Abstract
We assessed cumulative tobacco smoke cumulative damage (smoke load)/cancer mortality associations across time from 1979 to 2003 among Massachusetts males overall and at ages 30–74. Annual lung cancer death rates were used as smoke load bio-indices, and lung/all other (non-lung) cancer death age-adjusted rate linear regressions were run for analysis to calculate smoking-attributable fractions (SAF). Death rate SAFs are equal to: 1- estimated unexposed rate/observed rate. Fairly steady all age and ages 30–74 years lung and non-lung cancer death rate declines occurred since 1992. Non-lung cancer death rates were tightly and steeply associated with smoke load across year. The slopes of those associations are 1.69 (95% confidence interval (CI) 1.35–2.04, r=0.90, or 1.36 (CI 1.02–1.96, r=0.95) when adjusted for possible autocorrelation) and 1.36 (CI 1.14–1.58, r=0.94) without detected autocorrelation (Durbin-Watson statistic = 1.8), respectively. The lung/non-lung cancer death rate associations suggest 2003 all-sites cancer death rate SAFs of 73% (SR 61–82%) at all ages and 74% (SR 61–82%) at ages 30–74. The observed strong lung/non-lung cancer death rate associations suggest that tobacco smoke load may cause most prematurely fatal cancers at both lung and non-lung sites in Massachusetts male populations. Therefore, tobacco control may greatly reduce the overall cancer death rates.
Highlights
Different methods exist to estimate smoking attributable cancer mortality rates (Peto and Ezzati methods, as examples)
Massachusetts male cancer death rates peaked in the early 1990s, including the rates for all sites, and non-lung cancer death rates for all age groups and for the 30–74 years age group (Figure 1)
The lung/non-lung cancer death rate associations suggest that year 2003 all-sites male cancer death rate Smoking attributable fractions (SAF) are 73% (SR 61–82%) across all ages and 74% (SR 61–82%) for males aged 30–74 years, or 196 deaths per 100,000
Summary
Different methods exist to estimate smoking attributable cancer mortality rates (Peto and Ezzati methods, as examples). Recent estimates of smoking-attributable cancer mortality utilize lung cancer mortality data as an indicator of the accumulated hazards of tobacco smoking and tightly link several temporal, ethnic, and geographic cancer mortality disparities to smoking [1,2]. In the authors' words, the Peto estimates are based on a "simple halving of the excess risk [linked to smoke exposure which] is obviously not a satisfactory procedure, for it is crude and arbitrary and may seriously underestimate some of the true hazards of tobacco" [3] Both estimates are based in part on the Cancer Prevention Study (CPS) – II, which has considerable selection, exposure misclassification, and other biases [3,4,5]; and they may seriously underestimate the actual smoking attributable mortality. The absolute death rates among the non-smokers and the smokers (and the smoker/nonsmoker death rate ratios) in the CPSII study cannot be generalized over the US population [3,6]
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