Disease-Related Loss to Government Funding: Longitudinal Analysis of Individual-Level Health and Tax Data for an Entire Country.

OBJECTIVES: The objective of this longitudinal analysis was to estimate funding loss in terms of tax revenue to the New Zealand (NZ) government from disease and injury among working age adults. METHODS: Linked national health and tax data sets of the usually resident population between 2006 and 2016 were used to model 40 disease states simultaneously in a fixed-effects regression analysis to estimate population-level tax loss from disease and injury. To estimate tax revenue loss to the NZ government, we modeled a counterfactual scenario where all disease/injury was cause deleted. RESULTS: The estimated tax paid by all 25- to 64-year-olds in the eligible NZ population was $15 773 million (m) per annum (US dollar 2021), or $16 446 m for a counterfactual as though no one had any disease disease-related income loss (a 4.3% or $672.9 m increase in tax revenue per annum). The disease that-if it had no impact on income-generated the greatest impact was mental illness, contributing 34.7% ($233.3 m) of all disease-related tax loss, followed by cardiovascular (14.7%, $99.0 m) and endocrine (10.2%, $68.8 m). Tax revenue gains after deleting all disease/injury increased up to 65 years of age, with the largest contributor occurring among 60- to 64-year-olds ($131.7 m). Varied results were also observed among different ethnicities and differing levels of deprivation. CONCLUSIONS: This study finds considerable variation by disease on worker productivity and therefore tax revenue in this high-income country. These findings strengthen the economic and government case for prevention, particularly the prevention of mental health conditions and cardiovascular disease.

Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data.

AIM: We aimed to combine Global Burden of Disease (GBD) Study data and local data to identify the highest priority intervention domains for preventing cardiovascular disease (CVD) in the case study country of Aotearoa New Zealand (NZ). METHODS: Risk factor data for CVD in NZ were extracted from the GBD using the "GBD Results Tool." We prioritized risk factor domains based on consideration of the size of the health burden (disability-adjusted life years [DALYs]) and then by the domain-specific interventions that delivered the highest health gains and cost-savings. RESULTS: Based on the size of the CVD health burden in DALYs, the five top prioritized risk factor domains were: high systolic blood pressure (84,800 DALYs; 5400 deaths in 2019), then dietary risk factors, then high LDL cholesterol, then high BMI and then tobacco (30,400 DALYs; 1400 deaths). But if policy-makers aimed to maximize health gain and cost-savings from specific interventions that have been studied, then they would favor the dietary risk domain (e.g., a combined fruit and vegetable subsidy plus a sugar tax produced estimated lifetime savings of 894,000 health-adjusted life years and health system cost-savings of US$11.0 billion; both 3% discount rate). Other potential considerations for prioritization included the potential for total health gain that includes non-CVD health loss and potential for achieving relatively greater per capita health gain for Maori (Indigenous) to reduce health inequities. CONCLUSIONS: We were able to show how CVD risk factor domains could be systematically prioritized using a mix of GBD and country-level data. Addressing high systolic blood pressure would be the top ranked domain if policy-makers focused just on the size of the health loss. But if policy-makers wished to maximize health gain and cost-savings using evaluated interventions, dietary interventions would be prioritized, e.g., food taxes and subsidies.

Economic effects for citizens and the government of a country-level tobacco endgame strategy: a modelling study.

BACKGROUND: Aotearoa-New Zealand (A/NZ) was the first country to pass a comprehensive commercial tobacco endgame strategy into law. Key components include the denicotinisation of smoked tobacco products and a major reduction in tobacco retail outlets. Understanding the potential long-term economic impacts of such measures is important for government planning. DESIGN: A tobacco policy simulation model that evaluated the health impacts of the A/NZ Smokefree Action Plan was extended to evaluate the economic effects from both government and citizen perspectives. Estimates were presented in 2021 US$, discounted at 3% per annum. RESULTS: The modelled endgame policy package generates considerable growth in income for the A/NZ population with a total cumulative gain of US$31 billion by 2050. From a government perspective, increased superannuation payments and reduced tobacco excise tax revenue result in a negative net financial position and a cumulative shortfall of US$11.5 billion by 2050. In a sensitivity analysis considering future labour force changes, the government's cumulative net position remained negative by 2050, but only by US$1.9 billion. CONCLUSIONS: A policy such as the A/NZ Smokefree Action Plan is likely to produce substantial economic benefits for citizens, and modest impacts on government finances related to reduced tobacco tax and increases in aged pensions due to increased life expectancy. Such costs can be anticipated and planned for and might be largely offset by future increases in the size of the labour force and the proportion of people 65+ years old working in the formal economy.

Tobacco endgame intervention impacts on health gains and Maori:non-Maori health inequity: a simulation study of the Aotearoa/New Zealand Tobacco Action Plan.

BACKGROUND: The Aotearoa/New Zealand Government is aiming to end the tobacco epidemic and markedly reduce Maori:non-Maori health inequalities by legislating: (1) denicotinisation of retail tobacco, (2) 95% reduction in retail outlets and (c) a tobacco free-generation whereby people born after 2005 are unable to legally purchase tobacco. This paper estimates future smoking prevalence, mortality inequality and health-adjusted life year (HALY) impacts of these strategies. METHODS: We used a Markov model to estimate future yearly smoking and vaping prevalence, linked to a proportional multistate life table model to estimate future mortality and HALYs. RESULTS: The combined package of strategies (plus media promotion) reduced adult smoking prevalence from 31.8% in 2022 to 7.3% in 2025 for Maori, and 11.8% to 2.7% for non-Maori. The 5% smoking prevalence target was forecast to be achieved in 2026 and 2027 for Maori males and females, respectively.The HALY gains for the combined package over the population's remaining lifespan were estimated to be 594 000 (95% uncertainty interval (UI): 443 000 to 738 000; 3% discount rate). Denicotinisation alone achieved 97% of these HALYs, the retail strategy 19% and tobacco-free generation 12%.By 2040, the combined package was forcat to reduce the gap in Maori:non-Maori all-cause mortality rates for people 45+ years old by 22.9% (95% UI: 19.9% to 26.2%) for females and 9.6% (8.4% to 11.0%) for males. CONCLUSION: A tobacco endgame strategy, especially denicotinisation, could deliver large health benefits and dramatically reduce health inequities between Maori and non-Maori in Aotearoa/New Zealand.

Fifty-year forecasts of daily smoking prevalence: can Australia reach 5% by 2030?

OBJECTIVE: To compare 50-year forecasts of Australian tobacco smoking rates in relation to trends in smoking initiation and cessation and in relation to a national target of ≤5% adult daily prevalence by 2030. METHODS: A compartmental model of Australian population daily smoking, calibrated to the observed smoking status of 229 523 participants aged 20-99 years in 26 surveys (1962-2016) by age, sex and birth year (1910-1996), estimated smoking prevalence to 2066 using Australian Bureau of Statistics 50-year population predictions. Prevalence forecasts were compared across scenarios in which smoking initiation and cessation trends from 2017 were continued, kept constant or reversed. RESULTS: At the end of the observation period in 2016, model-estimated daily smoking prevalence was 13.7% (90% equal-tailed interval (EI) 13.4%-14.0%). When smoking initiation and cessation rates were held constant, daily smoking prevalence reached 5.2% (90% EI 4.9%-5.5%) after 50 years, in 2066. When initiation and cessation rates continued their trajectory downwards and upwards, respectively, daily smoking prevalence reached 5% by 2039 (90% EI 2037-2041). The greatest progress towards the 5% goal came from eliminating initiation among younger cohorts, with the target met by 2037 (90% EI 2036-2038) in the most optimistic scenario. Conversely, if initiation and cessation rates reversed to 2007 levels, estimated prevalence was 9.1% (90% EI 8.8%-9.4%) in 2066. CONCLUSION: A 5% adult daily smoking prevalence target cannot be achieved by the year 2030 based on current trends. Urgent investment in concerted strategies that prevent smoking initiation and facilitate cessation is necessary to achieve 5% prevalence by 2030.

Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities.

BACKGROUND: Simulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities. We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply. METHODS: We developed a disaggregation algorithm that iteratively rescales mortality, incidence and case-fatality rates by time-step of the model to ensure correct total population counts were retained at each step. To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality & morbidity rates, coronary heart disease incidence & case fatality rates; stroke incidence & case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups. The three interventions were then run on top of these scaled BAU scenarios. RESULTS: The algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (HALYs) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population. CONCLUSION: Policy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.

Comparing health gains, costs and cost-effectiveness of 100s of interventions in Australia and New Zealand: an online interactive league table.

BACKGROUND: This study compares the health gains, costs, and cost-effectiveness of hundreds of Australian and New Zealand (NZ) health interventions conducted with comparable methods in an online interactive league table designed to inform policy. METHODS: A literature review was conducted to identify peer-reviewed evaluations (2010 to 2018) arising from the Australia Cost-Effectiveness research and NZ Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programmes, or using similar methodology, with: health gains quantified as health-adjusted life years (HALYs); net health system costs and/or incremental cost-effectiveness ratio; time horizon of at least 10 years; and 3% to 5% discount rates. RESULTS: We identified 384 evaluations that met the inclusion criteria, covering 14 intervention domains: alcohol; cancer; cannabis; communicable disease; cardiovascular disease; diabetes; diet; injury; mental illness; other non-communicable diseases; overweight and obesity; physical inactivity; salt; and tobacco. There were large variations in health gain across evaluations: 33.9% gained less than 0.1 HALYs per 1000 people in the total population over the remainder of their lifespan, through to 13.0% gaining > 10 HALYs per 1000 people. Over a third (38.8%) of evaluations were cost-saving. CONCLUSIONS: League tables of comparably conducted evaluations illustrate the large health gain (and cost) variations per capita between interventions, in addition to cost-effectiveness. Further work can test the utility of this league table with policy-makers and researchers.

Updated Health and Cost Impacts of Electronic Nicotine Delivery Systems, Using Recent Estimates of Relative Harm for Vaping Compared to Smoking.

BACKGROUND: Measuring population health and costs effects of liberalizing access to electronic nicotine delivery systems (ENDS) is an evolving field with high persisting uncertainty. A critical area of uncertainty for policy-makers are estimates of net harms from ENDS relative to cigarettes, therefore, we model these harms using updated estimates incorporating disease specificity. METHODS: We use updated estimates of relative harm of vaping vs smoking, based upon relevant biomarker studies to model the impact of liberalizing access to ENDS in New Zealand (NZ), relative to a ban (where ENDS are not legally available), in an existing proportional multi-state life-table model of 16 tobacco-related diseases. RESULTS: This modeling suggests that ENDS liberalization results in an expected gain of 195 000 quality-adjusted life-years (QALYs) over the remainder of the NZ population's lifespan. There was wide uncertainty in QALYs gained (95% uncertainty interval [UI] = -8000 to 406 000) with a 3.2% probability of net health loss (based upon the number of simulation runs returning positive QALY gains). The average per capita health gain was 0.044 QALYs (equivalent to an extra 16 days of healthy life). Health system cost-savings were expected to be NZ$2.8 billion (US$2.1 billion in 2020 US$; 95%UI: -0.3 to 6.2 billion [2011 NZ$]), with an estimated 3% chance of a net increase in per capita cost. CONCLUSIONS: This updated modeling around liberalizing ENDs in NZ, still suggests likely net health and cost-saving benefits-but of lesser magnitude than previous work and with a small possibility of net harm to population health. IMPLICATIONS: This study found evidence using updated biomarker studies that ENDS liberalization could result in QALY gains across the New Zealand population lifespan that are also cost-saving to the health system. Governments should include the information from these types of modeling studies in their decision-making around potentially improving access to ENDS for existing smokers, while at the same further reducing access to tobacco.

Estimating cardiovascular health gains from eradicating indoor cold in Australia.

BACKGROUND: Exposure to cold indoor temperature (< 18 degrees Celsius) increases cardiovascular disease (CVD) risk and has been identified by the WHO as a source of unhealthy housing. While warming homes has the potential to reduce CVD risk, the reduction in disease burden is not known. We simulated the population health gains from reduced CVD burden if the temperature in all Australian cold homes was permanently raised from their assumed average temperature of 16 degrees Celsius to 20 degrees Celsius. METHODS: The health effect of eradicating cold housing through reductions in CVD was simulated using proportional multistate lifetable model. The model sourced CVD burden and epidemiological data from Australian and Global Burden of Disease studies. The prevalence of cold housing in Australia was estimated from the Australian Housing Conditions Survey. The effect of cold indoor temperature on blood pressure (and in turn stroke and coronary heart disease) was estimated from published research. RESULTS: Eradication of exposure to indoor cold could achieve a gain of undiscounted one and a half weeks of additional health life per person alive in 2016 (base-year) in cold housing through CVD alone. This equates to 0.447 (uncertainty interval: 0.064, 1.34; 3% discount rate) HALYs per 1,000 persons over remainder of their lives through CVD reduction. Eight percent of the total health gains are achievable between 2016 and 2035. Although seemingly modest, the gains outperform currently recommended CVD interventions including persistent dietary advice for adults 5-9% 5 yr CVD risk (0.017 per 1000 people, UI: 0.01, 0.027) and persistent lifestyle program for adults 5-9% 5 yr CVD risk (0.024, UI: 0.01, 0.027). CONCLUSION: Cardiovascular health gains alone achievable through eradication of cold housing are comparable with real-life lifestyle and dietary interventions. The potential health gains are even greater given cold housing eradication will also improve respiratory and mental health in addition to cardiovascular disease.

Closing the gaps in tobacco endgame evidence: a scoping review.

OBJECTIVE: Tobacco endgame policies aim to rapidly and permanently reduce smoking to minimal levels. We reviewed evidence syntheses for: (1) endgame policies, (2) evidence gaps, and (3) future research priorities. DATA SOURCES: Guided by JBI scoping review methodology, we searched five databases (PubMed, CINAHL, Scopus, Embase and Web of Science) for evidence syntheses published in English since 1990 on 12 policies, and Google for publications from key national and international organisations. Reference lists of included publications were hand searched. STUDY SELECTION: Two reviewers independently screened titles and abstracts. Inclusion criteria were broad to capture policy impacts (including unintended), feasibility, public and stakeholder acceptability and other aspects of policy implementation. DATA EXTRACTION: We report the results according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. DATA SYNTHESIS: Eight policies have progressed to evidence synthesis stage (49 publications): mandatory very low nicotine content (VLNC) standard (n=26); product standards to substantially reduce consumer appeal or remove the most toxic products from the market (n=1); moving consumers to reduced risk products (n=8); tobacco-free generation (n=4); ending sales (n=2); sinking lid (n=2); tax increases (n=7); and restrictions on tobacco retailers (n=10). Based on published evidence syntheses, the evidence base was most developed for a VLNC standard, with a wide range of evidence synthesised. CONCLUSIONS: VLNC cigarettes have attracted the most attention, in terms of synthesised evidence. Additional focus on policies that reduce the availability of tobacco is warranted given these measures are being implemented in some jurisdictions.

Disease-related income and economic productivity loss in New Zealand: A longitudinal analysis of linked individual-level data.

BACKGROUND: Reducing disease can maintain personal individual income and improve societal economic productivity. However, estimates of income loss for multiple diseases simultaneously with thorough adjustment for confounding are lacking, to our knowledge. We estimate individual-level income loss for 40 conditions simultaneously by phase of diagnosis, and the total income loss at the population level (a function of how common the disease is and the individual-level income loss if one has the disease). METHODS AND FINDINGS: We used linked health tax data for New Zealand as a high-income country case study, from 2006 to 2007 to 2015 to 2016 for 25- to 64-year-olds (22.5 million person-years). Fixed effects regression was used to estimate within-individual income loss by disease, and cause-deletion methods to estimate economic productivity loss at the population level. Income loss in the year of diagnosis was highest for dementia for both men (US$8,882; 95% CI $6,709 to $11,056) and women ($7,103; $5,499 to $8,707). Mental illness also had high income losses in the year of diagnosis (average of about $5,300 per year for males and $4,100 per year for females, for 4 subcategories of: depression and anxiety; alcohol related; schizophrenia; and other). Similar patterns were evident for prevalent years of diagnosis. For the last year of life, cancers tended to have the highest income losses, (e.g., colorectal cancer males: $17,786, 95% CI $15,555 to $20,018; females: $14,192, $12,357 to $16,026). The combined annual income loss from all diseases among 25- to 64-year-olds was US$2.72 billion or 4.3% of total income. Diseases contributing more than 4% of total disease-related income loss were mental illness (30.0%), cardiovascular disease (15.6%), musculoskeletal (13.7%), endocrine (8.9%), gastrointestinal (7.4%), neurological (6.5%), and cancer (4.5%). The limitations of this study include residual biases that may overestimate the effect of disease on income loss, such as unmeasured time-varying confounding (e.g., divorce leading to both depression and income loss) and reverse causation (e.g., income loss leading to depression). Conversely, there may also be offsetting underestimation biases, such as income loss in the prodromal phase before diagnosis that is misclassified to "healthy" person time. CONCLUSIONS: In this longitudinal study, we found that income loss varies considerably by disease. Nevertheless, mental illness, cardiovascular, and musculoskeletal diseases stand out as likely major causes of economic productivity loss, suggesting that they should be prioritised in prevention programmes.

Failures of quarantine systems for preventing COVID-19 outbreaks in Australia and New Zealand.

OBJECTIVES: To identify COVID-19 quarantine system failures in Australia and New Zealand. DESIGN, SETTING, PARTICIPANTS: Observational epidemiological study of travellers in managed quarantine in Australia and New Zealand, to 15 June 2021. MAIN OUTCOME MEASURES: Number of quarantine system failures, and failure with respect to numbers of travellers and SARS-CoV-2-positive travellers. RESULTS: We identified 22 quarantine system failures in Australia and ten in New Zealand to 15 June 2021. One failure initiated a COVID-19 outbreak that caused more than 800 deaths (the Victorian "second wave"); nine lockdowns were linked with quarantine system failures. The failure risk was estimated to be 5.0 failures per 100 000 travellers passing through quarantine and 6.1 (95% CI, 4.0-8.3) failures per 1000 SARS-CoV-2-positive travellers. The risk per 1000 SARS-CoV-2-positive travellers was higher in New Zealand than Australia (relative risk, 2.0; 95% CI, 1.0-4.2). CONCLUSIONS: Quarantine system failures can be costly in terms of lives and economic impact, including lockdowns. Our findings indicate that infection control in quarantine systems in Australia and New Zealand should be improved, including vaccination of quarantine workers and incoming travellers, or that alternatives to hotel-based quarantine should be developed.

Improving on estimates of the potential relative harm to health from using modern ENDS (vaping) compared to tobacco smoking.

BACKGROUND: Although the harm to health from electronic nicotine delivery systems (ENDS) compared to smoked tobacco remains highly uncertain, society and governments still need to know the likely range of the relative harm to inform regulatory policies for ENDS and smoking. METHODS: We identified biomarkers with specificity of association with different disease groupings e.g., volatile organic compound (VOCs) for chronic obstructive pulmonary disease; and tobacco-specific N´-nitrosamines (TSNAs) and polycyclic aromatic hydrocarbons (PAHs) for all cancers. We conducted a review of recent studies (post January 2017) that compared these biomarkers between people exclusively using ENDS and those exclusively smoking tobacco. The percentage differences in these biomarkers, weighted by study size and adjusted for acrolein from other sources, were used as a proxy for the assumed percentage difference in disease harm between ENDS and smoking. These relative differences were applied to previously modelled estimates of smoking-related health loss (in health-adjusted life-years; HALYs). RESULTS: The respective relative biomarker levels (ENDS vs smoking) were: 28% for respiratory diseases (five results, three studies); 42% for cancers (five results, four studies); and 35% for cardiovascular (seven results, four studies). When integrated with the HALY impacts by disease, the overall harm to health from ENDS was estimated to be 33% that of smoking. CONCLUSIONS: This analysis, suggests that the use of modern ENDS devices (vaping) could be a third as harmful to health as smoking in a high-income country setting. But this estimate is based on a limited number of biomarker studies and is best be considered a likely upper level of ENDS risk given potential biases in our method (i.e., the biomarkers used being correlated with more unaccounted for toxicants in smoking compared to with using ENDS).

The impact of voluntary front-of-pack nutrition labelling on packaged food reformulation: A difference-in-differences analysis of the Australasian Health Star Rating scheme.

BACKGROUND: Front-of-pack nutrition labelling (FoPL) of packaged foods can promote healthier diets. Australia and New Zealand (NZ) adopted the voluntary Health Star Rating (HSR) scheme in 2014. We studied the impact of voluntary adoption of HSR on food reformulation relative to unlabelled foods and examined differential impacts for more-versus-less healthy foods. METHODS AND FINDINGS: Annual nutrition information panel data were collected for nonseasonal packaged foods sold in major supermarkets in Auckland from 2013 to 2019 and in Sydney from 2014 to 2018. The analysis sample covered 58,905 unique products over 14 major food groups. We used a difference-in-differences design to estimate reformulation associated with HSR adoption. Healthier products adopted HSR more than unhealthy products: >35% of products that achieved 4 or more stars displayed the label compared to <15% of products that achieved 2 stars or less. Products that adopted HSR were 6.5% and 10.7% more likely to increase their rating by ≥0.5 stars in Australia and NZ, respectively. Labelled products showed a -4.0% [95% confidence interval (CI): -6.4% to -1.7%, p = 0.001] relative decline in sodium content in NZ, and there was a -1.4% [95% CI: -2.7% to -0.0%, p = 0.045] sodium change in Australia. HSR adoption was associated with a -2.3% [-3.7% to -0.9%, p = 0.001] change in sugar content in NZ and a statistically insignificant -1.1% [-2.3% to 0.1%, p = 0.061] difference in Australia. Initially unhealthy products showed larger reformulation effects when adopting HSR than healthier products. No evidence of a change in protein or saturated fat content was observed. A limitation of our study is that results are not sales weighted. Thus, it is not able to assess changes in overall nutrient consumption that occur because of HSR-caused reformulation. Also, participation into labelling and reformulation is jointly determined by producers in this observational study, impacting its generalisability to settings with mandatory labelling. CONCLUSIONS: In this study, we observed that reformulation changes following voluntary HSR labelling are small, but greater for initially unhealthy products. Initially unhealthy foods were, however, less likely to adopt HSR. Our results, therefore, suggest that mandatory labelling has the greatest potential for improving the healthiness of packaged foods.

Differences in cancer survival by remoteness of residence: an analysis of data from a population-based cancer registry.

PURPOSE: Cancer survival is generally lower for rural compared with urban residents, but findings have been inconsistent. We aimed to assess inequalities in cancer survival by remoteness of residence in Victoria, Australia. METHODS: Incident cancer cases diagnosed in 2001-2015 with 30 cancer types (n = 331,302) were identified through the Victorian Cancer Registry and followed to the end of 2015 through death registries. Five-year net survival was estimated using the Pohar-Perme method and differences assessed by excess mortality rate ratios (EMRRs) using Poisson regression, adjusting for sex, age and year of diagnosis. EMRRs adjusted for socio-economic disadvantage were also estimated. RESULTS: People living outside major cities had lower survival for 11 cancers: esophagus, stomach, colorectum, liver, gallbladder/biliary tract, pancreas, lung, connective/soft tissue, ovary, prostate, kidney. No differences in survival were found for cancers of uterus, small intestine and mesothelioma. After adjusting for socio-economic disadvantage, the observed differences in survival decreased for most cancers and disappeared for colorectal cancer, but they remained largely unchanged for cancers of esophagus, stomach, liver, pancreas, lung, connective/soft tissue, ovary and kidney. CONCLUSION: People with cancer residing outside major cities had lower survival from some cancers, which is partly due to the greater socio-economic disadvantage of rural residents.

Simulating future public health benefits of tobacco control interventions: a systematic review of models.

BACKGROUND: To prioritise tobacco control interventions, simulating their health impacts is valuable. We undertook a systematic review of tobacco intervention simulation models to assess model structure and input variations that may render model outputs non-comparable. METHODS: We applied a Medline search with keywords intersecting modelling and tobacco. Papers were limited to those modelling health outputs (eg, mortality, health-adjusted life years), and at least two of cancer, cardiovascular and respiratory diseases. Data were extracted for each simulation model with ≥3 arising papers, including: model type, untimed or with time steps and trends in business-as-usual (BAU) tobacco prevalence and epidemiology. RESULTS: Of 1911 papers, 186 met the inclusion criteria, including 13 eligible simulation models. The SimSmoke model had the largest number of publications (n=46), followed by Benefits of Smoking Cessation on Outcomes (n=12) and Tobacco Policy Model (n=10). Two of 13 models only estimated deaths averted, 1 had no time steps, 5 had no future trends in BAU tobacco prevalence, 9 had no future trends in BAU disease epidemiology and 7 had no time lags from quitting tobacco to reversal of health harm. CONCLUSIONS: Considerable heterogeneity exists in simulation models, making outputs substantively non-comparable between models. Ranking of interventions by one model may be valid. However, this may not be true if, for example, interventions that differentially affect age groups (eg, a tobacco-free generation policy vs increased cessation among adults) do not account for plausible future trends. Greater standardisation of model structures and outputs will allow comparison across models and countries, and for comparisons of the impact of tobacco control interventions with other preventive interventions.

Impact of tax and tobacco-free generation on health-adjusted life years in the Solomon Islands: a multistate life table simulation.

OBJECTIVE: To estimate health-adjusted life years (HALY) gained in the Solomon Islands for the 2016 population over the remainder of their lives, for three interventions: hypothetical eradication of cigarettes; 25% annual tax increases to 2025 such that tax represents 70% of sales price of tobacco; and a tobacco-free generation (TFG). DESIGN: We adapted an existing multistate life table model, using Global Burden of Disease (GBD) and other data inputs, including diseases contributing >5% of the GBD estimated disability-adjusted life years lost in the Solomon Islands in 2016. Tax effects used price increases and price elasticities to change cigarette smoking prevalence. The TFG was modelled by no uptake of smoking among those 20 years and under after 2016. RESULTS: Under business as usual (BAU) smoking prevalence decreased over time, and decreased faster under the tax intervention (especially for younger ages). For example, for 20-year-old males the best estimated prevalence in 2036 was 22.9% under BAU, reducing to 14.2% under increased tax. Eradicating tobacco in 2016 would achieve 1510 undiscounted HALYs per 1000 people alive in 2016, over the remainder of their lives. The tax intervention would achieve 370 HALYs per 1000 (24.5% of potential health gain), and the TFG 798 HALYs per 1000 people (52.5%). By time horizon, 10.5% of the HALY gains from tax and 8.0% from TFG occur from 2016 to 2036, and the remainder at least 20 years into the future. CONCLUSION: This study quantified the potential of two tobacco control policies over maximum health gains achievable through tobacco eradication in the Solomon Islands.