Effects of Insufficient Sleep on Blood Pressure Monitored by a New Multibiomedical Recorder
Abstract Blood pressure varies in relation to factors such as physical activity, body position, ambient temperature, and autonomic nervous system activity. Therefore, we have developed a portable multibiomedical (PMB) recorder that monitors five parameters: indirect blood pressure, physical activity, body position, ambient temperature, and RR interval of the electrocardiogram. In the present study, we applied the PMB recorder over a 24-hour period to study the effect of insufficient sleep on blood pressure in subjects doing extensive overtime work. The parameters listed above were measured by the PMB recorder throughout a normal workday (mean period of sleep, 8 hours) and throughout a day with insufficient sleep (mean period of sleep, 3.6 hours) in 18 male technical workers aged 23 to 48 years old. Blood pressure (mean systolic/diastolic pressure±SD) significantly increased the day after a sleep-insufficient night (129±8/79±6 mm Hg) compared with the day after a normal night (123±8/76±7 mm Hg, P<.05). However, ambient temperature, mean number of steps per minute, and percentage of time spent in a standing position showed no significant difference between these days. Spectral analysis of RR intervals showed that the ratio of the low-frequency component on the RR power spectrum (0.05 to 0.15 Hz) to the high-frequency component (0.15 to 0.40 Hz) was higher on the sleep-insufficient day (2.17±0.37 versus 1.81±0.37), as was the urinary excretion of norepinephrine (P<.05). Heart rate was significantly higher on the sleep-insufficient day (81±11 versus 76±8 beats per minute), after the data of two subjects with abnormal levels of physical activity were excluded (P<.01). These data suggest that lack of sleep may increase sympathetic nervous system activity on the following day, leading to increased blood pressure. The PMB recorder was useful for precisely evaluating the relationship between blood pressure and environmental factors.
- blood pressure monitoring, ambulatory
- circadian rhythm
- sympathetic nervous activity
- blood pressure determination
Because of increasing recognition of the great variability of BP, demand has risen for ambulatory BP monitoring, and various types of equipment have been developed for this purpose. Our team has previously reported the development of both direct and indirect ambulatory BP recorders and the results of clinical investigations using these instruments.1 2 3 4
BP varies according to ambient temperature, body position, physical activity, autonomic nervous system activity, and other factors.4 5 6 7 Simultaneous recording of these factors along with BP over 24 hours offers potential benefit for analysis of the mechanisms of BP variation. We therefore developed a PMB recorder in cooperation with the A&D Co. This BP recorder incorporates sensors for simultaneous evaluation of four influential factors: ambient temperature, body position (sitting or standing), acceleration or number of steps as an index of physical activity, and RRI of the ECG. Recently, spectral analysis of HR has been performed for evaluation of autonomic nervous system activity.8 9 10 Using the PMB recorder, we investigated the effect of sleep deprivation due to overtime work on BP and on components of the power spectrum of HR variability. Although karoshi (sudden death caused by overwork) is a serious socioeconomic problem in Japan, few reported studies have investigated the effects of insufficient sleep due to overtime work on BP, which is the most important cardiovascular risk factor.
Ambient temperature was recorded at 1-minute intervals by a small integrated circuit (IC) thermosensor (LM34CAZ, National Semiconductor Co), with a measurement range of −15° to 60°C and precision of ±0.2°C. The thermosensor was attached to the end of a cord 60 cm in length and could be freely positioned. For measurements of external temperature, the thermosensor is allowed to project outside the clothing. For measurement of body temperature, the thermosensor can be attached to the skin or used rectally. In the present study, external temperatures were measured by a sensor outside the clothing.
A body-position sensor was attached to the thigh for evaluation of whether the subject was sitting or standing. A glass tube (3.5×10 mm) containing a small bolus of mercury and a switch at one end was bound to the right thigh at an angle of 45° to the horizontal position (Fig 1⇓) for monitoring of whether the thigh was perpendicular or parallel to gravity forces. The sensor was placed such that if the thigh was parallel to the force of gravity, the mercury moved to the lower part of the tube and triggered the switch mechanism, and if the thigh was at an angle horizontal (perpendicular) or higher, the mercury shifted to the opposite side of the tube and the switch turned off. If the thigh was parallel to the force of gravity, the position was evaluated as standing; if the thigh was at an angle horizontal or higher, the position was evaluated as sitting or recumbent. Since the sensor could not distinguish between sitting and recumbent positions, recumbent position was recorded by the subjects.
A ceramic acceleration-pickup sensor (3.5×13.5 mm) was incorporated into the BP recorder. Cumulative values for 1-minute periods were recorded at 18-millisecond intervals at frequencies ranging from 1 to 10 Hz in the vertical direction (Z axis), with a sensitivity of 4.1×10−3 m/s2·bit. The number of steps was also recorded over 1-minute periods with a pedometer (ET-450, Yamasa Tokei Ltd).
ECG and RRI Analysis
ECG tracings were obtained with a precordial lead (V5), and variation of RRIs and ST level trendgrams were analyzed.
From 2-millisecond sampling intervals of an ECG tracing, an estimation of R waves was made with 73% of the points in the QRS complex peaks in the frequency band ranging from 0.3 to 32 Hz. A total of 512 RRIs were recorded at 30-minute intervals at a resolution of 7.8 milliseconds. Thus, with autoregressive modeling,11 spectral analysis of HR variability was performed 48 times over the 24-hour period. RRI data were resampled by a personal computer every 500 milliseconds with Lagrange’s equation. Optimal lag was determined by Akaike’s test.11 12 The average output of the point prediction error filter and its coefficient were obtained with Burg’s analytic method13 of the Yule-Walker equation. The ranges of 0.05 to 0.15 Hz and 0.15 to 0.4 Hz were taken as the LF and HF component ranges, respectively, giving the component ratio LF/HF. For ventricular premature contraction readings, prematurity of ventricular contraction was assumed to fulfill the following conditions: that the RRI (RRt) was less than 80% of the moving average (ARt) of the preceding RRIs of eight beats, and that (RRt+RRt+1−2·ARt) was within ±40 milliseconds. For HR variability, RR50 was defined as the change in RRI (RRt) exceeding ±50 milliseconds compared with the preceding RRI (RRt–1). The frequency of RR50 per minute was used as an index of parasympathetic activity, as has been suggested previously.14
The ST level was determined as the mean value over 1 minute following measurement of depth from the baseline 80 milliseconds after the R wave on the ECG tracing. ECG waveforms were recorded for 30 s/h, and throwing a switch enabled ECG waveforms to be recorded for 2 minutes.
BP, which could be recorded at intervals of 1, 3, 5, 10, 15, 20, 30, 60, or 120 minutes, was monitored for 24 hours. The modified version of the TM-2420 uses the Korotkoff sound (microphone) method and the oscillometric method. The microphone was taped to the left upper arm.
The accuracy of BP measurements recorded by the TM-2420 according to the criteria of the Association for the Advancement of Medical Instrumentation (AAMI)15 and British Hypertension Society (BHS)16 has previously been reported.17 18 The modified TM-2420 monitor also satisfies the accuracy levels recommended by AAMI and BHS.
Before the study was started, the accuracy of BP values measured by the PMB recorder was checked against simultaneous measurements with a mercury sphygmomanometer. Differences of less than 5 mm Hg were considered acceptable.
The recorded data of the five factors described above were input into a personal computer (PC9801, NEC) via an RS232C terminal and then analyzed. Fig 1⇑ shows the sensor assembly and the situation of the position sensor on the thigh. Fig 2⇓ shows examples of the actual records.
Application of the PMB Recorder
To test the application of the PMB recorder, we investigated the effect of sleep insufficiency on BP and autonomic nervous system activity. The subjects (volunteers) were male technical workers ranging from 23 to 48 years of age employed in the development of industrial products. From a group of volunteers, we selected 18 subjects (mean age, 34±14 years [±SD]) who frequently worked overtime. As far as possible, no alterations were made in their daily work, which involved research, design, and development of electronics. The subjects either could select days when their schedule allowed only 3 to 4 hours of sleep or they could deliberately work overtime, limiting themselves to no more than 4 hours of sleep. They worked as usual on the day after the night of insufficient sleep. Each subject slept at home. Aside from requesting that the subjects give precedence to work over BP measurements and that they not alter the nature of their work on the day after the insufficient-sleep night, we imposed no special restrictions on the subjects. All subjects submitted records of their activities. Physical examination of all subjects indicated that they were healthy, with no abnormal findings.
In nine subjects, the PMB device recorded measurements over a 24-hour period on a normal workday (office hours, 8:30 am to 5:30 pm), allowing a normal duration of sleep. The same measurements were then recorded by the PMB recorder on a workday when the same subjects worked overtime and could not sleep for more than 4 hours the previous night. In the other nine subjects, the measurements were recorded on a sleep-insufficient day first, followed by a routine workday after 1 week.
This study was approved by the Ethics Committee of the Department of Internal Medicine, Yokohama City University, and all subjects gave written informed consent. Following a standard protocol, recording began at 9 pm, and BP was measured every 30 minutes throughout 24 hours. Subjects awoke at approximately 6:30 am and remained awake until at least 10 pm. For analysis of BP values obtained during Korotkoff method monitoring, different time periods were defined as follows: 24-hour period, from 9 pm until 9 pm the next day; sleep period, from the time when subjects went to bed until awakening; waking hours, from awakening until 9 pm. Quality of sleep was assessed by the subjects themselves and by assessment of body position. Irregular BP readings were rejected automatically or after review under the following conditions: systolic BP greater than 270 or less than 70 mm Hg; diastolic BP greater than 160 or less than 40 mm Hg; pulse pressure less than 20 mm Hg; or any reading greater than double the preceding or subsequent reading without a simultaneous increase in HR. Statistical processing was performed after the elimination of these errors (mean error, 4±4% for 48 measurements) from the 24-hour period.
Physical activity was recorded by counting the number of steps taken by the subject per minute. For analysis of urinary excretion of norepinephrine, urine samples were collected by proportional urinary sampling devices19 that contained 6 mol/L HCl during sleeping and waking hours and were analyzed by high-performance liquid chromatography.20 The intra-assay and interassay variations of this method were 4% and 9%, respectively. Urinary excretion of creatinine and sodium was also measured in the laboratory with an autoanalyzer.
Standard statistical methods were used, including paired two-sample t test and ANOVA. Unless otherwise stated, values are expressed as mean±SD. Values of P<.05 were considered significant. The Multiple Statistical Analysis Program of the Social Survey Research Information Co, Ltd, was used for calculations.
The mean sleeping time was approximately 8 hours on normal (routine) workdays and 3.6 hours on overtime workdays (Table 2⇓). Fig 2⇑ shows BP and LF/HF ratio recorded by the PMB recorder over 24 hours on a routine workday. No significant differences between normal workdays and sleep-insufficient days were observed with regard to the number of steps per minute and percentage of time spent in a standing position (Table 2⇓), suggesting that work performance (in terms of physical activity per hour) showed little change. Similarly, ambient temperature, ST level, and RR50 showed no significant differences. Twenty-four-hour urinary excretion of sodium also showed no significant difference between sleep-insufficient days and normal workdays. However, systolic BP showed a significant mean increase of 6 mm Hg on days after sleep-insufficient nights compared with normal days after sufficient sleep (P<.01). Diastolic BP also rose by approximately 3 mm Hg (Fig 3⇓ and Table 2⇓), and urinary excretion of norepinephrine corrected for creatinine showed a significant increase on days after sleep-insufficient nights (Table 3⇓).
Although no significant difference was observed in mean HR between normal workdays and sleep-insufficient days (Table 2⇑), changes in HR and BP were parallel in all subjects except one (Fig 4⇓). Spectral analysis of RRIs showed that the LF/HF ratio increased significantly the day after a sleep-insufficient night (Fig 5⇓ and Table 3⇑).
BP levels and variation during waking hours vary in relation to activity, body position (standing, sitting, or lying down),4 6 seasonal variations, and ambient temperature.6 7 Therefore, for investigation of the mechanisms of the daily variation of BP, simultaneous measurement of these factors is necessary. Attempts have previously been made to quantify daily activity using an accelerometer with a ceramic acceleration-pickup sensor (Activetracer, GMS, Co),21 but this equipment cannot measure BP.
External temperature was measured because it can influence BP, HR alterations, and autonomic nervous system activity. The absence of considerable changes in external temperature suggests that external temperature did not directly influence BP or HR in the present study.
Recently, RR variation analysis has been used as an index for evaluation of autonomic nervous system activity.8 9 10 Originally, three BP and HR rhythmic oscillations were identified. Oscillations with a frequency of approximately 0.2 to 0.4 Hz, similar to that of normal respiratory activity, are defined as HF. Oscillations with a frequency of approximately 0.1 Hz are defined as mid-frequency and correspond to Mayer waves.22 23 Oscillations with a frequency between 0.02 and 0.07 Hz are defined as LF.8 Subsequent studies have elucidated that the amplitude and frequency of these oscillations are not constant but vary in relation to different behavioral conditions and breathing patterns.8 24 25 Oscillations between 0.02 and 0.07 Hz are usually disregarded, and the other two major components in the spectrum, with frequencies of approximately 0.1 and 0.3 Hz, are defined as LF and HF, respectively.26 27 According to previous studies, the HF components (>0.15 Hz) are considered to correlate with cardiac vagal activity.28 29 Therefore, in the present study, we defined HF as 0.15 to 0.40 Hz and LF as 0.05 to 0.15 Hz. However, the specificity of LF components relating to a single control mechanism is doubtful, because LF components between 0.03 and 0.15 Hz are suppressed by parasympathetic or sympathetic pharmacological blockade,30 31 and HR fluctuations in this region are associated with a wide variety of stimuli, such as thermoregulation, the respiratory cycle, and hemodynamic instability.32 33 Thus, LF components in HR spectra are not invariably specific sympathetic markers, as has been suggested previously.26 27 Therefore, in the present study, we used the LF/HF ratio as an index of sympathovagal balance.27 34
Ideally, since respiratory rate and breathing depth influence LF and HF power, respiration should be monitored as well. For this reason, the next modification of the PMB will be designed accordingly. The lack of respiratory data in the present study limits the interpretation of LF and HF power. Nonetheless, during the day after a night of insufficient sleep, when BP rose significantly above its normal workday levels, the LF/HF ratio also rose significantly. It is possible that the sympathovagal balance was different during this period.
The new PMB recorder simultaneously records five different factors: BP, ECG and RRI (LF/HF), physical activity (acceleration and/or number of steps), body position, and temperature. To test the application of this device, we examined the influence of insufficient sleep on BP. We observed that BP on a workday after a night with insufficient sleep was significantly higher than on normal days, although changes in body position and number of steps per minute remained approximately the same. No significant difference between normal workdays and sleep-insufficient days was observed in 24-hour urinary sodium excretion. Sympathovagal balance, as reflected by the LF/HF ratio, was more variable on days after insufficient sleep; changes in HR and BP were parallel except in one subject (Fig 4⇑); and urinary excretion of norepinephrine was greater on days after a night with insufficient sleep. Thus, it seems possible that increased sympathetic activity develops the day after a night with insufficient sleep, leading to increased BP. Insufficient sleep due to overtime work appears to be harmful to health, and especially to the cardiovascular system. However, the mechanism by which lack of sleep enhances sympathetic nervous system activity remains unclear. The increases in BP and LF/HF ratio after insufficient sleep were greater in the evening than the morning (Figs 3⇑ and 5⇑), suggesting that fatigue and mental stress due to lack of sleep may influence sympathovagal balance.
During both sleeping and waking hours, mean HR was approximately the same on sleep-insufficient and normal days (Table 2⇑). We further observed the HR and BP changes in each subject in order to explain the absence of a faster mean HR on days after insufficient sleep (Fig 4⇑). Three subjects (Nos. 3, 12, and 16 in Fig 4⇑) showed slower mean HR values during waking hours on sleep-insufficient days than on normal workdays. Clark et al35 demonstrated that the circadian rhythm of BP depends on physical activity. When subjects rest during the daytime instead of being ambulant, the circadian variation in BP and HR is significantly decreased.36 37 We speculate that the frequency of maintaining a standing position and the level of physical activity (number of steps per minute) might affect HR and BP. Therefore, we excluded two subjects (Nos. 3 and 16) because their levels of physical activity and frequency of maintaining a standing position (Fig 6⇓) were so different that they could not be considered part of the same subject population (Fig 7⇓). We compared the mean HR during waking hours in the other 16 subjects. A significant difference was observed between mean HR during waking hours on sleep-insufficient days and normal workdays (81.2±11.3 versus 76.4±8.3 beats per minute, P<.001) in these subjects. Whereas conventional devices measure only ambulatory BP and HR, the new PMB device can also measure body position and other factors, allowing more accurate speculation about the causes of BP and HR changes, such as those shown in Figs 6⇓ and 7⇓. Therefore, the PMB recorder has potential usefulness in clinical hypertension research.
Selected Abbreviations and Acronyms
The authors wish to thank Shigehiro Ishizuka, Tetsurou Nagashima, and Kenichirou Yasaka, Research and Development Section, A&D Co, Ltd, for creating and providing the PMB recorder (TM-2425 prototype). The PMB recorder is commercially available as the TM-2425 (using an acceleration-pickup sensor instead of a pedometer).
Reprint requests to Osamu Tochikubo, MD, The Second Department of Internal Medicine, Urafune Hospital of Yokohama City University, 3-46 Urafune-cho, Minami-ku, Yokohama 232, Japan.
- Received September 12, 1995.
- Revision received October 10, 1995.
- Accepted February 16, 1996.
Tochikubo O, Kaneko Y, Yokoi H, Yukinari Y. A new portable device for recording 24-h indirect blood pressure in hypertensive outpatients. J Hypertens. 1985;3:355-357.
Mann S, Altman DG, Raftery EB, Bannister R. Circadian variation of blood pressure in autonomic failure. Circulation. 1983;68:477-483.
Pickering TG. Effects of physical and mental activity on blood pressure variability. In: Ambulatory Monitoring and Blood Pressure Variability, Part 1. London, UK: Science Press Ltd; 1990:4.6-4.8.
Claconi S, Palombo C, Genovesi-Ebert A, Marabotti C, Voltervani D, Ghione S. Long-term reproducibility and evaluation of seasonal influences on blood pressure monitoring. J Hypertens. 1988;6(suppl 4):64-66.
Parati G, Saul JP, Di Rienzo M, Mancia G. Spectral analysis of blood pressure and heart rate variability in evaluating cardiovascular regulation. Hypertension. 1995;25:1276-1286.
Parati G, Castiglioni P, Di Rienzo M, Omboni S, Pedotti A, Mancia G. Sequential spectral analysis of 24-hour blood pressure and pulse interval in humans. Hypertension. 1990;16:414-421.
Malliani A, Pagani M, Lombardi F, Furlan R, Guzzetti S, Cerutti S. Spectral analysis to assess increased sympathetic tone in arterial hypertension. Hypertension. 1991;17(suppl III):III-36-III-42.
Akaike H. Power spectrum estimation through autoregressive model fitting. Ann Inst Stat Math. 1969;21:407-419.
Andersen M. On the calculation of filter coefficients for maximum entropy analysis. Geophysics. 1974;39:69-72.
Ewing DJ, Neilson JMM, Travis P. New method for assessing cardiac parasympathetic activity using 24 hour electrocardiograms. Br Heart J. 1984;52:396-402.
American National Standard. Electronic or Automated Sphygmomanometers. Arlington, Va: Association for the Advancement of Medical Instrumentation; 1993:1-39.
O’Brien E, Petrie J, Littler WA, de Swiet M, Padfield PL, O’Malley K, Jamieson M, Altman D, Bland M, Atkins N. The British Hypertension Society protocol for the evaluation of automated and semi-automated blood pressure measuring devices with special reference to ambulatory systems. J Hypertens. 1990;8:607-619.
Clark S, Fowler S, Coats A, Radaelli A, van der Putt M, Bird R, Conway J. Ambulatory blood pressure monitoring: validation of the accuracy and reliability of the TM-2420 according to the AAMI recommendations. J Hum Hypertens. 1991;5:77-82.
Palantini P, Penzo M, Canali C, Pessina AC. Validation of the A&D TM-2420 model 7 for ambulatory blood pressure monitoring and effect of microphone replacement on its performance. J Ambul Monit. 1991;4:281-288.
Tochikubo O, Uneda S, Kaneko Y. Simple portable device for sampling a whole day’s urine and its application to hypertensive outpatients. Hypertension. 1983;5:270-273.
Yoshimura M, Komori T, Nakanishi T, Takahashi H. Estimation of sulphoconjugated catecholamine concentrations in plasma by high-performance liquid chromatography. Ann Clin Biochem. 1993;30:135-141.
Sato Y, Otsuka K, Yamanaka T, Kubo Y, Nakajima S, Watanabe Y, Adachi M, Yanaga T, Watanabe H. Application of an activity monitor to chronocardiology: morning versus evening and circadian periodicity. Ther Res. 1992;13:764-770.
Mayer S. Studien zur Physiologie des Herzens und der Blutgefasse. V, Uber spontane Blutdruckschwankungen. Sitzungberichte der Kaserlichen Akademie der Wissenschaften Wien. 1876;74:281-307.
Preiss G, Iscoe S, Polosa CV. Analysis of a periodic pattern associated with Mayer waves. Am J Physiol. 1975;228:768-774.
Angelone A, Coulter CA. Respiratory sinus arrhythmia: a frequency dependent phenomenon. J Appl Physiol. 1964;19:H479-H482.
Hirsh JA, Bishop B. Respiratory sinus arrhythmia in humans: how breathing pattern modulates heart rate. J Appl Physiol. 1981;241:620-629.
Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991;84:482-492.
Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R, Pizzinelli P, Sandrone G, Malfatto G, Dell’Orto S, Piccaluga E, Turiel M, Baselli G, Cerutti S, Malliani A. Power of spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circ Res. 1986;59:178-193.
Billman GE, Dujardin JP. Dynamic changes in cardiac vagal tone as measured by time-series analysis. Am J Physiol. 1990;258:H896-H902.
Cerutti C, Gustin MP, Paultre CZ, Lo M, Julien C, Vincent M, Sassard J. Autonomic nervous system and cardiovascular variability in rats: a spectral analysis approach. Am J Physiol. 1991;261:H1292-H1299.
Saul JP, Berger RD, Albrecht P, Stein SP, Chen MH, Cohen RJ. Transfer function analysis of the circulation: unique insights into cardiovascular regulation. Am J Physiol. 1991;261:H1231-H1245.
Saul JP, Berger RD, Chen MH, Cohen RJ. Transfer function analysis of autonomic regulation, II: respiratory sinus arrhythmia. Am J Physiol. 1989;256:H153-H161.
Chess GF, Tam RMK, Calaresu FR. Influence of cardiac neural inputs on rhythmic variations of heart period in the cat. Am J Physiol. 1975;228:775-780.
Rowlands DB, Stallard TJ, Watson RDS, Littler WA. The influence of physical activity on arterial pressure during ambulatory recordings in man. Clin Sci. 1980;58:116-117.
Mann S, Craig MW, Melville DI, Balasubramanian V, Raftery EB. Physical activity and the circadian rhythm of blood pressure. Clin Sci. 1979;57:291s-294s.