2015年-CEPS欧洲政策研究中心_Demographic_Epidemiologic_Projections_of_Long_38页_435kb

Summary of Demographic Epidemiologic Projections of Long-Term Care Needs in Selected European Countries

Core Content

This report presents demographic epidemiologic projections of long-term care (LTC) needs in four European countries: Germany, Spain, the Netherlands, and Poland. The study is part of the ANCIEN project, which aims to understand future LTC requirements in the context of an aging population. The projections are based on the EUROPOP 2008 mortality forecasts and incorporate assumptions about the relationship between disability and mortality, as well as the effects of risk factors such as obesity and smoking.

Main Determinants and Key Findings

• Demographic Ageing: The primary driver of future LTC needs is the aging of the large post-war baby boom cohorts. Projections indicate:

  • Germany: 44% increase in care-dependent elderly.
  • Spain: 65% increase.
  • Netherlands: 82% increase.
  • Poland: 57% increase.

• Life Extension Effects: The impact of increased life expectancy on LTC needs is moderate and depends on the correlation between disability and mortality. Under conservative assumptions:

  • Germany: +11% increase.
  • Spain: +7% increase.
  • Netherlands: +9% increase.
  • Poland: +22% increase.

• Risk Factors (Smoking and Obesity): These factors have minimal impact on LTC needs, despite their known health effects. The report notes that:

  • Obesity leads to a small reduction in disability-free life expectancy but has limited effect on overall LTC numbers.
  • Smoking reduces life expectancy but also compresses disability, making its effect on LTC needs relatively small.

• Poland's Special Case: Poland's LTC needs are expected to increase significantly due to high disability rates and mortality, though convergence to a German disability schedule could moderate this trend.

Scenario Assumptions

The report evaluates several scenarios to project LTC needs:

Scenarios Without Risk Factors

• Constant Incidence and Mortality (CONST): Assumes no change in incidence or mortality, reflecting only demographic aging.
• Constant Prevalence (PREV): Uses constant age-specific disability prevalence to project future needs.
• Chronological Ageing (CHRON): Assumes incidence rates are dependent on chronological age, leading to increased prevalence due to lower mortality among disabled individuals.
• Biological Ageing (BIOL): Assumes disability is linked to biological age, which corresponds to mortality trends. This scenario predicts expansion of healthy life but not disabled life.
• Delayed Ageing (DELAY): A more conservative version of the BIOL scenario, assuming disability is postponed to older ages. It results in less disability at younger ages and more at older ages, compared to BIOL.

Scenarios With Risk Factors

• BMI Scenario (OBESE): Assumes a constant prevalence of obesity, leading to a small reduction in disability-free life expectancy.
• Leaner Population Scenario (LEAN): Assumes a halving of obesity prevalence in future cohorts, reflecting a return to 1960s levels.
• FAT Scenario: Assumes a doubling of obesity prevalence, leading to increased disability.
• Smoking Scenario (SMOK): Projects high smoking prevalence in future cohorts, leading to higher mortality and lower life expectancy.
• Trend Scenario (TREND): Assumes a realistic 2% annual quit rate among smokers.
• No Smoking Scenario (NoSMOK): Assumes no new smokers in future cohorts, leading to a gradual decline in smoking prevalence.
• No Smoking and Accelerated Quitting (NoSQuit): Assumes high quitting rates, leading to reduced smoking-related mortality and potential for increased disability.

Modelled Life Expectancies in 2040

• The report compares life expectancies at age 65 for each country, distinguishing between disability and non-disability status.
• Germany:
  • Women: 20.1 years (15.35 non-disabled, 4.75 disabled).
  • Men: 16.8 years (13.56 non-disabled, 3.32 disabled).
• Spain:
  • Women: 20.96 years (14.87 non-disabled, 6.09 disabled).
  • Men: 17.14 years (13.79 non-disabled, 3.35 disabled).
• Netherlands:
  • Women: 19.94 years (15.64 non-disabled, 4.30 disabled).
  • Men: 16.59 years (14.39 non-disabled, 2.20 disabled).
• Poland:
  • Women: 18.56 years (10.85 non-disabled, 7.71 disabled).
  • Men: 14.50 years (9.91 non-disabled, 4.59 disabled).

These projections are based on the assumption that disability and mortality are linked, with the impact of risk factors being relatively small.

Strengths and Weaknesses of the Approach

• Strengths:

  • Use of comprehensive data from SHARE, Rotterdam Study, and Eurostat.
  • Application of multi-state demographic models to simulate incidence and mortality.
  • Availability of user-friendly spreadsheets and R syntax for reproducibility.

• Weaknesses:

  • Implicit assumptions in mortality forecasts may affect the accuracy of disability projections.
  • Risk factors (obesity, smoking) have limited impact, which may be due to the models used or data limitations.
  • The model does not include fertility or migration, which could influence future LTC needs.

Priorities for Further Research

• Improved understanding of the interaction between disability and mortality.
• More detailed analysis of the effects of risk factors on LTC needs.
• Incorporation of fertility and migration trends into future models.
• Validation of the model using more granular and longitudinal data.

Conclusions

The future number of care-dependent elderly in the selected European countries will be primarily determined by demographic aging. While life extension and risk factors such as obesity and smoking have some effect, they are relatively minor compared to the impact of aging populations. The report highlights the importance of using consistent and transparent models for accurate LTC projections and underscores the need for further research to refine assumptions and improve model accuracy.