Abstract
Purpose
To describe health status and health state utilities measured by the EQ-5D-3L in a population-based sample of individuals aged 85 + in Germany, and to analyze associations with basic socio-demographic variables.
Methods
Cross-sectional data from follow-up wave 7 (n = 761) of the German AgeCoDe Study were used. The EQ-5D-3L questionnaire was used to record problems in five health dimensions, its visual analogue scale (EQ VAS) was used to record self-rated health status, and the German EQ-5D-3L index was used to derive health state utilities.
Results
Mean age of respondents was 88.9 years (SD 2.9; range 85 to 100), 67.4% were female. 81.9% reported problems in at least one of the EQ-5D dimensions, with 15.3% reporting extreme problems. Most frequent were problems with pain/discomfort (64.8%), followed by mobility (62.5%), usual activities (42.6%), self-care (28.2%), and anxiety/depression (20.5%). Mean EQ VAS score was 62.4 (SD 18.8), and mean EQ-5D index was 0.77 (SD 0.24). Multiple regression analysis showed associations of problem frequency in various EQ-5D dimensions with age, gender, living situation, marital status, and education. The EQ VAS score was negatively associated with age (β = − 0.56; p < 0.05) and female gender (β = − 3.49; p < 0.05). The EQ-5D index was negatively associated with not living in the community (β = − 0.10; p < 0.001) and being single (β = − 0.09; p < 0.05).
Conclusions
The results show a substantially impaired health status of the oldest-old population. The data can be used for comparing health status of population groups as well as for health economic models.
Similar content being viewed by others
References
Campion, E. (1994). The oldest old. The New England Journal of Medicine, 330(25), 1819–1820. https://doi.org/10.1056/NEJM199406233302509.
Suzman, R., & Riley, M. (1985). Introducing the "oldest old". The Milbank Memorial Fund Quarterly, Health and Society, 63(2), 177–186.
Statistisches Bundesamt (Destatis) (2016). Bevölkerung und Erwerbstätigkeit. Rückgerechnete und fortgeschriebene Bevölkerung auf Grundlage des Zensus 2011. Retrieved June 26, 2020 from https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Bevoelkerung/Bevoelkerungsstand/Publikationen/Downloads-Bevoelkerungsstand/rueckgerechnete-bevoelkerung-5124105119004.pdf?__blob=publicationFile
Statistisches Bundesamt (Destatis) (2017). Bevölkerung Deutschlands bis 2060. Ergebnisse der 14. koordinierten Bevölkerungsvorausberechnung - Hauptvarianten 1 bis 9. Retrieved June 26, 2020 from https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Bevoelkerung/Bevoelkerungsvorausberechnung/Publikationen/Downloads-Vorausberechnung/bevoelkerung-deutschland-2060-5124202199014.pdf?__blob=publicationFile
Statistisches Bundesamt (Destatis) (2017). Krankheitskosten 2015. Retrieved June 26, 2020 from https://www.destatis.de/GPStatistik/servlets/MCRFileNodeServlet/DEHeft_derivate_00033175/2120721159004.pdf%3Bjsessionid%3DB19129ECF3A61F8DB331D847FC4E599C
EuroQol Group. (1990). EuroQol–a new facility for the measurement of health-related quality of life. Health Policy, 16(3), 199–208. https://doi.org/10.1016/0168-8510(90)90421-9.
Drummond, M., Sculpher, M., Claxton, K., Stoddart, G., & Torrance, G. (2015). Methods for the economic evaluation of health care programmes (4th ed.). Oxford: Oxford University Press.
Teerawattananon, Y., Luz, A., Culyer, A., & Chalkidou, K. (2020). Charging for the use of survey instruments on population health: The case of quality-adjusted life years. Bulletin of the World Health Organization, 98(1), 59–65. https://doi.org/10.2471/BLT.19.233239.
Ramsey, S., Willke, R., Briggs, A., Brown, R., Buxton, M., Chawla, A., et al. (2005). Good research practices for cost-effectiveness analysis alongside clinical trials: The ISPOR RCT-CEA Task Force report. Value in Health, 8(5), 521–533. https://doi.org/10.1111/j.1524-4733.2005.00045.x.
National Institute for Health and Care Excellence (2013). Guide to the methods of technology appraisal 2013. Retrieved June 26, 2020 from https://www.nice.org.uk/process/pmg9/chapter/foreword
EUnetHTA Joint Action 2 Work Package 7 Subgroup 3, Heintz, E., Gerber-Grote, A., Ghabri, S., Hamers, F., Rupel, V., et al. (2016). Is There a European view on health economic evaluations? Results from a synopsis of methodological guidelines used in the EUnetHTA partner countries. PharmacoEconomics, 34(1), 59–76. https://doi.org/10.1007/s40273-015-0328-1.
Szende, A., Janssen, B., & Cabases, J. (2014). Self-reported population health: An international perspective based on EQ-5D. Amsterdam: Springer.
Janssen, M., Szende, A., Cabases, J., Ramos-Goñi, J., Vilagut, G., & König, H. (2019). Population norms for the EQ-5D-3L: A cross-country analysis of population surveys for 20 countries. The European Journal of Health Economics, 20(2), 205–216. https://doi.org/10.1007/s10198-018-0955-5.
König, H., Heider, D., Lehnert, T., Riedel Heller, S., Angermeyer, M., Matschinger, H., et al. (2010). Health status of the advanced elderly in six European countries: Results from a representative survey using EQ-5D and SF-12. Health and Quality of Life Outcomes. https://doi.org/10.1186/1477-7525-8-143.
Hong, E. (2015). Age differences in health-related quality of life among South Korean elderly. Journal of Nursing and Health Science, 1(4), 34–39.
Luthy, C., Cedraschi, C., Allaz, A. F., Herrmann, F. R., & Ludwig, C. (2015). Health status and quality of life: Results from a national survey in a community-dwelling sample of elderly people. Quality of Life Research, 24(7), 1687–1696. https://doi.org/10.1007/s11136-014-0894-2.
Mangen, M. J., Bolkenbaas, M., Huijts, S. M., van Werkhoven, C. H., Bonten, M. J., & de Wit, G. A. (2017). Quality of life in community-dwelling Dutch elderly measured by EQ-5D-3L. Health and Quality of Life Outcomes, 15(1), 3. https://doi.org/10.1186/s12955-016-0577-5.
Sun, S., Chen, J., Johannesson, M., Kind, P., Xu, L., Zhang, Y., et al. (2011). Population health status in China: EQ-5D results, by age, sex and socio-economic status, from the National Health Services Survey 2008. Quality of Life Research, 20(3), 309–320. https://doi.org/10.1007/s11136-010-9762-x.
Luck, T., Riedel Heller, S., Luppa, M., Wiese, B., Wollny, A., Wagner, M., et al. (2010). Risk factors for incident mild cognitive impairment–results from the German study on ageing, cognition and dementia in primary care patients (AgeCoDe). Acta Psychiatrica Scandinavica, 121(4), 260–272. https://doi.org/10.1111/j.1600-0447.2009.01481.x.
Greiner, W., Claes, C., Busschbach, J., & von der Schulenburg, J. (2005). Validating the EQ-5D with time trade off for the German population. The European Journal of Health Economics, 6(2), 124–130. https://doi.org/10.1007/s10198-004-0264-z.
Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 1095–1108. https://doi.org/10.1097/00005650-199711000-00002.
Arnold, M., Pfeifer, K., & Quante, A. (2019). Is risk-stratified breast cancer screening economically efficient in Germany? PLoS ONE, 14(5), e0217213. https://doi.org/10.1371/journal.pone.0217213.
Norström, F., Waenerlund, A., Lindholm, L., Hygren, R., Sahlén, K., & Brydsten, A. (2019). Does unemployment contribute to poorer health-related quality of life among Swedish adults? BMC Public Health, 19(1), 457.
Sapin, C., Fantino, B., Nowicki, M., & Kind, P. (2004). Usefulness of EQ-5D in assessing health status in primary care patients with major depressive disorder. Health and Quality of Life Outcomes, 2, 20. https://doi.org/10.1186/1477-7525-2-20.
Brauns, H., & Steinmann, S. (1999). Educational reform in France, West-Germany and the United Kingdom: Updating the CASMIN educational classification. ZUMA Nachrichten, 23(44), 7–44.
König, H., Bernert, S., & Angermeyer, M. (2005). Gesundheitszustand der deutschen Bevölkerung: Ergebnisse einer repräsentativen Befragung mit dem EuroQol-Instrument. Gesundheitswesen, 67(3), 173–182. https://doi.org/10.1055/s-2005-857991.
Janssen, B., & Szende, A. (2014). Population norms for the EQ-5D. In A. J. Szende & B. J. Cabases (Eds.), Self-reported population health: An international perspective based on EQ-5D (pp. 19–30). Amsterdam: Springer.
Hinz, A., Klaiberg, A., Brähler, E., & König, H. (2006). Der Lebensqualitätsfragebogen EQ-5D: Modelle und Normwerte für die Allgemeinbevölkerung. Psychotherapie, Psychosomatik, Medizinische Psychologie, 56(2), 42–48. https://doi.org/10.1055/s-2005-867061.
Mielck, A., Vogelmann, M., Schweikert, B., & Leidl, R. (2010). Gesundheitszustand bei Erwachsenen in Deutschland: Ergebnisse einer repräsentativen Befragung mit dem EuroQol 5D (EQ-5D). Gesundheitswesen, 72(8–9), 476–486. https://doi.org/10.1055/s-0029-1239508.
Borowiak, E., & Kostka, T. (2004). Predictors of quality of life in older people living at home and in institutions. Aging Clinical and Experimental Research, 16(3), 212–220. https://doi.org/10.1007/bf03327386.
Karakaya, M. G., Bilgin, S. C., Ekici, G., Köse, N., & Otman, A. S. (2009). Functional mobility, depressive symptoms, level of independence, and quality of life of the elderly living at home and in the nursing home. Journal of the American Medical Directors Association, 10(9), 662–666. https://doi.org/10.1016/j.jamda.2009.06.002.
Chen, C., Liu, G. G., Shi, Q. L., Sun, Y., Zhang, H., Wang, M. J., et al. (2020). Health-related quality of life and associated factors among oldest-old in China. The Journal of Nutrition, Health and Aging, 24(3), 330–338. https://doi.org/10.1007/s12603-020-1327-2.
Kwon, S., Park, J. H., Kim, W. S., Han, K., Lee, Y., & Paik, N. J. (2018). Health-related quality of life and related factors in stroke survivors: Data from Korea National Health and Nutrition Examination Survey (KNHANES) 2008 to 2014. PLoS ONE, 13(4), e0195713. https://doi.org/10.1371/journal.pone.0195713.
Lei, P., Xu, L., Nwaru, B. I., Long, Q., & Wu, Z. (2016). Social networks and health-related quality of life among Chinese old adults in urban areas: Results from 4th National Household Health Survey. Public Health, 131, 27–39. https://doi.org/10.1016/j.puhe.2015.10.009.
N'Goran, A. A., Déruaz-Luyet, A., Haller, D. M., Zeller, A., Rosemann, T., Streit, S., et al. (2017). Comparing the self-perceived quality of life of multimorbid patients and the general population using the EQ-5D-3L. PLoS ONE, 12(12), e0188499. https://doi.org/10.1371/journal.pone.0188499.
Park, H. E., Song, H. Y., Han, K., Cho, K. H., & Kim, Y. H. (2019). Number of remaining teeth and health-related quality of life: The Korean National Health and Nutrition Examination Survey 2010–2012. Health and Quality of Life Outcomes, 17(1), 5. https://doi.org/10.1186/s12955-019-1078-0.
Linden, M., Gilberg, R., Horgas, A., & Steinhagen-Thiessen, E. (2010). Die Inanspruchnahme medizinischer und pflegerischer Hilfe im hohen Alter. In U. Lindenberger, J. Smith, K. Mayer, & P. Baltes (Eds.), Die Berliner Altersstudie (pp. 499–519). Berlin: Akademie-Verlag.
Hajek, A., Brettschneider, C., Ernst, A., Posselt, T., Wiese, B., Prokein, J., et al. (2016). Longitudinal predictors of informal and formal caregiving time in community-dwelling dementia patients. Social Psychiatry and Psychiatric Epidemiology, 51(4), 607–616. https://doi.org/10.1007/s00127-015-1138-7.
Statistisches Bundesamt (Destatis) (2017). Pflegestatistik. Pflege im Rahmen der Pflegeversicherung. Deutschlandstatistik. Retrieved from June 26, 2020 from https://www.destatis.de/GPStatistik/servlets/MCRFileNodeServlet/DEHeft_derivate_00042871/5224001159004.pdf
Long, J., & Freese, J. (2014). Regression models for categorical dependent variables using Stata (3rd ed.). College Station: Stata Press.
Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736. https://doi.org/10.1007/s11136-011-9903-x.
Devlin, N., Shah, K., Feng, Y., Mulhern, B., & van Hout, B. (2018). Valuing health-related quality of life: An EQ-5D-5L value set for England. Health Economics, 27(1), 7–22. https://doi.org/10.1002/hec.3564.
Ludwig, K., Graf von der Schulenburg, J., & Greiner, W. (2018). German value set for the EQ-5D-5L. PharmacoEconomics, 36(6), 663–674. https://doi.org/10.1007/s40273-018-0615-8.
National Institute for Health and Care Excellence (2019). Position statement on use of the EQ-5D-5L value set for England. Retrieved from June 26, 2020 from https://www.nice.org.uk/about/what-we-do/our-programmes/nice-guidance/technology-appraisal-guidance/eq-5d-5l
Acknowledgements
We want to thank both all participating patients and their general practitioners for their good collaboration. Members of the AgeCoDe & AgeQualiDe Study Group: Wolfgang Maier (Principal Investigator), Martin Scherer (Principal Investigator), Steffi G. Riedel-Heller (Principal Investigator), Heinz-Harald Abholz, Christian Brettschneider, Cadja Bachmann, Horst Bickel, Wolfgang Blank, Hendrik van den Bussche, Sandra Eifflaender-Gorfer, Marion Eisele, Annette Ernst, Angela Fuchs, André Hajek, Kathrin Heser, Frank Jessen, Hanna Kaduszkiewicz, Teresa Kaufeler, Mirjam Köhler, Hans-Helmut König, Alexander Koppara, Diana Lubisch, Tobias Luck, Dagmar Lühmann, Melanie Luppa, Tina Mallon, Manfred Mayer, Edelgard Mösch, Michael Pentzek, Jana Prokein, Alfredo Ramirez, Susanne Röhr, Anna Schumacher, Janine Stein, Susanne Steinmann, Franziska Tebarth, Hendrik van den Bussche (Principal Investigator 2002-2011), Carolin van der Leeden, Michael Wagner, Klaus Weckbecker, Dagmar Weeg, Jochen Werle, Siegfried Weyerer, Birgitt Wiese, Steffen Wolfsgruber, Thomas Zimmermann.
Funding
This publication is part of the German Research Network on Dementia (KND), the German Research Network on Degenerative Dementia (KNDD; German Study on Ageing, Cognition and Dementia in Primary Care Patients; AgeCoDe), and the Health Service Research Initiative (Study on Needs, health service use, costs and health-related quality of life in a large sample of oldest-old primary care patients (85 + ; AgeQualiDe)) and was funded by the German Federal Ministry of Education and Research (Grants KND: 01GI0102, 01GI0420, 01GI0422, 01GI0423, 01GI0429, 01GI0431, 01GI0433, 01GI0434; grants KNDD: 01GI0710, 01GI0711, 01GI0712, 01GI0713, 01GI0714, 01GI0715, 01GI0716; Grants Health Service Research Initiative: 01GY1322A, 01GY1322B, 01GY1322C, 01GY1322D, 01GY1322E, 01GY1322F, 01GY1322G). The publication was also supported by the study “Healthy Aging: Gender specific trajectories into latest life” (AgeDifferent.De) that was funded by the German Federal Ministry of Education and Research (Grant Nos. 01GL1714A; 01GL1714B; 01GL1714C; 01GL1714D).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interests
All authors declare that they have no potential conflicts of interest.
Ethics approval
The AgeCoDe and the AgeQualiDe study have been approved by the ethics committees of all participating study centers (Approval Numbers: Hamburg: OB/08/02, 2817/2007, MC-390/13; Bonn: 050/02; 174/02, 258/07, 369/13; Mannheim: 0226.4/2002, 2007-253E-MA, 2013-662N-MA; Leipzig: 143/2002, 309/2007, 333-1318112013; Düsseldorf: 2079/2002, 2999/2008, 2999; Munich: 713/02, 713/02 E) and comply with the ethical standards of the Declaration of Helsinki of 1975, as revised in 1983.
Informed consent
All participants gave written informed consent prior to participation.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
König, HH., Brettschneider, C., Lühmann, D. et al. EQ-5D-3L health status and health state utilities of the oldest-old (85 +) in Germany: results from the AgeCoDe-AgeQualiDe study. Qual Life Res 29, 3223–3232 (2020). https://doi.org/10.1007/s11136-020-02597-0
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-020-02597-0