Latent Class Analysis of E-cigarette Use Sessions in Their Natural Environments.

BACKGROUND

Delivery of nicotine and substances from electronic nicotine delivery systems, or e-cigarettes, depends in part on how users puff on the devices. Little is known about variation in puffing behavior to inform testing protocols or understand whether puffing behaviors result in increased exposure to emissions.

METHODS

We analyzed puff topography data collected using a wireless portable use monitor (wPUM) continuously over 2 weeks among 34 current second-generation e-cigarette users in their everyday lives. For each puff, the wPUM recorded date, time, duration, volume, flow rate, and inter-puff interval.

RESULTS

We defined use session and classes at the session level using multilevel latent profile analysis, resulting in two session classes and three person types. Session class 1 ("light") was characterized by 14.7 puffs per session (PPS), low puff volume (59.9 ml), flow rate (28.7 ml/s), and puff duration (202.7 s × 100). Session class 2 ("heavy") was characterized by 16.7 PPS with a high puff volume (290.9 ml), flow rate (71.5 ml/s), and puff duration (441.1 s × 100). Person class 1 had almost exclusively "light" sessions (98.0%), whereas person class 2 had a majority of "heavy" sessions (60.7%) and person class 3 had a majority of "light" sessions (75.3%) but some "heavy" sessions (24.7%).

CONCLUSION

Results suggest there are different session topography patterns among e-cigarette users. Further assessment is needed to determine whether some users have increased exposure to constituents and/or health risks because of e-cigarettes.

IMPLICATIONS

Our study examines topography characteristics in a users' natural setting to identify two classes of e-cigarette session behavior and three classes of users. These results suggest that it is important for studies on the health effects of e-cigarettes to take variation in user topography into account. It is crucial to accurately understand the topography profiles of session and user types to determine whether some users are at greater exposure to harmful or potentially harmful constituents and risks from e-cigarettes as they are used by consumers.