Affiliations: Research School of Population Health, ANU College of Medicine, Biology and Environment, The Australian National University, Canberra, Australia
Correspondence:
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Correspondence to: Nasser Bagheri, Research School of Population Health, ANU College of Medicine, Biology and Environment, The Australian National University, Building 63, Mills Road, Acton ACT 2601, Canberra, Australia. Tel.: +61 02 6125 9564; E-mail: [email protected].
Abstract: We have a poor understanding of whether dementia clusters geographically, how this occurs, and how dementia may relate to socio-demographic factors. To shed light on these important questions, this study aimed to compute a dementia risk score for individuals to assess spatial variation of dementia risk, identify significant clusters (hotspots), and explore their association with socioeconomic status. We used clinical records from 16 general practices (468 Statistical Area level 1 s, N = 14,746) from the city of west Adelaide, Australia for the duration of 1 January 2012 to 31 December 2014. Dementia risk was estimated using The Australian National University-Alzheimer’s Disease Risk Index. Hotspot analyses were applied to examine potential clusters in dementia risk at small area level. Significant hotspots were observed in eastern and southern areas while coldspots were observed in the western area within the study perimeter. Additionally, significant hotspots were observed in low socio-economic communities. We found dementia risk scores increased with age, sex (female), high cholesterol, no physical activity, living alone (widow, divorced, separated, or never married), and co-morbidities such as diabetes and depression. Similarly, smoking was associated with a lower dementia risk score. The identification of dementia risk clusters may provide insight into possible geographical variations in risk factors for dementia and quantify these risks at the community level. As such, this research may enable policy makers to tailor early prevention strategies to the correct individuals within their precise locations.
Keywords: Dementia, dementia risk score tools, general practice data, geospatial analysis, hotspots, spatial variation
