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Effects of environment light during sleep on autonomic functions of heart rate and breathing



Poor sleep hygiene including sleeping in the daytime or with the lights on at night is discovered during the assessment of many sleep disorders including sleep apnea. The aim of this study was to investigate whether environmental light affected autonomic control of heart rate, sleep-disordered breathing (SDB), and/or breathing patterning.


Seventeen non-obese healthy volunteers without witnessed snoring and apneas were recruited. Studies were performed at home using a type 3 portable monitor combined with actigraphy for sleep-wake timing, using a randomly assigned, crossover between dark, or 1,000 lx of fluorescent lighting environment. The outcomes were low-frequency power divided by high-frequency power (LF/HF ratio) in the analysis of heart rate variability, the apnea-hypopnea index (AHI), and ventilatory pattern variability before and after sleep onset between environments.


The LF/HF ratio and AHI were both significantly higher in light as compared to dark. Before sleep onset, the coefficient of variation (CV) for breath-to-breath tidal volume representing breathing irregularity tended to be higher in light than in dark environment. The CV values for tidal volume after sleep onset were significantly decreased compared with before sleep onset in both sleep environments. Mutual information of the ventilatory pattern was significantly lower before sleep onset than after sleep onset, only in the light environment.


Sleeping in the light has effects like that of a stressor as it is associated with neuroexcitation, SDB, and resting breathing irregularity in healthy volunteers. These findings may be relevant to many sleep disorders associated with poor sleep hygiene.

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Apnea-hypopnea index


Body mass index


Nasal continuous positive airway pressure


Coefficient of variation





LF/HF ratio:

Low-frequency power divided by high-frequency power in the analysis of heart rate variability


Obstructive sleep apnea syndrome


Respiratory inductance plethysmography


Standard deviation


Sleep-disordered breathing


Pulse oximetry


Breath-to-breath respiratory duration


  1. Guilleminault C, Rosekind M (1981) The arousal threshold: sleep deprivation, sleep fragmentation, and obstructive sleep apnea syndrome. Bull Eur Physiopathol Respir 17(3):341–349

    CAS  PubMed  Google Scholar 

  2. Haraldsson PO, Carenfelt C, Knutsson E, Persson HE, Rinder J (1992) Preliminary report: validity of symptom analysis and daytime polysomnography in diagnosis of sleep apnea. Sleep 15(3):261–263

    CAS  PubMed  Google Scholar 

  3. Persson HE, Svanborg E (1996) Sleep deprivation worsens obstructive sleep apnea. Comparison between diurnal and nocturnal polysomnography. Chest 109(3):645–650

    Article  CAS  PubMed  Google Scholar 

  4. Stoohs RA, Dement WC (1993) Snoring and sleep-related breathing abnormality during partial sleep deprivation. N Engl J Med 328(17):1279

    Article  CAS  PubMed  Google Scholar 

  5. Laudencka A, Klawe JJ, Tafil-Klawe M, Zlomanczuk P (2007) Does night-shift work induce apnea events in obstructive sleep apnea patients? J Physiol Pharmacol 58(Suppl 5 (Pt 1)):345–347

    PubMed  Google Scholar 

  6. Pan A, Schernhammer ES, Sun Q, Hu FB (2011) Rotating night shift work and risk of type 2 diabetes: two prospective cohort studies in women. PLoS Med 8(12):e1001141

    Article  PubMed Central  PubMed  Google Scholar 

  7. Pimenta AM, Kac G, Souza RR, Ferreira LM, Silqueira SM (2012) Night-shift work and cardiovascular risk among employees of a public university. Rev Assoc Med Bras 58(2):168–177, Article in English, Portuguese

    Article  PubMed  Google Scholar 

  8. van Geijlswijk IM, Korzilius HP, Smits MG (2010) The use of exogenous melatonin in delayed sleep phase disorder: a meta-analysis. Sleep 33(12):1605–1614

    PubMed Central  PubMed  Google Scholar 

  9. Ferracioli-Oda E, Qawasmi A, Bloch MH (2013) Meta-analysis: melatonin for the treatment of primary sleep disorders. PLoS ONE 8(5):e63773

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  10. Saito Y, Shimizu T, Takahashi Y, Mishima K, Takahashi K, Ogawa Y, Kogawa S, Hishikawa Y (1996) Effect of bright light exposure on muscle sympathetic nerve activity in human. Neurosci Lett 219(2):135–137

    Article  CAS  PubMed  Google Scholar 

  11. Martin JL, Hakim AD (2011) Wrist actigraphy. Chest 139(6):1514–1527

    Article  PubMed Central  PubMed  Google Scholar 

  12. Morgenthaler T, Alessi C, Friedman L, Owens J, Kapur V, Boehlecke B, Brown T, Chesson A Jr, Coleman J, Lee-Chiong T, Pancer J, Swick TJ (2007) Practice parameters for the use of actigraphy in the assessment of sleep and sleep disorders: an update for 2007. Sleep 30(4):519–529

    PubMed  Google Scholar 

  13. Shannon CE (1997) The mathematical theory of communication. 1963. MD Comput 14(4):306–317

    CAS  PubMed  Google Scholar 

  14. Fraser AM, Swinney HL (1986) Independent coordinates for strange attractors from mutual information. Phys Rev A 33(2):1134–1140

    Article  PubMed  Google Scholar 

  15. Dhingra RR, Jacono FJ, Fishman M, Loparo KA, Rybak IA, Dick TE (2011) Vagal-dependent nonlinear variability in the respiratory pattern of anesthetized, spontaneously breathing rats. J Appl Physiol 111(1):272–284

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  16. Koo BB, Strohl KP, Gillombardo CB, Jacono FJ (2010) Ventilatory patterning in a mouse model of stroke. Respir Physiol Neurobiol 172(3):129–135

    Article  PubMed Central  PubMed  Google Scholar 

  17. Yamauchi M, Jacono FJ, Fujita Y, Yoshikawa M, Ohnishi Y, Nakano H, Campanaro CK, Loparo KA, Strohl KP, Kimura H (2013) Breathing irregularity during wakefulness associates with CPAP acceptance in sleep apnea. Sleep Breath 17(2):845–852

    Article  PubMed  Google Scholar 

  18. Jacono FJ, De Georgia MA, Wilson CG, Dick TE, Loparo KA (2010) Data acquisition and complex systems analysis in critical care: developing the intensive care unit of the future. J Healthc Eng 1(3):337–355

    Article  Google Scholar 

  19. Collop NA, Anderson WM, Boehlecke B, Claman D, Goldberg R, Gottlieb DJ, Hudgel D, Sateia M, Schwab R (2007) Clinical guidelines for the use of unattended portable monitors in the diagnosis of obstructive sleep apnea in adult patients. Portable Monitoring Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med 3(7):737–747

    PubMed  Google Scholar 

  20. Ayappa I, Rapoport DM (2003) The upper airway in sleep: physiology of the pharynx. Sleep Med Rev 7(1):9–33

    Article  PubMed  Google Scholar 

  21. Patil SP, Schneider H, Marx JJ, Gladmon E, Schwartz AR, Smith PL (2007) Neuromechanical control of upper airway patency during sleep. J Appl Physiol 102(2):547–556

    Article  PubMed  Google Scholar 

  22. Younes M (2003) Contributions of upper airway mechanics and control mechanisms to severity of obstructive apnea. Am J Respir Crit Care Med 168(6):645–658

    Article  PubMed  Google Scholar 

  23. Kripke DF, Garfinkel L, Wingard DL, Klauber MR, Marler MR (2002) Mortality associated with sleep duration and insomnia. Arch Gen Psychiatry 59(2):131–136

    Article  PubMed  Google Scholar 

  24. Patel SR, Ayas NT, Malhotra MR, White DP, Schernhammer ES, Speizer FE, Stampfer MJ, Hu FB (2004) A prospective study of sleep duration and mortality risk in women. Sleep 27(3):440–444

    PubMed  Google Scholar 

  25. Altman NG, Izci-Balserak B, Schopfer E, Jackson N, Rattanaumpawan P, Gehrman PR, Patel NP, Grandner MA (2012) Sleep duration versus sleep insufficiency as predictors of cardiometabolic health outcomes. Sleep Med 13(10):1261–1270

    Article  PubMed Central  PubMed  Google Scholar 

  26. Gangwisch JE, Heymsfield SB, Boden-Albala B, Buijs RM, Kreier F, Pickering TG, Rundle AG, Zammit GK, Malaspina D (2006) Short sleep duration as a risk factor for hypertension: analyses of the first National Health and Nutrition Examination Survey. Hypertension 47(5):833–839

    Article  CAS  PubMed  Google Scholar 

  27. Hasler G, Buysse DJ, Klaghofer R, Gamma A, Ajdacic V, Eich D, Rossler W, Angst J (2004) The association between short sleep duration and obesity in young adults: a 13-year prospective study. Sleep 27(4):661–666

    PubMed  Google Scholar 

  28. Javaheri S, Storfer-Isser A, Rosen CL, Redline S (2008) Sleep quality and elevated blood pressure in adolescents. Circulation 118(10):1034–1040

    Article  PubMed Central  PubMed  Google Scholar 

  29. Spiegel K, Leproult R, Van Cauter E (1999) Impact of sleep debt on metabolic and endocrine function. Lancet 354(9188):1435–1439

    Article  CAS  PubMed  Google Scholar 

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This study is partly supported by a grant to the Comprehensive Research on Life-Style Related Diseases including Cardiovascular Diseases and Diabetes Mellitus Group from the Ministry of Health, Labor and Welfare of Japan. US investigators were supported in part by the NIH-NHLBI [R33HL087340-01] and Award Number I01BX000873 from the Biomedical Laboratory Research and Development Service of the VA Office of Research and Development.

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None of the authors have financial conflicts of interest to declare as it relates to the contents of this manuscript.

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Correspondence to Motoo Yamauchi.



Mutual information

Mutual Information (MI) is a measure of the statistical dependence between two time series, or two collections of points from a data set, that can arise from both linear and nonlinear sources [Shannon, C.E. and Weaver, W. (1949). The mathematical theory of communication. University of Illinois Press, Urbana, Illinois.]. The Mutual Information between a given time series x(t) and its time-shifted version x(t + τ) is computed from the joint probability distribution of x(t) and x(t + τ) where τ represents a time lag. The joint probability distribution is defined as P[x(t), x(t + τ)] where P[x(t)] and P[x(t + τ)] are the marginal distributions of the original and time-shifted time series, respectively. The mutual information (MI) can be computed as follows:

$$ MI\left[x(t),x\left(t+\tau \right)\right]={\displaystyle \sum_i{\displaystyle \sum_jP\left[{x}_i(t),{x}_j\left(t+\tau \right)\right] \log}\left[\frac{P\left[{x}_i(t),{x}_j\left(t+\tau \right)\right]}{P\left[{x}_i(t)\right]\cdot P\left[{x}_j\left(t+\tau \right)\right]}\right]} $$

Because the breathing pattern over long time periods is strongly periodic, we computed MI for τ values from one sample (adjacent points separated by 100 ms) to 1 cycle length. MI tends to decrease quickly as τ is increased from a lag of one and then becomes more uniform at higher time lags, and the average MI of a given epoch was quantified excluding small lags as defined by the first minimum of the MI function.

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Yamauchi, M., Jacono, F.J., Fujita, Y. et al. Effects of environment light during sleep on autonomic functions of heart rate and breathing. Sleep Breath 18, 829–835 (2014).

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