Abstract
Study Objectives:
Targeted marketing has caused a recent surge in teen electronic cigarette usage. In all-age surveys, we isolated adolescent data (13–20 years) to assess age alongside electronic cigarettes, traditional tobacco, and dual usage of both with sleep quality and cough. Based on existing adult literature, we hypothesized an association between dual usage and increased sleep latency.
Methods:
Participants were recruited to complete surveys via social media sites. We performed 3 surveys: Survey 1 (n = 347) in 2018, Survey 2 (n = 1198) in 2019, Survey 3 (n = 554) in 2020. Surveys 1 and 2 had 3 sections: UCSD Inhalant Use Survey, Pittsburgh Sleep Quality Index, and Leicester Cough Questionnaire. Survey 3 did not include the Leicester Cough Questionnaire, instead the Hospital Anxiety and Depression Scale and Patient Health Questionnaire were used. The adolescent data were isolated (n = 609).
Results:
Adolescents reported longer sleep duration with increasing age by one-way analysis of variance. By Tukey’s multiple comparisons test, females slept more at ages 19 and 20 years than at age 14 years (P < .01). Female dual users slept more than nonsmokers, (P = .01; mean difference 43.8 minutes; confidence interval = 0.11 to 1.36). We observed an association between dual use and sleep latency vs nonsmokers (P = .0008; mean difference 6.27 minutes; confidence interval = 1.40 to 11.13). We saw no correlation between inhalant use and cough.
Conclusions:
In females, we observed a peak in sleep hours at age 19 years. College-aged females may wake later than younger adolescent females. The data also raised concern for sleep disruption and nicotine-induced wakefulness. Further data are required to guide public health strategies.
Citation:
Malhotra CK, Gunge D, Advani I, Boddu S, Nilaad S, Crotty Alexander LE. Assessing the potential impact of age and inhalant use on sleep in adolescents. J Clin Sleep Med. 2021;17(11):2233–2239.
Keywords: vaping, electronic cigarettes, tobacco, dual use, sleep latency
BRIEF SUMMARY
Current Knowledge/Study Rationale: Adolescents already face shorter sleep duration than the recommended 9 hours per night due to multiple factors, and short sleep duration has been associated with increased body weight, risk of myocardial infarction, anxiety, depression, and poor quality of life. With rising nicotine containing electronic cigarette use in adolescents, it is likely that vaping may further worsen sleep duration and quality due to the activating and sleep-disturbing effects of nicotine.
Study Impact: This work demonstrates that females in particular have more healthy sleep durations once they reach college age. Also, dual use of electronic cigarettes and conventional tobacco impacts sleep latency, lengthening the amount of time it takes for adolescents to fall asleep.
INTRODUCTION
Many people consider diet, exercise, and sleep to be the 3 pillars of health.1–3 These are particularly important in teenagers, because behaviors acquired at this stage may impact their health as adults.4 Electronic cigarette (e-cigarette) use, commonly known as vaping, has been surging in adolescents in recent years and could impact each of these 3 pillars: 1) Nicotine drives appetite suppression and the majority of e-cigarettes contain nicotine5; 2) Vaping can cause shortness of breath, and therefore impact exercise; and 3) In adults, vaping has been associated with increased sleep latency.6 Conventional tobacco use continues to be a problem, but the combination of e-cigarettes and tobacco (dual use) is not a well-studied area.
E-Cigarette companies such as JUUL and Puff Bar have marketed aggressively, targeting adolescents with fruity, minty, enticing flavors. They market them as a safer alternative to conventional smoking; of note, few teenagers fully understand the risks of nicotine addiction and health effects caused by vaping known to date, including asthma, bronchitis, lung injury, and cardiovascular disease.7,8 This aggressive, targeted marketing, coupled with easy accessibility to the product, including front door delivery, has led to increased acceptance of e-cigarettes and rising levels of adolescents who vape or combine the use of e-cigarettes and conventional tobacco.9 However, the impact of this trend on the 3 pillars of health is unknown.
Due to factors such as stress and electronic devices, adolescents tend already to face shorter sleep duration or worse quality than the recommended 9 hours per night.10–12 Short sleep duration has been associated with increased body weight, risk of myocardial infarction, anxiety, depression, and poor quality of life.13–17 Sleep issues are rarely prioritized in today’s 24/7 society, despite the health benefits of adequate quantity and quality sleep. Of note, men and women have differences in inclination to use inhalants. Also, according to the existing literature, anxiety and depression are more prevalent in females than males.18–21 Therefore, it is important to break down all data by gender to view any separate gender health implications. Little research has been done to assess not only sleep quality or duration across the spectrum of adolescence, but also the changes when combined with inhalant usage. The bulk of the prior literature is focused on adults, leaving little information about the specific effects on teenagers.
We sought to test the hypothesis that dual usage of e-cigarettes and conventional tobacco is associated with poor sleep quality in adolescents. Both inhalants have been associated with cough.6,22 We undertook these studies to determine if use of both e-cigarettes and conventional tobacco, dual use, had additive effects on cough. We also hypothesized an association between dual usage and increased anxiety and depression based on the correlation between shorter sleep duration and these mental health effects.
METHODS
Participants were recruited to complete online surveys via random posting on multiple days and at different times across social media sites such as Facebook, Craigslist, Reddit, and Twitter. We performed 3 surveys: Survey 1 (n = 347) was conducted in 2018, Survey 2 (n = 1198) in 2019, and Survey 3 during late March 2020 (n = 554). Participants were incentivized via a $250 Amazon gift card lottery. Surveys 1 and 2 were broken up into 3 sections: past and current inhalant use, the Pittsburgh Sleep Quality Index (PSQI; range 0–21, with lower scores representing better sleep quality), and the Leicester Cough Questionnaire (range 3–21, with higher scores representing less cough severity/prevalence and better quality of life). Because the Leicester Cough Questionnaire did not yield significant findings in Surveys 1 and 2, it was not included in subsequent surveys. Survey 3 instead included the Hospital Anxiety and Depression Scale and Patient Health Questionnaire to assess questions related to inhalant impact on mental health. The data were broken down by age group, specifically analyzing adolescents, ages 13–20 years, as well as by inhalant usage: e-cigarettes, conventional tobacco, dual users, and nonsmokers/nonvapers. For ages 13–20 years after removing outliers, Survey 1 received 71 responses; survey 2 received 475 responses, and Survey 3 received 63. Sleep-related assessments were conducted using all 3 surveys (n = 609; Table 1). An online software was utilized to map the IP addresses of all respondents’ ages 13–20 years (Figure 1).
Table 1.
Demographics of survey responders between ages 13–20 yrs.
| Total (n = 609) | Survey 1 (n = 71) | Survey 2 (n = 475) | Survey 3 (n = 63) | |
|---|---|---|---|---|
| Inhalant Group | ||||
| Nonsmoker | 424 (69.62%) | 43 (60.5%) | 342 (72.00%) | 39 (61.90%) |
| Conventional | 11 (1.81%) | 5 (7.04%) | 6 (1.26%) | 0 (0%) |
| Electronic cigarette | 86 (14.12%) | 14 (19.72%) | 61 (12.84%) | 11 (17.46%) |
| Dual | 88 (14.45%) | 9 (12.68) | 66 (14.45%) | 13 (20.63%) |
| Total | 609 (100%) | 71 (100%) | 475 (100%) | 63 (100%) |
| Gender | ||||
| Female | 347 (56.98%) | 38 (53.52%) | 269 (56.98%) | 40 (63.49%) |
| Male | 254 (41.71%) | 33 (46.48%) | 202 (41.71%) | 19 (30.16%) |
| Nonbinary | 6 (0.99%) | 0 (0%) | 2 (0.42%) | 4 (6.35%) |
| Missing | 2 (0.33%) | 0 (0%) | 2 (0.42%) | 0 (0%) |
| Total | 609 (100%) | 71 (100%) | 475 (100%) | 63 (100%) |
| Race | ||||
| Caucasian | 263 (43.19%) | 24 (33.80%) | 219 (46.11%) | 20 (31.75%) |
| East Asian | 186 (30.54%) | 18 (25.35%) | 149 (31.37%) | 19 (30.16%) |
| South Asian | 25 (4.11%) | 4 (5.63%) | 19 (4.00%) | 2 (3.17%) |
| Hispanic | 30 (4.93%) | 15 (21.13%) | 9 (1.89%) | 6 (9.53%) |
| Black | 11 (1.81%) | 4 (5.63%) | 5 (1.05%) | 2 (3.17%) |
| Pacific Islander | 10 (1.22%) | 1 1.41%) | 4 (0.84%) | 5 (7.94%) |
| Middle Eastern | 3 (0.49%) | 0 (0%) | 3 (0.63%) | 0 (0%) |
| Mixed | 61 (10.02%) | 2 (2.82%) | 51 (10.74%) | 8 (12.70%) |
| Missing | 20 (3.28%) | 3 (4.23%) | 16 (3.37%) | 1 (1.59%) |
| Total | 609 (100%) | 71 (100%) | 475 (100%) | 63 (100%) |
| Ethnicity | ||||
| Hispanic | 31 (5.09%) | 16 (22.54%) | 9 (1.89%) | 6 (9.52%) |
| Non-Hispanic | 561 (92.12%) | 55 (77.46%) | 450 (94.74%) | 57 (90.47%) |
| Missing | 17 (2.79%) | 0 (0%) | 16 (3.37%) | 0 (0%) |
| Total | 609 (100%) | 71 (100%) | 475 (100%) | 63 (100%) |
| Age | ||||
| Mean (range) | 17.14 (13–20) | 18.97 (16–20) | 16.57 (13–20) | 19.35 (17–20) |
Figure 1. Locations of the 609 adolescent survey responders by IP address.
Responses were collected from 19 countries across 6 continents.
RESULTS
From Figure 1, we see a global map of the respondents to our survey. Although we had good global representation, the majority of the respondents are from affluent countries, ie, from North America and Europe. From Table 1, the majority of our participants were non-Hispanic, with substantial representation of Caucasian and east Asian people.
Inhalant use impacts sleep latency
We observed a significant association between inhalant use and sleep latency (P < .001), with dual use correlating with a longer sleep latency than nonsmokers (mean difference = 6.27 minutes; confidence interval = 1.40 to 11.13 minutes) (Figure 2A). When broken down by gender, this finding was significant in male dual users only (Figure 2B). We saw no correlation between inhalant use and anxiety or depression nor between inhalant use and cough severity/prevalence.
Figure 2. Gender and usage impacts sleep latency.
(A) Dual users and conventional users reported significantly longer sleep latency than nonsmokers. (B) In males, but not females, dual users reported significantly longer sleep latency than nonsmokers and e-cigarette users. *P = .042, **P < .01, ****P < .0001
Sleep latency differences between genders
Adolescents reported an increase in sleep duration with increasing age by 1-way analysis of variance (P = .009). When broken down by gender, females got significantly more sleep at ages 19 and 20 years than at age 14 years, by Tukey’s multiple comparisons test (P < .01; Figure 3A). However, males had no change in sleep duration with increasing age (Figure 3B). There was no significant correlation between inhalant use and sleep duration. When broken down by gender, female dual users got significantly more sleep than female nonsmokers, (P = .01; mean difference = 0.73 hours; confidence interval = 0.11 to 1.36 hours) (Figure 3C), whereas there was no difference in males (Figure 3D).
Figure 3. Gender and age impact sleep duration.
(A) Older adolescent females reported longer sleep duration than younger ones. Nineteen-year-olds reported increased sleep duration over 14–16 year olds, and 20 year olds reported increased sleep duration over 14 year olds. (B) Males had no significant changes in sleep duration across ages. (C) In females, dual users reported significantly increased sleep duration over nonsmokers. (D) Inhalant use was not associated with changes in sleep duration in males. *P < .05, **P < .01.
Adolescent age impacts sleep and wake times
Older adolescents (aged 18–20 years) reported a significantly later wake time of 9:10 am relative to the earlier wake time of 6:41 am reported by younger adolescents (age 13–17; Figure 4A). While older adolescents reported a later falling to sleep time of 12:56 am, relative to 11:23 pm reported by younger adolescents (Figure 4B), this difference of 1 hour and 33 minutes was significantly less than the wake time difference of 2 hours and 29 minutes between younger and older adolescents.
Figure 4. Age and inhalant use lead to alterations in wake-up time and time at which participants fall asleep.
(A) Older adolescents (aged 18–20) reported a significantly later wake time than younger adolescents (age 13–17). (B) Older adolescents reported later bedtime than younger adolescents. (C) Dual users reported a later wake time than nonsmokers and e-cigarette users. (D) Inhalant use did not affect sleep time. **P < .01, ****P < .0001.
Inhalant use impacts wake time
Inhalant use was found to impact wake times, with dual users reporting a later wake time of 9:06 am relative to both nonsmokers (7:22 am) and e-cigarette users (7:53 am; Figure 4C). Time at sleep onset was not impacted by inhalant use (Figure 4D).
DISCUSSION
Adolescents are an understudied population in the world of sleep medicine. Because they have been a target population for e-cigarette and tobacco companies, more is known about their ever increasing use of nicotine delivery devices. Marijuana use, both smoked and vaped, is climbing in this demographic, but again this has been understudied.23 Our findings contribute to the existing literature in a number of ways. First, we observed that, particularly in adolescent males, dual usage of conventional tobacco and e-cigarettes is associated with increased sleep latency. This finding fits with the known effects of nicotine, of which dual users have a higher intake, such that dual users are more likely to experience greater symptoms and side effects specific to nicotine compared to other users. While the effects of dual use on the developing brain remain unknown, we hypothesize that the effects may be similar to those of nicotine alone but amplified due to the higher nicotine intake by dual users of conventional tobacco and e-cigarettes. Overall, it is well described that the use of addictive substances during years in which brain development is ongoing leads to altered susceptibility and response to all addictive substances as an adult. Further data on the impact of vaping nicotine, vaping marijuana, and dual use of either or both with conventional tobacco is desperately needed.
Females reported significantly more sleep at age 19 and 20 years than at age 14 years, a finding that suggests that females get more sleep during their college years relative to during high school. With males, sleep duration remained constant throughout adolescence. Thus, the lower duration of sleep seen in females aged 14–16 years may be routed in gender-specific differences present during high school. We found that females aged 18–20 years woke up later, which could be the driving factor for the increased sleep duration seen in this demographic, allowing females to catch up to and match the amount of sleep obtained by males. We hypothesize that females in the college age range have more control over their schedule, permitting them to sleep in to their preferred wake time.
Prior studies have found that a 9 to 9 hour and 15 minute sleep duration per night is optimal for adolescents to sustain attention and maximize cognitive abilities throughout the day.24 This sleep duration is also important for emotional regulation, which may be particularly critical for teenagers.25 However, adolescents currently only report an average of 7 hours of sleep on school nights, with males reporting more sleep on average than females.26 These studies confirm the importance of moving high school start times later, as allowing adolescents to sleep longer would likely improve the health and cognitive ability of the developing brain.24,27–29 Our work suggests that high school start times remain too early for females, as adolescents in college are able to self-regulate via setting their own wake times.
We observed no correlation between inhalant usage and cough severity and prevalence or anxiety and depression via Hospital Anxiety and Depression Scale. This result contradicted some existing data from adult inhalant users.22,30 Our findings suggest that teenagers may respond differently than adults to inhalants. Further studies of adolescents are needed to explore these differences.
Our study had a number of strengths, such as a large sample size for all sleep-related data, an understudied area, a potentially vulnerable population, and a clinically relevant outcome. However, as with most novel research, we acknowledge a number of limitations. First, we lacked statistical power for some comparisons. For example, our group of conventional users was small, which signifies a shift away from solely tobacco smoking toward e-cigarette or dual usage. It could also signify a limited user response, so people who vape may have been more likely to respond than others. Second, because our methodology was social media-based surveys, our data may have been susceptible to both participation and sampling bias. For example, we had no control over those who decided to complete the survey or the accuracy of reporting. People without access to social media may have been unlikely to respond. Moreover, we did not require responses to all questions, leading to incomplete data sets. However, we erred on the side of including as many participants as possible, rather than mandating responses from participants who may have been uncomfortable answering certain questions. We do not believe that the prize incentive led to false responses because participants were allowed to enter the prize lottery without completing the survey. Third, our questionnaire did not assess socioeconomic factors, leading to a lack of adjustments for some potential confounders in the statistical analyses. Our fourth limitation is the difficulty with assessing causation rather than correlation. Instead of inhalant usage causing changes in sleep, inadequate sleep could lead to inhalant usage or an external factor could cause both.31,32 Despite these acknowledged limitations, we hope that our findings stimulate further mechanistic research.
Another consideration for this study is that the difference of 6.27 minutes found in sleep latency may be a small difference in a clinical setting. However, a study regarding medications to treat insomnia showed that the Food and Drug Administration-approved drug had improved sleep latency by 9.6 minutes relative to placebo controls.33 Moreover our group has shown a 6 minute change in objective sleep latency with eszopiclone (Lunesta Sunovion Pharmaceuticals Inc. Marlborough, MA), ie, of similar magnitude to our findings in the present study.34 With the similarity in the minutes of altered sleep latency, dual use of cigarettes and e-cigarettes may have a similar disruption in sleep as those who are being treated for insomnia. Moreover, some argue that insomnia can be self-perpetuating, suggesting that any deterioration in sleep onset latency may be problematic for some individuals.35
Interestingly, we detected no significant differences in overall sleep quality by PSQI score. It is possible that an increased sleep latency coupled with consistent disruption causes a later wake time, which balances duration and quality. The observation that significant changes in sleep latency and duration were detected led us to question whether the PSQI instrument is able to detect sleep quality in the adolescent population. In other words, the PSQI was designed for adults and may not be sensitive for the detection of sleep abnormalities in adolescents. Teenagers and young adults have a different perception of sleep quality, which may lead to differences in their responses to questions on the PSQI.36 While few studies have analyzed the psychometric properties of PSQI in adolescents, a recent study determined that PSQI scores have a moderate-to-large correlation with adolescent emotional problems.36,37
Teenage vulnerability is often overlooked in favor of larger or adult-focused surveys regarding sleep or inhalant usage. However, today’s adolescent health is the future and thus important for the health of future generations. Further data are required regarding the health impact of conventional tobacco and e-cigarettes on teenage health to define public health strategies.
CONCLUSIONS
Usage of nicotine-containing inhalants not only alters sleep in adults, but also is associated with changes in adolescent sleep health. Gender is known to play a role in both inhalant effects and sleep quality; here we show that gender may impact both the sleep quality of adolescent females and the sleep latency of adolescent male inhalant users.
DISCLOSURE STATEMENT
All authors have seen and approved the manuscript. This study was funded by grants from the National Institutes of Health NHLBI R01HL147326 (to LCA), the American Heart Association Beginning Grant in Aid 16BGIA27790079 (to LCA), and the Tobacco-Related Disease Research Program T30IP0965 (to LCA). The authors report no conflicts of interest.
ACKNOWLEDGMENTS
Author contributions: Conception and design of the experiments: C.M., L.C.A., S.B., D.G., and I.A. Acquisition, analysis, and interpretation of data: C.M., D.G., I.A., S.B., S.N. and L.C.A. Manuscript composition: C.M., D.G., I.A. and L.C.A. All authors reviewed, contributed to, and approved the manuscript.
ABBREVIATIONS
- e-cigarette
electronic cigarette
- PSQI
Pittsburgh Sleep Quality Index
REFERENCES
- 1. Newson R . Diet and Exercise and Sleep. Sleep Foundation. https://www.sleepfoundation.org/physical-health/diet-exercise-sleep . Updated Dec 4, 2020. . Accessed Mar 22, 2021.
- 2. Wickham SR, Amarasekara NA, Bartonicek A, Conner TS . The big three health behaviors and mental health and well-being among young adults: a cross-sectional investigation of sleep, exercise, and diet . Front Psychol. 2020. ; 11 : 579205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Healthy Sleep . Harvard. http://healthysleep.med.harvard.edu/healthy/about . Accessed March 22, 2021.
- 4. Gradisar M, Gardner G, Dohnt H . Recent worldwide sleep patterns and problems during adolescence: a review and meta-analysis of age, region, and sleep . Sleep Med. 2011. ; 12 ( 2 ): 110 – 118. [DOI] [PubMed] [Google Scholar]
- 5. Jo YH, Talmage DA, Role LW . Nicotinic receptor-mediated effects on appetite and food intake . J Neurobiol. 2002. ; 53 ( 4 ): 618 – 632. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Boddu SA, Bojanowski CM, Lam MT, et al . Use of electronic cigarettes with conventional tobacco is associated with decreased sleep quality in women . Am J Respir Crit Care Med. 2019. ; 200 ( 11 ): 1431 – 1434. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Carlos WG, Crotty Alexander LE, Gross JE, et al . Vaping-associated pulmonary illness (VAPI) . Am J Respir Crit Care Med. 2019. ; 200 ( 7 ): P13 – P14. [DOI] [PubMed] [Google Scholar]
- 8. Park E, Kwon M, Gaughan MR, Livingston JA, Chang YP . Listening to adolescents: Their perceptions and information sources about e-cigarettes . J Pediatr Nurs. 2019. ; 48 : 82 – 91. [DOI] [PubMed] [Google Scholar]
- 9. Wang L, Chen J, Ho SY, Leung LT, Wang MP, Lam TH . Exposure to e-cigarette advertising, attitudes, and use susceptibility in adolescents who had never used e-cigarettes or cigarettes . BMC Public Health. 2020. ; 20 ( 1 ): 1349. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Pagel JF, Forister N, Kwiatkowki C . Adolescent sleep disturbance and school performance: the confounding variable of socioeconomics . J Clin Sleep Med. 2007. ; 3 ( 1 ): 19 – 23 . [PubMed] [Google Scholar]
- 11. Weaver E, Gradisar M, Dohnt H, Lovato N, Douglas P . The effect of presleep video-game playing on adolescent sleep . J Clin Sleep Med. 2010. ; 6 ( 2 ): 184 – 189. [PMC free article] [PubMed] [Google Scholar]
- 12. Danner F, Phillips B . Adolescent sleep, school start times, and teen motor vehicle crashes . J Clin Sleep Med. 2008. ; 4 ( 6 ): 533 – 535. [PMC free article] [PubMed] [Google Scholar]
- 13. Ayas N, White D, Manson J, et al . A prospective study of sleep duration and coronary artery disease in women . Arch Intern Med. 2003. ; 163 ( 2 ): 205 – 209 . . [DOI] [PubMed] [Google Scholar]
- 14. Patel SR, Malhotra A, White DP, Gottlieb DJ, Hu FB . Association between reduced sleep and weight gain in women . Am J Epidemiol. 2006. ; 164 ( 10 ): 947 – 954. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Daghlas I, Dashti HS, Lane J, Aragam KG, Rutter MK, Saxena R, Vetter C . Sleep Duration and Myocardial Infarction . J Am Coll Cardiol. 2019. ; 74 ( 10 ): 1304 – 1314. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Spiegel K, Leproult R, Van Cauter E . Impact of sleep debt on metabolic and endocrine function . Lancet. 1999. ; 23 : 1435 – 1439 . . [DOI] [PubMed] [Google Scholar]
- 17. Sandadi S, Frasure HE, Broderick MJ, Waggoner SE, Miller JA, von Gruenigen VE . The effect of sleep disturbance on quality of life in women with ovarian cancer . Gynecol Oncol. 2011. ; 123 ( 2 ): 351 – 355. [DOI] [PubMed] [Google Scholar]
- 18. Kessler RC, McGonagle KA, Zhao S, et al . Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey . Arch Gen Psychiatry. 1994. ; 51 ( 1 ): 8 – 19. [DOI] [PubMed] [Google Scholar]
- 19. McGuire MT, Troisi A . Prevalence differences in depression among males and females: are there evolutionary explanations? Br J Med Psychol. 1998. ; 71 ( Pt 4 ): 479 – 491. [DOI] [PubMed] [Google Scholar]
- 20. Inkelis SM, Ancoli-Israel S, Thomas JD, Bhattacharjee R . Elevated risk of depression among adolescents presenting with sleep disorders . J Clin Sleep Med. 2021. ; 17 ( 4 ): 675 – 683. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Kessler RC . Epidemiology of women and depression . J Affect Disord. 2003. ; 74 ( 1 ): 5 – 13. [DOI] [PubMed] [Google Scholar]
- 22. Dicpinigaitis PV, Lee Chang A, Dicpinigaitis AJ, Negassa A . Effect of e-cigarette use on cough reflex sensitivity . Chest. 2016. ; 149 ( 1 ): 161 – 165. [DOI] [PubMed] [Google Scholar]
- 23. Lam T, Ogeil RP, Allsop S, et al . Insomnia and regulation of sleep-wake cycle with drugs among adolescent risky drinkers . J Clin Sleep Med. 2018. ; 14 ( 9 ): 1529 – 1537. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Watson NF, Martin JL, Wise MS, et al. ; American Academy of Sleep Medicine Board of Directors . Delaying middle school and high school start times promotes student health and performance: An American Academy of Sleep Medicine Position Statement . J Clin Sleep Med. 2017. ; 13 ( 4 ): 623 – 625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Short MA, Blunden S, Rigney G, et al . Cognition and objectively measured sleep duration in children: a systematic review and meta-analysis . Sleep Health. 2018. ; 4 ( 3 ): 292 – 300. [DOI] [PubMed] [Google Scholar]
- 26. Galland BC, Short MA, Terrill P, et al . Establishing normal values for pediatric nighttime sleep measured by actigraphy: a systematic review and meta-analysis . Sleep. 2018. ; 41 ( 4 ): zsy017. [DOI] [PubMed] [Google Scholar]
- 27. Sheldon SH, Pelayo R . School start time: a public health crisis . J Clin Sleep Med. 2020. ; 16 ( S1 ): 11 – 12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Barlaan DR, Sinor K, Cromer LD . Delayed school start times and motor vehicle accidents: a need for further inquiry . J Clin Sleep Med. 2020. ; 16 ( 9 ): 1627. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Bin-Hasan S, Kapur K, Rakesh K, Owens J . School start time change and motor vehicle crashes in adolescent drivers . J Clin Sleep Med. 2020. ; 16 ( 3 ): 371 – 376. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Cassidy RN, Tidey JW, Colby SM . Exclusive e-cigarette users report lower levels of respiratory symptoms relative to dual e-cigarette and cigarette users . Nicotine Tob Res. 2020. ; 22 ( Suppl 1 ): S54 – S60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Oksenberg A . Alleviation of severe restless legs syndrome (RLS) symptoms by cigarette smoking . J Clin Sleep Med. 2010. ; 6 ( 5 ): 489 – 490. [PMC free article] [PubMed] [Google Scholar]
- 32. Campana LM, Clifford GD, Trinder J, Pittman SD, Malhotra A . A possible method to predict response to non-pharmacological insomnia therapy . J Clin Sleep Med. 2011. ; 7 ( 4 ): 370 – 375. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Rhyne DN, Anderson SL . Suvorexant in insomnia: efficacy, safety and place in therapy . Ther Adv Drug Saf. 2015. ; 6 ( 5 ): 189 – 195. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Eckert DJ, Owens RL, Kehlmann GB, et al . Eszopiclone increases the respiratory arousal threshold and lowers the apnoea/hypopnoea index in obstructive sleep apnoea patients with a low arousal threshold . Clin Sci (Lond). 2011. ; 120 ( 12 ): 505 – 514. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Riemann D, Spiegelhalder K, Feige B, et al . The hyperarousal model of insomnia: a review of the concept and its evidence . Sleep Med Rev. 2010. ; 14 ( 1 ): 19 – 31. [DOI] [PubMed] [Google Scholar]
- 36. Raniti MB, Allen NB, Schwartz O, et al . Sleep duration and sleep quality: associations with depressive symptoms across adolescence . Behav Sleep Med. 2017. ; 15 ( 3 ): 198 – 215. [DOI] [PubMed] [Google Scholar]
- 37. Dietch JR, Taylor DJ, Sethi K, Kelly K, Bramoweth AD, Roane BM . Psychometric evaluation of the PSQI in U.S. college students . J Clin Sleep Med. 2016. ; 12 ( 8 ): 1121 – 1129. [DOI] [PMC free article] [PubMed] [Google Scholar]