Decomposing Current Mortality Differences Into Initial Differences and Differences in Trends: The Contour...

Area of Science:

• Demography
• Biostatistics
• Epidemiology

Background:

• Aggregate measures often mask underlying demographic shifts.
• Understanding divergence in population health metrics requires nuanced analytical tools.

Purpose of the Study:

• To propose and validate a new decomposition method for analyzing aggregate measure differences.
• To differentiate contributions from initial event rates and trend changes.
• To facilitate comparative demographic analysis, particularly for life expectancy.

Main Methods:

• Developed a novel decomposition technique to partition aggregate differences.
• Assessed two approaches: additive change and contour decomposition.
• Extended the stepwise replacement algorithm for contour decomposition.

Main Results:

• Both methods yielded comparable results.
• The contour decomposition method demonstrated broader applicability.
• The method was applied to US and England/Wales life expectancy and disparity data (1980-2010).

Conclusions:

• The proposed decomposition method effectively isolates sources of change in aggregate measures.
• Contour decomposition offers a versatile tool for demographic trend analysis.
• This methodology enhances the understanding of population-level health metric divergence.