2)

Pooled Spearman r (95 % CI) = 0.81 (0.79;0.82), range: 0.46 - 0.96

    

Short form: total PA(Q1) – total PA(Q2)

Pooled Spearman r (95 % CI) = 0.76 (0.73;0.77), range: 0.32 - 0.88

Adults

Fjeldsoe (2009)[35]

7 days

AWAS

Total activity(Q1) – total activity(Q2)

ICC (95 % CI) = 0.73 (0.51;0.86)

    

HEPA(Q1) – HEPA(Q2)

ICC (95 % CI) = 0.80 (0.65;0.89)

    

Sitting(Q1) – sitting(Q2)

ICC (95 % CI) = 0.42 (0.13;0.64)

Adults

Friedenreich (2006)[36]

9 weeks (average)

PYTPAQ

Total MET-hr/week(Q1) – total MET-hr/week(Q2)

ICC (95 % CI) = 0.66 (0.56;0.74), Spearman r = 0.64 (P < 0.0001)

Adults

Kurtze (2007)[37]

7 days

HUNT2

Hard activity(Q1) – hard activity(Q2)

Spearman r = 0.17 (P < 0.01)

κ = 0.41 (0.29;0.54)

    

Occupational activity(Q1) – occupational activity(Q2)

Spearman r = 0.85 (P < 0.01)

κ = 0.80 (0.71;0.89)

    

Light activity(Q1) – light activity(Q2)

Spearman r = 0.17

κ = 0.20 (0.04;0.35)

Adults

Kurtze (2008)[38]

7 days

HUNT1

Frequency(Q1) – frequency(Q2)

Spearman r = 0.87 (P < 0.01)

κ = 0.80

    

Intensity(Q1) – intensity(Q2)

Spearman r = 0.87 (P < 0.01)

κ = 0.82

    

Duration(Q1) – duration(Q2)

Spearman r = 0.76 (P < 0.01)

κ = 0.69

Adults

Lowther (1999)[39]

2 days

SPAQ

Total min(Q1) – total min(Q2)

Pearson r = 0.998 (P < 0.01), repeatability coefficient R = 53 min.

MD (95 % LoA) = 3.09 ± 26.5 min

Adults

Mäder (2006)[40]

14 - 21 days

SHS97

Sweat episodes(Q1) – sweat episodes(Q2)

Spearman r = 0.63 (P < 0.05)

   

HEPA99

Active/inactive(Q1) – active/inactive(Q2)

κ = 0.46 (P < 005)

   

IPAQ

Total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r = 0.54 (P < 0.05)

    

Sitting(Q1) – sitting(Q2)

Spearman r = 0.60 (P < 0.05)

   

OIMQ

Total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r = 0.68 (P < 0.05)

Adults

Meriwether (2006)[41]

7 days

PAAT

Total min(Q1) – total min(Q2)

Spearman r = 0.618 (P < 0.001)

Adults

Reis (2005)[42]

2 weeks

OPAQ

Total activity(Q1) – total activity(Q2)

ICC (95 % CI) = 0.76 (0.59;0.86)

    

Sedentary(Q1) – sedentary(Q2)

ICC (95 % CI) = 0.78 (0.62;0.87)

Adults

Rosenberg (2010)[43]

2 weeks

SBQ

Weekday: total score(Q1) – total score(Q2)

ICC (95 % CI) = 0.85 (0.75;0.91), Spearman r (95 % CI) = 0.79 (0.65;0.88)

    

Weekend day: total score(Q1) – total score(Q2)

ICC (95 % CI) = 0.77 (0.63;0.86), Spearman r (95 % CI) = 0.74 (0.58;0.85)

Adults

Sobngwi (2001)[44]

10 - 15 days

SSAAQ

Total min(Q1) – total min(Q2)

Spearman r = 0.95 (P < 0.001)

Adults

Timperio (2003)[45]

3 days

1WPAR

Men: duration(Q1) – duration(Q2)

ICC (95 % CI) = 0.45 (0.20;0.64), P < 0.001

    

Women: duration(Q1) – duration(Q2)

ICC (95 % CI) = 0.80 (0.69;0.87), P < 0.001

    

Men: sufficient PA(Q1) – sufficient PA(Q2)

κ = 0.64 (P < 0.001)

    

Women: sufficient PA(Q1) – sufficient PA(Q2)

κ = 0.55 (P < 0.001)

Adults

Wareham (2002)[46]

3 months

EPAQ2

Men: total MET-hr/week(Q1) – total MET-hr/week(Q2)

Pearson r = 0.74 (P < 0.05)

κ = 0.64

    

Women: total MET-hr/week(Q1) – total MET-hr/week(Q2)

Pearson r = 0.72 (P < 0.05)

κ = 0.70

    

Men: TV time(Q1) – TV time(Q2)

Pearson r = 0.75 (P < 0.05)

κ = 0.71

    

Women: TV time(Q1) – TV time(Q2)

Pearson r = 0.78 (P < 0.05)

κ = 0.74

Adults

Wareham (2003)[47]

18 - 21 months

EPAQ

Physical activity index(Q1) – physical activity index(Q2)

κ = 0.60 (P < 0.0001)

Adults

Yore (2007)[48]

1 - 5 days

BRFSS PAQ

VPA(Q1) – VPA(Q2)

κ (95 % CI) = 0.86 (0.72;0.99)

    

MPA(Q1) – MPA(Q2)

κ (95 % CI) = 0.53 (0.31;0.75)

    

Recommended PA(Q1) – recommended PA(Q2)

κ (95 % CI) = 0.84 (0.69;0.99)

    

Walking(Q1) – walking(Q2)

κ (95 % CI) = 0.56 (0.34;0.77)

    

Strengthening PA(Q1) – strengthening PA(Q2)

κ (95 % CI) = 0.92 (0.81;1.00)

  

10 - 19 days

BRFSS PAQ

VPA(Q1) – VPA(Q3)

κ (95 % CI) = 0.80 (0.65;0.95)

    

MPA(Q1) – MPA(Q3)

κ (95 % CI) = 0.35 (0.11;0.59)

    

Recommended PA(Q1) – recommended PA(Q3)

κ (95 % CI) = 0.67 (0.46;0.88)

    

Walking(Q1) – walking(Q3)

κ (95 % CI) = 0.34 (0.10;0.57)

    

Strengthening PA(Q1) – strengthening PA(Q3)

κ (95 % CI) = 0.85 (0.71;0.99)

Elderly

Yasunaga (2007)[49]

1 month

PAQ-EJ

PAQ-EJ score(Q1) – PAQ-EJ score(Q2)

Pearson r = 0.70 (P < 0.05)

     

Median ICC = 0.76 (youth: 0.69, adults: 0.765, elderly: –)

 
     

Median Spearman r = 0.74 (youth: 0.71, adults: 0.75, elderly: –)

 
     

Median Pearson r = 0.76 (youth: 0.80, adults: 0.74, elderly: 0.70)

 
      

Median κ = 0.64 (youth: 0.53, adults: 0.655, elderly: –)

Q1 =first completed questionnaire, Q2 = second completed questionnaire, Q3 = third completed questionnaire, r = correlation coefficient (rho), ICC = Intraclass Correlation Coefficient, CI = Confidence Interval (lower;upper), %CV = coefficient of variation (within subjects standard deviation of typical error) as a percentage of the mean score, κ = kappa (i.e. Cohen weighted kappa unless specified otherwise), LoA = Limits of Agreement, MD = Mean Difference, – = not stated.

NB: No calculation of weighted kappa is specified in the papers. Usually the kappa statistic is used for categorical responses and weighted kappa for ordinal responses. Interpretation of values of kappa and weighted kappa were usually based on the classification system developed by Landis and Koch (1977), where <0.10 indicated poor agreement, 0.10-0.20 slight agreement, 0.21-0.40 fair agreement, 0.41-0.60 moderate agreement, 0.61-0.80 substantial agreement, 0.81-1.00 almost perfect agreement.

Ainsworth (2000): 3 point summary index = 3 domains: sports/exercise, occupation, active living habits. 4 point summary index = all 4 domains: sports/exercise, occupation, active living habits, housework/caregiving.

Chinapaw (2009): AQuAA score: all activities above 2 MET in MET-min/week.

Craig (2003): Pooled Spearman = pooled results from data of 22 studies examining the IPAQ long form and 23 studies examining the short form.

Dwyer (2011): Levels 1–2 = stationary, level 3 = moving slowly, level 4 = moving at a medium or moderate pace, level 5 = moving at a fast pace.

Economos (2010): Moderate-high METs = 3–6 METs. High METs = ≥6 METs. WBF score = weight-bearing factor score, calculated by adding the weight-bearing factor of the reported weight-bearing activities.

Fjeldsoe (2009): HEPA = Health Enhancing Physical Activity: brisk walking and moderate- and vigorous activities from the planned activity and transport domains.

Kurtze (2007): Light activity = no sweating or being out of breath. Hard activity = sweating/out of breath.

Lowther (1999): Total min = total minutes measured in the overlapping 4 days of both questionnaires. Repeatability coefficient (twice the standard deviation of the differences) means that 95 % of the differences in SPAQ from one measurement to the next (under similar conditions) would be between zero plus or minus 53 minutes.

Mäder (2006): IPAQ - Total MET-min/week = MET-min/week for total activity excluding sitting. OIMQ - Total MET-min/week = MET-min/week for total activity, i.e. moderate and vigorous activities.

Philippaerts (2006): Total hrs/week = Total hours per week spent in transport and sports participation, excluding sedentary activities. Total EE = Total EE spent in transport and sports participation, excluding sedentary activities.

Reis (2005): Sedentary = sitting or standing activities.

Ridley (2001): CDPAQ-HC = hard copy of CDPAQ.

Rosenberg (2010): Total score = all sedentary behaviors in hours per day for each item were summed separately for weekday and weekend days.

Telford (2004): Reliability results for frequency/duration of overall total PA for 5 to 6 or 10 to 12 year old children in parental proxy-reports or self-administered questionnaires.

Timperio (2003): Duration = duration of total physical activity. Sufficient PA was calculated as 150 minutes of combined walking, moderate- and vigorous-intensity physical activity, with reported duration of vigorous-intensity physical activity weighted by two.

Treuth (2003): GAQ score = MET weighted mean score of 28 activities. Activitygram score = average intensity/min. Other sedentary = sedentary activities excluding TV watching.

Treuth (2005): Fels PAQ score = total activity score; MET weighted sum of sport, leisure, work index.

Wareham (2003): Physical activity index is a four-category index of inactive, moderately inactive, moderately active, active. TV time = hours per week watching television and videos.

Wong (2006): Combined activity = combined score of the SHAPES derived variables which contains the variables: VPA, MPA, MVPA, screen time, PAL and BMI.

Yasunaga (2007): PAQ-EJ score (MET-hr/week) = number of days*time*intensity weight.

Yore (2007): MPA ≥ 30 min/day on 5 days/week. VPA ≥ 20 min/day on 3 days/week. Recommended PA, i.e. ≥ subjects who met the criteria for moderate or vigorous PA. Walking ≥ 30 min/day. Strengthening PA = any muscle-strengthening activity on ≥ 2 days/week. Kappa's are reported for the subsamples who met the criteria for the physical activity intensities.

Reliability was usually reported as ICC (n = 13), Pearson/Spearman correlation (n = 6), kappa statistic (n = 3) or a combination of these statistics (n = 9). Higher reliability coefficients were more often seen in association with shorter periods between test and retest. Poor correlation (ICC or r <0.4) was found only in subcategories of a few PAQs. Median correlations from reported data for recall of sedentary behaviours across all PAQs were acceptable: ICC = 0.68, Spearman r = 0.60, Pearson r = 0.475, kappa = 0.66.

Youth

Median reliability correlations for the youth were as follows: ICC = 0.69, Spearman r = 0.71, Pearson r = 0.80, kappa = 0.53. The Activitygram (ICC = 0.24) [26] and the self-reported CLASS questionnaire (frequency: ICC = 0.36, duration ICC = 0.24) [25] showed fairly low reliability correlations, whereas the MARCA (ICC = 0.93) [52] and both computer and paper versions of the CDPAQ (ICC = 0.91–0.98) [23] demonstrated high reliability.

Adults

Median reliability correlations for adults were as follows: ICC = 0.765, Spearman r = 0.75, Pearson r = 0.74, kappa = 0.655. Reliability was poor for the AQuAA score for adults (ICC = 0.22) [53]. Similarly, reliability coefficients were poor for the HUNT2 [37] components of light (r = 0.17, κ = 0.20) and hard activity (r = 0.17, κ = 0.41). The primary version of this questionnaire (HUNT1), which was designed a decade earlier, however demonstrated high reliability (r = 0.76–0.87, κ = 0.69–0.82) [54]. The majority of the questionnaires showed acceptable to good reliability: KPAS (ICC = 0.82–0.83) [30], RPAQ (ICC = 0.76) [31], PPAQ (ICC = 0.78) [32], IPAQ short (r = 0.76) and long version (r = 0.81) [34], AWAS (ICC = 0.73–0.80) [35], FPACQ (ICC = 0.68–0.80) [22], OPAQ (ICC = 0.78) [42], SBQ (ICC = 0.77-0.85, r = 0.74-0.79) [43], SPAQ (r = 0.998) [39] and SSAAQ (r = 0.95) [44].

Elderly

Median Pearson reliability correlation for the elderly was r = 0.70. The PAQ-EJ was the only new PAQ designed for (Japanese) elderly that reported reliability results and has acceptable recall properties (r = 0.70) [49].

Validity

All validity results for new PAQs are listed in Table 4.
Table 4

Validity results of new PAQs

Age Group

Reference

Criterion method

Duration of validation

PAQ

Variables tested

Criterion intensity thresholds

Validity results

       

Correlation coefficients

Agreement

Youth

Dwyer (2011)[19]

Acc (ActiGraph)

4 - 5 days

Pre-PAQ

Level 5 min/day(Q) – VPA min/day(Acc)

>5016 counts/min

Pearson r = 0.17

MD (95 % LoA) = 1.9 ± 39.4 min/day

     

Level 4 min/day(Q) – MPA min/day(Acc)

3560-5016 counts/min

Pearson r = 0.13

MD (95 % LoA) = 48.2 ± 73.1 min/day

     

Level 3 min/day(Q) – LPA min/day(Acc)

1592-3560 counts/min

Pearson r = −0.07

MD (95 % LoA) = −4.8 ± 100.7 min/day

     

Levels 1–2 min/day(Q) – sedentary min/day(Acc)

<1592 counts/min

Pearson r = 0.19

MD (95 % LoA) = −235.4 ± 147.7 min/day

Youth

Economos (2010)[20]

Acc (ActiGraph)

2 days

BONES PAS

High METs(Q) – total counts/min(Acc)

Spearman r (95 % CI) = 0.25 (−0.07;0.52)

     

High METs(Q) – VPA(Acc)

6-9 METs, 1952–5724 counts/min

Spearman r (95 % CI) = 0.23 (−0.09;0.51)

     

Moderate-high METs(Q) – total counts/min(Acc)

Spearman r (95 % CI) = 0.27 (−0.05;0.54)

Youth

Martinez-Gomez (2010)[21]

Acc (ActiGraph)

1 day

RPAR

Total MET-min(Q) – total counts(Acc)

Pearson r = 0.42 (P = 0.021)

κ = 0.16

     

MVPA min(Q) – MVPA counts(Acc)

≥2000 counts/min

Pearson r = 0.52 (P < 0.001)

MD (95 % LoA) = 2.15 ± 7.19 min

  

Acc (Biotrainer)

1 day

 

Total MET-min(Q) – total counts(Acc)

Pearson r = 0.40 (P = 0.025)

κ = 0.39

     

Total MET-min(Q) – total counts/mov(Acc)

Pearson r = 0.54 (P = 0.004)

κ = 0.16

Youth

Philippaerts (2006)[22]

Acc (ActiGraph)

7 days

FPACQ

Total hr/week(Q) – total counts(Acc)

Pearson r = 0.56 (P < 0.01)

     

Total hr/week(Q) – mean counts/min(Acc)

Pearson r = 0.43 (P < 0.05)

     

TEE(Q) – total counts(Acc)

Pearson r = 0.58 (P < 0.01)

     

TEE(Q) – mean counts/min(Acc)

Pearson r = 0.49 (P < 0.05)

     

Inactivity(Q) – total counts(Acc)

Pearson r = −0.13

     

Inactivity(Q) – mean counts/min(Acc)

Pearson r = −0.06

Youth

Ridley (2001)[23]

Acc (Caltrac)

2x 1 day

CDPAQ

Total METs(Q) – total counts(Acc)

Pearson r = 0.41 (P < 0.05)

     

Total compendium METs(Q) – total counts(Acc)

Pearson r = 0.54 (P < 0.05)

     

Total mins(Q) – total counts(Acc)

Pearson r = 0.41 (P < 0.05)

  

HR (Polar)

2x 1 day

 

MVPA mins(Q) – MVPA mins(HR)

≥145 bpm

Pearson r = 0.66 (P = 0.01)

  

Acc (Caltrac)

2x 1 day

CDPAQ-HC

Total METs(Q) – total counts(Acc)

Pearson r = 0.25 (P < 0.05)

     

Total compendium METs(Q) – total counts(Acc)

Pearson r = 0.22 (P < 0.05)

     

Total mins(Q) – total counts(Acc)

Pearson r = 0.33 (P < 0.05)

  

HR (Polar)

2x 1 day

 

MVPA mins(Q) – MVPA mins(HR)

≥145 bpm

Pearson r = 0.48 (P = 0.05)

Youth

Ridley (2006)[24]

Acc (ActiGraph)

1 day

MARCA

PAL(Q) – total counts(Acc)

Spearman r = 0.45 (P < 0.01)

Youth

Telford (2004)[25]

Acc (ActiGraph)

8 days

CLASS-parental report

5-6 yrs: total min/day(Q) – total min/day(Acc)

Spearman r = −0.04

MD (95 % LoA) = −140.7 (−164.9;-116.6) min/day

     

10-12 yrs: total min/day(Q) – total min/day(Acc)

Spearman r = 0.09

MD (95 % LoA) = 11.2 (−6.9;29.4) min/day

     

5-6 yrs: total min/day(Q) – total raw counts/day(Acc)

Spearman r = 0.05

     

10-12 yrs: total min/day(Q) – total raw counts/day(Acc)

Spearman r = 0.11

    

CLASS-self

10-12 yrs: total min/day(Q) – total min/day(Acc)

Spearman r = −0.04

MD (95 % LoA) = 1.5 (−17.2;20.3) min/day

     

10-12 yrs: total min/day(Q) – total raw counts/day(Acc)

Spearman r = 0.06

Youth

Treuth (2003)[26]

Acc (ActiGraph)

4 days

GAQ

Yesterday: GAQ score(Q) – mean counts/min(Acc)

Pearson r = 0.27 (P < 0.05)

     

Usual: GAQ score(Q) – mean counts/min(Acc)

Pearson r = 0.29 (P < 0.05)

     

Yesterday: TV watching(Q) – mean counts/min(Acc)

Pearson r = −0.145 (P = 0.24)

     

Usual: TV watching(Q) – mean counts/min(Acc)

Pearson r = −0.004 (P = 0.98)

     

Yesterday: other sedentary(Q) – mean counts/min(Acc)

Pearson r = 0.0227 (P = 0.85)

     

Usual: other sedentary(Q) – mean counts/min(Acc)

Pearson r = −0.0916 (P = 0.46)

    

Activitygram

Activitygram score(Q) – mean counts/min(Acc)

Pearson r = 0.37 (P < 0.002)

Youth

Treuth (2005)[27]

Acc (Actiwatch)

6 days

Fels PAQ

Elementary: Fels PAQ score(Q) – mean counts/min(Acc)

Spearman r = 0.34 (P = 0.004)

     

Middle: Fels PAQ score(Q) – mean counts/min(Acc)

Spearman r = 0.11 (P = 0.31)

     

High: Fels PAQ score(Q) – mean counts/min(Acc)

Spearman r = 0.21 (P = 0.006)

Youth

Welk (2007)[28]

Acc (ActiGraph)

7 days

YMCLS

Weekly PA bouts(Q) – weekly PA bouts(Acc)

r = 0.24 (P < 0.05)

MD (95 % LoA) = −8.4 ± 28.4 min

     

Previous day: total MVPA mins(Q) – total MVPA mins(Acc)

3-6 METs

r = 0.53 (P < 0.05)

MD (95 % LoA) = 14.5 ± 173.9 min

Youth

Wong (2006)[29]

Acc (ActiGraph)

7 - 9 days

SHAPES

VPA min/day(Q) – VPA min/day(Acc)

≥8200 counts/min

Spearman r = 0.25 (P = 0.07)

     

MVPA min/day(Q) – MVPA min/day(Acc)

≥3200 counts/min

Spearman r = 0.44 (P < 0.01)

     

MPA min/day(Q) – MPA min/day(Acc)

3200-8199 counts/min

Spearman r = 0.31 (P = 0.02)

Adults

Ainsworth (2000)[30]

Acc (Caltrac)

2x 7 days

KPAS

3 point summary index(Q) – MET-min/day(Acc)

Spearman r = 0.53 (P < 0.01)

     

4 point summary index(Q) – MET-min/day(Acc)

Spearman r = 0.49 (P < 0.01)

Adults

Besson (2010)[31]

DLW

14 days

RPAQ

TEE(Q) – TEE(DLW)

Spearman r = 0.67 (P < 0.0001)

MD (95 % LoA) = −3451.9 ± 2025.1 kJ/day (P < 0.05)

     

PAEE(Q) – PAEE(DLW)

Spearman r = 0.39 (P = 0.0004)

MD (95 % LoA) = −12.9 ± 23.9 kJ/day (P < 0.05)

  

Acc + HR (Actiheart)

11 days

 

VPA(Q) – VPA(Acc + HR)

>6 METs

Spearman r = 0.70 (P < 0.0001)

MD (95 % LoA) = 0.2 ± 0.4 h/day

     

MPA(Q) – MPA(Acc + HR)

3.6-6 METs

MD (95 % LoA) = −0.8 ± 1.0 h/day

     

Light PA(Q) – light PA(Acc + HR)

2-3.5 METs

MD (95 % LoA) = −0.1 ± 2.4 h/day

     

Sedentary time(Q) – sedentary time(Acc + HR)

<2 METs

Spearman r = 0.27 (P = 0.06)

MD (95 % LoA) = 0.7 ± 2.8 h/day

Adults

Chasan-Taber (2004)[32]

Acc (ActiGraph)

7 days

PPAQ

Total activity(Q) – Swartz cut point min/day(Acc)

≥3 METs, ≥574 counts/min

Spearman r = 0.32

     

Total activity(Q) – Hendelman cut point min/day(Acc)

≥3 METs, ≥191 counts/min

Spearman r = 0.43

     

Total activity(Q) – Freedson cut point min/day(Acc)

≥3 METs, ≥1952 counts/min

Spearman r = 0.08

     

Total activity(Q) – mean counts/min(Acc)

Spearman r = 0.27

     

Sedentary(Q) – Swartz cut point min/day(Acc)

<1.5 METs

Spearman r = −0.17

     

Sedentary(Q) – Hendelman cut point min/day(Acc)

<1.5 METs

Spearman r = −0.34

     

Sedentary(Q) – Freedson cut point min/day(Acc)

<1.5 METs

Spearman r = 0.12

     

Sedentary(Q) – mean counts/min(Acc)

Spearman r = −0.10

Adults

Chinapaw (2009)[33]

Acc (ActiGraph)

14 days

AQuAA

Adolescents: AQuAA score(Q) – counts/min(Acc)

≥ 2 METs, ≥699 counts/min

Spearman r = 0.13

     

Adults: AQuAA score(Q) – counts/min(Acc)

≥ 2 METs, ≥699 counts/min

Spearman r = −0.16

     

Adolescents: sedentary(Q) – counts/min(Acc)

< 2 METs, <699 counts/min

Spearman r = 0.23

     

Adults: sedentary(Q) – counts/min(Acc)

< 2 METs, <699 counts/min

Spearman r = 0.15

Adults

Craig (2003)[34]

Acc (ActiGraph)

7 days

IPAQ

Long form: total PA(Q) – total counts(Acc)

Pooled Spearman r (95 % CI) = 0.33 (0.26;0.39), range: -0.27 - 0.61

     

Short form: total PA(Q) – total counts(Acc)

Pooled Spearman r (95 % CI) = 0.30 (0.23;0.36), range: -0.12 - 0.57

Adults

Fjeldsoe (2009)[35]

Acc (ActiGraph)

7 days

AWAS

Total activity(Q) – total activity(Acc)

≥100 counts/min

Spearman r = 0.13 (P = 0.24)

     

HEPA(Q) – Freedson cut point min/week(Acc)

Spearman r = 0.28 (P = 0.01)

     

HEPA(Q) – Swartz cut point min/week(Acc)

Spearman r = 0.06 (P = 0.64)

     

Sitting(Q) – sitting(Acc)

<100 counts/min

Spearman r = 0.32 (P = 0.006)

Adults

Friedenreich (2006)[36]

Acc (ActiGraph)

4x 7 days

PYTPAQ

Total MET-hr/week(Q) – total MET-hr/week(Acc)

Spearman r = 0.26 (P < 0.05), ICC (95 % CI) = 0.18 (0.03;0.32)

Adults

Kurtze (2007)[37]

Acc (ActiReg)

7 days

HUNT2

Hard activity(Q) – EE(Acc)

Spearman r = 0.11

     

Hard activity(Q) – PAL(Acc)

Spearman r = 0.16

     

Light activity(Q) – EE(Acc)

Spearman r = 0.21 (P < 0.05)

     

Light activity(Q) – PAL(Acc)

Spearman r = 0.08

     

Occupational activity(Q) – EE(Acc)

Spearman r = 0.39 (P < 0.01)

     

Occupational activity(Q) – PAL(Acc)

Spearman r = 0.38 (P < 0.01)

Adults

Kurtze (2008)[38]

Acc (ActiReg)

7 days

HUNT1

Summary index(Q) – EE(Acc)

Spearman r = 0.03

     

Summary index(Q) – PAL(Acc)

Spearman r = 0.07

     

Summary index(Q) – MET-min/day(Acc)

Spearman r = 0.07

Adults

Lowther (1999)[39]

Acc (Caltrac)

4 days

SPAQ

Total mins(Q) – total kcal(Acc)

r = 0.1294, corrected for confounding: r = 0.52 (P < 0.05)

Adults

Mäder (2006)[40]

Acc (ActiGraph)

7 days

SHS97

Sweat episodes/week(Q) – total counts/min(Acc)

Spearman r = 0.23

    

HEPA99

    

IPAQ

Total MET-min/week(Q) – total counts/min(Acc)

Spearman r = 0.39 (P < 0.05)

     

Sitting(Q) – sitting(Acc)

<100 counts/min

Spearman r = 0.22

    

OIMQ

Total MET-min/week(Q) – total counts/min(Acc)

Spearman r = 0.44 (P < 0.05)

Adults

Meriwether (2006)[41]

Acc (MTI)

14 days

PAAT

VPA min/week(Q) – VPA min/week(Acc)

≥5 METs, ≥5725 counts/min

Spearman r = 0.380 (P < 0.01)

     

MVPA min/week(Q) – MVPA min/week(Acc)

≥5 METs, ≥1952 counts/min

Spearman r = 0.392 (P < 0.01)

     

MPA min/week(Q) – MPA min/week(Acc)

3-4.9 METs, 1952–5724 counts/min

Spearman r = 0.392 (P < 0.01)

Adults

Reis (2005)[42]

Acc (ActiGraph)

7 days

OPAQ

Total hr/week(Q) – VPA(Acc)

≥5725 counts/min

Spearman r = −0.02

     

Total hr/week(Q) – MPA(Acc)

1952-5724 counts/min

Spearman r = 0.12

     

Total hr/week(Q) – light activity(Acc)

<1952 counts/min

Spearman r = 0.22

     

Sedentary(Q) – light activity(Acc)

<1952 counts/min

Spearman r = −0.20

Adults

Rosenberg (2010)[43]

Acc (ActiGraph)

7 days

SBQ

Female: total sedentary hr/week(Q) – total sedentary counts(Acc)

<100 counts/min

Partial r = 0.10 (P = 0.07)

     

Male: total sedentary hr/week(Q) – total sedentary counts(Acc)

<100 counts/min

Partial r = −0.01 (P = 0.81)

Adults

Sobngwi (2001)[44]

Acc (Caltrac)

1 day

SSAAQ

Female: total METs(Q) – total METs(Acc)

r = 0.74 (P < 0.01)

     

Male: total METs(Q) – total METs(Acc)

r = 0.60 (P < 0.01)

  

HR (Polar)

1 day

 

Urban female: total METs(Q) – total activity(HR)

r = 0.63 (P < 0.01)

     

Rural female: total METs(Q) – total activity(HR)

r = 0.41 (P < 0.05)

     

Urban male: total METs(Q) – total activity(HR)

r = 0.54 (P < 0.05)

     

Rural male: total METs(Q) – total activity(HR)

r = 0.59 (P < 0.01)

Adults

Timperio (2003)[45]

Acc (ActiGraph)

7 days

1WPAR

Men: total min/day(Q) – total min/day(Acc)

≥3 METs, ≥1952 counts/min

Spearman r = 0.29 (P < 0.05)

     

Women: total min/day(Q) – total min/day(Acc)

≥3 METs, ≥1952 counts/min

Spearman r = 0.25 (P < 0.05)

Adults

Wareham (2002)[46]

HR (Polar)

4x 4 days

EPAQ2

Total MET-hr/week(Q) – EE(HR)

Pearson partial r = 0.28 (P < 0.001)

     

TV time(Q) – EE(HR)

Pearson partial r = −0.07

Adults

Wareham (2003)[47]

HR (Polar)

4x 4 days

EPAQ-s

Physical activity index(Q) – DayPAR(HR)

P for trend = 0.003

     

Total hr/week(Q) – DayPAR(HR)

r = 0.04 (P = 0.59)

Adults

Yore (2007)[48]

Acc (ActiGraph)

7 days

BRFSS PAQ

VPA min/week(Q1) – VPA min/week(Acc)

≥5999 counts/min

Pearson r = 0.52

     

VPA min/week(Q2) – VPA min/week(Acc)

≥5999 counts/min

Pearson r = 0.54

     

VPA min/week(Q3) – VPA min/week(Acc)

≥5999 counts/min

Pearson r = 0.63

     

MPA min/week(Q1) – MPA min/week(Acc)

2020-5998 counts/min

Pearson r = 0.27

     

MPA min/week(Q2) – MPA min/week(Acc)

2020-5998 counts/min

Pearson r = 0.20

     

MPA min/week(Q3) – MPA min/week(Acc)

2020-5998 counts/min

Pearson r = 0.16

Elderly

Yasunaga (2007)[49]

Acc (Kenz Lifecorder)

1 month

PAQ-EJ

PAQ-EJ score(Q) – MET-min/day(Acc)

Spearman r = 0.41 (P < 0.05)

       

Median Spearman r = 0.25 (youth: 0.22, adults: 0.27, elderly: 0.41)

 
       

Median Pearson r = 0.41 (youth: 0.41, adults: 0.28, elderly: –)

 

Q1 = first completed questionnaire, Q2 = second completed questionnaire, Q3 = third completed questionnaire, r = correlation coefficient (rho), CI = Confidence Interval (lower;upper), κ = kappa (i.e. Cohen weighted kappa unless specified otherwise), LoA = Limits of Agreement, MD = Mean Difference, – = not stated.

Acc = Accelerometry [NB: ActiGraph (Model 7164) is successor of preceding accelerometer by MTI, formerly CSA]. Accelerometer names as used in the respective papers.

Ainsworth (2000): 3 point summary index = 3 domains: sports/exercise, occupation, active living habits. 4 point summary index = all 4 domains: sports/exercise, occupation, active living habits, housework/caregiving.

Craig (2003): Pooled Spearman = pooled results from data of 22 studies examining the IPAQ long form and 23 studies examining the short form.

Dwyer (2011): Levels 1–2 = stationary, level 3 = moving slowly, level 4 = moving at a medium or moderate pace, level 5 = moving at a fast pace.

Economos (2010): Moderate-high METs = 3–6 METs. High METs = ≥6 METs.

Fjeldsoe (2009): Total activity includes light-, moderate-, and vigorous-intensity activities. HEPA = Health Enhancing Physical Activity: brisk walking and moderate- and vigorous activities from the planned activity and transport domains.

Kurtze (2007): EE = Energy Expenditure in MJ/day. PAL = total EE divided by basal metabolic rate (BMR). Light activity = no sweating or being out of breath. Hard activity = sweating/out of breath.

Kurtze (2008): EE = Energy Expenditure in MJ/day. PAL = total EE divided by basal metabolic rate (BMR).

Lowther (1999): Initial r = 0.1294, but after correction for less reliable high data (occupational walking data, extreme data for 4 participants) the correlation improved to 0.52.

Mäder (2006): IPAQ - Total MET-min/week = MET-min/week for total activity excluding sitting. OIMQ - Total MET-min/week = MET-min/week for total activity, i.e. moderate and vigorous activities.

Martinez-Gomez (2010): Counts/mov = counts adjusted by movement time over the recess time. MD = mean difference between the mean times spent at MVPA by the two instruments. Kappa = agreement between the two instruments among tertiles of total PA.

Reis (2005): ActiGraph only worn during occupational hours. Sedentary = sitting or standing activities.

Ridley (2001): CDPAQ-HC = hard copy of CDPAQ. MVPA = Moderate-to-Vigorous Physical Activity. Total compendium METs = compendium values to derive total METs due to reported problems associated with children's perception of intensity (Compendium of physical activities: classification of energy costs of human physical activities. Ainsworth BE, Haskell WL, Leon AS, Jacobs DR Jr, Montoye HJ, Sallis JF, Paffenbarger RS Jr. Med Sci Sports Exerc. 1993 Jan;25(1):71–80).

Rosenberg (2010): Partial r = partial correlation, adjusted for age, marital status, white or nonwhite ethnicity, number of children, and highest level of education.

Sobngwi (2001): Total activity by Heart Rate monitoring is defined as variability in heart rate measured as area under the minute-to-minute heart rate curve and above individual resting heart rate.

Telford (2004): Validity results for total PA minutes for 5 to 6 or 10 to 12 year old children in parental proxy-reports or self-administered questionnaires.

Timperio (2003): Total activity in min/day is specified as ≥3 METs.

Treuth (2003): GAQ score = MET weighted mean score of 18 more reliable, and more frequently performed, activities. Activitygram score = average intensity/min over 3 day period. Other sedentary = sedentary activities excluding TV watching. The scores are an average of the two days administrations.

Treuth (2005): Fels PAQ score = mean Fels PAQ score (total activity) of both administrations of the PAQ. Counts/min = mean counts/min. Elementary = elementary school. Middle = middle school. High = high school.

Wareham (2002): Subject wore the HR monitor 4x four days across one year. EE = Energy Expenditure in kJ/hr. TV time = hours per week watching television and videos. Partial correlation coefficient is adjusted for age and sex.

Wareham (2003): Subject wore the HR monitor 4x four days across one year. Physical activity index = combined index for the four-level classification of self-reported occupational activity and four-level categorisation of time spent in cycling and other physical exercise. DayPAR = Physical Activity Ratio calculated as the ratio of daytime energy expenditure to resting energy expenditure. P for trend = P for positive trend of the association between DayPAR (measured by calibrated HR data) over four categories of physical activity (i.e. inactive, moderately inactive, moderately active, active) estimated from the EPAQ.

Welk (2007): PA bouts = number of sessions of physical activity performed during the week. Total MVPA mins = total minutes in moderate to vigorous physical activity performed during the previous day. Cut point used is Freedson age-based cut point, calculated as METs = 2.757 + (0.0015*counts per minute) - (0.0896*age[yr]) - (0.000038*counts per minute*age[yr]). Correlation = group-level correlation. No correlation coefficient specified.

Yasunaga (2007): PAQ-EJ score = MET score in MET-hr/week, calculated as number of days*time*intensity weight.

Accelerometry and in particular the ActiGraph accelerometer was the most commonly used criterion method (n = 19), followed by the Caltrac accelerometer (n = 4) and the Polar heart rate monitor (n = 4). DLW was used in one study, where absolute validity was moderate to high for PAEE (r = 0.39) and TEE (r = 0.67) [31]. In general, validity coefficients were considerably lower than reliability coefficients. Median correlations across all PAQs between reported sedentary behaviours and calculated inactivity from objective measures were low: Spearman r = 0.12.

Youth

Median validity correlations for the youth were as follows: Spearman r = 0.22, Pearson r = 0.41. CLASS self- and parental reported physical activity (r = −0.04–0.11) [25] was among the least valid questionnaires for children, although several other PAQs also showed low correlations with objective measures: Pre-PAQ (r = −0.07–0.17) [19], BONES PAS (r = 0.23–0.27) [20], GAQ (r = 0.27–0.29) [26], Fels PAQ (0.11–0.34) [27]. None of the newly developed PAQs for children demonstrated high validity.

Adults

Median validity correlations for adults were as follows: Spearman r = 0.27, Pearson r = 0.28. Highest validity in adults was demonstrated for the SSAAQ when tested against the Caltrac accelerometer (r = 0.60-0.74) [44]. Low validity correlations for total activity or for all subcategories were observed for the HUNT1 (r = 0.03–0.07) [54], and the short EPIC PAQ (r = 0.04), although the main outcome, a 4 category physical activity index, derived from this instrument was significantly associated with objectively measured physical activity energy expenditure (p for trend = 0.003) [47]. A follow-up study in 1941 adults from 10 European countries suggested moderate validity (r = 0.33) of this instrument using physical activity energy expenditure from combined heart rate and movement sensing as the criterion [51].

Rosenberg et al. assessed the validity of sedentary behaviour only, and demonstrated low correlations (partial r = −0.01–0.10) with objectively measured sedentary time (<100 counts/min) by the ActiGraph accelerometer [43].

Elderly

Median Spearman validity correlation for the elderly was r = 0.41. The PAQ-EJ was tested by correlating a total score with MET-min/day calculated from the Kenz Lifecorder accelerometer-based pedometer (r = 0.41) [49].

Existing PAQs

New validity and reliability results for existing PAQs were reported in 35 studies, and 30 studies reported new results on validity only (Table 5). One study is classified as a study testing an existing PAQs, but also reports both validity and reliability data for a new PAQ (SP2PAQ) [55]. Twenty-six of the 65 studies were undertaken in the US with the remaining coming from Australia (n = 5), Sweden (n = 5), China (n = 4), Belgium (n = 3), Spain (n = 3), Canada (n = 2), France (n = 2), Norway (n = 2), Japan (n = 2), Brazil, Portugal, Singapore, South Africa, Turkey, United Kingdom and Vietnam. There were four multi-country studies; three testing the IPAQ modified for adolescents [56, 57] and the EPAQ-s in 9–10 European cities [51]. The GPAQ was tested in diverse sample of nine global countries [58]. Eighteen studies were undertaken in youth [57, 5974], 12 in elderly [7586]; and 35 in adults with a few studies including both older adolescents and adults. In 48 studies men and women were combined, 10 studies examined women only [70, 72, 8793], and seven studies included only men [54, 75, 78, 9497]. All authors concluded that the questionnaires had shown at least satisfactory results for reliability and validity (see results below); seven studies noted considerable limitations in aspects of their questionnaires [56, 59, 63, 90, 98100].
Table 5

Descriptive characteristics of existing PAQs

Age Group

Reference

Name questionnaire

Country

Domains of activity

Population

Primary outcome

     

Size

Age (years)

Sex

Ethnicity

 

Youth

Affuso (2011)[59]

SAPAC (modified)

United States

Sedentary

201

11 - 15

M/F

Mixed

Total min/day

Youth

Allor (2001)[60]

PDPAR

United States

Moderate, hard, very hard activity

46

12 ± 0.6

F

Mixed, urban

METs (kcal/hr)

Youth

Corder (2009)[61]

YPAQ, CPAQ, CHASE, SWAPAQ

United Kingdom

All domains, including school and leisure time

62 reliability, 76 validity

4 - 17

M/F

Mainly white

PAEE, lifestyle scores, MET-min/week

Youth

Eisenmann (2002)[62]

GLTEQ

United States

Mild, moderate and strenuous activity in leisure time

31

10.6 ± 0.2

M/F

Mixed

METs

Youth

Gwynn (2010)[63]

MRPARQ

Australia

All organised and non-organised physical activities

86

10 - 12

M/F

Aboriginal, Torres Strait Islander, non-Indigenous

MET-min/day

Youth

Hagströmer (2008)[56]

IPAQ-A

9 countries

Sedentary, leisure, household, occupation, transportation

248

12 - 14, 15 -17

M/F

European

MET-min/day

Youth

Huang (2009)[64]

CLASS (Chinese version)

China

31 physical activities and 14 sedentary activities over weekday and weekends

216 reliability, 99 validity

9 - 12

M/F

Chinese

Total min/day

Youth

Kowalski (1997)[65]

PAQ-C

Canada

Moderate and vigorous PA during school, including sports/exercise

73

8 - 13

M/F

5-point scale of activity

Youth

Martinez-Gomez (2010)[66]

BAD

Spain

Leisure, occupation

37

12 - 16

M/F

MET-min/day

Youth

Martinez-Gomez (2011)[67]

PAQ-A

Spain

Usual moderate and vigorous PA during schooldays and weekend days

203

13 - 17

M/F

PAQ-A score

Youth

Mota (2002)[68]

WAC (modified)

Portugal

Activities outside school

30 reliability, 109 validity

8 - 16

M/F

Hispanic

METs/15 min

Youth

Ottevaere (2011)[57]

IPAQ-A

10 countries

Sedentary, leisure, household, occupation, transportation

2018

12.5 - 17

M/F

European

Total min/day

Youth

Rangul (2008)[69]

HBSC, IPAQ-s

Norway

HBSC: sports/exercise (outside school hours). IPAQ-s: sedentary, leisure, household, occupation, transportation

71

13 - 18

M/F

TEE, PAL

Youth

Scerpella (2002)[70]

GSQ

United States

Habitual activity in strenuous, moderate and light intensity

61

7 - 11

F

Godin-Shephard scores

Youth

Slinde (2003)[71]

MLTPAQ

Sweden

Sedentary, leisure, household

35

15

M/F

TEE

Youth

Treuth (2004)[72]

GAQ

United States

28 physical, 7 sedentary usual activities

90 reliability, 76 comparison validity, 86 intervention validity

8 - 10

F

African-American

GAQ score

Youth

Troped (2007)[73]

YRBS

United States

Leisure, occupation

128 reliability, 125 validity

12.7 ± 0.6

M/F

Mixed

Minutes and bouts of MPA and VPA

Youth

Weston (1997)[74]

PDPAR

United States

Sedentary, leisure, occupation, transportation, sports/exercise

90 reliability, 48 validity

Grades 7 - 12

M/F

Mainly white

METs

Adults

Ainsworth (1999)[87]

TOQ, 7DR-O (modified)

United States

Occupation

46

18 - 60

F

Mainly white

MET-min/week

Adults

Bassett (2000)[101]

CAQ

United States

Stair climbing, walking, sports/exercise, leisure

96

25 - 70

M/F

Mainly Caucasian

MET-min/week

Adults

Brown (2008)[88]

AAS (modified)

Australia

Walking briskly, moderate leisure activity, vigorous leisure activity

44

54 - 59

F

Mainly white

MET-min/week

Adults

Bull (2009)[58]

GPAQ

9 countries

Sedentary, leisure, occupation, transportation

2221 reliability, 298 validity

18-75

M/F

Mixed

Total min/day

Adults

Conway (2002)[94]

7DPAR, S7DR

United States

Household, occupation, walking, light, moderate, vigorous activities

24

27 - 65

M

MET-min/day, EE

Adults

Cust (2008)[102]

EPAQ

Australia

Leisure, household, occupation

182

50 - 65

M/F

Mainly white

Total PA index, Cambridge PA index

Adults

Cust (2009)[103]

EPAQ, IPAQ-s

Australia

Sedentary, leisure, household, occupation, transportation

177

50 - 65

M/F

Mainly white

MET-hr/week

Adults

Duncan (2001)[104]

7DPAR

United States

Sedentary, leisure, household, occupation, sports/exercise

94 reliability, 66 validity

30 - 69

M/F

Mainly Caucasian

TEE, METs

Adults

Ekelund (2006)[95]

IPAQ-s

Sweden

Sedentary, leisure, household, occupation, transportation

87

20 - 69

M

MET-min/day

Adults

Gauthier (2009)[105]

IPAQ-SALVCF

Canada

Sedentary, leisure, household, occupation, transportation

31

20 - 63

M/F

French Canadians

MET-min/week

Adults

Hagströmer (2006)[106]

IPAQ

Sweden

Sedentary, leisure, household, occupation, transportation

46

40.7 ± 10.3

M/F

MET-hr/week

Adults

Hagströmer (2010)[107]

IPAQ

Sweden

Sedentary, leisure, household, occupation, transportation

980

18 - 65

M/F

MET-min/day

Adults

Hallal (2010)[108]

IPAQ (modified)

Brazil

Leisure, transportation

156

≥ 20

M/F

Total min/week, total score

Adults

InterAct Consortium (2011)[51]

EPAQ-s

10 countries

Leisure, household, occupation, transportation

1941

53.8 ± 9.4

M/F

European

MET-hr/week, total PA index, Cambridge index, recreational index

Adults

Jacobi (2009)[109]

MAQ

France

Sedentary, leisure, occupation

160

18 - 74

M/F

MET-hr/week

Adults

Kurtze (2008)[54]

IPAQ-s

Norway

Sedentary, leisure, household, occupation, transportation

108

20 - 39

M

MET-hr/week

Adults

Lee (2011)[98]

IPAQ-s (Chinese version)

China

Sedentary, leisure, household, occupation, transportation

1270

42.9 ± 14.4

M/F

Asian

MET-min/week

Adults

MacFarlane (2007)[99]

IPAQ-s (Chinese version)

China

Sedentary, leisure, household, occupation, transportation

49

15 - 55

M/F

Asian

MET-min/week

Adults

MacFarlane (2010)[110]

IPAQ-LC

China

Sedentary, leisure, household, occupation, transportation

28 reliability, 83 validity

26.2 ± 9.9 (reliability), 40.9 ± 11.1 (validity)

M/F

Asian

MET-min/day

Adults

Mahabir (2006)[89]

HAQ, FCPQ, CAPS-4WR, CAPS-TWR

United States

Leisure, household

65

49 - 78

F

EE, METs

Adults

Matton (2007)[111]

FPACQ

Belgium

Sedentary, leisure, household, occupation, transportation

102 reliability, 111 validity

22 - 78

M/F

Hr/week, EE, PAL (METs)

Adults

Nang (2011)[55]

IPAQ, SP2PAQ

Singapore

Sedentary, leisure, household, occupation, transportation

152

> 21

M/F

Asian

EE (kcal/day), METs

Adults

Nicaise (2011)[90]

IPAQ

United States

Sedentary, leisure, household, occupation, transportation

105

35.9 ± 9.0

F

Latino

MET-min/week

Adults

Pettee-Gabriel (2009)[91]

PMMAQ, PWMAQ, NHS-PAQ, AAS, WHI-PAQ

United States

Sedentary, leisure, sports/exercise

66

45 - 65

F

Mainly white

MET-hr/week, total min/day

Adults

Philippaerts (1999)[96]

BAQ, FCPQ, TCQ

Belgium

Leisure, occupation, sports/exercise

19

40

M

PAL scores

Adults

Philippaerts (2001)[97]

BAQ, TCQ

Belgium

Leisure, occupation, sports/exercise

66

40

M

Activity indices, EE

Adults

Richardson (2001)[100]

S7DR

United States

Leisure, occupation

77

20 - 59

M/F

Mainly white

MET-min/day

Adults

Saglam (2010)[112]

IPAQ (short and long version)

Turkey

Sedentary, leisure, household, occupation, transportation

330 reliability, 80 validity

18 - 32

M/F

MET-min/week

Adults

Schmidt (2006)[92]

KPAS-mod

United States

Household, occupation, active living, sports/exercise

63

18 - 47

F

KPAS activity indexes

Adults

Smitherman (2009)[113]

JPAC

United States

Leisure, household, occupation, sports/exercise

40 reliability, 404 validity

54.4 ± 15.7 (reliability), 57.1 ± 11.54 (validity)

M/F

African American

JPAC index scores

Adults

Staten (2001)[93]

AAFQ

United States

Leisure, household, occupation

35

31 - 60

F

Mixed

TEE, PAEE, RMR, MET-hr/day

Adults

Strath (2004)[114]

CAQ-PAI

United States

Leisure

25

20 - 56

M/F

Mainly Caucasian

MET-min/week

Adults

Trinh (2009)[115]

GPAQ

Vietnam

Sedentary, leisure, occupation, transportation

169 dry season, 162 wet season

25 - 64

M/F

Asian

Total min/day

Adults

Washburn (2003)[116]

S7DR

United States

Sleep, moderate, hard and very hard physical activities

46

17 - 35

M/F

Mixed

TEE, PAEE

Adults

Wolin (2008)[117]

IPAQ-s

United States

Sedentary, leisure, household, occupation, transportation

142

24 - 67

M/F

Black or African American

MET-min/week

Elderly

Bonnefoy (2001)[75]

MLTPAQ, YPAS, BAQ-mod, CAQ, 7DR, DQ-mod, LRC, SUA, PASE, QAPSE

France

Light, moderate, vigorous intensity PA, walking, specific activities

19

73.46 ± 4.1

M

TEE, PAL, PAEE

Elderly

De Abajo (2001)[76]

YPAS (Spanish version)

Spain

Sedentary, occupation, sports/exercise

108

61 - 80

M/F

Hispanic

Total time, EE

Elderly

Dinger (2004)[77]

PASE

United States

Leisure, household, occupation

56

75.7 ± 7.9

M/F

Mainly Caucasian

Subscale and total PASE scores

Elderly

Dubbert (2004)[78]

7DPAR

United States

Shopping, household, occupation, sports/exercise

220 reliability, 42 validity

60 - 80

M

Mixed

TEE, METs

Elderly

Giles (2009)[79]

CHAMPS-MMSCV

Australia

Leisure, household

47

≥ 65

M/F

Mainly non-Indigenous Australian

MET-min/week (volume), times/week (frequency), min/week (duration)

Elderly

Hagiwara (2008)[80]

PASE

Japan

Leisure, household, occupation

257 reliability, 200 validity

72.6 ± 4.9

M/F

Japanese

Total PASE score, hr/day

Elderly

Harada (2001)[81]

CHAMPS, PASE, YPAS

United States

Leisure, household

87

65 - 89

M/F

Mixed

EE, total PASE score

Elderly

Hurtig-Wennlöf (2010)[82]

IPAQ-E

Sweden

Sedentary, leisure, household, occupation, transportation

54

66 - 85

M/F

Total min/day

Elderly

Kolbe-Alexander (2006)[83]

IPAQ-s, YPAS

South Africa

Sedentary, leisure, household, occupation, transportation

122

> 60

M/F

Mixed

MET-min/week, EE

Elderly

Starling (1999)[84]

MLTPAQ, YPAS

United States

MLTPAQ: Leisure, household. YPAS: leisure, household, sports/exercise

67

45 - 84

M/F

Caucasian

TEE

Elderly

Tomioka (2011)[85]

IPAQ-s (Japanese version)

Japan

Sedentary, leisure, household, occupation, transportation

325

65 - 89

M/F

Japanese

MET-min/week

Elderly

Washburn (1999)[86]

PASE

United States

Leisure, household, occupation

20

67 - 80

M/F

Total PASE scores

Domains named in paper were reclassified, unless the activities were very different from categories used, according to the following system: Occupation: work, school, labour. Transportation: travel, commuting, employment. Household: home/life, housework, caregiving, domestic life, child/elder/self care, cooking, chores, gardening, stair climbing. Leisure: leisure, recreation time. Sports/exercise: play, sports, exercise, workout. Sedentary: sedentary behaviours, e.g. sitting, TV viewing activities, eating, sleeping, bathing, inactivity.

– = not stated, M = Male, F = Female.

Reliability

All reliability results for existing PAQs are listed in Table 6.
Table 6

Reliability results of existing PAQs

Age Group

Reference

Test-retest period

PAQ

Variables tested

Reliability results

     

Correlation coefficients

Agreement

Youth

Allor (2001)[60]

Within 1 week

PDPAR

METs(Q1) – METs(Q2)

ICC = 0.98

Youth

Corder (2009)[61]

1 week

YPAQ

12-13 yrs: PAEE(Q1) – PAEE(Q2)

ICC = 0.86 (P < 0.001)

    

16-17 yrs: PAEE(Q1) – PAEE(Q2)

ICC = 0.79 (P < 0.001)

   

CPAQ

PAEE(Q1) – PAEE(Q2)

ICC = 0.25

   

CHASE

Lifestyle score(Q1) – lifestyle score(Q2)

ICC = 0.02

   

SWAPAQ

PAEE(Q1) – PAEE(Q2)

ICC = 0.64 (P < 0.001)

Youth

Eisenmann (2002)[62]

Same day

GLTEQ

Total leisure activity score(Q1) – total leisure activity score(Q2)

Pearson r = 0.62 (P < 0.05)

MD (95 % LoA) = −33.4 ± 10.28

Youth

Huang (2009)[64]

1 week

CLASS

VPA min/week(Q1) – VPA min/week(Q2)

ICC (95 % CI) = 0.73 (0.64;0.79), P < 0.05

    

MVPA min/week(Q1) – MVPA min/week(Q2)

ICC (95 % CI) = 0.71 (0.61;0.77), P < 0.05

    

MPA min/week(Q1) – MPA min/week(Q2)

ICC (95 % CI) = 0.61 (0.49;0.70), P < 0.05

    

Sedentary min/week(Q1) – sedentary min/week(Q2)

ICC (95 % CI) = 0.69 (0.59;0.77), P < 0.05

Youth

Mota (2002)[68]

7 days

WAC

Total activity(Q1) – total activity(Q2)

ICC = 0.71

Youth

Rangul (2008)[69]

8 - 12 days

HBSC

Frequency: sessions/week(Q1) – sessions/week(Q2)

ICC (95 % CI) = 0.73 (0.60;0.82)

    

Duration: hr/week(Q1) – hr/week(Q2)

ICC (95 % CI) = 0.71 (0.57;0.81)

   

IPAQ-s

VPA min/day(Q1) – VPA min/day(Q2)

ICC (95 % CI) = 0.30 (−0.07;0.56)

    

MPA min/day(Q1) – MPA min/day(Q2)

ICC (95 % CI) = 0.34 (0.22;0.60)

    

Walking min/day(Q1) – walking min/day(Q2)

ICC (95 % CI) = 0.10 (−0.10;0.39)

    

Sitting min/day(Q1) – sitting min/day(Q2)

ICC (95 % CI) = 0.27 (−0.50;0.54)

Youth

Treuth (2004)[72]

12 weeks

GAQ

Yesterday: GAQ score(Q1) – GAQ score(Q2)

Pearson r = 0.59 (P < 0.001)

    

Usual: GAQ score(Q1) – GAQ score(Q2)

Pearson r = 0.59 (P < 0.001)

    

Yesterday: TV watching(Q1) – TV watching(Q2)

Pearson r = 0.13 (P < 0.373)

    

Usual: TV watching(Q1) – TV watching(Q2)

Pearson r = 0.31 (P < 0.024)

    

Yesterday: other sedentary(Q1) – other sedentary(Q2)

Pearson r = 0.32 (P < 0.019)

    

Usual: other sedentary(Q1) – other sedentary(Q2)

Pearson r = 0.30 (P < 0.032)

Youth

Troped (2007)[73]

5 - 40 days

YRBS

VPA(Q1) – VPA(Q2)

ICC = 0.46

    

MPA(Q1) – MPA(Q2)

ICC = 0.51

Youth

Weston (1997)[74]

Within 1 hour

PDPAR

TEE(Q1) – TEE(Q2)

Pearson r = 0.98 (P < 0.01)

Adults

Brown (2008)[88]

7 - 28 days

AAS

Frequency/week(Q1) – frequency/week(Q2)

Spearman r = 0.58

    

Total min/week(Q1) – total min/week(Q2)

Spearman r = 0.64

Adults

Bull (2009)[58]

3 - 7 days

GPAQ

Leisure: total min(Q1) – total min(Q2)

Spearman r = 0.78 (P < 0.01)

    

Occupation: total min(Q1) – total min(Q2)

Spearman r = 0.77 (P < 0.01)

    

Transportation: total min(Q1) – total min(Q2)

Spearman r = 0.81 (P < 0.01)

    

Leisure: sedentary(Q1) – sedentary(Q2)

κ (% agreement) = 0.68 (85.6)

    

Occupation: sedentary(Q1) – sedentary(Q2)

κ (% agreement) = 0.73 (86.9)

Adults

Cust (2008)[102]

10 months

EPAQ

Total MET-hr/week(Q1) – total MET-hr/week(Q2)

Spearman r (95 % CI) = 0.65 (0.55;0.72), P < 0.0001

    

Total PA index(Q1) – total PA index(Q2)

κ (95 % CI) = 0.62 (0.53;0.71), P < 0.0001

    

Cambridge PA index(Q1) – Cambridge PA index(Q2)

κ (95 % CI) = 0.66 (0.58;0.74), P < 0.0001

Adults

Cust (2009)[103]

10 months

EPAQ

High confidence: total PA index(Q1) – total PA index(Q2)

κ (95 % CI) = 0.65 (0.53;0.76)

    

Low confidence: total PA index(Q1) – total PA index(Q2)

κ (95 % CI) = 0.58 (0.45;0.71)

    

High confidence: Cambridge PA index(Q1) – Cambridge PA index(Q2)

κ (95 % CI) = 0.73 (0.61;0.84)

    

Low confidence: Cambridge PA index(Q1) – Cambridge PA index(Q2)

κ (95 % CI) = 0.59 (0.47;0.71)

   

IPAQ-s

High confidence: total MET-hr/week(Q1) – total MET-hr/week(Q2)

Spearman r (95 % CI) = 0.53 (0.36;0.67)

    

Low confidence: total MET-hr/week(Q1) – total MET-hr/week(Q2)

Spearman r (95 % CI) = 0.33 (0.11;0.52)

    

High confidence: sitting hr/day(Q1) – sitting hr/day(Q2)

Spearman r (95 % CI) = 0.50 (0.32;0.65)

    

Low confidence: sitting hr/day(Q1) – sitting hr/day(Q2)

Spearman r (95 % CI) = 0.65 (0.51;0.75)

Adults

Duncan (2001)[104]

7 days

7DPAR

TEE(Q1) – TEE(Q2)

ICC (95 % CI) = 0.44 (0.26;0.59)

Adults

Gauthier (2009)[105]

1 day

IPAQ-SALVCF

Total MET-min/week(Q1) – total MET-min/week(Q2)

ICC (95 % CI) = 0.929 (0.860;0.965), P < 0.01

    

Sitting(Q1) – sitting(Q2)

ICC (95 % CI) = 0.899 (0.800;0.950), P < 0.01

Adults

Hallal (2010)[108]

5 days

IPAQ

Total score(T1) – total score(T2)

Spearman r = 0.90

MD = 3 min, κ (% agreement) = 0.78 (90.0)

    

Total score(T1T2) – total score(FTF)

Spearman r = 0.87

MD = 30 min, κ (% agreement) = 0.69 (85.5)

Adults

Kurtze (2008)[54]

1 week

IPAQ-s

VPA hr/day(Q1) – VPA hr/day(Q2)

ICC (95 % CI) = 0.62 (0.47;0.73)

    

MPA hr/day(Q1) – MPA hr/day(Q2)

ICC (95 % CI) = 0.30 (0.09;0.49)

    

Walking hr/day(Q1) – walking hr/day(Q2)

ICC (95 % CI) = 0.42 (0.23;0.59)

    

Sitting hr/day(Q1) – sitting hr/day(Q2)

ICC (95 % CI) = 0.80 (0.70;0.87)

Adults

MacFarlane (2007)[99]

3 days

IPAQ-s

Total MET-min/week(Q1) – total MET-min/week(Q2)

ICC (95 % CI) = 0.79 (0.66;0.88), %CV (95 % CI) = 26 (22;33)

    

Sitting MET-min/week(Q1) – sitting MET-min/week(Q2)

ICC (95 % CI) = 0.97 (0.95;0.98), %CV (95 % CI) = 15 (12;18)

Adults

MacFarlane (2010)[110]

3 days

IPAQ-LC

Total MET-min/week(Q1) – total MET-min/week(Q2)

ICC = 0.93, %CV = 22.8

    

Sitting MET-min/week(Q1) – sitting MET-min/week(Q2)

ICC = 0.71, %CV = 15.0

Adults

Matton (2007)[111]

2 weeks

FPACQ

Employed/unemployed men: total EE(Q1) – total EE(Q2)

ICC (95 % CI) = 0.95 (0.89;0.97)

    

Employed/unemployed women: total EE(Q1) – total EE(Q2)

ICC (95 % CI) = 0.92 (0.85;0.96)

    

Retired men: total EE(Q1) – total EE(Q2)

ICC (95 % CI) = 0.90 (0.76;0.96)

    

Retired women: total EE(Q1) – total EE(Q2)

ICC (95 % CI) = 0.96 (0.90;0.99)

    

Employed/unemployed men: PAL(Q1) – PAL(Q2)

ICC (95 % CI) = 0.92 (0.84;0.96)

    

Employed/unemployed women: PAL(Q1) – PAL(Q2)

ICC (95 % CI) = 0.78 (0.61;0.88)

    

Retired men: PAL(Q1) – PAL(Q2)

ICC (95 % CI) = 0.89 (0.76;0.96)

    

Retired women: PAL(Q1) – PAL(Q2)

ICC (95 % CI) = 0.77 (0.47;0.91)

    

Employed/unemployed men: TV hr/week(Q1) – TV hr/week(Q2)

ICC (95 % CI) = 0.93 (0.86;0.97)

    

Employed/unemployed women: TV hr/week(Q1) – TV hr/week(Q2)

ICC (95 % CI) = 0.92 (0.84;0.96)

    

Retired men: TV hr/week(Q1) – TV hr/week(Q2)

ICC (95 % CI) = 0.76 (0.49;0.89)

    

Retired women: TV hr/week(Q1) – TV hr/week(Q2)

ICC (95 % CI) = 0.89 (0.72;0.96)

Adults

Nang (2011)[55]

2 - 10 months

IPAQ

VPA(Q1) – VPA(Q2)

Spearman r = 0.38 (P < 0.05)

    

MPA(Q1) – MPA(Q2)

Spearman r = 0.58 (P < 0.0001)

   

SP2PAQ

VPA(Q1) – VPA(Q2)

Spearman r = 0.75 (P < 0.0001)

    

MPA(Q1) – MPA(Q2)

Spearman r = 0.55 (P < 0.0001)

Adults

Pettee-Gabriel (2009)[91]

1 - 4 weeks

PMMAQ

MET-hr/week(Q1) – MET-hr/week(Q2)

ICC (95 % CI) = 0.64 (0.48;0.77), P < 0.0001

   

PWMAQ

MET-hr/week(Q1) – MET-hr/week(Q2)

ICC (95 % CI) = 0.74 (0.60;0.83), P < 0.0001

   

NHS-PAQ

MET-hr/week(Q1) – MET-hr/week(Q2)

ICC (95 % CI) = 0.48 (0.26;0.65), P < 0.0001

   

AAS

Min/day(Q1) – min/day(Q2)

ICC (95 % CI) = 0.32 (0.09;0.52), P < 0.01

   

WHI-PAQ

MET-hr/week(Q1) – MET-hr/week(Q2)

ICC (95 % CI) = 0.91 (0.86;0.95), P < 0.0001

Adults

Richardson (2001)[100]

1 month

S7DR

Men: total MET-min/day(Q1) – total MET-min/day(Q2)

Spearman r = 0.60 (P < 0.01)

    

Women: total MET-min/day(Q1) – total MET-min/day(Q2)

Spearman r = 0.36 (P < 0.05)

Adults

Saglam (2010)[112]

3 - 7 days

IPAQ

Total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r (95 % CI) = 0.64 (0.56;0.72), P < 0.001

    

Sitting min(Q1) – sitting min(Q2)

Spearman r (95 % CI) = 0.83 (0.77;0.89), P < 0.001

   

IPAQ-s

Total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r (95 % CI) = 0.69 (0.61;0.77), P < 0.001

    

Sitting min(Q1) – sitting min(Q2)

Spearman r (95 % CI) = 0.78 (0.71;0.85), P < 0.001

Adults

Schmidt (2006)[92]

7 days

KPAS-mod

Total activity score(Q1) – total activity score(Q2)

ICC = 0.84

    

Weighted activity score(Q1) – weighted activity score(Q2)

ICC = 0.76

Adults

Smitherman (2009)[113]

2 weeks

JPAC

JPAC total score(Q1) – JPAC total score(Q2)

ICC = 0.99

Adults

Trinh (2009)[115]

2 weeks (dry season)

GPAQ

GPAQ total score(Q1) – GPAQ total score(Q2)

Spearman r = 0.69 (P < 0.001)

MD (95 % LoA) = 1.00 (0.03;31.82), κ (95 % CI) = 0.66 (0.53;0.79)

  

2 months (wet season)

 

GPAQ total score(Q1) – GPAQ total score(Q2)

Spearman r = 0.55 (P < 0.001)

MD (95 % LoA) = 1.12 (0.02;71.09), κ (95 % CI) = 0.57 (0.46;0.65)

  

2 weeks (dry season)

 

Sedentary time(Q1) – sedentary time(Q2)

Spearman r = 0.69 (P < 0.001)

κ (95 % CI) = 0.61 (0.58;0.70)

  

2 months (wet season)

 

Sedentary time(Q1) – sedentary time(Q2)

Spearman r = 0.50 (P < 0.001)

κ (95 % CI) = 0.45 (0.36;0.54)

Elderly

De Abajo (2001)[76]

2 weeks

YPAS

Total time(Q1) – total time(Q2)

ICC = 0.66 (P = 0.001)

    

Total EE(Q1) – total EE(Q2)

ICC = 0.65 (P = 0.001)

    

YPAS summary index(Q1) – YPAS summary index(Q2)

ICC = 0.31 (P = 0.002)

    

Sitting(Q1) – sitting(Q2)

ICC = 0.29 (P = 0.003)

Elderly

Dinger (2004)[77]

3 days

PASE

Total PASE score(Q1) – total PASE score(Q2)

ICC (95 % CI) = 0.91 (0.83;0.94)

Elderly

Dubbert (2004)[78]

2 - 4 weeks

7DPAR

TEE(Q1) – TEE(Q2)

ICC = 0.89 (P < 0.001)

Elderly

Giles (2009)[79]

1 - 2 weeks

CHAMPS-MMSCV

Volume: MET-min/week(Q1) – MET-min/week(Q2)

ICC (95 % CI) = 0.84 (0.69;0.91), Spearman r = 0.62

    

Frequency: sessions/week(Q1) – sessions/week(Q2)

ICC (95 % CI) = 0.89 (0.77;0.95), Spearman r = 0.79

    

Duration: min/week(Q1) – min/week(Q2)

ICC (95 % CI) = 0.81 (0.63;0.90), Spearman r = 0.57

Elderly

Hagiwara (2008)[80]

3 - 4 weeks

PASE

Total PASE score(Q1) – total PASE score(Q2)

ICC (95 % CI) = 0.65 (0.58;0.72)

Elderly

Harada (2001)[82]

2 weeks

CHAMPS

EE(Q1) – EE(Q2)

ICC = 0.62, Pearson r = 0.62

Elderly

Kolbe-Alexander (2006)[83]

3 - 5 days

IPAQ-s

Men: total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r = 0.54 (P = 0.0001)

MD (95 % LoA) = 324.58 ± 7534.85 MET-min/week

    

Women: total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r = 0.60 (P = 0.0000)

MD (95 % LoA) = 347.14 ± 4016.88 MET-min/week

    

Men: sitting MET-hr/week(Q1) – sitting MET-hr/week(Q2)

Spearman r = 0.76 (P = 0.0000)

    

Women: sitting MET-hr/week(Q1) – sitting MET-hr/week(Q2)

Spearman r = 0.77 (P = 0.0000)

   

YPAS

Men: total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r = 0.57 (P = 0.00001)

MD (95 % LoA) = −582.17 ± 4867.14 MET-min/week

    

Women: total MET-min/week(Q1) – total MET-min/week(Q2)

Spearman r = 0.62 (P = 0.0000)

MD (95 % LoA) = 26.77 ± 4474.64 MET-min/week

Elderly

Tomioka (2011)[85]

2 weeks

IPAQ-s

Young old men: MET-min/week(Q1) – MET-min/week(Q2)

ICC (95 % CI) = 0.65 (0.46;0.78)

    

Young old women: MET-min/week(Q1) – MET-min/week(Q2)

ICC (95 % CI) = 0.57 (0.34;0.72)

    

Old old men: MET-min/week(Q1) – MET-min/week(Q2)

ICC (95 % CI) = 0.50 (0.22;0.68)

    

Old old women: MET-min/week(Q1) – MET-min/week(Q2)

ICC (95 % CI) = 0.56 (0.30;0.72)

    

Young old men: sitting hr/day(Q1) – sitting hr/day(Q2)

ICC (95 % CI) = 0.82 (0.71;0.88)

    

Young old women: sitting hr/day(Q1) – sitting hr/day(Q2)

ICC (95 % CI) = 0.70 (0.54;0.80)

    

Old old men: sitting hr/day(Q1) – sitting hr/day(Q2)

ICC (95 % CI) = 0.66 (0.48;0.78)

    

Old old women: sitting hr/day(Q1) – sitting hr/day(Q2)

ICC (95 % CI) = 0.67 (0.48;0.80)

     

Median ICC = 0.71 (youth: 0.64, adults: 0.79, elderly: 0.65)

 
     

Median Spearman r = 0.62 (youth: –, adults: 0.64, elderly: 0.60)

 
     

Median Pearson r = 0.62 (youth: 0.605, adults: –, elderly: 0.62)

 
      

Median κ = 0.655 (youth: –, adults: 0.655, elderly: –)

Q1 = first completed questionnaire, Q2 = second completed questionnaire, r = correlation coefficient (rho), ICC = Intraclass Correlation Coefficient, CI = Confidence Interval (lower;upper), %CV = coefficient of variation (within subjects standard deviation of typical error) as a percentage of the mean score, κ = kappa (i.e. Cohen weighted kappa unless specified otherwise), LoA = Limits of Agreement, MD = Mean Difference, – = not stated.

Bull (2009): Total min = total time per domain of the pooled data (n = 2221) of 7 countries (Bangladesh, China, Ethiopia, Indonesia, South Africa, Japan, Taiwan). Leisure = discretionary domain, occupation = work domain, transportation = transport domain. Sedentary = categorical variable of pooled data (n = 1524) for no physical activity in the discretionary or work domain.

Corder (2009): PAEE in kJ/kg/day for total group, or for 12 – 13 or 16 – 17 year old children. Lifestyle score = summed score of four multiple choice questions regarding active transport, school break activities, activity outside school, and the amount of "exercise that makes you out of breath".

Cust (2008): Total MET-hr/week = total MET hours per week of non-occupational activity. Total PA index = cross-tabulation of level of occupational activity with combined recreational and household activities - inactive, moderately inactive, moderately active, active. Cambridge PA index = index based on occupational, cycling and sports activity (generally more intense activities).

Cust (2009): Results are stratified according to the group of participants reporting high or low confidence in recall of PA. High confidence = group of participants reporting high self-reported confidence in recall of physical activity. Low confidence = group of participants reporting low self-reported confidence in recall of physical activity.

De Abajo (2001): EE in kJ/day. YPAS summary index = summed time for each activity, expressed in hours per week for each subject. Individual indices were created by multiplying a frequency score by a duration score and multiplying again by a weighting factor.

Dinger (2004): Total PASE score = weighted and summed score of individual items using the PASE scoring algorithm.

Eisenmann (2002): Same day = beginning and end of the day. Total leisure activity score was calculated by multiplying the frequency of each category by the MET value and summing the score.

Gauthier (2009): Total MET-min/week = total activity excluding sitting.

Hagiwara (2008): PASE score was calculated by adding the score for each component determined on the basis of the time spent on each activity or the presence or absence of activity over the past 7 days. In the paper more details (κ or weighted κ and the proportion of consistency) are reported for each separate activity component.

Hallal (2010): Total score = sum of minutes spent on MPA (including walking) per week, and twice the number of minutes spent on VPA. T1 = telephone interview on day 1. T2 = telephone interview on day 6. FTF = face-to-face interview on day 1.

Harada (2001): EE in kcal/week.

Huang (2009): Activity intensities classified according to a compendium of physical activities.

Kolbe-Alexander (2006): sitting = time spent sitting during a week and weekend day.

Kurtze (2008): VPA = 8 METs, MPA = 4 METs, Walking = 3.3 METs on average.

MacFarlane (2007/2010): Total MET-min/week = total activity excluding sitting (1 MET).

Matton (2007): EE in kcal/week. PAL is calculated as total EE divided by 168 (number of hours per week) and the reported body weight. TV hr/week = time per week spent watching television or videos or playing computer games during weekdays and weekends.

Nang (2011): VPA(Q) = 3–6 METs kcal/day, MPA(Q) = >6 METs kcal/day.

Pettee-Gabriel (2009): Test-retest period = 1 week for PWMAQ (n = 65), NHS-PAQ (n = 62), AAS (n = 65), WHI-PAQ (n = 63) and 1 month for PMMAQ (n = 65).

Schmidt (2006): Total activity score = activity score of all four domains, calculated as: (household/caregiving index*0.25 + occupational index*0.25 + active living index*0.25 + sports/exercise index*0.25)*4. Weighted activity score = activity score of all four domains, calculated as: (household/caregiving index*0.50 + occupational index*0.20 + active living index*0.25 + sports/exercise index*0.05)*4.

Smitherman (2009): JPAC total score = total score calculated by summing the 4 index scores (active living, work, home/family/yard/garden, sport/exercise index) and can range from 3 to 20.

Tomioka (2011): Young old = age 65–74, old old = age 75–89.

Treuth (2004): GAQ score yesterday = summary score estimated from 28 physical activities performed on the previous day (yesterday), applying the code 0 for the response "none", 1 for the response "less than 15 min", and 10 for the response "15 min or more". GAQ score usual = summary score estimated from usual activities, based on frequency of physical activities performed, applying the code 0 for the response "none", 1 for the response "a little", and 10 for the response "a lot". The GAQ summary scores were computed as the total MET-weighted score divided by the number of nonmissing items. TV watching = time spent watching TV or video. Other sedentary = time spent performing computer or video games, arts and crafts, board games, homework or reading, talking on phone or hanging out.

Trinh (2009): GPAQ total score = score of 19 items following the GPAQ analysis protocol. Sedentary time = time spent sitting or reclining. MD (95 % LoA) = log-transformed average difference with 95 % limits of agreement. Compared with the baseline assessment, the GPAQ score was on average not different and 12 % higher, respectively, 2 weeks later.

Troped (2007): MPA = number of days participating in ≥ 30 min of moderate PA during past 7 days. VPA = number of days participating in ≥ 20 min of vigorous PA during past 7 days.

Weston (1997): TEE in kcal/kg/day.

Most studies examining the reliability of existing PAQs reported reliability as ICC (n = 20), Pearson/Spearman correlation coefficients (n = 8); some studies also used a combination of correlation statistics (n = 7). Similar to the new PAQs, the existing PAQs demonstrated moderate correlations for reliability. Median correlations from reported data for recall of sedentary behaviours were divergent: ICC = 0.76, Spearman r = 0.725, Pearson r = 0.305, kappa = 0.645.

Youth

Median reliability correlations for the youth were as follows: ICC = 0.64, Pearson r = 0.605. The CHASE (ICC = 0.02) and the CPAQ (ICC = 0.25) showed poor test-retest reliability, whereas the reliability was strong for YPAQ (ICC = 0.79–0.86) in the same study [61]. Previous day physical activity recall instruments proved to be highly reliable in children (ICC = 0.98 [60], r = 0.98 [74]).

Adults

Median reliability correlations for adults were as follows: ICC = 0.79, Spearman r = 0.64, kappa = 0.655. The IPAQ-SALVCF (ICC = 0.929) [105], IPAQ long version (r = 0.87–0.90 [108], ICC = 0.93 [110]), IPAQ short version (ICC = 0.79) [99], FPACQ (ICC = 0.77–0.96) [111], KPAS-mod (ICC = 0.76–0.84) [92] and the JPAC (ICC = 0.99) [113] showed acceptable or strong reliability. Notably, the IPAQ-s showed a wide range of results for reliability, with ICCs ranging from 0.27–0.97 for sitting [54, 69, 83, 85, 99, 103, 112], 0.10–0.42 for walking [54, 69], 0.30–0.34 for MPA [54, 69], 0.30–0.62 for VPA [54, 69], and 0.33–0.79 for total PA [83, 85, 99, 103, 112]. For sedentary time the short IPAQ appeared to be the most reliable questionnaire when the test retest duration was short (i.e. 3 days, [ICC = 0.97]) [99]. All existing PAQs for adults reported acceptable to high reliability properties, overall.

Elderly

Median reliability correlations for the elderly were as follows: ICC = 0.65, Spearman r = 0.60, Pearson r = 0.62. Similarly, all existing PAQs for elderly also showed overall acceptable to high reliability, with the PASE (ICC = 0.91) [77], 7DPAR (ICC = 0.89) [78] and CHAMPS-MMSCV (ICC = 0.81–0.89) [79] performing best.

Validity

All validity results for existing PAQs are listed in Table 7.
Table 7

Validity results of existing PAQs

Age Group

Reference

Criterion method

Duration of validation

PAQ

Variables tested

Criterion intensity thresholds

Validity results

       

Correlation coefficients

Agreement

Youth

Affuso (2011)[59]

Acc (ActiGraph)

3 days

SAPAC

Sedentary mins(Q) – sedentary mins(Acc)

<100 counts/min

Pearson r (95 % CI) = 0.18 (0.07;0.28), Spearman r (95 % CI) = 0.14 (0.05;0.23)

Youth

Allor (2001)[60]

Acc (Caltrac)

2 days

PDPAR

EE(Q) – EE(Acc)

Pearson r = 0.76 (P < 0.01)

MD = ~100 kcal/hr (P < 0.01)

  

HR

2 days

 

EE(Q) – EE(HR)

Pearson r = 0.50 (P < 0.01)

MD = ~100 kcal/hr

Youth

Corder (2009)[61]

DLW

11 days

YPAQ

12-13 yrs: PAEE(Q) – PAEE(DLW)

Spearman r = 0.09 (P = 0.67)

MD (95 % LoA) = 0.59 ± 6.3 kJ/kg/day

     

16-17 yrs: PAEE(Q) – PAEE(DLW)

Spearman r = 0.46 (P = 0.03)

MD (95 % LoA) = 0.32 ± 4.6 kJ/kg/day

  

Acc (ActiGraph)

11 days

 

12-13 yrs: MVPA(Q) – MVPA(Acc)

≥1952 counts/min

Spearman r = 0.42 (P = 0.04)

MD (95 % LoA) = 2.01 ± 2.25 min/week

     

16-17 yrs: MVPA(Q) – MVPA(Acc)

≥1952 counts/min

Spearman r = 0.11 (P = 0.61)

MD (95 % LoA) = 1.38 ± 2.97 min/week

  

DLW

11 days

CPAQ

PAEE(Q) – PAEE(DLW)

Spearman r = 0.22 (P = 0.28)

MD (95 % LoA) = 0.76 ± 3.1 kJ/kg/day

  

Acc (ActiGraph)

11 days

 

MVPA(Q) – MVPA(Acc)

≥1952 counts/min

Spearman r = 0.42 (P = 0.04)

MD (95 % LoA) = 1.63 ± 2.24 min/week

  

DLW

11 days

CHASE

Lifestyle score(Q) – PAEE(DLW)

Spearman r = 0.45 (P = 0.02)

  

Acc (ActiGraph)

11 days

 

Lifestyle score(Q) – MVPA(Acc)

≥1952 counts/min

Spearman r = 0.12 (P = 0.57)

  

DLW

11 days

SWAPAQ

PAEE(Q) – PAEE(DLW)

Spearman r = 0.40 (P = 0.04)

MD (95 % LoA) = 0.46 ± 8.5 kJ/kg/day

  

Acc (ActiGraph)

11 days

 

MVPA(Q) – MVPA(Acc)

≥1952 counts/min

Spearman r = 0.23 (P = 0.27)

MD (95 % LoA) = 1.03 ± 2.58 min/week

Youth

Eisenmann (2002)[62]

Acc (Caltrac)

1 day

GLTEQ

Total leisure activity score(Q) – counts/hr(Acc)

Pearson r = 0.50

Youth

Gwynn (2010)[63]

Acc (ActiGraph)

7 days

MRPARQ

MVPA min/day(Q) – MVPA min/day(Acc)

≥1952 counts/min

Pearson r = 0.37 (P < 0.05), ICC = 0.25 (P < 0.05)

Youth

Hagströmer (2008)[56]

Acc (ActiGraph)

7 days

IPAQ-A

Total MET-min/day(Q) – total counts/min(Acc)

Spearman r = 0.20 (P < 0.01)

Youth

Huang (2009)[64]

Acc (ActiGraph)

7 days

CLASS

Boys: VPA min/week(Q) – VPA min/week(Acc)

≥6 METs

Spearman r = 0.29

MD (95 % LoA) = 12.6 ± 47.4 min/week

     

Girls: VPA min/week(Q) – VPA min/week(Acc)

≥6 METs

Spearman r = 0.43 (P < 0.05)

MD (95 % LoA) = 12.6 ± 47.4 min/week

     

Boys: MVPA min/week(Q) – MVPA min/week(Acc)

≥3 METs

Spearman r = 0.27

MD (95 % LoA) = −6.2 ± 95.3 min/week

     

Girls: MVPA min/week(Q) – MVPA min/week(Acc)

≥3 METs

Spearman r = 0.48 (P < 0.05)

MD (95 % LoA) = −6.2 ± 95.3 min/week

     

Boys: MPA min/week(Q) – MPA min/week(Acc)

3-5.9 METs

Spearman r = 0.33

MD (95 % LoA) = −18.9 ± 70.4 min/week

     

Girls: MPA min/week(Q) – MPA min/week(Acc)

3-5.9 METs

Spearman r = 0.29 (P < 0.05)

MD (95 % LoA) = −18.9 ± 70.4 min/week

     

Boys: sedentary min/week(Q) – sedentary min/week(Acc)

<100 counts/min

Spearman r = 0.06

     

Girls: sedentary min/week(Q) – sedentary min/week(Acc)

<100 counts/min

Spearman r = 0.25 (P < 0.05)

Youth

Kowalski (1997)[65]

Acc (Caltrac)

7 days

PAQ-C

PAQ-C score(Q) – total counts(Acc)

Pearson r = 0.39 (P < 0.05)

Youth

Martinez-Gomez (2010)[66]

Acc (ActiGraph)

3 days

BAD

Total MET-min/day(Q) – total counts/day(Acc)

Spearman r = 0.29

     

Total MET-min/day(Q) – total counts/min/day(Acc)

Spearman r = 0.33

Youth

Martinez-Gomez (2011)[67]

Acc (ActiGraph)

7 days

PAQ-A

PAQ-A score(Q) – total counts/min(Acc)

Spearman r = 0.39 (P < 0.001)

     

PAQ-A score(Q) – MVPA mins(Acc)

≥1952 counts/min

Spearman r = 0.31 (P < 0.001)

Youth

Mota (2002)[68]

Acc (ActiGraph)

3 days

WAC

METs/15 min(Q) – counts/min(Acc)

Pearson r = 0.30 (P = 0.01)

Youth

Ottevaere (2011)[57]

Acc (ActiGraph)

7 days

IPAQ-A

VPA min/day(Q) – VPA min/day(Acc)

≥4000 counts/min

Spearman r = 0.25 (P < 0.01)

MD (95 % LoA) = 13.2 ± 78.2 min/day

     

MVPA min/day(Q) – MVPA min/day(Acc)

≥2000 counts/min

Spearman r = 0.21 (P < 0.01)

     

MPA min/day(Q) – MPA min/day(Acc)

2000-3999 counts/min

Spearman r = 0.15 (P < 0.01)

MD (95 % LoA) = 31.6 ± 105.6 min/day

Youth

Rangul (2008)[69]

Acc (ActiReg)

7 days

HBSC

Frequency(Q) – TEE(Acc)

Spearman r = 0.20

     

Frequency(Q) – PAL(Acc)

Spearman r = 0.02

     

Duration(Q) – TEE(Acc)

Spearman r = 0.23

     

Duration(Q) – PAL(Acc)

Spearman r = 0.01

    

IPAQ-s

VPA min/day(Q) – TEE(Acc)

Spearman r = −0.14

     

VPA min/day(Q) – PAL(Acc)

Spearman r = −0.08

     

MPA min/day(Q) – TEE(Acc)

Spearman r = 0.01

     

MPA min/day(Q) – PAL(Acc)

Spearman r = 0.01

     

Walking min/day(Q) – TEE(Acc)

Spearman r = 0.24

     

Walking min/day(Q) – PAL(Acc)

Spearman r = 0.43 (P < 0.01)

     

Sitting min/day(Q) – TEE(Acc)

Spearman r = −0.04

     

Sitting min/day(Q) – PAL(Acc)

Spearman r = −0.29

Youth

Scerpella (2002)[70]

Acc (Caltrac)

2x 3 days

GSQ

Godin-Shephard score(Q) – Caltrac score(Acc)

Spearman r = 0.102 (P = 0.422)

Youth

Slinde (2003)[71]

DLW

14 days

MLTPAQ

TEE(Q) – TEE(DLW)

Spearman r = 0.49 (P < 0.01)

    

eMLTPAQ

TEE(Q) – TEE(DLW)

Spearman r = 0.65 (P < 0.01)

MD (95 % LoA) = 2.8 ± 2.8 MJ/day

     

Sedentary min/day(Q) – TEE(DLW)

Spearman r = 0.030 (P = 0.86)

Youth

Treuth (2004)[72]

Acc (ActiGraph)

3 days

GAQ

Baseline: yesterday GAQ score(Q) – mean counts/min(Acc)

Pearson r = 0.06 (P = 0.42)

     

Follow-up: yesterday GAQ score(Q) – mean counts/min(Acc)

Pearson r = 0.08 (P = 0.28)

     

Baseline: usual GAQ score(Q) – mean counts/min(Acc)

Pearson r = 0.12 (P = 0.10)

     

Follow-up: usual GAQ score(Q) – mean counts/min(Acc)

Pearson r = 0.07 (P = 0.36)

Youth

Troped (2007)[73]

Acc (ActiGraph)

7 days

YRBS

Total VPA min/day(Q) – total VPA min/day(Acc)

>6 METs

Sensitivity = 0.86, specificity: 0.26

κ = −0.002 – 0.06

     

Total MPA min/day(Q) – total MPA min/day(Acc)

3-6 METs

Sensitivity = 0.23, specificity: 0.92

κ = −0.05 – 0.03

Youth

Weston (1997)[74]

Acc (Caltrac)

1 day (after school)

PDPAR

TEE(Q) – total counts(Acc)

Pearson r = 0.77 (P < 0.01)

  

HR (Polar)

1 day (after school)

 

EE(Q) – %HRR(HR)

Pearson r = 0.53 (P < 0.01)

Adults

Ainsworth (1999)[87]

Acc (Caltrac)

7 days

TOQ

MPA MET-min/week(Q) – EE(Acc)

Pearson r = 0.34 (P < 0.05)

    

7DR-O

7DR scores(Q) – EE(Acc)

Low correlations (P > 0.05)

Adults

Bassett (2000)[101]

Ped (Yamax)

7 days

CAQ

Men: distance(Q) – distance(Ped)

r = 0.346 (P = 0.02)

     

Women: distance(Q) – distance(Ped)

r = 0.481 (P = 0.001)

Adults

Brown (2008)[88]

Acc (ActiGraph)

7 days

AAS

Frequency/week(Q) – frequency(Acc)

≥3 METs, ≥1952 counts/min

Spearman r = 0.48 (P = 0.001)

     

Total min/week(Q) – MVPA(Acc)

≥3 METs, ≥1952 counts/min

Spearman r = 0.52 (P < 0.001)

     

Total min/week(Q) – total counts(Acc)

Spearman r = 0.23 (P = 0.14)

Adults

Bull (2009)[58]

Acc (MTI)

> 7 days

GPAQ

China: VPA(Q) – mean VPA counts/day(Acc)

Spearman r = 0.23 (P < 0.05)

     

South Africa: VPA(Q) – mean VPA counts/day(Acc)

Spearman r = 0.26 (P < 0.05)

     

China: MPA(Q) – mean MPA counts/day(Acc)

Spearman r = 0.23 (P < 0.05)

     

South Africa: MPA(Q) – mean MPA counts/day(Acc)

Spearman r = −0.03

     

China: sedentary min/day(Q) – mean sedentary counts/day(Acc)

<100 counts/min

Spearman r = 0.40 (P < 0.05)

     

South Africa: sedentary min/day(Q) – mean sedentary counts/day(Acc)

<100 counts/min

Spearman r = −0.02

Adults

Conway (2002)[94]

DLW

14 days

7DPAR

TEE(Q) – TEE(DLW)

R2 = 0.10

MD (±SEM) = 0.91 ± 0.42 (7.9 ± 3.2 %) MJ/day

    

S7DR

TEE(Q) – TEE(DLW)

R2 = 0.14

MD (±SEM) = 4.14 ± 1.36 (30.6 ± 9.9 %) MJ/day

Adults

Cust (2008)[102]

Acc (ActiGraph)

3x 7 days

EPAQ

Total MET-hr/week(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.21 (0.07;0.35), P < 0.01

     

Total PA index(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.29 (0.15;0.42), P < 0.0001

     

Cambridge PA index(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.32 (0.19;0.45), P < 0.0001

Adults

Cust (2009)[103]

Acc (ActiGraph)

3x 7 days

EPAQ

High confidence: total PA index(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.37 (0.17;0.54)

     

Low confidence: total PA index(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.22 (0.02;0.41)

     

High confidence: Cambridge PA index(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.30 (0.10;0.48)

     

Low confidence: Cambridge PA index(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.35 (0.15;0.52)

    

IPAQ-s

High confidence: total MET-hr/week(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.26 (0.04;0.45)

     

Low confidence: total MET-hr/week(Q) – total MET-hr/week(Acc)

≥574 counts/min

Spearman r (95 % CI) = 0.27 (0.07;0.46)

     

High confidence: sitting hr/day(Q) – sedentary(Acc)

<100 counts/min

Spearman r (95 % CI) = 0.36 (0.18;0.52)

     

Low confidence: sitting hr/day(Q) – sedentary(Acc)

<100 counts/min

Spearman r (95 % CI) = 0.45 (0.25;0.62)

Adults

Duncan (2001)[104]

HR (Polar)

1 weekday

7DPAR

Very hard activity(Q) – very hard activity(HR)

≥ 85 % HRR

MD = 0.00 hours

     

Hard activity(Q) – hard activity(HR)

60-84 % HRR

MD = 0.02 hours

     

Moderate activity(Q) – moderate activity(HR)

45-59 % HRR

MD = 0.21 hours

Adults

Ekelund (2006)[95]

Acc (ActiGraph)

7 days

IPAQ-s

Total MET-min/day(Q) – mean counts/min(Acc)

Pearson r = 0.34 (P < 0.001)

MD (95 % CI) = −25.9 (−172;120) min/day, P < 0.001

     

Sitting(Q) – sedentary min/day(Acc)

<100 counts/min

Pearson r = 0.16 (P < 0.05)

Adults

Gauthier (2009)[105]

Ped (Yamax)

7 days

IPAQ-SALVCF

Walking(Q) – step counts(Ped)

Pearson r = 0.493 (P < 0.005)

Adults

Hagströmer (2006)[106]

Acc (ActiGraph)

7 days

IPAQ

Total MET-hr/week(Q) – total counts/min(Acc)

Spearman r = 0.55 (P < 0.001)

MD (95 % LoA) = 1.0 ± 16.7 hr/week

     

Sitting hr/week(Q) – inactivity hr/week(Acc)

<101 counts/min

Spearman r = 0.17

Adults

Hagströmer (2010)[107]

Acc (ActiGraph)

7 days

IPAQ

Total min/day(Q) – total min/day(Acc)

Spearman r = 0.28 (P < 0.01)

     

Total MET-min/day(Q) – total counts/min(Acc)

Spearman r = 0.30 (P < 0.01)

     

Sitting min/day(Q) – sitting min/day(Acc)

<100 counts/min

Spearman r = 0.23 (P < 0.01)

MD (±SD) = 130  ±  207 min/day, P < 0.001, R2 = 0.50

Adults

Hallal (2010)[108]

Acc (ActiGraph)

4 days

IPAQ

Total score(Q) – total score(Acc)

≥1952 counts/min

Spearman r = 0.22

Adults

InterAct Consortium (2011)[51]

Acc + HR (Actiheart)

≥ 4 days

EPAQ-s

Total PA index(Q) – PAEE(Acc + HR)

Pearson r (95 % CI) = 0.14 (0.04;0.24), P = 0.000

     

Cambridge index(Q) – PAEE(Acc + HR)

Pearson r (95 % CI) = 0.33 (0.28;0.38), P = 0.118

     

Recreational index(Q) – PAEE(Acc + HR)

Pearson r (95 % CI) = 0.22 (0.16;0.28), P = 0.042

Adults

Jacobi (2009)[109]

Acc (ActiGraph)

7 days

MAQ

Total MET-hr/week(Q) – total counts/day(Acc)

Spearman r = 0.18 (P < 0.05)

     

Sedentary hr/week(Q) – sedentary hr/week(Acc)

<100 counts/min

Spearman r = 0.14 (P < 0.1)

Adults

Kurtze (2008)[54]

Acc (ActiReg)

7 days

IPAQ-s

Total MET-min/week(Q) – EE(Acc)

Spearman r = 0.26 (P < 0.05)

MD (95 % LoA) = −433 ± 2038 min/week

     

Total MET-min/week(Q) – PAL(Acc)

Spearman r = 0.29 (P < 0.05)

     

Sitting hr/day(Q) – EE(Acc)

Spearman r = −0.25 (P < 0.05)

     

Sitting hr/day(Q) – PAL(Acc)

Spearman r = −0.35 (P < 0.01)

Adults

Lee (2011)[98]

Acc (ActiGraph)

4 days

IPAQ-s

Total MET-min/week(Q) – total MET-min/week(Acc)

Spearman r (±SE) = 0.11 ± 0.03, P < 0.001

MD (±SE) = 2966.3 ± 140.1 MET-min/week, P < 0.001

     

Total MET-min/week(Q) – total counts/min(Acc)

Spearman r (±SE) = 0.16 ± 0.03, P < 0.001

Adults

MacFarlane (2007)[99]

Acc (ActiGraph)

7 days

IPAQ-s

Total min/week(Q) – total MVPA min/week(Acc)

≥1952 counts/min

Spearman r = 0.09 (P = 0.52)

R2 = 0.78, slope = 1.59 (P < 0.01); %bias = −102, %LoA = 176

Adults

MacFarlane (2010)[110]

Acc (ActiTrainer)

7 days

IPAQ-LC

Total MET-min/day(Q) – total MET-min/day(Acc)

Spearman r = 0.35 (P = 0.001)

MD (95 % LoA) = −21.6 ± 575.5 MET-min/day, P = 0.643

Adults

Mahabir (2006)[89]

DLW

HAQ

EE(Q) – EE(DLW)

Spearman r = 0.36 (P < 0.05)

MD (95 % LoA) = 1782.5 ± 2237.4 kcal/day

    

FCPQ

EE(Q) – EE(DLW)

Spearman r = 0.47 (P < 0.05)

MD (95 % LoA) = 732.8 ± 2126.7 kcal/day

    

CAPS-4WR

EE(Q) – EE(DLW)

Spearman r = 0.16

MD (95 % LoA) = 1765.8 ± 8973.7 kcal/day

    

CAPS-TWR

EE(Q) – EE(DLW)

Spearman r = 0.15

MD (95 % LoA) = −413.4 ± 2958.6 kcal/day

Adults

Matton (2007)[111]

Acc (RT3)

7 days

FPACQ

Employed/unemployed men: total EE(Q) – total EE(Acc)

Pearson r = 0.80 (P < 0.001)

t-test = 9.02 (P < 0.001)

     

Employed/unemployed women: total EE(Q) – total EE(Acc)

Pearson r = 0.65 (P < 0.001)

t-test = 10.18 (P < 0.001)

     

Retired men: total EE(Q) – total EE(Acc)

Pearson r = 0.55 (P < 0.01)

t-test = 11.48 (P < 0.001)

     

Retired women: total EE(Q) – total EE(Acc)

Pearson r = 0.85 (P < 0.001)

t-test = 10.79 (P < 0.001)

     

Employed/unemployed men: PAL(Q) – PAL(Acc)

Pearson r = 0.56 (P < 0.01)

t-test = 9.87 (P < 0.001)

     

Employed/unemployed women: PAL(Q) – PAL(Acc)

Pearson r = 0.44 (P < 0.05)

t-test = 11.68 (P < 0.001)

     

Retired men: PAL(Q) – PAL(Acc)

Pearson r = 0.39 (P < 0.05)

t-test = 11.91 (P < 0.001)

     

Retired women: PAL(Q) – PAL(Acc)

Pearson r = 0.50 (P < 0.05)

t-test = 13.93 (P < 0.001)

     

Employed/unemployed men: TV hr/week(Q) – TV hr/week(Acc)

Pearson r = 0.69 (P < 0.001)

t-test = −0.75

     

Employed/unemployed women: TV hr/week(Q) – TV hr/week(Acc)

Pearson r = 0.83 (P < 0.001)

t-test = −3.32 (P < 0.01)

     

Retired men: TV hr/week(Q) – TV hr/week(Acc)

Pearson r = 0.78 (P < 0.001)

t-test = −3.98 (P < 0.001)

     

Retired women: TV hr/week(Q) – TV hr/week(Acc)

Pearson r = 0.80 (P < 0.001)

t-test = −2.41 (P < 0.05)

Adults

Nang (2011)[55]

Acc (Actical)

5 days

IPAQ

VPA(Q) – VPA(Acc)

Spearman r = 0.18 (P < 0.05)

MD (95 % CI) = 139 (82;196) kcal/day

     

MPA(Q) – MPA(Acc)

Spearman r = 0.13

MD (95 % CI) = −169 (−236;-90) kcal/day

    

SP2PAQ

VPA(Q) – VPA(Acc)

Spearman r = 0.42 (P < 0.0001)

MD (95 % CI) = 81 (47;116) kcal/day

     

MPA(Q) – MPA(Acc)

Spearman r = 0.24 (P < 0.05)

MD (95 % CI) = −196 (−295;-97) kcal/day

Adults

Nicaise (2011)[90]

Acc (ActiGraph)

7 days

IPAQ

VPA(Q) – VPA(Acc)

≥5725 counts/min

Pearson r = −0.01

     

MPA(Q) – MPA(Acc)

1952-5724 counts/min

Pearson r = 0.08

     

Walking(Q) – steps(Acc)

Pearson r = 0.07

     

Weekday: sitting(Q) – light PA(Acc)

≤1951 counts/min

Pearson r = −0.17

     

Weekend: sitting(Q) – light PA(Acc)

≤1951 counts/min

Pearson r = −0.08

Adults

Pettee-Gabriel (2009)[91]

Acc (ActiGraph)

≥ 4 days

PMMAQ

Total MET-hr/week(Q) – total counts/day(Acc)

Spearman r = 0.60 (P < 0.0001)

     

Total MET-hr/week(Q) – mean counts/min/day(Acc)

Spearman r = 0.59 (P < 0.0001)

    

PWMAQ

Total MET-hr/week(Q) – total counts/day(Acc)

Spearman r = 0.60 (P < 0.0001)

     

Total MET-hr/week(Q) – mean counts/min/day(Acc)

Spearman r = 0.56 (P < 0.0001)

    

NHS-PAQ

Total MET-hr/week(Q) – total counts/day(Acc)

Spearman r = 0.46 (P < 0.001)

     

Total MET-hr/week(Q) – mean counts/min/day(Acc)

Spearman r = 0.42 (P < 0.001)

    

AAS

Total min/day(Q) – total counts/day(Acc)

Spearman r = 0.46 (P < 0.001)

     

Total min/day(Q) – mean counts/min/day(Acc)

Spearman r = 0.50 (P < 0.0001)

    

WHI-PAQ

Total MET-hr/week(Q) – total counts/day(Acc)

Spearman r = 0.47 (P < 0.001)

     

Total MET-hr/week(Q) – mean counts/min/day(Acc)

Spearman r = 0.45 (P < 0.001)

Adults

Philippaerts (1999)[96]

DLW

14 days

BAQ

Total activity index(Q) – ADMR(DLW)

Pearson r = 0.68 (P < 0.01)

     

Total activity index(Q) – PAL(DLW)

Pearson r = 0.69 (P < 0.001)

    

FCPQ

7 day index(Q) – ADMR(DLW)

Pearson r = 0.61 (P < 0.01)

     

7 day index(Q) – PAL(DLW)

Pearson r = 0.34

    

TCQ

TEE(Q) – ADMR(DLW)

Pearson r = 0.63 (P < 0.01)

     

TEE(Q) – PAL(DLW)

Pearson r = 0.64 (P < 0.01)

Adults

Philippaerts (2001)[97]

Acc (Tracmor)

4 days

BAQ

Total activity index(Q) – mean counts(Acc)

Pearson r = 0.47 (P < 0.001)

    

TCQ

TEE(Q) – mean counts(Acc)

Pearson r = 0.22

Adults

Richardson (2001)[100]

Acc (Caltrac)

14x 2 days

S7DR

Men, visit 10: total MET-min/day(Q) – total MET-min/day(Acc)

Spearman r = 0.54 (P < 0.01)

     

Men, visit 11: total MET-min/day(Q) – total MET-min/day(Acc)

Spearman r = 0.45 (P < 0.05)

     

Women, visit 10: total MET-min/day(Q) – total MET-min/day(Acc)

Spearman r = 0.20

     

Women, visit 11: total MET-min/day(Q) – total MET-min/day(Acc)

Spearman r = 0.06

Adults

Saglam (2010)[112]

Acc (Caltrac)

4 days

IPAQ

Total MET-min/week(Q) – TEE(Acc)

Spearman r (95 % CI) = 0.29 (0.05;0.47), P = 0.009

    

IPAQ-s

Total MET-min/week(Q) – TEE(Acc)

Spearman r (95 % CI) = 0.30 (0.07;0.49), P = 0.008

Adults

Schmidt (2006)[92]

Acc (ActiGraph)

7 days

KPAS-mod

Total activity score(Q) – mean counts/min(Acc)

Spearman r = 0.52

     

Weighted activity score(Q) – mean counts/min(Acc)

Spearman r = 0.59

Adults

Smitherman (2009)[113]

Acc (ActiGraph)

1 day

JPAC

JPAC total score(Q) – mean counts/min(Acc)

Spearman r = 0.24 (P < 0.0001)

Adults

Staten (2001)[93]

DLW

8 days

AAFQ

TEE-ic(Q) – TEE(DLW)

Pearson r = 0.40 (P < 0.001)

MD = 1935 kJ/day

     

TEE-mif(Q) – TEE(DLW)

Pearson r = 0.45 (P < 0.001)

MD = 697 kJ/day

     

TEE-met(Q) – TEE(DLW)

Pearson r = 0.58 (P < 0.001)

MD = 3595 kJ/day

Adults

Strath (2004)[114]

Acc + HR (ActiGraph + Polar)

7 days

CAQ-PAI

MET-min/week(Q) – MET-min/week(Acc + HR)

Spearman r = 0.35

Adults

Trinh (2009)[115]

Acc (ActiGraph)

7 days

GPAQ

Dry season: GPAQ total score(Q) – total counts(Acc)

Spearman r = 0.33

MD (95 % LoA) = 2.6 (0.03;224)

     

Wet season: GPAQ total score(Q) – total counts(Acc)

Spearman r = 0.19

MD (95 % LoA) = 2.6 (0.03;224)

     

Dry season: sedentary time(Q) – sedentary time(Acc)

<100 counts/min

Spearman r = 0.22

     

Wet season: sedentary time(Q) – sedentary time(Acc)

<100 counts/min

Spearman r = 0.31

Adults

Washburn (2003)[116]

DLW

14 days

S7DR

TEE(Q) – TEE(DLW)

Pearson r = 0.58 (P < 0.01)

MD (95 % LoA) = −96 ± 4161 kJ/day

     

PAEE(Q) – PAEE(DLW)

Pearson r = 0.12

MD (95 % LoA) = −222 ± 4144 kJ/day

Adults

Wolin (2008)[117]

Acc (Actical)

6 days

IPAQ-s

1-min bout: MET-min/week(Q) – counts/day(Acc)

Spearman r = 0.36 (P < 0.001)

κ (95 % CI) = 0.21 (−0.04;0.47)

     

10-min bout: MET-min/week(Q) – counts/day(Acc)

Spearman r = 0.26 (P = 0.002)

κ (95 % CI) = 0.04 (0.01;0.06)

Elderly

Bonnefoy (2001)[75]

DLW

14 days

MLTPAQ

Total activity(Q) – TEE(DLW)

Pearson r = 0.23, Spearman r = 0.17

    

YPAS

Summary index(Q) – TEE(DLW)

Pearson r = 0.11, Spearman r = 0.10

    

BAQ-mod

Questionnaire score(Q) – TEE(DLW)

Pearson r = 0.21, Spearman r = 0.28

    

CAQ

Total activity(Q) – TEE(DLW)

Pearson r = 0.39, Spearman r = 0.37

    

7DR

Total activity(Q) – TEE(DLW)

Pearson r = 0.37, Spearman r = 0.51 (P < 0.05)

    

DQ-mod

Total score(Q) – TEE(DLW)

Pearson r = 0.21, Spearman r = 0.34

    

LRC

Enhanced LRC score(Q) – TEE(DLW)

Pearson r = 0.33, Spearman r = 0.29

    

SUA

MPA(Q) – TEE(DLW)

Pearson r = 0.65 (P < 0.05), Spearman r = 0.46

     

VPA(Q) – TEE(DLW)

Pearson r = 0.63 (P < 0.05), Spearman r = 0.64 (P < 0.05)

    

PASE

Total score(Q) – TEE(DLW)

Pearson r = 0.28, Spearman r = 0.23

    

QAPSE

Mean habitual DEE(Q) – TEE(DLW)

Pearson r = 0.32, Spearman r = 0.25

Elderly

De Abajo (2001)[76]

Acc (Caltrac)

3 days

YPAS

Total hr/week(Q) – activity units/day(Acc)

Pearson r = 0.20 (P = 0.049)

     

TEE(Q) – activity units/day(Acc)

Pearson r = 0.23 (P = 0.022)

     

YPAS summary index(Q) – activity units/day(Acc)

Pearson r = 0.24 (P = 0.018)

     

Sitting(Q) – activity units/day(Acc)

Pearson r = −0.06 (P = 0.54)

Elderly

Dinger (2004)[77]

Acc (ActiGraph)

7 days

PASE

Total PASE score(Q) – mean counts/min(Acc)

Spearman r = 0.43 (P = 0.001)

Elderly

Dubbert (2004)[78]

Acc (Tritrac R3D)

3 days

7DPAR

TEE(Q) – counts/min(Acc)

Spearman r = 0.49 (P < 0.01)

Elderly

Giles (2009)[79]

Ped (Yamax)

7 days

CHAMPS-MMSCV

Volume T1: walking(Q) – step counts(Ped)

Spearman r = 0.40 (P < 0.01)

     

Frequency T1: walking(Q) – step counts(Ped)

Spearman r = 0.57 (P < 0.01)

     

Volume T2: walking(Q) – step counts(Ped)

Spearman r = 0.53 (P < 0.01)

     

Frequency T2: walking(Q) – step counts(Ped)

Spearman r = 0.60 (P < 0.01)

Elderly

Hagiwara (2008)[80]

Acc (Kenz Lifecorder)

3 days

PASE

Total PASE score(Q) – EE(Acc)

Spearman r = 0.16 (P = 0.02)

     

Total PASE score(Q) – walking steps(Acc)

Spearman r = 0.17 (P = 0.01)

Elderly

Harada (2001)[81]

ML (Mini-Mitter)

7 days

CHAMPS

EE(Q) – ankle counts(ML)

Pearson r = 0.36 (P < 0.01)

     

EE(Q) – waist counts(ML)

Pearson r = 0.42 (P < 0.001)

    

PASE

Total PASE score(Q) – ankle counts(ML)

Pearson r = 0.59 (P < 0.001)

     

Total PASE score(Q) – waist counts(ML)

Pearson r = 0.52 (P < 0.001)

    

YPAS

EE(Q) – ankle counts(ML)

Pearson r = 0.46 (P < 0.001)

     

EE(Q) – waist counts(ML)

Pearson r = 0.61 (P < 0.001)

Elderly

Hurtig-Wennlöf (2010)[82]

Acc (ActiGraph)

7 days

IPAQ-E

Walking + MPA min/day(Q) – mean counts/min(Acc)

Spearman r = 0.347 (P < 0.01)

κ (95 % CI) = 0.448 (0.18;0.72), P < 0.001

     

VPA min/day(Q) – VPA counts/min(Acc)

>4944 counts/min

Spearman r = 0.369 (P < 0.01)

     

MPA min/day(Q) – MPA counts/min(Acc)

760-4944 counts/min

Spearman r = 0.396 (P < 0.01)

     

Sitting min/day(Q) – sitting counts/min(Acc)

<100 counts/min

Spearman r = 0.277 (P < 0.05)

Elderly

Kolbe-Alexander (2006)[83]

Acc (ActiGraph)

7 days

IPAQ-s

Men: vigorous MET-min/week(Q) – high counts(Acc)

≥5725 counts/min

Spearman r = 0.43 (P = 0.05)

     

Women: vigorous MET-min/week(Q) – high counts(Acc)

≥5725 counts/min

Spearman r = 0.05

     

Men: moderate MET-min/week(Q) – moderate min(Acc)

1952-5724 counts/min

Spearman r = 0.31 (P = 0.004)

     

Women: moderate MET-min/week(Q) – moderate min(Acc)

1952-5724 counts/min

Spearman r = −0.09

     

Men: walking MET-min/week(Q) – total counts(Acc)

Spearman r = 0.57 (P = 0.00007)

     

Women: walking MET-min/week(Q) – total counts(Acc)

Spearman r = 0.42 (P = 0.006)

     

Men: sitting MET-min/week(Q) – total counts(Acc)

Spearman r = −0.40 (P = 0.001)

     

Women: sitting MET-min/week(Q) – total counts(Acc)

Spearman r = −0.35 (P = 0.005)

    

YPAS

Men: total MET-min/week(Q) – total counts(Acc)

Spearman r = 0.54 (P = 0.0002)

     

Women: total MET-min/week(Q) – total counts(Acc)

Spearman r = 0.13

Elderly

Starling (1999)[84]

DLW

10 day

MLTPAQ

Men: TEE(Q) – TEE(DLW)

MD (95 % LoA) = 752 ± 972 kcal/day

     

Women: TEE(Q) – TEE(DLW)

MD (95 % LoA) = 487 ± 698 kcal/day

    

YPAS

Men: TEE(Q) – TEE(DLW)

MD (95 % LoA) = 104 ± 1414 kcal/day

     

Women: TEE(Q) – TEE(DLW)

MD (95 % LoA) = 9 ± 972 kcal/day

Elderly

Tomioka (2011)[85]

Acc (Kenz Lifecorder)

2 weeks

IPAQ-s

Young old men: MET-min/week(Q) – MET-min/week(Acc)

Spearman r = 0.42 (P < 0.01)

κ (95 % CI) = 0.49 (0.34;0.64)

     

Young old women: MET-min/week(Q) – MET-min/week(Acc)

Spearman r = 0.49 (P < 0.01)

κ (95 % CI) = 0.39 (0.22;0.56)

     

Old old men: MET-min/week(Q) – MET-min/week(Acc)

Spearman r = 0.53 (P < 0.01)

κ (95 % CI) = 0.46 (0.29;0.63)

     

Old old women: MET-min/week(Q) – MET-min/week(Acc)

Spearman r = 0.49 (P < 0.01)

κ (95 % CI) = 0.47 (0.28;0.66)

Elderly

Washburn (1999)[86]

Acc (ActiGraph)

3 days

PASE

Total PASE score(Q) – mean counts/5 min epoch(Acc)

Spearman r = 0.49 (P < 0.05)

       

Median Spearman r = 0.30 (youth: 0.25, adults: 0.30, elderly: 0.40)

 
       

Median Pearson r = 0.39 (youth: 0.38, adults: 0.46, elderly: 0.345)

 

Q1 = first completed questionnaire, Q2 = second completed questionnaire, Q3 = third completed questionnaire, r = correlation coefficient (rho), CI = Confidence Interval (lower;upper), κ = kappa (i.e. Cohen weighted kappa unless specified otherwise), LoA = Limits of Agreement, MD = Mean Difference, – = not stated.

Acc = Accelerometry [NB: ActiGraph (Model 7164) is successor of preceding accelerometer by MTI, formerly CSA]. Accelerometer names as used in the respective papers.

Affuso (2011): Sedentary mins = total minutes TV/video watching, computer/internet use, talking on phone, playing video/computer games.

Ainsworth (1999): MPA MET-min/week = energy expended in moderate-intensity occupational standing activities. 7DR-scores = scores of occupational activity only. EE = Energy Expenditure in kcal/day. All other associations between the TOQ and Caltrac scores were low and non significant.

Allor (2001): HR monitor brand not specified. EE = Energy Expenditure in kcal/hr.

Bonnefoy (2001): MLTPAQ total activity = light, moderate, heavy, household activity. YPAS summary index = sum of vigorous, walking, moving, standing, sitting scores. BAQ-mod questionnaire score = sum of household, sports, leisure activity scores. CAQ total activity = sum of walking, stairs, sports. 7DR total activity = weighted sum of sleep, light, moderate, hard, very hard activity. Dallosso-mod total score = weighted sum of walking standing, productive, leisure, muscle-loading activity. Enhanced LRC score = self report of usual activity. SUA MPA = six habitual moderate activities. SUA VPA = five habitual vigorous activites. PASE total score = activity weight*frequency across work-related leisure, household activities. QAPSE mean habitual DEE = activity weight*duration as daily energy expenditure.

Brown (2008): Frequency/week = frequency of total activity per week. Total min/week = minutes per week of total activity ≥3 METs. Total counts = all accelerometer recorded minutes.

Bull (2009): VPA/MPA = total vigorous/moderate intensity activity across all domains. Sedentary min/day = time spent sitting per day in minutes. Data categorized for studies in China (n = 215) and South Africa (n = 83).

Conway (2002): R2 = regression against PAR; explained variance is 10 % for 7DPAR and 14 % for S7DR. MD = mean differences ± SEM (percentages in parentheses) between each method and EE(DLW).

Cust (2008): Total MET-hr/week = total MET hours per week of non-occupational activity. Total PA index = cross-tabulation of level of occupational activity with combined recreational and household activities - inactive, moderately inactive, moderately active, active. Cambridge PA index = index based on occupational, cycling and sports activity (generally more intense activities).

Cust (2009): Results are stratified according to the group of participants reporting high or low confidence in recall of PA. High confidence = group of participants reporting high self-reported confidence in recall of physical activity. Low confidence = group of participants reporting low self-reported confidence in recall of physical activity. Remarkably, the correlation for the Cambridge index is slightly higher compared to the total PA index (MET-hrs) comparing accelerometry with the EPAQ. Total MET-hr/week(Acc) = total physical activity in MET-hr/week, calculated as light + moderate + vigorous activity (no sedentary time). Data are averages of three 7-day accelerometer periods.

De Abajo (2001): Total hr/week = total activity time. Activity units = kilocalorie score divided by resting metabolic rate. TEE = Total Energy Expenditure in kJ/day. YPAS summary index = summed time for each activity, expressed in hours per week for each subject. Individual indices were created by multiplying a frequency score by a duration score and multiplying again by a weighting factor.

Dinger (2004): Total PASE score = weighted and summed score of individual items using the PASE scoring algorithm.

Duncan (2001): HRR = each subject's individual heart rate reserve (individual maximal MET capacity), where HRmax was determined from the graded exercise test and HRrest from the average of three measures after a 10-min seated test. Mean difference = 0.21, i.e. 0.21 hours overreported in PAR.

Eisenmann (2002): Total leisure activity score was calculated by multiplying the frequency of each category by the MET value and summing the score.

Ekelund (2005): MD = mean difference between objectively measured accelerometry time in MVPA and self-reported time in MVPA and walking.

Giles (2009): Volume T1/T2 = walking MET-min per week at first/second administration (T1/T2) of the CHAMPS. Frequency T1/T2 = walking sessions per week at first/second administration (T1/T2) of the CHAMPS.

Hagiwara (2008): PASE score was calculated by adding the score for each component determined on the basis of the time spent on each activity or the presence or absence of activity over the past 7 days. EE = Energy Expenditure divided by bodyweight in kcal/day/wt. Walking steps = daily number of walking steps measured by the Lifecorder accelerometer.

Hagströmer (2008): Data shown is data from the average intensity measured by the accelerometer.

Hagströmer (2006): Bland-Altman results from analysis for time spent in at least moderate physical activity (hr/week) as assessed by the IPAQ and measured using an activity monitor.

Hallal (2010): Total score(Q) = sum of minutes spent on MPA (including walking) per week, and twice the number of minutes spent on VPA, calculated from the IPAQ data. Total score(Acc) = accelerometer-based total score: moderate + vigorous-intensity counts.

Harada (2001): MiniLogger measures activity by counting the number of mercure switch closures, resulting in a 'count' of activity, over a predetermined time interval. EE = Energy Expenditure in kcal/week. Total PASE score = total score computed by 1) multiplying an activity frequency value from a conversion of hours per day in six categories of activity (e.g., moderate sports) by the respective weight and summing over these activities and 2) adding a weight to this summated score for each six other household activities if the activity was reported over the past 7 days.

Huang (2009): Results from Bland-Altman analysis are combined results for boys and girls (no results for sedentary time). Cut points used are Freedson age-based cut point, calculated as METs = 2.757 + (0.0015*counts per minute) - (0.0896*age[yr]) - (0.000038*counts per minute*age[yr]).

Hurtig-Wennlöf (2010): Agreement (κ) = Cohen's kappa for testing total agreement between the IPAQ-E and accelerometry.

InterAct Consortium (2011): Total PA index = cross-tabulation of level of occupational activity with combined recreational and household activities (MET-hr/week) - inactive, moderately inactive, moderately active, active. Cambridge index = index based on occupational, cycling and sports activity (h/week). Recreational index = index based on quartiles of the sum of walking, cycling, and sports (MET-hr/week). Fisher-transformed correlations were estimated for each country, and random effect meta-analysis methods were used to calculate the overall combined correlation of PAEE (kJ/kg/day) measured by the combined HR and movement sensor with the three PA indices from the EPAQ-s.

Jacobi (2009): Sedentary time = time spent watching TV/video or playing video games and time spent using a computer.

Kolbe-Alexander (2006): High counts = counts in high-intensity physical activity. Moderate min = time spent in moderate-intensity activity. Total counts = total counts for physical activity. Sitting = time spent sitting during a weekend day.

Kowalski (1997): PAQ-C score = calculated as the mean of the nine items, ranging from 1 to 5. Total counts = total counts measured by the Caltrac that reflect vertical acceleration of the body.

Kurtze (2008): EE = Energy Expenditure in MJ/day. PAL = average Physical Activity Level in 7 days, calculated as total EE divided by basal metabolic rate (BMR). Results from Bland-Altman analysis are combined results for total moderate, vigorous and walking activity.

MacFarlane (2007): Total MVPA min/week(Q) = total weighted minutes, calculated as moderate + (2*vigorous). R2, slope = result from regression analysis between the Bland-Altman differences and averages. %Bias, LoA = bias and limits of agreement expressed as percentage of the mean score.

Mahabir (2006): Duration of validation not stated, likely to be 14 days. EE = Energy Expenditure in kcal/day.

Martinez-Gomez (2010): Correlation coefficient = correlation between the two instruments for the 3 day mean.

Martinez-Gomez (2011): PAQ-A score = mean score of 8 activity items scored on a 5-point scale.

Matton (2007): EE = Energy Expenditure in kcal/week. PAL = Physical Activity Level, calculated as total EE divided by 168 (number of hours per week) and the reported body weight. TV hr/week = time per week spent watching television or videos or playing computer games; this time was recalled in the FPACQ and also directly coded in the written activity log of the accelerometer reflecting the same activity domain. T-test = paired t-test to compare the magnitude of activity variables calculated from the RT3 and FPACQ (absolute validity).

Nang (2011): VPA(Q) = 3–6 METs kcal/day, MPA(Q) = >6 METs kcal/day. VPA(Acc), MPA(Acc) = moderate and vigorous physical activity using cutoff points of 3 METs between light and moderate activity, and 6 METs between moderate and vigorous activity.

Nicaise (2011): PA variables from questionnaire assessed in MET-min/week. Steps(Acc) = number of steps taken per day (from the dual mode function).

Pettee-Gabriel (2009): Participants wore the accelerometer on average 6.3 ± 0.7 days/week or 30.7 ± 4.8 days during 35 days of observation and 14.4 ± 1.1 hours/day.

Philippaerts (1999): Total activity index = index calculated from the work, sport and leisure time index. ADMR = Average Daily Metabolic Rate in MJ/day. PAL = Physical Activity Level, determined as the ratio of ADMR (Average Daily Metabolic Rate) over SMR (Sleeping Metabolic Rate). 7 day index = index in kcal/day calculated from hours spent on vigorous (8 times resting metabolic rate) and moderate (4 times resting metabolic rate) activities and including sleeping time and the time spent on light activities (remaining time) during the last seven days. TEE = Total Energy Expenditure in kcal/day.

Philippaerts (2001): Total activity index = index calculated from the work, sport and leisure time index. TEE = Total Energy Expenditure in kcal/day.

Rangul (2008): Frequency = out of breath or sweat sessions per week. Duration = out of breath or sweat hours per week. TEE = Total Energy Expenditure in MJ/week. PAL = Average Physical Activity Level for 7 days, calculated as total energy expenditure divided by basal metabolic rate.

Richardson (2001): Visit 10/11 = comparison for direct validation at study visit 10/11. Caltrac MET-min/day are obtained by dividing average 24-hour Caltrac readings (kcal/day) by the Caltrac's estimate of 24-hour resting energy expenditure and multiplying by 1440 min/day.

Scerpella (2002): 2x 3 Days = two measurement periods of 2 weekdays and 1 weekend day. Score calculations not specifically reported.

Schmidt (2006): Total activity score = activity score of all four domains, calculated as: (household/caregiving index*0.25 + occupational index*0.25 + active living index*0.25 + sports/exercise index*0.25)*4. Counts/min = mean accelerometer output per 1-min epoch, reflecting raw accelerometer output without any categorization according to activity intensity. Weighted activity score = activity score of all four domains, calculated as: (household/caregiving index*0.50 + occupational index*0.20 + active living index*0.25 + sports/exercise index*0.05)*4.

Slinde (2003): eMLTPAQ = extended MLTPAQ with additional questions about inactivity during leisure time. TEE = Total Energy Expenditure in MJ/day. Sedentary min/day = time spent watching TV, videos and computer time.

Smitherman (2009): JPAC total score = total score calculated by summing the 4 index scores (active living, work, home/family/yard/garden, sport/exercise index) and can range from 3 to 20.

Starling (1999): TEE = Total Energy Expenditure in kcal/day.

Staten (2001): TEE = Total Energy Expenditure in kJ/day, -ic = average total energy expenditure with RMR measured by indirect calorimetry, -mif = average total energy expenditure with RMR calculated using the Mifflin et al. Equation, -met = average total energy expenditure with RMR calculated using the MET conversion.

Tomioka (2011): Young old = age 65–74, old old = age 75–89.

Treuth (2004): GAQ score yesterday = summary score estimated from 18 physical activities reliably recalled and frequently performed on the previous day (yesterday) or usually. The GAQ summary scores were computed as the total MET-weighted score divided by the number of nonmissing items. Average counts/min: all counts measured between 6 AM to 12 midnight averaged per minute. Baseline: n = 197, follow-up: n = 168.

Trinh (2009): Dry season is baseline (n = 135). Measurements in wet season (n = 116) were performed 2 months after baseline during dry season. Sedentary time = time spent sitting or reclining. Mean (95 % LoA) = log-transformed average difference between the time spent in MVPA measured with GPAQ (averaged over dry and wet season) and accelerometer with 95 % limits of agreement.

Troped (2007): MPA = number of days participating in ≥ 30 min of moderate PA during past 7 days. VPA = number of days participating in ≥ 20 min of vigorous PA during past 7 days. Sensitivity = probability of the YRBS items correctly classifying students as meeting recommendations. Specificity = probability of YRBS items correctly classifying students as not meeting the recommended level of PA. Kappa range = range of kappa coefficients between Actigraph measures (accumulated minutes, minutes in bouts ≥ 5 min, minutes in bouts ≥ 10 min, sustained minutes of PA) and the YRBS measure. Cut points used are based on the Freedson age-dependent equation; METs = 2.757 + (0.0015*counts per minute) - (0.0896*age[yr]) - (0.000038*counts per minute*age[yr]).

Washburn (1999): Total PASE score was computed by multiplying the amount of time spent in each activity (hours/week) or participation (yes/no) in an activity by the empirically derived item weights and summing over all activities. Accelerometer readings are averaged over five-minute epoch periods.

Washburn (2003): Interviewer reliability tested: ICC = 0.85. TEE = Total Energy Expenditure, including sleep, in kJ/day. PAEE = Physical Activity Energy Expenditure, i.e. light, moderate, hard and very hard activities, excluding sleep.

Weston (1997): 1 Day = 1 day after school hours. TEE = Total relative Energy Expenditure in kcal/kg/day. EE = mean estimated rate of Energy Expenditure in kcal/kg/hr for the entire after school period, derived from both mode and intensity. %HRR = mean percent of heart rate range. HRR was calculated as HRmax - HRrest, where HRmax was estimated from the formula 220 - age, and HRrest was taken from the mean of the five lowest 1-min heart rates recorded during the measurement period. All heart rates (HRraw) were converted to a %HRR using the formula HRraw/HRR*100 and averaged to produce mean %HRR.

Wolin (2008): 1-Min bout = accelerometer bout lasting at least 1 minute. 10-Min bout = accelerometer bout lasting at least 10 minutes.

Of the 65 studies that report new results for the validity of existing questionnaires, 14 studies [55, 61, 69, 75, 81, 83, 84, 87, 89, 91, 94, 96, 97, 103] tested two or more questionnaires. Forty-five studies used accelerometry as the criterion, and the remaining used DLW (n = 8) [71, 75, 84, 89, 93, 94, 96, 116], pedometry (n = 3) [79, 101, 105], HR monitoring (n = 1) [104], MiniLogger (n = 1) [81] or a combination of methods (n = 5) [51, 60, 61, 74, 114]. Spearman and Pearson correlations were the most commonly used statistical measures for assessing validity; four studies reported 95 % confidence intervals with these correlations [51, 102, 103, 112] and three studies solely reported results using the Bland-Altman levels of agreement method [84, 94, 104]. Median correlations between reported sedentary behaviours and inactivity from objective measures were calculated: Spearman r = 0.23, Pearson r = 0.435.

Youth

Median validity correlations for the youth were as follows: Spearman r = 0.25, Pearson r = 0.38. Many PAQs (SAPAC [59], HBSC [54], IPAQ-s [54], GSQ [70] and GAQ [118]) demonstrated low validity coefficients (r < 0.2) in youth and only one instrument (PDPAR [60]) was regarded as highly valid (r = 0.76) when compared with physical activity assessed by the Caltrac accelerometer.

Adults

Median validity correlations for adults were as follows: Spearman r = 0.30, Pearson r = 0.46. Validity correlations were generally low for most PAQs, except for the FPACQ [111] compared with accelerometry in multiple subcategories (r = 0.39–0.85) and the BAQ (r = 0.68–0.69), FCPQ (r = 0.34–0.61) and TCQ (r = 0.63–0.64) for estimated TEE compared with TEE measured with the DLW method [96]. Pettee-Gabriel et al. compared five different PAQs with accelerometry from the Actigraph accelerometer and showed acceptable validity for all instruments; PMMAQ (r = 0.59–0.60), PWMAQ (r = 0.56–0.60), NHS-PAQ (r = 0.42–0.46), AAS (r = 0.46–0.50), WHI-PAQ (r = 0.45–0.47) [91]. Several studies, including the 7DR-O [87], MAQ [109], CAPS [89], IPAQ [55, 90] and the IPAQ-s [54, 98, 99], demonstrated poor validity.

Elderly

Median validity correlations for the elderly were as follows: Spearman r = 0.40, Pearson r = 0.345. Bonnefoy et al. tested the validity of 10 previously developed well known PAQs using DLW as the criterion measure [75]. The results of this study suggested that the Stanford Usual Activity questionnaire performed best (r = 0.63–0.65). Other studies in elderly generally found low correlations between self-reported PA with objective measures, also demonstrated by the generally weak performances of the YPAS in several studies (r = 0.11–0.61) [75, 76, 81, 83, 84], and PASE in one of the studies (r = 0.16–0.17) [80].

Discussion

This systematic review covered the most recent 15-year period. We identified 31 studies that adequately tested newly developed PAQs for both validity and reliability during this period. This suggests that whilst assessing physical activity by means of objective monitoring has become widespread also when examining population levels of activity [119121], PAQs remain an active area of research and are now generally considered complementary to any objective measure. Several previous reviews have assessed the reliability and validity of PAQs with a special focus on their overall performance [9], or performance in specific age groups [11, 14, 15]. Conversely, we compared whether newly developed PAQs performed better than older PAQs, as this will inform researchers and practitioners when choosing an existing PAQ or developing a new instrument for assessing physical activity. We therefore comprehensively summarized the results to allow an adequate appraisal of the existing PAQs performance across domains and physical activity intensities.

In concordance with previous reviews [11, 14, 15], very few questionnaires showed acceptable reliability and validity across age groups. Developing new PAQs requires careful consideration of the study design in terms of target population, sample size, age group, recall period, dimension and intensity of PA, relative and absolute validity, standardized quality criteria and appropriate comparison measures. The lack of formulating a priori hypotheses was recently highlighted as a limitation in most studies examining the validity of PAQs [11] and comprehensive key criteria for physical activity and sedentary behaviour validation studies have been proposed [122, 123].

Since the comprehensive review by Kriska and Caspersen [9], it is apparent that more appropriate criterion methods, in particular accelerometry, have been used to test the validity of PAQs. Yet, a considerable number of studies were excluded from the present review due to an inappropriate criterion method (e.g. aerobic fitness). Many studies reported reliability and validity results for existing and well established questionnaires, which suggests that these instruments are still frequently used. Importantly, newly developed PAQs do not seem to perform any better than existing instruments in terms of reliability and validity. Unfortunately, we were not able to conduct a formal meta-analysis due to differences in reported outcomes, different criterion measures and different time frames between questionnaires.

Total energy expenditure (TEE) was frequently used as the outcome measure of the PAQ and the validity scores from these types of instruments are usually high. However, the results from many of these studies should be interpreted carefully. This is because TEE from any self-report incorporates an estimate of resting energy expenditure (REE) generally calculated from body weight, sex and age. REE explains most of the variation in TEE and, consequently, high correlations may be generated when comparing TEE from self-report with measured or estimated TEE from the criterion method. This is particularly problematic when those same predictions of REE are used by both the criterion method and the self-reported calculation of energy expenditure. Therefore, other outputs (e.g. time spent in different intensity levels, physical activity energy expenditure normalised for body size) from the criterion method appear more appropriate to serve as criterion measures. In these studies correlations between the criterion measure and self-reported PA are considerably weaker than those for TEE, although the concerning PAQs may still be considered valid as demonstrated in some studies [31, 116]. The notion of validity, however, is a matter of degree, rather than an all-or-nothing determination.

The validity correlation coefficients from the vast majority of existing and newly developed PAQs were considered poor to moderate and usually only acceptable when results were presented as Pearson or Spearman correlation coefficients. This suggests that most PAQs may be valid for ranking individuals’ behaviour whereas their absolute validity is limited to quantify PA. Although our summary of the correlations in a single median value should be interpreted with caution, we did not observe any substantial difference between newly and existing PAQs. This may suggest that, despite considerable effort, accurate and precise self-report physical activity instruments are still scarce [124]. Many of the newly developed instruments collected information in various domains of physical activity including transportation and housework. Despite this, it appears almost impossible to obtain a valid estimation of a highly variable behaviour such as free-living physical activity by self-report. While results from large scale observational cohort studies have convincingly demonstrated the beneficial effects of self-reported physical activity on various health outcomes including all-cause mortality, coronary and cardiovascular disease morbidity and mortality, some types of cancer, and type 2 diabetes, the detailed dose–response associations are still unknown [125]. Increased sample size is usually considered to improve precision but may not overcome issues about accuracy. Further, a large sample size does not overcome misclassification due to differential measurement error. Therefore, future studies should consider including an objective measure of physical activity in addition to self-report or consider recommendations to reduce self-report error [126].

With few exceptions, most PAQs reviewed showed acceptable to good reliability with only minor differences between existing and newly developed PAQs. The median reliability correlations were acceptable to good in youth (0.64 – 0.65), adults (0.64 – 0.79), and the elderly (0.60 – 0.65) for existing PAQs; and marginally higher for newly developed PAQs in youth (0.69 – 0.80), adults (0.74 – 0.765), and the elderly (0.70). However, only 3 of 11 newly developed PAQs [21, 23, 24] showed consistently good reliability.

For existing PAQs, median validity correlations were poor to acceptable in youth (0.25 – 0.38), adults (0.30 – 0.46), and elderly (0.345 – 0.40); and essentially similar for newly developed PAQs in youth (0.22 – 0.41), adults (0.27 – 0.28), and the elderly (0.41).

Only four of the reviewed questionnaires, the IPAQ-s (existing) [85], the FPACQ (existing) [111], PDPAR (existing) [60] and the RPAR (new) [21] showed acceptable to good results for both reliability and validity. Sedentary behaviour appeared to be one of the most difficult domains to assess with questionnaires as demonstrated by the poor correlations with objectively measured sedentary time, although arguably, there are also limitations of the criterion measures, which contribute to poorer agreement between methods. About one third (n = 11) of the studies reporting data on newly developed PAQs assessed both validity and reliability for sedentary behaviour. 17 and 15 studies reported data on validity and reliability for sedentary behaviour from existing PAQs, respectively.

Accuracy of PA recall may be increased at the second retest administration by an increased physical activity awareness as a result of completing the questionnaire previously [105]. Many of the reviewed studies did not specify details about their reliability testing, making it difficult to distinguish test-retest reliability of the instrument from a measure of stability of physical activity. It is therefore complex to assign the correlations to either the reliability of the instrument or to the stability of the behaviour of the participant. Assessing test-retest reliability for a last seven day PAQ is generally more straight forward compared to a PAQ assessing usual or last year physical activity. This is because when examining the reliability of a last seven days instrument the respondents should be prompted to report their PA during exactly the same week at two different occasions separated in time. However, this must be weighed against administering the test and retest too close in time that the respondent remembers the answers given to the first administration, resulting in inflation of reliability estimates from correlated error. Several other study details than timeframe of recall can be identified to have a marked influence on the study results, such as socio-cultural background, sex, age, literacy, and cognitive abilities.

The DLW method is usually considered the most accurate criterion method available for measuring TEE and PAEE. However, as discussed above, when using the DLW method and other objective methods which provide outputs in TEE as the criterion instrument, individual variability in body weight needs to be considered. It is therefore recommended that data from these methods should be expressed as PAEE, with and without normalisation for body weight in subsequent validation studies. Combined heart rate and movement sensing may be more accurate than either of the methods used alone for measuring time spent at different intensity levels [31]. However, most of the newly developed PAQs used a single accelerometer mounted at the hip as the criterion method, possibly due to its reasonable costs and feasibility in large study groups. Accelerometry also has some inherent limitations including its inability to accurately assess the intensity of specific types such as weight-bearing activities, cycling, and swimming [33]. Further, the choice of somewhat arbitrary cut-off points [127129] to classify intensities of activity when using accelerometry as a criterion method has been documented before. The use of accelerometers is especially problematic to validate time spent in different intensities of physical activity from PAQs and this also hampers comparison of studies [33]. Usually criterion measures assess overall PA (e.g. time in MVPA, PAEE) which precludes a direct test of the validity of self-reported domain specific activity (e.g. occupation). It is therefore not surprising that some PAQs [e.g. 86] which only asses a specific domain of activity demonstrate low validity when compared with overall physical activity from the criterion instrument. More research is therefore needed to compare time stamped criterion data with domain specific self-reported activity and to develop criterion instruments which can accurately categorise types of activities. Adopting a conceptual framework for physical activity [130] in combination with standardized procedures when developing and validating PAQs [122, 123] is highly recommended.

Pearson and Spearman correlations may not be the most appropriate statistical methods to use for reporting results on the validity of PAQs. ICC is considered a more appropriate method for continuous measures on the same scale, whereas weighted kappa is a better choice of method for categorical measures [131, 132]. When reporting validation results researchers are encouraged to report absolute validity in terms of mean bias with limits of agreement as well as the error structure of the instrument across the measurement range. We noted that many of the newly developed instruments reported results on absolute validity by means of the Bland-Altman method, which is a simple, intuitive and easy to interpret method to analyse assess measurement error [133]. Descriptive details of the study population may be helpful to explain any heterogeneity in the findings from different studies. Researchers can individually interpret all data for quality and applicability.

In summary, we systematically reviewed studies assessing both reliability and validity of PAQs in various domains, across age groups, and with a focus on total PA and sedentary time. PAQs are inherently subject to many limitations and the choice of PAQs should be dictated by the research question and the population under study. Considerations for researchers when using PAQs in practice have been identified and new research should consider including an objective method for assessing physical activity in addition to any self-report [134]. This review has identified a limited number of PAQs that appear to have both acceptable reliability and validity. Newly developed PAQs do not appear to perform substantially better than existing PAQs in terms of reliability and validity.

Declarations

Acknowledgments

Some of the questionnaires in this review have been made available to the authors and are available on the recently launched UK Medical Research Council Toolkit of Diet and Physical Activity Measurement [8].

Authors’ Affiliations

(1)
Medical Research Council Epidemiology Unit
(2)
Academic Medical Center, University of Amsterdam
(3)
Medical Research Council Human Nutrition Resource centre
(4)
Danone Baby Nutrition (Nutricia Ltd)
(5)
Department of Sports Medicine, Norwegian School of Sport Sciences

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© Helmerhorst et al.; licensee BioMed Central Ltd. 2012

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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