Psychological distress among refugees in Germany: a cross-sectional analysis of individual and contextual risk factors and potential consequences for integration using a nationally representative survey

Abstract

Objectives: Responding to the mental health needs of refugees remains a pressing challenge worldwide. We estimated the prevalence of psychological distress in a large refugee population in Germany and assessed its association with host country factors amenable to policy intervention and integration indicators.

Design: A cross-sectional and population-based secondary analysis of the 2017 wave of the IAB-BAMF-SOEP refugee survey.

Setting: Germany.

Participants: 2639 adult refugees who arrived in Germany between 2013 and 2016.

Main outcome measures: Psychological distress involving symptoms of depression, anxiety and post-traumatic stress disorder was measured using the Refugee Health Screener-13.

Results: Almost half of the population surveyed (41.2% (95% CI: 37.9% to 44.6%)) was affected by mild, moderate or severe levels of psychological distress. 10.9% (8.4% to 13.5%) of the population screened positive for severe distress indicative of an urgent need for care. Prevalence of distress was particularly high for females (53.0% (47.2% to 58.8%)), older refugees (aged ≥55, 70.4% (58.5% to 82.2%)) and Afghans (61.5% (53.5% to 69.5%)). Individuals under threat of deportation were at a greater risk of distress than protection status holder (risk ratio: 1.55 (95% CI: 1.14 to 2.10)), single males at a greater risk than males with nuclear families living in Germany (1.34 (1.04 to 1.74)) and those in refugee housing facilities at a greater risk than those in private housing (1.21 (1.02 to 1.43)). Distressed males had a lower likelihood of employment (0.67 (0.52 to 0.86)) and reduced participation in integration courses (0.90 (0.81 to 0.99)). A trend of reduced participation in educational programmes was observed in affected females (0.42 (0.17 to 1.01)).

Conclusion: The finding that a substantial minority of refugees in Germany exhibits symptoms of distress calls for an expansion of mental health services for this population. Service providers and policy-makers should consider the increased prevalence among female, older and Afghan refugees, as well as among single males, residents in housing facilities and those under threat of deportation. The associations between mental health and integration processes such as labour market, educational programme and integration course participation also warrant consideration.

Keywords: epidemiology; mental health; public health.

Figure 1

The association between postmigration factors and psychological distress. Risk ratio (RR) estimates and 95% CIs from nine separate modified poisson regression models predicting positive screens for psychological distress (cut-off used: 11 points on the RHS-13) from a) legal status (reference category: ‘Protected since 2016’), b) nuclear family situation (reference category: ‘All Nuclear Family Members in Germany’; data from 2016, since there was no information on children in second wave), c) housing type (reference category: ‘Private Housing’), respectively, stratified and non-stratified by gender, adjusted for gender (when non-stratified), age, nationality, level of education and year of arrival in Germany. For the legal status regression, we omitted the non-significant results for the ‘Other’ category, whose legal meaning is unknown, for the sake of clarity. Results are pooled from 50 multiply imputed datasets and weighted. For complete regression results, please see online supplementary tables S5.

Figure 2

The association between psychological distress and indicators of integration. Risk ratio (RR) estimates and 95% CIs from nine separate modified poisson regression models predicting current employment (binary), currently being in education (binary) and course participation (binary) from psychological distress screening status (reference category: ‘Negative Screen’, cut-off used: 11 points on the RHS-13), respectively, stratified and non-stratified by gender, adjusted for gender (when non-stratified), age, nationality, level of education and year of arrival in Germany. Results are pooled from 50 multiply imputed datasets and weighted. For complete regression results, please see online supplementary table S6.