ShapleyHALE: Sağlık Ayarlı Yaşam Beklentisi Değişiminin Sıralama-Serbest Ayrıştırması İçin Bir R Paketi

Özet (abstract)

Conventional decompositions of health‑adjusted life expectancy (HALE) change assume that diseases act independently and produce results that depend on the order in which causes are evaluated. They also cannot quantify whether the combined effect of two causes is larger or smaller than the sum of their separate effects. The Shapley value from cooperative game theory provides an ordering‑free and additive attribution that can quantify population‑level complementarities among causes. Its adoption in population health has been hindered by computational complexity and the absence of reusable software. We developed shapleyHALE , an open‑source R package that performs a complete Shapley decomposition of HALE change. The package treats each disease as a player and averages its marginal contribution over 5,000 randomly sampled cause orderings by default. It yields a unique and additive attribution with no residual. Mortality‑driven and disability‑driven components are separated. Second‑order Shapley interaction indices are computed to quantify pairwise synergies and antagonisms. A parametric bootstrap with 1,000 iterations propagates input data uncertainty to all outputs by default. The package accepts standard age‑cause matrices of mortality and morbidity rates. It is compatible with any population‑based surveillance data. We used Global Burden of Disease Study 2023 data for 22 causes across five Socio‑demographic Index (SDI) quintiles over 1990–2023. The decomposition ranked cause contributions, separated mortality from disability effects, and quantified pairwise interactions. Mental disorders appeared among the 10 leading causes in the Low, Middle, and High SDI groups. They were a negative contributor in each group, with values of −0.336 years (95% UIs : −0.482 to −0.252), −0.295 years (−0.440 to −0.213), and −0.342 years (−0.518 to −0.234), respectively. The separation of mortality and disability effects showed that mental disorders and diabetes and kidney diseases contributed negatively primarily through disability. The interaction analysis revealed predominantly positive complementarities among major causes. Mental disorders exhibited systematic antagonism with other major causes in every group where they appeared among the top 10. shapleyHALE provides an open‑source and ordering‑free decomposition tool for HALE with population‑level interaction indices. It offers a standardised and reproducible platform to generate evidence for integrated and multi‑disease health strategies in an era of rising multimorbidity. Not applicable.

Yazarların özeti; kaynağından alınmıştır. BMC Medical Research Methodology, 2026 · DOI ↗