Stress and sleep: a survey based on wearable sleep trackers among medical and nursing staff in Wuhan during the COVID-19 pandemic

Participants

We included medical and nursing staff members working in Wuhan Children’s Hospital, Wuhan Central Hospital and other COVID-19 designated hospitals between January and March 2020. Prior to their enrolment, the participants were clinically evaluated by psychiatrists in the Shanghai Psychological First Aid Team for Wuhan.

Inclusion criteria

Patients (1) aged ≥18 years; (2) frequently presenting with symptoms of nocturnal insomnia, such as difficulty in falling asleep, difficulty in maintaining sleep and waking up early, which were accompanied by daytime fatigue, decline in attention or memory, impulsiveness and irritability, sleepiness and other symptoms since they began participating in COVID-19 efforts, as well as meeting the ICSD-3 (International Classification of Sleep Disorders-3) diagnostic criteria for short-term insomnia; (3) who have not taken benzodiazepine or non-benzodiazepine sedative hypnotics within the past month; and (4) who have provided a written informed consent.

Exclusion criteria

(1) Patients with concomitant cardiovascular, lung, liver, kidney, hematopoietic and other severe primary diseases and those with severe organic brain disease and mental illnesses; (2) patients with a history of alcoholism or use of other psychoactive substances; and (3) pregnant or breastfeeding women.

Medical ring-shaped pulse oximeter is a new type of wearable preliminary sleep screening instrument that can monitor pulse rate and blood oxygen changes overnight. Pulse rate indicators include mean pulse rate, minimum/maximum pulse rate and nocturnal pulse elevation index (ie, the number of sleeping heart rate fluctuations >6 times/min). Blood oxygen indicators include oxygen desaturation index (ODI₄; ie, the number of times blood oxygen saturation decreases by ≥4% per hour), mean percutaneous oxygen saturation (MSpO₂), percentage of total sleeping time spent with blood oxygen saturation <90% (TS 90%), among others. Studies conducted in China and globally have shown that ODI₄ is positively correlated with the Apnoea-Hypopnea Index, and an ODI₄ ≥15 times/hour was considered to provide an adequate degree of sensitivity and specificity to screen moderate to severe OSAHS.12

The Insomnia Severity Index (ISI) is an instrument developed by Morin et al to measure the self-perceived symptoms of insomnia in the prior 2 weeks.13 Compared with the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale, the ISI specifically assesses the severity of insomnia. ISI includes seven items, is relatively simple and convenient to administer and has a high level of empirical validity. It has been widely applied in clinical research and has demonstrated an excellent degree of consistency and effectiveness in reflecting the quality of sleep.

The Self-Reporting Questionnaire (SRQ-20) is an questionnaire developed by the WHO to screen for mental disorders and was designed specifically for developing countries. It consists of 20 questions, each of which may be scored as 0 or 1, and a higher score indicates a higher prominence of symptoms associated with mental disorders. Previously, this questionnaire was applied in the postdisaster mental health survey of the population, and it demonstrated considerably consistency reliability and criterion-related validity.14

Statistical analysis

Statistically analysis was performed using SPSS V.19.0. Measurement data obtained by monitoring were expressed as   ±s, and count data as percentage (%). T-tests and non-parametric Wilcoxon tests were respectively performed based on whether the data were normally distributed or not; χ² tests were performed to compare the incidences between two groups. We used the Pearson and Spearman correlation to analyse normally distributed and non-normally distributed measurement data, respectively. Stepwise logistic regression was performed to analyse the independent risk factors of insomnia with comorbid OSAHS. P<0.05 indicated that the difference was statistically significant.

General demographics and questionnaire survey

Forty-nine medical and nursing staff members were screened of which 30 enrolled. Finally 26 participants (14 men and 12 women) completed the study. The participant demographics, along with the questionnaire results are presented in table 1. The monitoring results of medical pulse oximetry are shown in table 2.

Analysis of ring-shaped pulse oximetric monitoring indicators

The total sleep time (TST), sleep efficiency (SE), light sleep stage, deep sleep stage, REM sleep stage, ODI, frequency of oxygen desaturation, TS90%, MSpO₂ and mean pulse rate were monitored using the pulse oximeter, and their results are shown in table 2. Using ODI ≥5 times/hour as the cut-off value for classification revealed that 14 cases (53.8%) presented with SAHS. Considering the fact that an ODI ≥15 times/hour was used to classify moderate to severe disorder, 10 cases (38.5%) were found to have moderate to severe SAHS.

Using the cut-off value of ODI ≥15 times/hour, we categorised the participants with an ODI <15 times/hour into the insomnia group, while those with ≥15 times/hour to the comorbid moderate to severe SAHS group, following which an intergroup comparison was performed. We used the non-parametric Wilcoxon test since both sets of data were not normally distributed. The results of the same are presented in table 3.

Given the significant intergroup differences with regard to the number of male and female participants, the analysis of covariance was performed with the patient sex as a covariate. The results indicated that the intergroup differences for ISI, SRQ, ODI, TS90% and MSpO₂ remained statistically significant (F=7.738, 7.472, 114.9, 6.925 and 11.64, p=0.011, 0.012, 0.000, 0.015 and 0.002, respectively).

Spearman correlation analysis for age, sex, ISI and SRQ with the various sleep indicators revealed that ISI was positively correlated with SRQ and TST (r=0.685, 0.435; p<0.001 and p<0.026) and negatively correlated with deep sleep (r=−0.495, p=0.010); furthermore, SRQ was positively correlated with TST, SE and REM% (r=0.454, 0.389, 0.512; p=0.020, 0.050 and 0.008, respectively).

Main findings

Outcomes of the screening conducted in this study revealed that the incidence of comorbid moderate to severe SAHS in insomnia patients was 38.5% (10/26). However, using a cut-off value of ODI ≥5 times/hour demonstrated that the proportion of SAHS patients with comorbid insomnia was even higher (53.8%). This finding further validates the outcomes of previous investigations using polysomnography. Guilleminault et al 15 first proposed the concept of OSAHS comorbid with insomnia in 1973, while Krakow et al 16 reported that OSAHS comorbidity was clinically significant in more than 50% of insomnia patients. The high comorbidity rate of OSAHS and insomnia suggests that these two diseases may not be purely concomitant but may share common pathophysiological mechanisms. In addition, the overactivation of the hypothalamic–pituitary–adrenal (HPA) axis under stress may be the link between the two.

In cases of traumatic stress, acute stress suppresses REM sleep and increases the duration of non-REM sleep, which is followed by restorative sleep compensation, increased sleep time and increased REM sleep.17 However, persistent or repeated chronic stress exposure may have a more negative impact on sleep, resulting in the presentation of sleep disorders, insomnia and other problems.18 In the presence of an active HPA axis, individuals may experience a lighter sleep, increasing awakenings and sleep fragmentation.19 Fragmented sleep can subsequently excite the sympathetic catecholamine system and elevate cortisol levels, which eventually results in persistent insomnia.20 Repeated awakenings and an increased frequency of light sleep can also lead to frequent sleep phase changes and upper airway instability, thereby exacerbating SAHS symptoms.21 SAHS-induced decrease in blood oxygen saturation generates hypoxic stress, which further activates the HPA axis while increasing the patients’ breathing rate to maintain adequate alveolar ventilation. This results in repeated microarousals during sleep, which disrupts the continuity and periodicity of sleep, which further fragments the sleep cycle.22

The Insomnia Severity Index (ISI) has demonstrated an acceptable degree of consistency and validity in reflecting the severity of insomnia.13 Our screening results showed that participants with insomnia and comorbid SAHS scored higher on the ISI than those with insomnia alone, and ISI was negatively correlated with the duration of deep sleep. These findings indicated that the lack of deep sleep continues to be the main cause of insomnia and that SAHS is a key factor responsible for the fragmentation and superficialisation of the sleep process.22 ISI was positively correlated with TST (r=0.435, p=0.026), which is inconsistent with the outcomes of previous studies that have reported a decrease in subjective and objective TST in insomnia patients. This may be attributed to the concomitant presentation of insomnia and SAHS that may further damage the sleep structure; alternatively, it may be due to the relatively small sample size of this study.

The self-reporting questionnaire (SRQ-20) has been translated into more than 10 languages for use in the corresponding regions around the world, and each version has been scrutinised for its reliability and validity.14 23 24 Jiang et al 14 studied the reliability and validity of the Chinese version of the SRQ-20, which was administered 3 weeks after the Wenchuan earthquake, and reported that this questionnaire had an acceptable degree of consistency reliability and criterion-related validity in reflecting the postdisaster traumatic stress experienced by victims. In this study, participants with insomnia and comorbid SAHS showed significantly higher SRQ scores than those with insomnia alone. The results of logistic regression analysis also indicated that the SRQ-20 score was a risk factor for insomnia with comorbid SAHS, with a higher score indicating a greater risk for insomnia with comorbid SAHS. This finding suggested that SAHS comorbidity may further introduce psychological problems in individuals who had previously experienced traumatic stress. Some studies have shown that OSAHS patients often concomitantly present with depression and anxiety, which are the factors that significantly contribute to a decline in their quality of life and lead to incidence rates of 34%–56%.25 Our correlation analyses revealed that the participants’ SRQ-20 scores were positively correlated with TST, SE and REM%, suggesting the significant impact of psychological factors on the participants’ sleep duration, quality and structure. Given that the participants had been under stress for 2 months when this screening was performed, they had been exposed to its effects for a relatively long period of time, which suggested the possibility of chronic stress exposure. Therefore, individuals may exhibit restorative sleep compensation, along with increased sleep duration and REM sleep, which is consistent with the outcomes of previous investigations.17

Middle-aged and overweight men are reportedly considered to be at risk for OSAHS.26 We also observed that the proportion of men was higher in the comorbid SAHS group, while the results of logistic regression analysis showed that men were more likely to have insomnia with comorbid SAHS. However, when considering sex as a covariate for further analysis, the results showed that the intergroup differences in ISI, SRQ, ODI, TS90% and MSpO₂ persisted, which suggests that sex may generate comorbid OSAHS in men with insomnia. However, the severity of SAHS and the degree of psychological distress were not affected by sex differences.

Wearable devices significantly improved the convenience of using sleep trackers, especially when we could continue to monitor the patients at their residence, which ensured that the monitoring environment was closer to natural sleep. However, research in China and globally on wearable sleep trackers is relatively limited. A study has shown that27 compared with portable EEG, wearable sleep trackers had better sensitivity (92.1%) and accuracy (88.5%) when evaluating TST and SE but showed significant bias when determining sleep latency and sleep cycle. Hence, this approach has its limitations.

Limitations

This study has certain limitations. First, this was a cross-sectional observational study. Although wearable pulse oximeters can easily monitor participants’ breathing during sleep, its clinical applications are considerably limited, and further testing is required to verify its reliability. Second, mental health screening was only performed using the ISI and SRQ, and a comprehensive psychological evaluation was not conducted on the participants’ stress severity, anxiety, depression and other psychological conditions. Lastly, the small sample size of this study may have affected our screening results. Therefore, future studies should effectively record clinical symptoms and signs, improve the parameters for psychological and sleep questionnaires and confirm the diagnosis of suspected insomnia with comorbid SAHS using overnight polysomnography, thereby exploring the inherent connections of stress, insomnia and SAHS to a greater degree.

Implications

During crisis intervention, sedative-hypnotic drugs, such as benzodiazepines, have been widely used to alleviate symptoms such as anxiety, tension and insomnia after stress and can rapidly improve clinical symptoms. Nevertheless, insomnia with comorbid SAHS has long been neglected in previous reports, and the use of benzodiazepines may worsen SAHS symptoms. Therefore, when assessing the situation during future emergency rescues, it is necessary to combine symptoms, signs and other clinical data to thoroughly screen insomnia patients with comorbid SAHS and avoid the adverse reactions caused by benzodiazepines.