gms | German Medical Science

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH)

08.09. - 13.09.2024, Dresden

Common symptoms and post-COVID associated symptoms in Germany – results from the NAKO study

Meeting Abstract

  • Sophie Diexer - Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany
  • Oliver Purschke - Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany
  • Julia Fricke
  • Peter Ahnert - Universität Leipzig, Leipzig, Germany
  • Sabine Gabrysch
  • Cornelia Gottschick - Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany
  • Barbara Bohn - NAKO e.V., Heidelberg, Germany
  • Hermann Brenner - German Cancer Research Centre (DKFZ), Heidelberg, Germany
  • Christoph Buck - Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Bremen, Germany
  • Stefanie Castell - Helmholtz-Zentrum für Infektionsforschung, Braunschweig, Germany
  • Sylvia Gastell - Deutsches Institut für Ernährungsforschung, Nuthetal, Germany
  • Karin Halina Greiser - Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • Volker Harth - Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
  • Jana-Kristin Heise - Helmholtz-Zentrum für Infektionsforschung, Braunschweig, Germany
  • Bernd Holleczek - Krebsregister Saarland, Saarbrücken, Germany
  • Rudolf Kaaks - Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • Lilian Krist - Charité – Universitätsmedizin Berlin, Berlin, Germany
  • Michael F. Leitzmann - Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
  • Claudia Meinke-Franze
  • Karin B. Michels - Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
  • Ilais Moreno - Max-Delbrueck-Centre for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
  • Nadia Obi - Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
  • Leo Panreck - NAKO e.V., Heidelberg, Germany
  • Annette Peters - Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
  • Tobias Pischon - Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
  • Tamara Schikowski - IUF – Leibniz-Institut für umweltmedizinische Forschung GmbH, Düsseldorf, Germany
  • Börge Schmidt - Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital of Essen (AöR), Essen, Germany
  • Marie Standl
  • Andreas Stang - Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Essen, Germany
  • Henry Völzke - Institut für Community Medicine, Abteilung Study of Health in Pomerania – Klinisch-epidemiologische Forschung (SHIP-KEF), Universitätsmedizin Greifswald, Greifswald, Germany
  • Andrea Weber - Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
  • Hajo Zeeb - Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Abteilung Prävention und Evaluation, Bremen, Germany
  • André Karch - Westfälische Wilhelms-Universität Münster, Münster, Germany
  • Rafael Mikolajczyk - Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH). Dresden, 08.-13.09.2024. Düsseldorf: German Medical Science GMS Publishing House; 2024. DocAbstr. 556

doi: 10.3205/24gmds341, urn:nbn:de:0183-24gmds3410

Veröffentlicht: 6. September 2024

© 2024 Diexer et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Introduction: A Post-COVID-19 condition (PCC) can be a substantial burden for those affected. However, symptoms linked to PCC are also common in the general population independent of SARS-CoV-2 infection. We aimed to compare the current symptom burden among those who reported having symptoms 4 to 12 months after a SARS-CoV-2 infection (defined as PCC) with two other groups: individuals who reported no infection and individuals who reported a SARS-CoV-2 infection, but no symptoms 4-12 months after infection.

Methods: Participants of the German National Cohort (NAKO) were invited to participate in an online survey from September to December 2022. The participants were asked about their current health status and symptoms they were experiencing. Additionally, they were asked to provide information on SARS-CoV-2 infections and symptoms following infection. We defined PCC as having at least one out of 20 self-reported symptoms 4-12 months post-infection. We compared number of current symptoms among three groups: 1) no reported SARS-CoV-2 infection, 2) reported SARS-CoV-2 infection but no symptoms after infection, and 3) reported infection and symptoms after infection (PCC). We used logistic regression to investigate the association of the number of symptoms and being classified as PCC with the current health status (poor and fair vs. good to excellent).

Results: Of 110,375 responders (73% response), 92,456 had complete data and were considered for this analysis. 44,451 (48%) did not report an infection (no infection), 29,921 (32%) reported an infection but no symptoms qualifying for PCC (infection and no PCC), leaving 18,084 (20%), who reported symptoms after infection (PCC). The mean number of symptoms at the time of the survey for the ‘no infection’ group was 3.3, for the ‘infection and no PCC’ group 2.5 and for the PCC group 6.2. Women had on average 4.3 symptoms, while men had 3. A higher number of symptoms was associated with a poorer current health status (Odds Ratio = 1.43, 95% Confidence Interval: 1.43; 1.44 per one symptom increase) after adjusting for age and sex. Per 10 years of age the odds of a poorer health status increased by 1.35 (1.33; 1.38).

Conclusion: While symptoms linked to PCC were also present among those with no SARS-CoV-2 infection and those who have had an infection, the number of symptoms was nearly twice as high among those who developed PCC after infection. There is a strong association between the number of symptoms and a poorer health status.

The authors declare that they have no competing interests.

The authors declare that a positive ethics committee vote has been obtained.