Introduction: Out-of-hospital cardiac arrest (OHCA) is a major public health issue. Bystander CPR is an important predictor of survival following OHCA. Previous reports have shown significant regional variation in bystander CPR rates, even among witnessed cases. We examined the extent to which variation in both OHCA incidence and bystander CPR rates across local government areas (LGAs) in Victoria, Australia could be explained by regional characteristics. Methods: Using prospectively collected population-based OHCA data (2008–2013), we calculated OHCA incidence and bystander CPR rates among witnessed cases across 79 LGAs. We used mixed effects models to examine the proportion of variation in these rates which could be explained by (i) population density, (ii) socioeconomic status, (iii) ischaemic heart disease death rate (as a proxy for cardiovascular health) and the proportion of residents who: (iv) speak a language other than English in the home, (v) were foreign-born, (vi) were over 65 years, and (vii) obtained a bachelor degree. Results: There were 21,436 cases for analysis. In the multivariable analysis, older population, higher proportion of population with a bachelor degree and lower socio-economic status were all associated with an increased incidence of OHCA (all p<0.001), which explained 88.4% of the LGA-level variation in incidence. Only populationdensitywas significantly associatedwith bystander CPR rates (p<0.001). Arrests in the highest density quartile for LGAshad 38% lower odds of receiving bystander CPR compared to the LGAs in the least dense quartile, with 72.9% of the variation in the LGA bystander CPR rate explained by differences in population density. Conclusion: We found that a significant proportion of the regional variation in the incidence of OHCA and bystander CPR could be explained by regional characteristics. Interventions to improvebystanderCPR rates should target the regional characteristic of areas at highest-risk (high incidence and low bystander CPR). Further research is needed to understand themechanism bywhich population density affects bystander CPR rates.

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