  Cancer is a significant health issue globally and it is well known that
cancer risk varies geographically. However in many countries there are no small
area level data on cancer risk factors with high resolution and complete reach,
which hinders the development of targeted prevention strategies. Using
Australia as a case study, the 2017-2018 National Health Survey was used to
generate prevalence estimates for 2221 small areas across Australia for eight
cancer risk factor measures covering smoking, alcohol, physical activity, diet
and weight. Utilising a recently developed Bayesian two-stage small area
estimation methodology, the model incorporated survey-only covariates, spatial
smoothing and hierarchical modelling techniques, along with a vast array of
small area level auxiliary data, including census, remoteness, and
socioeconomic data. The models borrowed strength from previously published
cancer risk estimates provided by the Social Health Atlases of Australia.
Estimates were internally and externally validated. We illustrated that in
2017-18 health behaviours across Australia exhibited more spatial disparities
than previously realised by improving the reach and resolution of formerly
published cancer risk factors. The derived estimates reveal higher prevalence
of unhealthy behaviours in more remote areas, and areas of lower socioeconomic
status; a trend that aligns well with previous work. Our study addresses the
gaps in small area level cancer risk factor estimates in Australia. The new
estimates provide improved spatial resolution and reach and will enable more
targeted cancer prevention strategies at the small area level, supporting
policy makers, researchers, and the general public in understanding the spatial
distribution of cancer risk factors in Australia. To help disseminate the
results of this work, they will be made available in the Australian Cancer
Atlas 2.0.

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