Abstract
Background
The prevalence of sleep disturbance is high and increasing. The study investigated whether active, former and passive smoking were associated with sleep disturbance.
Methods
This cross-sectional study used data from the UK Biobank: a cohort study of 502 655 participants, of whom 498 208 provided self-reported data on smoking and sleep characteristics. Multivariable multinomial and logistic regression models were used to examine the associations between smoking and sleep disturbance.
Results
Long-sleep duration (>9 h) was more common among current smokers [odds ratio (OR): 1.47; 95% confidence interval (CI): 1.17–1.85; probability value (P) = 0.001] than never smokers, especially heavy (>20/day) smokers (OR: 2.85; 95% CI: 1.66–4.89; P < 0.001). Former heavy (>20/day) smokers were also more likely to report short (<6 h) sleep duration (OR: 1.41; 95% CI: 1.25–1.60; P < 0.001), long-sleep duration (OR: 1.99; 95% CI: 1.47–2.71; P < 0.001) and sleeplessness (OR: 1.47; 95% CI: 1.38–1.57; P < 0.001) than never smokers. Among never smokers, those who lived with more than one smoker had higher odds of long-sleep duration than those not cohabitating with a smoker (OR: 2.71; 95% CI: 1.26–5.82; P = 0.011).
Conclusions
Active and passive exposure to high levels of tobacco smoke are associated with sleep disturbance. Existing global tobacco control interventions need to be enforced.
Keywords: passive smoking, sleep disorders, smoking cessation, tobacco
Introduction
Worldwide, sleep disturbance affects more than one-third of the adult general population,1 and the prevalence is rising partly due to the ageing population and increasing urbanisation.2,3 The proportion of the English population taking sleep medication has doubled since 1983.4 Symptoms of sleep disturbance include sleeplessness or insomnia, short- and long-sleep duration, difficulty awakening in the morning and signs of daytime dysfunction, such as daytime sleepiness.5
Sleep disturbance predisposes to poor health, including cardiovascular diseases and mental health problems.6,7 Short (<6 h/day) and long (>9 h/day) sleep duration are particularly associated with increased risk of diabetes,8 cardiovascular diseases9 and memory impairment.10 Meta-analyses of cohort studies11,12 have consistently shown an increased mortality risk in persons reporting short- or long-sleep duration. Economic implications of sleep disturbance cannot be overlooked and include increased absenteeism and lost productivity,13 more accidents14 and increased healthcare utilisation and costs.13 In the USA, the annual economic burden of sleep disturbance has been estimated at $100 billion,13 and the National Health Service (NHS) in England spends around £50 million on sleep medication each year.15
It is evident that nicotine can stimulate the release of neurotransmitters, such as acetylcholine and norepinephrine16 which, in turn, may inhibit gamma-aminobutyric acid (GABA) and sleep-promoting neurons located in the ventrolateral preoptic area (VLPO), causing excessive arousal of the body.17 Electroencephalography (EEG) reports have also revealed marked differences in sleep waves between smokers and non-smokers, with smokers having frequent arousals.18 There is strong evidence that smoking cessation is associated with poor sleep;19 however, previous studies on active smoking and sleep characteristics have produced conflicting results. For instance, while some studies have reported positive associations between active smoking and sleep disturbance,20–25 others have reported no association26–32 or even negative associations.33–35 Furthermore, research is lacking into whether exposure to passive smoking is associated with sleep disturbance.
With the increasing geriatric population and increasing prevalence of sleep disturbance, understanding how exposure to tobacco smoke is associated with sleep behaviour may help strengthen the existing tobacco control interventions, which may subsequently reduce the impact of smoking on a wide range of health parameters, including sleep disturbance. We used the baseline data of a large population-based cohort study to examine the associations of active, former and passive smoking with various self-reported sleep characteristics including total sleep duration, sleeplessness, difficulty awakening in the morning and daytime dozing (DD).
Methods
Study population and procedures
UK Biobank36 recruited 502 655 men and women aged 40–69 years from the general population between 2006 and 2010. Participants attended one of 22 assessment centres across the UK where they completed a touch-screen questionnaire.37 A validated questionnaire was used to obtain information on a number of variables such as socio-demographic characteristics (age, sex and ethnicity), lifestyle factors (smoking behaviour), occupational information (frequency of shift work) and self-reported health (stress, depression and health rating) from the participants.36 Our study was cross-sectional and we used the baseline data in the UK Biobank.
In our study, we grouped the participants into ‘never smokers’, ‘former smokers’ and ‘current smokers’ based on their response to the questions: ‘Do you smoke now?’ and subsequent ones. Those who responded ‘Yes’ were considered as ‘current smokers.’ Participants who responded ‘No’ were further asked whether they had previously smoked. Those who had previously smoked were grouped as ‘former smokers’, and those who were neither current smokers nor had previously smoked were grouped as ‘never smokers.’ In addition, data on daily number of cigarettes consumed by current and former smokers, and whether never smokers lived with one or more current smoker were obtained from the participants.37
Sleep duration was defined as the total number of hours a respondent reported to be sleeping in a day. The participants were asked: ‘About how many hours of sleep do you get in every 24 h?’ We categorised the numerical responses into short-sleep duration (<6 h per day), normal (6–9 h per day) and long-sleep duration (>9 h per day) using the National Sleep Foundation definition of short-, long- and normal-sleep duration.38 The questions: ‘Do you have trouble falling asleep at night or do you wake up in the middle of the night?’ and ‘How likely are you to doze off or fall asleep during the daytime when you don’t mean to?’ were used to evaluate sleeplessness and DD, respectively.37
The participants’ health state was evaluated with a question that asked the participants to rate their health on a scale of 1–4: ‘1’ equated to ‘excellent health’ and ‘4’ equated to ‘poor health.’ They were also asked whether they felt ‘stressed’ or ‘depressed’ and their responses were used to ascertain stress and depression separately.37 Shift work was evaluated with a question that asked the participants to describe their current shift pattern, whether it involved a shift schedule. The responses were: ‘Not’, ‘Sometimes’, ‘Usually’ and ‘Always’ in shift work. Participants were further asked whether they considered themselves to be ‘Definitely a morning person’, ‘More of a morning person’, ‘More of an evening person’ and ‘Definitely an evening person’ based on the time they were most active. This was used to assess chronotype.37
Postcode of residence was used to allocate the participants to general population quintiles of socioeconomic status (proxy for household status), using the Townsend index which is derived from area-based information on unemployment, car ownership, ownership of house and overcrowding. The design of the UK Biobank has been published elsewhere.36,39
Statistical analyses
In order to identify confounding factors, the Pearson Chi-square (χ2), Chi-square test for trend and Kruskal–Wallis rank tests were used to examine whether there were significant differences in sleep characteristics and smoking status according to socio-demographic characteristics, lifestyle, occupational and health factors. A series of logistic regression models were used to investigate the associations between tobacco exposure and sleep characteristics: sleeplessness, difficulty awakening in the morning and DD. We used a multinomial logistic regression model to examine the association between tobacco exposure and total sleep duration (long-, short- and normal-sleep duration). The models were initially run univariately, then multivariably. The multivariable models adjusted for covariates—age, sex, ethnicity, socioeconomic deprivation, self-reported stress and depression, alcohol and coffee consumption, physical activity level, engagement in shift work and self-identified chronotype—that were significantly associated with both the exposure and the outcome. Interaction tests were conducted and the associations were further stratified by covariates that had statistically significant interactions with smoking on the association with sleep disturbance, as appropriate.
Two-tailed test was used in all the analyses. Our study comprised a very large sample and might therefore be prone to Type I error. We therefore set statistically significant level at P ≤ 0.01, instead of the conventional P < 0.05. The assumptions underlying the validity of χ2 and Kruskal–Wallis tests were examined, and the Hosmer–Lemeshow test was further used to assess the goodness-of-fit of the multivariable regression models. All analyses were undertaken using Stata version 14.0. This study was conducted under the generic approval for UK Biobank from the NHS National Research Ethics Service (approval letter dated 17 June 2011, ref 11/NW/0382).
Results
Characteristics of the participants
Of the 502 655 UK Biobank participants, 498 208 (99.1%) were eligible for inclusion in the study. Of these, 54.4% were women and the mean age was 56.5 years. Overall, 27 383 (5.5%) reported short total sleep duration (<6 h), 9234 (1.9%) long-sleep duration (>9 h), 359 722 (28.2%) sleeplessness, 378 828 (24.1%) DD and 407 251 (18.1%) difficulty awakening in the morning (Table 1).
Table 1.
Participants’ characteristics by sleep characteristics
| <6 h, n = 27 383 (%) | 6–9 h, n = 461 591 (%) | >9 h, n = 9234 (%) | Sleeplessness, n = 141 427 (%) | DMA, n = 89 723 (%) | DD, n = 120 047 (%) | |
|---|---|---|---|---|---|---|
| Sex | ||||||
| Male | 43.6 | 45.8 | 44.5 | 61.6 | 45.6 | 49.2 |
| Female | 56.4 | 54.2 | 55.5 | 38.4 | 54.4 | 50.8 |
| Age (years) | ||||||
| <47 | 13.1 | 15.5 | 12.7 | 11.3 | 15.3 | 10.8 |
| 47–56 | 32.0 | 30.1 | 24.8 | 29.5 | 30.2 | 26.0 |
| 57–66 | 43.9 | 43.8 | 46.5 | 47.4 | 43.8 | 48.4 |
| >66 | 10.7 | 10.6 | 16.0 | 11.8 | 10.7 | 14.9 |
| Ethnicity | ||||||
| White | 89.6 | 95.0 | 92.0 | 95.7 | 94.5 | 91.6 |
| Black | 4.7 | 1.4 | 2.6 | 1.2 | 1.7 | 2.8 |
| Asian | 2.8 | 1.9 | 2.8 | 1.6 | 2.0 | 3.1 |
| Chinese | 0.3 | 0.3 | 0.4 | 0.2 | 0.3 | 0.5 |
| Other | 1.6 | 0.9 | 1.5 | 0.8 | 0.9 | 1.4 |
| Mixed | 1.0 | 0.7 | 0.8 | 0.6 | 0.6 | 0.6 |
| Deprivation quintile | ||||||
| 1 (least deprived) | 14.4 | 20.6 | 13.8 | 19.0 | 20.7 | 17.8 |
| 2 | 15.5 | 20.4 | 16.3 | 19.2 | 20.0 | 18.4 |
| 3 | 17.6 | 20.3 | 17.7 | 19.6 | 19.9 | 19.2 |
| 4 | 21.1 | 19.9 | 21.5 | 20.2 | 20.0 | 20.3 |
| 5 (most deprived) | 31.4 | 18.9 | 30.7 | 21.9 | 20.1 | 24.3 |
| Alcohol consumption (glasses/day) | ||||||
| 0 | 43.4 | 32.9 | 46.1 | 24.1 | 33.4 | 35.0 |
| 1–4 | 30.9 | 36.8 | 28.4 | 22.1 | 36.4 | 37.1 |
| 5–9 | 15.0 | 18.5 | 13.9 | 11.5 | 18.3 | 17.2 |
| >9 | 10.7 | 11.9 | 11.7 | 8.0 | 11.9 | 10.7 |
| Physical activity (min/day) | ||||||
| 0 | 0.1 | 0.1 | 0.3 | 0.1 | 0.1 | 0.2 |
| 1–30 | 45.3 | 48.2 | 48.2 | 47.5 | 47.5 | 48.1 |
| 31–60 | 27.1 | 28.4 | 27.3 | 27.9 | 28.3 | 27.9 |
| 61–90 | 4.5 | 4.2 | 4.3 | 4.4 | 4.4 | 4.3 |
| >90 | 23.0 | 19.1 | 19.9 | 20.1 | 19.6 | 19.7 |
| Engagement in shift work | ||||||
| Never | 72.6 | 83.4 | 73.0 | 82.4 | 82.6 | 77.9 |
| Sometimes | 10.3 | 7.3 | 8.8 | 7.4 | 7.5 | 8.6 |
| Usually | 3.3 | 2.1 | 3.1 | 2.1 | 2.1 | 2.8 |
| Always | 13.8 | 7.3 | 15.1 | 8.0 | 7.9 | 10.6 |
| Self-identified chronotype | ||||||
| Definitely morning | 34.8 | 26.7 | 24.7 | 27.7 | 27.2 | 28.9 |
| More morning | 29.3 | 36.0 | 27.0 | 34.3 | 35.4 | 34.1 |
| More evening | 24.5 | 28.6 | 32.5 | 27.8 | 28.5 | 27.4 |
| Definitely evening | 11.3 | 8.7 | 15.8 | 10.2 | 8.9 | 9.6 |
| Self-reported stress | ||||||
| No | 69.5 | 77.1 | 66.4 | 69.3 | 76.5 | 71.1 |
| Yes | 30.5 | 22.9 | 33.6 | 30.7 | 23.5 | 28.9 |
| Self-reported depression | ||||||
| No | 43.0 | 60.8 | 43.6 | 46.9 | 59.5 | 50.9 |
| Yes | 57.0 | 39.2 | 56.4 | 53.1 | 40.5 | 49.1 |
| Self-reported health state | ||||||
| Excellent | 8.9 | 17.1 | 8.0 | 11.2 | 16.4 | 12.0 |
| Good | 45.6 | 59.2 | 37.7 | 52.1 | 57.9 | 53.0 |
| Fair | 31.8 | 20.2 | 32.4 | 27.7 | 21.2 | 26.7 |
| Poor | 13.7 | 3.6 | 21.9 | 9.0 | 4.6 | 8.3 |
n, Number of participants; DMA, Self-reported Difficulty in morning awakening; DD, Self-reported daytime dozing
Participants who reported short- or long-sleep duration, sleeplessness and DD were older, more likely to be socioeconomically deprived, more likely to report feeling stressed or depressed, more likely to report poor overall health, less physically active, consumed more coffee and were more likely to work shifts (Table 1). In addition, women were more likely than men to report short- or long-sleep duration (Table 1) and sleeplessness (31.9% versus 23.8%), but were less likely to report DD (22.4% versus 26.0%).
Current smokers were more likely to report short- or long-sleep duration (10.9%) than either never (7.1%) or former (6.7%) smokers (Table 2). The prevalence of short- or long-sleep duration increased with the amount currently and previously smoked among current and former smokers, respectively (Table 2). Compared with never smokers who did not live with a smoker (6.9%), the prevalence of short- or long-sleep duration was higher among those who lived with one smoker (9.1%) and highest among those who lived with more than one smoker in the house (11.8%).
Table 2.
Prevalence of sleep characteristics
| <6 h, n = 27 383 (%) | 6–9 h, n = 461 591 (%) | >9 h, n = 9234 (%) | Sleeplessness, n = 141 427 (%) | DMA n = 89 723 (%) | DD, n = 120 047 (%) | |
|---|---|---|---|---|---|---|
| Smoking status | ||||||
| Never | 39.6 | 40.1 | 36.7 | 37.5 | 39.9 | 39.2 |
| Former | 44.5 | 49.4 | 46.6 | 50.7 | 48.9 | 49.7 |
| Current | 15.9 | 10.5 | 16.7 | 11.8 | 11.1 | 11.1 |
| Live with a smoker (never smokers) | ||||||
| No | 88.5 | 91.6 | 89.4 | 91.7 | 91.3 | 90.8 |
| Yes (1) | 9.9 | 7.5 | 9.4 | 7.4 | 7.8 | 8.2 |
| Yes (>1) | 1.6 | 0.9 | 9.4 | 0.9 | 1.0 | 1.1 |
n, Number of participants; DMA, Difficulty in morning awakening.
Smoking and sleep disturbance
On univariate analysis (Table 3), current smokers were more likely than never smokers to have short- or long-sleep duration. However, following adjustment for potential confounders, only the association with long-sleep duration remained statistically significant (adjusted odds ratio (OR): 1.47; 95% confidence interval (CI): 1.17–1.85; P = 0.001). When we adjusted for health status, we found that 8.8% of the observed association could be explained by poor health. The odds of long-sleep duration was particularly highest among those who smoked more than 20 cigarettes per day (adjusted OR: 2.85; 95% CI: 1.66–4.89; P < 0.001). Current smokers were, however, less likely to report DD than never smokers (adjusted OR: 0.91; 95% CI: 0.86–0.96; P = 0.001), with evidence of a dose-relationship whereby the likelihood of DD decreased with the amount smoked per day (Table 4).
Table 3.
Multinomial logistic regression analyses of smoking and sleep duration
| Univariate | Multivariable | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| <6 h | 6–9 h | >9 h | <6 h | 6–9 h | >9 h | |||||
| OR (95% CI) | P-value | OR | OR (95% CI) | P-value | OR (95% CI) | P-value | OR | OR (95% CI) | P-value | |
| Smoking status | ||||||||||
| Never | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| Former | 0.91 (0.89–0.94) | <0.001 | 1.00 | 1.03 (0.98–1.08) | 0.197 | 0.96 (0.90–1.02) | 0.154 | 1.00 | 1.13 (0.97–1.33) | 0.122 |
| Current | 1.54 (1.49–1.60) | <0.001 | 1.00 | 1.74 (1.64–1.85) | <0.001 | 1.03 (0.94–1.13) | 0.534 | 1.00 | 1.47 (1.17–1.85) | 0.001* |
| Cigarettes/day (current smokers) | ||||||||||
| 0 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| 1–10 | 1.43 (1.34–1.53) | <0.001 | 1.00 | 1.60 (1.43–1.80) | <0.001 | 1.08 (0.91–1.29) | 0.351 | 1.00 | 1.47 (1.00–2.18) | 0.052 |
| 11–20 | 1.77 (1.67–1.87) | <0.001 | 1.00 | 1.96 (1.79–2.15) | <0.001 | 0.99 (0.85–1.17) | 0.947 | 1.00 | 1.11 (0.73–1.69) | 0.626 |
| >20 | 2.55 (2.34–2.77) | <0.001 | 1.00 | 2.78 (2.41–3.19) | <0.001 | 1.46 (1.15–1.87) | 0.002* | 1.00 | 2.85 (1.66–4.89) | <0.001* |
| Cigarettes/day (former smokers) | ||||||||||
| 0 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| 1–10 | 0.85 (0.80–0.90) | <0.001 | 1.00 | 0.85 (0.77–0.94) | 0.002 | 0.88 (0.77–1.01) | 0.062 | 1.00 | 0.98 (0.71–1.37) | 0.917 |
| 11–20 | 0.96 (0.92–1.00) | 0.070 | 1.00 | 1.24 (1.16–1.33) | <0.001 | 0.96 (0.87–1.06) | 0.395 | 1.00 | 1.23 (0.97–1.56) | 0.085 |
| >20 | 1.44 (1.37–1.52) | <0.001 | 1.00 | 1.90 (1.75–2.06) | <0.001 | 1.41 (1.25–1.60) | <0.001* | 1.00 | 1.99 (1.47–2.71) | <0.001* |
| Live with a smoker (never smokers) | ||||||||||
| No | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| Yes (1) | 1.37 (1.28–1.46) | <0.001 | 1.00 | 1.28 (1.14–1.44) | <0.001 | 1.02 (0.87–1.20) | 0.792 | 1.00 | 0.86 (0.54–1.38) | 0.402 |
| Yes (>1) | 1.91 (1.63–2.24) | <0.001 | 1.00 | 1.46 (1.07–1.99) | 0.018 | 1.47 (0.99–2.15) | 0.051 | 1.00 | 2.71 (1.26–5.82) | 0.011* |
Multivariable adjusted for age, sex, ethnicity, social deprivation quintile, self-reported stress, self-reported depression, alcohol and coffee consumption, physical activity level, shift work and self-identified chronotype.
*Statistically significant results (P-value ≤0.01).
Table 4.
Logistic regression analysis of smoking and sleeplessness, DMA and DD
| Sleeplessness | DMA | DD | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Univariate | Multivariable | Univariate | Multivariable | Univariate | Multivariable | |||||||
| OR (95% CI) | P-value | OR (95% CI) | P-value | OR (95% CI) | P-value | OR (95% CI) | P-value | OR (95% CI) | P-value | OR (95% CI) | P-value | |
| Smoking status | ||||||||||||
| Never | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | ||||||
| Former | 1.14 (1.13–1.16) | <0.001 | 1.10 (1.07–1.14) | <0.001* | 1.00 (0.99–1.02) | 0.745 | 1.01 (0.98–1.05) | 0.392 | 1.04 (1.03–1.06) | <0.001 | 1.05 (1.02–1.08) | 0.004* |
| Current | 1.22 (1.19–1.24) | <0.001 | 1.05 (1.00–1.10) | 0.041 | 1.00 (0.98–1.03) | 0.641 | 1.03 (0.98–1.08) | 0.269 | 1.05 (1.03–1.07) | <0.001 | 0.91 (0.86–0.96) | 0.001* |
| Cigarettes/day (current smokers) | ||||||||||||
| 0 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | ||||||
| 1–10 | 1.20 (1.15–1.24) | <0.001 | 1.07 (0.98–1.16) | 0.728 | 0.97 (0.93–1.02) | 0.273 | 0.92 (0.84–1.02) | 0.109 | 0.96 (0.92–1.00) | 0.036 | 0.87 (0.79–0.96) | 0.007* |
| 11–20 | 1.34 (1.29–1.38) | <0.001 | 1.01 (0.93–1.10) | 0.783 | 1.01 (0.97–1.05) | 0.542 | 1.11 (1.01–1.21) | 0.023 | 1.05 (1.02–1.09) | 0.003 | 0.83 (0.75–0.91) | <0.001* |
| >20 | 1.70 (1.60–1.80) | <0.001 | 1.15 (0.99–1.36) | 0.072 | 0.99 (0.92–1.06) | 0.694 | 1.04 (0.88–1.23) | 0.664 | 1.17 (1.10–1.25) | <0.001 | 0.74 (0.62–0.89) | 0.001* |
| Cigarettes/day (former smokers) | ||||||||||||
| 0 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.0.00 | ||||||
| 1–10 | 1.23 (1.20–1.27) | <0.001 | 1.14 (1.08–1.21) | <0.001* | 1.00 (0.96–1.03) | 0.768 | 0.98 (0.92–1.04) | 0.440 | 1.03 (1.00–1.06) | 0.053 | 1.08 (1.01–1.15) | 0.016* |
| 11–20 | 1.25 (1.23–1.28) | <0.001 | 1.18 (1.13–1.23) | <0.001* | 1.02 (0.99–1.04) | 0.201 | 1.02 (0.97–1.07) | 0.358 | 1.04 (1.02–1.07) | <0.001 | 0.97 (0.92–1.02) | 0.215 |
| >20 | 1.50 (1.46–1.55) | <0.001 | 1.47 (1.38–1.57) | <0.001* | 1.02 (0.99–1.06) | 0.210 | 1.03 (0.95–1.11) | 0.479 | 1.32 (1.28–1.36) | <0.001 | 1.05 (0.97–1.13) | 0.230 |
| Live with a smoker (never smokers) | ||||||||||||
| No | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | ||||||
| Yes (1) | 1.15 (1.11–1.20) | <0.001 | 1.05 (0.97–1.13) | 0.261 | 1.01 (0.97–1.06) | 0.507 | 1.10 (1.01–1.20) | 0.025 | 1.09 (1.05–1.14) | <0.001 | 1.08 (0.99–1.17) | 0.104 |
| Yes (>1) | 1.21 (1.10–1.34) | <0.001 | 1.03 (0.83–1.29) | 0.785 | 1.10 (0.98–1.24) | 0.113 | 1.17 (0.93–1.47) | 0.186 | 1.30 (1.17–1.44) | <0.001 | 1.23 (0.97–1.55) | 0.153 |
Multivariable adjusted for age, sex, ethnicity, social deprivation quintile, self-reported stress, self-reported depression, alcohol and coffee consumption, physical activity level, shift work and self-identified chronotype.
*Statistically significant results (P-value ≤0.01).
Overall, there was no statistically significant association between former smokers and short- or long-sleep duration: (adjusted OR: 0.96; 95% CI: 0.90–1.02) and (adjusted OR: 1.13; 95% CI: 0.97–1.33), respectively. However, on sub-group analysis, former smokers who had previously smoked more than 20 cigarettes per day had statistically significantly higher odds of short (adjusted OR: 1.41; 95% CI: 1.25–1.60; P < 0.001) and long-sleep duration (adjusted OR: 1.99; 95% CI: 1.47–2.71; P < 0.001) than never smokers (Table 3). Former smokers were also more likely to report sleeplessness (adjusted OR: 1.10; 95% CI: 1.07–1.14; P < 0.001) and DD (adjusted OR: 1.05; 95% CI: 1.02–1.08; P = 0.004) than never smokers, with the highest risk of sleeplessness apparent among those who previous smoked more than 20 cigarettes per day (Table 4). Similarly, never smokers who lived with one or more smoker had an increased odds of long-sleep duration (adjusted OR: 2.71; 95% CI: 1.26–5.82; P = 0.011). However, neither active nor passive exposure to tobacco smoke was significantly associated with difficulty in awakening in the morning in this study.
Sub-group analyses revealed that most of the statistically significant associations were stronger in men, white participants, those aged 47–66 years and participants who were not in any shift work. In addition, ‘evening type’ current smokers were more likely to report long-sleep duration but were less likely to doze off at daytime, while sleeplessness was stronger among ‘morning type’ former smokers. However, there was no substantial difference in the effect size of the association between smoking and sleep disturbance in the deprivation quintiles.
In the sensitivity analysis (Supplementary Tables 2 and 3), current smokers still had statistically significantly higher odds of long-sleep duration (adjusted OR: 1.29; 95% CI: 1.04–1.60) and lower odds of DD (adjusted OR: 0.87; 95% CI: 0.83–0.92) than former smokers. Additionally, compared to former smokers, current smokers had lower odds of sleeplessness (adjusted OR: 0.95; 95% CI: 0.91–1.00).
Discussion
Main findings
Active, former and passive smoking were all associated with sleep disturbance. Consistent with previous studies, we demonstrated that former heavy smokers were more likely to report short- or long-sleep duration and sleeplessness. Furthermore, current and never smokers exposed to high levels of passive smoke were also more likely to report long-sleep duration. These associations were independent of socio-demographic, lifestyle, occupational and health confounding factors.
What is already known about the topic
Whilst previous studies have consistently shown an association between smoking cessation and sleep disturbance,19,40,41 the existing evidence in relation to current smoking is inconsistent.29–31,33–35 Some of the previous studies have been much smaller in size (range 88–498) and have varied in their definition of sleep disturbance.25,28,31 In addition, most previous studies have focused on sleeplessness; in comparison, sleep duration and daytime dysfunction have been relatively neglected. Some studies have also combined current and former smokers in a single group in the analyses,42–44 and many did not adjust for potential confounders such as engagement in shift work, chronotype and mental health.23,30,42,43,45
There is some evidence to suggest that sleep disturbance may vary by ethnicity;46 hence, it may be difficult to generalise findings from one country to another. Only one previous study has been conducted in the UK; a cross-sectional study of 1484 men and women living in rural Oxfordshire.47 The investigators reported that cigarette smoking was associated with shorter self-reported sleep duration in both sexes, but smoking was not associated with self-reported sleep quality.47 The investigators stratified the analyses by sex and adjusted for age but could not control for other potential confounders.
What this study adds
Our study comprised a very large sample of the general population. We were able to examine three types of tobacco exposure (current, former and passive smoking) and five measures of sleep disturbance (short-sleep duration, long-sleep duration, sleeplessness, difficulty awakening in the morning and DD) in the same study population. There is strong evidence of increased morbidity and mortality risk in persons reporting long-sleep duration.11,12 We showed that current smokers might be at increased risk of long-sleep duration and this might mediate the established harmful health effects of cigarette smoking. Importantly, short-, long- and normal-sleep durations were defined using a standard definition.38 To the best of our knowledge, this is the first population-based study to investigate how passive smoking is associated with both long-sleep duration and DD. Additionally, we were able to examine whether there was evidence of a dose-response relationship with the level of tobacco exposure in all the three groups: daily number of cigarettes smoked for current and former smokers and number of cohabitants who smoked for never smokers. A number of other factors are known to be associated with sleep disturbance and smoking including age, sex, physical illnesses,48 socioeconomic deprivation,4 alcohol consumption49 and we were able to adjust for these, and other potential confounders, in the analyses. Moreover, we stratified the associations by age, sex, ethnicity, chronotype and social deprivation. Furthermore, we conducted a sensitivity analysis to examine whether the sleep characteristics in current smokers differed from former smokers. These, in particular, have not been considered in the majority of the previous studies.
The mechanism underlying the association between cigarette smoking and sleep disturbance has been widely explored. Nicotine is known to stimulate the release of neurotransmitters, such as acetylcholine, dopamine and norepinephrine.16 It is believed that these neurotransmitters inhibit GABA and sleep-promoting neurons located in the VLPO, causing excessive arousal of the body, which may consequently lead to sleep disturbance.17 This has also been observed in EEG reports, where marked differences in the sleep waves were observed between smokers and non-smokers, with smokers having frequent arousals.18 Nicotine can entrain circadian timing mechanisms which strongly regulate the timing of the sleep wake cycle,50 and these might explain the increased risk of sleep disturbance and nicotine withdrawal effects such as sleeplessness and DD observed in our study.
Limitations of the study
The UK Biobank is representative of the UK general population, within the age range recruited, in terms of age, sex, ethnic and socioeconomic breakdown. However, participants are not necessarily representative in terms of lifestyle. Therefore, it would be inappropriate to generalise summary statistics, such as prevalence, to the general population. However, estimates of the magnitude of associations, such as between tobacco and sleep, should be generalisable. In common with most epidemiological studies of sleep, sleep characteristics were self-reported; objective measurement of parameters such as sleep duration would, however, not be feasible within such a large study. It is also important to mention that the questions used to evaluate sleep disturbance were not from a validated scale such as the General Sleep Disturbance Scale. Smoking characteristics were also self-reported; reports of smoking status and level of exposure could not be corroborated by objective measures such as cotinine assay. Whilst we adjusted for a wide range of potential confounders, residual confounding is always possible within any observational study. For instance, we used self-reported depression and stress as a proxy for mental health and it is possible that these do not completely measure overall mental health. Anxiety disorders are the most common mental disorders and are also associated with sleep disturbance and probably initiation of cigarette smoking, but we could not adjust for anxiety in our analysis. Additionally, since this was a cross-sectional study, it was not possible to determine the temporal relationship between smoking and sleep; therefore, reverse causation cannot be excluded. For example, sleep disturbance might lead to mental disorders such as anxiety and depression.51 There is some evidence to suggest that poor stress control and anxiety disorders are among the factors that predict initiation of cigarette smoking.52,53
Conclusions
Tobacco exposure is known to directly increase the risk of many diseases including respiratory and cardiovascular diseases and many cancers.54 Our study suggests that there is also an association between tobacco exposure and a number of sleep characteristics. If this association is causal, tobacco exposure may also be impacting on health partly via an effect on sleep. Smoking prevalence and exposure to passive smoking are declining in many developed countries. However, these improvements are more than offset by increases in highly populated, developing, and newly industrialised countries such as China. As a result, the global prevalence of active smoking and passive exposure to tobacco is expected to continue increasing over the next few decades.55 Currently, ~6 million deaths are attributed to smoking every year, of which 0.6 million are associated with passive smoke exposure.56 It may be beneficial to enforce the existing global tobacco control interventions to reduce the impact on a wide range of health parameters, including sleep disturbance.
Supplementary Material
Acknowledgements
We would like to thank the UK Biobank for providing an invaluable database for research in the interest of the general public.
Conflict of interest
None declared.
Authors’ contributions
DB, JPP and DFM designed the study, analysed the data and wrote the draft of the manuscript. CAW, CAM and SD contributed to the statistical analyses and review of the manuscript. SMB, MESB, JMRG and JW reviewed the final draft for submission.
Funding
Daniel Boakye was funded by the Commonwealth Scholarships Commission. UK Biobank was funded by the Wellcome Trust, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also received funding from the Welsh Assembly Government and the British Heart Foundation.
References
- 1. Zailinawati AH, Ariff KM, Nurjaham MI et al. . Epidemiology of insomnia in Malaysian adults. Asia-Pacific J Public Health 2008;20(3):224–33. [DOI] [PubMed] [Google Scholar]
- 2. Edwards B, O’Driscoll D, Ali A et al. . Aging and sleep: physiology and pathophysiology. Semin Respir Crit Care Med 2010;31(5):618–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Cyril S, Oldroyd JC, Renzaho A. Urbanisation, urbanicity, and health: a systematic review of the reliability and validity of urbanicity scales. BMC Public Health 2013;13:513–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Calem M, Bisla J, Begum A et al. . Increased prevalence of insomnia and changes in hypnotics use in England over 15 years: analysis of the 1993, 2000, and 2007 National Psychiatric Morbidity Surveys. Sleep 2012;35(3):377–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Walker HK, Hall WD, Hurst JW (eds). Clinical Methods: The History, Physical, and Laboratory Examinations, 3rd ed Boston: Butterworths, 1990:398–403. [PubMed] [Google Scholar]
- 6. Laugsand LE, Vatten LJ, Platou C et al. . Insomnia and the risk of acute myocardial infarction: a population study. Circulation 2011;124(19):2073–81. [DOI] [PubMed] [Google Scholar]
- 7. Concepcion T, Barbosa C, Velez JC et al. . Daytime sleepiness, poor sleep quality, eveningness chronotype and common mental disorders among Chilean college students. J Am Coll Heal 2014;62(7):441–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Kachi Y, Ohwaki K, Yano E. Association of sleep duration with untreated diabetes in Japanese men. Sleep Med 2012;13(3):307–9. [DOI] [PubMed] [Google Scholar]
- 9. Magee CA, Kritharides L, Attia J et al. . Short and long sleep duration are associated with prevalent cardiovascular disease in Australian adults. J Sleep Res 2012;21(4):441–7. [DOI] [PubMed] [Google Scholar]
- 10. Xu L, Jiang CQ, Lam TH et al. . Short or long sleep duration is associated with memory impairment in older Chinese: the Guangzhou Biobank Cohort Study. Sleep 2011;34(5):575–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. da Silva AA, de Mello RGB, Schaan CW et al. . Sleep duration and mortality in the elderly: a systematic review with meta-analysis. BMJ 2016;6(2):e008119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Cappuccio FP, D’Elia L, Strazzullo P et al. . Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies. Sleep 2010;33(5):585–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Wickwire EM, Shaya FT, Scharf SM. Health economics of insomnia treatments: the return on investment for a good night’s sleep. Sleep Med Rev 2016;30:72–82. [DOI] [PubMed] [Google Scholar]
- 14. Helbig AK, Döring A, Heier M et al. . Association between sleep disturbances and falls among the elderly: results from the German Cooperative Health Research in the Region of Augsburg-Age study. Sleep Med 2013;14(12):1356–63. [DOI] [PubMed] [Google Scholar]
- 15. Adams S. Sleeping pill cost to NHS almost £50 m - Telegraph [Internet]. The Telegraph. 2012. [cited 2016 May 25]. Available from: http://www.telegraph.co.uk/news/health/news/9257191/Sleeping-pill-cost-to-NHS-almost-50m.html
- 16. Benowitz NL. Pharmacology of nicotine: addiction, amoking-induced disease, and therapeutics. Annu Rev Pharmacol Toxicol 2009;49:57–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Saint-Mleux B, Eggermann E, Bisetti A et al. . Nicotinic enhancement of the noradrenergic inhibition of sleep-promoting neurons in the ventrolateral preoptic area. J Neurosci 2004;24(1):63–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Zhang L, Samet J, Caffo B et al. . Power spectral analysis of EEG activity during sleep in cigarette smokers. Chest 2008;133(2):427–32. [DOI] [PubMed] [Google Scholar]
- 19. Jaehne A, Loessl B, Bárkai Z et al. . Effects of nicotine on sleep during consumption, withdrawal and replacement therapy. Sleep Med Rev 2009;13(5):363–77. [DOI] [PubMed] [Google Scholar]
- 20. McNamara JPH, Wang J, Holiday DB et al. . Sleep disturbances associated with cigarette smoking. Pschol, Health Med 2014;19(4):410–9. [DOI] [PubMed] [Google Scholar]
- 21. Riedel B, Durrence H, Lichstein K et al. . The relation between smoking and sleep: the influence of smoking level, health and psychological variables. Behav Sleep Med 2004;2(1):63–78. [DOI] [PubMed] [Google Scholar]
- 22. Zhang L, Samet J, Caffo B et al. . Cigarette smoking and nocturnal sleep architecture. Am J Epidemiol 2006;164(6):529–37. [DOI] [PubMed] [Google Scholar]
- 23. Brook DW, Rubenstone E, Zhang C et al. . Trajectories of cigarette smoking in adulthood predict insomnia among women in late mid-life. Sleep Med 2012;13(9):1130–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Brook JS, Zhang C, Seltzer BA et al. . Insomnia in adults: the impact of earlier cigarette smoking from adolescents to adulthood. J Addict Med 2015;9(1):40–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Cohrs S, Rodenbeck A, Riemann D et al. . Impaired sleep quality and sleep duration in smokers-results from the German Multicenter Study on Nicotine Dependence. Addict Biol 2012;May:1–12. [DOI] [PubMed] [Google Scholar]
- 26. Jaehne A, Unbehaun T, Feige B et al. . How smoking affects sleep: a polysomnographical analysis. Sleep Med 2012;13(10):1286–92. [DOI] [PubMed] [Google Scholar]
- 27. Masood S, Cappelli C, Li Y et al. . Cigarette smoking is associated with unhealthy patterns of food consumption, physical activity, sleep impairment, and alcohol drinking in Chinese male adults. Int J Public Health 2015;60(8):891–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Haario P, Rahkonen O, Laaksonen M et al. . Bidirectional associations between insomnia symptoms and unhealthy behaviours. J Sleep Res 2013;22(1):89–95. [DOI] [PubMed] [Google Scholar]
- 29. Cheek RE, Shaver JL, Lentz MJ. Lifestyle practices and nocturnal sleep in midlife women with and without insomnia. Biol Res Nurs 2004;6(1):46–58. [DOI] [PubMed] [Google Scholar]
- 30. Kim K, Uchiyama M, Okawa M et al. . Lifestyles and sleep disorders among the Japanese adult population. Psychiatry Clin Neurosci 1999;53(2):269–70. [DOI] [PubMed] [Google Scholar]
- 31. Kageyama T, Kobayashi T, Nishikido N et al. . Associations of sleep problems and recent life events with smoking behaviors among female staff nurses in Japanese hospitals. Ind Health 2005;43(1):133–41. [DOI] [PubMed] [Google Scholar]
- 32. Asghari A, Kamrava SK, Rezaee Hemami M et al. . Cigarette smoking habit and subjective quality of sleep. Scimetr 2015;3(1):3–6. [Google Scholar]
- 33. Fabsitz RR, Sholinsky P, Goldberg J. Correlates of sleep problems among men: the Vietnam Era Twin Registry. J Sleep Res 1997;6(1):50–6. [DOI] [PubMed] [Google Scholar]
- 34. Wang Y-M, Chen H-G, Song M et al. . Prevalence of insomnia and its risk factors in older individuals: a community-based study in four cities of Hebei Province, China. Sleep Med 2015;10(18):4–18. [DOI] [PubMed] [Google Scholar]
- 35. Xiang Y-T, Ma X, Cai Z-J et al. . The prevalence of insomnia, its sociodemographic and clinical correlates, and treatment in rural and urban regions of Beijing, China: a general population-based survey. Sleep 2008;31(12):1655–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. UK Biobank Coordinating Centre UK Biobank: Protocol for a large-scale prospective epidemiological resource UK Biobank Coordinating Centre Stockport. Design 2007;06(March):1–112. [Google Scholar]
- 37. UK Biobank UK Biobank Touchscreen Questionnaire [Internet]. [Accessed 7 June 2017]. p. 1–78. Available from: https://www.ukbiobank.ac.uk/wp-content/uploads/2011/06/Touch_screen_questionnaire.pdf?phpMyAdmin=trmKQlYdjjnQIgJ%2CfAzikMhEnx6
- 38. The National Sleep Foundation National Sleep Foundation Recommends New Sleep Times [Internet]. [Accessed 27 May 2016]. p. 12–4. Available from: http://sleepfoundation.org/media-center/press-release/national-sleep-foundation-recommends-new-sleep-times
- 39. Sudlow C, Gallacher J, Allen N et al. . UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 2015;12(3):1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Hu L, Sekine M, Gaina A et al. . Association between sleep quality and smoking in Japanese civil servants. Sleep Biol Rythm 2007;5(3):196–203. [Google Scholar]
- 41. Benbir G, Demir AU, Aksu M et al. . Prevalence of insomnia and its clinical correlates in a general population in Turkey. Psychiatry Clin Neurosci 2015;69(9):543–52. [DOI] [PubMed] [Google Scholar]
- 42. Aslan S, Gulcat Z, Albayrak FS et al. . Prevalence of insomnia symptoms: results from an urban district in Ankara, Turkey. Int J Psychiatry Clin Pract 2006;10(1):52–8. [DOI] [PubMed] [Google Scholar]
- 43. Allavena C, Guimard T, Billaud E et al. . Prevalence and risk factors of sleep disturbance in a large HIV-infected adult population. AIDS Behav 2015;20:339–44. [DOI] [PubMed] [Google Scholar]
- 44. Abe Y, Mishima K, Kaneita Y et al. . Stress coping behaviors and sleep hygiene practices in a sample of Japanese adults with insomnia. Sleep Biol Rhythms 2011;9(1):35–45. [Google Scholar]
- 45. Philips BA, Danner FJ. Cigarette smoking and sleep disturbance. Arch Intern Med 1995;155:734–7. [PubMed] [Google Scholar]
- 46. Baldwin CM, Ervin AM, Mays MZ et al. . Sleep disturbances, quality of life, and ethnicity: the Sleep Heart Health Study. J Clin Sleep Med 2010;6(2):176–83. [PMC free article] [PubMed] [Google Scholar]
- 47. Palmer CD, Harrison GA, Hiorns RW. Association between smoking and drinking and sleep duration. Ann Hum Biol 1980;7(2):103–7. [DOI] [PubMed] [Google Scholar]
- 48. Tsou M-T. Prevalence and risk factors for insomnia in community-dwelling elderly in northern Taiwan. J Clin Gerontol Geriatr 2013;4(3):75–9. [Google Scholar]
- 49. Canham SL, Kaufmann CN, Mauro PM et al. . Binge drinking and insomnia in middle-aged and older adults: the Health and Retirement Study. Int J Geriatr Psychiatry 2015;30(3):284–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Gillman A, Leffel J, Kosobud A et al. . Behavioural characteristics and pharmacological manipulations of a nicotine-entrainable circadian oscillator. Chronobiol Int 2013;30(7):855–69. [DOI] [PubMed] [Google Scholar]
- 51. Alvaro PK, Roberts RM, Harris JK. A systematic review assessing bidirectionality between sleep disturbances, anxiety and depression. Sleep 2013;36(7):1059–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52. Choi D, Ota S, Watanuki S. Does cigarette smoking relieve stress? Evidence from event-related potential (ERP). Int J Psychophysiol 2015;98(3):470–6. [DOI] [PubMed] [Google Scholar]
- 53. Ah DV, Ebert S, Ngamvitroj A et al. . Factors related to cigarette smoking initiation and use among college students. Tob Induc Dis 2005;3(1):27–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54. U.S. Department of Health and Human Services Executive Summary (The Health Consequences of Smoking - 50 Years of Progress: A Report of the Surgeon General). Atlanta, GA; 2014.
- 55. Han J, Chen X. A meta-analysis of cigarette smoking prevalence among adolescents in China: 1981 – 2010. Int J Environ Res Public Health 2015;12:4617–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. World Health Organization WHO Global Report on Trends in Prevalence of Tobacco Smoking 2015. Geneva, Switzerland: World Health Organization, 2015:1. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.