2017年-世界发展银行全球_Modeling_the_Long-Term_Health_and_Cost_Impacts_of_Reducing_Smoking_Prevalence_through_Tobacco_Taxation_in_Ukraine_45页_6mb

Summary of the Report: Modeling the Long-Term Health and Cost Impacts of Reducing Smoking Prevalence Through Tobacco Taxation in Ukraine

Core Content

This report presents the results of a microsimulation model designed to estimate the long-term health and economic impacts of increasing tobacco excise taxes in Ukraine. The model simulates the effects of a tax increase implemented in 2017 and forecasts outcomes up to 2035, comparing them to a baseline scenario where no tax changes occur.

Main Points

• Smoking as a Major Health Risk: Smoking is a leading cause of preventable premature deaths and contributes to a range of non-communicable diseases (NCDs), including coronary heart disease (CHD), stroke, chronic obstructive pulmonary disease (COPD), and lung cancer.

• Ukraine's Tobacco Control Progress: Ukraine has implemented comprehensive tobacco control policies since 2005, including smoke-free legislation, graphic health warning labels, and bans on tobacco advertising. These efforts have led to significant declines in smoking prevalence, although challenges remain.

• Taxation as a Tool for Reduction: The report evaluates the impact of a 40% increase in the minimum specific excise tax on cigarettes. This policy was intended to increase prices and reduce consumption, but in practice, tobacco companies responded with "price wars," leading to increased consumption.

• Modeling Approach: A microsimulation model was used to project the health and economic consequences of the tax increase. The model is based on population data, smoking prevalence, and disease risk factors, and it accounts for changes in smoking behavior over time.

• Scenario Assumptions: The model compares a "baseline" scenario (no tax changes) with a "tax increase" scenario. The tax increase scenario assumes a 5.61% reduction in male smoking uptake and a 10.2% reduction in cigarette consumption overall, with the assumption that these changes occur immediately in 2017 and follow a linear trend.

• Model Outputs:

  • Health Impacts: The tax increase is projected to avoid 126,730 new cases of smoking-related disease, 29,172 premature deaths, and 267,098 potential years of life lost by 2035.
  • Economic Impacts: The tax increase is expected to avoid 1.5 billion UAH in direct healthcare costs and 16.5 billion UAH in premature mortality costs by 2035.
  • Smoking Prevalence Trends: By 2035, smoking prevalence is projected to decrease from 45% among men and 11% among women in 2015 to 38.2% and 5.0%, respectively.

Key Information

Model Overview

• A microsimulation model was used, which simulates a virtual population of Ukraine based on known population statistics.
• The model is based on the UK Health Forum's microsimulation framework, originally developed for the English government's Foresight enquiry.
• The model includes five modules and accounts for disease incidence, mortality, and health costs, as well as changes in smoking behavior over time.

Data Sources

• Smoking Prevalence Data: Extracted from the 2015 Annual Household Survey and extrapolated for 2035.
• Disease Data: Derived from the Global Burden of Disease (GBD) database, including incidence, mortality, and survival data.
• Population Data: Taken from the UN population prospects database, including age and sex distributions, fertility rates, and mortality rates.

Disease Modeling

• The following smoking-related NCDs were modeled: CHD, stroke, COPD, and lung cancer.
• Relative risks (RR) for these diseases in smokers versus non-smokers were obtained from peer-reviewed literature.
• Ex-smokers' relative risks were modeled using a decay function, which reflects reduced risk over time since cessation.

Economic Modeling

• Direct healthcare costs were estimated from the literature, while indirect costs (e.g., lost productivity) were not included due to lack of data.
• Premature mortality costs were calculated using average annual income and GDP loss estimates, assuming death before age 65.
• A discount rate of 5% was applied, as used in Russia, to calculate the present value of future costs.

Limitations

• No data on survival for the modeled NCDs were available, so survival rates were estimated using DISMOD equations.
• Limited data on ex-smokers and social group differences constrained the model's accuracy.
• The model does not account for future policy changes or technological advancements.
• No change in secondhand smoke exposure was modeled.
• The baseline is static, not dynamic, which may not reflect real-world changes.

Key Findings

• Health Impacts: The tax increase is expected to lead to significant reductions in smoking-related disease cases and premature deaths, particularly in men.
• Economic Impacts: The health and mortality cost savings are substantial, with over 16 billion UAH in premature mortality costs avoided by 2035.
• Behavioral Response: The model assumes an immediate and linear effect of tax increases on smoking behavior, but real-world data shows that tobacco companies may counteract these effects through price manipulation.

Conclusion

The model highlights the potential long-term health and economic benefits of increasing tobacco excise taxes in Ukraine. However, it also underscores the importance of sustained and comprehensive tobacco control policies to ensure these benefits are realized, as the tobacco industry's responses can undermine the intended effects. The results provide a critical basis for evaluating the effectiveness of taxation as a public health intervention in Ukraine.