Using age, period and cohort models to estimate future mortality rates

Area of Science:

• Demography
• Epidemiology
• Biostatistics

Background:

• Mortality rate analysis is crucial for public health.
• Traditional models often struggle to disentangle age, period, and cohort effects.
• Forecasting future mortality trends is essential for resource allocation and policy development.

Purpose of the Study:

• To describe age, period, and cohort models for mortality rate analysis.
• To extend these models for future mortality rate estimation.
• To apply and validate the technique using lung cancer mortality data for women in England and Wales.

Main Methods:

• Utilized age, period, and cohort models to analyze mortality data.
• Estimated future mortality rates by incorporating birth cohort and period of death trends.
• Validated the model by comparing estimated rates for 1971-1980 against observed data.
• Projected mortality rates up to the year 2000 based on historical data (1951-1980).

Main Results:

• The models successfully described age- and period-specific mortality rates.
• Future mortality rates were estimated, accounting for cohort and period effects.
• The technique demonstrated accuracy when applied to lung cancer mortality in England and Wales.
• Projections provided insights into mortality trends up to the year 2000.

Conclusions:

• Age, period, and cohort models are effective tools for describing and forecasting mortality rates.
• The method allows for the incorporation of complex temporal trends in mortality.
• This approach has broad applicability for various conditions and public health surveillance.
• The study validates the utility of these models for epidemiological research and planning.