Beyond the Preston Curve: Analyzing Variations in Life Expectancy Around the World Using Multivariate Regression Circa 2000 and 2015

Multiple studies, starting with Preston’s work in 1975, have suggested that gross domestic product per capita (GDPPC) is an important explanatory factor for understanding differentials in life expectancy at birth (LEB) in countries around the world. This proposition was tested in the present study using two-period cross-sectional regression across a large number of both advanced and developing countries and 16 socioeconomic factors, including GDPPC. The best-performing regression equations in the periods around 2000 and 2015 included four to six of these factors (government effectiveness, safe sanitation, poverty and contraception, plus, in the circa-2000 period, the Gini index and CO2 emissions); perhaps surprisingly, these equations did not include GDPPC. The results were examined in greater detail for the world’s 15 most populous countries, helping to identify key drivers of LEB growth for each of these countries from circa 2000 to 2015. The fact that GDPPC drops out of the best equations calls into question the view that economic growth is the correct primary target for nations seeking to increase their average life expectancy.

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Publication Details

Journal
Systems
Published
2025-07-14
DOI
https://doi.org/10.3390/systems13070577
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
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0.00
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article

Beyond the Preston Curve: Analyzing Variations in Life Expectancy Around the World Using Multivariate Regression Circa 2000 and 2015

Jack Homer
Systems
Insurance, Mortality, Demography, Risk Management
article

Beyond the Preston Curve: Analyzing Variations in Life Expectancy Around the World Using Multivariate Regression Circa 2000 and 2015

Jack Homer
article en

Abstract

Multiple studies, starting with Preston’s work in 1975, have suggested that gross domestic product per capita (GDPPC) is an important explanatory factor for understanding differentials in life expectancy at birth (LEB) in countries around the world. This proposition was tested in the present study using two-period cross-sectional regression across a large number of both advanced and developing countries and 16 socioeconomic factors, including GDPPC. The best-performing regression equations in the periods around 2000 and 2015 included four to six of these factors (government effectiveness, safe sanitation, poverty and contraception, plus, in the circa-2000 period, the Gini index and CO2 emissions); perhaps surprisingly, these equations did not include GDPPC. The results were examined in greater detail for the world’s 15 most populous countries, helping to identify key drivers of LEB growth for each of these countries from circa 2000 to 2015. The fact that GDPPC drops out of the best equations calls into question the view that economic growth is the correct primary target for nations seeking to increase their average life expectancy.

SystemsVol. 13(7)
Openalex Percentile: Top 70%
Insurance, Mortality, Demography, Risk Management
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Beyond the Preston Curve: Analyzing Variations in Life Expectancy Around the World Using Multivariate Regression Circa 2000 and 2015 — Jack Homer · Systems (2025) | TGRS Research Map | TGRS