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Published on: January 8, 2020
Forecasting United States mortality using cohort smoking histories
Haidong Wang1, Samuel H Preston
1Institute for Health Metrics and Evaluation, University of Washington, Seattle, 2301 5th Avenue, Seattle, WA 98121, USA.
Summary
This study integrates cohort smoking patterns into mortality projections, revealing faster mortality decline due to reduced smoking. The enhanced model improves accuracy for U.S. adult mortality forecasts.
Area of Science:
- Demography
- Public Health
- Epidemiology
Background:
- Traditional mortality models often fail to capture cohort-specific behaviors like smoking.
- Recent U.S. mortality trends show anomalies not fully explained by existing projection models.
- Cohort smoking intensity is a significant, yet often overlooked, factor in adult mortality.
Purpose of the Study:
- To incorporate cohort smoking patterns into mortality projections for the United States.
- To refine the Lee-Carter model by adding a smoking intensity variable.
- To improve the accuracy of U.S. adult mortality forecasts between 2004 and 2034.
Main Methods:
- Modified the Lee-Carter mortality projection model.
- Introduced a variable for cohort smoking intensity.
- Projected age-specific mortality rates for U.S. adults aged 50-84.
Main Results:
- The revised model accounts for anomalies in recent age/sex mortality changes.
- A common temporal trend for mortality change is enabled for both sexes.
- Mortality is projected to decline significantly faster due to smoking reductions.
Conclusions:
- Incorporating cohort smoking patterns enhances mortality projection accuracy.
- Projected faster mortality declines are directly linked to observed and projected smoking reductions.
- This approach offers a more robust method for forecasting U.S. adult mortality.
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