Method of decomposition for the assessment of life expectancy trends with example of analysis of life expectancy stagnation in England and Wales

Abstract

Demographers often compare populations using aggregated scalar indices, for instance, the life expectancy or total fertility rate. These indices are functions of event-rates across various dimensions including age, cause of death, population group, etc. The classic decomposition task is to attribute the total between-population difference in the aggregate index into contributions from differences in the covariates. In the case of a non-linear function, this task is not trivial. There are several approaches to solve this task. We extend the decomposition agenda further and introduce a second dimension – time. The complex approach is based on using classic decomposition methods to build decomposition surfaces and contour decomposition to assess the influence of time trends and initial conditions on the final difference. We illustrate this approach using an example of recent stagnation of mortality improvement in England and Wales. We analyze the unfavorable trend observed in the UK since 2011 in the context of changes over the long-term and in relation to a group of 22 other high-income countries. The recent slowdown mortality improvement in England and Wales was steeper than elsewhere and driven by relative disadvantage at all adult ages. Mortality slow-down at ages under 65 contributed more than one half to the overall increase in the LE disadvantage of E&W for men and more than 1/3 women, respectively. E&W has lost its former advantage in mortality of adults aged 15 to 50. Since the mid-2000s for the first time, mortality rates in England and Wales at ages 25-50 years are appreciably higher than in the comparator group.

References:

Leon, D.A.; Jdanov, D.A.; Shkolnikov V.M.: Trends in life expectancy and age-specific mortality in England and Wales 1970-2016 in comparison with a set of 22 high income countries. Lancet Public Health (forthcoming)

Jdanov, D. A.; Shkolnikov, V. M.; Van Raalte, A. A.; Andreev, E. M. Decomposing current mortality differences into initial differences and differences in trends: the contour decomposition method.  Demography, 54:4, 1579-1602 (2017). DOI: http://dx.doi.org/10.1007/s13524-017-0599-6

Biography

Dmitri Jdanov is Head of the Laboratory for Demographic Data at the Max Planck Institute for Demographic Research, Germany, and Chief Research Fellow at the Research University Higher School of Economics, Russia. Since 2000 he works for the Human Mortality Database, currently as head of the MPIDR team. He is also director of the Human Fertility Database project and the Human Cause-of-Death Database. Dmitri Jdanov is demographer and mathematician who has extensive experience in the collection, assessment, and usage of demographic and epidemiological data; his current research focuses on inequality in mortality, quality of demographic data, and health of the aging population.