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A Cross-National Analysis of Lifespan Inequality, 1950–2015: Examining the Distribution of Mortality Within Countries

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Abstract

Cross-national health research devotes considerable attention to lifespan and survival rate disparities that are found between countries. However, the distribution of mortality across the world is shaped mostly by what happens within countries. We address this striking gap in the literature by modeling length-of-life inequality for individual nation-states. We use life tables from the United Nation’s (2015) World Population Prospects to estimate inequality levels for 200 countries across 13 waves between 1950 and 2015. We find that lifespan inequality is steadily declining across the world, but that each country’s level of inequality, and the rate at which it declines, vary considerably. Our models account for more than 90% of the longitudinal and cross-sectional variation in country-level lifespan inequality during the 1990–2015 period. Maternal mortality is the strongest predictor in our model, while disease prevalence, access to safe water, and health interventions figure prominently, as well. Gross domestic product per capita shows the expected curvilinear association with lifespan inequality, while primary education (both overall enrollment and gender equity in enrollment), external debt, and migration also play critical roles in shaping health outcomes. By contrast, the distribution of political and economic resources (i.e., democracy and income inequality) is less important.

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Notes

  1. The Gini produces estimates that are downwardly biased. This bias is greatest in small populations and dissipates rapidly with increases in the sample size. In particular, Gini’s downward bias is 10% when the sample is 10, but declines to 1% when the sample increases to 100, and drops to 0.1% when the sample reaches 1000 (Di Maio and Landoni 2015). Fortunately, our sample size is 100,000 for each country, making our downward bias .001% (i.e., 1/1000th of 1%). Several scholars propose an adjustment, replacing n2 with n*(n − 1) (Deaton 1997; Deltas 2003). However, we do not take this additional step (i.e., multiplying all our estimates by 1.00001), as the change in our results would be imperceptible.

  2. Both the Gini and Theil can accommodate population weights applied to the mean (u), the sample size (n), as well as the number of actor-pairs (Gini) or number of ratios (Theil).

  3. It is also possible to decompose lifespan inequality within each country by gender, as life tables are reported for both males and females in World Population Prospects. Past work shows that the mortality distribution across the world for males and females are quite similar (Smits and Monden 2009; Stromme and Norheim 2016) and that cross-national variation in lifespan inequality cannot be attributed to mortality differences across gender (Edwards and Tuljapurkar 2005). Nevertheless, we performed an auxiliary analysis to assess the contribution of gender to lifespan inequality within countries. To do so, we selected the five countries in our data with the largest gender gap in life expectancy for the most recent wave (2010–2015): Syria, Belarus, Russia, Lithuania, and Ukraine. In these countries, women are outliving men by about 10–12 years. We then calculated the mortality distribution for each country by merging the male and female life tables together. The between-gender contribution to each country’s lifespan inequality ranges from 6.4% (Ukraine) to 10.2% (Belarus). Thus, even in those states where the gender gap in mortality is greatest, gender only accounts for about 10% of the mortality distribution.

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Acknowledgements

We thank Amy Kroska, Martin Piotrowski, and Cyrus Schleifer for their generous assistance.

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Authors and Affiliations

  1. Department of Sociology, University of Oklahoma, Norman, OK, 73019, USA

    Rob Clark

  2. Department of Sociology, Indiana University, Bloomington, IN, 47405, USA

    Kara Snawder

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Appendix

Appendix

See Table 3.

Table 3 Descriptive statistics (N = 637)
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Clark, R., Snawder, K. A Cross-National Analysis of Lifespan Inequality, 1950–2015: Examining the Distribution of Mortality Within Countries. Soc Indic Res 148, 705–732 (2020). https://doi.org/10.1007/s11205-019-02216-7

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