BackgroundCountries are increasingly considering how to reduce or even end tobacco consumption, and raising tobacco taxes is a potential strategy to achieve these goals. We estimated the impacts on health, health inequalities, and health system costs of ongoing tobacco tax increases (10% annually from 2011 to 2031, compared to no tax increases from 2011 [“business as usual,” BAU]), in a country (New Zealand) with large ethnic inequalities in smoking-related and noncommunicable disease (NCD) burden.Methods and FindingsWe modeled 16 tobacco-related diseases in parallel, using rich national data by sex, age, and ethnicity, to estimate undiscounted quality-adjusted life-years (QALYs) gained and net health system costs over the remaining life of the 2011 population (n = 4.4 million). A total of 260,000 (95% uncertainty interval [UI]: 155,000–419,000) QALYs were gained among the 2011 cohort exposed to annual tobacco tax increases, compared to BAU, and cost savings were US$2,550 million (95% UI: US$1,480 to US$4,000). QALY gains and cost savings took 50 y to peak, owing to such factors as the price sensitivity of youth and young adult smokers. The QALY gains per capita were 3.7 times greater for Māori (indigenous population) compared to non-Māori because of higher background smoking prevalence and price sensitivity in Māori. Health inequalities measured by differences in 45+ y-old standardized mortality rates between Māori and non-Māori were projected to be 2.31% (95% UI: 1.49% to 3.41%) less in 2041 with ongoing tax rises, compared to BAU. Percentage reductions in inequalities in 2041 were maximal for 45–64-y-old women (3.01%). As with all such modeling, there were limitations pertaining to the model structure and input parameters.ConclusionsOngoing tobacco tax increases deliver sizeable health gains and health sector cost savings and are likely to reduce health inequalities. However, if policy makers are to achieve more rapid reductions in the NCD burden and health inequalities, they will also need to complement tobacco tax increases with additional tobacco control interventions focused on cessation.

ACTRN12609000779279.

Implementing endgame strategies is needed to achieve tobacco endgame targets and reduce inequalities in smoking. Given such strategies are new, modelling studies provide provisional information on what approaches may be best.

These tobacco outlet reductions reduced smoking prevalence, achieved health gains and saved health system costs. Effects would be larger if outlet reductions have additional spill-over effects (eg, smoking denormalisation). While these interventions were not as effective as tobacco tax increases (using the same model), these and other strategies could be combined to maximise health gain and to maximise cost-savings to the health system.

BackgroundObesity is an important risk factor for many chronic diseases. Mobile health interventions such as smartphone apps can potentially provide a convenient low-cost addition to other obesity reduction strategies.ObjectiveThis study aimed to estimate the impacts on quality-adjusted life-years (QALYs) gained and health system costs over the remainder of the life span of the New Zealand population (N=4.4 million) for a smartphone app promotion intervention in 1 calendar year (2011) using currently available apps for weight loss.MethodsThe intervention was a national mass media promotion of selected smartphone apps for weight loss compared with no dedicated promotion. A multistate life table model including 14 body mass index–related diseases was used to estimate QALYs gained and health systems costs. A lifetime horizon, 3% discount rate, and health system perspective were used. The proportion of the target population receiving the intervention (1.36%) was calculated using the best evidence for the proportion who have access to smartphones, are likely to see the mass media campaign promoting the app, are likely to download a weight loss app, and are likely to continue using this app.ResultsIn the base-case model, the smartphone app promotion intervention generated 29 QALYs (95% uncertainty interval, UI: 14-52) and cost the health system US $1.6 million (95% UI: 1.1-2.0 million) with the standard download rate. Under plausible assumptions, QALYs increased to 59 (95% UI: 27-107) and costs decreased to US $1.2 million (95% UI: 0.5-1.8) when standard download rates were doubled. Costs per QALY gained were US $53,600 for the standard download rate and US $20,100 when download rates were doubled. On the basis of a threshold of US $30,000 per QALY, this intervention was cost-effective for Māori when the standard download rates were increased by 50% and also for the total population when download rates were doubled.ConclusionsIn this modeling study, the mass media promotion of a smartphone app for weight loss produced relatively small health gains on a population level and was of borderline cost-effectiveness for the total population. Nevertheless, the scope for this type of intervention may expand with increasing smartphone use, more easy-to-use and effective apps becoming available, and with recommendations to use such apps being integrated into dietary counseling by health workers.