Table 1 provides an overview of the general characteristics of the included studies. Our search identified 41 studies that met the selection criteria. The studies were published between 2018 and 2025 and indicate increasing uptake of the PALY metric over time. The studies cover a diverse range of health conditions, from chronic diseases (e.g. chronic kidney disease, sleep apnoea) to environmental factors (e.g. ambient PM2.5, non-optimum temperatures) and occupational health impacts (e.g. truck driving). The majority of studies were conducted in high-income countries (n = 27, 66%) [10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36], particularly Australia, followed by upper-middle-income countries (n = 10, 24%) [30, 37,38,39,40,41,42,43,44,45]. A small number of studies examined lower-middle-income countries (n = 4) [46,47,48,49]. Most studies (n = 21, 51%) focused on the impact of disease prevention [10,11,12,13, 16, 19, 20, 23, 25, 27, 34, 36,37,38,39,40, 44, 46, 47, 49] rather than disease management (n = 18, 44%) [17, 18, 21, 22, 24, 26, 28,29,30,31,32,33, 42, 43, 45, 48, 50, 51]. However, two studies took a more comprehensive approach, addressing both prevention and disease management [14, 16] (Fig. 1).

Geographic distribution of study locations

The most commonly used modelling approaches were life table models (n = 26, 63%) [10,11,12,13,14, 17, 18, 22, 23, 25,26,27, 29, 31, 33, 35, 37,38,39,40, 42, 44, 46, 47, 49, 50] and dynamic models incorporating both incidence and prevalence (n = 10, 24%) [15,16,17, 19,20,21, 24, 34, 36, 43, 51]. Other studies used time-series analysis, for example studies by Wen et al. [26, 39, 47]. Most studies (n = 26, 63%) [10,11,12,13,14,15, 17, 18, 21, 25,26,27, 29, 31, 32, 37,38,39,40, 44,45,46,47,48,49,50] compared disease cohorts with healthy cohorts, and four studies explicitly quantified early prevention versus standard of care [13, 14,