Life expectancy and lifespan disparity forecasting: a long short-term memory approach

Abstract

After the World War II, developed countries experienced a constant decline in mortality. As a result, life expectancy has never stopped increasing, despite an evident deceleration in developed countries, e.g. England, USA and Denmark. In this paper, we propose a new approach for forecasting life expectancy and lifespan disparity based on the recurrent neural networks with a long short-term memory. This type of neural network leads to predicting future values of longevity indexes while maintaining the significant influence of the past trend, but at the same time adequately reproducing the recent trend into forecasting. The model was applied to five countries for two fitting periods focusing on the forecasting life expectancy and lifespan disparity, both independently and simultaneously at birth and age 65. The results were compared to the projections obtained by four different models, namely, the Double Gap, ARIMA, CoDa and Lee-Carter in the independent case and the first-order Vector Autoregression model in the simultaneous case. Our predictions seem to be coherent with historical trends and biologically reasonable, providing a more accurate portrait of the future life expectancy and lifespan disparity.

Normalized lifespan inequality: disentangling the longevity–lifespan variability nexus

“…For instance, Aburto and colleagues ( 2020 ) showed that the association was stronger when mortality reduction occurred more at younger ages, and weaker when mortality improvement was more observed at older ages. Nigri and colleagues ( 2021a , 2021b ) found that the strength of this association is related to the location and speed when a country moves along the life expectancy distribution.…”

“…This is a question with important theoretical and practical implications. From a theoretical perspective, studying the relationship between average longevity and lifespan variability is fundamental for a proper understanding of the dynamics in human mortality, and is crucial for forecasting future patterns of population health (see related work by Bohk-Ewald et al, 2017 ; Nigri et al, 2021a , 2021b ; Rabbi & Mazzuco, 2021 ). From a practical and policy-making perspective, it is very important to know whether and to what extent the normatively desirable goals of increasing longevity and reducing lifespan variability can be achieved simultaneously or if one can only be attained to the detriment of the other (Benach et al, 2011 , 2013 ; Smits & Monden, 2009 ; Vaupel et al, 2011 ).…”

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