Reassessing socioeconomic inequalities in mortality via distributional similarities

Commonly used measures of socioeconomic inequalities in mortality, such as the slope and the relative index of inequality, are based on summary measures of the group-specific age-at-death distributions (e.g. standardized mortality rate or life expectancy). While this approach is informative, it ignores valuable information contained in the group-specific distributions. A recent approach applied a measure of distributional dissimilarity (the non-overlap index) to measure lifespan stratification. In this paper, we rigorously evaluate and further implement the multi-group extension of the non-overlap index ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> ) to measure socioeconomic inequalities in mortality across a number of groups, and assess whether differences across countries and over time are driven by mortality or compositional changes in two applications with different data availability: educational groups (Sweden and Denmark) and groups defined by an area-level deprivation measure (England). Our findings suggest that the multi-group <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> is sensitive not only to changes in the means or variances, but also to broader mortality changes that affect distributional shapes. The method can be employed to any context where mortality rates by age are available by sub-groups. Furthermore, levels and trends in mortality inequalities computed with the multigroup <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> often differ compared to other conventional summary-based measures. Moreover, we find that the contribution of mortality changes to changes in inequalities is generally greater than that of the changes in the population composition. Whereas levels and trends of inequalities may depend on whether life expectancy- or lifespan variation-based measures are employed, the multi-group <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> provides a holistic perspective by capturing both dimensions simultaneously.

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Publication Details

Journal
Population Health Metrics
Published
2025-02-22
DOI
https://doi.org/10.1186/s12963-025-00365-1
Citations
1
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
Field-Weighted Citation Impact
5.59

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Reassessing socioeconomic inequalities in mortality via distributional similarities

Carlo Giovanni Camarda, Fanny Janssen, Ugofilippo Basellini, Emilio Zagheni et al.
1 citations
Population Health Metrics
Insurance, Mortality, Demography, Risk Management
5.59
article

Reassessing socioeconomic inequalities in mortality via distributional similarities

Carlo Giovanni Camarda, Fanny Janssen, Ugofilippo Basellini, Emilio Zagheni, Ana C. Gómez-Ugarte
article en
1 citations

Abstract

Commonly used measures of socioeconomic inequalities in mortality, such as the slope and the relative index of inequality, are based on summary measures of the group-specific age-at-death distributions (e.g. standardized mortality rate or life expectancy). While this approach is informative, it ignores valuable information contained in the group-specific distributions. A recent approach applied a measure of distributional dissimilarity (the non-overlap index) to measure lifespan stratification. In this paper, we rigorously evaluate and further implement the multi-group extension of the non-overlap index ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> ) to measure socioeconomic inequalities in mortality across a number of groups, and assess whether differences across countries and over time are driven by mortality or compositional changes in two applications with different data availability: educational groups (Sweden and Denmark) and groups defined by an area-level deprivation measure (England). Our findings suggest that the multi-group <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> is sensitive not only to changes in the means or variances, but also to broader mortality changes that affect distributional shapes. The method can be employed to any context where mortality rates by age are available by sub-groups. Furthermore, levels and trends in mortality inequalities computed with the multigroup <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> often differ compared to other conventional summary-based measures. Moreover, we find that the contribution of mortality changes to changes in inequalities is generally greater than that of the changes in the population composition. Whereas levels and trends of inequalities may depend on whether life expectancy- or lifespan variation-based measures are employed, the multi-group <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>S</mml:mi> <mml:mi>P</mml:mi></mml:msup> </mml:math> provides a holistic perspective by capturing both dimensions simultaneously.

Population Health MetricsVol. 23(1)
Institut national d'études démographiques (FR), University of Groningen (NL), Max Planck Institute for Demographic Research (DE), Netherlands Interdisciplinary Demographic Institute (NL)
Max-Planck-Institut für demografische Forschung
Good health and well-being
Openalex Percentile: Top 8%
Insurance, Mortality, Demography, Risk Management
5.59
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