Hansen · Journal of health economics 2025 · mathematical and demographic modeling study · n=?

How do we age? A decomposition of Gompertz law.

Cited 4 times in the scientific literature.

Level 5 - mechanism / opinion, no new human data

Level 5 by design analogy (theoretical mathematical decomposition and demographic modeling)

PubMed 40127516 · doi:10.1016/j.jhealeco.2025.102988 · record verified 2026-08-30

What was done

The authors formulated a mathematical framework decomposing Gompertz's law of exponential mortality into two constituent parts: an exponential accumulation of health deficits (measured by the frailty index and derived from the self-productivity of deficits) and a power law relationship linking the frailty index to mortality rates. They evaluated the consistency of this decomposition across sexes, countries, and time periods, and applied it to infer biological aging in historical populations, including Australians in 1940 and Swedes in 1770.

What was found

The abstract provides no specific numerical values, effect sizes, or goodness-of-fit metrics. It reports conceptually that Gompertz's law can be decomposed into exponential frailty growth and a power-law frailty-mortality link, and that this framework can infer historical population health states from aggregate mortality rates.

Why it matters

This framework links chronological mortality patterns to biological health deficits, offering a method to estimate population-level biological aging and health status using standard demographic mortality tables.

Limits

The abstract reports no empirical sample sizes, data sources, or quantitative error margins. As an aggregate demographic modeling approach, findings rely on theoretical assumptions regarding deficit accumulation that may not capture individual-level physiological variation or specific disease etiologies.

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