# Life expectancy and transition in cause of death patterns

Posted on 2022-03-27 by Karl Pettersson. Tags: epidemiology, julia

This week, the Swedish statistical agency has published life tables for Sweden 2021 (Statistics Sweden 2022). With the first waves of the COVID pandemic, life expectancy at birth decreased from 84.73 years for females and 81.34 years for males in 2019 to 84.29/80.60 years in 2020. For 2021, the numbers were again 84.82/81.21 years. This reflects, of course, the decreased COVID mortality due to vaccination. Moreover, the flu A(H3N2) wave, which peaked around Christmas with rather high rates of illness among young people, did not cause substantial excess mortality, which may, in part, be due to people with respiratory symptoms having less contacts than usual with older people and other risk groups.

The increase in life expectancy in Sweden, and many other countries, up until the mid-20th century was largely driven by decreasing childhood mortality, which also caused changes in the cause of death patterns, with directly communicable diseases becoming less common relative to age-related diseases, such as circulatory diseases and cancer. In contrast, the continued increase in rich countries after that, which was temporarily interrupted by the pandemic, is largely due to decreased mortality at older ages.

Vishnevsky (2017) discusses the development in life expectancy and causes of death after 1960 in Russia, compared to high-income countries, in particular Western European countries. In the EU-15 countries, age-standardised mortality rates from circulatory, external and respiratory causes have decreased greatly since 1970, while cancer mortality has decreased modestly. The proportion of deaths from circulatory causes has also decreased (from nearly 50 percent to about 30 percent), while the proportion of deaths from cancer has increased (from about 20 percent to about 30 percent). No such changes have occurred in Russia, where life expectancy has not improved much since the 1960s (although it has improved relative to the dramatic increases in mortality during the 1990s).

From this, one might conclude that the increased life expectancy in rich countries largely has been about decreased circulatory mortality. However, Vishnevsky points out that focusing on standardised rates for all ages hides a significant increase in life expectancy for those dying also of non-circulatory causes. In Sweden, for example, the life expectancy for people dying of cancer or other neoplasms increased 8.2 years for females and 7.6 years for males during to period 1960–2010. The corresponding increase for circulatory diseases (where life expectancy was higher than for cancer already in 1960) is 8.0/6.8 years. It is clear that this reflects a marked decrease in cancer mortality at young ages, a point similar to what has been made earlier by researchers like Riggs (1994).

One factor not discussed by Vishnevsky is the impact of changing practices in reporting causes of death over a long time. For example, the increase in life expectancy has been particularly strong for the residual category, other diseases, in Sweden, with 20.0 years for females and 17.8 years for males. This category includes dementia, which was a rare underlying cause of death in 1960. Back then, most people with dementia probably had circulatory or respiratory causes reported instead, and the other category was dominated by other causes, with a much lower life expectancy.

In light of this, it may be interesting to compare the correlation between general life expectancy and proportion of deaths ascribed to different causes in varying countries more in detail. I made a Julia package, MortIntl, which can be used to analyse such trends, based on cause-specific mortality data from WHO (2022) and life tables from University of California, Berkeley and Max Planck Institute for Demographic Research (2022). It uses a configuration similar to my earlier Mortchartgen, which I have used to generate Mortality Charts, but extracts data directly from the data files using AWK instead of relying on a SQL database.

Fig. 1 and fig. 2 show female and male life expectancy at birth in relation to proportion of deaths from circulatory causes (as defined for Mortality Charts) for the Nordic and Baltic countries, with Iceland excluded due to small population.1

The charts clearly show that improvements in life expectancy continued for a long time among, for example, females in Finland and Sweden, after circulatory causes became dominant, without any substantial change in the proportion of deaths ascribed to these causes. That proportion really started decreasing after the 1980s, when dementia became more commonly reported (see Mortality Charts).

The Baltic countries, especially Estonia, have in recent years attained a female life expectancy close to the Nordic countries, but the proportion of circulatory deaths there is higher than it has been in the Nordic countries at any point in time. In contrast, Denmark, has had a lower proportion of circulatory deaths than the other Nordic countries, a pattern which has been more pronounced in recent decades. The difference in circulatory deaths between Denmark and Estonia in recent years, when both have had similar life expectancy among females, is greater than the temporal variation, over nearly 70 years, in any of the Nordic countries.

From this, it seems that clear that great caution is warranted in drawing any epidemiological conclusions from trends for officially reported circulatory mortality over all ages.

## References

Riggs, J. E. 1994. “The cohort mortality perspective: The emperor′s new clothes of epidemiology, an illustration using cancer mortality.” Regulatory Toxicology and Pharmacology 19 (2): 202–210. doi:10.1006/rtph.1994.1018.
Statistics Sweden. 2022. “Life table by sex and age.” https://www.statistikdatabasen.scb.se/goto/en/ssd/LivslangdEttariga.
University of California, Berkeley and Max Planck Institute for Demographic Research. 2022. Human Mortality Database.” https://www.mortality.org.
Vishnevsky, Anatoly. 2017. “Mortality in russia: The second epidemiological revolution that never was.” Demographic Review 2 (5): 4–33. doi:10.17323/demreview.v2i5.5581.
WHO. 2022. “WHO Mortality Database.” https://www.who.int/data/data-collection-tools/who-mortality-database.

1. The charts can be generated by cloning the blog repository, installing MortIntl with the relevant data files, as described in the documentation, and running circall_e0_baltnord.jl in the subdirectory postdata/2022-03-27-transition.↩︎