Creating an interactive map visualising the geographic variations of the burden of diabetes to inform policymaking: An example from a cohort study in Tasmania, Australia

Abstract

Objectives: To visualise the geographic variations of diabetes burden and identify areas where targeted interventions are needed. Methods: Using diagnostic criteria supported by hospital codes, 51,324 people with diabetes were identified from a population-based dataset during 2004–2017 in Tasmania, Australia. An interactive map visualising geographic distribution of diabetes prevalence, mortality rates, and healthcare costs in people with diabetes was generated. The cluster and outlier analysis was performed based on statistical area level 2 (SA2) to identify areas with high (hot spot) and low (cold spot) diabetes burden. Results: There were geographic variations in diabetes burden across Tasmania, with highest age-adjusted prevalence (6.1%), excess cost ($2627), and annual costs per person ($5982) in the West and Northwest. Among 98 SA2 areas, 16 hot spots and 25 cold spots for annual costs, and 10 hot spots and 10 cold spots for diabetes prevalence were identified (p<0.05). 15/16 (94%) and 6/10 (60%) hot spots identified were in the West and Northwest. Conclusions: We have developed a method to graphically display important diabetes outcomes for different geographical areas. Implications for Public Health: The method presented in our study could be applied to any other diseases, regions, and countries where appropriate data are available to identify areas where interventions are needed to improve diabetes outcomes. Key words: diabetes, data linkage, geospatial mapping, prevalence, mortality, costs