Abstract

BackgroundPopulation models have been developed to evaluate the impact of new tobacco products on the overall population. Reliable input parameters such as longitudinal tobacco use transitions are needed to quantify the net population health impact including the number of premature deaths prevented, additional life years, and changes in cigarette smoking prevalence.MethodsThis secondary analysis assessed transition patterns from PATH wave 1 (2013–14) to wave 2 (2014–15) among adult exclusive cigarette smokers, exclusive e-cigarette users, and dual users. Transition probabilities were calculated by taking into account factors including cigarette smoking and e-cigarette use histories and experimental or established use behaviors. Multinomial logistic regression models were constructed to further evaluate factors associated with transition patterns.ResultsDifferential transition probabilities emerged among study subgroups when taking into account cigarette smoking and e-cigarette use histories and experimental or established use behaviors. For example, overall 45% of exclusive e-cigarette users in wave 1 continued using e-cigarettes exclusively in wave 2. However, we observed approximately 11 to 14% of wave 1 exclusive experimental e-cigarette users continued to use e-cigarette exclusively in wave 2, compared to about 62% of exclusive established e-cigarette users. The history of cigarette smoking and e-cigarette use is another important factor associated with transition patterns. Among experimental e-cigarette users, 7.5% of individuals without a history of cigarette smoking transitioned to exclusive cigarette smoking, compared to 30% of individuals with a history of cigarette smoking. Additionally, 1.3% of exclusive cigarette smokers in wave 1 transitioned to exclusive e-cigarette use, with the highest transition probability (3.7%) observed in the established cigarette smoker with a history of e-cigarette use subgroup.ConclusionsProduct use histories and current use behaviors are important factors influencing transitions between product use states. Given that experimental users’ transition behaviors may be more variable and more influenced by tobacco use history, long-term predictions made by population models could be improved by the use of transition probabilities from established users. As transition patterns might be changing over time, long-term transition patterns can be examined through analysis of future waves of PATH data.

Highlights

  • Prevalence of cigarette smoking among adults in the United States (US) declined from 20.9% in 2005 to 16.8% in 2014 [1], and continues to decline with the most recently reported rate of 14.0% in 2017 [2]

  • As transition patterns might be changing over time, long-term transition patterns can be examined through analysis of future waves of Population Assessment of Tobacco and Health (PATH) data

  • Of the 1.1% exclusive e-cigarette users, 0.4% were experimental e-cigarette users, of whom, about half had a history of cigarette smoking; 0.7% were established e-cigarette users, 82% of whom had a history of cigarette smoking

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Summary

Introduction

Prevalence of cigarette smoking among adults in the United States (US) declined from 20.9% in 2005 to 16.8% in 2014 [1], and continues to decline with the most recently reported rate of 14.0% in 2017 [2]. Adult e-cigarette use patterns have been studied in cross-sectional national surveys, such as NHIS [3,4,5,6] and the Behavioral Risk Factor Surveillance System (BRFSS) [7, 8]. The study generates longitudinal epidemiologic data on tobacco use behaviors, including patterns of use, attitudes, beliefs, exposures, and health consequences associated with use of tobacco products among the US population [9]. Population models have been developed to evaluate the impact of new tobacco products on the overall population Reliable input parameters such as longitudinal tobacco use transitions are needed to quantify the net population health impact including the number of premature deaths prevented, additional life years, and changes in cigarette smoking prevalence

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