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On forecasting mortality.

S J Olshansky1

  • 1National Opinion Research Center, University of Chicago.

The Milbank Quarterly
|January 1, 1988
PubMed
Summary
This summary is machine-generated.

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Official mortality forecasts consistently underestimate declines by using static trend extrapolation. A multiple cause-delay model, incorporating risk factors, offers more realistic projections for population aging and healthcare costs.

Area of Science:

  • Demography
  • Public Health
  • Biostatistics

Background:

  • Official U.S. mortality forecasts have historically underestimated actual mortality declines.
  • This underestimation stems from reliance on static extrapolation of past trends, neglecting key influencing factors.

Purpose of the Study:

  • To introduce and evaluate a "multiple cause-delay model" for more accurate mortality forecasting.
  • To assess the impact of revised mortality assumptions on elderly population size, morbidity, disability, and healthcare cost estimates.

Main Methods:

  • Utilized a "multiple cause-delay model" that incorporates population-level risk factor dynamics.
  • Compared model outputs against traditional static extrapolation methods.

Main Results:

Keywords:
AdultAge FactorsAgedAmericasBehaviorCritiqueDelivery Of Health Care--costDemographic FactorsDeveloped CountriesDeveloping CountriesDiseasesEconomic FactorsEstimation TechnicsEvaluationHealthMethodological StudiesModels, TheoreticalMorbidityMortalityNorth AmericaNorthern AmericaPopulationPopulation At RiskPopulation CharacteristicsPopulation DynamicsPopulation ForecastResearch MethodologySocioeconomic FactorsUnited States

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  • The multiple cause-delay model provides a more realistic portrayal of mortality trends.
  • Revised assumptions lead to significantly increased forecasts for the elderly population size.
  • Substantial impacts on projected morbidity, disability rates, and healthcare expenditures were observed.

Conclusions:

  • Static extrapolation methods are inadequate for accurate long-term mortality forecasting.
  • The multiple cause-delay model offers a more robust framework for projecting future population health and resource needs.
  • Accurate mortality forecasting is critical for effective public health planning and resource allocation.