BACKGROUND: Many governments have in recent years been setting targets to eradicate commercial tobacco supply/use, i.e., achieve a ‘tobacco endgame’, as part of their health agenda. While a target has recently been set in Australia’s National Tobacco Strategy, of ≤5% daily smoking prevalence by 2030, this fails to explicitly address the inequity in smoking rates across sociodemographic groups. We aimed to address the impact of excluding equity consideration in the target, by quantifying the future possible health impact of two hypothetical scenarios: 1. a 'modest' population-level endgame being achieved by 2030 (with remaining inequity), 2. an equitable endgame where all strata by geographic remoteness and socioeconomic status (SES) achieve the 2030 target.
METHODS: A Markov process was constructed to simulate future smoking behaviours in the Australian population, with a proportional multi-state life-table that quantifies the health impacts of 31 smoking-related diseases. This model is utilised to quantify the difference in deaths and health-adjusted life years (HALYs) for the Australian population under different hypothetical endgame scenarios in comparison to ‘business-as-usual’ (BAU), over 20 years, across sociodemographic groups.
RESULTS: In comparison to BAU, the modest scenario would result in 16,700 (95% uncertainty interval [UI] 13,200- 21,800) deaths being averted, and 122,000 (95% UI 95,900-158,000) HALYs being gained, over the next 20 years. The equitable scenario resulted in a 1.3-fold increase in these health gains, with the greatest improvement being for more disadvantaged population groups.
CONCLUSIONS: Our findings highlight the importance of future tobacco policies having an equity focus. The results also show the need for cessation-focused policies to achieve a rapid endgame. This analysis provides a comparative baseline for future modelling of specific tobacco control interventions in Australia, including population-level and targeted interventions. The model includes novel advancements, incorporating population heterogeneity and pack-year disease risk quantification, which can be applied to other contexts.