Introduction: Some studies show that truck drivers use tobacco and other stimulants to stay awake as they drive. Despite their increased risks for many of tobacco-related health disparities, there is limited engagement of truck drivers in smoking cessation programs. The objective of this study was to describe smoking characteristics and identify their preferred smoking cessation methods among truck drivers. Methods: This was a cross-sectional mixed methods study. Participants were truck drivers recruited at trucking companies in Utah in 2019. Participants were either individually interviewed (n = 4), or filled out a survey (n = 33). We conducted qualitative data analysis of the interviews followed by descriptive statistics of smoking and cessation characteristics from the survey. Results: Reasons for smoking included, staying awake, stress reduction, or something to do while driving. Of the drivers surveyed, 68.8% were daily smokers while 97% had smoked at least 100 cigarettes in their life time. The mean number of cigarettes per day (cpd) was 15.7, and 25 among those who had 10 or more cpd. Sixty-one percent had made at least a quit attempt. In addition to counseling or brief advice, 68% reported interest in using Nicotine Replacement Therapy (NRT) either as gum or patch to help them quit. 21% reported interest in telephone text messaging to engage them in treatment. Conclusion: Cigarette smoking is a public health problem among truck drivers. Our findings suggest that truck drivers are interested in quitting smoking. Evidence based interventions tailored to this population are needed to help them quit and reduce their smoking-related morbidity.
Objectives: To explore the relationships between tobacco, social support, job satisfaction, and depression among truck drivers. Methods: Cross-sectional data were collected from 797 truck drivers in six US states. Data collected included self-reported medical history and biological samples. Modified Zung depression scale and Work Apgar scores were used to measure depression and social support. Adjusted logistic regression models were used to calculate odds ratios (OR). Results: 24.0% of tobacco users were in the least depressed category and 18.2% were most depressed. 22.8% of the tobacco users had the most social support compared with 27.9% of the non-users. Drivers in the two most depressed categories were significantly less likely to use tobacco (OR = 0.62, 95% confidence interval [CI] = 0.39–0.96, and OR = 0.64, 95% CI = 0.41–0.99). Conclusions: Drivers with low social support or low levels of depression are more likely to be tobacco users.
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