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|Year : 2009
: 11 | Issue : 45 | Page
|Blink rate during tests of executive performance after nocturnal traffic noise
Markus Breimhorst1, Anke Marks2, Sibylle Robens2, Barbara Griefahn2
1 University Medical Centre of the Johannes-Gutenberg University, Langenbeckstr. 1, 55101 Mainz, Germany
2 Leibniz Research Centre for Working Environment and Human Factors, TU Dortmund University, Ardeystrasse 67, 44139 Dortmund, Germany
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|Date of Web Publication||2-Oct-2009|
This analysis is on the hypothesis that nocturnal traffic noise affects sleep quality whereas performance decrement is avoided by increased effort expressed by a decrease in blink rates (BRs) during a visual task. Twenty-four persons (12 women, 12 men; 19-28 years, 23.56 ± 2.49 years) slept during three consecutive weeks in the laboratory while exposed to road, rail, or aircraft noise with weekly permuted changes. Each week consisted of a random sequence of a quiet night (32 dBA) and three nights with equivalent noise levels of 39, 44 and 50 dBA respectively. The polysomnogram was recorded during all nights. Every morning the participants rated their sleep quality and then completed two executive tasks (Go/Nogo-, Switch-task). Neither of the two performance tests was affected by nocturnal noise. Sleep efficiency and subjective sleep quality decreased with increasing noise levels but were not associated with the type of noise. In contrast, BRs were associated with the type of noise, not with noise levels. The results do not support the hypothesis concerning the BR. The possible reasons are discussed. However, the results do not exclude that other physiological parameters such as heart rate or brain potentials measured during the tests might have revealed alterations associated with nocturnal noise exposure.
Keywords: Blink rate, executive tests, sleep efficiency, subjective sleep quality, traffic noise
|How to cite this article:|
Breimhorst M, Marks A, Robens S, Griefahn B. Blink rate during tests of executive performance after nocturnal traffic noise. Noise Health 2009;11:217-22
| Introduction|| |
Due to already high traffic density any further increase of traffic volume must, to keep a reasonable traffic flow, result in a temporal redistribution with relatively larger increase in shoulder hours and night than during the day. Nocturnal traffic noise has been shown to impair physiological and subjectively evaluated sleep quality. ,,, Effects on performance the next day were, however, found in only a few studies.  A major reason for performance not being affected as concluded by most studies , is most likely the ability to compensate for possible impairment by more effort. , Elevated effort increases mental work load,  i.e. the overall demand of information processing resources  and might be indicated by (a) quantity and quality of performance, (b) physiological alterations of heart rate or of evoked potentials etc. and (c) subjective rating of the effort. ,
The blink rate (BR) that decreases with increasing mental work load ,, is regarded a suitable physiological indicator of elevated cognitive demands , during the processing of visual tasks. The investigation of BR during performance tests after nights with traffic noise is based on an experiment by Griefahn et al.  The authors performed polysomnographic sleep recordings with 24 healthy young persons who slept for one week each under the influence of aircraft, road and rail traffic noise in a permuted order with three equivalent sound pressure levels. Sleep quality was rated each morning and the participants then performed in an alternating order a Go/Nogo- and a Switch-task while event-related potentials (ERPs) and BRs were recorded. In a very first approach Schapkin et al. analyzed the performance, ERPs and BRs recorded in that study, but only during the Go/Nogo-task and only after nights with railway noise. They found no alteration in performance. However, the amplitudes of the ERPs reduced and BR decreased in a dose-dependent manner; the higher the equivalent sound pressure level during the night the more the decrease. Thus, the authors concluded that cognitive performance was maintained due to increased concentration and increased physiological costs. 
Further to this rough but encouraging explorative analysis the present paper concerns the analysis of the whole study. It considers the BR not only during the Go/Nogo- but also during the Switch-task, not only after nights with exposure to railway noise but also after nights with aircraft and with road traffic noise. Moreover, where Schapkin et al.  referred to subjectively evaluated sleep quality, this analysis also used the sleep efficiency index as an objective indicator of sleep quality.
| Methods|| |
As the experimental design and procedure were described in detail by Griefahn et al.  and Marks et al.  the following description concentrates on the essentials for this analysis.
Twenty-four healthy students (12 women, 12 men; 19-28 years, 23.56 ± 2.49 years) participated and gave written informed consent to the study approved by the local ethics committee. The participants had no experience in laboratory sleep studies and stated their habitual bedtime between 22 and 24 o'clock and sleep durations between six to 10 hours. Nine to 11 days prior to the experiment they were familiarized with the procedure and completed a training session on the Go/Nogo- and the Switch-task without measuring the electrooculogram (EOG). At the end of the study they were paid for participation.
Experimental design and procedure
After a habituation night from Sunday evening to Monday morning the participants slept during three consecutive weeks, for four consecutive nights each (Monday evening to Friday morning) in the laboratory (single sound proof bedroom) where they were exposed with weekly permuted changes to aircraft, road, or rail traffic noise. The four nights of each week consisted of a permuted sequence of a quiet night (L Aeq = 32 dB) and three noisy nights with L Aeq, 8h = 39, 44 and 50 dB, respectively.
After the participants arrived at the laboratory at 2100 hours, the electrodes for registration of the polysomnogram (electroencephalogram: EEG, electrooculogram: EOG, electromyogram: EMG) were fixed according to the recommendations of Rechtschaffen and Kales.  Then the participants went to bed. At 2300 hours, lights were put off, registration of the polysomnogram and noise presentation was started. At 0700 hours the participants were woken up and completed the Go/Nogo- and the Switch-task 15 - 20 minutes later. The order was alternated every other day. During both tasks BRs were measured.
Nocturnal noise load
A red noise with L Aeq equal to 32 dB was applied as a background noise during all nights, even during the 'quiet' nights. The traffic noises were superimposed as shown in [Table 1]. To simulate a realistic scenario the number of noise events and thereby the hourly equivalent noise levels were gradually reduced from 2300 to 0100 hours and again elevated between 0400 and 0700 hours.
Using personal computers a Switch- and a Go/Nogo-task were performed each morning. Both these tests refer to executive functions  that originate in the prefrontal cortex and are vulnerable to sleep deprivation. , The order of the two tasks was balanced across the subjects.
The Go/Nogo-task focuses on the ability to inhibit intended actions. The stimuli for this task were the German words 'drόck' ('press') or 'stopp' ('stop') written in lower or in uppercase. The inter-stimulus-interval was 1750 milliseconds. Participants were advised to respond only to 'drόck' and 'STOPP' but not to 'DRάCK' and 'stopp'. Each of these four stimuli was presented 50 times in a random order.
The Switch-task focuses on the ability to switch between two tasks.  A two-digit number occurred for 170 milliseconds in one of four corners of a virtual square that surrounds the focal point, i.e. a small circle in the centre of the screen. The participants were instructed to indicate the position of the even digit if the number occurred above the virtual horizontal middle line and the position of the greater digit if the number occurred below that line while using two correspondingly arranged keys. In this task 240 stimuli were presented clockwise, so that the participants could prepare for the next task.
During the tasks an EOG was recorded with one electrode fixed one centimeter above the lateral orbital rim of the left eye and one electrode one centimeter below the lateral orbital rim of the right eye. The reference was A1 (left mastoid). The Software Brain Vision 1.04 (Brain Products, Germany) was used to analyse the EOG. An experienced evaluator detected the BRs by visually checking the EOG. The evaluation of the EOG was blinded with respect to the noise conditions. Sections with not clearly assignable blinks or with concurrent vertical/horizontal eye movements were discarded from the analysis.
| Evaluation and Statistics|| |
The dependent variables considered in this analysis were:
Sleep efficiency: It is an objective measure of sleep quality, expressed by the Sleep Efficiency Index (SEI). That is, for laboratory studies with fixed times in bed, the quotient of total sleep time (TST) divided by the sleep period time (SPT; SEI = TST/SPT, where SPT denotes the time elapsed between initial sleep onset and final sleep offset and TST, i.e. the difference of SPT - intermittent wakefulness).
Subjective Sleep Quality (SSQ): Using six 10-point scales the participants estimated the difficulty to fall asleep (very easy - very difficult), calmness of sleep (very calm - very restless), sleep depth (very sound - very shallow), sleep duration (very long - very short), restoration (very high - very low), body movements (very little - very much). According to a factor analysis, all these scales loaded on a single factor. They were summed up and subtracted from the maximum achievable number (60) and the result was labeled as Subjective Sleep Quality (SSQ).
Performance: Parameters for the Go/Nogo-task were the reaction time in ms for Go-trials (RT-Go) and false alarms for Nogo-trials (FA Nogo). To achieve normal distribution Miss-Go and FA-Nogo were square-root transformed. Concerning the Switch-task the reaction times (ms) and the number of errors were determined separately for Switch and Non-Switch trials.
Blink Rate (BR): The BR is defined by the number of blinks per minute.
The data on two participants who obviously did not adhere to the instructions for the completion of the performance tests was discarded from further analyses.
Normality was checked for all data by the ratio of kurtosis and the corresponding standard error as well as the ratio of skewness and its standard error. 
For statistical analyses 3Χ4 ANOVAs with repeated measurement on the factors 'Type' (aircraft, road, and rail traffic noise) and 'Level' (L Aeq = 32, 39, 44, 50 dB) of noise were calculated separately for SSQ, performance, and BR. The analysis was performed with the SAS proc mixed procedure. Post-hoc comparisons were conducted with Bonferroni-correction. Significance was stated for p < or equal to 0.05.
All statistical procedures were performed using SAS (version 9.1).
| Results|| |
As shown in [Table 2], none of the parameters derived from the Switch-task or from the Go/Nogo-task revealed a significant association with nocturnal noise exposure, neither concerning the type nor the level of noise and there was no interaction.
BRs measured during the Switch-task did not deviate statistically from the rates measured during the Go/Nogo-task and this was true for all types and all levels of noise exposure in the preceding night. As performance was also not affected by any of the various noise conditions, BRs were averaged across both tasks to a single value. Concerning gender, the mean BRs after the quiet nights did not differ between women and men (p = 0.67) and therefore gender was not included in following analyses.
| Effects of Noise on Sleep Efficiency, Sleep Quality and BR|| |
Global noise effects
When comparing 'quiet' with noisy nights, irrespective of the type and the level of noise, there was a significant decrease of the SEI (F SEI, 1/21 = 10.36, p < 0.01) in noisy nights and the SSQ was then rated worse (F SSQ, 1/21 = 42.15, p < 0.01). The BR was, however, not affected after nocturnal noise exposure (F BR, 1/21 = 2.62, p = 0.12).
The effects of the noise parameters 'type' and 'level' was then calculated with 3Χ4 ANOVAs with repeated measurement on the factors 'Type' (aircraft, road, rail traffic noise) and 'Level' (L Aeq = 32, 39, 44, 50 dB). Post-hoc tests were conducted with Bonferroni-corrections.
Effects of types of noise
[Figure 1] shows mean BRs separately for the three types of traffic noise. The ANOVA revealed a significant effect (F 2/42 = 8.33, p < 0.01). The BR after aircraft noise exposure was significantly higher than after nights with road or rail traffic noise (p air/road < 0.01, p air/rail < 0.01) where the difference after nights with road and rail noise exposure was not significant (p road/rail = 0.62). In contrast to the BR the type of noise had no significant influence on sleep efficiency (F 2/42 = 2.52, p = 0.09) or on SSQ (F 2/42 = 1.25, p = 0.30).
Effects of noise levels
[Figure 2] shows mean BRs separately for the four noise levels. Though BRs seem to decrease gradually with increasing noise levels the ANOVA did not reveal significant differences (F 3/63 = 1.39, p = 0.25).
Sleep efficiency was, however, significantly associated with the noise level (F 3/63 = 4.28, p = 0.02). The SEI was significantly higher in 'quiet' than in noisy nights with equivalent noise levels of 39, 44, and 50 dBA (p quiet/39dBA = 0.02, p quiet/44dBA = 0.06, p quiet/50dBA < 0.01), but there were no significant differences between noise levels of 39 dBA and higher.
Concerning SSQ, ANOVA revealed a significant association with noise levels (F 3/63 = 24.19, p < 0.01) where post-hoc tests revealed significant differences (p < 0.01) between the single levels, except for the difference between 39 and 44 dBA.
There were no significant interactions between the 'Type' and the 'Level' of noise, neither for the BR (F 6/126 = 1.23, p = 0.30) nor for SSQ (F 6/126 = 0.35, p = 0.91) or for sleep efficiency (F 6/126 = 0.59, p = 0.74).
Eventually, BRs were correlated with the SEI and with the SSQ for all conditions combined. The respective correlations were r = -0.07, p = 0.29 for the SEI and r = -0.08, p = 0.21 for SSQ. Both the indicators of sleep quality correlated significantly with each other, though the coefficient was again relatively small (r = 0.23, p < 0.01). The corresponding correlations separately calculated for the conditions after nocturnal exposure to aircraft, road or rail traffic noise were negative but did not exceed r = 0.12 and were not significant.
The results of the cognitive tasks were correlated with the SEI. There were significant negative correlations (p < 0.01) between the SEI and the reaction times of both Switch tasks (r switch = -0.28, r non-switch = -0.28) as well as significant positive correlations (p < 0.01) with the number of errors in all tasks (r switch = 0.20, r non-switch = 0.19, r go-/nogo = 0.20). There were no significant correlations between SSQ with any of the performance parameters. The BRs were not significantly correlated with the reaction times but they were inversely and significantly (p < 0.01) related to the number of errors of the switch tasks (r switch = -0.22, r non-switch = -0.18).
| Discussion|| |
This analysis concerned the hypothesis that nocturnal noise exposure reduces sleep efficiency and subjective sleep quality. , These disturbances are not necessarily followed by performance decrements. The latter can be prevented e.g. by elevated concentration  which in turn increases mental work load  as indicated by a reduced BR.  This hypothesis was previously verified in a rather exploratory analysis . where the elevated effort was indicated by a decrease of the BR during the Go/Nogo-task after nights with railway noise exposure. This paper here gives an extended analysis. It includes both performance tasks (Go/Nogo- and Switch-task) after nights with exposure to aircraft, to road and to rail traffic noise and the effects were related to subjective and to objective sleep quality (SSQ, SEI).
Performance was in accordance with majority of studies in the laboratory and field ,, not impaired after nocturnal noise exposure. As expected BRs were as well not influenced by the type of the performance tests certainly due to the same general instruction, namely to work as fast and as accurately as possible. This allowed averaging the BRs across both the Go/Nogo- and the Switch-task.
In contrast to nocturnal noise exposure, performance was significantly correlated with the SEI. The participants worked the faster the greater the sleep efficiency was but the error rate increased simultaneously. This might indicate that inter- and intra-individual variances exceed the additional variation introduced by noise exposure. On the other hand SSQ did not correlate with any of the performance measures. This is in some sense conceivable as both SSQ and performance indicate after-effects measured at almost the same time.
When comparing all quiet with all noisy nights (irrespective of the type and of the level of noise) SEI and SSQ were, according to the hypothesis, significantly reduced in respectively after noisy nights. Both these sleep parameters decreased in accordance with other studies with increasing noise levels, , whereas the type of noise had no influence. In contrast, BRs were not associated with noise levels but significantly with the type of noise. The incongruence between these parameters is also reflected in the non significant correlation coefficients between BRs on one hand and objective and subjective sleep quality on the other hand.
The BR determined during the performance tests in the morning revealed, as indicated by the data presented in [Figure 2], a slight decrease with increasing noise levels. This association failed, however, to become significant. This suggests that the completion of the performance tasks did not demand more effort after noise-induced sleep disturbances as indicated by the SEI for the physiological and by the SSQ for the subjective level. These results seem to contradict the analysis published by Schapkin et al.  However, the present analysis assumed, due to multiple testing and repeated measurements, stronger criteria for significance than those applied by Schapkin et al.  in their rather exploratory analysis.
The discrepancy between BRs and sleep indicators does not necessarily deny the hypothesis formulated above. Instead, several factors might have prevented the hypothesized effects on BR.
- First, the small alterations of sleep efficiency (about three per cent) and the rather moderate alterations of the SSQ (about 16%) might be insufficient to cause effects on performance and do therefore not need a higher effort to maintain the performance level.
- Second, the BR might be the wrong indicator as it is to some extent deliberately controlled. Other physiological variables such as heart rate or the evaluation of evoked potentials might be more suitable indicators. ,
- Third, the duration of each task, which was three to four minutes, might have been too short and performance decrements that induce compensatory efforts might show up only with longer test durations as demonstrated by Stern et al.  and Backs et al.  who studied the BR during a vigilance task and a continuous manual tracking task, respectively.
- Fourth, results might have been masked by the high inter-individual differences in the BR. 
Moreover, the sleep parameters chosen here do not sufficiently reflect sleep disturbances. The Sleep Efficiency Index is an objective but only rough measure for sleep quality. It does not concern the alteration of the sleep architecture, i.e. the amount and the temporal distribution of the various sleep stages. Subjectively evaluated sleep quality is undoubtedly most important for the individual. The questionnaire used here concerns several aspects of sleep quality and has been successfully applied in several studies, ,, but the poor ability to estimate correctly the quantitative and qualitative parameters of sleep is well known. ,, Assessment of sleep is difficult as sleep, when evaluated, already belongs to the past and has been experienced in a totally different state of consciousness. Thus, the evaluation of sleep bases on recalled wakefulness, the duration and the difficulty to fall asleep in the evening and after intermittent awakening and is further influenced by the actual situation.
The type of noise did not cause differentiated alterations of sleep quality but was significantly associated with the BR. The latter was significantly lower after nights with road and rail traffic than with aircraft noise. However, there is no plausible explanation for this effect leaving the suspicion that this is merely a rather random effect.
| Conclusions|| |
This study has shown that sleep efficiency and subjective sleep quality decreased after noisy as compared to quiet nights, whereas BRs were not affected. Obviously nocturnal noise exposure as applied here had no overt after-effects on performance. However, this does not exclude effects on the electrophysiological level that might be indicated by alterations of the latency and/or the amplitude of event-related potentials as shown by Schapkin et al.  or by other physiological variables like heart rate.
| Acknowledgement|| |
This study was supported by the Virtual Institute 'Transportation Noise - Effects on Sleep and Performance' of the Helmholtz Gemeinschaft (HGF) under the grant-no. VH-VI-111.
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Institute for Occupational Physiology at Dortmund Technical University, Ardeystr. 67, 44139 Dortmund
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2]
[Table 1], [Table 2]
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