OBJECTIVES: We sought to quantify the mortality attributable to smoking across the lifetime, and assess the potential effects of several smoking intervention scenarios in the Australian population.

METHODS: Using life table modelling in combination with a Markov model we estimated a smoking-related mortality in a population for which the following data inputs are available: annual mortality by sex and age, smoking prevalence, population attributable deaths due to smoking. Decision analysis was applied to allow for the assessment of various smoking intervention scenarios. An intervention achieving a relative reduction in smoking prevalence of 10% was modelled as per 2012-2018 National Tabacco Strategy in Australia. A 5.0% annual discount rate is applied to all future, and the baseline year of the model was 2017. Outcome of interest was relative difference in years of life lived, relative difference in deaths, however model can capture quality of life and societal costs.

RESULTS: The results are expressed based on of the total resident Australian population (17,754,150 people, aged between 20-85) in 2016. Over a 20-year period, with no intervention (current smoking status quo) women and men experienced an estimated 1.8 and 3.8 million deaths, respectively. When the intervention was applied women and men experienced an estimated 1.7 and 3.7 million deaths, respectively. Expressed as relative change, this intervention resulted in 3.8% fewer deaths in men and 3.4% fewer deaths in women, corresponding to a 1.7% and 2.3% more years of life lived, compared with no intervention.

CONCLUSIONS: We present an easy-to-apply smoking model that captures and quantifies burden of disease and societal costs, which will help with decision-making in clinical practice, public health and health policy.