Open Access
CC BY 4.0 · Psychother Psychosom Med Psychol
DOI: 10.1055/a-2763-8046
Originalarbeit

Erkrankungsprävalenzen und Leistungsunfähigkeit von Menschen in Arbeitslosigkeit in Deutschland

Eine Analyse der Daten des Ärztlichen Dienstes 2016–2021Prevalence and socio-medical performance among unemployed people in GermanyAnalysis of data of the Medical Service of the Federal Employment Agency

Authors

  • Andreas Guenter Franke

    1   Fachbereich Beratungswissenschaften, Hochschule der Bundesagentur für Arbeit, Mannheim
    1   Fachbereich Beratungswissenschaften, Hochschule der Bundesagentur für Arbeit, Mannheim
  • Kirsi Manz

    3   Klinik für Hämatologie, Hämostaseologie, Onkologie und Stammzellentransplantation, Medizinische Hochschule Hannover
  • Norbert Scherbaum

    4   LVR-Universitätsklinik Essen, Klinik für Psychiatrie und Psychotherapie, Medizinische Fakultät, Universität Duisburg-Essen, Essen
  • Claudia Pieper

    5   Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen
  • Patrik Roser

    4   LVR-Universitätsklinik Essen, Klinik für Psychiatrie und Psychotherapie, Medizinische Fakultät, Universität Duisburg-Essen, Essen
  • Gabriele Lotz-Metz

    6   Ärztlicher Dienst, Bundesagentur für Arbeit, Nürnberg

Zusammenfassung

Einleitung

Seit langem ist der grundsätzliche Zusammenhang zwischen Arbeitslosigkeit (ALO) und gesundheitlichen Beeinträchtigungen bekannt. Dabei stellen sich Fragen nach den häufigsten Erkrankungen unter Menschen in ALO sowie darauf basierende (etwaige) Leistungseinbußen. Ziel der Studie ist es, die 20 häufigsten Erkrankungen von im Ärztlichen Dienst (ÄD) der Bundesagentur für Arbeit (BA) untersuchten Menschen in ALO darzustellen sowie (etwaige) darauf basierende Leistungseinbußen für den (allgemeinen) Arbeitsmarkt und weitere assoziierte Faktoren zu analysieren.

Methoden

Für die vorliegende mehrjährige Querschnittsstudie (2016–2021) wurden die 20 häufigsten Erkrankungen/ Diagnosen aller (n=4 249 028) sozialmedizinischer Begutachtungen des ÄD der BA mit den jeweiligen Erst- und Zweitdiagnosen auf der Basis von ICD-10-Codes sowie damit assoziierte Faktoren (Geschlecht, Alter, Leistungsbild) aus Datenbanken des ÄD analysiert. Zur Analyse der Daten wurde neben deskriptiver Statistik binäre logistische Regression genutzt.

Ergebnisse

Von den jährlich rund 500 000 im ÄD begutachteten KundInnen erhielten nahezu alle (2016: 90,1%; 2021: 99,5%) eine Erstdiagnose. Von den 20 häufigsten Diagnosen stammt die Hälfte aus dem Bereich der psychischen Erkrankungen. Am häufigsten wurden depressive Episoden (n=416 531; 10,2%), rezidivierend depressive Störungen (n=415 651; 10,1%) und (andere) Angststörungen (n=169 112; 4,6%) diagnostiziert. Bei den nicht-psychiatrischen Störungen belegen Rückenschmerzen (n=243 389; 6,6%), essentielle Hypertonien (n=146 316; 4,0%) und (sonstige) Bandscheibenschäden (n=91 861; 2,2%) die ersten drei Plätze. Alter und Geschlecht differieren je nach Erkrankung signifikant. Insgesamt wurden 33,9% aller begutachteten Personen als leistungsunfähig (<3 Std./Tag) eingestuft, wobei psychische Erkrankungen den häufigsten Grund dafür darstellen, dabei am häufigsten mit 63,6% Schizophrenien.

Diskussion

Psychische Erkrankungen sind unter von ALO betroffenen Menschen besonders häufig. Dies sollte bei der ärztlichen Versorgung sowie der Arbeitsmarktintegration Beachtung finden. Die Vernetzung von arbeitsmarktlichen und gesundheitlichen und insbesondere psychiatrischen Hilfen scheint sinnvoll, um psychische Erkrankungen und ALO möglichst rasch und nachhaltig zu überwinden. Stichworte: Arbeitslosigkeit, Erkrankungen, Epidemiologie, Leistungsunfähigkeit, Langzeitarbeitslosigkeit

Abstract

Introduction

The fundamental association between unemployment and health problems has long been recognized. This raises questions about the most common illnesses among unemployed people and any resulting loss of productivity. The aim of the study is to present the 20 most common illnesses among unemployed people examined by the Medical Service (ÄD) of the Federal Employment Agency (BA) and to analyze any resulting loss of productivity for the (general) labor market and other associated factors.

Methods

For this multi-year cross-sectional study study (2016–2021), the 20 most common diseases/ diagnoses from all (n=4,249,028) social medical assessments conducted by the Medical Service (ÄD) of the Federal Employment Agency were analyzed, along with the respective primary and secondary diagnoses based on ICD-10 codes and associated factors (gender, age, performance profile) from the ÄD databases. For data analyses descriptive statistics and binary logistic regression were used.

Results

Of the approximately 500,000 social medical assessments carried out by the MS each year, nearly all clients (2016: 90.1%; 2021: 99.5%) received a diagnosis. Depressive episodes (n=416,531; 10.2%), recurrent depressive disorders (n=415,651; 10.1%) and (other) anxiety disorders (n=169,112; 4.6%) belong to the most frequent diagnoses. Among the non-psychiatric disorders, back pain (n=243,389; 6.6%), (primary) hypertension (n=146,316; 4.0%) and (other) disc damage (n=91,861; 2.2%) occupy the top three places. Age and gender differed significantly depending on the disease. Overall, 33.9% of all assessed clients were classified as incapacitated (<3 hours/day), with mental illnesses being the most common reason for this, with schizophrenia being the most common at 63.6%).

Discussion

Mental disorders are particularly common among people who are unemployed. This should be taken into account in medical care and labor market integration to overcome both: unemployment and (psychiatric) illness. Keywords: Unemployment, illnesses, epidemiology, inability to work, long term unemployment



Publication History

Received: 15 May 2025

Accepted: 19 November 2025

Article published online:
27 January 2026

© 2026. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/).

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

 
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