Measurement of Active and Sedentary Behaviors: Closing the Gaps in Self-Report Methods
Heather R. Bowles
Resources for Locating and Selecting Self-Report Measures of Physical Activity
Laurel A. Borowski and Heather R. Bowles
Health Related Quality of Life by Level of Physical Activity in Arthritic Older Adults With and Without Activity Limitations
Julie Freelove-Charton, Heather R Bowles, and Steven Hooker
This study examined the association between health-related quality of life (HRQOL) and physical activity (PA) among adults with arthritis.
National 2003 2003 Behavioral Risk Factor Surveillance System (BRFSS) survey data for 51,444 adults, age ≥50 y, with physician-diagnosed arthritis were used to analyze the relationships between PA, self-reported health, HRQOL, and activity limitations related to arthritis.
The percentage of older adults with or without an activity limitation who reported fair/poor health or poor HRQOL was significantly higher in inactive persons compared to those who met PA recommendations (p < .0001). Older adults with and without limitations attaining either recommended or insufficient levels of PA were 39% to 70% less likely to report ≥14 unhealthy mental or physical days compared to inactive older adults (p < .0001).
Participation in PA at the recommended level was strongly associated with improved perceived health and higher levels of HRQOL; however, participation in some PA was clearly better than being inactive. These data were consistent for persons with arthritis despite the presence of an activity limitation.
Engaging Physical Activity Policymakers
Robin A. McKinnon, Heather R. Bowles, and Matthew J. Trowbridge
A Checklist for Evaluating the Methodological Quality of Validation Studies on Self-Report Instruments for Physical Activity and Sedentary Behavior
Maria Hagströmer, Barbara E. Ainsworth, Lydia Kwak, and Heather R. Bowles
The quality of methodological papers assessing physical activity instruments depends upon the rigor of a study’s design.
We present a checklist to assess key criteria for instrument validation studies.
A Medline/PubMed search was performed to identify guidelines for evaluating the methodological quality of instrument validation studies. Based upon the literature, a pilot version of a checklist was developed consisting of 21 items with 3 subscales: 1) quality of the reported data (9 items: assess whether the reported information is sufficient to make an unbiased assessment of the findings); 2) external validity of the results (3 items: assess the extent to which the findings are generalizable); 3) internal validity of the study (9 items: assess the rigor of the study design). The checklist was tested for interrater reliability and feasibility with 6 raters.
Raters viewed the checklist as helpful for reviewing studies. They suggested minor wording changes for 8 items to clarify intent. One item was divided into 2 items for a total of 22 items.
Checklists may be useful to assess the quality of studies designed to validate physical activity instruments. Future research should test checklist internal consistency, test-retest reliability, and criterion validity.
Associations of Type, Organization, and Number of Recreational Activities With Total Activity
Heather R. Bowles, Dafna Merom, Tien Chey, Ben J. Smith, and Adrian Bauman
The aim of this study was to examine the associations between characteristics of recreational activity and total physical activity (PA).
Recreational activity type and number were assessed for 3,385 adult respondents to the population-based Exercise Recreation and Sport Survey and categorized as “no recreational activity,” “walking only,” “sport only,” or “combined walking and sport.” Total PA was assessed by the International Physical Activity Questionnaire and categorized as “low,” “moderate,” or “high.”
Odds of high total PA were 1.7 times greater among walking-only participants, 2.9 times greater among sport-only participants, and 3.3 times greater among participants in combined walking and sport compared to no recreational activity participants. Greater number of recreational activities related to increased odds of high total PA. Similar associations were observed between recreational activity and moderate total PA.
Participants in more than one type of recreational activity were less likely to have a low-active lifestyle.
Identifying GIS Measures of the Physical Activity Built Environment Through a Review of the Literature
Eboneé N. Butler, Anita M.H. Ambs, Jill Reedy, and Heather R. Bowles
Examining relationships between features of the built environment and physical activity is achievable with geographic information systems technology (GIS). The purpose of this paper is to review the literature to identify GIS measures that can be considered for inclusion in national public health surveillance efforts. In the absence of a universally agreed upon framework that integrates physical, social, and cultural aspects of the environment, we used a multidimensional model of access to synthesize the literature.
We identified 29 studies published between 2005 and 2009 with physical activity outcomes that included 1 or more built environment variables measured using GIS. We sorted built environment measures into 5 dimensions of access: accessibility, availability, accommodation, affordability, and acceptability.
Geospatial land-use data, street network data, environmental audits, and commercial databases can be used to measure the availability, accessibility, and accommodation dimensions of access. Affordability and acceptability measures rely on census and self-report data.
GIS measures have been included in studies investigating the built environment and physical activity, although few have examined more than 1 construct of access. Systematic identification and collection of relevant GIS measures can facilitate collaboration and accelerate the advancement of research on the built environment and physical activity.
Utility of Computer-Assisted Approaches for Population Surveillance of Physical Activity
MeLisa Creamer, Heather R. Bowles, Belinda von Hofe, Kelley Pettee Gabriel, Harold W. Kohl III, and Adrian Bauman
Computer-assisted techniques may be a useful way to enhance physical activity surveillance and increase accuracy of reported behaviors.
Evaluate the reliability and validity of a physical activity (PA) self-report instrument administered by telephone and internet.
The telephone-administered Active Australia Survey was adapted into 2 forms for internet self-administration: survey questions only (internet-text) and with videos demonstrating intensity (internet-video). Data were collected from 158 adults (20–69 years, 61% female) assigned to telephone (telephone-interview) (n = 56), internet-text (n = 51), or internet-video (n = 51). Participants wore an accelerometer and completed a logbook for 7 days. Test-retest reliability was assessed using intraclass correlation coefficients (ICC). Convergent validity was assessed using Spearman correlations.
Strong test-retest reliability was observed for PA variables in the internet-text (ICC = 0.69 to 0.88), internet-video (ICC = 0.66 to 0.79), and telephone-interview (ICC = 0.69 to 0.92) groups (P-values < 0.001). For total PA, correlations (ρ) between the survey and Actigraph+logbook were ρ = 0.47 for the internet-text group, ρ = 0.57 for the internet-video group, and ρ = 0.65 for the telephone-interview group. For vigorous-intensity activity, the correlations between the survey and Actigraph+logbook were 0.52 for internet-text, 0.57 for internet-video, and 0.65 for telephone-interview (P < .05).
Internet-video of the survey had similar test-retest reliability and convergent validity when compared with the telephone-interview, and should continue to be developed.
Single Versus Multiple Item Questions on Occupational Physical Activity
Michelle M. Yore, Heather R. Bowles, Barbara E. Ainsworth, Caroline A. Macera, and Harold W. Kohl III
In 2002, the National Physical Activity and Weight Loss Survey asked two sets of questions on occupational physical activity—one question from the Behavioral Risk Factor Surveillance System (BRFSS) and eight detailed questions from the occupational physical activity questionnaire (OPAQ). This study compares the responses.
On the basis of percentage of occupational physical activity reported on OPAQ, 5847 respondents were classified by three levels (sitting or standing, walking, and heavy labor). Kappa, MET-min per day, and median hours worked at the three levels were calculated to compare the two sets of questions.
Levels of occupational physical activity reported on the BRFSS question agreed with OPAQ (kappa = 0.56). Hours of heavy labor per day reported on OPAQ increased among the three activity levels on BRFSS.
The BRFSS question and OPAQ classify respondents similarly by occupational physical activity. The BRFSS question is useful for overview and OPAQ, for more detailed analyses.