[Fatigue in the general population: results of the "German Health Update 2023" study].

Christina Poethko-M��ller, Angelika Schaffrath Rosario, Giselle Sarganas, Ana Ordonez Cruickshank, Christa Scheidt-Nave, Robert Schlack
Author Information
  1. Christina Poethko-M��ller: Abt. Epidemiologie und Gesundheitsmonitoring, FG K��rperliche Gesundheit, Robert Koch-Institut, General-Pape-Str. 62-66, 12101, Berlin, Deutschland. Poethko-MuellerC@rki.de.
  2. Angelika Schaffrath Rosario: Abt. Epidemiologie und Gesundheitsmonitoring, FG Gesundheitsberichterstattung, Robert Koch-Institut, Berlin, Germany.
  3. Giselle Sarganas: Abt. Epidemiologie und Gesundheitsmonitoring, FG K��rperliche Gesundheit, Robert Koch-Institut, General-Pape-Str. 62-66, 12101, Berlin, Deutschland.
  4. Ana Ordonez Cruickshank: Abt. Epidemiologie und Gesundheitsmonitoring, FG K��rperliche Gesundheit, Robert Koch-Institut, General-Pape-Str. 62-66, 12101, Berlin, Deutschland.
  5. Christa Scheidt-Nave: Abt. Epidemiologie und Gesundheitsmonitoring, FG K��rperliche Gesundheit, Robert Koch-Institut, General-Pape-Str. 62-66, 12101, Berlin, Deutschland.
  6. Robert Schlack: Abt. Epidemiologie und Gesundheitsmonitoring, FG Psychische Gesundheit, Robert Koch-Institut, Berlin, Germany.

Abstract

BACKGROUND: Fatigue is an unspecific symptom complex characterized by tiredness, lack of energy, and lack of concentration and is of considerable public health relevance, due to its links with incapacity for work, risk of accidents, and increased need for healthcare.
METHODS: The analyses are based on data from 9766 adults of the telephone survey "Gesundheit in Deutschland aktuell (GEDA)" 2023. Fatigue was recorded using the Fatigue Assessment Scale (FAS), a validated instrument with 10 questions for self-assessment of fatigue. The scale was dichotomized into yes (at least mild to moderate fatigue) versus no (no fatigue). Population-weighted prevalences of fatigue and associated sociodemographic and health-related factors were calculated in descriptive analyses and multivariable Poisson regression.
RESULTS: The overall prevalence of fatigue in adults in Germany is 29.7% (95% CI 28.1-31.2), is highest in 18- to 29-year-olds (39.6% (95% CI 35.0-44.4)), and decreases in the age groups up to 65-79 years (20.6% (95% CI 18.2-23.3)). It is higher again in the very old age group (33.2% (95% CI 28.9-37.7)). Women have a higher risk of fatigue than men (aRR 1.19 (95% CI 1.08-1.32)). Fatigue is significantly associated with age, lower education, chronic illness, depression, and long COVID, regardless of covariates.
DISCUSSION: GEDA 2023 is one of the few population-based studies to have collected data on fatigue. The results allow estimates to be made for Germany on the frequency of fatigue and the significance of physical, psychological, and social influencing factors. They can be used as a reference or as a basis for trends over time as part of continuous health monitoring in Germany.

Keywords

References

  1. Chen MK (1986) The epidemiology of self-perceived fatigue among adults. Prev Med 15:74���81. https://doi.org/10.1016/0091-7435(86)90037-x [DOI: 10.1016/0091-7435(86)90037-x]
  2. Landmark-Hoyvik H, Reinertsen KV, Loge JH et al (2010) The genetics and epigenetics of fatigue. PM R 2:456���465. https://doi.org/10.1016/j.pmrj.2010.04.003 [DOI: 10.1016/j.pmrj.2010.04.003]
  3. Maisel P, Baum E, Donner-Banzhoff N (2021) Fatigue as the Chief Complaint-Epidemiology, Causes, Diagnosis, and Treatment. Dtsch ��rztebl Int 118:566���576. https://doi.org/10.3238/arztebl.m2021.0192 [DOI: 10.3238/arztebl.m2021.0192]
  4. Mota DD, Pimenta CA (2006) Self-report instruments for fatigue assessment: a systematic review. Res Theory Nurs Pract 20:49���78. https://doi.org/10.1891/rtnp.20.1.49 [DOI: 10.1891/rtnp.20.1.49]
  5. Estevez-Lopez F, Mudie K, Wang-Steverding X et al (2020) Systematic Review of the Epidemiological Burden of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Across Europe: Current Evidence and EUROMENE Research Recommendations for Epidemiology. J Clin Med. https://doi.org/10.3390/jcm9051557 [DOI: 10.3390/jcm9051557]
  6. Yoon JH, Park NH, Kang YE, Ahn YC, Lee EJ, Son CG (2023) The demographic features of fatigue in the general population worldwide: a systematic review and meta-analysis. Front Public Health 11:1192121. https://doi.org/10.3389/fpubh.2023.1192121 [DOI: 10.3389/fpubh.2023.1192121]
  7. Yoo EH, Choi ES, Cho SH, Do JH, Lee SJ, Kim JH (2018) Comparison of Fatigue Severity and Quality of Life between Unexplained Fatigue Patients and Explained Fatigue Patients. Korean J Fam Med 39:180���184. https://doi.org/10.4082/kjfm.2018.39.3.180 [DOI: 10.4082/kjfm.2018.39.3.180]
  8. Basu N, Yang X, Luben RN et al (2016) Fatigue is associated with excess mortality in the general population: results from the EPIC-Norfolk study. BMC Med 14:122. https://doi.org/10.1186/s12916-016-0662-y [DOI: 10.1186/s12916-016-0662-y]
  9. Ricci JA, Chee E, Lorandeau AL, Berger J (2007) Fatigue in the U.S. workforce: prevalence and implications for lost productive work time. J Occup Environ Med 49:1���10. https://doi.org/10.1097/01.jom.0000249782.60321.2a [DOI: 10.1097/01.jom.0000249782.60321.2a]
  10. Swaen GMH, van Amelsvoort LGPM, B��ltmann U, Kant IJ (2003) Fatigue as a risk factor for being injured in an occupational accident: results from the Maastricht Cohort Study. Occup Environ Med 60:88���92 [DOI: 10.1136/oem.60.suppl_1.i88]
  11. Elnegaard S, Andersen RS, Pedersen AF et al (2015) Self-reported symptoms and healthcare seeking in the general population���exploring ���The Symptom Iceberg���. BMC Public Health 15:685. https://doi.org/10.1186/s12889-015-2034-5 [DOI: 10.1186/s12889-015-2034-5]
  12. O���Mahoney LL, Routen A, Gillies C et al (2023) The prevalence and long-term health effects of Long Covid among hospitalised and non-hospitalised populations: A systematic review and meta-analysis. EClinicalMedicine 55:101762. https://doi.org/10.1016/j.eclinm.2022.101762 [DOI: 10.1016/j.eclinm.2022.101762]
  13. Poole-Wright K, Guennouni I, Sterry O, Evans RA, Gaughran F, Chalder T (2023) Fatigue outcomes following COVID-19: a systematic review and meta-analysis. BMJ Open 13:e63969. https://doi.org/10.1136/bmjopen-2022-063969 [DOI: 10.1136/bmjopen-2022-063969]
  14. Azzam A, Khaled H, Refaey N et al (2024) The burden of persistent symptoms after COVID-19 (long COVID): a meta-analysis of controlled studies in children and adults. Virol J 21:16. https://doi.org/10.1186/s12985-024-02284-3 [DOI: 10.1186/s12985-024-02284-3]
  15. Galland-Decker C, Marques-Vidal P, Vollenweider P (2019) Prevalence and factors associated with fatigue in the Lausanne middle-aged population: a population-based, cross-sectional survey. BMJ Open 9:e27070. https://doi.org/10.1136/bmjopen-2018-027070 [DOI: 10.1136/bmjopen-2018-027070]
  16. Lerdal A, Wahl A, Rustoen T, Hanestad BR, Moum T (2005) Fatigue in the general population: a translation and test of the psychometric properties of the Norwegian version of the fatigue severity scale. Scand J Public Health 33:123���130. https://doi.org/10.1080/14034940410028406 [DOI: 10.1080/14034940410028406]
  17. Loge JH, Ekeberg O, Kaasa S (1998) Fatigue in the general Norwegian population: normative data and associations. J Psychosom Res 45:53���65. https://doi.org/10.1016/s0022-3999(97)00291-2 [DOI: 10.1016/s0022-3999(97)00291-2]
  18. Chalder T, Berelowitz G, Pawlikowska T et al (1993) Development of a fatigue scale. J Psychosom Res 37:147���153. https://doi.org/10.1016/0022-3999(93)90081-p [DOI: 10.1016/0022-3999(93)90081-p]
  19. Martin A, Chalder T, Rief W, Braehler E (2007) The relationship between chronic fatigue and somatization syndrome: A general population survey. J Psychosom Res 63:147���156. https://doi.org/10.1016/j.jpsychores.2007.05.007 [DOI: 10.1016/j.jpsychores.2007.05.007]
  20. Beutel ME, Klein EM, Henning M et al (2020) Somatic Symptoms in the German General Population from 1975 to 2013. Sci Rep 10:1595. https://doi.org/10.1038/s41598-020-58602-6 [DOI: 10.1038/s41598-020-58602-6]
  21. Allen JB, Damerow SS (2021) Gesundheit in Deutschland aktuell (GEDA 2019/2020-EHIS) ��� Hintergrund und Methodik. J Health Monit 6:72���87. https://doi.org/10.25646/8558 [DOI: 10.25646/8558]
  22. von der Heyde C (2013) Das ADM-Stichprobensystem f��r Telefonbefragungen. https://www.gessgroup.de/wp-content/uploads/2016/09/Beschreibung-ADM-Telefonstichproben_DE-2013.pdf . Zugegriffen: 18. M��rz 2024
  23. American Association for Public Opinion Research (AAPOR) (2016) Final Dispositions of Case Codes and Outcome Rates for Surveys. 9th edition. In, Deerfield. https://aapor.org/wp-content/uploads/2022/11/Standard-Definitions20169theditionfinal.pdf . Zugegriffen: 19. M��rz 2024
  24. De Vries J, Michielsen HJ, Van Heck GL (2003) Assessment of fatigue among working people: a comparison of six questionnaires. Occup Environ Med 60(1):i10���i15. https://doi.org/10.1136/oem.60.suppl_1.i10 [DOI: 10.1136/oem.60.suppl_1.i10]
  25. de Kleijn WP, De Vries J, Wijnen PA, Drent M (2011) Minimal (clinically) important differences for the Fatigue Assessment Scale in sarcoidosis. Respir Med 105:1388���1395. https://doi.org/10.1016/j.rmed.2011.05.004 [DOI: 10.1016/j.rmed.2011.05.004]
  26. Hendriks C, Drent M, Elfferich M, De Vries J (2018) The Fatigue Assessment Scale: quality and availability in sarcoidosis and other diseases. Curr Opin Pulm Med 24:495���503. https://doi.org/10.1097/MCP.0000000000000496 [DOI: 10.1097/MCP.0000000000000496]
  27. Michielsen HJ, De Vries J, Van Heck GL (2003) Psychometric qualities of a brief self-rated fatigue measure: The Fatigue Assessment Scale. J Psychosom Res 54:345���352. https://doi.org/10.1016/s0022-3999(02)00392-6 [DOI: 10.1016/s0022-3999(02)00392-6]
  28. Berentschot JC, Drexhage HA, Aynekulu Mersha DG et al (2023) Immunological profiling in long COVID: overall low grade inflammation and T���lymphocyte senescence and increased monocyte activation correlating with increasing fatigue severity. Front Immunol 14:1254899. https://doi.org/10.3389/fimmu.2023.1254899 [DOI: 10.3389/fimmu.2023.1254899]
  29. Davis HE, Assaf GS, McCorkell L et al (2021) Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. EClinicalMedicine 38:101019. https://doi.org/10.1016/j.eclinm.2021.101019 [DOI: 10.1016/j.eclinm.2021.101019]
  30. Hussain N, Samuelsson CM, Drummond A, Persson CU (2022) Prevalence of fatigue at one-year follow-up from the Gothenburg recovery and rehabilitation after COVID-19 and intensive care unit study. Sci Rep 12:11501. https://doi.org/10.1038/s41598-022-14787-6 [DOI: 10.1038/s41598-022-14787-6]
  31. Peter RS, Nieters A, Kr��usslich H���G et al (2022) Post-acute sequelae of covid-19 six to 12 months after infection: population based study. BMJ 379:e71050. https://doi.org/10.1136/bmj-2022-071050 [DOI: 10.1136/bmj-2022-071050]
  32. Schmidbauer L, Kirchberger I, Gosslau Y et al (2023) The association between the number of symptoms and the severity of Post-COVID-Fatigue after SARS-CoV���2 infection treated in an outpatient setting. J Neurol 270:3294���3302. https://doi.org/10.1007/s00415-023-11752-9 [DOI: 10.1007/s00415-023-11752-9]
  33. Zhao S (2024) Long COVID is associated with severe cognitive slowing. EClinicalMedicine. https://doi.org/10.1016/j.eclinm.2024.102434 [DOI: 10.1016/j.eclinm.2024.102434]
  34. Gorst SL, Seylanova N, Dodd SR et al (2023) Core outcome measurement instruments for use in clinical and research settings for adults with post-COVID-19 condition: an international Delphi consensus study. Lancet Respir Med 11:1101���1114. https://doi.org/10.1016/S2213���2600(23)00370���3 [DOI: 10.1016/S2213-2600(23)00370-3]
  35. Brauns HS, Steinmann SS (2003) The CASMIN educational classification in international comparativ research. In: Hoffmeyer-Zlotnik JWC (Hrsg) Advances in cross-national comparison. Kluwer, New York, S 221���244 [DOI: 10.1007/978-1-4419-9186-7_11]
  36. Pawlikowska T, Chalder T, Hirsch SR, Wallace P, Wright DJ, Wessely SC (1994) Population based study of fatigue and psychological distress. BMJ 308:763���766. https://doi.org/10.1136/bmj.308.6931.763 [DOI: 10.1136/bmj.308.6931.763]
  37. Furberg H, Olarte M, Afari N, Goldberg J, Buchwald D, Sullivan PF (2005) The prevalence of self-reported chronic fatigue in a US twin registry. J Psychosom Res 59:283���290. https://doi.org/10.1016/j.jpsychores.2005.05.008 [DOI: 10.1016/j.jpsychores.2005.05.008]
  38. Schwarz R, Krauss O, Hinz A (2003) Fatigue in the general population. Onkologie 26:140���144. https://doi.org/10.1159/000069834 [DOI: 10.1159/000069834]
  39. Junghaenel DU, Christodoulou C, Lai JS, Stone AA (2011) Demographic correlates of fatigue in the US general population: results from the patient-reported outcomes measurement information system (PROMIS) initiative. J Psychosom Res 71:117���123. https://doi.org/10.1016/j.jpsychores.2011.04.007 [DOI: 10.1016/j.jpsychores.2011.04.007]
  40. Engberg I, Segerstedt J, Waller G, Wennberg P, Eliasson M (2017) Fatigue in the general population-associations to age, sex, socioeconomic status, physical activity, sitting time and self-rated health: the northern Sweden MONICA study 2014. BMC Public Health 17:654. https://doi.org/10.1186/s12889-017-4623-y [DOI: 10.1186/s12889-017-4623-y]
  41. Hinz A, Ernst J, Glaesmer H et al (2017) Frequency of somatic symptoms in the general population: Normative values for the Patient Health Questionnaire-15 (PHQ-15). J Psychosom Res 96:27���31. https://doi.org/10.1016/j.jpsychores.2016.12.017 [DOI: 10.1016/j.jpsychores.2016.12.017]
  42. Statistisches Bundesamt (2024) Gender Care Gap 2022: Frauen leisten 43,8���% mehr unbezahlte Arbeit als M��nner. In:destatis, Wiesbaden. https://www.destatis.de/DE/Presse/Pressemitteilungen/2024/02/PD24_073_63991.html . Zugegriffen: 18. M��rz 2024
  43. Watt T, Groenvold M, Bjorner JB, Noerholm V, Rasmussen NA, Bech P (2000) Fatigue in the Danish general population. Influence of sociodemographic factors and disease. J Epidemiol Community Health 54:827���833. https://doi.org/10.1136/jech.54.11.827 [DOI: 10.1136/jech.54.11.827]
  44. Baum E, Lindner N, Maisel P (2022) DEGAM Leitlinie S3: M��digkeit. In:Deutsche Gesellschaft f��r Allgemeinmedizin und Familienmedizin (DEGAM), Berlin. https://register.awmf.org/assets/guidelines/053-002l_S3_Muedigkeit_2023-01_01.pdf . Zugegriffen: 18. M��rz 2024
  45. Wessely S (1995) The Epidemiology of Chronic Fatigue Syndrome. Epidemiol Rev 17:139���151. https://doi.org/10.1093/oxfordjournals.epirev.a036170 [DOI: 10.1093/oxfordjournals.epirev.a036170]
  46. Tylee A, Gastpar M, L��pine JP, Mendlewicz J, Comm DS (1999) Identification of depressed patient types in the community and their treatment needs:: findings from the DEPRES II (Depression Research in European Society II) Survey. Int Clin Psychopharmacol 14:153���165. https://doi.org/10.1097/00004850-199905002-00002 [DOI: 10.1097/00004850-199905002-00002]
  47. Abbey SE, Garfinkel PE (1991) Chronic Fatigue Syndrome and Depression���Cause, Effect, or Covariate. Rev Infect Dis 13:S73���S83 [DOI: 10.1093/clinids/13.Supplement_1.S73]
  48. Skapinakis P, Lewis G, Meltzer H (2000) Clarifying the relationship between unexplained chronic fatigue and psychiatric morbidity: Results from a community survey in Great Britain. Am J Psychiatry 157:1492���1498. https://doi.org/10.1176/appi.ajp.157.9.1492 [DOI: 10.1176/appi.ajp.157.9.1492]
  49. Franco JVA, Garegnani LI, Oltra GV et al (2022) Long-Term Health Symptoms and Sequelae Following SARS-CoV���2 Infection: An Evidence Map. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph19169915 [DOI: 10.3390/ijerph19169915]
  50. Office for National Statistics (ONS) (2024) Self-reported coronavirus (COVID-19) infections and associated symptoms, England and Scotland: November 2023 to March 2024. In: Statistical bulletin. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/articles/selfreportedcoronaviruscovid19infectionsandassociatedsymptomsenglandandscotland/november2023tomarch2024 . Zugegriffen: 11. Juli 2024
  51. Wong TL, Weitzer DJ (2021) Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)-A Systemic Review and Comparison of Clinical Presentation and Symptomatology. Medicina. https://doi.org/10.3390/medicina57050418 [DOI: 10.3390/medicina57050418]

MeSH Term

Humans
Germany
Adult
Male
Female
Middle Aged
Fatigue
Aged
Young Adult
Adolescent
Prevalence
COVID-19
Health Surveys
Risk Factors
Age Distribution
SARS-CoV-2
Sex Distribution

Word Cloud

Created with Highcharts 10.0.0fatigueFatigue95%CIGermanyagelackhealthriskanalysesdataadultsGEDA2023associatedfactors286%1resultsdeterminantsBACKGROUND:unspecificsymptomcomplexcharacterizedtirednessenergyconcentrationconsiderablepublicrelevanceduelinksincapacityworkaccidentsincreasedneedhealthcareMETHODS:based9766telephonesurvey"GesundheitDeutschlandaktuell"recordedusingAssessmentScaleFASa validatedinstrument10 questionsself-assessmentscaledichotomizedyesleastmildmoderateversusPopulation-weightedprevalencessociodemographichealth-relatedcalculateddescriptivemultivariablePoissonregressionRESULTS:overallprevalence297%1-312highest18-29-year-olds39350-444decreasesgroups65-79 years20182-233higheroldgroup332%9-377Womena highermenaRR1908-132significantlylowereducationchronicillnessdepressionlongCOVIDregardlesscovariatesDISCUSSION:onepopulation-basedstudiescollectedallowestimatesmadefrequencysignificancephysicalpsychologicalsocialinfluencingcanuseda referencea basistrendstimepartcontinuousmonitoring[Fatiguegeneralpopulation:"GermanHealthUpdate2023"study]GeneralpopulationHealth-relatedSociodemographicSurvey

Similar Articles

Cited By