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Christine Hanley, Mitch J. Duncan and W. Kerry Mummery

Background:

Population surveys are frequently used to assess prevalence, correlates and health benefits of physical activity. However, nonsampling errors, such as question order effects, in surveys may lead to imprecision in self reported physical activity. This study examined the impact of modified question order in a commonly used physical activity questionnaire on the prevalence of sufficient physical activity.

Methods:

Data were obtained from a telephone survey of adults living in Queensland, Australia. A total of 1243 adults participated in the computer-assisted telephone interview (CATI) survey conducted in July 2008 which included the Active Australia Questionnaire (AAQ) presented in traditional or modified order. Binary logistic regression analyses was used to examine relationships between question order and physical activity outcomes.

Results:

Significant relationships were found between question order and sufficient activity, recreational walking, moderate activity, vigorous activity, and total activity. Respondents who received the AAQ in modified order were more likely to be categorized as sufficiently active (OR = 1.28, 95% CI 1.01−1.60).

Conclusions:

This study highlights the importance of question order on estimates of self reported physical activity. This study has shown that changes in question order can lead to an increase in the proportion of participants classified as sufficiently active.

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Mitch J. Duncan, Hannah M. Badland and William Kerry Mummery

Background:

The aim of this study was to examine the relationship between occupational category and 3 health-related behaviors: participation in leisure-time physical activity, active transport (AT) and occupational sitting in a sample of employed Australian adults.

Methods:

A random, cross-sectional sample of 592 adults aged 18 to 71 years completed a telephone survey in October/November 2006. Reported occupations were categorized as professional (n = 332, 56.1%), white-collar (n = 181, 30.6%), and blue-collar (n = 79, 13.3%). Relationships between occupational category and AT, sufficient physical activity and occupational sitting were examined using logistic regression.

Results:

White-collar employees (OR = 0.36, 95% CI 0.14−0.95) were less likely to engage in AT and more likely to engage in occupational sitting (OR = 3.10, 95% CI 1.63−5.92) when compared with blue-collar workers. Professionals (OR = 3.04, 95% CI 1.94−4.76) were also more likely to engage in occupational sitting compared with blue-collar workers. No relationship was observed between occupational category and engagement in sufficient physical activity.

Conclusions:

No association between occupational category and sufficient physical activity levels was observed, although white-collar and professionals were likely to engage in high levels of occupational sitting. Innovative and sustainable strategies are required to reduce occupational sitting to improve health.

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Melody Oliver, Hannah Badland, Suzanne Mavoa, Mitch J. Duncan and Scott Duncan

Background:

Global positioning systems (GPS), geographic information systems (GIS), and accelerometers are powerful tools to explain activity within a built environment, yet little integration of these tools has taken place. This study aimed to assess the feasibility of combining GPS, GIS, and accelerometry to understand transport-related physical activity (TPA) in adults.

Methods:

Forty adults wore an accelerometer and portable GPS unit over 7 consecutive days and completed a demographics questionnaire and 7-day travel log. Accelerometer and GPS data were extracted for commutes to/from workplace and integrated into a GIS database. GIS maps were generated to visually explore physical activity intensity, GPS speeds and routes traveled.

Results:

GPS, accelerometer, and survey data were collected for 37 participants. Loss of GPS data was substantial due to a range of methodological issues, such as low battery life, signal drop out, and participant noncompliance. Nonetheless, greater travel distances and significantly higher speeds were observed for motorized trips when compared with TPA.

Conclusions:

Pragmatic issues of using GPS monitoring to understand TPA behaviors and methodological recommendations for future research were identified. Although methodologically challenging, the combination of GPS monitoring, accelerometry and GIS technologies holds promise for understanding TPA within the built environment.

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Corneel Vandelanotte, Camille Short, Matthew Rockloff, Lee Di Millia, Kevin Ronan, Brenda Happell and Mitch J. Duncan

Background:

A better understanding of how occupational indicators influence physical activity levels will aid the design of workplace interventions.

Methods:

Cross-sectional data were collected from 1194 participants through a telephone interview in Queensland, Australia. The IPAQ-long was used to measure physical activity. Multiple logistic regression was applied to examine associations.

Results:

Of participants, 77.9% were employed full-time, 32.3% had professional jobs, 35.7% were engaged in shift work, 39.5% had physically-demanding jobs, and 66.1% had high physical activity levels. Participants with a physicallydemanding job were less likely to have low total (OR = 0.25, 95% CI = 0.17 to 0.38) and occupational (OR = 0.17, 95% CI = 0.12 to 0.25) physical activity. Technical and trade workers were less likely to report low total physical activity (OR = 0.44, 95% CI = 0.20 to 0.97) compared with white-collar workers. Part-time (OR = 1.74, 95% CI = 1.15 to 2.64) and shift workers (OR = 1.86, 95% CI = 1.21 to 2.88) were more likely to report low leisure-time activity.

Conclusions:

Overall, the impact of different occupational indicators on physical activity was not strong. As expected, the greatest proportion of total physical activity was derived from occupational physical activity. No evidence was found for compensation effects whereby physically-demanding occupations lead to less leisure-time physical activity or vice versa. This study demonstrates that workplaces are important settings to intervene, and that there is scope to increase leisure-time physical activity irrespective of occupational background.

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Stephanie Alley, Jannique G.Z. van Uffelen, Mitch J. Duncan, Katrien De Cocker, Stephanie Schoeppe, Amanda L. Rebar and Corneel Vandelanotte

This study examined sitting time, knowledge, and intentions to change sitting time in older adults. An online survey was completed by 494 Australians aged 65+. Average daily sitting was high (9.0 hr). Daily sitting time was the highest during TV (3.3 hr), computer (2.1 hr), and leisure (1.7 hr). A regression analysis demonstrated that women were more knowledgeable about the health risks of sitting compared to men. The percentage of older adults intending to sit less were the highest for TV (24%), leisure (24%), and computer (19%) sitting time. Regression analyses demonstrated that intentions varied by gender (for TV sitting), education (leisure and work sitting), body mass index (computer, leisure, and transport sitting), and physical activity (TV, computer, and leisure sitting). Interventions should target older adults’ TV, computer, and leisure time sitting, with a focus on intentions in older males and older adults with low education, those who are active, and those with a normal weight.