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BACKGROUND: Partnering with a public transport (PT) provider, state government, and local government, the single-blinded randomised controlled trial, trips4health, investigated the impact of PT use incentives on transport-related physical activity (PA) in Tasmania, Australia. The intervention involved 16-weeks of incentives (bus trip credits) for achieving weekly PT use targets, supported by weekly text messages. This study objective was to conduct a process evaluation of the COVID-19 disrupted trips4health study. METHODS: The Medical Research Council UK's framework for complex public health interventions guided the process evaluation. Participant reach, acceptability, fidelity and feasibility were evaluated. Administrative and post-intervention survey data were analysed descriptively. Semi-structured interviews with intervention participants (n = 7) and PT provider staff (n = 4) were analysed thematically. RESULTS: Due to COVID-19, trips4health was placed on hold (March 2020) then stopped (May 2020) as social restrictions impacted PT use. At study cessation, 116 participants (approximately one third of target sample) had completed baseline measures, 110 were randomised, and 64 (n = 29 in the intervention group; n = 35 in the control group) completed post-intervention measures. Participants were 18 - 80 years (average 44.5 years) with females (69%) and those with tertiary education (55%) over-represented. The intervention was delivered with high fidelity with 96% of bus trip credits and 99% of behavioural text messages sent as intended. Interviewed PT staff said implementation was highly feasible. Intervention participant acceptability was high with 90% reporting bus trip incentives were helpful and 59% reporting the incentives motivated them to use PT more. From a total of 666 possible bus trip targets, 56% were met with 38% of intervention participants agreeing and 41% disagreeing that 'Meeting the bus trip targets was easy'. Interviews and open-ended survey respo

BACKGROUND: Public transport users often accumulate more physical activity than motor vehicle users, but most studies have been conducted in large metropolitan areas with multiple public transport options with limited knowledge of the relationship in regional and rural areas. In a regional city, this pilot study aimed to (1) test the feasibility of preliminary hypotheses to inform future research, (2) test the utility of survey items, and (3) establish stakeholder engagement. METHODS: Data were collected via a cross-sectional online survey of 743 Tasmanian adults. Physical activity outcomes were walking (min/week), total moderate- to vigorous-intensity physical activity (min/week) and attainment of physical activity guidelines (yes/no). Transport variables were frequency of public and private transport use per week. Truncated and log binomial regression examined associations between public/private transport use and physical activity. RESULTS: Neither frequency of public nor private transport use was associated with minutes of walking (public transport: B - 24.4, 95% CI: - 110.7, 61.9; private transport: B - 1.1, 95% CI: - 72.4, 70.1), minutes of total physical activity (public transport: B - 90.8, 95% CI: - 310.0, 128.5; private transport: B 0.4, 95% CI: - 134.0, 134.9) or not meeting physical activity guidelines (public transport: RR 1.02, 95%CI: 0.95, 1.09; private transport: RR 1.02, 95%CI: 0.96, 1.08). CONCLUSIONS: The hypothesis that public transport users would be more physically active than private transport users was not supported in this pilot study. Stakeholders were engaged and involved in various phases of the research including development of research questions, participant recruitment, and interpretation of findings. Further studies using representative samples and refined measures are warranted to confirm or refute findings.

BACKGROUND: Public transport (PT) users typically accumulate more physical activity (PA) than private motor vehicle users yet redressing physical inactivity through transport-related PA (TRPA) interventions has received limited attention. Further, incentive-based strategies can increase leisure-time PA but their impact on TRPA, is unclear. This study's objective is to determine the impact of an incentive-based strategy on TRPA in a regional Australian setting. METHODS: trips4health is a single-blinded randomised controlled trial with a four-month intervention phase and subsequent six-month maintenance phase. Participants will be randomised to: an incentives-based intervention (bus trip credit for reaching bus trip targets, weekly text messages to support greater bus use, written PA guidelines); or an active control (written PA guidelines only). Three hundred and fifty adults (≥18 years) from southern Tasmania will be recruited through convenience methods, provide informed consent and baseline information, then be randomised. The primary outcome is change in accelerometer measured average daily step count at baseline and four- and ten-months later. Secondary outcomes are changes in: measured and self-reported travel behaviour (e.g. PT use), PA, sedentary behaviour; self-reported and measured (blood pressure, waist circumference, height, weight) health; travel behaviour perspectives (e.g. enablers/barriers); quality of life; and transport-related costs. Linear mixed model regression will determine group differences. Participant and PT provider level process evaluations will be conducted and intervention costs to the provider determined. DISCUSSION: trips4health will determine the effectiveness of an incentive-based strategy to increase TRPA by targeting PT use. The findings will enable evidence-informed decisions about the worthwhileness of such strategies. TRIAL REGISTRATION: ACTRN12619001136190. UNIVERSAL TRIAL NUMBER: U1111-1233-8050.

ISSUE ADDRESSED: Public transport (PT) users typically accumulate more physical activity (PA) than motor vehicle users. This mixed methods study aimed to determine acceptability and perceived effectiveness of strategies to increase bus use for PA gain in a regional Australian setting. METHODS: In a 2017 online survey, Tasmanian adults (n = 1091) rated the likelihood of increasing their bus use according to ten hypothetical strategies (fare-, incentives-, information- or infrastructure-based). Three focus groups and five interviews (n = 31) included infrequent bus users from the survey to determine reasons for strategy preferences and potential impact on PA. RESULTS: The top three strategies in the survey, with supporting rationale from qualitative data, were: provision of real-time bus information ("…because I can better plan…"); bus-only lanes ("…it just speeds the whole thing up…") and employee incentives/rewards for example bus fare credits ("…it really comes down to money…"). Full-time students favoured cost-saving strategies most and residents in outer suburbs favoured infrastructure-based strategies most. Qualitative data indicated that potential for enhanced certainty, efficiency or cost-savings drove strategy preferences and some strategies may lead to PA gain (eg through the location of Park and Ride facilities). CONCLUSIONS: Real-time information, bus-only lanes and employee incentives/rewards appear most promising for increasing bus use in this population, but tailoring strategies may be required. Discrete PT enhancement strategies may result in PA gain. SO WHAT?: Increasing PA through transport behaviour has been underexplored. The potential for PA gain through greater PT use and discrete PT use enhancement strategies is an important public health consideration.

BACKGROUND: Whether not meeting common guidelines for lifestyle behaviours is associated with weight gain is uncertain. This study examined whether 5-year weight gain was predicted by not meeting guidelines for: breakfast consumption (eating between 6 and 9 am), takeaway food consumption (<2 times/week), television viewing (<2 h/day) and daily steps (≥10,000 steps/day). METHODS: One thousand one hundred and fifty-five Australian participants (43% men, 26-36 years) completed questionnaires and wore a pedometer at baseline (2004-06) and follow-up (2009-11). Weight was measured or self-reported, with a correction factor applied. For each behaviour, participants were classified according to whether they met the guideline: consistently met at baseline and follow-up (reference group); not met at baseline but met at follow-up; met at baseline but not met at follow-up; consistently not met at baseline and follow-up. For each behaviour, weight gain was calculated using linear regression. Weight gain by number of guidelines met was also examined. RESULTS: Mean 5-year weight gain was 2.0 kg (SD:6.3). Compared to the reference group, additional weight (mean, 95% CI) was gained among those who did not meet the guideline at follow-up, or consistently did not meet the guideline, for breakfast (1.8 kg, 0.7-2.9; 1.5 kg, 0.1-2.8); takeaway food (2.2 kg, 0.7-3.6; 1.9 kg, 0.7-3.1); watching television (1.9 kg, 0.9-2.9; 1.4 kg, 0.4-2.3); and daily steps (2.6 kg, 1.1-4.04; 1.6 kg, 0.5-2.7). Those who met ≤1 guideline at follow-up gained 3.8 kg (95% CI 2.3-5.3) more than those meeting all guidelines. CONCLUSION: Individuals who adopted healthier behaviours between baseline and follow-up had similar weight gain to those who met the guidelines at both time points. Encouraging young adults to meet these simple guidelines may reduce weight gain.

OBJECTIVE: To examine how fitness in both childhood and adulthood is associated with adult obesity and insulin resistance. RESEARCH DESIGN AND METHODS: A prospective cohort study set in Australia in 2004-2006 followed up a cohort of 647 adults who had participated in the Australian Schools Health and Fitness Survey in 1985 and who had undergone anthropometry and cardiorespiratory fitness assessment during the survey. Outcome measures were insulin resistance and obesity, defined as a homeostasis model assessment index above the 75th sex-specific percentile and BMI >or=30 kg/m(2), respectively. RESULTS: Lower levels of child cardiorespiratory fitness were associated with increased odds of adult obesity (adjusted odds ratio [OR] per unit decrease 3.0 [95% CI 1.6-5.6]) and insulin resistance (1.7 [1.1-2.6]). A decline in fitness level between childhood and adulthood was associated with increased obesity (4.5 [2.6-7.7]) and insulin resistance (2.1 [1.5-2.9]) per unit decline. CONCLUSIONS: A decline in fitness from childhood to adulthood, and by inference a decline in physical activity, is associated with obesity and insulin resistance in adulthood. Programs aimed at maintaining high childhood physical activity levels into adulthood may have potential for reducing the burden of obesity and type 2 diabetes in adults.

The objective of this study was to determine whether change in physical activity was associated with maintaining a healthy weight from childhood to adulthood. This prospective cohort study examined 1,594 young Australian adults (48.9% female) aged 27–36 years who were first examined at age 9–15 years as part of a national health and fitness survey. BMI was calculated from measured height and weight, and physical activity was self-reported at both time points; pedometers were also used at follow-up. Change in physical activity was characterized by calculating the difference between baseline and follow-up z-scores. Change scores were categorized as decreasing (large, moderate), stable, or increasing (large,moderate). Healthy weight was defined in childhood as a BMI less than international overweight cutoff points, and in adulthood as BMI<25 kg/m2. Healthy weight maintainers were healthy weight at both time points. Compared with those who demonstrated large relative decreases in physical activity, females in all other groups were 25–37% more likely to be healthy weight maintainers, although associations differed according to the physical activity measure used at follow-up and few reached statistical significance. Although younger males whose relative physical activity moderately or largely increased were 27–34% more likely to be healthy weight maintainers than those whose relative physical activity largely decreased, differences were not statistically significant. In conclusion, relatively increasing and stable physical activity from childhood to adulthood was only weakly associated with healthy weight maintenance. Examining personal, social, and environmental factors associated with healthy weight maintenance will be an important next step in understanding why some groups avoid becoming overweight.

Background: To determine whether the provision of higher levels of compulsory school physical activity is associated with higher physical activity and fitness levels and less overweight in childhood and 20 years later. Methods: As part of the 1985 Australian Schools Health and Fitness Survey, 109 schools reported how much compulsory physical education (PE) and school sport they provided and were classified as low (<110 and <150 minutes/week for primary and secondary schools, respectively), medium (110–149 and 150–189 minutes/week for primary and secondary schools, respectively) or high (≥150 and ≥190 minutes/week for primary and secondary schools, respectively) compulsory physical activity schools by tertile cutpoints. 6,412 children reported frequency and duration of school (PE and sport) and non-school (commuting and non-organised exercise) physical activity and had height and weight measured; overweight was defined using body mass index (BMI)(m/kg2)cutpoints. 9, 12 and 15 year-olds (n = 2,595) completed a cycle ergometer fitness test (physical working capacity at heart rate 170, PWC170). At follow-up in 2004–5, 2,346 participants kept a pedometer record, completed the International Physical Activity Questionnaire and/or a PWC170 fitness test; and had height and weight measured (overweight = BMI≥25 m/kg2). Results: At baseline and follow-up, median total physical activity, fitness and BMI were similar in participants who attended low, medium and high physical activity schools, and those attending high physical activity schools reported only modestly higher school physical activity. There was no difference in the prevalence of high total physical activity and fitness levels in childhood or adulthood across compulsory school physical activity categories. The prevalence of overweight in childhood and adulthood was similar across low, medium and high compulsory physical activity schools. Conclusion: The amount of compulsory physical activity reported by schools was no

PURPOSE: To compare the ability of alternative measures of physical activity and fitness to quantify associations with health outcomes. METHODS: Associations between a range of subjective and objective physical activity and fitness measures and cardio-metabolic risk factors were examined using data from 1,631 Australians aged 26-36 years. Anthropometry, fitness, blood pressure and fasting blood glucose, insulin, and lipids were measured at study clinics. Participants completed the International Physical Activity Questionnaire (IPAQ), 7-day pedometer diaries, and reported sedentary behavior (sitting, television viewing). RESULTS: In men and women, associations were strongest for fitness, with those in the highest (versus lowest) fitness quarter having a 75-80% lower prevalence of two or more primary risk factors (waist circumference, HDL cholesterol, and insulin resistance). In men, a 60-70% reduced prevalence of two or more risk factors was observed across extreme quarters of IPAQ leisure, IPAQ vigorous, sitting duration and pedometer measures. Similar reductions in prevalence were observed only across extreme quarters of pedometer activity and television viewing in women. CONCLUSIONS: Associations between alternative measures and cardio-metabolic risk were relatively independent, suggesting that a range of physical activity and fitness measures may be needed to most accurately quantify associations between physical activity and health.

The objective of this study was to determine whether change in physical activity was associated with maintaining a healthy weight from childhood to adulthood. This prospective cohort study examined 1,594 young Australian adults (48.9% female) aged 27–36 years who were first examined at age 9–15 years as part of a national health and fitness survey. BMI was calculated from measured height and weight, and physical activity was self-reported at both time points; pedometers were also used at follow-up. Change in physical activity was characterized by calculating the difference between baseline and follow-up z-scores. Change scores were categorized as decreasing (large, moderate), stable, or increasing (large,moderate). Healthy weight was defined in childhood as a BMI less than international overweight cutoff points, and in adulthood as BMI<25 kg/m2. Healthy weight maintainers were healthy weight at both time points. Compared with those who demonstrated large relative decreases in physical activity, females in all other groups were 25–37% more likely to be healthy weight maintainers, although associations differed according to the physical activity measure used at follow-up and few reached statistical significance. Although younger males whose relative physical activity moderately or largely increased were 27–34% more likely to be healthy weight maintainers than those whose relative physical activity largely decreased, differences were not statistically significant. In conclusion, relatively increasing and stable physical activity from childhood to adulthood was only weakly associated with healthy weight maintenance. Examining personal, social, and environmental factors associated with healthy weight maintenance will be an important next step in understanding why some groups avoid becoming overweight.