Introduction

Electronic nicotine dispensing systems (ENDSs), also known as electronic cigarettes or in simpler terms referred to as e-cigarettes, are designed to mimic the traditional cigarettes by dispensing nicotine as e-liquid without the tobacco intoxicants. It was invented in 2003 by Chinese pharmacist Hon Lik as a replacement to the conventional cigarette smoking; it was introduced to the European and American markets in 2006.¹ Since then, the use of e-cigarettes increased exponentially among young adults, despite controversies and safety concerns.² The age of initiation of e-cigarette use is generally in high school. Survey suggests that 3.3% and 14.1% of middle and high school students in the United States were reported to have started the use of e-cigarettes, which corresponds to 2.55 million school students in 2022.³

Considered as less harmful than the conventional tobacco-containing products, e-cigarettes are marketed as replacement to traditional smoking or as an adjunct to quit conventional cigarette smoking. However, research has generated conflicting evidence on the efficacy of e-cigarettes in smoking cessation. Some studies have shown decreased use of conventional cigarettes upon introducing e-cigarettes while some other reports have shown increased probability of being dual users.⁴ Risk factors associated with dual use in adolescents include being a male, urban environment, increased stress, alcohol or substance use, and weekly allowance.⁵

A recent survey in 2022, which assessed the estimated e-cigarette use, enumerated 18.3 million adult users in 14 countries, with the highest prevalence in Russia and the least in India.⁶ Male gender, 15–24 years of age, urban dwellers, high socioeconomic status, and higher education were associated with the increased use of first-time users. Of the total users, an overwhelming 85% preferred using flavored e-cigarettes.⁶

Saudi Arabia has the higher burden of illness from traditional cigarette smoking, because higher prevalence rates have constantly been reported in this region. Earlier studies have documented varied prevalence of tobacco smoking among different age groups: 16.5% in school students, 13.5% among university students, 22.6% among adults, and 25% in the elderly people.⁷ In recent years, in view of reducing the traditional cigarette consumption, the population began the use of e-cigarettes to either quit smoking or to reduce nicotine exposure owing to its less harmful perception. Prevalence of e-cigarette use in Saudi Arabia has shown diverse results. Higher prevalence is seen in the western region (27.7%), while central and eastern provinces report 12.2% and 10.6% among university students.⁸ Among the many reasons for the use of e-cigarettes in Saudi Arabia, the most common is to quit traditional cigarette smoking or reduce tobacco use, followed by peer influence and curiosity to use the new product.⁹

Many studies have suggested a link between e-cigarette use and mental health status. In addition to substance abuse and other psychiatric complaints, longitudinal data have demonstrated higher PHQ-9 depression scores and increased odds of depression in e-smokers compared to nonsmokers.^10–12 Furthermore, e-cigarette users have reported poor sleep quality and difficulty in sleeping with reliance on sleep medication.^13,14 Studies on physical activity behavior showed contradictory results—some studies demonstrated increased physical activity pattern while some reported abstinence from moderate to severe physical activity.^15,16

Recognizing the inconclusive evidence of harm associated with e-cigarettes, it is important to understand the pattern and associated factors of e-cigarette use in society. Therefore, this study was conducted to determine the pattern of e-cigarette use and its association with lifestyle-related factors like stress levels, sleep quality, and physical activity.

Methods

Study population

A cross-sectional study design was adopted to address the research objectives, and was conducted in a large University with current enrolled students as the study subjects.

Students diagnosed with psychological conditions such as depression or anxiety, those having sleep disorders, handicapped subjects who are unable to perform physical activity, and traditional cigarette smokers were excluded from the study.

The required ethical approval was obtained from the institutional review board of King Saud University. Informed consent was obtained from the participants, and the confidentiality of the information and privacy of the participants were protected.

Sample size estimation

The sample size of 372 participants was calculated using the two proportions formula. Since there are three different outcomes, the largest sample size was considered with 95% confidence interval and the margin of error was 5%.

Study variables

The study variables include sociodemographic variables (age, gender, monthly income, area of residence), history of chronic illnesses, history and pattern of smoking including e-cigarettes smoking, level of stress, physical activity and sleep quality. The main exposure is e-cigarettes smoking, associating with level of stress, physical activity and sleep quality between non-smokers and e-cigarettes smokers.

Measures

The data was collected online using an e-questionnaire that included the sociodemographic status, smoking status, physical activity level, sleep quality, and stress level. The development of questionnaire survey was based on the Pittsburgh Sleep Quality Index (PSQI) and Perceived Stress Scale. The Perceived Stress Scale score is obtained by summing the points awarded to the 10 items ranging from 0 to 40; they were graded as: 0–13 low stress, 14–26 moderate stress, and 27–40 high perceived stress.

Statistical analysis

The data was analyzed using the IBM Statistical software for Windows version 26.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics (frequencies, percentages, mean and standard deviation) were used to describe the categorical and quantitative variables. Bivariate analysis was done using student’s t-test for independent samples, and a P-value of < 0.05 was considered significant.

Results

Of the total 372 participants, 195 (52.4%) were men. Around 88.4% were never smokers and 11.6% ever smokers. Most had an income greater than SAR 15,000 per month. The age at smoking initiation was 17 years for current e-cigarette smokers. Most of the e-cigarette smokers used one type of tobacco and almost 84% smoked daily. The mean age of the study population was 20 ± 1.5 years. The distribution of sociodemographic characteristics according to smoking status and type is shown in Table 1.

Most of the participants specified either good or average level of fitness while at least 82 (24.8%) of the nonsmokers reported poor health. Frequency of playing sports was similar across the groups, while the most common reason for playing sports was for enjoyment in the nonsmoking (32.3%) group and intention to stay fit among the e-smokers (33.3%). The distribution of physical activity specifications was similar across the groups and none of the parameters reached the level of statistical significance. The physical activity and the smoking status are presented in Table 2.

The sleep quality characteristics of current and past e-cigarette smokers are presented in Table 3. The average bedtime and time taken to fall asleep was similar across the three groups. The current smokers showed slightly longer sleep time with early bedtime, and on average woke up few minutes later than the other two groups. They also seemed to have less disturbed sleep and did not wake up in the middle of the night. The other characteristics of sleep quality are described in Table 3.

Additionally, the Perceived Stress Scale score was obtained by summing the points awarded to the 10 items ranging from 0 to 40. The mean (SD) stress score of nonsmokers was 11.3 (6.1), current e-cigarette smokers scored 11.2 (5.7), and past e-cigarettes smokers scored 12.7 (8.6). The mean scores did not show significant difference between the groups (f = 0.243; P = 0.784).

Discussion

This study investigated e-cigarette smoking and its relationship with sleep quality, stress levels, and physical activity status. The age of e-cigarette initiation was 17 years, and frequent use was found among men and higher income status. No associations were found between e-cigarette use and stress, sleep quality, and physical activity levels. Lack of statistically significant results between both comparison groups—nonsmokers and current e-smokers—might be related to heterogeneity between the groups and the low number of e-cigarette users compared to nonsmoker participants.

Relation between stress levels and e-cigarette use is a largely underexplored subject, and its use has increased among adolescents and young adults in general and among the stressed in particular.^17,18 Many studies have demonstrated a positive link between increasing stress levels and vaping; however, the initiation stage of e-cigarette has not been proven to be associated with stress while progressive use has been linked to stress, anxiety, and depression.^19,20 This study demonstrated no significant difference between Perceived Stress Scores and e-cigarette use. Some of the probable reasons could be related to the relatively younger age of the study sample and lesser mean duration of smoking history. However, longitudinal data are needed to establish the association between e-cigarette use and stress levels.

Furthermore, this study did not find a significant association between physical activity and e-cigarette use. The levels of physical activity were similar across ever smokers and never smokers. Research has generated conflicting evidence between physical activity among e-smokers. A Canadian youth study reported e-cigarette users’ increased likelihood of getting involved in sports compared to nonusers,²¹ whereas a study from the United States reported diminished activity among ever users.²² A recent study also enumerated similar reports suggesting an inverse relationship between physical activity and e-cigarette use. More research is needed in this direction to ascertain the relation between physical activity and e-cigarette use.

Moreover, this study showed some differences in quality of sleep and pattern between e-smokers and nonsmokers. Although the significance level was not achieved, e-smokers exhibited better quality, undisturbed, and longer duration of sleep. These findings are in stark contradiction with other studies. A study by Brett et al. from the US demonstrated sleep difficulties and poor sleep health among e-cigarette users in college students (mean score = 7.17) compared to traditional smokers (6.73) and nonsmokers (5.45; P = 0.022), thus showing negative impact of smoking on sleep.¹⁴ Another similar study done in a large sample of about 85,000 university students also enumerated sleep impediments among smokers.²³ Population Assessment of Tobacco and Health study (PATH) reported greater odds of sleep disturbances in current and ever users compared to never users.¹³ Hence, we suggest more studies to determine the association in the direction of causation among ever and never users.

Study limitations

This study contains numerous limitations. Data from cross-sectional design are not accurate for this subject and further research using longitudinal studies is highly recommended. The sample size and single center data is not representative of the population. Self-administered questionnaire contains a degree of response bias that might affect the results. The authors suspect that the prevalence of e-cigarette smoking has been largely underrepresented due to the sensitive nature of the topic, even though anonymity was maintained. Furthermore, confounders of stress and sleep were not assessed and causal associations cannot be established; however, the study provides preliminary data for future longitudinal research.

Conclusion

This study did not find any differences in quality of sleep, stress, and physical activity between e-smokers and nonsmokers. Given the rising prevalence of e-cigarettes in the global population, larger well-designed studies are highly recommended to determine the association.