ObjectivesThe study aimed (1) to quantify differences in modifiable risk factors between urban and rural populations, and (2) to determine the number of rural cardiovascular disease (CVD) and ischaemic heart disease (IHD) deaths that could be averted or delayed if risk factor levels in rural areas were equivalent to metropolitan areas.SettingNational population estimates, risk factor prevalence, CVD and IHD deaths data were analysed by rurality using a macrosimulation Preventable Risk Integrated Model for chronic disease risk. Uncertainty analysis was conducted using a Monte Carlo simulation of 10 000 iterations to calculate 95% credible intervals (CIs).ParticipantsNational data sets of men and women over the age of 18 years living in urban and rural Australia.ResultsIf people living in rural Australia had the same levels of risk factors as those in metropolitan areas, approximately 1461 (95% CI 1107 to 1791) deaths could be delayed from CVD annually. Of these CVD deaths, 793 (95% CI 506 to 1065) would be from IHD. The IHD mortality gap between metropolitan and rural populations would be reduced by 38.2% (95% CI 24.4% to 50.6%).ConclusionsA significant portion of deaths from CVD and IHD could be averted with improvements in risk factors; more than one-third of the excess IHD deaths in rural Australia were attributed to differences in risk factors. As much as two-thirds of the increased IHD mortality rate in rural areas could not be accounted for by modifiable risk factors, however, and this requires further investigation.

Remoteness is a key determinant of IHD burden in Australia. The reasons for increased IHD burden in rural compared to metropolitan communities of Australia are poorly understood, which has implications for the design of targeted interventions to reduce geographical inequalities.

Summary Physical inactivity is a major contributing factor to obesity, and both follow a socio‐economic gradient. This systematic review aims to identify whether the physical activity environment varies by socio‐economic position (SEP), which may contribute to socio‐economic patterning of physical activity behaviours, and in turn, obesity levels. Six databases were searched. Studies were included if they compared an objectively measured aspect of the physical activity environment between areas of differing SEP in a high‐income country. Two independent reviewers screened all papers. Results were classified according to the physical activity environment analysed: walkability/bikeability, green space, and recreational facilities. Fifty‐nine studies met the inclusion criteria. A greater number of positive compared with negative associations were found between SEP and green space, whereas there were marginally more negative than positive associations between SEP and walkability/bikeability and recreational facilities. A high number of mixed and null results were found across all categories. With a high number of mixed and null results, clear socio‐economic patterning in the presence of physical activity environments in high‐income countries was not evident in this systematic review. Heterogeneity across studies in the measures used for both SEP and physical activity environments may have contributed to this result.

Objective:To (i) determine the proportion of deaths from CVD that could be avoided in both rural and metropolitan Australia if public health recommendations were met; (ii) assess the impact on the rural CVD mortality; and (iii) determine if policy priorities should be different by rurality for CVD prevention.Design:A macro-simulation modelling study of population data. Population, risk factor and CVD death data stratified by rurality were analysed using the Preventable Risk Integrated Model. The baseline scenario was the current risk factor levels (including physical activity, smoking, diet and alcohol). The counterfactual scenario was the population levels of these risk factors expected if public health recommendations were met.Setting:Metropolitan and rural Australia.Participants:Rural- and metropolitan-dwelling adults in Australia.Results:Both populations would experience similar relative declines in the proportion of deaths from CVD. A total of 14 892 deaths from CVD would be avoided annually; with similar declines in the proportions of deaths by rurality. Critically, the order of policy priorities for public health recommendation attainment would differ by rurality CVD prevention, with addressing fat intakes being a higher priority in rural areas.Conclusions:Achieving public health recommendations in Australia would result in large declines in CVD mortality. Despite declines in overall CVD mortality under this scenario, an inequality in CVD burden would persist for rural populations. The order of risk factor priorities would differ by rurality.

Background Approximately a quarter of Australian children are classified as overweight or obese. In high-income countries, childhood obesity follows a socio-economic gradient, with greater prevalence amongst the most socio-economically disadvantaged children. Community-based interventions (CBI), particularly those using a systems approach, have been shown to be effective on weight and weight-related behaviours. They are also thought to have an equitable impacts, however there is limited evidence of their effectiveness in achieving this goal. Methods Secondary analysis was conducted on data collected from primary school children (aged 6–13 years) residing in ten communities (five intervention, five control) involved in the Whole of Systems Trial of Prevention Strategies for Childhood Obesity (WHO STOPS) cluster randomised trial in Victoria, Australia. Outcomes included Body Mass Index z-score (BMI-z) derived from measured height and weight, self-reported physical activity and dietary behaviours and health related quality of life (HRQoL). Repeat cross-sectional data from 2015 (n = 1790) and 2019 (n = 2137) were analysed, stratified by high or low socio-economic position (SEP). Multilevel linear models and generalised estimating equations were fitted to assess whether SEP modified the intervention effect on the outcomes. Results There were no overall changes in BMI-z for either SEP strata. For behavioural outcomes, the intervention resulted in a 22.5% (95% CI 5.1, 39.9) point greater improvement in high-SEP compared to low-SEP intervention schools for meeting physical activity guidelines. There were also positive dietary intervention effects for high SEP students, reducing takeaway and packaged snack consumption, although there was no significant difference in effect between high and low SEP students. There were positive intervention effects for HRQoL, whereby scores declined in control communities with no change in intervention communities, and this did not differ by SEP. Conclusion The WHO STOPS intervention had differential effects on several weight-related behaviours according to SEP, including physical activity. Similar impacts on HRQoL outcomes were found between high and low SEP groups. Importantly, the trial evaluation was not powered to detect subgroup differences. Future evaluations of CBIs should be designed with an equity lens, to understand if and how these types of interventions can benefit all community members, regardless of their social and economic resources.