About
Welcome to Path to Smoke-Free
Sweden’s experience has created a dramatic gap: a 5.3% smoking rate versus the global average of 20.9% and the EU average of 24%. This milestone positions Sweden to reach smoke-free status 15 years ahead of the EU’s 2040 target. While Sweden has implemented traditional public policies and regulatory frameworks – including the WHO’s Framework Convention on Tobacco Control (WHO FCTC) recommendations, MPOWER initiatives, and EU directives and recommendations – becoming smoke-free requires a comprehensive approach.
Through analysis and empirical evidence gathered from ex-smokers in Sweden, we have identified three crucial elements that are an integral part of Sweden’s comprehensive approach:
1
Accessibility
Ensuring innovative nicotine products are available through conventional and online retail channels, with comprehensive and relevant information for adults.
2
Acceptability
Leveraging a variety of flavors and nicotine levels in innovative nicotine products to provide a compelling and realistic alternative to smoking.
3
Affordability
Ensuring that taxes on innovative nicotine products remain at a level that does not discourage adults from choosing to use them over smoking due to cost.
Our website provides a unique analytical tool that reassesses global tobacco control policies through these three critical lenses. Using the comprehensive data from the Effective Anti-Smoking Policies Global Index as our foundation, we evaluate how the approaches of different nations align with or diverge from Sweden’s experience.
Visitors to our platform can:
- Compare their country’s approach against Sweden’s benchmark
- Access detailed analysis of policy effectiveness across multiple nations
- Explore interactive visualizations of global progress achieving smoke-free targets
- Understand the practical implications of different approaches
- Learn from real-world success stories and empirical evidence
By combining rigorous analysis with real-world insights from successful quitters, we offer a unique perspective in relation to smoke-free targets. Our platform serves as both a resource hub, helping policymakers, researchers, and health professionals understand and implement more effective strategies to achieve smoke-free targets.
The stark success of Sweden’s comprehensive approach – achieving smoking rates nearly 80 percent lower than the EU average – demonstrates the potential impact of measures that embrace innovation while maintaining strong public health protection. Through this platform, we aim to accelerate global progress toward a healthier, smoke-free future by sharing valuable information.
Together, we can work toward a future where smoking-related illness becomes a thing of the past, guided by a blend of traditional measures and innovation.
What is “smoke-free”?
Global public health experts consider a country to be “smoke-free” when its smoking incidence is no more than 5% of the adult population.
The WHO’s Framework Convention on Tobacco Control (WHO FCTC) recommendations, MPOWER initiatives, and EU directives and recommendations have made invaluable contributions to reducing smoking. Sweden’s 5.3% smoking rate, however, is significantly lower than the global average of 20.9% and the EU average of 24%, which has prompted research on the public policies and regulatory frameworks applicable to smoking but also the use of innovative nicotine products and surveys among ex-smokers.
Ex-smokers in Sweden consistently identified elements within the Accessibility, Acceptability, and Affordability of innovative nicotine products as having empowered them to move and stay away from smoking.
Methodology
We have sourced information on public policy and regulation from the Smoke-Free Innovation Index and research conducted by We Are Innovation. To identify the 3 As that empower smokers to move and stay away from smoking, we complemented that information with findings from surveys conducted by Ipsos among ex-smokers in Sweden.
We have drawn data from the WHO and the European Commission to estimate smoking prevalence and used interpolation to fill in missing data points.
To forecast smoking prevalence declines beyond the latest available data point, we have calculated that the trend model applies an exponential decay approach up to when the country’s smoking prevalence reaches 5% or less of the adult population. This provides an estimate of when the country is likely to become smoke-free if public policy and regulation do not change.
However, we aim to quantify how much those estimates would change if countries adopted Sweden’s experience. To illustrate this, we added a second line to our charts to forecast a decline in the prevalence of alternative smoking in each country. It adjusts the trend calculation to the year-on-year decline of Sweden.
Finally, even though the experience of Sweden is unique, we recognize that the experiences of the UK, New Zealand, and Japan have similarities and, importantly, validate the fact that a comprehensive approach towards eradicating smoking can be effective despite cultural and historical differences (which are evident across these countries).
Therefore, we added a third line to our charts to forecast an alternative smoking prevalence decline. It adjusts the trend calculation to the year-on-year decline of these countries combined.
Strengths
- Simple and efficient: This method provides a straightforward way to estimate long-term trends without requiring complex modeling techniques.
- Useful for long-term forecasting: Despite its simplicity, it effectively captures general downward or upward trends over extended periods.
- Applicable across multiple countries: This approach allows for consistent comparison across different countries, making it useful for high-level regional and global analyses.
Limitations
- Does not account for short-term fluctuations: This is a simplified model that does not account for short-term fluctuations (e.g., temporary increases or plateaus), which more complex methods—such as exponential fitting or regression analysis—might capture.
- Interpolation uncertainty: Data gaps are filled using interpolation, which assumes a smooth trend between known data points. This method does not account for real-world fluctuations caused by economic crises, cultural shifts, or sudden public policy changes.
- Constant Decay Rate Assumption: The model assumes that smoking prevalence declines at a constant proportional rate each year. In reality, declines may be non-linear, influenced by public policy changes, economic conditions, and behavioral shifts that may accelerate or slow smoking reduction over time.
- Potential misinterpretation of late-stage rebounds: Since the decay rate calculation relies only on the first and last values, it can be misleading if a country’s trend includes a late-stage rebound. For example, Austria shows an overall long-term decline but appears to follow an upward trajectory in this model due to recent increases in prevalence.
- Endgame Target Estimates May Be Unrealistic: The choice of baseline years (2005/2006 and 2022/2023) means that if either year had an unusual smoking prevalence (e.g., due to a public policy change or reporting anomaly), the calculated decay rate may not reflect the actual long-term trend. Countries with late-stage rebounds (such as Austria) may be misrepresented, showing an upward trend despite an overall long-term decline.
- No Consideration for Public Policy or Societal Changes: The model does not incorporate future public policies, such as higher taxes, stricter regulations, or communication bans, which could significantly alter smoking trends. Additionally, social and economic factors (e.g., increased vaping, economic downturns) are not accounted for, despite their potential impact on smoking rates.
- Data consistency: The model uses data from WHO and Eurobarometer for the countries involved, and data for Sweden, New Zealand, the UK, and Japan comes from their respective sources, each with different survey methodologies, sample sizes, smoking definitions, and years taken. This could lead to inconsistencies across the datasets.
Caution Regarding Phrasing and Assumptions
- It is important to emphasize that this model is a heuristic tool, not a rigorously validated statistical model. The methodology relies on assumptions and simplifications that may not fully capture the complexities of smoking prevalence trends.
- The model assumes that the country being analyzed will follow a similar trend to the average of these countries, but this is not guaranteed.
- It is not designed for precise validation against real-world data, so the results should be interpreted as rough estimates that provide a general sense of direction rather than definitive predictions.
- Public policy changes that could impact smoking prevalence—such as tax policies, communication bans, or public health campaigns—are not factored into the formula.
- These assumptions introduce significant uncertainty, and the results should be cautiously viewed.
