Vol.2, No.10, 1163-1169 (2010) Health
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
Effects of cigarette smoking on the evolution of hearing
loss caused by industrial noise
Abbate Carmelo1*, Giorgianni Concetto1, Zirilli Agata2, Tringali Maria Antonietta1, D’Arrigo
Graziella2, Brecciaroli Renato1, Abbate Adriana1, Salmaso Luigi3
1Department of Social Medicine of Messina University, Section of Occupational Medicine, Messina, Italy; *Corresponding Author:
2Statistics Department, Messina University, Messina, Italy
3Statistics Department, Vicenza University, Vicenza, Italy
Received 11 June 2010; revised 6 July 2010; accepted 26 July 2010.
The few studies evaluating the changes caused
by cigarette smoking on hearing loss induced by
occupational exposure to noise have reached
discordant conclusions. The aim of this study is
to investigate the interactions between cigarette
smoking and occupational exposure to noise as
risk factors in the onset and development of he-
aring loss. The study was performed on a sam-
ple of 557 shipyard workers exposed to noise at
an Equivalent Level (Leq) of 93 dBA. On the ba-
sis of their smoking habits, they were divided
into three groups: group (A), non-smokers; gro-
up (B), smokers (15-30 cigarettes per day); and
group (C), heavy smokers (over 30 cigarettes
per day). The study focussed on the audiometric
responses of the subjects at the frequencies of
500, 1000, 2000, 3000 and 4000 Hz. The results
were then compared using statistical technique-
es (Internal correlation coefficient, exponential
model, ANCOVA, NPC test). Comparison of the
audiometric responses showed statistically sig-
nificant differences between the three groups.
Non-parametric analysis, performed using the
NPC test, highlighted that the interaction betwe-
en smoking and exposure to noise has an influ-
ence on hearing loss at all frequencies, and
particularly at high frequencies (3000-4000 Hz).
The data obtained from the examined sample
show that smoking and exposure to noise cause
an increase in occupational hearing loss and
that this is directly related to the number of
cigarettes smoked.
Keywords: Smoking; Hearing Loss; Noise;
Audiometric Test; Non Parametric Test
Hearing loss as a result of exposure to noise is one of the
most frequent pathologies found in workers, and is in-
fluenced by a number of parameters, such as intensity of
the noise, temporal and spectral patterns, duration of the
exposure and susceptibility factors. Controlling these
parameters may improve the individual response to noise
and evolution of the damage.
One of the factors influencing hearing susceptibility
which has attracted growing interest in recent years is
cigarette smoking, although the role of smoking in abet-
ting the development of sensory neural hearing loss is
controversial, as recent literature shows.
Some authors highlight that smokers have a greater
risk of hearing loss than non-smokers [1-3], while others
find no connection between the onset of sensory neural
hearing loss and cigarette smoking [4,5]. Nomura [6] in
a review referring to the period 1966-2003 , mentions 9
studies which report a positive association between smo-
king and hearing loss, and 6 which reach completely op-
posite conclusions. The author, however, concludes by
supporting the thesis of a positive association between
smoking and hearing loss.
Few studies evaluate the effects of the association be-
tween smoking, occupational exposure to noise and hea-
ring loss. Palmer et al. [7] hypothesises that exposure to
noise in smokers aggravates the degree of sensory neural
hearing loss, probably due to the effect that these factors
have on the vascular system. In fact, both exposure to no-
ise and smoking cause vasoconstriction in the cochlear
vessels with consequent reduced perfusion, increased pl-
asma viscosity and/or possible creation of carboxyhaem-
oglobin, which aggravate any local hearing loss. Mizoue
et al. [8] observes that the hearing loss affects only the
cells responsible for the hearing response to high freque-
ncies, since their position at the end of the nutritive ar-
teries makes them more vulnerable to ischaemic damage.
Abbate C. et al. / Health 2 (2010) 1163-1169
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
Dengerink et al. [9], in an experimental study on tempo-
rary threshold shifts (TTS) in man, highlights how ciga-
rette smoking modifies the response of hearing to noise
exposure, and attributes this effect to carbon monoxide
(CO) and nicotine. Ferrite et al. (2005) confirm a syner-
gic effect between cigarette smoking, exposure to noise
and age on hearing loss caused by industrial noise. No-
mura [10], in a cross-sectional study, carried out on 397
Japanese workers exposed to noise, finds a positive as-
sociation between smoking, exposure to noise and hear-
ing loss, even if this is often masked by atherosclerotic
Jaruchinda [11] asserts that cigarette smoking influ-
ences noise injury in helicopter pilots and aircraft mech-
anics. Uclide asserts that the combined effects of noise
and smoking is not interactive but additive. Recently,
Pouryaghoub [12] concludes that smoking can accelerate
noise induced hearing loss, but more research is needed
to understand the underlying mechanism
Other authors reach opposite conclusions. Pyykko et al.
[13] observe that smoking does not affect the incidence
of noise-induced hearing loss in 199 forestry workers.
Nakashima et al. [14], in a case-control study conducted
on 109 subjects, reports that hearing loss is not affected
by smoking.
Since the interactions between industrial noise, cigar-
ette smoking and hearing loss are uncertain, this study
aims to clarify the relationship between such variables
by trying to evaluate the effects of external factors on he-
aring loss. This information is particularly useful when
drawing up prevention programs aimed at protecting
workers’ hearing. As far as regards smoking, and in the
absence of specific studies, the possible effect of the nu-
mber of cigarettes smoked per day is also taken into con-
The study was carried out on male subjects, who had
only ever had one job, as shipwrights at a large shipyard
for the construction of high-speed boats in southern Italy.
The enrolled sample was composed of the entire work-
force of 900 men.
Noise measurement, performed in November 2003 ac-
cording to European directives 89/391/EEC and 86/188/
EEC, showed that all the subjects were exposed to a dai-
ly personal exposure level (LEP,d) of 93 ± 2 dBA of eq-
uivalent level. The exposure value reported did not disp-
lay significant variations compared to the controls prev-
iously performed by the company every three years from
1992 onwards, as provided for by Italian legislation re-
garding occupational exposure to noise. This lays down
that the noise risk in working environments and the LEP,
d for each individual worker must be assessed.
The subjects enrolled for the study were selected by
applying the following exclusion criteria:
1) previous exposure to neurotoxic drugs
2) frequent use of ototoxic drugs
3) metabolism diseases
4) haematological or neurological diseases
5) acute and chronic ear, nose and throat conditions
6) residence since birth in a Council district other than
that in which the subject works
7) alcoholism
8) former smokers, those who had been smoking for
under 10 years and subjects whose smoking habits had si-
gnificantly changed over the years
9) hobbies such as hunting, underwater fishing, frequ-
ent visits to discos (> once per week)
10) work experience with other companies
11) length of service < 10 years.
All the subjects normally used individual hearing pro-
tection devices supplied by the company (earphones and
The sample thus selected was composed of 557 subj-
ects, who were divided into three groups on the basis of
their smoking habits. The first was composed of non-sm-
okers since birth (Group A), the second (Group B) of
smokers (15-30 cigarettes per day for at least 10 years),
and the third (Group C) of heavy smokers (over 30 ciga-
rettes per day for at least 10 years). People smoke lass
than 14 sigarettes a day have not been taken in conside-
ration because the data is not significant.
The entire sample was given a general medical exam-
ination, routine blood tests, otoscopic examination, and a
tonal audiometric test after at least 16 hours without ex-
posure to occupational noise.
For the purposes of tonal audiometric assessment, the
study took into consideration hearing threshold values at
the frequencies of 500, 1000, 2000, 3000 and 4000 Hz.
The study was based on the values recorded by the
tonal audiometric traces.
Table 1 shows the sample size, average age and years
of service of the subjects, by group:
Table 1. Sample size of the groups and mean values for age
and length of service.
GroupSample sizeAge ± σ Length of service ± σ
A 215 41.45 ± 7.81 21.36 ± 7.57
B 194 40.77 ± 8.83 20.15 ± 8.34
C 148 40.12 ± 8.77 20.25 ± 8.35
ABC 557 40.98 ± 8.52 20.77 ± 8.15
Abbate C. et al. / Health 2 (2010) 1163-1169
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The aim of the analysis was to assess any significant
differences, if they exist, between the audiometric resp-
onses of the three groups determined not only by their
being smokers or not, but also by the quantity of cigare-
ttes smoked daily.
Statistical analysis – To evaluate whether the audio-
metric responses of the two ears are interdependent, we
used an internal correlation coefficient. An exponential
model was also used to describe the trend of audiometric
responses in function of the risk index. Moreover, to
verify whether the trend of the responses may be expre-
ssed with a single function, the ANCOVA (Analysis of
Covariance) model was adopted. Lastly, we used an NPC
(Non-Parametric Combination) test to compare all the
audiometric responses of the three groups for the various
risk indexes.
Considering that biological age and the duration of ex-
posure influence audiometric response, and consequently
may determine modifications in the individual responses
at the various frequencies, we used a risk index [14] wh-
ich made it possible to evaluate the combined action of
the aforementioned variables.
The relation which makes it possible to determine the
risk index (Ir) is:
Al represents length of service;
Ea biological age.
each group, the following type of model was used:
Ra = a·bx
where x = (Age of starting work)(Risk index).
The Table 2 shows the audiometric responses at dif-
ferent frequencies in the three group. Since we meas-
ured the audiometric responses of both ears for each
subject, we decided to assess whether there was any
close interdependence between them. In order to achieve
this we established the internal correlation co-efficients
between the distributions of the responses of the two
ears, for each group and frequency (Table 3).
The internal correlation coefficients all indicate inter-
dependence between the responses of the left and right
ear for all frequencies and all groups.
Consequently, analysis may be performed on the resp-
onses of either ear, chosen at random, in each subject.
The risk index showed the following equation to the sc-
Table 2. Audiometric responses at different frequencies of the
three tested groups as mean and DS.
(Hz) A – no smokersB - smokers C – heavy smokers
500 10,09 ± 3,09411,06 ± 2,05 15,78 ± 3,44
1000 11,84 ± 4,01513,76 ± 3,74 18,58 ± 5,05
2000 21,77 ± 8,03926,91 ± 5,31 29,32 ± 3,76
3000 33,3 ± 10,11 42,29 ± 8,11 46,32 ± 9,26
4000 36,93 ± 10,3553,76 ± 8,22 60,47 ± 5,48
Table 3. Values of internal correlation coefficients for each gr-
oup and five frequencies.
Frequencies (Hz)Group A Group B Group C
500 5,1875 5,340277778 5,779861
1000 5,93125 6,185416667 5,577778
2000 6,185416667 5,691666667 5,857639
3000 6,593055556 6,286805556 6,432639
4000 6,670138889 6,479861111 5,8625
The response trend for each audiometric frequency of
the three tested groups were:
()3.0925 1.26610.8089
500( )3.8716 1.23820.8419
()8.5578 1.14680.8277
 
 
 
( )3.09331.30630.8033
1000( )6.2183 1.18840.8255
()7.7757 1.21430.8354
 
 
 
( )4.87751.34590.8572
2000( )14.4558 1.14640.8037
()20.1123 1.09010.8614
 
 
 
()11.0088 1.24810.8146
3000( )22.7629 1.14650.9180
()24.2708 1.15720.8840
 
 
 
()13.3375 1.22640.8091
4000()32.7116 1.11670.9298
()46.2579 1.06360.8496
 
 
The Figures 1-5 below show the theoretical trends
determined by means of the aforementioned relation, by
group, of the audiometric responses at the various fre-
quencies, hypothesising a subject starting work at twenty
years (average age of starting work found in each
The model proves that Ir increase corresponds to incr-
eased hearing loss at each frequency in all tested groups.
The ANCOVA (Analysis of Covariance), applied to
Abbate C. et al. / Health 2 (2010) 1163-1169
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Figure 1. Theoretical trend of audiometric response at the
frequency of 500 Hz.
Figure 2. Theoretical trend of audiometric response at the
frequency of 1000 Hz.
Figure 3. Theoretical trend of audiometric response at the
frequency of 2000 Hz.
the audiometric responses of the three groups, demon-
strated that the trends of each group, for all the frequen-
cies, may not be described by a single function, as can
be seen from the results obtained by means of the paral-
lelism test (Table 4).
The high significance of the p-values indicates that the
relation between the variables studied is not sufficiently
Figure 4. Theoretical trend of audiometric response at the
frequency of 3000 Hz.
Figure 5. Theoretical trend of audiometric response at the
frequency of 4000 Hz.
Table 4. Results of the parallelism test.
Groups F p-value
ABC 877.40.00 0.000
AB 205.74 0.000
AC 12079.35 0.000
BC 16503.14 0.000
represented by one single regression coefficient. Conseq-
uently, the three groups had to be considered separately.
The analysis thus far performed allowed us to demon-
strate that the three groups, distinguished on the basis of
smoking habits, underwent different variations in the te-
mporal evolution of noise-induced hearing loss for all fr-
The results obtained led us to analyse the data in gre-
ater depth, in order to address a series of questions wh-
ich naturally sprang to mind:
1) does smoking act generically on the audiometric
responses, or only at specific frequencies?
2) are the audiometric responses equally influenced in
the two groups of smokers?
3) do age and occupational exposure influence the two
Abbate C. et al. / Health 2 (2010) 1163-1169
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groups compared differently?
For this reason, the Ir for the whole sample was strati-
fied in 10 layers using Ir distribution percentiles.
We stratified Ir relative to all subjects, in 10 layers us-
ing Ir distribution percentiles. Table 5 shows Ir values.
We conducted a comparative analysis for layers and
each frequency of Ra, between the three groups. The me-
thod used was the Nonparametric test Combination (NPC
test), that provides effective solutions for problems of
multidimensional hypothesis testing within nonparamet-
ric permutations, and is used to test multidimensional
hypotheses which are too complex to manage paramet-
Consequently, we conducted a comparative nonparam-
etric analysis of audiometric responses among the three
groups for each layer and all frequencies, using the NPC
test. The results obtained, showing that the null hypothe-
sis is not verified for both partials and combined test, pr-
ove that relating to cigarettes smoking the three groups
are significantly different.
The test results highlighted that the three groups are
different for all the frequencies and all the layers (p =
But are the results attributable to the Ra values for all
the frequencies of the three groups, or are just some of th-
ese, and only for some frequencies, the cause of the sig-
nificant differences between non-smokers and more or
less heavy smokers?
We thus performed comparisons in pairs of the Ra
values between the groups of subjects, by layer and for
all the frequencies.
The hypothesis for the comparison between one group
(X) and another (Y), homogeneous in terms of age and
length of exposure, is as follows:
0( ):( ()()
500 4000
iFr aa
RGrX RGrY with j
As far as regards the comparison between non-smok-
ers and smokers, the test showed that the Ra values in the
two groups were not differentiated for the frequency of
500 Hz from the fourth layer of the risk index upwards
(average length of exposure of 17 years), while for the
frequencies 1000 and 2000 Hz from the eighth layer up-
wards (average length of exposure of 27 years) (Table
Table 5. Ir distribution percentiles.
Ir Values
Minimum Maximum
10° 1,519444444 2,231944444
20° 2,240277778 2,634027778
30° 2,670833333 3,002777778
40° 3,009027778 3,279166667
50° 3,289583333 3,472222222
60° 3,545833333 3,684722222
70° 3,69375 3,941666667
80° 3,945833333 4,119444444
90° 4,133333333 4,323611111
100° 4,340277778 4,728472222
Table 6. Results of the comparison between non-smokers and smokers.
Audiometric Responses
500 Hz 1000 Hz 2000 Hz 3000 Hz 4000 Hz T.C.
Ir1 0.000 0.000 0.000 0.000 0.000 0.000
Ir2 0.000 0.004 0.000 0.000 0.000 0.000
Ir3 0.014 0.001 0.000 0.000 0.000 0.000
Ir4 0,343055556 0.000 0.000 0.000 0.000 0.000
Ir5 0,3125 0.000 0.000 0.000 0.000 0.000
Ir6 0,421527778 0.003 0.000 0.000 0.000 0.000
Ir7 0.069 0.000 0.005 0.000 0.000 0.000
Ir8 0,236111111 0,119444444 0.098 0.002 0.000 0.003
Ir9 0,229861111 0.067 0,072917 0.000 0.000 0.000
Ir10 0,141666667 0,122916667 0,266667 0.020 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000
Abbate C. et al. / Health 2 (2010) 1163-1169
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The data obtained from the sample under study demonst-
rated that cigarette smoking interferes with the onset and
development of hearing loss caused by industrial noise.
The results of the statistical study applied to the audio-
metric responses displayed statistically significant differ-
ences between non-smokers, smokers and heavy smok-
This demonstrates that smoking has an influence on
noise-induced hearing loss and that this effect is corre-
lated to the quantity of cigarettes smoked daily.
The theoretical model applied for each frequency on
the distribution trend of the values of Ra highlighted that,
with increased age and length of service, the audiometric
responses for all frequencies increase in all three groups,
albeit in a differentiated manner.
Furthermore, the ANCOVA(Analysis of Covariance)
results show that the trends of the Ra values for the three
groups may not be described using a model with the sa-
me parameters.
The results of the non-parametric analysis demonstr-
ated that the three groups examined are differentiated, in
relation to the audiometric responses for all the frequen-
cies and for each layer.
In particular it was found that the risk factor influen-
ces all frequencies, and especially those at the higher end
of the spectrum.
These observations are in accordance with the findings
of Mizoue et al. [8] who, in a study on 4624 steel work-
ers exposed to noise, highlighted an increase in noise-
induced damage mainly at high frequencies, in relation to
the quantity of cigarettes smoked.
Our result agree with Wild’s ones [15] that showed
noise-inducted hypoacusis increase at 3000-4000 Hz, in
a group of long time smokers compared with no smokers
with similar occupational history.
Our data show effects at low frequencies, not found by
Mizoue et al. [8], and this observation is due to the dif-
ferent sensitivity of the statistical techniques used, and in
particular in the use of the NPC test.
Regarding the comparison between smokers and hea-
vy smokers, the statistical study, which highlighted sign-
ificantly different behaviour for all the frequencies, con-
firmed, as reported by the studies of Nakanishi et al. [16]
and Mizoue et al. [8], that the effects of cigarette smok-
ing have an effect on noise-induced hearing loss which
depends on the quantity of cigarettes smoked per day.
The pathogenetic mechanisms involved may be identi-
fied as:
1) the ototoxic effect performed by nicotine, which
stimulates the nicotine receptors of the acoustic cells as
described by Evans [17] and by Blachet et al. [18].
2) the mechanisms correlated to ischaemic damage
caused by decreased blood flow. In fact, the physiopath-
ology of hearing loss involves a reduction in cochlear
blood flow and gaseous exchange, and contemporaneous
increased levels of circulating CO caused by chronic ex-
posure to cigarette smoking further reduces the quantity
of oxygen to the cochlear cells, thus contributing to sen-
sory neural damage. This hypothesis, suggested by Mat-
schke [19] in acute noise-induced damage, was subse-
quently confirmed by the studies of Fechter et al. [20-22],
Rao et al. [23] and Shahbaz Hassan et al. [24] for chro-
nic noise-induced damage. Rao et al. [23], in an experi-
mental study, highlighted that the simultaneous exposure
to noise and CO increases noise-induced hearing loss.
Fechter et al. [22], in an experimental study on labora-
tory animals, demonstrates that CO increases noise-in-
duced hearing loss. Shahbaz Hassan et al. [24] reaches
the same conclusions, claiming that CO increases noise-
induced hearing loss.
Our data confirm the aforementioned hypotheses also in
conditions of chronic exposure.
In conclusion, the observations deriving from the
study show that cigarette smoking acts in synergy with
exposure to industrial noise on hearing loss, and that this
effect is correlated to the amount of cigarettes smoked.
Thus, we feel it is necessary to encourage workers occ-
upationally exposed to high levels of noise to limit ciga-
rette smoking.
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