Creating a Web-Based Interactive Map Visualising the Geographic Variations of the Burden of Diabetes to Inform Policymaking: An Example From Tasmania, Australia

OBJECTIVES: With Tasmania, a state of Australia as an example, our study aimed to use mapping in combination with statistical analyses 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. An interactive map visualising geographic distribution of diabetes prevalence, annual costs, and mortality rates in people with diabetes was generated. The Getis-Ord Gi* method was performed based on statistical area level 2 to identify areas with high (hot spot) and low (cold spot) diabetes burden. Fisher’s exact test was conducted to investigate the association of hot/cold spots and Index of Relative Socio-economic Disadvantage (IRSD) quintiles.

RESULTS: There were geographic variations in diabetes burden across Tasmania, with highest age-adjusted prevalence (6.1%-based on the Australian population in 2017), mortality rates (20.7/10,000 people), and annual costs per person (AUD 5982) in the West and Northwest. Among 98 areas, 23 hot spots and 41 cold spots for annual costs, 14 hot spots and 11 cold spots for diabetes prevalence were identified (p<0.1). 21/23 (91%) and 9/14 (64%) hot spots identified are in the West and Northwest. The map indicated similar distribution of hot clusters and IRSD level 1 areas (most disadvantaged) as well as cold clusters and IRSD level 5 areas (least disadvantaged). Fisher’s exact test demonstrated an association between hot/cold spots and IRSD quintiles (p=0.01 and p=0.002, respectively).

CONCLUSIONS: We have developed a method to graphically display important diabetes outcomes for different geographical areas. The method presented in our study can be applied to any other regions and countries to identify areas where interventions are needed to support evidence-based policymaking as well as enhance community’s awareness.