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28 février 2023
info:eu-repo/semantics/openAccess
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Linh Hoang Khanh Dang et al., « The question of the human mortality plateau: Contrasting insights by longevity pioneers », Archined : l'archive ouverte de l'INED, ID : 10.4054/DemRes.2023.48.11
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Background: The debate about limits to the human life span is often based on outcomes from mortality at the oldest ages among longevity pioneers. To this day, scholars disagree on the existence of a late-life plateau in human mortality. Amid various statistical analysis frameworks, the parametric proportional hazards model is a simple and valuable approach to test the presence of a plateau by assuming different baseline hazard functions on individual-level data. Objective: We replicate and propose some improvements to the methods of Barbi et al. (2018) to explore whether death rates reach a plateau at later ages in the French population as it does for Italians in the original study. Methods: We use a large set of exceptionally reliable data covering the most recently extinct birth cohorts, 1883–1901, where all 3,789 members who were born and died in France, were followed from age 105 onward. Individual life trajectories are modeled by a proportional hazards model with fixed covariates (gender, birth cohort) and a Gompertz baseline hazard function. Results: In contrast with Barbi et al. (2018)’s results, our Gompertz slope parameter estimate is statistically different from zero across all model specifications, suggesting death rates continue to increase beyond 105 years old in the French population. In addition, we find no significant birth cohort effect but a significant male disadvantage in mortality after age 105. Conclusions: Using the best data currently available, we did not find any evidence of a mortality plateau in French individuals aged 105 and older. Contribution: The evidence for the existence of an extreme-age mortality plateau in recent Italian cohorts does not extend to recent French cohorts. Caution in generalizations is advised, and we encourage further studies on long-lived populations with high-quality data.