Type of Refugee Accommodation and Health of Residents: A Cross-Sectional, Population-Based Cluster Analysis in South-West Germany

Int J Public Health. 2023 Sep 6:68:1605786. doi: 10.3389/ijph.2023.1605786. eCollection 2023.

Abstract

Objectives: Few studies have assessed whether refugees' health is associated with accommodation characteristics. We aimed to devise a typology of refugee accommodation based on variables on the accommodation and its physical context before assessing its association with health in multivariate analyses. Methods: We performed a cluster analysis based on a hierarchal, agglomerative clustering algorithm using Euclidean Distance and Ward's method. We analysed accommodation clusters based on number of inhabitants, degree of housing deterioration, urbanity of location (urban/rural distinction), and remoteness (walking distance to shops, medical or administrative services). In total, we analysed health and accommodation data of 412 refugees and asylum seekers from 58 different accommodation facilities in the federal state of Baden-Württemberg in the south-west of Germany. Results: Accommodations with a moderate occupation, lowest levels of deterioration, and a central urban location showed the best health outcomes in terms of subjective general health status, depression, and generalized anxiety disorder (GAD). Associations were strongest for GAD and weakest for depression. Conclusion: Our findings inform policymakers on layout and location of refugee collective accommodation centres.

Keywords: accommodation; asylum seekers; mental health; neighbourhoods; refugees.

MeSH terms

  • Algorithms
  • Cluster Analysis
  • Cross-Sectional Studies
  • Germany
  • Humans
  • Refugees*

Grants and funding

The primary data collection was funded by the German Federal Ministry for Education and Research (BMBF) in the scope of the project RESPOND (Grant Number: 01GY1611). The study was realised with funding of the German Science Foundation (DFG) in the scope of the Research Unit PH-LENS (FOR 2928), subprojects DEPRIV (409654512) and NEXUS (GZ: BO 5233/1-1). AM acknowledges financial support by the Else Kröner-Fresenius-Stiftung (2017_Promotionskolleg.08) within the Heidelberg Graduate School of Global Health. The funders had no influence on study design, analysis, or decision to publish. We acknowledge the financial support of the Open Access Publication Fund of Bielefeld University for the article processing charge.