Using lung cancer mortality to indirectly approximate smoking patterns in space

Area of Science:

• Epidemiology
• Biostatistics
• Public Health

Background:

• Smoking is the primary cause of lung cancer, but non-smoking factors also contribute.
• Existing Swiss survey data on tobacco use are geographically and temporally limited.
• Understanding tobacco use distribution is crucial for estimating its disease burden.

Purpose of the Study:

• To estimate spatial smoking patterns in Switzerland.
• To develop proxies for smoking prevalence using available data.
• To assess the burden of tobacco use on lung cancer mortality.

Main Methods:

• Bayesian regression models with spatial random effects (SREs) were applied.
• Data from the Swiss Health Survey (14,521 participants) were utilized.
• Smoking proxies were derived from mortality rates and SREs, adjusted for environmental factors.

Main Results:

• A moderate correlation was found between observed smoking prevalence and smoking proxies, stronger in females.
• Spatial random effects models provided estimates of smoking patterns.
• Population attributable fractions were calculated to quantify tobacco's contribution to lung cancer.

Conclusions:

• Smooth unadjusted mortality rates can serve as effective proxies for smoking patterns in Switzerland.
• These methods can help estimate the burden of tobacco use on lung cancer mortality in data-scarce regions.
• Accurate spatial distribution of tobacco use is essential for public health interventions.