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The literature provides evidence that maternal health is strongly linked with noncommunicable diseases (NCDs) and their associated risk factors. Enabling women with the asset of health literacy may help to reduce the intergenerational impact of NCDs. However, little is known about the health literacy of pregnant women and women with young children in Tasmania and globally. This study aimed to identify the health literacy status of pregnant women and women with young children (0-8 years) living in Tasmania and describe their health literacy status according to their demographic characteristics.An online cross-sectional survey was undertaken. The survey included demographic questions and a health literacy questionnaire (HLQ). The description of demographic differences across the HLQ scales focused on effect sizes (ES) for standardised differences in mean health literacy scores. The differences found to be statistically significant at P 0.05 were also included.194 participants completed the survey with a mean age of 35.3 years. 73.2% were married, 16.5% were pregnant, 93% had one or more children and 81.5% were university educated. For the first five HLQ scales (score range 1-4), the lowest overall score was seen for the scale "Actively managing my health" (mean = 2.96; SD = 0.54). For the last four scales (score range 1-5), the lowest overall score was seen for the scale "Navigating the health care system" (mean = 3.75, SD = 0.67). Nonpregnant women, women with children, women with chronic health conditions and nonmarried women experienced more health literacy challenges.Women in our study showed various strengths and challenges with mean scores varying across the nine HLQ scales. Understanding the health literacy needs of women will enable health services to co-design solutions and interventions capable of responding to the evolving health needs of pregnant women and women with young children. This approach will ensure that codesigned solutions can engage the end-user in healthy lifestyle practices and the solutions are sustainable. SO WHAT?: We must shift away from a "one size fits all" approach to tailor services to respond to the differing health literacy needs of pregnant women and women with young children to support healthy lifestyle practices and reduce the NCD burden.

Purpose: To promote greater muscular strength across the life course and, in turn, help improve long-term health outcomes, strategies aimed at increasing muscular strength are required. To inform these strategies, this study identified childhood factors associated with muscular strength trajectories. Methods: Prospective longitudinal study of 1280 Childhood Determinants of Adult Health participants who had a range of potentially modifiable factors (e.g., anthropometric measures, physical activity) and health and risk motivation items (e.g., attitudes, beliefs, and intentions on health-related actions) measured in childhood and had their muscular strength assessed up to three times between childhood and midlife. Associations between childhood factors and three predetermined life course muscular strength trajectories (identified previously using group-base trajectory modeling as follows: above average and increasing, average, and below average and decreasing) were examined using log multinomial regression. Results: Greater physical fitness, physical activity, fat-free mass, enjoyment of physical activity, physical education, and school sports, and positive attitudes regarding the importance of exercising, staying fit, and body image were associated with a lower likelihood of being in the below average and decreasing muscular strength trajectory (relative risk range, 0.45–0.98). Greater physical fitness, physical activity, and fat-free mass, and attending an independent school were associated with a higher likelihood of being in the above average and increasing muscular strength trajectory (relative risk range, 1.03–1.93). Conclusions: In addition to providing health benefits in the short term, physical activity, physical fitness, positive health attitudes, and healthy weight in childhood may lead to better muscular strength in the long term.

Objective To describe the status of and identify factors associated with physical activity promotion by podiatrists. Design Cross sectional survey. Method In 2016−17 Australian podiatrists were invited to complete an online survey. Items assessed by Likert scale included; frequency of assessing and promoting physical activity and podiatrists’ intentions, attitudes, social norms, confidence, barriers, role beliefs and perceived knowledge and skills regarding the promotion of physical activity. Data were analysed using descriptive statistics, exploratory factor analysis and structural equation modelling. Results Of 316 respondents, 62% reported always/or often giving general and 39% specific physical activity advice. Attitudes to physical activity promotion were mostly positive and 83% agreed it was part of their role. Many believed they have the knowledge 62%) and skills to promote physical activity. Most podiatrists were confident to carry out basic physical activity promotion activities (83%), but fewer were confident assessing physical activity levels (54%), providing specific advice (47%), monitoring patient physical activity levels (49%) and carrying out physical activity counselling (41%). Modelling revealed intention to promote physical activity was most strongly influenced by experiential beliefs (β = 0.35, 95%CI 0.20−0.51) and instrumental beliefs (β = 0.27, 95%CI 0.15−0.40), whereas physical activity promotion was influenced by intention (β = 0.45, 95%CI 0.35−0.55) and behavioural control (β = 0.43, 95%CI 0.33−0.53). Conclusion Physical activity promotion is feasible and regularly practiced in the podiatry setting, however current practice appears suboptimal. Attitudes and behavioural control appear influential in engagement and deserve consideration when designing strategies to improve delivery in podiatric practice.

A better understanding of the physical activity (PA) infrastructure in schools, the walkability of neighborhoods close to schools, and the food environments around schools, particularly in rural, socioeconomically challenged areas such as the North-West (NW) of Tasmania, could be important in the wider effort to improve the health of school-age children. Accordingly, this research aimed to assess PA resources, walkability, and food environments in and around schools in three socioeconomically disadvantaged, regional/rural Local Government Areas (LGAs) of Tasmania, Australia. A census of schools (including assessment of the PA infrastructure quality within school grounds), a walkability assessment, and a census of food outlets surrounding schools (through geospatial mapping) were executed. Most of the schools in the study region had access to an oval, basketball/volleyball/netball court, and free-standing exercise equipment. In all instances (i.e., regardless of school type), the quality of the available infrastructure was substantially higher than the number of incivilities observed. Most schools also had good (i.e., within the first four deciles) walkability. Numerous food outlets were within the walking zones of all schools in the study region, with an abundance of food outlets that predominantly sold processed unhealthy food.

Issue addressed: Physical activity is lower and rates of preventable common diseases are higher in regional/rural than urban Australia. Active commuting (walking/bicycling to get from one place to another) may benefit health through increased physical activity, but most evidence of its correlates come from urban studies. This study aimed to investigate associations between active commuting, socio-demographic characteristics, behaviours, total physical activity and health in a regional/rural Australian state. Methods: This study used data from the 2016 Tasmanian Population Health Survey, a representative cross-sectional self-report survey of 6,300 adults in Tasmania, Australia. Logistic regression modelling investigated associations between socio-demographic, behavioural and health characteristics and past week active commuting frequency. Results: In multivariable models, being younger, having tertiary qualifications, living in a socio-economically advantaged area, being physically active, having a healthy body mass index and good/excellent self-rated health were associated with engaging in more active commuting. Inner regional dwellers were no more likely than outer regional dwellers to actively commute after covariate adjustment. Conclusion: Strategies to promote active commuting in regional/rural areas might consider targeting older adults, those less educated, those living in socio-economically disadvantaged areas, those less physically active, those with poorer health and those with higher body mass index. Research could further investigate why these groups appear to be less active for commuting purposes. So what?: Increasing physical activity and active commuting may help to reduce rates of preventable common diseases in regional/remote areas.

usc Background: Past Physical Activity Report Cards have indicated a minority of Australian children and young people are sufficiently active. The purpose of this paper is to summarise grades across 10 indicators of the 2022 Australian Physical Activity Report Card, to assess physical activity behaviours and supports. Methods: A development team consisting of research experts synthesised and evaluated national and state level data to inform grades for each indicator. Data were drawn from nationally and state/territory representative datasets spanning 2016-2021. Results: Overall Physical Activity Levels and Screen Time were both assigned grades of D-, remaining the worst performing indicators. Australia's best performing indicator was Community and the Built Environment (A-), followed by Organised Sport and Physical Activity (B-). Remaining indicators were Family and Peers (C+), School (C+), Strategies and Investments (C-), Active Transport (D-) and Physical Fitness (D-). Active Play was unable to be graded, due to lack of consensus on a primary metric for this indicator and a lack of representative data. Conclusion: Evidence suggests that physical activity levels of Australian children remain consistently low, despite access to and availability of facilities and open spaces. There is a strong need for a National Physical Activity Plan to address this. The theme for the 2022 Australian Physical Activity Report Card, REBOOT! Reimagining physically active lives encourages us all to think more imaginatively about how we might engage all children and young people through diverse physical activity opportunities to be more active. Refereed/Peer-reviewed

COVID-19-related restrictions disrupted the normal social and environmental systems within which children live, learn and play. These sudden societal changes provided opportunities for children and young people, their families, and the professionals and authorities supporting them to observe and experience a different type of world and reflect on what they value and what children’s lives could be.

Background Children with overweight or obesity are at greatly increased risk of experiencing obesity in adulthood but for reasons generally unknown some attain a healthier adult weight. This qualitative study investigated individual, social and environmental factors that might explain diverging body mass index (BMI) trajectories. This knowledge could underpin interventions to promote healthy weight. Methods This 2016 study included participants from three adult follow-ups of children who (when 7–15 years) participated in the 1985 Australian Schools Health and Fitness Survey and provided BMI data at each time point. Trajectory-based group modelling identified five BMI trajectories: stable below average, stable average, increasing from average, increasing from very high and decreasing from very high. Between six and 12 participants (38–46 years) from each BMI trajectory group were interviewed (n = 50; 60% women). Thematic analysis guided by a social-ecological framework explored individual, social and environmental influences on diet and physical activity within the work setting. Results A distinct approach to healthy behaviour was principally identified in the stable and decreasing BMI groups – we term this approach “health identity” (exemplified by “I love having a healthy lifestyle”). This concept was predominant in the stable or decreasing BMI groups when participants explained why work colleagues seemingly did not influence their health behaviour. Participants in the stable and decreasing BMI groups also more commonly reported, bringing home-prepared lunches to work, working or being educated in a health-related field, having a physically active job or situating physical activity within and around work – the latter three factors were common among those who appeared to have a more distinct “health identity”. Alcohol, workplace food culture (e.g. morning teas), and work-related stress appeared to influence weight-related behaviours, but generally these factors were similarly discussed across all trajectory groups. Conclusion Work-related factors may influence weight or weight-related behaviours, irrespective of BMI trajectory, but the concept of an individual’s “health identity” may help to explain divergent BMI trajectories. “Health identity” and its influence on health behaviour warrants further exploratory work. Electronic supplementary material The online version of this article (10.1186/s40608-019-0239-3) contains supplementary material, which is available to authorized users.

Background: Our aim was to describe patterns of sitting over time and determine the sociodemographic predictors of sitting over time among women living in socioeconomically disadvantaged neighbourhoods. Methods: Women age between 18 and 45 years (mean = 34.4 ±8.1, n = 4349) reported their sitting time, sociodemographic (e.g., age), and health (e.g., body mass index) three times over 5 years. Linear mixed modelling was used to determine the predictors of change in sitting over time, adjusting for covariates. Results: Mean baseline sitting time was 40.9 h/week, decreasing to 40.1 h/week over five years. Greater sitting time was reported in participants ≤25 years of age, living with obesity, living in urban areas, self-reported poor/fair health, working full-time, with higher education, never married and with no children. Annually, the average sitting time decreased by 0.4 h/week (95% CI, −0.7 to −0.05) in women working full-time but increased by 0.1 h/week (95% CI, −0.2 to 0.6) who were not working. Similarly, annual sitting time decreased by 0.6 h/week (95% CI, −0.2 to 1.3) in women with no children but increased by 0.4 h/week (95% CI, −0.2 to 0.5) and 0.9 h/week (95% CI, 0.3 to 1.3) among those with two and three/more children, respectively. Conclusion: Among disadvantaged women, those not working and with two or more children may be at particular risk for increased sitting time and warrant further attention.

Background: Socioeconomically disadvantaged women are at an increased risk of sedentary behaviors including television (TV) viewing and computer use, so identifying determinants of these behaviors is important. Methods: Women (n = 4349) self-reported weekly TV and computer time (in minutes per week), sociodemographic, and health data at 3 time points (2007–2013). Mixed-effect negative binomial regression was used to determine the baseline determinants of TV viewing and computer use over time, adjusting for confounders. Results: Over 5 years, median TV viewing decreased while median computer time increased. Cross-sectionally TV viewing was highest among participants classified as obese, with poorer health, current smokers, with lower education, not working, with no income, without partners and with no children and computer time was greater among younger women, living in urban areas, working full time, with higher education, without partners and with no children. Average computer time per year increased among those not working (7%), with lower education (5%), and with children (5%) but decreased among those with higher education (1%). However, no factors were associated with a change in TV viewing over time. Conclusion: Among socioeconomically disadvantaged women, interventions aimed at preventing increases in computer time should consider women with lower education, not working, and with children in their design.

Objectives The 2014 Australian Physical Activity and Sedentary Behaviour Guidelines (Adults) recommend muscle-strengthening activities ≥2 days/week. This study aimed to identify factors associated with 5-year change and stability in adherence to these guidelines. Design Two adult follow-ups of the Childhood Determinants of Adult Health (CDAH) Study. Participants (n = 1510) were 26–36 years (CDAH-1, 2004–06) and 31–41 years (CDAH-2, 2009–11). Methods Information on muscle-strengthening activities, sociodemographics, health, physical activity and sedentary behaviour was collected. Participants reporting muscle-strengthening activities ≥2 days/week ‘met guidelines’, with change and stability categorised as ‘persistent adherence’, ‘increasing adherence’, ‘decreasing adherence’ and ‘persistent non-adherence’. Differences in sociodemographic, health and behavioural factors were analysed using log multinomial regression. Results Between 15–21% of women (CDAH-1: 14.5%, 95% confidence interval = 12.5–16.9; CDAH-2: 20.7%, 95% confidence interval = 18.3–23.4) and ~21% of men (CDAH-1: 22.2%, 95% confidence interval = 19.0–26.0; CDAH-2: 21.0%, 95% confidence interval = 17.8–24.7) met muscle-strengthening guidelines, but only 8.5% (95% confidence interval = 7.2–10.1) of participants were persistently adherent. Remaining in or moving from a major city, CDAH-1 weight status, cumulative self-rated health and vigorous physical activity were positively associated with persistent adherence (relative risk range = 1.51–3.92), while female gender, becoming partnered and having children at any timepoint were negatively associated with persistent adherence (relative risk range = 0.38–0.58). Conclusions Adherence – particularly persistent adherence – to muscle-strengthening guidelines in this sample was low. Gender, marital status, weight status, BMI, self-rated health, urban-rural status, parental status, physical activity and sedentary behaviour were associated with adherence, and should be considered in intervention development to maximise effectiveness.

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.

Background Mothers from socioeconomically disadvantaged neighbourhoods are at elevated risk of physical inactivity and high levels of screen time. Yet, little is known regarding the social ecological factors that are longitudinally associated with physical activity and screen time in this target group, and whether the age of their children impacts these relationships. This study aimed to longitudinally examine the social ecological factors associated with physical activity and screen time amongst mothers living in socioeconomically disadvantaged neighbourhoods, and whether these differed according to their child’s age. Methods Data were from 895 mothers living in socioeconomically disadvantaged neighbourhoods (mean age 36.7 years) at baseline and three-year follow-up. Mothers self-reported weekly discretionary physical activity (leisure-time, LTPA; transport-related, TRPA) and screen time durations. Linear regression models assessed associations between five intrapersonal, three social and five physical environmental factors and LTPA, TRPA and screen time, adjusting for confounding factors, clustering by neighbourhood and baseline variables. Interaction analysis was conducted for age of children (younger and older children (n = 442) and mothers with older children (aged 5–12 years) only (n = 453). Results In adjusted models, all intrapersonal factors (self-efficacy, enjoyment, outcome expectations, behavioural intentions and behavioural skill), social support from friends, neighbourhood cohesion and number of televisions were longitudinally associated with LTPA amongst all mothers. Interaction models showed that findings were generally consistent across groups (i.e., those with both younger and older children compared to those with older children only), with three exceptions. Physical activity enjoyment and social support from family were associated with LTPA only among mothers with older children. Neighbourhood cohesion was associated with screen time only amongst mothers with both younger and older children. No associations were detected for TRPA. Conclusion Intrapersonal, social and physical environmental factors were longitudinally associated with mother’s LTPA, whilst neighbourhood cohesion was longitudinally associated with screen time behaviours amongst mothers. Interventions aimed at increasing LTPA amongst mothers (particularly those from socioeconomically disadvantaged neighbourhoods) may need to target all domains of the social ecological model and may require some tailoring according to the age of children. Further work is needed to identify longitudinal associations with screen time and TRPA in this population group.

Objective To identify factors associated with non-medical health professionals’ engagement in physical activity (PA) promotion. Methods Five electronic databases were searched for studies including practising health professionals (excluding medical doctors), a PA promotion practice measure, a test of association between potential influencing factors and PA promotion practice, and written in English. Two researchers independently screened studies and extracted data. Extracted data were synthesized in a tabular format with a narrative summary (thematic analysis). Results Thirty studies involving 7734 non-medical health professionals were included. Self-efficacy in PA promotion, positive beliefs in the benefits of PA, assessing patients’ PA, and PA promotion training were the main factors associated with engaging in PA promotion. Lack of remuneration was not associated. Common study limitations included a lack of information on non-responders, data collection by survey only and limited reliability or validity testing of measurements. Conclusions There are common factors influencing PA promotion, but the absence of studies from some health professions, limitations related to study measures, and the lack of randomised controlled intervention trials highlights the need for further research. Practice Implications The factors identified may prove useful for guiding the development of strategies to encourage greater engagement in PA promotion by health professionals.

Issue addressed: parkrun is a free, weekly, timed, international mass community 5‐km walk/run event. Unlike other paid events, parkrun attracts populations harder to engage in physical activity (PA) (eg, women, those with overweight/obesity or illness/injury/disability). This exploratory qualitative study investigated the individual, social and environmental factors associated with parkrun's broad appeal in Australia. Methods: Tasmanian parkrunners who completed a quantitative survey (2016) were purposively recruited for a 2017 interview study. Semistructured interviews focused on reasons for parkrun participation. Data saturation was achieved by the tenth interview. Data were analysed thematically. Results: Four themes emerged: (a) participation facilitators and barriers; (b) PA gain and broader community benefit; (c) social connections/networks; and (d) organisational issues. Appealing characteristics of parkrun included strong social support, performance gain opportunities, socialising, inclusivity (eg, all ages/abilities), sense of community, positive atmosphere and accessibility (eg, no cost and convenience). Some participants reported that parkrun had stimulated gains in their total PA (not always limited to walking/running) and that parkrun may also result in other community benefits (eg, supporting local businesses, fee‐based running club/event participation and "parkrun tourism"). Most participants first attended parkrun because of encouragement from their social networks, and participants subsequently encouraged others to attend. Participants found parkrun events well organised, but identified some potential threats (eg, local politics). Conclusions: Social factors appeared critical in driving initial and ongoing parkrun participation. parkrun may lead to wider community benefits beyond that gained through increased individual PA. These findings highlight the "success factors" driving parkrun participation and provide insights for other community‐based PA promotion activities.

Purpose: “ parkrun” is a free and increasingly popular weekly 5-km walk/run international community event, representing a novel setting for physical activity (PA) promotion. However, little is known about who participates or why. This study aimed to identify sociodemographic, health, behavioral, individual, social, and environmental factors associated with higher levels of participation. Design: Cross-sectional. Setting: Tasmania, Australia; June 2016. Participants: Three hundred seventy two adult parkrun participants. Measures: Online survey measuring sociodemographic, health, individual, social and environmental factors, parkrun participation, and PA. Analysis: Descriptive statistics, zero-truncated Poisson regression models. Results: Respondents (n = 371) were more commonly women (58%), aged 35 to 53 years (54%), and occasional or nonwalkers/runners (53%) at registration. A total of 44% had overweight/obesity. Half had non-adult children, most spoke English at home, and 7% reported PA-limiting illness/injury/disability. Average run/walk time was 30.2 ± 7.4 minutes. Compared to regular walkers/runners at registration, nonwalkers/runners were less commonly partnered, more commonly had overweight/obesity, less physically active, and had poorer self-rated health. Multivariate analyses revealed relative parkrun participation was inversely associated with education level and positively associated with interstate parkrun participation, perceived social benefits, self-efficacy for parkrun, and intentions to participate. Conclusion: parkrun attracts nonwalkers/runners and population groups hard to engage in physical activity. Individual- and social-level factors were associated with higher relative parkrun participation. parkrun’s scalability, accessibility, and wide appeal confers a research imperative to investigate its potential for public health gain.

ObjectiveThe purpose of the current study was to examine associations of individual and aggregated screen-based behaviours, and total sitting time, with healthy and unhealthy dietary intakes among adolescents.DesignCross-sectional study of adolescents. Participants self-reported durations of television viewing, computer use, playing electronic games (e-games), total sitting time, daily servings of fruits and vegetables, and frequency of consumption of sugar-sweetened beverages (SSB), diet beverages, fast foods and discretionary snacks. Logistic regression models were conducted to identify associations of screen-based behaviours, total screen time and total sitting time with dietary intakes.SettingVictoria, Australia.SubjectsAdolescents (n 939) in School Year 11 (mean age 16·8 years).ResultsThe results showed that watching television (≥2 h/d) was positively associated with consuming SSB and diet beverages each week and consuming discretionary snacks at least once daily, whereas computer use (≥2 h/d) was inversely associated with daily fruit and vegetable intake and positively associated with weekly fast-food consumption. Playing e-games (any) was inversely associated with daily vegetable intake and positively associated with weekly SSB consumption. Total screen (≥2 h/d) and sitting (h/d) times were inversely associated with daily fruit and vegetable consumption, with total screen time also positively associated with daily discretionary snack consumption and weekly consumption of SSB and fast foods.ConclusionsIndividual and aggregated screen-based behaviours, as well as total sitting time, are associated with a number of indicators of healthy and unhealthy dietary intake. Future research should explore whether reducing recreational screen time improves adolescents’ diets.

This study examined two year changes in children's active transport and independent mobility and prospective associations between individual, social and physical environmental predictors of interest and these behaviors two years later. Overall, 43.5% of children (12.0 ± 2.1 years) used active transport on the school journey at T1 and at T2 (p=0.77), and 35.3% engaged in independent mobility on the school journey at T1 and 29.6% at T2 (p=0.07). Enjoyment, parental safety concerns, and proximity to walking tracks were associated with independent mobility on the school journey. Road safety and social norms were associated with active transport and independent mobility to local destinations. These factors provide potential targets for interventions.

To help inform strategies aimed at increasing muscular fitness levels, we examined factors associated with childhood muscular fitness (strength and power) that preceded the recently observed secular decline. Data were available from a nationally representative sample of Australian children aged 7–15 years in 1985 (n = 8469). Muscular fitness measures included strength (right and left grip, shoulder extension and flexion, and leg strength) and power (standing long jump distance). Anthropometric (adiposity, fat-free mass), cardiorespiratory fitness (CRF), flexibility, speed capability, physical activity (individual and parental), dietary quality and intake (fruit, vegetable, protein) and sociodemographic (area-level socioeconomic status (SES), school type) data were available. Statistical analyses included sex-stratified linear regression. Of all examined factors, measures of adiposity, fat-free mass, CRF, flexibility and speed capability were associated with muscular fitness at levels that met Cohen’s threshold for important effects (r-squared = 0.02 to 0.28). These findings highlight the multifactorial relationship between muscular fitness and its determinants. Collectively, these factors were powerful in explaining muscular strength (females: r-squared = 0.32; males: r-squared = 0.41) and muscular power (females: r-squared = 0.36; males: r-squared = 0.42). These findings highlight modifiable and environmental factors that could be targeted to increase childhood muscular fitness.

Purpose: Child and adult muscular power have been shown to associate with contemporary cardiometabolic health. Muscular power typically persists (tracks) between childhood and adulthood. Few studies span childhood to adulthood, so we aimed to identify modifiable and environmental factors associated with the persistence or change in muscular power across the life course. Methods: Prospective study examining 1938 participants who had their muscular power (standing long jump distance) measured in 1985 as children 7–15 yr old and again 20 yr later in adulthood (26–36 yr old). A selection of objectively measured anthropometric characteristics (adiposity and fat-free mass), cardiorespiratory fitness (CRF), self-reported physical activity, dietary (quality and fruit, vegetable, and protein intake), and sociodemographic data were available at both time points. Muscular power was separated into thirds, and participants were reported as having persistently low, decreasing, persistently moderate, increasing, or persistently high muscular power. Results: Higher adiposity, lower physical activity, diet quality and socioeconomic status (SES) across the life course, and lower adult CRF were associated with persistently low muscular power. Lower adult protein intake and an increase in adiposity over time were associated with decreasing muscular power. An increase in fat-free mass was associated with a reduced probability of decreasing or persistently high muscular power and an increased probability of increasing muscular power. Higher adult fruit intake was associated with increasing muscular power. Lower adiposity across the life course, higher adult CRF and SES, and higher child protein intake were associated with persistently high muscular power. Conclusion: Healthy weight, good CRF, greater protein intake, and high SES are important correlates of high muscular power maintained from childhood to adulthood.

Objective: Little is known about how the physical environment impacts physical activity behaviour among rural populations, who are typically less active and at higher risk of chronic disease than urban dwellers. The lack of individual-level instruments to assess the physical environment in rural areas limits advancement of this field. Among rural adults, this study aimed to evaluate (a) the test-retest reliability of a self-reported questionnaire of individual-level perceptions of the physical activity environment, and (b) the stability of a self-reported physical activity questionnaire. Design: Cross-sectional questionnaire repeated twice, 2 weeks apart. The questionnaire included 94 items relating to the perceived physical environment (representing nine summary scores), demographic characteristics and physical activity. Setting: Rural Australia. Participants: Rurally residing adults (≥18 years) across three Australian states.Main outcome measures: Test-retest reliability evaluated by weighted Kappa statistics(individual items) and intra-class correlations (summary scores). Results: A total of 292 participants (20% men) completed both questionnaires, on average22 days apart. Test-retest reliability of individual items ranged from weighted Kappa 0.37-0.85 (median: 0.59). Internal reliability for five summary scores was good to excellent (Cronbach's alpha: 0.81-0.97). Test-retest reliability was good to excellent for six summary scores (intra-class correlations: 0.67-0.77). Conclusions: The findings indicated good to excellent test-retest reliability for most items, particularly “fixed” constructs for this new questionnaire measuring the perceived physical environment in rural populations. This study represents an important step towards improving measurement of physical activity environments in rural populations, potentially leading to better tailored interventions to promote active and healthy living in rural areas. Refereed/Peer-reviewed

Background: Understanding body mass index (BMI) trajectories across the lifecourse may help identify risk of overweight or obesity and strategic points for preventive interventions. We describe BMI trajectories from childhood to adulthood in four population-based cohorts established in the 1970s-80s and their sociodemographic correlates. Methods: Data were from 12,086 participants (45% male) from four cohorts established in Australia, Finland and the US. Participants had ≥3 measures of height and weight, including ≥1 in childhood (6-18 years, mean 9.7 to 11.1 years at first visit) and ≥1 in adulthood (mean 40.0 to 50.9 years at last visit). Latent Class Growth Mixture Modelling estimated BMI trajectory groups. Correlates (age, gender, race, parental education) of BMI trajectories were identified with log multinomial regression. Results: Mean BMI ranged from 17.8-18.3 kg/m 2 at first visit and 26.4-30.2 kg/m 2 at last visit. Six BMI trajectories (Figure) were identified in three cohorts: persistently normal (48-57% of participants), improving from high (1-2%), progressing to overweight (30-39%), progressing to obese (1-8%), late onset obese (2-6%), and progressing to severe obesity (1-3%). One cohort had a seventh group: greatly improving ( Conclusion: Similar BMI trajectories were identified across cohorts, countries and time, despite different BMI distributions. Females and black Americans were most likely to be of high BMI at the end of follow-up. Few participants (≤2%) improved from high BMI. A better understanding of the factors that influence the highest and improving BMI trajectories may help identify risk reduction strategies.

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. Summary: Public transport use can lead to physical activity (PA) gain. About 1091 adult Tasmanian survey respondents favoured three/ten strategies to increase bus use: real-time bus information, bus-only lanes and employee incentives/rewards. Follow-up focus groups/interviews (n = 31) indicated: potential for better certainty, efficiency or cost-savings drove strategy preferences; some strategies may facilitate PA gain.

Body mass index (BMI) trajectories that improve over the lifecourse result in better cardiometabolic profiles, but only a small proportion of children of an unhealthy weight show improving BMI trajectories. This study aimed to examine the childhood factors related to diverging BMI trajectories from childhood into adulthood using data from the Childhood Determinants of Adult Health study. A convergent parallel mixed methods design was used. Quantitative data (n = 2206) came from the first (2004–06) and second (2009–11) adult follow-ups of 8498 Australian children (7–15 years) assessed in 1985. Using BMI z-scores, group-based trajectory modelling identified five trajectory groups: Persistently Low, Persistently Average, High Decreasing, Average Increasing and High Increasing. Qualitative data (n = 50) were collected from a sub-group (2016; 38–46 years). Semi-structured interviews with 6–12 participants from each BMI trajectory group focused on individual, social and environmental influences on weight, diet and physical activity across the lifecourse. Log multinomial regression modelling estimated relative risks of trajectory group membership across childhood demographic, behavioural, health, parental and school factors. Qualitative data were thematically analysed using a constant comparative approach. Childhood factors influenced BMI trajectories. Paternal education, main language spoken, alcohol and self-rated health were significant quantitative childhood predictors of BMI trajectory. A distinct ‘legacy effect’ of parental lifestyle influences during childhood was apparent among interview participants in the Stable and High Decreasing groups, a strong and mostly positive concept discussed by both men and women in these groups and persisting despite phases of unhealthy behaviours. In contrast, the ‘legacy effect’ was much weaker in the two Increasing BMI groups. This study is the first to simultaneously identify important quantitative and qualitative childhood factors related to divergent BMI trajectories, and to observe a legacy effect of parents' lifestyle behaviours on divergent BMI trajectories. This work provides direction for further exploration of the factors driving divergent BMI trajectories.

Walking to more distant public transport stops is commonly promoted for physical activity gain. We examined the uptake of, and reasons for, this behaviour and its correlates through a cross-sectional survey (n = 944) and independent interview study (n = 22). Quantitative analysis examined correlates of frequency of walking to more distant bus stops, including demographic variables, past week bus use, bus stop accessibility, and physical activity. Interviews explored reasons for engaging in this behaviour. Of participants (38%) who had used the bus the previous week, 13% had walked to a more distant bus stop every/most times. Median walking and total physical activity were highest (P = 0.003) among this group (210 and 465 min/week, respectively) compared to those who did sometimes (150 and 260 min/week, respectively) or not at all (150 and 270 min/week, respectively). Among interview participants who engaged in this behaviour (n = 12), over half did so for physical activity gain, with the remaining being driven by other co-benefits. Many interviewees overlooked the physical activity benefit of this behaviour. This novel study integrated quantitative and qualitative data and discovered those who walk to more distant public transport stops were generally more physically active than those who do not. While some users were aware of the health benefits, many did so for other reasons.

Limited longitudinal evidence of the predictors of physical activity (PA) patterns over time exists, particularly among high-risk groups such as women living in socioeconomically disadvantaged areas. This study aimed to: 1) describe leisure-time PA (LTPA) and transport-related PA (TRPA) patterns over time; and 2) identify individual, social and physical environmental predictors of LTPA and TRPA patterns over five years. Baseline (2007–08) data were collected and analysed (2016–18) from n = 4349 women (18–46 years) from disadvantaged areas of Victoria, Australia. Three- and five-year follow-up data were collected in 2010–11 (n = 1912) and 2012 (n = 1560). LTPA and TRPA were self-reported using the International Physical Activity Questionnaire, and patterns categorised as consistently low, persistently increasing, persistently decreasing, or inconsistent. Compared to a consistently low LTPA pattern, greater family support predicted both persistent decreases (odds ratio [OR] 1.20, 95% CI 1.05–1.36) and persistent increases (OR 1.17, 95% CI 1.04–1.32) in LTPA, while access to childcare predicted inconsistent LTPA patterns (OR 1.66, 95% CI 1.03–2.65). For both LTPA and TRPA, PA enjoyment predicted persistent increases (LTPA: OR 1.05, 95% CI 1.02–1.10; TRPA: OR 1.03, 95% CI 1.00–1.07), persistent decreases (LTPA: OR 1.04, 95% CI 1.00–1.08; TRPA OR 1.04, 95% CI 0.99–1.08), and inconsistent patterns (LTPA: OR 1.04, 95% CI 1.02–1.07; TRPA: OR 1.03, 95% CI 1.01–1.06). Although directionality was inconsistent, and the magnitude of effects were small, PA enjoyment, family social support for PA and access to childcare warrant further investigation and consideration as potentially key factors impacting PA patterns among women living in socioeconomically disadvantaged areas.

Background The mechanisms explaining the positive relationship between television (TV) viewing and body mass index (BMI) are unclear. ‘Mindless eating’ and ‘physical activity displacement’ theories have been suggested, but have not been tested longitudinally among young adults. This study aimed to determine whether longitudinal associations between young adults’ TV viewing and BMI are explained by changes in TV-related food and beverage consumption (FBC) and/or leisure-time physical activity (LTPA) over 5 years among young adults. Methods A cohort of young Australian adults (n = 1068) was assessed in 2004–6 (T1) and 2009–2011 (T2), height and weight were measured (T1) or self-reported (T2), and participants self-reported TV viewing time (hours/day), weekly TV-related FBC and LTPA (mins/week). Linear regression was used to examine direct pathways between TV viewing and BMI, adjusting for TV-related FBC and LTPA to examine indirect pathways. Results The association between TV viewing time and BMI (β: 0.41, 95% CI 0.03, 0.78 for > 1-h increase in TV viewing/day) was not explained by TV-related FBC (β: 0.37, 95% CI -0.18, 0.91) or LTPA (β: 0.38, 95% CI -0.17, 0.93) hypotheses. Increased TV-related FBC was associated with increased TV viewing (0.39 ± 1.54 h/day) and greater increases in BMI (0.92 ± 2.28 kg/m2, p = 0.16). LTPA increases were not associated with changes in TV viewing (− 0.07 ± 1.42 h/day), and increases in BMI were smallest when LTPA increased (0.44 ± 2.25 kg/m2) and greatest when LTPA decreased (0.82 ± 2.30 kg/m2) (p = 0.13). Conclusions Factors other than changes in TV-related FBC or LTPA may explain the longitudinal relationship between TV viewing and increasing BMI among young adults. Findings confirm that TV viewing is a risk factor for weight gain in young adults but the underlying causal mechanisms remain unclear. Electronic supplementary material The online version of this article (10.1186/s12889-018-5674-4) contains supplementary material, which is available to authorized users.

Issue addressed Social-ecological models of health behaviour acknowledge environmental influences, but research examining how the environment shapes physical activity in rural settings is limited. This study aimed to explore the environmental factors that act as barriers or facilitators to physical activity participation among rural adults. Methods Forty-nine adults from three regions of rural Tasmania, Australia, participated in semi-structured interviews that explored features of the environment that supported or hindered physical activity. Interviews were digitally recorded, transcribed verbatim and analysed thematically. Results Four key themes emerged: functionality, diversity, spaces and places for all and realistic expectations. ‘Functionality’ included connectivity with other destinations, distance, safety, continuity, supporting infrastructure and surfacing. While there was limited ‘diversity’ of structured activities and recreational facilities, the importance of easy and convenient access to a natural environment that accommodated physical activity was highlighted. ‘Spaces and places for all’ highlighted the importance of shared-use areas, particularly those that were family- and dog-friendly. Despite desires for more physical activity opportunities, many participants had ‘realistic expectations’ of what was feasible in rural settings. Conclusions Functionality, diversity, spaces and places for all and realistic expectations were identified as considerations important for physical activity among rural adults. Further research using quantitative approaches in larger samples is needed to confirm these findings. So what? Urban-centric views of environmental influences on physical activity are unlikely to be entirely appropriate for rural areas. Evidence-based recommendations are provided for creating new or modifying existing infrastructure to support active living in rural settings.

This study aimed to determine whether associations between the perceived environment and physical activity are moderated by urban-rural status among midolder aged adults. Environmental (safety, aesthetics, physical activity environment) and physical activity (total, leisure, transport) data from 3,888 adults (55 to 65 years) from urban and rural areas of Victoria, Australia, were analyzed. Multinomial logistic regression examined interactions between urban-rural status and environments in associations with physical activity. Significant (P < .05) interactions were evident and indicated positive associations only among older rural adults for both safety and aesthetics with total and transport physical activity (e.g., rural adults reporting higher safety were 91% to 118% more likely to have higher activity than rural adults reporting low safety). In contrast, the physical activity environment was positively associated with leisure activity among only urban adults. Findings suggest that some tailoring of physical activity promotion strategies targeting the environment may be required for urban and rural midolder aged adults.

Purpose This prospective cohort study investigated whether body mass index (BMI) and weight status in mid-adulthood were predicted by trajectories of urban-rural residence from childhood to adulthood. Methods Participants aged 7–15 years in 1985 (n = 8498) were followed up in 2004–2006 (n = 3999, aged 26–36 years) and 2009–2011 (n = 3049, aged 31–41 years). Area of residence (AOR) was classified as urban or rural at each time point. BMI and/or weight status was calculated from self-reported weight and height (2009–2011). We tested which of three life-course models (“accumulation,” “sensitive period,” “mobility”) best explained the AOR-BMI and/or weight status association using a novel life-course modeling framework. Results Accumulation and sensitive period models best described the effect of AOR on mid-adulthood BMI and weight status. Those with greater accumulated exposure to rural areas had a higher BMI (β = 0.29 kg/m2 per time in a rural area, P = .005) and were more likely obese (relative risk = 1.13 per time in a rural area, P = .002). Living in rural areas at ages 26–30 years was also associated with a higher BMI and obesity in mid-adulthood. Conclusions Greater cumulative exposure to rurality and exposure during the “sensitive period” of young adulthood is associated with obesity in middle-aged adults. This study highlights the important contribution of context to the development of obesity over the life course.

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 (

Issues addressed Physical activity recommendations for adults worldwide advise participation in moderate-intensity physical activity, such as walking, on most days of the week. Younger adults report the lowest prevalence of walking. This mixed-methods study explores the salience of Australia’s activity recommendations around moderate-intensity physical activity, particularly walking, for young Australian adults. Methods Semistructured interviews were conducted with 24 young Australians aged 17–25 years. During interviews, Australia’s physical activity recommendations for adults were explained to participants, highlighting the inclusion of moderate-intensity physical activity such as walking. Participants were asked to comment on the recommendations and walking for physical activity and exercise. Data from interviews underwent an iterative thematic form of analysis. Participants also completed the International Physical Activity Questionnaire (IPAQ) and were asked to complete a pedometer diary. Results No participant was classified as sedentary; twenty three participants reported walking for transport and nine for leisure (IPAQ). During interviews, the majority of participants (n = 20) did not identify walking as physical activity or exercise. Participants focussed on the cardiorespiratory (fitness) benefits associated with physical activity and believed walking was of insufficient intensity to achieve these benefits at their age. Conclusions Walking was considered an everyday activity and of insufficient intensity to achieve any health or fitness benefits. So what? The belief that only vigorous physical activity conveys any fitness benefits may act as a barrier to participation in moderate-intensity physical activity such as walking, particularly among sedentary young people.

Summary To evaluate the effectiveness of school-based physical activity interventions on fitness, adiposity and cardiometabolic outcomes among schoolchildren. Medline, Embase, EBSCOhost CINAHL and ERIC databases were searched up to October 2012. Inclusion criteria: intervention delivered at school with controls having no intervention or usual physical education classes; participants aged 5‐18 years; outcomes spanning some or all of the above. We assessed levels of evidence for identified trials based on methodological quality and sample size. Dose of the interventions (a total summary measure of intensity, frequency and duration) were considered. Eighteen randomized controlled trials (RCTs, total participants = 6,207) were included, of which six were large, higher quality trials with high dose of the intervention. The intervention was consistent in increasing fitness with large, higher quality studies and high dose of intervention providing strong evidence. Dose of school-based physical activity is an important determinant of trial efficiency. Some large, higher quality RCTs provided strong evidence for interventions to decrease skin-fold thickness, increase fitness and high-density lipoprotein cholesterol. Evidence for body mass index, body fat and waist circumference, blood pressure and triglycerides, low-density lipoprotein cholesterol and total cholesterol remain inconclusive and require additional higher quality studies with high dose of interventions to provide conclusive evidence.

Objectives The aims of this study were to map obesity prevention activity being implemented by government, non-government, and community-based organizations; to determine practitioner and policy-maker perceptions of the feasibility and effectiveness of a range of evidence-based obesity prevention strategies; and to determine practitioner and policy-maker perceptions of preferred settings for obesity prevention strategies. Design and Methods This study involved a cross-sectional survey of 304 public health practitioners and policy-makers from government, non-government, and community organizations across Victoria, Australia. Participants reported their organizations' current obesity prevention programs and policies, their own perceptions of the feasibility and effectiveness of strategies to prevent obesity and their preferred settings for obesity prevention. Results Thirty-nine percent had an obesity prevention policy, and 92% were implementing obesity prevention programs. The most common programs focused on education, skill-building, and increasing access to healthy eating/physical activity opportunities. School curriculum-based initiatives, social support for physical activity, and family-based programs were considered the most effective strategies, whereas curriculum-based initiatives, active after-school programs, and providing access to and information about physical activity facilities were deemed the most feasible strategies. Schools were generally perceived as the most preferred setting for obesity prevention. Conclusion Many organizations had obesity prevention programs, but far fewer had obesity prevention policies. Current strategies and those considered feasible and effective are often mismatched with the empirical literature. Systems to ensure better alignment between researchers, practitioners, and policy-makers, and identifying effective methods of translating empirical evidence into practice and policy are required. Copyright © 2012 The Obesity Society.

Associations between parental perceived home and neighbourhood environments and children's physical activity (PA), and sedentary time (ST) and screen time and moderating effects according to urban/rural location were examined. Data were collected (2007-2008) from a cohort of women (aged 18-45 years) and their children (5-12 years) participating in the Resilience for Eating and Activity Despite Inequality (READI) study. A total of 613 children (47% boys; mean age 9.4±2.2 years) and their mothers were included in the study. Urban children had higher screen time than rural children. Mothers in rural areas reported greater access to physical activity equipment in the home, higher levels of descriptive norms for physical activity, greater knowledge of the neighbourhood, a stronger social network, and higher personal safety than urban mothers. There were five significant interactions between the home and neighbourhood environment and PA/ST according to urban/rural location. Among urban children, the importance of doing PA together as a family was positively associated with ST. Interventions targeting PA and ST may need to target different factors according to urban/rural location. © 2013 Elsevier Ltd.

Physical activity is important for preventing weight gain and obesity, but women experiencing socioeconomic disadvantage are at high risk of inactivity. This study aimed to determine the effectiveness of interventions to increase physical activity among women experiencing disadvantage, and the intervention factors (i.e. physical activity measure, delivery mode, delivery channel, setting, duration, use of theory, behavioural techniques, participant age, risk of bias) associated with effectiveness. We conducted a meta-analysis of controlled trials using random-effects models and meta-regression. Seven databases were searched for trials among healthy women (18-64 years), which included a physical activity intervention, any control group, and statistical analyses of a physical activity outcome at baseline and post-intervention. Nineteen studies were included (n = 6,339). Because of substantial statistical heterogeneity (χ(2) = 53.61, df = 18, P < 0.0001, I(2) = 66%), an overall pooled effect is not reported. In subgroup analyses, between-group differences were evident for delivery mode, which modestly reduced heterogeneity (to 54%). Studies with a group delivery component had a standardized mean difference of 0.38 greater than either individual or community-based delivery. Programs with a group delivery mode significantly increase physical activity among women experiencing disadvantage, and group delivery should be considered an essential element of physical activity promotion programs targeting this population group.