Spatial characterization of hypertension clusters using a rural Australian clinical database

Rachel Whitsed, Ana Horta, Herbert F. Jelinek, Faezeh Marzbanrad

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Abstract

This study aimed to characterize the spatial distribution of hypertension (HT) clusters in a rural Australian city using self-reported HT data collected at a local health-screening clinic. HT status was recorded for 515 self-selected participants in a free health-screening program in Albury, New South Wales, Australia. We compared predictions of HT clusters computed using spatial scan statistic and Generalised Additive Model (GAM). We then implemented a new approach incorporating sensitivity analysis in GAM to combine cluster predictions at multiple span sizes. A statistically significant cluster for HT was identified in Albury centered to the north of the main urban center, with relative risk up to 2.29. The sensitivity analysis confirmed the cluster location and highlighted other potential HT clusters. Our approach allows detection of irregularly-shaped disease clusters and highlights potential clusters that may be overlooked using traditional methods. This is important in cases using local, small datasets where regularly-shaped or overly smoothed disease clusters may not provide enough detail to be suitable for targeting place-based interventions.

Original languageEnglish
Title of host publication2017 Computing in Cardiology (CinC 2017)
EditorsChristine Pickett, Cristiana Corsi, Pablo Laguna, Rob MacLeod
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-4
Number of pages4
Volume44
ISBN (Electronic)9781538666302
ISBN (Print)9781538645550
DOIs
Publication statusPublished - 1 Jan 2017
EventComputing in Cardiology Conference 2017 - Rennes, France
Duration: 24 Sep 201727 Sep 2017

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861

Conference

ConferenceComputing in Cardiology Conference 2017
Abbreviated titleCINC 2017
CountryFrance
CityRennes
Period24/09/1727/09/17

Cite this

Whitsed, R., Horta, A., Jelinek, H. F., & Marzbanrad, F. (2017). Spatial characterization of hypertension clusters using a rural Australian clinical database. In C. Pickett, C. Corsi, P. Laguna, & R. MacLeod (Eds.), 2017 Computing in Cardiology (CinC 2017) (Vol. 44, pp. 1-4). (Computing in Cardiology). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.22489/CinC.2017.327-065