Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Objective This study evaluated how well subjective life expectancy (SLE) predicts mortality and actual life expectancy (ALE), along with factors associated with inaccurate expectations. Methods Using panel data on approximately 2,000 individuals with up to 28 years of follow-up from a nationally representative sample of older Japanese adults, we examined relationships among SLE, actual mortality, and ALE by survival analysis. We also evaluated health and socioeconomic disparities using concentration indices and investigated factors influencing SLE–ALE discrepancies and focal-point (i.e. rounded or anchored estimates) and do-not-know responses. SLE was measured as a self-reported point estimate, whereas ALE mainly came from official records and family reports. Results SLE was significantly associated with both actual mortality and ALE, even after accounting for demographic and socioeconomic variables. Nonetheless, significant inaccuracies remain: approximately 59% of individuals surpassed their expected lifespan. SLE was positively associated with ALE; however, the association was inelastic. Women and those with higher education levels were more likely to outlive their SLE, whereas those in poorer health were less likely to do so. Higher education correlated with fewer focal point responses to the SLE question. Discussion SLE effectively predicts ALE; however, gaps are non-negligible and differ across gender and socioeconomic groups. Offering more precise data, such as sex- and age-specific remaining life expectancy, can enhance SLE formation and lead to more informed economic choices. Highlights Subjective life expectancy is linked to actual mortality and life expectancy. Significant inaccuracies in subjective life expectancy remain. Approximately 59% of individuals outlived their expected lifespan. Women and the better-educated were more likely to outlive their expectations. Providing sex- and age-specific data can improve one’s lifespan expectations.
Source: medRxiv
Language: English
Subfield: Demography
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7204539563