Modelling the spatial risk pattern of dementia in Denmark using residential location data: A registry-based national cohort

Prince M. Amegbor*, Clive E. Sabel, Laust H. Mortensen, Amar J. Mehta

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Dementia is a major global public health concern that is increasingly leading to morbidity and mortality among older adults. While studies have focused on the risk factors and care provision, there is currently limited knowledge about the spatial risk pattern of the disease. In this study, we employ Bayesian spatial modelling with a stochastic partial differential equation (SPDE) approach to model the spatial risk using complete residential history data from the Danish population and health registers. The study cohort consisted of 1.6 million people aged 65 years and above from 2005 to 2018. The results of the spatial risk map indicate high-risk areas in Copenhagen, southern Jutland and Funen. Individual socioeconomic factors and population density reduce the intensity of high-risk patterns across Denmark. The findings of this study call for the critical examination of the contribution of place of residence in the susceptibility of the global ageing population to dementia.

Original languageEnglish
Article number100643
JournalSpatial and Spatio-temporal Epidemiology
Volume49
DOIs
Publication statusPublished - Jun 2024

ASJC Scopus subject areas

  • Epidemiology
  • Geography, Planning and Development
  • Infectious Diseases
  • Health, Toxicology and Mutagenesis

Keywords

  • Bayesian spatial modelling
  • Contextual factors
  • Dementia
  • Socioeconomic factors
  • Stochastic partial differential equation (SPDE)

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