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Cancer is a significant health issue globally and it is well known thatcancer risk varies geographically. However in many countries there are no smallarea level data on cancer risk factors with high resolution and complete reach,which hinders the development of targeted prevention strategies. UsingAustralia as a case study, the 2017-2018 National Health Survey was used togenerate prevalence estimates for 2221 small areas across Australia for eightcancer risk factor measures covering smoking, alcohol, physical activity, dietand weight. Utilising a recently developed Bayesian two-stage small areaestimation methodology, the model incorporated survey-only covariates, spatialsmoothing and hierarchical modelling techniques, along with a vast array ofsmall area level auxiliary data, including census, remoteness, andsocioeconomic data. The models borrowed strength from previously publishedcancer risk estimates provided by the Social Health Atlases of Australia.Estimates were internally and externally validated. We illustrated that in2017-18 health behaviours across Australia exhibited more spatial disparitiesthan previously realised by improving the reach and resolution of formerlypublished cancer risk factors. The derived estimates reveal higher prevalenceof unhealthy behaviours in more remote areas, and areas of lower socioeconomicstatus; a trend that aligns well with previous work. Our study addresses thegaps in small area level cancer risk factor estimates in Australia. The newestimates provide improved spatial resolution and reach and will enable moretargeted cancer prevention strategies at the small area level, supportingpolicy makers, researchers, and the general public in understanding the spatialdistribution of cancer risk factors in Australia. To help disseminate theresults of this work, they will be made available in the Australian CancerAtlas 2.0.

Mapping the prevalence of cancer risk factors at the small area level in Australia