Journal of Sleep Disorders & Therapy
Open Access

Enhancing First-Night Sleep Quality in Hotels: A Preliminary Study Utilizing Withings to Measure Sleep Patterns at Home and in Hotel Settings

Author info »

Introduction

Sleep is a fundamental physiological process that remains essential for the overall well-being of living organisms [1]. It plays a pivotal role in various aspects of human physical and mental health, as well as overall well-being. Beyond its physical advantages, sleep promotes emotional well-being, stress alleviation, and heightened concentration and memory [2]. The interplay of different sleep stages, along with their dynamic evolution throughout the night, contributes to the sleep architecture and sleep continuity. Deviations from these normal sleep stages often manifest as sleep disorders [3,4]. Sleep disorders have become increasingly prevalent in recent decades, affecting a significant portion of the population. In France, for example, one in three individuals’ reports experiencing sleep disturbances, with the French population now sleeping 1.5 hours less on average than they did 50 years ago [5].

Encountering difficulty sleeping in a novel environment is frequent, often termed the FNE. Polysomnographic (PSG) recordings consistently reveal compromised sleep architecture and sleep continuity during FNE, characterized by a reduction in total sleep time, increased wakefulness, diminished sleep efficiencies, a decrease in Rapid Eye Movement (REM) sleep, and prolonged REM sleep latencies on the first night fall [6-8]. Despite suggestions that FNE might extend beyond the initial night [9], increasing evidence demonstrates that FNE is often limited to the first night fall, and that sleep improves significantly during the second night fall, particularly in young and healthy participants [6,10-12].

During sleep, several physiological changes affect different body systems. These changes include modifications in cardiovascular parameters, respiratory patterns, cerebral blood flow and metabolism, shifts in renal function, and on endocrine functions [13-15]. These changes are well-tolerated in healthy individuals, while they may pose challenges to those with underlying health conditions. Also, sleep deprivation is recognized to have detrimental effects on both physiological and psychological well-being [16], which encompasses altered mood states, compromised decision-making skills, and cognitive impairment [17].

Our approach aims to prevent the FNE, encompassing a spectrum of sleep enhancement interventions, incorporating carefully designed practices to create an ideal sleep setting. We hypothesized that participants following this procedure would not have FNE in the hotel compared to home. To evaluate the duration of sleep and appraise its quality, we used wearable innovative tools that do not require any attachments to the body such as the Withings Sleep Analyzer (WSA) [18,19].

This study compared home sleep compared to sleep at hotel in 49 healthy medication-free participants using WSA to assess whether FNE may be prevented by sleep enhancement interventions.

Materials and Methods

Participants

Among the 60 screened participants, sleep data at both home and the hotel were successfully obtained for 49 individuals. Participants for whom sleep data were not recorded or correctly collected, either at home and/or at the hotel were excluded from the analysis. The average age of participants was 37 years (± 9.97), with 66% women, 32% men, and 2% other, undefined. The study focused on healthy volunteers without specific medical conditions or the intake of sleep drugs. All participants provided signed informed consent before participating in the study (Dream’night Hôtel Sofitel Arc-de-Triomphe study).

Study design

The study included two consecutive nights of sleep assessment, in which participants spent the initial night at home and the subsequent night in a hotel, with a few exceptions. The study utilized the Withings Sleep Analyzer (WSA), a device designed to assess sleep quantity [18], to compare nights in both settings, at home and in the hotel. WSA was positioned beneath the participants' mattresses. The Sleep Analyzer is classified as a medical device of level 2, designed to detect moderate to severe sleep apnea syndrome but also to evaluate sleep quality. Briefly, WSA consists of an air-filled thermoplastic polyurethane cushion linked to a pressure sensor. The device is encased in a protective sleeve and is powered by a 5V 1A power adapter, supplied with the device. Within the sleeve lies the air pocket, connected to a housing safeguarding the electronic components of the device. Automatic sleep period detection occurs in two stages. Initially, an algorithm detects the user's presence or absence on the bed, followed by a second algorithm that categorizes each minute as awake or asleep. Both algorithms employ a classifier that takes input from body movement, respiration, and heart rate activity channels, subsequently outputting the user's state (in bed/out of bed and awake/asleep). Total Sleep Time (TST) is defined as the total number of minutes during which a user is detected in bed and simultaneously labeled as asleep. Sleep Efficiency (SE) is calculated as TST divided by the total number of minutes during which a user is detected in bed.

WSA quantifies sleep quality and derives a 100-point score based on four key factors: Duration (total time spent sleeping), Depth (proportion of the night spent in restorative phases), Regularity (consistency in bedtime and wake-up times), and Interruptions (awake time). Duration and depth are the most important factors in computing the sleep score.

Sleep enhancement measurements

The study was conducted at the Sofitel Arc de Triomphe hotel in Paris, France. In the pursuit of optimizing sleep quality during hotel stays, various aspects have been established to promote restful sleep, from changing temperature, light, noise, food to relaxation. Temperature regulation is a pivotal factor in optimizing sleep, and this study maintained an ambient room temperature of 18°C to create the ideal sleep environment [20-24]. We also encouraged the use of warm socks, ensuring that individuals maintain physical warmth throughout the night for added comfort [25]. The Sofitel bed “MyBed” is designed exclusively for Sofitel and provides targeted pressure relief, ensuring comfort to the participants.

The food menu further emphasizes the interplay between dietary choices and sleep quality avoiding excesses in fat, salt, sugar, or spice, a selection chosen by a committee of scientific experts to guarantee a restorative night's sleep [26,27]. The study also focuses on auditory environments. It highlights the benefits of white and pink noise generators, which have a calming effect on the nervous system. Silicone earplugs that provide silence, have also been proposed, enabling restorative sleep undisturbed by external noise [28-30]. These auditory cues can mask unwanted external noises, establish a regular ambient background, and assist in focusing the mind during the process of falling asleep [31,32].

The study promotes the implementation of a structured presleep routine, featuring a session with the “Morphée” meditation box. This practice aims at reducing anxiety, combating bad sleep at night, and fostering relaxation, ultimately leading to improved sleep quality [33-35]. Accompanying this with a herbal tea to promote a restful sleep [36-38].

The “Baume du Dodo”, a lip balm that ensures soft lips during the night, together with a silk sleep mask, naturally hypoallergenic and gentle on the skin, were proposed to block out light for an uninterrupted sleep experience. Finally, a pillow spray enriched with essential oils, including lavender, chamomile, and marjoram, contributes to quicker sleep onset and improved sleep quality [39-42].

Statistical analysis

The statistical software GraphPad PRISM was used for conducting statistical tests. Statistical significance was assessed using Paired t-test. Data are presented as mean ± SEM (Standard Error of the Mean). In the figures the following scheme is used to express p-values: *denotes P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001.

Results

Global sleep score and sleep quality variations

Among 60 participants enrolled in the study, sleep measurements were successfully obtained for 49 individuals. The average sleep scores were significantly higher at the hotel compared to home setting (Figure 1A).

All participants were healthy with no sleep abnormalities. A subgroup analysis was conducted, focusing on individuals classified as poor-quality sleep participants, having sleep scores below 60 at home (n=20). For this subgroup, the sleep score at the hotel was significantly higher than that at home (Figure 1B), indicating that these poor-quality sleep participants experienced improved sleep quality at the hotel.

In participants with a high global sleep score (score >80), 52.8% (n=28) achieved this score at the hotel, compared to only 30% (n=16) at home (Figure 1C).

Figure 1: Variations in global sleep scores quality. Measurement of overall sleep score for all participants (A) and for poor-quality sleep participants (B). Each point represents the score of a participant measured at home and at the hotel. Data is represented as mean ± SEM. Paired t-test was used to determine the statistical significance between the two groups. (C) Number of participants with a high overall sleep score (>80).

Sleep duration and deep sleep quality

The duration and quality of sleep are two important factors that profoundly impact the computation of the sleep score. An analysis showed that participants experienced a significantly longer average sleep duration at the hotel (~453 min) compared to their sleep at home (~388 min). On average, this translates to an additional 65 minutes of sleep enjoyed by participants at the hotel (Figure 2A).

The duration of deep sleep, characterized by a profound relaxation of the body and a further slowdown of respiratory and heart rates, was significantly greater at the hotel compared to the home environment (Figure 2B). This observation highlights a superior sleep quality experienced at the hotel, marked by more extended and restorative phases of deep sleep.

Heart rates did not differ between nights spent at the hotel and at home (Figure 2C). This suggests that the sleep environment, whether at the hotel or home, did not significantly influence participants' heart rates during sleep.

Figure 2: Measurement of sleep duration and heart rate. (A) Measurement of total sleep duration. Each red or blue point represents a participant's sleep duration in minutes at home or at the hotel, respectively; (B) Measurement of deep sleep at home and at the hotel; (C) Heart rate measurement. Each point represents an individual participant's measurement during sleep. Data is presented as mean ± SEM. BPM: Beat Per Minute.

Discussion

This study examined the relationship between sleep duration and the surrounding sleep environment using the Withings Sleep Analyzer in healthy volunteers, with the aim of enhancing the overall sleep experience for individuals away from their familiar sleeping environment and thus avoid the FNE. This study provided a broad spectrum of factors that have the potential to enhance sleep duration and quality. For instance, the dietary habits such as avoiding excessive caffeine or heavy, spicy meals close to bedtime can improve sleep patterns. Practices such as meditation, progressive muscle relaxation, or controlled breathing can help individuals alleviate stress, a common disruptor of sleep. Offering an optimal ambient temperature, a silent environment, and without light certainly also helped improve sleep in a hotel setting [43,44]. These techniques were an integral component of a sleep-conducive environment by creating a state of mental promoting sleep initiation and maintenance. Notably, individuals classified as healthy but with sleep scores below 60 at home, demonstrated enhanced sleep quality when exposed to the optimized sleep environment at hotel. The prolonged duration of deep sleep observed in the participants also pointed to the potential of environmental adjustments to promote this essential phase of sleep.

During sleep, the heart rate usually drops, indicating the body's restful state [45,46]. Individual variations exist in both awake and sleeping heart rates, but no changes were found between nights spent in hotels and at home. This suggests that the sleep environment, whether in a hotel or at home, had no significant impact on participants' heart rates during sleep.

Study limitations

Our study has several key limitations that merit consideration. Firstly, the lack of randomization in the selection the nights spent at home and in a hotel can introduce bias into the study, as individual preferences, habits, or environmental factors may influence the results. Furthermore, the night spent in a hotel may not be optimized if the enhancement program is not fully implemented. The lack of data specifying which enhancement measures were tracked and which are important to the overall experience further hampers the study's ability to draw definitive conclusions. Indeed, it remains unclear how rigorously participants adhere to the proposed measures and to what extent they consider them as effective, raising questions about the reliability and consistency of the findings. Addressing these limitations is essential for ensuring the robustness and validity of any comparative sleep study between home and hotel environments. Sleep recordings in hotel and home settings were carried out during the weekdays and weekends, reflecting the variability of bedtimes, rising times and time in bed durations between days. Additionally, participants were recommended to participate in regular work activities the day after the hotel night, simulating the demands of everyday life. Bed arrangements exhibited variability, as participants were either alone in the hotel bed (with one exception), or, at home, the presence or absence of a bed partner was not explicitly specified. Unlike the hotel, factors such as ambient temperature, lighting and noise were not standardized at home, reflecting the variability of sleep environment under home conditions.

Conclusion

In conclusion, this study highlighted the importance of considering sleep solutions for conditions like the first-night effect, combining behavioral interventions, and optimizing sleep environments to improve sleep duration and quality. The preliminary study conducted on enhancing first-night fall in hotels through the utilization of Withings to measure sleep patterns at home and in hotel settings has provided valuable insights into the potential impact of the hotel environment on guests' sleep quality. This study underscores the importance of customized sleep solutions for conditions like FNE, emphasizing the need for a holistic approach that combines behavioral interventions and optimized sleep environments to improve overall sleep experience.

Acknowledgments

We extend our sincere gratitude to the Accor team for generously providing us access to their facilities. Special thanks to Hugo Saldmann and Leonie James from the Minerais Group for their assistance. We thank Prof. Yves Dauvilliers for proofreading this manuscript and providing insightful suggestions for the study.

Conflict of Interest

This study was financed by Minerais group.

References

1. Hobson JA. Sleep is of the brain, by the brain and for the brain. Nature. 2005;437(7063):1254-1256.

   [Crossref] [Google Scholar] [PubMed]

2. Goldstein AN, Walker MP. The role of sleep in emotional brain function. Annu Rev Clin Psychol. 2014;10:679-708.

   [Crossref] [Google Scholar] [PubMed]

3. Rémi J, Pollmächer T, Spiegelhalder K, Trenkwalder C, Young P. Sleep-related disorders in neurology and psychiatry. Dtsch Arztebl Int. 2019;116(41):681.

   [Crossref] [Google Scholar] [PubMed]

4. Ting L, Malhotra A. Disorders of sleep: An overview. Prim Care. 2005;32(2):305-318.

   [Crossref] [Google Scholar] [PubMed]

5. Beck F, Richard JB, Léger D. Insomnia and total sleep time in France: Prevalence and associated socio-demographic factors in a general population survey. Rev Neurol. 2013;169(12):956-964.

   [Crossref] [Google Scholar] [PubMed]

6. Agnew Jr HW, Webb WB, Williams RL. The first night effect: An Eeg studyof sleep. Psychophysiology. 1966;2(3):263-266.

   [Crossref] [Google Scholar] [PubMed]

7. Mendels J, Hawkins DR. Sleep laboratory adaptation in normal subjects and depressed patients (“first night effect”). Electroencephalogr Clin Neurophysiol. 1967;22(6):556-558.

   [Crossref] [Google Scholar] [PubMed]

8. Sharpley AL, Solomon RA, Cowen PJ. Evaluation of first night effect using ambulatory monitoring and automatic sleep stage analysis. Sleep. 1988;11(3):273-276.

   [Crossref] [Google Scholar] [PubMed]

9. Le Bon O, Staner L, Hoffmann G, Dramaix M, San Sebastian I, Murphy JR, et al. The first-night effect may last more than one night. J Psychiatr Res. 2001;35(3):165-172.

   [Crossref] [Google Scholar] [PubMed]

10. Lorenzo JL, Barbanoj MJ. Variability of sleep parameters across multiple laboratory sessions in healthy young subjects: The “very first night effect”. Psychophysiology. 2002;39(4):409-413.

    [Crossref] [Google Scholar] [PubMed]

11. Tamaki M, Bang JW, Watanabe T, Sasaki Y. The first-night effect suppresses the strength of slow-wave activity originating in the visual areas during sleep. Vision Res. 2014;99:154-161.

    [Crossref] [Google Scholar] [PubMed]

12. Ding L, Chen B, Dai Y, Li Y. A meta-analysis of the first-night effect in healthy individuals for the full age spectrum. Sleep Med. 2022;89:159-165.

    [Crossref] [Google Scholar] [PubMed]

13. Altevogt BM, Colten HR, editors. Sleep disorders and sleep deprivation: An unmet public health problem. 2006.

    [Crossref] [Google Scholar] [PubMed]

14. Carskadon MA, Dement WC. Normal human sleep: An overview. Principles and practice of sleep medicine. 2005;4(1):13-23.

    [Google Scholar]

15. Benarroch EE. Control of the cardiovascular and respiratory systems during sleep. Auton Neurosci. 2019;218:54-63.

    [Crossref] [Google Scholar] [PubMed]

16. Kamdar BB, Needham DM, Collop NA. Sleep deprivation in critical illness: Its role in physical and psychological recovery. J Intensive Care Med. 2012;27(2):97-111.

    [Crossref] [Google Scholar] [PubMed]

17. Killgore WD. Effects of sleep deprivation on cognition. Prog Brain Res. 2010;185:105-129.

    [Crossref] [Google Scholar] [PubMed]

18. Edouard P, Campo D, Bartet P, Yang RY, Bruyneel M, Roisman G, et al. Validation of the Withings Sleep Analyzer, an under-the-mattress device for the detection of moderate-severe sleep apnea syndrome. J Clin Sleep Med. 2021;17(6):1217-1227.

    [Crossref] [Google Scholar] [PubMed]

19. Pellegrini M, Lannin NA, Mychasiuk R, Graco M, Kramer SF, Giummarra MJ. Measuring sleep quality in the hospital environment with wearable and non-wearable devices in adults with stroke undergoing inpatient rehabilitation. Int J Environ Res Public Health. 2023;20(5):3984.

    [Crossref] [Google Scholar] [PubMed]

20. Fan X, Shao H, Sakamoto M, Kuga K, Lan L, Wyon DP, et al. The effects of ventilation and temperature on sleep quality and next-day work performance: Pilot measurements in a climate chamber. Build Environ. 2022;209:108666.

    [Crossref] [Google Scholar]

21. Xiong J, Lan L, Lian Z, de Dear R. Associations of bedroom temperature and ventilation with sleep quality. Sci Technol Built Environ. 2020;26(9):1274-1284.

    [Crossref] [Google Scholar]

22. Zhang X, Luo G, Xie J, Liu J. Associations of bedroom air temperature and CO2 concentration with subjective perceptions and sleep quality during transition seasons. Indoor air. 2021;31(4):1004-1117.

    [Crossref] [Google Scholar] [PubMed]

23. Akiyama Y, Miyake E, Matsuzaki R, Ogata M, Tsuzuki K, Tanabe SI. Effect of thermal environment on sleep quality in actual bedroom in summer by sleep stages analysis. Japan Architectural Review. 2021;4(1):211-221.

    [Crossref] [Google Scholar]

24. Tsang TW, Mui KW, Wong LT. Investigation of thermal comfort in sleeping environment and its association with sleep quality. Built Environ. 2021;187:107406.

    [Crossref] [Google Scholar]

25. Ko Y, Lee JY. Effects of feet warming using bed socks on sleep quality and thermoregulatory responses in a cool environment. J Physiol Anthropol. 2018;37:1-1.

    [Crossref] [Google Scholar] [PubMed]

26. Crispim CA, Zimberg IZ, dos Reis BG, Diniz RM, Tufik S, de Mello MT. Relationship between food intake and sleep pattern in healthy individuals. J Clin Sleep Med. 2011;7(6):659-664.

    [Crossref] [Google Scholar] [PubMed]

27. Khan MK, Faught EL, Chu YL, Ekwaru JP, Storey KE, Veugelers PJ. Is it nutrients, food items, diet quality or eating behaviours that are responsible for the association of children's diet with sleep? J Sleep Res. 2017;26(4):468-476.

    [Crossref] [Google Scholar] [PubMed]

28. Röösli M, Brink M, Rudzik F, Cajochen C, Ragettli MS, Flückiger B, et al. Associations of various nighttime noise exposure indicators with objective sleep efficiency and self-reported sleep quality: A field study. Int J Environ Res Public Health. 2019;16(20):3790.

    [Crossref] [Google Scholar] [PubMed]

29. Xie H, Kang J, Mills GH. Clinical review: The impact of noise on patients' sleep and the effectiveness of noise reduction strategies in intensive care units. Crit Care. 2009;13(2):1-8.

    [Crossref] [Google Scholar] [PubMed]

30. Duggan NM, Hasdianda MA, Baker O, Jambaulikar G, Goldsmith AJ, Condella A, et al. The effect of noise-masking earbuds (sleep buds) on reported sleep quality and tension in health care shift workers: Prospective single-subject design study. JMIR Form Res. 2022;6(3):e28353.

    [Crossref] [Google Scholar] [PubMed]

31. Diep C, Garcia-Molina G, Jasko J, Manousakis J, Ostrowski L, White D, et al. Acoustic enhancement of slow wave sleep on consecutive nights improves alertness and attention in chronically short sleepers. Sleep Med. 2021;81:69-79.

    [Crossref] [Google Scholar] [PubMed]

32. Cordi MJ, Ackermann S, Rasch B. Effects of relaxing music on healthy sleep. Sci Rep. 2019;9(1):9079.

    [Crossref] [Google Scholar] [PubMed]

33. Black DS, O’Reilly GA, Olmstead R, Breen EC, Irwin MR. Mindfulness meditation and improvement in sleep quality and daytime impairment among older adults with sleep disturbances: A randomized clinical trial. JAMA internal medicine. 2015;175(4):494-501.

    [Crossref] [Google Scholar] [PubMed]

34. Nagendra RP, Maruthai N, Kutty BM. Meditation and its regulatory role on sleep. Front Neurol. 2012;3:54.

    [Crossref] [Google Scholar] [PubMed]

35. Rusch HL, Rosario M, Levison LM, Olivera A, Livingston WS, Wu T, Gill JM. The effect of mindfulness meditation on sleep quality: A systematic review and meta‐analysis of randomized controlled trials. Ann N Y Acad Sci. 2019;1445(1):5-16.

    [Crossref] [Google Scholar] [PubMed]

36. Ngan A, Conduit R. A double‐blind, placebo‐controlled investigation of the effects of Passiflora incarnata (Passionflower) herbal tea on subjective sleep quality. Phytother Res. 2011;25(8):1153-1159.

    [Crossref] [Google Scholar] [PubMed]

37. Ehiri JC. the role of tea in sleep improvement and cancer prevention. In Neurological modulation of sleep 2020;245-254. Academic Press.

    [Crossref] [Google Scholar]

38. Chang SM, Chen CH. Effects of an intervention with drinking chamomile tea on sleep quality and depression in sleep disturbed postnatal women: A randomized controlled trial. J Adv Nurs. 2016;72(2):306-365.

    [Crossref] [Google Scholar] [PubMed]

39. Karadag E, Samancioglu S, Ozden D, Bakir E. Effects of aromatherapy on sleep quality and anxiety of patients. Nurs Crit Care. 2017;22(2):105-112.

    [Crossref] [Google Scholar] [PubMed]

40. Lin PC, Lee PH, Tseng SJ, Lin YM, Chen SR, Hou WH. Effects of aromatherapy on sleep quality: A systematic review and meta-analysis. Complement Ther Med. 2019;45:156-166.

    [Crossref] [Google Scholar] [PubMed]

41. Özkaraman A, Dugum O, Yilmaz HÜ, Usta Yeşilbalkan ÖZ. Aromatherapy The effect of lavender on anxiety and sleep quality in patients treated with chemotherapy. Clin J Oncol Nurs. 2018;22(2).

    [Crossref] [Google Scholar] [PubMed]

42. Radwan A, Ashton N, Gates T, Kilmer A, van Fleet M. Effect of different pillow designs on promoting sleep comfort, quality, and spinal alignment: A systematic review. Eu J Integr Med. 2021;42:101269.

    [Crossref] [Google Scholar]

43. Consensus Conference Panel, Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, et al. Recommended amount of sleep for a healthy adult: A joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. J Clin Sleep Med. 2015;11(6):591-592.

    [Crossref] [Google Scholar] [PubMed]

44. Eugene AR, Masiak J. The neuroprotective aspects of sleep. MEDtube Sci. 2015;3(1):35.

    [Crossref] [Google Scholar] [PubMed]

45. Baust W, Bohnert B. The regulation of heart rate during sleep. Exp Brain Res. 1969;7:169-180.

    [Crossref] [Google Scholar] [PubMed]

46. Versace F, Mozzato M, Tona GD, Cavallero C, Stegagno L. Heart rate variability during sleep as a function of the sleep cycle. Biol Psychol. 2003;63(2):149-162.

    [Crossref] [Google Scholar] [PubMed]