At a Glance
Methods of Measurement and Decomposition in Mortality Studies
Conducted by Vladimir M. Shkolnikov; Dmitri A. Jdanov, Georg Wenau, Alyson van Raalte; in Collaboration with Evgeny M. Andreev (National Research University – Higher School of Economics, Moscow, Russian Federation), David A. Leon (London School of Hygiene & Tropical Medicine, United Kingdom)
The project includes studies that develop methods for the measurement and analysis of mortality and the length of life, with an emphasis on disparities within and between national populations.
A chain of studies was initiated by our core study of 2002. It introduced a universal method (the stepwise replacement algorithm) for decomposing differences between two values of life expectancy, health expectancy, the total fertility rate, or any other aggregate demographic measure on a variety of dimensions such as age, cause of death, birth order, and population sub-group. The formula for the decomposition of changes in healthy life expectancy (deduced using the stepwise replacement algorithm) allows splitting the overall change not only by contributions of health and mortality but also by age. This is an important advantage of our formula over alternative decomposition methods.
In 2017, the decomposition methodology was complemented by a new contour decomposition method that further develops the stepwise replacement algorithm. It allows splitting a present-time difference between the values of an aggregate index (such as life expectancy) according to the impacts of past conditions and mortality trends on the two populations. This method was applied in a study of ours in 2019 to identify components for the growing life-expectancy disadvantage of England and Wales compared to the rich countries' mainstream. We have found that the disadvantage was induced by a slowdown among the elderly and by mortality excess at young adult and midlife ages.
The stepwise replacement algorithm was applied to solve two novel decomposition tasks. In studies published in 2016 and 2017, we decomposed changes in the amount of inter-country and inter-regional life-expectancy variation to assess the contributions of different age groups, countries, and regions to the growing disparity. In a study of 2019, we used the same method to decompose the East-West life expectancy divide in Germany at age 65 as to the weights of pension income groups and mortality within these groups. The analysis suggests that deteriorating income structure in the East represents a health threat, potentially slowing the expectancy increase.
Another study of ours on socioeconomic mortality differences in Germany of 2019 assessed for the first time ever differences related to education and current income among the economically active population. The study is based on large administrative data of the German Pension Fund. It highlights the particular importance of socioeconomic inequalities in health in the East.
In a technical report (2018), we provided a working instrument for the estimation of two demographic models of cancer, based on synthetic-cohort increment-decrement life tables. Our models allow for estimate probabilities of survival and survival times and for shares of population and total population lifetime spent with cancer.
Aging, Mortality and Longevity, Health Care, Public Health, Medicine, and Epidemiology, Historical Demography, Statistics and Mathematics
Finland, India, Russian Federation, United Kingdom, USA, World
BMJ Open 9:10, e028001–e028001. (2019)
The Lancet Public Health 4:11, e575–e582. (2019)
The Lancet Public Health 4:4, e181–e188. (2019)
Journal of Epidemiology and Community Health 73:7, 605–611. (2019)
MPIDR Technical Report TR-2018-004. (2018)
Demography 54:4, 1579–1602. (2017)
MPIDR Working Paper WP-2017-016. (2017)
European Journal of Population 33:5, 733–763. (2017)
Voprosy Statistiki, 72–82. (2016)
Population Health Metrics 14:29, 1–19. (2016)
Demographic Review 2:1, 24–55. (2015)
Population Health Metrics 13:23, 1–25. (2015)
MPIDR Working Paper WP-2014-010. (2014)
Demography 50:5, 1615–1640. (2013)
MPIDR Technical Report TR-2012-002. (2012)
European Journal of Public Health 22:4, 602–604. (2012)
Journal of Epidemiology and Community Health 66:6, e7–e7. (2012)
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Population Studies 65:1, 73–89. (2011)
Demography 48:1, 211–239. (2011)
Demografische Forschung Aus Erster Hand 8:2, 3–3. (2011)
MPIDR Technical Report TR-2010-006. (2010)
MPIDR Technical Report TR-2010-001. (2010)
MPIDR Technical Report TR-2010-002. (2010)
MPIDR Working Paper WP-2009-013. (2009)
MPIDR Working Paper WP-2009-042. (2009)
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