TY  - JOUR
A1  - Sanchez-Cespedes, Lina María
T1  - Modifying model life tables to derive mortality curves for countries with excess mortality
Y1  - 2025/07/08
JF  - Demographic Research
JO  - Demographic Research
SN  - 1435-9871
SP  - 21
EP  - 46
DO  - 10.4054/DemRes.2025.53.2
VL  - 53
IS  - 2
UR  - https://www.demographic-research.org/volumes/vol53/2/
L1  - https://www.demographic-research.org/volumes/vol53/2/53-2.pdf
L2  - https://www.demographic-research.org/volumes/vol53/2/53-2.pdf
L3  - https://www.demographic-research.org/volumes/vol53/2/files/readme.53-2.txt
L3  - https://www.demographic-research.org/volumes/vol53/2/files/demographic-research.53-2.zip
N2  - Background: Model life tables are valuable tools for filling gaps in mortality data when estimates are only available for specific age groups, and have been used in many countries. However, their relevance has declined, as they fail to account for cause-specific mortality, leading to biased results in populations with significant differences from the reference data, such as countries with high levels of violence or road accidents. 

Objective: This study examines whether traditional model life tables can still be used to estimate mortality curves and their backward projection in countries with excess mortality due to external causes. 

Methods: We propose a simple method to adjust Coale–Demeny or UN model life tables in order to estimate mortality curves for countries with excess mortality. The method identifies the most appropriate model life table that reflects the mortality pattern without excess deaths and adjusts it to the actual one by considering external-cause mortality rates. This allows for estimating life expectancy differences with and without excess mortality. 

Results: We exemplify the method with the case of Colombia. The results show a difference in life expectancy at birth between no excess mortality and excess mortality, Δe(0)no-excess and excess, of about –5 years in the 1990s, reaching –5.47 in 2000 and –2.39 in 2017. 

Conclusions: This variation reflects key historical moments related to drug trafficking, the armed conflict, and shifts in government policy. 

Contribution: This method estimates mortality curves that more accurately reflect the realities of countries with high external-cause mortality, providing a better understanding of its impact on life expectancy, and improving backward population projections. 

ER  -