The timing of the transition from mortality compression to mortality delay in Europe, Japan and the United States

Abstract

Previous research found evidence for a transition from mortality compression (declining lifespan variability) to mortality delay (increasing ages at death) in low-mortality countries. We specifically assessed the year at which increases in life expectancy at birth transitioned from being predominantly due to mortality compression to being predominantly due to mortality delay in 26 European countries, Japan, and the United States of America (USA), 1950-2014. To unsmoothed age-and sex-specific death rates from the Human Mortality Database, we applied the CoDe (compression and delay) mortality model. Among women, the transition first occurred in the USA around 1950, then in NorthWestern Europe (1955-1970) and Southern Europe (1970-1975), and still later in Eastern Europe. Among men, the transition occurred about 10 years later and is still incomplete in Eastern Europe. We identified four stages: (1) predominance of compression mainly due to mortality declines at young ages, (2) declining importance of mortality compression due to the decreasing impact of mortality declines at young ages, (3) delay becomes predominant due to the increasing impact of mortality delay and the counterbalancing effects of mortality compression/expansion at different ages, and (4) strong predominance of delay accompanied by strong adult mortality declines and declining compression at old ages. Our results suggest that life expectancy and maximum lifespan will increase further. With mortality delay, premature mortality and old-age mortality are shifting towards older ages.

Patterns in age and cause of death contribution to the sex gap in life expectancy: a comparison among ten countries

“…Our findings introduced an additional aspect of an earlier proposal that mortality hazards have, over the years, shifted rigidly to older ages. Our findings showed that with mortality delay (Bongaarts, 2005;Canudas-Romo, 2008;Edwards, 2008;Janssen & de Beer, 2019;Kannisto et al, 1994;Robine, 2008;Zuo et al, 2018), the most relevant age contributors to the sex gap in mortality, with regards to both premature mortality and old-age mortality (e.g., due to cancer, cardiovascular diseases and external causes), indeed shifted towards older ages, but the shift was not rigid. On the contrary, it could involve, depending on the cause of death and the country, either a compression of the most relevant age-contributors or a dispersion.…”

“…Several studies, particularly in low mortality countries, revealed that the absolute difference between male and female mortality risk reaches its maximum at old ages (King et al, 2012). On the one hand, some studies argued that old-age deaths should become compressed at advanced ages; on the other hand, others argued that old-age deaths should become more dispersed with age (Bongaarts, 2005;Canudas-Romo, 2008;Cheung & Robine, 2007;Edwards, 2008;Janssen & de Beer, 2019;Kannisto et al, 1994;Robine, 2008;Robine et al, 2007;Zuo et al, 2018). As survival patterns at old ages become more important in driving the overall mortality decline in low mortality countries, old ages are also becoming more crucial in determining the sex difference in life expectancy.…”

Análise regional do processo de compressão da mortalidade na Argentina

“…Estudios previos en diversos países y regiones del mundo desarrollado han observado evidencia empírica relacionada con el proceso de compresión de la mortalidad (KANNISTO et al, 1994;NUSSELDER;MACKENBACH, 1996;WILMOTH;HORIUCHI, 1999;CHEUNG;ROBINE, 2007;STALLARD, 2016;JANSSEN;DE BEER, 2019). En países en desarrollo existen pocos estudios que analicen el proceso de compresión de la mortalidad, en parte debido a la baja calidad de los datos (GONZAGA et al, 2009).…”

Modal lifespan and disparity at older ages by leading causes of death: a Canada-U.S. comparison

“…50, 65, 75, increases more slowly. It should also be added that M has special mathematical properties, making for instance widely-used mortality models (e.g., Gompertz, logistic, Weibull) more clearly and straightforwardly understandable when M is used in replacement of the original mortality level parameter (Bergeron-Boucher et al 2015 ; Horiuchi et al 2013 ; Janssen and de Beer 2019 ; Missov et al 2015 ).…”