Perceived stress and psychological distress are associated with more cigarette craving and withdrawal, higher nicotine dependence, and less success during quit attempts. Low income smokers have disproportionately higher rates of smoking and may be particularly vulnerable to the effects of stress on smoking dependence. The aim of the current study was to assess if lower income smokers have a stronger association between stress and nicotine dependence than higher income smokers. Data were obtained from the Pennsylvania Adult Smoking Study, which included 351 daily smokers. Subjects completed PhenX Toolkit and other self-report measures of socioeconomic factors, the 10-item Perceived Stress Scale, Kessler Psychological Distress Scale (K6), Fagerstrom Test for Nicotine Dependence (FTND), and the Hooked on Nicotine Checklist (HONC). Moderation analyses using linear regression examined income-related differences in the association between stress and nicotine dependence. Income groups were categorized by an annual household income of $50,000 based on visual-inspection of scatter plots of income by nicotine dependence. Compared to higher income smokers, lower income smokers had significantly higher mean levels of nicotine dependence on the FTND [3.74 vs. 4.79, p < 0.001], perceived stress [15.63 vs. 17.95, p = 0.004], and psychological distress [5.30 vs. 6.86, p = 0.001], respectively. There were interaction effects, such that lower income smokers had a strong, positive associations between FTND and perceived stress (B = -0.11, CI = -0.17 to -0.04, p = 0.002) and psychological distress (B = -0.13, CI = -0.25 to -0.02, p = 0.022) whereas no association was found in higher income smokers. No significant moderation effects were found for the HONC or when income groups were categorized by U.S. federal poverty level. The results highlight that the relationship between increasing stress and FTND was found in lower but not higher income groups. Future research should examine socioeconomic, environmental and psychosocial factors that may facilitate increased smoking during stress-induced craving.

COVID-19 has become a global pandemic, with over 81 million cases worldwide. To assess changes in tobacco use as a result of the pandemic, we surveyed a convenience sample of current tobacco users between April and June 2020. The sample was taken from a tobacco user research registry (n = 3396) from the Penn State College of Medicine in Hershey, Pennsylvania, USA. Participants who responded to the survey and were eligible for this study (n = 291) were 25.6% male, 93% white, and had a mean age of 47.3 (SD = 11.6) years. There were no reports of participants testing positive for COVID-19, but 21.7% reported experiencing symptoms associated with the virus. Most participants (67%) believed that their risk of contracting COVID-19 was the same as non-tobacco users, but 57.7% believed that their risk of serious complications, if infected, was greater compared to non-tobacco users. A total of 28% reported increasing their cigarette use during the pandemic. The most common reasons for increased use were increased stress, more time at home, and boredom while quarantined. Nearly 15% reported decreasing their tobacco use. The most common reasons for reduced use were health concerns and more time around non-smokers (including children). A total of 71 (24.5%) users reported making a quit attempt. Characterizing these pandemic-related changes in tobacco use may be important to understanding the full scope of subsequent health outcomes resulting from the pandemic. Tobacco cessation resources should be tailored to allow for safe, appropriate access for those interested in quitting.

Socioeconomic status (SES) is a major determinant of tobacco use but little is known whether SES affects nicotine exposure and the degree of nicotine dependence. The Pennsylvania Adult Smoking Study is a cross-sectional study of smoke exposure and nicotine dependence among adults conducted in central Pennsylvania between June 2012 and April 2014. The study included several measures of SES, including assessments of education and household income, as well as occupation, home ownership, health insurance, household density and savings accounts. Measurements included saliva for the nicotine metabolites cotinine (COT), 3-‘hydroxycotinine (3HC) and total metabolites (COT +3HC). Puffing behavior was determined using portable smoking topography devices. The income levels of lighter smokers (< 20 cigarettes per day) was $10,000 more than heavier smokers. Higher Fagerström Test for Nicotine Dependence scores were associated with lower income and job status, scores ranged from 5.4 in unemployed, 4.4 in blue-collar, and 3.8 in white-collar workers. In principal components analysis used to derive SES indicators, household income, number in household, and type of dwelling were the major SES correlates of the primary component. Job category was the major correlate of the second component. Lower SES predicted significantly higher adjusted total nicotine metabolite levels in the unemployed group. Job category was significantly associated with total daily puffs, with the highest level in the unemployed, followed by blue-collar workers, after adjustment for income. Among smokers, there was a relationship between lower SES and increased nicotine dependence, cigarettes per day and nicotine exposure, which varied by job type.

The role of inhalation behaviors as predictors of nicotine uptake was examined in the Pennsylvania Adult Smoking Study (2012–2014), a study of 332 adults whose cigarette smoking was measured in a naturalistic environment (e.g., at home) with portable handheld topography devices. Piecewise regression analyses showed that levels of salivary cotinine, trans-3′-hydroxycotinine, and total salivary nicotine metabolites (cotinine + trans-3′-hydroxycotinine) increased linearly up to a level of about 1 pack per day (20 cigarettes per day (CPD)) (P < 0.01). Total daily puff volume (TDPV; in mL) (P < 0.05) and total daily number of puffs (P < 0.05), but not other topographical measures, increased linearly with CPD up to a level of about 1 pack per day. The mean level of cotinine per cigarette did not change above 20 CPD and was 36% lower in heavy smokers (≥20 CPD) than in lighter smokers (<20 CPD) (15.6 ng/mL vs. 24.5 ng/mL, respectively; P < 0.01). Mediation models showed that TDPV accounted for 43%–63% of the association between CPD and nicotine metabolites for smokers of <20 CPD. TDPV was the best predictor of nicotine metabolite levels in light-to-moderate smokers (1–19 CPD). In contrast, neither CPD, total daily number of puffs, nor TDPV predicted nicotine metabolite levels above 20 CPD (up to 40 CPD). Finally, although light smokers are traditionally considered less dependent on nicotine, these findings suggest that they are exposed to more nicotine per cigarette than are heavy smokers due to more frequent, intensive puffing.

Background: This study was conducted to determine sex/gender differences in smoke exposure and to quantify the role of potential predictors including puffing behaviors, nicotine dependence, and non-nicotinic factors. Methods: The Pennsylvania Adult Smoking Study (PASS) of 332 adult cigarette smokers utilized portable handheld topography devices to capture the smokers' profiles in a naturalistic environment. Sex/gender differences in salivary biomarkers were modeled using ANCOVA to account for measures of dependence (Fagerstrom Test for Nicotine Dependence, nicotine metabolite ratio [3-hydroxycotinine/cotinine]), and nondependence covariates including anthropomorphic factors and stress. The Blinder-Oaxaca method was used to decompose the sex/gender differences in nicotine uptake due to covariates. Results: Men had significantly higher cotinine levels (313.5 ng/mL vs. 255.8 ng/mL, p < 0.01), cotinine +3-hydroxycotinine levels, (0.0787 mol/L vs. 0.0675 mol/L, p = 0.01), puff volumes (52.95 mL vs. 44.77 mL, p < 0.01), and a lower nicotine metabolite ratio (0.396 vs. 0.475, p = 0.01) than women. The mean Fagerström Test for Nicotine Dependence score did not differ between men and women (p = 0.24). Women had a higher mean Hooked on Tobacco Checklist score than men (7.64 vs. 6.87, p < 0.01). In multivariate analysis, nicotine metabolite levels were not significantly different by sex. Decomposition results show that ten predictors can explain 83% of the sex/gender differences in cotinine uptake. Height was the greatest contributor to these differences, followed by average puff volume. Conclusion and Impact: The higher levels of nicotine metabolites in men, compared to women, can be explained by height, weight, puff volume, and nicotine metabolism.