Spatio-temporal analysis of the risk of depression at district-level and association with greenness based on the Heinz Nixdorf Recall Study

Spat Spatiotemporal Epidemiol. 2020 Jun:33:100340. doi: 10.1016/j.sste.2020.100340. Epub 2020 Mar 20.

Abstract

In urban health studies where spatial and temporal changes are of importance, spatio-temporal variations are usually neglected. For the Heinz Nixdorf Recall Study, we investigate spatio-temporal variation in analyses of effects of urban greenness on depression by including spatio-temporal random effect terms in a Poisson model on district level. Our results show negative associations between greenness and depression. The findings suggest strong temporal autocorrelation and weak spatial effects. Even if the weak spatial effects are suggestive of neglecting them, as in our case, spatio-temporal random effects should be taken into account to provide reliable inference in urban health studies.

Keywords: Conditional autoregressive; Depression; Greenness; Spatio-temporal autocorrelation.

MeSH terms

  • Cohort Studies
  • Depressive Disorder / epidemiology*
  • Environment Design / statistics & numerical data*
  • Germany / epidemiology
  • Humans
  • Parks, Recreational / statistics & numerical data*
  • Risk Assessment
  • Spatio-Temporal Analysis*
  • Urban Population / statistics & numerical data*