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Dafna Merom, Heather Bowles and Adrian Bauman

Background:

Walking is the most prevalent form of leisure time physical activity (LTPA). Advances in measurement of walking depend on understanding sources of error in self report. We examined the effect of prompting “walking for exercise, recreation, and sport” (WERS) upon surveillance estimates of LTPA and assessed what types of walking were recalled when reporting LTPA generally and when WERS was prompted specifically.

Methods:

Data were collected by telephone survey from a random sample of 3,415 Australian adults (≥15yrs). Respondents were asked first to recall any type of LTPA they participated in (unprompted) and if walking was not mentioned, WERS was prompted. All walkers were asked to describe the type of walking they did. Open-ended responses were categorized according to physical activity measurement dimensions.

Results:

Forty three percent did not report WERS unless prompted to do so. The prevalence of meeting recommendations by all LTPA was reduced by 10% for both genders and across all age groups if not prompted to recall WERS. The interpretation of WERS was broad and included travel related walking and dog walking whether unprompted or prompted.

Conclusions:

Current challenges in walking surveillance include ensuring that both researchers and respondents understand WERS in a standardized manner.

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Takemi Sugiyama, Dafna Merom, Marina Reeves, Eva Leslie and Neville Owen

Background:

Television viewing time is associated with obesity risk independent of leisure-time physical activity (LTPA). However, it is unknown whether the relationship of TV viewing time with body mass index (BMI) is moderated by other domains of physical activity.

Methods:

A mail survey collected height; weight; TV viewing time; physical activity for transportation (habitual transport behavior; past week walking and bicycling), for recreation (LTPA), and in workplace; and sociodemographic variables in Adelaide, Australia. General linear models examined whether physical activity domains moderate the association between BMI and TV viewing time.

Results:

Analysis of the sample (N = 1408) found that TV time, habitual transport, and LTPA were independently associated with participant’s BMI. The interaction between TV time and habitual transport with BMI was significant, while that between TV time and LTPA was not. Subgroup analyses found that adjusted mean BMI was significantly higher for the high TV viewing category, compared with the low category, among participants who were inactive and occasionally active in transport, but not among those who were regularly active.

Conclusions:

Habitual active transport appeared to moderate the relationship between TV viewing time and BMI. Obesity risk associated with prolonged TV viewing may be mitigated by regular active transport.

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Rona Macniven, Victoria Pye, Dafna Merom, Andrew Milat, Claire Monger, Adrian Bauman and Hidde van der Ploeg

Background:

Physical activity interventions targeting older adults are optimized if barriers and enablers are better understood. This study identified barriers and enablers of physical activity and examined whether these were associated with meeting physical activity recommendations.

Methods:

2225 adults aged 65 years and above who perceived themselves to be insufficiently active but would like to be more physically active self-reported their barriers and enablers to physical activity in the 2009 New South Wales Falls Prevention Survey. Binary logistic regression analyses examined associations between barriers and enablers and meeting the physical activity recommendation.

Results:

After adjusting for gender, age, BMI, and education, people who listed ill health (52%; OR = 0.56, 95% CI 0.45 to 0.70) as a barrier or who listed people to exercise with (4%; OR = 0.49, 95% CI 0.27 to 0.88) as an enabler had significantly lower odds of meeting recommendations. Those citing too expensive (3%) as a barrier (OR = 2.07, 95% CI 1.11 to 3.87) or who listed nothing will help (29%; OR = 1.40, 95% CI 1.10 to 1.77) and making time to be active (9%; OR = 1.78, 95% CI 1.23 to 2.58) as enablers had significantly higher odds of meeting physical activity recommendations.

Conclusions:

These findings give insights into older adults’ perceptions of factors that influence their physical activity, which could assist physical activity program planning in this population.

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Louise L. Hardy, Ding Ding, Louisa R. Peralta, Seema Mihrshahi and Dafna Merom

Background: To examine the associations between school-age children’s sedentary behavior, screen time, and 3 physical activity attributes: muscular strength, cardiorespiratory endurance (CRE), and fundamental movement skills. Methods: Cross-sectional survey of 2734 children in years 2 and 4 and 3671 adolescents in years 6, 8, and 10. Total sitting time, 6 screen time behaviors, and physical activity were measured by self-report. Muscular strength was assessed by standing broad jump; CRE by 20-m shuttle run test; and fundamental movement skills by process-oriented checklists. Associations between incremental sitting and screen time (in hours) and meeting the healthy zone of physical activity attributes were examined using logistic regression. Results: After adjusting for covariates and physical activity, children had lower odds of achieving the healthy zone for muscular strength and CRE for each hour of week (but not weekend) screen time. For adolescents, each hour of screen time per day was associated with lower odds of achieving the healthy fitness zone for CRE, locomotor skills, and overall healthy zone, and each hour of weekend screen time was associated with lower odds of achieving the healthy zone for most attributes and overall healthy zone. The associations were slightly stronger among adolescent girls than boys. The findings were similar for total sitting time. Conclusions: Screen time was associated with a lower likelihood to achieve healthy zones of physical activity attributes, and the effect was more consistent and slightly stronger among adolescents than children. This may suggest that the negative effects of screen time are incremental, emerging during adolescence.

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Chris Rissel, Dafna Merom, Adrian Bauman, Jan Garrard, Li Ming Wen and Carolyn New

Background:

Encouraging cycling could increase levels of physical activity and health in the community. A population survey of cycling and physical activity was conducted as part of the baseline evaluation of a new intervention research project (Cycling Connecting Communities).

Methods:

A telephone survey of adults (18+) living within 2 kilometers of selected major new bicycle paths in 3 local government areas in south western Sydney, Australia was conducted using a 2-stage sampling method. Multiple logistic regression analyses examined factors associated with riding in the last year, wanting to cycle more, and use of local bicycle paths.

Results:

With a 65% response rate, 1450 interviews were completed. Having ridden a bicycle in the past year was associated with younger age, being male, having access to a bicycle, and living close to destinations of interest. Two thirds of respondents (65%) wanted to ride more than they currently did. Factors associated with wanting to ride more were having children aged between 5−18 years, having used local bicycle paths, and perceptions of ease of cycling.

Conclusions:

The study found that there is a latent desire for more cycling among respondents, prompted to some extent by having children of an age (5−18 years) that like cycling, and having a reasonable opportunity to cycle due to local bicycle paths. Being relatively close to destinations of interest increases the likelihood of recent cycling.

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Heather R. Bowles, Dafna Merom, Tien Chey, Ben J. Smith and Adrian Bauman

Background:

The aim of this study was to examine the associations between characteristics of recreational activity and total physical activity (PA).

Methods:

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.”

Results:

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.

Conclusion:

Participants in more than one type of recreational activity were less likely to have a low-active lifestyle.