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INTRODUCTION Despite that the smoking prevalence has considerably declined in Australia after successful public health strategies over many decades, smoking is still the leading cause of preventable diseases and death in Australia. These declines have not occurred consistently across all geographical-demographic domains. In order to provide an evidence base for monitoring the trend towards the goal of reducing smoking across all domains in Australia, this study aims to estimate trends of smoking prevalence for small domains cross-classified by seven age groups (18-24, 25-29, 30-39, 40-49, 50-59, 60-69, and ≥70 years), two genders, and eight states and territories over twenty years (2001-2021). METHODS Direct estimates of smoking prevalence for the target small domains were calculated from the micro-data of the Australian National Health Surveys conducted in seven rounds during 2001-2021. The obtained direct estimates were then used as input for developing time-series models expressed in a hierarchical Bayesian structure as a form of small-area estimation. The developed models borrow cross-sectional, temporal, and spatial strength in such a way that they can interpolate smoking levels in the non-survey years for all detailed level small domains. Smoothed trends of smoking prevalence for higher aggregation levels are obtained by aggregation of the detailed level trend predictions. RESULTS Model-based small area estimators provide consistent and reasonable smoothed trends at both detailed and higher aggregation levels. Results show that the national-level trend exhibits a steeper linear decline over the study period, from 24% in 2001 to 12% in 2021, with a considerable gender difference of around 5% over the period, with males reporting a higher prevalence. Improved model-based estimates at the state level and by age also show steady declines in trends except for the Northern Territory (still above 20%) and older age groups 60-69 and ≥70 years (declining trends remain stable after 2012). CONCLUSIONS The findings of the study identify the geographical-demographic groups that had poor improvement over the period 2001-2021, and are still behind the target of achieving lower smoking prevalence. These, in turn, will help health researchers and policymakers deliver targeted programs to the most vulnerable, enabling the nation to meet its health goals in a timely way. [ABSTRACT FROM AUTHOR]

Physical activity (PA) during childhood and adolescence is important for the accrual of maximal peak bone mass. The precise dose that benefits bone remains unclear as methods commonly used to analyze PA data are unsuitable for measuring bone‐relevant PA. Using improved accelerometry methods, this study identified the amount and intensity of PA most strongly associated with bone outcomes in 11–12‐year‐olds. Participants (n = 770; 382 boys) underwent tibial peripheral quantitative computed tomography to assess trabecular and cortical density, endosteal and periosteal circumference and polar stress‐strain index. Seven‐day wrist‐worn raw acceleration data averaged over 1‐s epochs was used to estimate time accumulated above incremental PA intensities (50 milli‐gravitational unit (mg) increments from 200 to 3000 mg). Associations between time spent above each 50 mg increment and bone outcomes were assessed using multiple linear regression, adjusted for age, sex, height, weight, maturity, socioeconomic position, muscle cross‐sectional area and PA below the intensity of interest. There was a gradual increase in mean R2 change across all bone‐related outcomes as the intensity increased in 50 mg increments from >200 to >700 mg. All outcomes became significant at >700 mg (R2 change = 0.6%–1.3% and p = 0.001–0.02). Any further increases in intensity led to a reduction in mean R2 change and associations became non‐significant for all outcomes >1500 mg. Using more appropriate accelerometry methods (1‐s epochs; no a priori application of traditional cut‐points) enabled us to identify that ∼10 min/day of PA >700 mg (equivalent to running ∼10 km/h) was positively associated with pQCT‐derived measures of bone density, geometry and strength in 11–12‐year‐olds. Highlights: Accelerometry methods that are commonly used to assess free‐living, bone‐relevant physical activity (PA) are not well suited to measuring bone‐specific characteristics of PA (short bursts of high‐impact activity).Processing raw acceleration data using much shorter epochs (1‐s) and using incremental 50 mg intensity thresholds (rather than traditional, broad intensity thresholds) enabled a bone‐specific, beneficial intensity to be identified.The methods outlined provide a means for more precisely assessing free‐living bone‐relevant PA and permit the transparent and reproducible analysis of raw accelerometry data, which will enhance our ability to quantify dose‐response associations in the future. [ABSTRACT FROM AUTHOR]

Telerehabilitation is an appealing service delivery option for optimising recovery. Internationally, the equity of telerehabilitation services for people from culturally and linguistically diverse (CALD) backgrounds has been questioned. Using a 31-item survey, our study explored the access, readiness and willingness of 260 patients receiving allied health services from a large tertiary health service located in Sydney, Australia, to use telerehabilitation for adults. Overall, 72% patients reported having access to technology, 38% met our readiness criteria and 53% reported willingness to engage in telerehabilitation. There were no differences in access, readiness and willingness to engage in telerehabilitation between patients from CALD and non-CALD backgrounds. Age was the only factor that influenced access (OR = 0.94, 95% CI 0.90 to 0.97), readiness (OR = 0.95, 95% CI 0.92 to 0.98) and willingness (OR = 0.97, 95% CI 0.95 to 1.00) to engage in telerehabilitation. Past experience of telerehabilitation was related to willingness (OR = 2.73, 95% CI 1.55–4.79) but not access (OR = 1.79, 95% CI 0.87 to 3.68) or readiness (OR = 1.90, 95% CI 0.93 to 3.87). Our findings highlight the importance of ensuring positive patient experiences to promote ongoing willingness to use telerehabilitation. Efforts are needed to improve patients' digital health literacy, especially patients from older age groups, to ensure equitable engagement in telerehabilitation services. [ABSTRACT FROM AUTHOR]