Improving Prediction of Tobacco Use Over Time: Findings from Waves 1-4 of the Population Assessment

Mills SD, Zhang Y, Wiesen CA, Hassmiller Lich K.
Improving Prediction of Tobacco Use Over Time: Findings from Waves 1-4 of the Population Assessment Of Tobacco And Health Study
Nicotine Tob Res. 2023 Sep 6:ntad171. doi: 10.1093/ntr/ntad171. Epub ahead of print. PMID: 37671638.

Introduction. First-order Markov models assume future tobacco use behavior is dependent on current tobacco use and are often used to characterize patterns of tobacco use over time. Higher-order Markov models that assume future behavior is dependent on current and prior tobacco use may better estimate patterns of tobacco use. This study compared Markov models of different orders to examine whether incorporating information about tobacco use history improves model estimation of tobacco use and estimated tobacco use transition probabilities.

Methods. We used data from four waves of the Population Assessment of Tobacco and Health Study. In each wave a participant was categorized into one of the following tobacco use states: never smoker, former smoker, menthol cigarette smoker, non-menthol cigarette smoker, or e-cigarette/dual user. We compared 1 st, 2 nd and 3 rd order Markov models using multinomial logistic regression and estimated transition probabilities between tobacco use states.

Results. The 3 rd order model was the best fit to the data. The percentage of former smokers, menthol cigarette smokers, non-menthol cigarette smokers, and e-cigarette/dual users in Wave 3 that remained in their same tobacco use state in Wave 4 ranged from 63.4%-97.2%, 29.2%-89.8%, 34.8%-89.7%, and 20.5%-80.0%, respectively, dependent on tobacco use history. Individuals who were current tobacco users, but former smokers in the prior two years, were most likely to quit.

Conclusions. Transition probabilities between tobacco use states varied widely dependent on tobacco use history. Higher-order Markov models improve estimation of tobacco use over time and can inform understanding of trajectories of tobacco use behavior.

Implications. Findings from this study suggest that transition probabilities between tobacco use states vary widely dependent on tobacco use history. Tobacco product users (cigarette or e-cigarette/dual users) who were in their same tobacco use state in the prior two years were least likely to quit. Individuals who were current tobacco users, but former smokers in the prior two years, were most likely to quit. Quitting smoking for at least two years is an important milestone in the process of cessation.