A Typology for Charting Socioeconomic Mortality Gradients

Tony A Blakely · George Disney · June Atkinson · Andrea M. Teng · Johan Pieter Mackenbach

30 citations0/0 files storedEpidemiology

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Abstract

BACKGROUND: Holistic depiction of time-trends in average mortality rates, and absolute and relative inequalities, is challenging. METHODS: We outline a typology for situations with falling average mortality rates (m↓; e.g., cardiovascular disease), rates stable over time (m-; e.g., some cancers), and increasing average mortality rates (m↑; e.g., suicide in some contexts). If we consider inequality trends on both the absolute (a) and relative (r) scales, there are 13 possible combination of m, a, and r trends over time. They can be mapped to graphs with relative inequality (log relative index of inequality [RII]; r) on the y axis, log average mortality rate on the x axis (m), and absolute inequality (slope index of inequality; SII; a) as contour lines. We illustrate this by plotting adult mortality trends: (1) by household income from 1981 to 2011 for New Zealand, and (2) by education for European countries. RESULTS: Types range from the "best" m↓a↓r↓ (average, absolute, and relative inequalities all decreasing; southwest movement in graphs) to the "worst" m↑a↑r↑ (northeast). Mortality typologies in New Zealand (all-cause, cardiovascular disease, nonlung cancer, and unintentional injury) were all m↓r↑ (northwest), but variable with respect to absolute inequality. Most European typologies were m↓r↑ types (northwest; e.g., Finland), but with notable exceptions of m-a↑r↑ (north; e.g., Hungary) and "best" or southwest m↓a↓r↓ for Spain (Barcelona) females. CONCLUSIONS: Our typology and corresponding graphs provide a convenient way to summarize and understand past trends in inequalities in mortality, and hold potential for projecting future trends and target setting.

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