Feasibility study of geospatial mapping of chronic disease risk to inform public health commissioning.

BMJ Open
Douglas NobleTrisha Greenhalgh

Abstract

To explore the feasibility of producing small-area geospatial maps of chronic disease risk for use by clinical commissioning groups and public health teams. Cross-sectional geospatial analysis using routinely collected general practitioner electronic record data. Tower Hamlets, an inner-city district of London, UK, characterised by high socioeconomic and ethnic diversity and high prevalence of non-communicable diseases. The authors used type 2 diabetes as an example. The data set was drawn from electronic general practice records on all non-diabetic individuals aged 25-79 years in the district (n=163 275). The authors used a validated instrument, QDScore, to calculate 10-year risk of developing type 2 diabetes. Using specialist mapping software (ArcGIS), the authors produced visualisations of how these data varied by lower and middle super output area across the district. The authors enhanced these maps with information on examples of locality-based social determinants of health (population density, fast food outlets and green spaces). Data were piloted as three types of geospatial map (basic, heat and ring). The authors noted practical, technical and information governance challenges involved in producing the maps. Usable data...Continue Reading

Citations

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Nov 7, 2015·Royal Society Open Science·Jannah BakerKerrie Mengersen
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Software Mentioned

Excel
GIS
Adobe Illustrator
ArcGIS
QDScore
EMIS
STATA

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