INTRODUCTION

Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder. The prevalence of OSA in China, Spain, Korea, Sweden, the United States, Japan, and India between 1993 and 2013 was 22% and 17% in males and females, respectively¹. Over 90% of patients with OSA are misdiagnosed; therefore, most of them remain untreated². OSA is a growing health problem that is associated with various complications such as daytime fatigue, neurocognitive effects, headaches on awakening, fetal growth retardation, and disruption of bed partners’ sleep quality. If left untreated, OSA can be accompanied by glaucoma, cardiovascular events, stroke, and pulmonary hypertension³. Therefore, to prevent health deterioration due to the complications of OSA, identifying the risk factors for OSA is an important public health challenge.

The gold standard for diagnosing OSA is by using an overnight polysomnogram; however, it is time-consuming, expensive, and requires a professional examiner. Therefore, several alternate, simple, and reliable methods were devised to identify individuals at high risk for OSA^4-6. However, even these were complex or time-consuming and required upper airway evaluation. The STOP-Bang questionnaire, developed in 2008, is a simple and useful tool for screening OSA risk groups⁷. The STOP-Bang questionnaire is a self-reported questionnaire with four yes/no questions about snoring, tiredness, observed apnea, and high blood pressure, and four additional demographic questions concerning BMI (≥35 kg/m²), age (>50 years), neck circumference (>40 cm), and sex (male). Each question is assigned 1 point; thus, the total number of points ranges 0–8. Originally, the STOP-Bang scores were classified as: ≥3 for moderate-to-severe risk, and <3 for low risk of OSA. This tool has a sensitivity of ≥84%, 93%, and 100% and a specificity of 56.4%, 43%, and 37% for detecting any OSA, moderate to severe OSA, and severe OSA, respectively⁸. Owing to its high sensitivity and simplicity, STOP-Bang has been widely used in diverse populations^8,9.

Male sex, older age, familial aggregation, obesity, central body fat distribution, large neck girth, upper airway abnormalities, congestive heart failure, type 2 diabetes mellitus, and stroke are well-known risk factors for sleep apnea¹⁰. Several recent studies have found an association between smoking and alcohol use and sleep apnea or snoring¹¹. Current and former smoking, as well as heavy smoking, are associated with OSA¹². The effects of smoking on OSA and their mechanisms have been studied; although it is still a hypothesis, the mechanisms may include alterations in sleep architecture, impairment of upper airway neuromuscular function, higher arousal index, and upper airway inflammation¹⁴. However, only a few studies have investigated the association between OSA and electronic cigarette (e-cigarette) use, even though e-cigarettes are becoming increasingly popular¹⁴. Since e-cigarettes are considered healthier alternatives to cigarettes, their use is increasing; hence, they are used to reduce or quit cigarette smoking¹⁶. Despite such beliefs, there is still a lack of information about smoking risks according to the type of cigarette, including electronic cigarettes. Thus, we investigated the association between smoking behavior including smoking status, types of cigarettes and OSA, as determined by the STOP-Bang score.

METHODS

RESULTS

Table 1 presents the general characteristics of the study participants. Among the 7350 participants, 417 (5.7%) had a high risk for OSA according to the 2-stage STOP-Bang score. The number of participants who were dual users (e-cigarettes and cigarettes) was 431 (5.9%), cigarette only users were 2520 (34.3%), and never smokers were 4399 (59.9%). A high risk of OSA was observed in 49 (11.4%) of the 431 dual users and in 290 (11.5%) of the 2520 cigarette only users. Among the 4399 never smokers, 78 (1.8%) had a high risk of OSA, according to the STOP-Bang score.

Table 2 shows the factors associated with a high risk of OSA through multiple logistic regression analysis. Compared to those who were never smokers, cigarette only users and dual users had higher risks of increased OSA (cigarette only users, AOR=2.75; 95% CI: 1.33–5.68 and dual users, AOR=2.45; 95% CI: 1.04–5.79). Other factors that increased the probability of high risk for OSA were male sex, obesity, a history of diabetes, and hypertension.

Figure 1 shows the results of the subgroup analysis. Individuals who did not currently smoke but had a history of dual use were associated with a significant risk of OSA (AOR=3.61; 95% CI: 1.32–9.92). Furthermore, former cigarette smoking was associated with the likelihood of OSA (AOR=3.66; 95% CI: 1.63–8.23). Individuals who were dual users in the past and the present had increased odds of OSA, although this was not statistically significant.

Figure 1

Subgroup analysis of the association of previous and current cigarette type with the risk of obstructive sleep apnea using STOP-Bang score

Table 3 presents the results of the stratified analyses according to the independent variables. The probability of a high risk of OSA was 7.35 times higher for females with dual use (AOR=7.35; 95% CI: 1.04–59.80), but this was not significant for males with dual use. The association between the dual use of e-cigarettes and cigarettes and OSA was prominent in the those with low aerobic activity (AOR=2.04; 95% CI: 1.11–3.76) and low muscle strengthening activity (AOR=2.27; 95% CI: 1.17–4.37), and those with high-risk obesity (BMI >30 kg/m²) (AOR=4.98; 95% CI: 1.47–16.86). We observed a significant multiplicative interaction between smoking behavior and BMI (p<0.001).

DISCUSSION

We investigated the association between the STOP-Bang score, which reflects the risk of OSA, and smoking behavior, including smoking status and types of cigarettes (e-cigarettes or cigarettes). The odds of having a high risk for OSA in the dual users and the cigarette only users were significantly higher than in the never smokers. Interestingly, we observed a significantly increased risk for OSA in participants who did not currently smoke but had previously were dual users or cigarette only users.

Several hypotheses may explain our result concerning cigarettes, although the mechanisms are still unclear¹³. First, alterations in sleep architecture caused by smoking may increase the risk of OSA. This hypothesis was based on a prospective study using electroencephalogram spectrum analysis, which found that smokers’ sleep quality was inferior to that of non-smokers, especially in the early stages of sleep²⁰. Another study using polysomnography showed that smokers had a higher rapid eye movement sleep density, shorter sleep time, and longer sleep latency²¹. Second, the impairment of upper airway neuromuscular function in smokers can lead to a higher risk of OSA. However, the relationship between nicotine use and upper airway damage has only been demonstrated in animal experiments²². In humans, it is unclear whether smoking causes upper airway damage, although it has been shown that smoking can reduce reflexive mechanisms after damage²³. Third, arousal mechanisms may increase the risk of developing OSA. Smokers have a higher arousal index, which can result in increased sleep instability²⁴. Lastly, upper airway inflammation can lead to a higher risk of OSA. Smoking can cause airway inflammation and, consequently, upper airway narrowing²⁵.

Although the association between smoking and OSA has been investigated, only a few studies have addressed the association between dual use of e-cigarettes and cigarettes and OSA. However, as more people are using e-cigarettes to quit smoking, and OSA is a growing health problem, awareness of the need for studies on the relationship between e-cigarettes and OSA is gradually increasing. Therefore, in this study, in addition to the association between cigarette smoking and a higher likelihood of OSA, we investigated the association between dual use of cigarettes and OSA. E-cigarettes cause various health problems because e-cigarette aerosols contain highly oxidized freebase nicotine²⁶. Additionally, flavoring materials in e-cigarettes are associated with cytotoxicity²⁷, and toxic compounds such as carbonyls, metals, volatile organic compounds, and nitrosamines are found in almost all e-cigarettes^28,29. Nicotine withdrawal can also lead to sleep instability, which can predispose patients to upper airway obstruction³⁰. However, considering that our study investigating the association between dual use and the risk of OSA is a cross-sectional study and that the dual users may include many e-cigarette experimenters, the above interpretation requires caution. Cohort studies that can ensure causality are needed.

Despite the knowledge of the effects of e-cigarettes, to the best of our knowledge, Brett et al.³¹ in 2020 were the first to investigate the association between e-cigarettes and sleep disturbance; therefore, the relationship between e-cigarettes and sleep disorders and the mechanism by which e-cigarette use causes sleep disorders is still unclear. According to a previous study, even the sporadic use of e-cigarettes can cause sleep disturbances due to high nicotine exposure. On average, more e-cigarette smokers take sleeping medications than cigarette smokers³¹. Although these hypotheses support the association of dual use with the high risk of OSA, participants who smoked both e-cigarettes and cigarettes, both in the past and present, tended to have a higher risk of OSA than those who never smoked; however, this was not significant. These results could be due to the small number of respondents in these groups, which may show a tendency but is considered insufficient to draw a significant result. Moreover, dual users of cigarettes and e-cigarettes in the past to the present may not have consumed excessive nicotine due to the control on the amount of smoking³². Further research needs to be conducted using data from more participants and e-cigarette users.

In the stratified analyses, the association between dual use and the risk of OSA was much more pronounced in females. Although the risk of OSA is lower in females than in males, there is a need to raise awareness as our study shows that dual use was associated with a higher reported likelihood of OSA in females¹. Furthermore, the association between dual use and OSA was significant in those with low physical activity. Considering that there was no association between aerobic activity and muscle-strengthening activity levels and OSA, the lack of aerobic or muscle-strengthening activity and the dual use of e-cigarettes and cigarettes may exert a synergistic effect on the development of OSA. This suggests that physical activity can offset the negative effects of smoking on OSA³³. In participants with a BMI > 30 kg/m², the standard of obesity presented by the World Health Organization, mixing the types of tobacco increased the odds of having OSA by approximately five times. The strength of this association was much higher than in those with low BMI, and much higher than in cigarette only users. These results suggest that substances such as cytokines or inflammatory markers released from dual use of cigarettes can affect airway inflammation in obese individuals³⁴.

CONCLUSIONS

There are insufficient studies on the association between the types of cigarettes used and OSA, and the association between the two has not been fully elucidated. In the current study, we found that the dual use of e-cigarettes and cigarettes was significantly associated with OSA when compared to non-smoking. In addition, the dual use of cigarettes in the past was associated with a significant likelihood of OSA, even if the participants did not currently smoke or currently smoked only one product type. The association between dual use and OSA was more pronounced in females, participants with obesity, and those with a low level of physical activity. Further research is needed to confirm the causal relationship between the dual use of cigarettes and the risk of OSA.