Modeling all-cause mortality: projections of the impact of smoking cessation based on the NHEFS. NHANES I Epidemiologic Follow-up Study (original) (raw)
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BMC Public Health, 2021
Background Cigarettes and smokeless tobacco (SLT) products are among a wide range of tobacco products that are addictive and pose a significant health risk. In this study, we estimated smoking- and SLT use-related mortality hazard ratios (HRs) among U.S. adults by sex, age group, and cause of death, for nine mutually exclusive categories of smoking and/or SLT use. Methods We used data from the public-use National Health Interview Survey Linked Mortality with mortality follow-up through 2015. We used Cox proportional hazard models to estimate mortality HRs, adjusted by race/ethnicity, education, poverty level, body mass index, and tobacco-use status. Results With never users as reference group, HRs for smoking-related diseases for male exclusive current smokers aged 35–64 and 65+ were 2.18 (95% confidence interval [CI]: 1.79–2.65), and 2.45 (95% CI: 2.14–2.79), respectively. Similar significant HR estimates were found for females and for all-cause mortality (ACM) and other-cause mort...
Re: "Modeling Smoking History: A Comparison of Different Approaches
American Journal of Epidemiology, 2003
The impact of cigarette smoking on various diseases is studied frequently in epidemiology. However, there is no consensus on how to model different aspects of smoking history. The aim of this investigation was to elucidate the impact of several decisions that must be made when modeling smoking variables. The authors used data on lung cancer from a case-control study undertaken in Montreal, Quebec, Canada, in 1979-1985. The roles of smoking status, intensity, duration, cigarette-years, age at initiation, and time since cessation were investigated using time-dependent variables in an adaptation of Cox's model to case-control data. The authors reached four conclusions. 1) The estimated hazard ratios for current and ex-smokers depend strongly on how long subjects are required to not have smoked to be considered "ex-smokers." 2) When the aim is to estimate the effect of continuous smoking variables, a simple approach can be used (and is proposed) to separate the qualitative difference between never and ever smokers from the quantitative effect of smoking. 3) Using intensity and duration as separate variables may lead to a better model fit than using their product (cigarette-years). 4) When estimating the effects of time since cessation or age at initiation, it is still useful to use cigarette-years, because it reduces multicollinearity.
American Journal of Epidemiology, 2002
The authors investigated the association between changes in smoking habits and mortality by pooling data from three large cohort studies conducted in Copenhagen, Denmark. The study included a total of 19,732 persons who had been examined between 1967 and 1988, with reexaminations at 5- to 10-year intervals and a mean follow-up of 15.5 years. Date of death and cause of death were obtained by record linkage with nationwide registers. By means of Cox proportional hazards models, heavy smokers (>or=15 cigarettes/day) who reduced their daily tobacco intake by at least 50% without quitting between the first two examinations and participants who quit smoking were compared with persons who continued to smoke heavily. After exclusion of deaths occurring in the first 2 years of follow-up, the authors found the following adjusted hazard ratios for subjects who reduced their smoking: for cardiovascular diseases, hazard ratio (HR) = 1.01 (95% confidence interval (CI): 0.76, 1.35); for respiratory diseases, HR = 1.20 (95% CI: 0.70, 2.07); for tobacco-related cancers, HR = 0.91 (95% CI: 0.63, 1.31); and for all-cause mortality, HR = 1.02 (95% CI: 0.89, 1.17). In subjects who stopped smoking, most estimates were significantly lower than the heavy smokers'. These results suggest that smoking reduction is not associated with a decrease in mortality from tobacco-related diseases. The data confirm that smoking cessation reduces mortality risk.
Modeling smoking history: a comparison of different approaches
American journal of epidemiology, 2002
The impact of cigarette smoking on various diseases is studied frequently in epidemiology. However, there is no consensus on how to model different aspects of smoking history. The aim of this investigation was to elucidate the impact of several decisions that must be made when modeling smoking variables. The authors used data on lung cancer from a case-control study undertaken in Montreal, Quebec, Canada, in 1979-1985. The roles of smoking status, intensity, duration, cigarette-years, age at initiation, and time since cessation were investigated using time-dependent variables in an adaptation of Cox's model to case-control data. The authors reached four conclusions. 1) The estimated hazard ratios for current and ex-smokers depend strongly on how long subjects are required to not have smoked to be considered "ex-smokers." 2) When the aim is to estimate the effect of continuous smoking variables, a simple approach can be used (and is proposed) to separate the qualitative...
Differences between studies in reported relative risks associated with smoking: An overview
Public Health Reports
REPORTED RELATIVE RISKS associated with smoking differ between studies; these differences may reflect true biological differences between populations or may be research artifacts introduced by differences in factors such as amount smoked or smoking duration. The authors reviewed the literature published before June 1-992 on relative risks associated with smoking for heart disease, stroke, lung cancer, and chronic obstructive lung disease. They quantified the effect of variables such as age, amount smoked, and smoking duration on reported relative risks. The main reasons for the variation in reported relative risks were: misclassification of former smokers as never smokers, the use of mortality rate ratios rather than incidence rate ratios, a possible period effect suggesting increasing relative risks over time, and differences in the amount smoked. It is far more likely that these factors are responsible for the observed variation between studies than that the variations reflect true biological differences between populations. Using relative risks from other studies is therefore justified in calculating a population attributable risk if the studies are carefully selected and address factors such as amount smoked and period effects.
Re:" Modeling smoking history: A comparison of different approaches"-Reply
The impact of cigarette smoking on various diseases is studied frequently in epidemiology. However, there is no consensus on how to model different aspects of smoking history. The aim of this investigation was to elucidate the impact of several decisions that must be made when modeling smoking variables. The authors used data on lung cancer from a case-control study undertaken in Montreal, Quebec, Canada, in 1979. The roles of smoking status, intensity, duration, cigarette-years, age at initiation, and time since cessation were investigated using time-dependent variables in an adaptation of Cox's model to case-control data. The authors reached four conclusions. 1) The estimated hazard ratios for current and ex-smokers depend strongly on how long subjects are required to not have smoked to be considered "ex-smokers." 2) When the aim is to estimate the effect of continuous smoking variables, a simple approach can be used (and is proposed) to separate the qualitative difference between never and ever smokers from the quantitative effect of smoking. 3) Using intensity and duration as separate variables may lead to a better model fit than using their product (cigarette-years). 4) When estimating the effects of time since cessation or age at initiation, it is still useful to use cigarette-years, because it reduces multicollinearity. Downloaded from 816 Leffondré et al. Am J Epidemiol 2002;156:813-823 by guest on July 3, 2015 http://aje.oxfordjournals.org/ Downloaded from 820 Leffondré et al. Am J Epidemiol 2002;156:813-823