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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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Lauren Waters, Marina Reeves, Brianna Fjeldsoe and Elizabeth Eakin

Background:

Several recent physical activity intervention trials have reported physical activity improvements in control group participants. Explanations have been proposed, but not systematically investigated.

Methods:

A systematic review of physical activity intervention trials was conducted to investigate the frequency of meaningful improvements in physical activity among control group participants (increase of ≥ 60 minutes [4 MET·hours] of moderate-to-vigorous physical activity per week, or a 10% increase in the proportion of participants meeting physical activity recommendations), and possible explanatory factors. Explanatory factors include aspects of behavioral measurement, participant characteristics, and control group treatment.

Results:

Eight (28%) of 29 studies reviewed reported meaningful improvements in control group physical activity, most of which were of similar magnitude to improvements observed in the intervention group. A number of factors were related to meaningful control group improvements in physical activity, including the number of assessments, mode of measurement administration, screening to exclude active participants, and preexisting health status.

Conclusions:

Control group improvement in physical activity intervention trials is not uncommon and may be associated with behavioral measurement and participant characteristics. Associations observed in this review should be evaluated empirically in future research. Such studies may inform minimal contact approaches to physical activity promotion.

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Winnie Y.H. Lee, Bronwyn K. Clark, Elisabeth Winkler, Elizabeth G. Eakin and Marina M. Reeves

Background:

This study evaluated the responsiveness to change in physical activity of 2 self-report measures and an accelerometer in the context of a weight loss intervention trial.

Methods:

302 participants (aged 20 to 75 years) with type 2 diabetes were randomized into telephone counseling (n = 151) or usual care (n = 151) groups. Physical activity (minutes/week) was assessed at baseline and 6-months using the Active Australia Survey (AAS), the United States National Health Interview Survey (USNHIS) walking for exercise items, and accelerometer (Actigraph GT1M; ≥1952 counts/minute). Responsiveness to change was calculated as responsiveness index (RI), Cohen’s d (postscores) and Cohen’s d (change-scores).

Results:

All instruments showed significant improvement in the intervention group (P < .001) and no significant change for usual care (P > .05). Accelerometer consistently ranked as the most responsive instrument while the least responsive was the USHNIS (responsiveness index) or AAS (Cohen’s d). RIs for AAS, USNHIS and accelerometer did not differ significantly and were, respectively: 0.45 (95% CI: 0.26–0.65); 0.38 (95% CI: 0.20–0.56); and, 0.49 (95% CI: 0.23–0.74).

Conclusions:

Accelerometer tended to have the highest responsiveness but differences were small and not statistically significant. Consideration of factors, such as validity, feasibility and cost, in addition to responsiveness, is important for instrument selection in future trials

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Marina M. Reeves, Alison L. Marshall, Neville Owen, Elisabeth A.H. Winkler and Elizabeth G. Eakin

Background:

We compared the responsiveness to change (prepost intervention) of 3 commonly-used self-report measures of physical activity.

Methods:

In a cluster-randomized trial of a telephone-delivered intervention with primary care patients, physical activity was assessed at baseline and 4 months (n = 381) using the 31-item CHAMPS questionnaire; the 6-item Active Australia Questionnaire (AAQ); and, 2 walking for exercise items from the US National Health Interview Survey (USNHIS). Responsiveness to change was calculated for frequency (sessions/week) and duration (MET·minutes/week) of walking and moderate-to-vigorous intensity physical activity.

Results:

The greatest responsiveness for walking frequency was found with the USNHIS (0.45, 95% CI: 0.19, 0.72) and AAQ (0.43, 95% CI: 0.19, 0.67), and for walking duration with the USNHIS (0.27, 95%CI 0.13, 0.41) and CHAMPS (0.24, 95% CI: 0.12, 0.36). For moderate-to-vigorous activity, responsiveness for frequency was slightly higher for the AAQ (0.50, 95% CI: 0.30, 0.69); for duration it was slightly higher for CHAMPS (0.32, 95% CI: 0.17, 0.47).

Conclusions:

In broad-reach trials, brief self-report measures (USNHIS and AAQ) are useful for their comparability to population physical activity estimates and low respondent burden. These measures can be used without a loss in responsiveness to change relative to a more detailed self-report measure (CHAMPS).