26-08-2020
EQ-5D-3L health status and health state utilities of the oldest-old (85 +) in Germany: results from the AgeCoDe-AgeQualiDe study
Auteurs: Hans-Helmut König, Christian Brettschneider, Dagmar Lühmann, Hanna Kaduszkiewicz, Anke Oey, Birgitt Wiese, Jochen Werle, Siegfried Weyerer, Angela Fuchs, Michael Pentzek, Ines Conrad, Susanne Röhr, Dagmar Weeg, Horst Bickel, Kathrin Heser, Michael Wagner, Martin Scherer, Wolfgang Maier, Steffi G. Riedel-Heller, André Hajek
Gepubliceerd in: Quality of Life Research | Uitgave 12/2020
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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.