Long term sleep disturbance due to traffic noise

Long term sleep disturbance due to traffic noise

Journal ofSound and Vibration (1983) 90(2), 173-191 LONG TERM SLEEP DISTURBANCE DUE TO TRAFFIC NOISE M. VALLET, J.-M. GAGNEUX, V. BLANCHET, B. FA...

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Journal ofSound and Vibration (1983) 90(2), 173-191

LONG TERM

SLEEP DISTURBANCE

DUE TO TRAFFIC

NOISE

M. VALLET, J.-M. GAGNEUX, V. BLANCHET, B. FAVRE AND G. LABIALE Institut de Recherche de Transports-CERNE,

109 Avenue Salvador Allende, 69500 Bron, France

(Received 4 June 1982, and in revised form 26 November 1982)

This contribution to the evaluation of the effects of traffic noise on sleep disturbance is focused on the responses of people living near a main road. Experiments were carried out in the homes of subjects who had habitually been exposed to noise for periods of more than four years. The chronic changes in overall sleep patterns and the temporary sleep responses to particular noise events caused by traffic are demonstrated. Young people show mainly stage 3 and 4 deficits whilst older people show REM sleep deficits. The cardiac response to noise during sleep was also examined. These results highlight that both long term average and peak levels are important in assessing sleep disturbance. The threshold levels, measured inside the bedroom and above which sleep quality starts to become impaired, are 37 L,(A) and 45 dB(A)L,,.,, respectively. For the type of traffic studied these two levels are coherent and it is therefore possible that a single noise index, L,,(A), is sufficient to scale sleep disturbance.

1. INTRODUCTION social surveys carried out on people living in noisy places have shown adverse effects of traffic noise, and in particular that sleep and disturbance at night play a significant part in the total disamenity. In addition to specific social surveys [l, 21 other sleep disturbance research has been conducted with greater physiological basis. In these different criteria have been used for evaluating sleep disturbance: physiological polygraphy and, in particular, electroencephalography [3], body movements [4], and signaled arousals [5]. All this work has been reviewed by Griefahn [6], who has described the different aspects of sleep disturbance, and by Rice [7] who has proposed a nocturnal noise index and noise limits to be respected to avoid disturbance. In spite of its undoubted value all this research may be criticized from a number of standpoints: all the experiments were carried out in the laboratory, often with young and healthy subjects, the specific effects related to sex and age being evaluated later; the periods of observation were limited to those which are normally accepted in the laboratory, i.e., about 15 nights maximum noise exposure which is not enough to take account of any long term adaptation of sleep that may take place; there was considerable success in reproducing noises realistically but the background noise levels in the test chambers were sometimes artificially high, around 35 dB L,,(A); the authors were particularly interested in examining the physiological micro-changes in response to an isolated and well monitored noise [8], and often paid little attention to gross changes in the structure of sleep, which in fact are often the most important from the physiological point of view and better reveal the overall impact of noise. This article sets out the results of experiments carried out in home conditions (in situ), which are considered to be more realistic than laboratory studies and especially enable the long term effects of road noise on sleep to be investigated, an aspect on which virtually no physiological data are available according to the W.H.O. [9]. Only two Many

173 0022-460X/83/180173+ 19 $03.00/O

@ 1983AcademicPressInc. (London)Limited

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research projects of this type are known: one on aircraft noise by Friedmann [lo] and one on road noise by Vallet [ll]; the investigations carried out by Fidel1 [12], Vernet [13], and Vallet [14], although also carried out in situ, were mostly concerned with instantaneous effects. The research described here was carried out as part of a co-operative venture involving laboratories from four E.E.C. countries: the Medical Research Council, Cambridge, United Kingdom; the Institut fur Arbeit Medizin, Diisseldorf, Federal Republic of Germany; TN0 Delft and Amsterdam University, Netherlands; and Institut de Recherche des Transports-CERNE, Bron, France. The paper presents the results obtained by the French team. 2. METHODOLOGY

Common procedures were drawn up by the four participating team leaders although additional scope for specific research items was still permitted within each laboratory. 2.1. EXPERIMENTAL

SCHEME

As the intention was to study the long term effects of road traffic noise on sleep, the subjects considered were selected from people who had been living for at least four years near the A43 motorway and the Paris Boulevard PQiphCrique. Since it was not practicable to compare the sleep of the same individuals at an interval of four years (for example, before the road was opened and four years after it opened) an experimental scheme was drawn up whereby the subjects could sleep in two contrasting noise situations: the existing normal noisy situation (Nl and N3) and an experimentally quieter one (N2) (see Figure 1). The quieter situation (N2) was obtained by asking the subjects to sleep Noise

&let

Noise

I I I I lmaa Getting accustomed to weormg electrodes

Recording

for

I I or 12consecutive

nights

I

L

N,

I 4

I 4

Figure 1. Experimental scheme.

at the back of the house, their bed being moved, and the temperature and morning light intensity being monitored as closely as possible. After spending several nights in relative quiet the subjects came back to sleep again in their normal bedroom (N3). The first change, from noise (Nl) to quiet (N2), caused problems of adaptation in a few subjects, but it did reveal effects in certain stages of sleep significant of chronic deprivation due to noise. Although these conditions were realistic, they did not in fact reproduce subjects’ actual experience, with the pre-existing normal quiet environment as the first environmental condition. In the other teams [15-191 nights have been registered for each subject continuously or discontinuously at home, depending on the experimental design of each team. Consequently all subjects were recorded under both noisy and quiet conditions, meaning that registrations were done under “normal” and experimental conditions as well. The experimental conditions in other teams consisted of opening windows (noisier than normal), wearing ear plugs, or fitting double glazing. All these methods to obtain a difference of 10 dB(A) L, between the two situations, noise and quiet, have several disadvantages: for example, the temperature varies when the windows are open or when

SLEEP DISTURBANCE

DUE TO TRAFFIC NOISE

17s

fitting fixed double glazing. It has thus been impossible to reproduce actual domestic experience. The question is whether or not this experimental design may affect the results discussed. In our research moving into another room to change the noise condition probably produced effects due to both the new acoustical level and to the new room. The hypothesis is that the sleep quality increases in quieter conditions and that this increase is substantial enough not to be masked by the effects due to the room change. If people have better sleep in the quiet condition one can consider that the real improvement of the sleep quality is higher than observed. In the U.K. study [18], with the noise condition changed by fitting double glazing, one week was provided for the subjects to get used to the new condition. In this experimental design troubles due to the novelty of the condition are almost completely suppressed. The continuous recording design used in our work permits one to observe more clearly the effects on the various sleep stages, which is a physiological sign of chronic deficit (in the noisy condition). The U.K. way is interesting in showing the changes in a second set of sleep stages, essentially giving a more stable degree of improvement of the sleep quality in the quiet condition. 2.2. EXPERIMENTAL SAMPLE Twenty-six subjects were chosen and noted by sex and age. Twenty-two subjects slept as couples, four slept separately. TABLE

I

Age and sex of the subjects

Age (years) Sex M F Total

245

>45’

Total

6 5 11

7 8 15

13 13 26

Great care was taken in choosing the subjects, particularly to ensure that none of them were taking sleeping pills, a criterion which proved to be very difficult to abide by for the oldest subjects. All subjects had a pure tone audiogram (air conduction). It was verified that the subjects had lived near the road, and hence been exposed to noise, for at least four years. They were also given a detailed medical examination including the essential neurological tests together with a psycho-pathological examination using personality tests such as MMPI, Eysenck EPI, Cattell Anxiety and Rosenzweig Frustration. 2.3. DATA ACQUISITION In the process of selecting subjects, the usual time at which each went to bed was determined. Since technical recording preparations took an hour, this was done in such a way that the subjects were able to go to bed at their normal times. The physical and physiological recordings were then started and continued until the subject got up next morning. By contrast with laboratory procedures, no particular times for going to bed and getting up were imposed. 2.3.1. Noise recordings Noise recordings were made by using a : in Briiel and Kjaer (B & K) microphone located at the foot of the bed connected by cable to a 2607 B & K amplifier with a

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dB(A) filter and a sampling frequency of 0.5 s, this equipment being in the laboratory truck outside the building. The signal was recorded on an Ampex FR1300A instrument, 1 in track, recording at lf in/s and on an Alvar paper system. During certain nights, the signals were recorded also on a linear dB scale in addition to dB(A). Minimum and maximum temperatures were recorded each night. 2.3.2. Physiological recordings Depth of sleep was identified by recording a number of parameters, the related changes in which determine the stages or states according to the international standards laid down by Rechtschatfen and Kales [20]. The following were recorded: two EEG signals, which were central vertex-right occipital Cz 0 2, and anterior vertex-left occipital Fz Ai; two signals for eye movements (EOG) and one for muscular activity (EMG) on the chin. An electrocardiographic (ECG) signal was added to study any passive reactions to noise. 2.4.

PROCESSING

THE

DATA

The data were considered under the following three headings: characterization of noise in 15 minute periods throughout the night; noise and physiological characterization of whole nights in order to examine the effects on the pattern of sleep and changes in its structure (258 nights analyzed); physiological and noise characterization of isolated events causing micro-changes in sleep-for heart rate 72 nights were analyzed, each period of 1 min being characterized by the L,, and by the average heart rate in order to demonstrate any indirect effect of noise on cardiac response (the response appears generally with a few seconds’ latency period and the analysis does not take account of this question), and, as regards the EEG, noises causing a temporary effect were noted visually and characterized by the peak level and the duration. 2.4.1. Acoustic description of nights For all the nights, values were obtained for the following noise indices: Leq, L1, LIO, LEO, LIVP, and TNZ, in dB(A), during the whole night recorded period. These indices were also calculated for 15 min periods and the nocturnal noise profiles were plotted. Using these profiles, we characterized the duration of continuous periods during which a given level (in L*(A)) was not exceeded, and the level L,,(A) of continuous periods having a duration fixed beforehand (6 h, 7 h, 8 h) and which correspond to minimum and optimal periods of sleep. These indices were not used because 15 min is too long a period for integrating levels and irons out the sharper peaks. It would be possible to do this by using a short L,, (10 s, 20 s, 1 min). 2.4.2. Description of nights After having characterized periods of sleep on the basis of 1 min, hypnograms for each night were drawn up showing variations in sleep during the night, and from which the following variables were defined: the total sleep time TST; the latency of the first period of sleep SL; the latency of the first dream period RL; the duration in minutes and, as a percentageof the total sleep time, the durations of stages 1,2,3 and 4, dreaming (SP or REM), and the waking periods within the sleep time; the barycenters of deep sleep (stages 3 and 4) aod of dreaming (SP or REM) (i.e., the centers of gravity calculated from the start of the recording); the number of waking periods during sleep (see Figure 2).

SLEEP DISTURBANCE

DUE

ITme ’ I I

f

NOISE

177

(h)

I

k

1

Total sleep tune

I

, I

L4 /Sleep latency k

TO TRAFFIC

I 9

REM latency

V

Awakemng



Lights out

Figure 2. Hypnogram and main sleep parameters.

2.4.3. Relations between the noise variables and the physiological variables On the basis of the two types of quantities described above, all the data were assembled to establish the relationships between the physical and noise parameters for the night as a whole. In a finer process, we also noted the physiological, EEG and cardiac micro-changes in response to the passage of vehicles which could be isolated from the background noise. The EEG reactions were characterized visually by specialists familiar with reaction patterns and the acoustic properties of the noise to which the noise was attributed were also noted (peak, duration, emergence from background noise). For the cardiac data, automatic methods were used which give for each 1 min period the following parameters: standard deviation, maxima and minima in heart rate, as well as the L,,. The relationships between the two types of variables provide a basis for proposing possible noise limits to avoid nocturnal disturbance.

3. RESULTS

3.1. NOCTURNAL NOISE LEVELS Table 2 shows the values of the noise parameters measured indoors, averaged for each subject and noise situation (quiet or noisy) and the difference between the two situations. The levels expressed as L, in the bedrooms lie between 39 dB(A) and 51 dB(A) for the noisy situation, and between 27 and 42 dB(A) for the quiet situation. The differences between the acoustic levels in L,,(A) of the two situations vary from 2 to 14 dB(A). The profiles of the noise variations (see Figures 3(a) and (b)) show the extent of these differences for certain noise indices according to subject, and these relate essentially to the position of the dwellings with respect to the road. These values are representative of heavy traffic, above 40 000 vehicles per day travelling at between 40 and 100 km/h according to the time of day. The levels presented (Table 2) are established on the same period as physiological recordings.

5 375 175

5 395 1,5

695 4 2,5

78 41 37 69 47 22 7 4 3

67 40 27 E 18 695 5,O 195

49 16 33

50 28 22

45 2’5 ‘2

Q 16

Q28

D 19

:2”5 D1:5

LNP

SD

t N: noisy situation,

Q: quiet situation,

N47

D 27

N43

D 13

between

63 47 16

62 47 15

56 44 12

51 40 11

44 33 11

41 27 14

Q 27

N40

D 12

Q 20

N 32

D 15

D: difference

63 37 26

63 37 26

64 39 15

37 32 15

31 20 11

32 20 12

TN1

46 36 10

36 25 11

Q21

N 36

D 15

37 21 16

55 42 13

40 31 9

39 32 7 49 39 10

47 37 10

46 37 9

48 40 8

58 40 13

52 41 11

the two situations.

43 36 7

29 26 3

35 31 4

45 37 8

57 47 10

48 33 15

56 48 8

44 27 17

N42

Q27

52 45 7

60 47 13

10

55 44 11

9

52 39 13

Nt51 Q 39 D 12

7,8

5,6

2

1

,3,4

Noise indices

TABLE

2

7 4 3

61 40 21

75 48 27 9 5 4

6 3 3 9 595 335

86 49 37

46 35 11

29 25 4

10 8 2

78 60 18

97 74 27

49 40 9

27 26 1

39 34 5

53 46 7

52 38 14 43 31 12

63 53 10

20,21

58 44 14

18,19

62 40 22

69 30 39

46 34 12

32 28 4

40 32 8

49 36 13

57 43 14

16,17

72 51 21

87 57 30

50 42 8

44 34 10 70 37 23

31 27 4

41 32 9

53 42 11

61 54 7

14,15

31 22 9

39 26 13

48 34 14

53 44 10

2,13

Subject(s)

Noise levels observed in nocturnal recordings

7 4 3

55 37 18

62 28 34

39 35 4

25 24 1

33 27 6

42 32 10

48 43 5

22

7 5 2

65 45 20

68 43 25

47 42 5

32 25 7

42 31 11

50 37 13

57 52 5

23

7 5 2

66 47 19

77 48 29

49 40 9

31 26 5

41 31 10

50 39 11

57 50 7

24

8 4 4

63 44 19

77 41 36

47 41 6

28 25 3

37 31 6

48 37 11

55 49 6

25

,

6 5 1

58 47 11

64 46 18

42 40 2

31 27 4

38 32 6

47 39 8

54 49 5

26,27

t; 00

SLEEP DISTURBANCE 55

DUE TO TRAFFIC

r

I

I

I

1

179

NOISE I

((1)

L *4

L!X

L90

251 2200

I

I 2400

I 0200 I

I 0400 I

I 0600 I

I 0700

I

I

I

(b)

Ll

_

LIO -

4

-

ho 40

101 2200

1

I

2400

0200 Time

1

0400

I

0500

(h)

Figure 3. Variation of acoustic indices during (a) “noisy” and (b) “quiet” nights.

3.2. CHANGES IN SLEEP The observed changes in sleep structure are distributed throughout the night and reflect significant effects of noise; similar effects can be triggered by endogenous factors such as hormonal imbalance, depression, or physical or nervous fatigue. One also can take into account short lived disturbances which in principle have no very significant effect but which interrupt the natural pattern of sleep and are very annoying when they wake the subject. 3.2.1. EEG changes in sleep pattern Average values of all results are given in Table 3, which shows the values observed in quiet and noisy conditions. The statistical comparison was done by using non-parametric tests; in order to take account of individual differences, these tests were applied to the differences between the two experimental situations. It was observed that after a number of years of exposure to noise, there are changes in sleep when the subject sleeps in quiet conditions, this reflecting the chronic disturbance caused by noise. The changes affect in particular the paradoxal or dream sleep: its latency

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ET AL.

TABLE 3

. Comparison of noise and quiet nights Difference @of #) Ail subjects

Total sleep time (min) Sleep latency (min) REM latency (min) Sleep stage 1 + 2 (min) % TST 3 + 4 (min) % l3T REM (min) % lXT Wake stage (min) % K!ZT Barycenter of REM Barycenter of Stage 4 Changes to wakening Heart rate (beats/min)? Heart rate variability

Reaction time (ms)S Subjective sleep quality No. of wakenings Sleep.latency (min) Av. period awake (min)

N-Q

Noise

Quiet

455 18 9s 272 60 63 14 83 23 28 6 270 89 8.2

(a) Sleep stages 455 17 *** 84 263 58 65 14.6 *** 99 *** 29 * 24 * 4.5 268 107 Y 6.9

+1*3 -0.8 15 9 1.1 -2 -1.5 -14 -3 6 2 4 -18 1.3

(b) Cardiovascular 61.9 11.64

1 0.9

63 12.58

308 7.2 1.9 23 14.1

P

(c) Performan*ce 276

15

(d) Sleep questionnaire ** 8.1 1.5 Y 18 12.9

-0.9 0.4 6 1



t Data for 35 nights. $ Data for 16 subjects only.

***p
**p CO.05;

* p < 0.05 (one-tailed); Y, p < 0.10 (Mann-Whitney).

of appearance is reduced during quiet nights; its duration both in absolute terms and as a percentage of total sleep time increases in quiet nights. Waking periods are shorter and fewer (trend only) in quiet situations. 3.2.1.1. Individual patterns However the average figures, which are a combination of the data for all subjects in the sample, show only slight differences, while the results given in Table 4 for each subject highlight the extent and variety of reactions. The most characteristic responses may be discussed. In the quiet situation the total sleep time rises for about half the sample and falls for the other half. It one examines the concomitant variation in the duration of waking periods one sees (subject 1) that this period falls, as do the latencies of sleep and dreaming. This subject obtains great benefit from returning to the quiet situation. For subject 3, 7ST falls by 25 min, which appears negative but in fact it is the waking time within the TST which falls. This type of reaction indicates an improve-

SLEEP DISTURBANCE DUE TO TRAFFIC

182

NOISE

TABLE 4

Negative (-) or positive (+) variations of TST, waking period, latency, from noisy conditions to quiet conditions TST

r Subject 1

f +

2

+

3 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 22 23 24 25 26 27

zz + + + + + _ + + = + + + + + +

Duration (min)

Latency Waking f

28

_

13 25 10 28

= _ = + + = = _ + + _ _ = _ = =

42 30 16 5 9 8 30 12 15 69 35 20 31 33 20 50 12 12

Duration (min)

15 21 33 12 10 7

21 40 34 32 10 62 18 8 20 12 8 41

I

,

I Sleep

REM

-

-

= zz _ = + +

_ = + z.z _ _ z 1 + + = = + + =

= = + = + = = =

ment. Subject 15, and to a lesser extent, subjects 5 and 9, obtain no benefit by changing to the quiet situation, but these are the only ones. A fourth type (subjects 7 and 8) shows

a sharp increase in TST but only a moderate rise in their waking times. For these two subjects the latency of sleep diminishes and it may be concluded that changing to the quiet situation is on the whole beneficial. This classification does not appear in the averaged figures and a total of 17 out of 20 subjects sleep better, on the whole, in the quiet situation. The experimental observations reported here indicate the individual variability of EEG response to noise. This variability in sleep behavior due to noise is fairly easily explained by reference to the theories of sleep [21]. In fact the control systems of the three states of alertness (awake, asleep and dreaming) are different, each having a separate anatomical, neurological and biochemical basis. Each of these systems is governed by a neurobiochemical activator and inhibitor. The sequences and the triggering pattern are complex, since the activity of each system is partially independent and partially interactive with another system. Thus it is understandable that each individual should have different sleep responses to noise, some being biased to the waking periods, the others to the periods of sleep or even dreaming. Averaging the results gives only a mediocre indication of these differences and it is more fruitful to follow the procedure of examining the classification of pattern responses to noise.

182

ET AL.

M. VALLET

3.2.1.2. Selection of a noise index and threshold From the physiological observations carried out, it is possible to take into account the impact of noise on sleep by comparing them with the measured noise values. Of the physiological indicators analyzed, that relating to the length of time spent awake during the night and that of the duration of paradoxal sleep (REM) show the most significant variations between the two experimental situations. These two partial indicators are used since there is no overall indicator of the physiological quality of sleep. The average values of the physiological parameters and the noise indices calculated for each subject for the quiet and the noisy experimental situations are shown in Table 5, along with their correlation.

TABLE 5 Relationships between the two main physiological indicators and the noise indices

Physiological parameter

Noise index

Time spent awake TO

L, Ll L 10 Lo L 90 L& TNI

Duration sleep

of REM

LW LI L 10 Lso L 90 Lib

“IX”, not significant;

* p < 0.10;

** p < 0.05;

Correlation 0.08 0.12 0.10 0.03 -0.12 0.27 0.22 0.16 -0.33 -0.33 -0.35 -0.25 -0.11 -0.44 -0.42

Statistical significance ns ns ns ns ns ** ns ns ** ** *** * ns *** ***

*** p -C0.01; for n = 52.

At the noise levels measured in the rooms, it is observed that the variation in instantaneous levels (a) is significant both in the duration of the periods spent awake and in reducing REM sleep. The indices of the type LAP and ZNI, which integrate not only the overall level but also the variations, are slightly better correlated with the physiological indicator than L,, or L1 taken separately. The differences in the links between the noise values and the physiological responses do not seem sufficient for any reliable noise index to be suggested. However Lgo and LsO are impractical as nocturnal noise indices on the criterion of relationships with sleep responses. To refine this analysis of the selection of an acoustical index and to explain the variables Z’c and TS and, in particular, to look for a possible threshold, a discriminatory analysis program AID (Automatic Interactive Detection) was carried out on the same data. This technique has been clearly described by Langdon [22]. For the first physiological para-

SLEEP

DISTURBANCE

DUE

TO

TRAFFIC

NOISE

183

meter, time spent awake during the night (T,), the following scheme (or tree diagram) is obtained: Physiological variable: TO awake I

[ L,c3;dB(A)

L,, 2 38 dB(A) I

1

The first noise index to emerge, because it is the best parameter for prediction of time spent awake (To), is L,, and the break point occurs at 37 dB(A). The following indices, LIO and 7iVI, both make greater allowance for the high levels, each in its own way. For the second physiological variable, duration of REM sleep, the following scheme is obtained:

I

Physiological REM Sleep Ts

1

I L t c 47 dB(A) I

Lla48dB(A) I

The first split is made on L1; this underlines the weight of the peak events during the night, but this noise index is difficult to forecast and it is not used in regulations. The second split is made on LNP on both sides. On the basis of these two quantitative analyses, with consideration of the convenience in predicting it and its connection with present regulations in France, the index L,, may be put forward as a good representation of the total physiological disturbance to sleep. The proposed threshold is 37 dB(A), based only on the physiological analysis. 3.2.2. The instantaneous EEG modifications of sleep Instantaneous modifications of sleep can be identified from visual analysis of the micro-changes in the noise signal, caused by passing vehicles. The physical and physiological patterns are easily recognizable to a trained observer. The instantaneous EEG effects can take four forms: no effect results (reaction 0); the noise may cause a slight and transient reaction detectable on the EEG, the EMG and the EOG with a duration of 6-20 s; there is a change in sleep stage, with a minimum duration of one epoch; the subject awakens. In the noise analysis one makes use of the level of the noise peak (maximum noise with the FAST time constant, 0.125 s), the point of emergence from the background noise and the duration of the noise.

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AL.

3.2.2.1. Frequency of instantaneous reactions according to the noise condition The sample analyzed covers 106 quiet or noisy nights for 10 subjects, equivalent to 63 482 separate noises: 2281 noises produced an EEG effect, 447 an awakening, 940 changes in sleep state and 894 transient effects. The number of disturbances varied appreciably according to the noise situation of the night in question. On the average for noisy nights 31 effects were observed if the three types of effect are taken into account, and 21 if only awakenings and changes in sleep state are considered. For quiet nights, 15 effects for the three types are observed and nine effects for the two types. Improving the noise situation of subjects who have been exposed to noise for five years -and who have therefore possibly had the time to get accustomed to itproduces a sharp fall in the number of EEG effects. It is concluded from this that, after five years of exposure to noise, isolated noises still produce EEG reactions: there is thus no acclimatization to the noise. There are substantial individual differences in the immediate reactivity of the sleep to noise (micro-changes), just as for overall modifications in sleep patterns; these are shown in the graphs of Figure 4.

2 3 4 5 6 7 8 9 IO II Nqht 951 mnl1230 yQ 276 321 365 3;” 1220 12iu 1520

No.of

980 91I I184 1”: 346 m5 314 290 309, ,218 012

Oulet penod

Owet penod vechicles

detected

by the microphone

Figure 4. Evolution of temporary responses to noise events with the acoustic conditions. (a) Subject 7; (b) subject 4.

For subjects such as 7, moving into a quieter bedroom produces an appreciable fall the number of disturbances, which increases again when the subject returns to the noisy bedroom. For people of the second type (subject 4), reducing peak noise levels by 10 dB(A) gives only a slight initial improvement. in

3.2.2.2. Degree of disturbance of sleep according to noise levels To begin with, it is found that the average noise level causing awakening is higher than that which leads to changes in sleep state, which is in turn higher than that causing transient reactions. In our sample of 2281 noise peaks extending from 28 to 70dB(A), it is seen that the average peak noise level producing awakening is 50.3 dB(A), c = 8.5 dB(A), changes in sleep state is 48.5 dB(A), u = 8 dB(A), and transient reactions is 47.6 dB(A), u = 7 dB(A). On the average, the greatest disturbance is caused by the loudest noises. The cumulative distribution of the different effects (see Figure 5) shows that if the peak noise levels do not exceed 40 dB(A), 80% of transient effects and changes in sleep

SLEEP DISTURBANCEDUE

TO

TRAFFIC

185

NOISE

80

70 60 50

28 31 34 37 40

43

46 49

Peak levels

52 55

58 6,

64 67 70

(de(A))

Figure 5. Cumulative distribution of sleep responses by peak levels. -, shift; - - -, awakening.

Transient effects;

. ., sleep stage

state would be avoided and 87% of awakenings eliminated. Although these levels are inside dwellings, they may seem unrealistic. A peak threshold of 45 dB(A) would eliminate about two-thirds of the disturbing effects of isolated noises. The choice of threshold lies between these levels of 40 and 45 dB(A). Tests have been tried to demonstrate the effect of factors such as age and sex. No difference has been found between men and women as regards sleep reaction to isolated noises. Subjects older than 45 years tend to be less sensitive to isolated noises than do younger subjects. This is statistically significant for the transient effects and changes in sleep state, but not for the awakenings. The principal observation concerns the difference between the peak noise levels leading to sleep reactions in the noisy and quiet situations respectively. It was observed that in a “quiet” period fewer sleep reactions took place, but the peak noise levels producing these reactions are lower (see Table 6) than in noisy conditions. In quiet conditions the average peak noise level causing an EEG effect varies from 42 to 44 dB(A) while that causing the same effects in a noisy situation ranges from 50 to 53 dB(A).

TABLE 6 Peak noise levels producing sleep reactions Quiet condition

Noisy condition

u

N

I dB(A) peak level

7.86 7.37

333 641 584

43.85 42.38 41.99

T dB(A) peak level Awakenings Sleep stage shift Transient effect

52.56 51 SO.57

6.29

, u

N

Difference (Student’s t-test)

S-85 5.23 5.33

114 299 310

p
It is concluded that the peak level of an isolated noise is not sufficient to take into account the time dependent sleep reactions. It is necessary to take into account also the overall level and that at which the peak noise emerges.

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ETAL.

3.2.3. The response of heart rate to noise during sleep The heart rate response was analyzed from the mean heart rate-t, calculated per minute, and the variabilty calculated over the same time. 3.2.3.1. The mean heart rate The heart rate was analyzed in periods of 1 min, throughout the night, and the noise extracted in the form of short I.,,. The correlation between the noise levels L,, and the heart rate (Hm)t was calculated per night and per subject. From the standard deviation in the heart rate the coefficient of variation of heart rate was calculated, again per minute, and denoted as Vm. The levels of variation, which indicate the fine structure of cardiac response, were expressed in terms of the noise levels. A second correlation series was obtained. The calculations were carried out over 62 nights. The results are summarized and in Table 7 which shows the number of nights for which the correlations Hm/L,, Vm/L,, are non-zero (r = 0.13 at a threshold with p C 0.05 for a sample number of 150) and positive. TABLE

7

Mean heart rate response results

Subject

Nights with positive correlation HmIL,

Nights with positive correlation VmIL,

Total number of nights analyzed 5 4 9 6 9 9 11 9 62

20 21 22 23 24 25 26 27

1; 7

3 1 2 2 7 7 3 5

Total

56

30

5

2 : 9

All in all, there is positive correlation between heart rate and L,, for nearly all nights for all subjects. There is positive correlation between the variability in heart rate and L, for half of the nights. 3.2.3.2. Variability in heart rate response to noise The mean heart rate (EKG) does not change with age but the EKG variability is lower in older subjects (see Table 8). Cardiac variability is greater in the women. A threshold for the cardiac data was obtained by applying a breakdown as for sleep patterns. This analysis gives a threshold at 37 dB(A) for short Leq, a level which agrees entirely with that provided by the analysis of the overall sleep pattern. 3.2.4. Psychological responses after disturbed sleep Each morning, the subject assessed the quality of his sleep during the past night (subjective aspect) and performed a psychomotor test (objective aspect). The overall t The heart rate frequency does not show the same metric qualities as the period time, but it is frequently used in the literature.

SLEEP DISTURBANCEDUE TO TRAFFIC NOISE

187

TABLE 8 Heart rate responses to noise events and its variability with age and sex

Mean heart rate EKG (Hm) beats/min) Standard deviation EKG Variability EKG (VW) maximum MAX minimum MIN Difference MAX-MIN

Mean heart rate EKG (Hm) (beats/min) Standard deviation EKG Variability EKG (Vm) Maximum MAX Minimum MIN Difference MAX-MIN

Subjects aged < 45 years

Subjects aged >4S years

Student’s t-test comparison of values of means

64.72

65.06

ns

S-48

4.84

p co.05

8.37

6.78

p
79.67 52.00 27.67

79.93 54.13 25.80

p JZOS p co.05

Men

Women

Student’s t-test

65.01

64.83

ns

3.56

6.74

5.34

9.62

75.46 56.53 18.87

84.48 49.84 34.55

p p p p p

-co*05
subjective quality of sleep improves significantly in a quiet environment, although there is a negative reaction to the first one or two nights passed in the quiet situation when it is a new experience. The average score goes from 7.2 for noisy nights to 8.1 for quiet nights. In the questionnaire a self-evaluation of physiological quantities is also attempted. The estimated number of waking periods falls in the quiet situation (1.5 compared with 1.9 in the noisy situation), the latency in falling asleep diminishes in the quiet situation (18 min compared with 23 min in the noisy situation), and the duration of the period spent awake during the night falls slightly (12.9 min compared with 14.1 min). As regards psychomotor performance, it is observed that the motor reaction time to a sensory stimulus is significantly shorter after quiet nights than after noisy nights (308 ms noisy-276 ms quiet. The difference is significant, p < 0.05). This low amplitude result does have some value because it demonstrates the chain effect, noise + effect on sleep + effect on efficiency, after a slightly disturbed night.

4. DISCUSSION

The experimental results show first of all the part played by noise in modifying sleep patterns, and physiological acclimatization so slight that it may be taken that no acclimatization to noise takes place after five years of exposure. Shown in addition is the importance of the noise energy level, which, for the type of traffic observed, is greater than that of the peak levels: indeed the changes in EEG patterns are greater for the physiologist than the micro-changes caused by the peaks. The most marked and the most novel result of this research is the modification in the night sleep pattern due to changes in dream latency, and in the dream and waking period durations during the night. Analysis of individual results has highlighted the extent of

188

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ET AL.

the differences between subjects, for which a partial explanation has been given in section 3.2.1 as being the complexity of the systems governing the different types of sleep. The result concerning the reduction in REM has been confirmed by the work of Jurriens, carried out as part of the same joint project [15], wherein nine subjects out of 11 showed a reduction in REM duration, the subjects ages varying from 20 to 50 years. However, the same author [16] observed in a laboratory experiment that it was the duration of deep sleep (stages 3 and 4) which was reduced by noise. Two exogeneous differences may affect this difference in sleep response to noise: the experimental location (laboratory and home) and the age of the sample. Wilkinson [17], whose work was carried out in the framework of the joint European project mentioned, has also stressed the reduction of deep sleep in a noisy situation. We ourselves [ 1 l] had observed on a sample of subjects aged between 25 and 50 years that the effect of noise was focused on deep sleep. Ehrenstein and Muller-Limmroth [23] observed in a laboratory experiment that noise led first of all to a reduction in deep sleep during the first two nights spent in noisy conditions, then to a reduction in REM sleep, the latter being confirmed by a significant recovery during the two quiet nights that followed. Eberhardt and Akselsson [24] have observed in an experiment in the home a 10% decreasing of the deep sleep duration (stages 3 and 4) for a group of subjects aged 22-27 years and a trend to a decreasing REM period with a 60-65-year-old subjects group. The above are a number of very recent observations which show the effect of nocturnal noise on sleep patterns. The reduction of duration affects not only deep sleep (stages 3 and 4), which affects young subjects in particular, but also the first period after the appearance of the noise in the environment and the REM sleep which is reduced particularly in older people and after long exposure. This supports earlier results which show that lack of deep sleep (3 and 4) is compensated first of all, followed by REM sleep rebound. The physiological amplitude of these changes in sleep owes more to the energy or background level than to the peak levels, the latter having a marked effect on the appearance of temporary sleep reactions. The question is therefore how to characterize nocturnal noise and whether one or two energy indices should be used: i.e., the energy index already mentioned together with a peak index. Before investigating a two parameter system observations were made to see if the peak level at the threshold of 45 dB(A) and the energy level at the threshold of 35-37 dB(A) were coherent. A relationship between L,, and L,,,, is established on the basis of the prevailing conditions and the results of noise measurements. The physical measurements carried out throughout the nights in question put the traffic at about 75 events per hour; the distance between the road and the dwellings is 50 m; the vehicle speed is 25-30m/s. The experiments showed a difference of l-2dB(A) between the arithmetic mean and the peak energy mean for the type of traffic considered. It is known that for a point source radiating in all directions, with absorption and applies: following relationship effect neglected, the Doppler (L,g )T = L, - 10 log T - 10 log dV + 10 log & - 8. Here (Leq)~ is the equivalent energy level due to the passing source, where T is the period of integration, &- is the subtended angle during the period T, d is the distance of the observer from the line followed by the vehicle (m), and V is the vehicle speed in (m/s). The following relationship relates noise power level L, to peak level Lpmax: Lpmax= L, - 10 log 2?rd2. One therefore has or (Leq) (1 h)= tLeq)T =&ma. - 1010gT+1010g2~d2-lOlogdV+lOlog&--8, L gmax+ 10 log (d/u) - 30, and (Leq) (1 min) = Lpmax+ 10 log (d/v) - 30, and (L,,) (1 min) = Lpmax+ 10 log (d/u) - 12. Let Q and q be the traffic flow per hour and per minute (vehicles per hour, vehicles per minute). For these traffic values, one has CL,,)

SLEEP

DISTURBANCE

DUE

TO

TRAFFIC

NOISE

189

or (Leq) (1 min)=L,,.,+lOlog(d/v)-12+ (1 h) = Lpmax+lOlog(d/u)-30+10logQ, 10 log 4. Applying these equations shows that an L,,,, of 45 dB(A) corresponds to an L,, level varying from 35.5 to 39.5 dB(A), a range which covers the noise threshold of 37 dB(A) which should not be exceeded to avoid sleep disturbance, suggested in section 3.2.1.2. 5. CONCLUSIONS

This comprehensive physiological approach to the disturbance of sleep by road traffic noise has led to an essential conclusion: after many years of exposure to noise, transfer to a quieter environment provokes a considerable change for better sleep, for most people. This improvement is systematic for heart rate and EEG responses to isolated noise. The overall sleep pattern amelioration is less regular, both the total sleep time and the durations of various sleep stages being affected: young people show mainly stages 3 and 4 deficits in noisy conditions whilst older people show REM sleep deficits. The experimental design allows one to assert that the adaptation to noise is far from complete after four years of noise exposure, but one cannot affirm that there is not a beginning of adaptation by subjects, who may adjust sleep structures to compensate. In the case of traffic on motorways or urban highways one can propose the index L,, to account for human sleep response to noise, because it is linked with several aspects of the overall sleep patterns. One finds that the peak levels are as significant as the mean energy level, and that they do not exceed 45 dB(A) inside the bedrooms. At these acoustical levels, coherence between the L,, index and the peak levels has been found. The index L,, thus is itself sufficient as a nocturnal noise index. The threshold proposed, which is based on three physiological parameters, modification to sleep patterns, responses of heart rate to noise and instantaneous sleep reactions to noise, lies at 37 dB(A). Our experimental data validate the World Health Organization recommendation in which the threshold is placed at 35 dB(A) L,, inside the bedroom [9]. To take a broader view, one may recall that daytime noise has a direct effect on the quality of sleep at night [25], when this is in a quiet situation. This observation invokes the relationship between daytime and nocturnal noise levels, which is fairly well established for high, stable traffic flows. For lower, more random traffic flows, in the present state of knowledge, it is not possible to use a peak level: so many factors are involved for a peak to cause a reaction, covering the physical aspect (emergence from background, number of noises and intervals between them) and the physiological aspect (sleep state, latency since the preceding EEG reaction). It may be possible to carry out an analysis by using the short L,, to characterize a single event and also to establish an L,, for the night. There is a need for research in the near future into the effect of shortened or broken sleep on the health of peope living in noisy places. So far only the physiological changes have been demonstrated; Battig [26] has stressed the difference that exists between the cardiac response to noise which he studied in detail and some cardiovascular pathology which is unproven and in fact hardly understood. One way of demonstrating the assumed pathological effect of noise on sleep would be to work on limiting subjects (as has been done often in human sciences), which in our case would be the most sensitive and the most stressed people. One avenue would be to study the consumption of sleeping pills, which seems to increase with noise. Another more ambitious and more basic field of research would be the physiological changes brought on by noise, particularly those in the systems governing the functioning of certain anatomical and physiological systems in man.

190

M. VALLET ET AL ACKNOWLEDGMENTS

Thanks are due to Dr A. Muzet and J. Mouret for scientific advice, to J, C. Bruyere, J. F. Laurens; R. Vidon, J. L. Ygnace for assistance in collecting and processing data and to workers in the associated European teams, A. Jurriens, A. Kumar, R. Wilkinson, K. Campbell, B. Griefahn, and E. Gras, and finally to P. Guillot, responsible for managing the program. The work was done under contract to the Commission of the European Community, N” ENVF 149 77, and the Minis&e de 1’Environnement GBV and CETUR.

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L. EBERHARDT and K. R. AKSELSSON 1982 University of Lund, Sweden, Report. The disturbance of road traffic noise of the sleep of young and elderly males as recorded in the home. 25. R. BLOIS, G. DEBILLY and J. MOURET 1980 American Speech and Hearing Association 10,425-432. Daytime noise and its subsequent sleep effects. 26. K. BATITG et al. 1980 Archives of Environmental Health 35, 228-235. A field study on vegetative effects of aircraft noise.

24.J.