Old-age care prevalence in Switzerland: drivers and future development


Long-term care (LTC) delivered to elderly persons in need of assistance in activities of daily living is a topic of increasing importance. The financing of LTC, the needs for specialized infrastructure and the limited number of caregivers will pose a systemic threat in many developed countries. In this paper, we analyze the factors influencing the old-age care prevalence rates in Switzerland through a log-linear regression model. Based on a cross-sectional dataset covering the LTC needs from 1995 to 2014, we statistically support the effect of key drivers such as the age, the gender and the region of residence. We distinguish the prevalence by the mild, moderate and severe frailty levels and by care received either at home or in an institution. Our regression results evidence that prevalence rates exponentially increase with the age yielding significantly higher values for women. These effects are emphasized for moderate and severe dependence and for institutional care. Finally, we forecast the number of dependent persons until 2045. Our projections reveal an important increase in the future numbers. While we observe that the dependent population more than doubles over the 30-year horizon, we report significant cantonal differences. Our results are relevant to governments, practitioners and academics alike and help to better understand the factors affecting the demand of LTC and predicting future needs.

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  1. 1.

    Three linguistic regions are distinguished in Switzerland. These regions are (1) the German-speaking region comprising the cantons of Aargau (AG), Appenzell Innerrhoden (AI), Appenzell Ausserrhoden (AR), Bern (BE), Basel-Landschaft (BL), Basel-Stadt (BS), Glarus (GL), Graubünden (GR), Lucerne (LU), Nidwalden (NW), Obwalden (OW), St.Gallen (SG), Schaffhausen (SH), Solothurn (SO), Schwyz (SZ), Thurgau (TG), Uri (UR), Zug (ZG), and Zurich (ZH); (2) the French-speaking region comprising the cantons of Fribourg (FR), Geneva (GE), Jura (JU), Neuchâtel (NE), Vaud (VD), and Valais (VS); and (3) the Italian-speaking region formed by the canton of Ticino (TI).

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  3. 3.


  4. 4.

    Differences in the numbers may arise from the exact registration dates of the acuity levels, how up-to-date the sources are, if former years are revised over time, the processes for aggregation used, and the cleaning of incomplete entries.

  5. 5.


  6. 6.

    The historical census on the population for the years 1995–2014 is built upon the aggregation of two publicly available datasets, the first one covering the years of interest from 1995 to 2010 and the second one covering the years from 2010 to 2014. For the year 2010 which appears in both datasets, we take the average values between the datasets. Furthermore, the first dataset covers the ages from 65 to 98 years separately and comprises a \(99+\)-category while the second dataset covers the ages from 65 to 99 and has a \(100+\)-category. We merge the datasets and build a \(99+\)-category corresponding to the sum of the \(99+\) in the first dataset and the classes 99 and 100+ from the second dataset.

  7. 7.

    When adding the age–gender interaction in the forecasts, the robustness analysis in Sect. 5.3 would yield increased relative errors.

  8. 8.

    For years before 2014, we omit the hat “\({}^{\wedge }\)” in our notation since the numbers are reported statistics and do not represent forecast estimates.


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Funding was provided by Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH) (grant no. 100018_169662) and the Swiss Insurance Association. Support from the Swiss Central Compensation Office for providing the data is kindly acknowledged.

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Correspondence to Joël Wagner.

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Fuino, M., Wagner, J. Old-age care prevalence in Switzerland: drivers and future development. Eur. Actuar. J. 8, 321–362 (2018). https://doi.org/10.1007/s13385-018-0185-3

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  • Long-term care
  • Log-linear regression
  • Prevalence rates
  • Forecast