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Computing population-based estimates of health-adjusted life expectancy
M A Rosenberg1, D G Fryback, W F Lawrence
1University of Wisconsin-Madison, 53706, USA.
Summary
Estimating health-adjusted life expectancy (HALE) for communities reveals significant variations depending on the calculation method. A new Bayesian approach combines local and regional data for more accurate HALE estimates.
Area of Science:
- Public Health
- Biostatistics
- Health Economics
Background:
- Health-adjusted life expectancy (HALE) is a key population health indicator.
- Existing methods for calculating community HALE can yield diverse estimates.
- Variability in HALE estimates necessitates exploring improved methodologies.
Purpose of the Study:
- To evaluate different methods for computing community HALE.
- To demonstrate the impact of data sources on HALE estimates.
- To develop and assess a novel Bayesian approach for HALE calculation.
Main Methods:
- Utilized Quality of Well-being (QWB) scores from 1,430 participants as weights.
- Employed actuarial life-table methods with community mortality and census data (Wisconsin and U.S.).
- Developed a Bayesian method integrating local and regional data for HALE estimation.
Main Results:
- Different HALE computation methods produced varying estimates.
- Community-level HALE may not be accurately represented by large-scale mortality data.
- The Bayesian method provided smoothed rates, preserved local characteristics, and quantified HALE variability.
Conclusions:
- Accurate community HALE estimation requires careful consideration of data sources and methodologies.
- A Bayesian approach offers a robust method for calculating community HALE, balancing local specificity with broader data.
- The developed Bayesian method enhances the reliability and interpretability of HALE as a population health metric.