Open Access

The association between long working hours and hearing impairment in noise unexposed workers: data from the 5th Korea National Health and Nutrition Examination Survey (KNHANES 2010–2012)

  • Jung-Woo Park1,
  • Jin-Soo Park1,
  • Seyoung Kim1,
  • Minkyu Park1,
  • Hyunrim Choi1, 2 and
  • Sinye Lim1, 2Email author
Annals of Occupational and Environmental MedicineThe official journal of the Korean Society of Occupational and Environmental Medicine201628:55

DOI: 10.1186/s40557-016-0140-1

Received: 22 April 2016

Accepted: 22 September 2016

Published: 6 October 2016

Abstract

Background

This study is aimed at finding out the relationship between long working hours, one of major job stress elements, and hearing impairment in unexposed workers to occupational and environmental noise.

Methods

This study was performed on 1628 regular, full-time wage workers between the age of 25-64 who indicated in the survey of having no experience of exposure to noise, normal otoscopic findings, and not suffering from diabetes based on the data from the fifth Korea National Health and Nutrition Examination Survey (KNHANES 2010–2012). The average working hours per week was categorized into 40 h and lower group, more than 40 to 48 h group, more than 48 to 60 h group, and more than 60 h group. The groups were defined as suffering from low or high frequencies hearing impairment if the average hearing threshold for 0.5, 1, 2 kHz or 3, 4, 6 kHz in both ears exceeds 25 dB based on the pure tone audiometry. The association between average weekly working hours and hearing impairment was analyzed using logistic regression after gender stratification.

Results

The prevalences of low and high frequencies hearing impairment in male workers were 4.3 and 28.6 %, respectively, which were much higher than female’s prevalence of 2.7 and 11.1 %. For male workers, no significant association was found between average weekly working hours and low and high frequencies hearing impairment. For female workers, odds ratios (OR) of low and high frequencies hearing impairment were 4.22 (95 % confidence interval (CI) 1.09–16.27) and 4.49 (95 % CI 1.73–11.67), respectively, after controlling for several related factors, such as, age, Body Mass Index (BMI), socio-economic status, health-related behavioral, and occupational characteristics variables, in the final model in the group working more than 60 h compared to the group working 40 h and lower. In addition, a dose-response relationship was observed that ORs of low and high frequencies hearing impairment were increased according to increasing average weekly working hours.

Conclusions

The association between long working hours and hearing impairment in both low and high frequencies was significant in Korean female workers with a dose-response relationship. Therefore, the law to change the culture of long working hours should be enacted in order to protect the workers’ health and improve the quality of life in Korean workers.

Keywords

Long working hours Hearing impairment KNHANES

Background

The International Labor Organization (ILO) announced the first agreement limiting daily working hours to 8 h and weekly working hours to 48 h for the manufacturing sector in 1919. Around 100 years have passed since then, and the statutory working hours have decreased gradually with many countries currently limiting it to 40 h per week [1]. However, there is a difference in the actual working hours by country with many developing countries still showing long working hours compared to developed countries due to reasons of low hourly wage, non-existence of a labor union, and insufficient labor market management capacity [2]. In the case of Korea, despite the fact that it has been industrialized as a typical country which has East Asia’s distinctive ‘long working hour culture’ [2], the characteristic of long working hours still exists, and it held the second-highest record for long working hours among the Organisation for Economic Co-operation and Development (OECD) countries in 2014 [3].

The results of previous studies suggested that long working hours have had influence in various fields. In the short term, long working hours increase fatigue through growing job demands, interference with life outside work, and shortening sleep time and cause negative health behaviors, such as, smoking and alcohol abuse [4]. These results increase the occurrence of accidents in workplace [5], mental illnesses [6], and cerebro-cardiovascular diseases [7] on a personal level and lead to social losses, such as, declining productivity [8] and frequent absences [9] in the long term.

Meanwhile, hearing impairment creates problems, such as, difficulty in formation of relationships, social isolation, and limited career choices and it has become an important social problem that causes mental illness like depression [10]. Increasing age, history of ear diseases, diabetes, and smoking are common causes of hearing impairment which lead to various problems mentioned above in the general population while the major cause is exposure to occupational noise in the working population [1113].

In addition, some studies presented the association between stress and hearing problems. In a study conducted on symphony orchestra musicians occupationally exposed to loud noise frequently, it has been observed that there is a significant correlation between stress-related symptoms and hearing problems, with most hearing problems starting off gradually after a stressful life event [14]. Meanwhile, another study analyzed the impact of stress on hearing in workers unexposed to noise. A study analyzing the Swedish Longitudinal Occupational Survey of Health (SLOSH) data in 2008 reported that increase in stress, such as, change of occupation or risk of dismissal raised the prevalence of hearing impairment or tinnitus [15]. A case-control study conducted in Germany showed that patients with sudden hearing impairment and acute tinnitus symptoms even without being exposed to loud noise had a significantly higher level of stress compared to the control group, suggesting that stress can be considered a significant risk factor in occurrence of these diseases [16]. Based on these previous studies, the idea that stress can cause or aggravate hearing impairment was proposed [17].

However, most previous studies did not differentiate hearing impairment and tinnitus or hyperacusis, based on a self-reported survey regarding hearing impairment, and not excluding well-known hearing impairment related factors. Therefore, this study is aimed at revealing the association between one of major stress elements, long working hours, and hearing impairment by using the data from the fifth Korea National Health and Nutrition Examination Survey (KNHANES) and analyzing the working hours which have not been presented as the cause of hearing impairment until now, although being one of the most important stress factors in the occupational health field [18].

Methods

Study participants

The KNHANES is a study conducted on Koreans nationwide by the Korea Centers for Disease Control and Prevention with the first survey conducted in 1998 and the sixth survey currently in progress. The data from the fifth KNHANES carried out from 2010 to 2012 was used in this study. The survey was constructed with independency and homogeneity through the introduction of the Rolling Sampling Survey in each survey year. In the fifth KNHANES, 192 sampling areas were chosen each year representing Koreans and all members of the 3800 households were surveyed, therefore, 11,400 households from a total of 576 areas surveyed in 3 years.

This study was performed on regular, full-time wage workers between the age of 25–64 among the total study participants of the fifth KNHANES. Among them, 1815 workers unexposed to noise who answered ‘no’ to ‘have experience using earphones at a noisy place’, ‘have experience being exposed to noise at workplace’, and ‘have experience being exposed to instantaneous noise’, and also have been diagnosed normal for both ears in otoscopic examination conducted by a otolaryngologist using 4 mm degree endoscope were chosen. The final study population was determined to 1628 study participants by excluding workers diagnosed with diabetes to rule out the impact of diabetes on hearing impairment [19, 20], soldiers with possible frequent exposure to firing noise, and participants with missing question entry in each variable.

Long working hours

The International Labor Organization (ILO) stated that working more than 48 h a week is considered a major job stress and that the occurrence of cerebro-cardiovascular diseases are highly associated with working hours exceeding 60 h per week [21]. Therefore, it was advised to avoid working more than 48 h per week and best not to exceed 40 h per week. Many countries have already limited the statutory working hours to 40 h per week [1], while paragraph 1 of Article 50 of the Korean Labor Standards Act of Korea also states that working hours should not exceed 40 h per week excluding recess hours [22].

Based on these standards, this study made evaluations by using the value of the response to the question ‘how many hours do you work per week on average at work place including overtime and night overtime, excluding lunch hours?’ and classifying them into group working 40 h and lower, group working more than 40 to 48 h, group working more than 48 to 60 h, and group working more than 60 h.

Hearing impairment

To evaluate the hearing level of the study participants, a pure tone audiometry at 0.5, 1, 2, 3, 4, 6 kHz was conducted on both ears through the Entomed SA 203 in a double wall audiology booth. World Health Organization (WHO) had defined normal hearing as the average result recording below 25 dB at 0.5, 1, 2, 4 kHz for the good-ear side [23], and it is widely used as the standard in judging daily life auditory abilities. However, using such definition to judge the degree of hearing impairment will rule out unilateral hearing impairment and lead to the emergence of the problem of not being able to find out the pattern of hearing impairment. To resolve this problem, some studies have defined hearing impairment with the average hearing threshold in both ears [24], and analyzed the pattern of low and high frequencies hearing impairment [25]. Based on this information, this study defines the binaural pure-tone average of both ears at 0.5, 1, 2 kHz for low frequency and the binaural pure-tone average at 3, 4, 6 kHz for high frequency. In addition, the binaural pure-tone average of both ears for low frequency or high frequency exceeding 25 dB was judged as having hearing impairment.

Other variables

In this study, some related factors that can affect hearing impairment suggested by previous studies were included. Some studies showed relatively consistent results that cerebro-cardiovascular risk factors, such as obesity and smoking, have a negative effect on hearing [26, 27]. These results were considered to be due to the fact that cochlea was vulnerable to ischemic changes [28]. In a research relating to the socio-economic status, high prevalence of hearing impairment was observed in deprived families. This finding was explained by frequent prematurity and low birth weight in the lower socio-economic status [29], and a negative tendency for the noisy environment and a favor for wearing hearing protection aids in the higher socio-economic status individuals [30]. In addition, there was a limited evidence that healthy lifestyles, such as moderate exercise and moderate alcohol consumption, can help prevent hearing loss [31, 32].

The related factors were constructed as follows to consider socio-economic status, health-related behavior characteristics, and occupational characteristics of the study participants. The age was classified into units of 10 years with Body Mass Index (BMI) of less than 18.5 kg/m2 classified as underweight, BMI of 18.5–25 kg/m2 normal weight, and BMI of over 25 kg/m2 overweight. Socio-economic status included level of educational attainment, marital status, and household income. The level of educational attainment was classified into less than high school, graduated from high school, and graduated from junior college or higher educational level. The marital status was classified into single, married and living together, and others (separated, death of spouse, divorced). The household income was classified into four classes of low, middle-low, middle-high, and high in accordance with the monthly average equivalent household income (monthly household income divided by the square root of number of household members).

Health-related behavior characteristic variables include smoking, alcohol consumption, and exercise status. Smoking was classified into non-smoker for participants who have smoked less than 100 cigarettes in their lifetime, ex-smoker for those who smoked more than 100 cigarettes in their lifetime but currently not smoking, and current smoker for those currently smoking and have smoked more than 100 cigarettes in their lifetime. Alcohol consumption was classified into non-drinker for participants who did not drink at all in the past year, light drinker for participants drinking less than twice a week or drinking less than seven glasses per occasion for male (less than five glasses for female), and high-risk drinker for those drinking more than twice a week or drinking more than seven glasses per occasion for male (more than five glasses for female). The exercise status was classified into exercise group for participants having conducted intense physical activities more than 3 days a week and over 30 min per occasion resulting in experiencing body pain or breathing heavily than usual while those not applicable to such activities were classified as non-exercise group.

Occupational characteristic variables include job type and shift work status. The job type was classified mainly into non-manual jobs for ‘manager’, ‘specialist and related business employee’, ‘office worker’, and ‘service industry employee’ and manual jobs for ‘workers skilled in agriculture and fishery’, ‘technician or related skill employee’, ‘machine operating or assembly worker’, and ‘simple labor employee’. The shift work status was classified into day work group and shift work group for participants applicable to work pattern other than day shift (evening shift, night shift, day and night regular shift, 24-hour shift, split shift, irregular shift, and others).

Statistical analyses

The fifth KNHANES is designed with all Koreans living in Korea as the target population and it is a complex sampling design data extracted after conducting the initial area-stratification and then the secondary stratification of households within the area. In this study, analysis was carried out considering weight, stratified variables, and cluster variables so that the sample represents the population and prevents biased outcomes.

To examine the general characteristics of the study population, the frequency and the average of each independent variable were presented through stratification by gender while chi-square tests were conducted to compare the distribution and t-tests were conducted to figure out significant mean difference. Taking into consideration previous study outcomes showing significant health impacts of long working hours on female workers [3335], the association between the independent variables and hearing impairment was gender-stratified and then chi-square tests were conducted, and the results were presented by classifying it into low and high frequencies hearing impairment. To find out the degree of the association between long working hours and low and high frequencies hearing impairment by gender, logistic regression was applied to calculate odds ratio (OR). In the crude model, no adjustments were made while age, BMI, and socio-economic status variables were controlled in the second model, and health-related behavior characteristic variables and occupational characteristic variables were more controlled in the final model. SPSS v.19.0 was used for the statistical analyses and the significance level was set at p < 0.05.

Results

General characteristics of the study population

The general characteristics of the study population are presented in Table 1. Among all participants, male accounted for 53.7 % and female 47.3 %. The average age was 40.3 years for male and 39.6 years for female and the average age was slightly higher in male workers without statistical significance (p = 0.174). The proportion of educational attainment level of college or higher was significantly higher in male (p = 0.003) with the proportion of manual job in male at 31.0 % and higher than that of female of 16.8 % (p < 0.001). The proportion of shift work in female was slightly higher but not statistically significant (p = 0.239). The average working hours per week in male was 49.2 h, showing significantly longer than female’s 44.5 h (p < 0.001) while the percentage of group working more than 60 h in male was significantly higher than that in female, with male accounting for 12.6 % and female 7.2 % (p < 0.001).
Table 1

General characteristics of the study population

Variables

Total

 

Male

 

Female

 

p-value

na

nb(%c)

na

nb(%c)

na

nb(%c)

Total

1628

3780449(100.0)

768

2030862(100.0)

860

1749588(100.0)

 

Age (years)

 Mean ± SE

40.0 ± 0.3

 

40.3 ± 0.4

 

39.6 ± 0.4

 

0.174

 25–34

444

1246970(33.0)

165

610588(30.1)

279

636382(36.4)

0.069

 35–44

603

1368113(36.2)

311

791293(39.0)

292

576820(33.0)

 

 45–54

394

858442(22.7)

193

469842(23.1)

201

388600(22.2)

 55–64

187

306924(8.1)

99

159138(7.8)

88

147786(8.4)

BMI (kg/m2)

 Underweight

72

153504(4.1)

8

20560(1.0)

64

132944(7.6)

<0.001

 Normal

1092

2480000(65.6)

454

1190804(58.6)

638

1289196(73.7)

 

 Obese

464

1146946(30.3)

306

819498(40.4)

158

327448(18.7)

Education

  ≤ Middle school

170

362359(9.6)

58

151184(7.4)

112

211175(12.1)

0.003

 High school

564

1427402(37.8)

252

725608(35.7)

312

701795(40.1)

 

  ≥ College

894

1990688(52.7)

458

1154070(56.8)

436

836618(47.8)

Marital status

 Never married

254

753440(19.9)

82

335275(16.5)

172

418165(23.9)

<0.001

 Married

1289

2817011(74.5)

672

1653806(81.4)

617

1163205(66.5)

 

 Others

85

209998(5.6)

14

41780(2.1)

71

168218(9.6)

Household income

 Low

56

162234(4.3)

19

73594(3.6)

37

88640(5.1)

0.017

 Mid-low

381

1008432(26.7)

207

621443(30.6)

174

386988(22.1)

 

 Mid-high

576

1368482(36.2)

271

720932(35.5)

305

647550(37.0)

 High

615

1241302(32.8)

271

614892(30.3)

344

626410(35.8)

Smoking

 Non-smoker

967

2044875(54.1)

181

478096(23.5)

786

1566780(89.6)

<0.001

 Ex-smoker

267

638628(16.9)

236

570841(28.1)

31

67787(3.9)

 

 Current smoker

394

1096946(29.0)

351

981925(48.4)

43

115022(6.6)

Alcohol

 None

269

549452(14.5)

80

212616(10.5)

189

336836(19.3)

<0.001

 Light drinker

1123

2586279(68.4)

500

1290078(63.5)

623

1296201(74.1)

 

 Heavy drinker

236

644718(17.1)

188

528167(26.0)

48

116551(6.7)

Exercise

 No

1335

3060829(81.0)

619

1602748(78.9)

716

1458080(83.3)

0.051

 Yes

293

719621(19.0)

149

428113(21.1)

144

291507(16.7)

 

Job type

 Non-manual

1278

2857188(75.6)

554

1401179(69.0)

724

1456009(83.2)

<0.001

 Manual

350

923262(24.4)

214

629683(31.0)

136

293579(16.8)

 

Shift work

 No

1373

3172611(83.9)

646

1730392(85.2)

727

1442219(82.4)

0.239

 Yes

255

607838(16.1)

122

300469(14.8)

133

307369(17.6)

 

Weekly working hours

 Mean ± SE

47.0 ± 0.3

49.2 ± 0.5

44.5 ± 0.5

<0.001

  ≤ 40

673

1460816(38.6)

243

625000(30.8)

430

835816(47.8)

<0.001

 40 < x ≤ 48

401

930976(24.6)

176

480684(23.7)

225

450292(25.7)

 

 48 < x ≤ 60

399

1007298(26.6)

248

669145(32.9)

151

338153(19.3)

  > 60

155

381360(10.1)

101

256032(12.6)

54

125328(7.2)

SE standard error

aunweighted count, bestimated population size, ccolumn and estimated percentage

Working hours by the characteristics of the study population

Average working hours per week according to the characteristics of study population are presented in Table 2. The largest percentage of the group working 40 h and lower was shown in the case of female, older age, higher educational level, high household income, non-smoker, non-drinker, non-manual job, and day work group. In contrast, the case of male, older age, lower educational level, manual job, and shift work showed the largest percentage of the group working more than 60 h. Notably, the oldest age group, 55–64 years, showed a bimodal distribution in working hours that the largest percentage was observed both in the group working 40 h and lower and more than 60 h. In addition, the proportion of current smoker and heavy drinker was the highest in the group working more than 60 h. There was no significant difference found in relation to BMI, marital status, and exercise.
Table 2

Baseline characteristics of study participants in relation to weekly working hours

Variables

Average working hours per week

p-value

≤40

40 < x ≤ 48

48 < x ≤ 60

>60

na

%b

na

%b

na

%b

na

%b

Sex

 Male

625000

30.8 %

480684

23.7 %

669145

32.9 %

256032

12.6 %

<0.001

 Female

835816

47.8 %

450292

25.7 %

338153

19.3 %

125328

7.2 %

 

Age (years)

 Mean ± SE

40.6 ± 0.4

39.1 ± 0.6

39.0 ± 0.6

42.3 ± 1.0

0.003

 25–34

434679

34.9 %

352466

28.3 %

352545

28.3 %

107280

8.6 %

0.021

 35–44

532509

38.9 %

306509

22.4 %

408269

29.8 %

120827

8.8 %

 

 45–54

353381

41.2 %

206971

24.1 %

196742

22.9 %

101348

11.8 %

 55–64

140247

45.7 %

65030

21.2 %

49742

16.2 %

51905

16.9 %

BMI (kg/m2)

 Underweight

66465

43.3 %

28302

18.4 %

54891

35.8 %

3845

2.5 %

0.118

 Normal

984258

39.7 %

589535

23.8 %

670664

27.0 %

235542

9.5 %

 

 Obese

410092

35.8 %

313138

27.3 %

281742

24.6 %

141973

12.4 %

Education

  ≤ Middle school

116233

32.1 %

77087

21.3 %

106274

29.3 %

62766

17.3 %

0.008

 High school

530333

37.2 %

342979

24.0 %

375414

26.3 %

178677

12.5 %

 

  ≥ College

814249

40.9 %

510911

25.7 %

525610

26.4 %

139917

7.0 %

Marital status

 Never married

268863

35.7 %

216956

28.8 %

192447

25.5 %

75174

10.0 %

0.681

 Married

1104046

39.2 %

655606

23.3 %

766179

27.2 %

291180

10.3 %

 

 Others

87907

41.9 %

58413

27.8 %

48671

23.2 %

15007

7.1 %

Household income

 Low

51287

31.6 %

31609

19.5 %

64473

39.7 %

14865

9.2 %

0.001

 Mid-low

313868

31.1 %

231306

22.9 %

315850

31.3 %

147408

14.6 %

 

 Mid-high

529608

38.7 %

334116

24.4 %

365995

26.7 %

138763

10.1 %

 High

566053

45.6 %

333944

26.9 %

260980

21.0 %

80325

6.5 %

Smoking

 Non-smoker

947579

46.3 %

533403

26.1 %

411757

20.1 %

152136

7.4 %

<0.001

 Ex-smoker

220452

34.5 %

144646

22.6 %

207975

32.6 %

65555

10.3 %

 

 Current smoker

292784

26.7 %

252927

23.1 %

387565

35.3 %

163670

14.9 %

Alcohol

 None

244192

44.4 %

143659

26.1 %

107894

19.6 %

53707

9.8 %

0.003

 Light drinker

1031733

39.9 %

634730

24.5 %

700198

27.1 %

219618

8.5 %

 

 Heavy drinker

184891

28.7 %

152587

23.7 %

199206

30.9 %

108035

16.8 %

Exercise

 No

1190610

38.9 %

728900

23.8 %

823902

26.9 %

317417

10.4 %

0.611

 Yes

270206

37.5 %

202076

28.1 %

183396

25.5 %

63943

8.9 %

 

Job type

 Non-manual

1237357

43.3 %

695717

24.3 %

695575

24.3 %

228538

8.0 %

<0.001

 Manual

223459

24.2 %

235258

25.5 %

311722

33.8 %

152822

16.6 %

 

Shift work

 No

1248109

39.3 %

809858

25.5 %

867887

27.4 %

246757

7.8 %

<0.001

 Yes

212706

35.0 %

121118

19.9 %

139411

22.9 %

134603

22.1 %

 

SE standard error

aestimated population size, brow and estimated percentage

Hearing impairment and its association with relevant variables

The prevalences of low and high frequencies hearing impairment for each independent variable was presented after gender-stratified analysis in Tables 3 and 4. The prevalences of low and high frequencies hearing impairment in male were 4.3 and 28.6 %, respectively, which are much higher than female’s prevalence of 2.7 and 11.1 %.
Table 3

Characteristics by hearing impairment in male subjects

Variables

Low frequency hearing threshold

High frequency hearing threshold

Normala

Impaireda

Rateb

p-valuec

Normala

Impaireda

Rateb

p-valuec

Total

1943952

86909

4.3 %

 

1450702

580160

28.6 %

 

Age

 25–34

601667

8921

1.5 %

0.003

536836

73752

12.1 %

< 0.001

 35–44

767129

24164

3.1 %

 

639708

151585

19.2 %

 

 45–54

433876

35966

7.7 %

 

228438

241405

51.4 %

 55–64

141281

17857

11.2 %

 

45720

113418

71.3 %

BMI (kg/m2)

 Underweight

20560

0

0.0 %

0.594

14802

5759

28.0 %

0.987

 Normal

1132208

58595

4.9 %

 

853128

337675

28.4 %

 

 Obese

791184

28314

3.5 %

 

582771

236726

28.9 %

Education

  ≤ Middle school

138168

13016

8.6 %

0.069

76552

74632

49.4 %

< 0.001

 High school

684015

41593

5.7 %

 

449823

275785

38.0 %

 

  ≥ College

1121769

32300

2.8 %

 

924326

229743

19.9 %

Marital status

 Never married

330788

4487

1.3 %

0.285

293642

41634

12.4 %

0.001

 Married

1571384

82422

5.0 %

 

1137760

516046

31.2 %

 

 Others

41780

0

0.0 %

 

19300

22480

53.8 %

Household income

 Low

72438

1156

1.6 %

0.868

41672

31921

43.4 %

0.503

 Mid-low

591940

29504

4.7 %

 

434735

186708

30.0 %

 

 Mid-high

690088

30844

4.3 %

 

522569

198364

27.5 %

 High

589487

25406

4.1 %

 

451726

163166

26.5 %

Smoking

 Non-smoker

464148

13948

2.9 %

0.391

373600

104496

21.9 %

0.085

 Ex-smoker

535904

34937

6.1 %

 

380557

190284

33.3 %

 

 Current smoker

943901

38024

3.9 %

 

696544

285380

29.1 %

Alcohol

 None

200508

12108

5.7 %

0.382

141176

71441

33.6 %

0.608

 Light drinker

1246716

43362

3.4 %

 

933381

356697

27.6 %

 

 Heavy drinker

496727

31440

6.0 %

 

376145

152022

28.8 %

Exercise

 No

1539723

63025

3.9 %

0.428

1173529

429219

26.8 %

0.081

 Yes

404229

23884

5.6 %

 

277173

150940

35.3 %

 

Occupation

 Non-manual

1356037

45141

3.2 %

0.060

1086389

314789

22.5 %

< 0.001

 Manual

587915

41768

6.6 %

 

364312

265371

42.1 %

 

Shift work

 No

1656145

74247

4.3 %

0.966

1268234

462159

26.7 %

0.012

 Yes

287807

12662

4.2 %

 

182468

118001

39.3 %

 

Weekly working hours

  ≤ 40

600759

24241

3.9 %

0.740

463403

161597

25.9 %

0.226

 40 < x ≤ 48

452960

27724

5.8 %

 

328092

152592

31.7 %

 

 48 < x ≤ 60

646323

22822

3.4 %

 

498059

171086

25.6 %

  > 60

243910

12122

4.7 %

 

161147

94885

37.1 %

aestimated population size

bprevalence rate

ctested by chi-square test

Table 4

Characteristics by hearing impairment in female subjects

Variables

Low frequency hearing threshold

High frequency hearing threshold

Normala

Impaireda

Rateb

p-valuec

Normala

Impaireda

Rateb

p-valuec

Total

1702929

46659

2.7 %

 

1555827

193761

11.1 %

 

Age

 25–34

630799

5583

0.9 %

< 0.001

631885

4497

0.7 %

< 0.001

 35–44

566561

10259

1.8 %

 

542400

34420

6.0 %

 

 45–54

374768

13832

3.6 %

 

300648

87951

22.6 %

 55–64

130801

16985

11.5 %

 

80894

66892

45.3 %

BMI (kg/m2)

 Underweight

129378

3565

2.7 %

0.119

126952

5992

4.5 %

0.292

 Normal

1247967

41229

3.2 %

 

1134145

155051

12.0 %

 

 Obese

325584

1864

0.6 %

 

294730

32718

10.0 %

Education

  ≤ Middle school

188166

23009

10.9 %

< 0.001

138642

72534

34.3 %

< 0.001

 High school

686690

15105

2.2 %

 

616569

85226

12.1 %

 

  ≥ College

828073

8545

1.0 %

 

800616

36002

4.3 %

Marital status

 Never married

414719

3446

0.8 %

0.125

416248

1916

0.5 %

< 0.001

 Married

1123927

39277

3.4 %

 

1002594

160611

13.8 %

 

 Others

164283

3936

2.3 %

 

136984

31234

18.6 %

Household income

 Low

86509

2131

2.4 %

0.985

76211

12429

14.0 %

0.901

 Mid-low

376350

10639

2.7 %

 

340629

46359

12.0 %

 

 Mid-high

628839

18711

2.9 %

 

581604

65946

10.2 %

 High

611231

15178

2.4 %

 

557382

69027

11.0 %

Smoking

 Non-smoker

1526154

40625

2.6 %

0.455

1399823

166956

10.7 %

0.482

 Ex-smoker

67787

0

0.0 %

 

61194

6593

9.7 %

 

 Current smoker

108988

6033

5.2 %

 

94810

20212

17.6 %

Alcohol

 None

320909

15928

4.7 %

0.190

283099

53737

16.0 %

0.044

 Light drinker

1269704

26496

2.0 %

 

1159958

136243

10.5 %

 

 Heavy drinker

112316

4235

3.6 %

 

112770

3781

3.2 %

Exercise

 No

1417873

40208

2.8 %

0.663

1293030

165051

11.3 %

0.664

 Yes

285056

6451

2.2 %

 

262797

28710

9.8 %

 

Occupation

 Non-manual

1432594

23414

1.6 %

< 0.001

1348346

107663

7.4 %

< 0.001

 Manual

270335

23244

7.9 %

 

207481

86098

29.3 %

 

Shift work

 No

1402762

39457

2.7 %

0.780

1301174

141045

9.8 %

0.041

 Yes

300167

7202

2.3 %

 

254653

52716

17.2 %

 

Weekly working hours

  ≤ 40

822475

13340

1.6 %

0.014

773741

62075

7.4 %

< 0.001

 40 < x ≤ 48

442782

7511

1.7 %

 

412838

37454

8.3 %

 

 48 < x ≤ 60

322857

15296

4.5 %

 

279331

58822

17.4 %

  > 60

114816

10512

8.4 %

 

89917

35410

28.3 %

aestimated population size

bprevalence rate

ctested by chi-square test

The results of the analysis conducted on the prevalences of hearing impairment according to independent variables in male showed that the prevalences of low and high frequencies hearing impairment increased by age (low frequency: p = 0.003, high frequency: p < 0.001) while the prevalence of high frequency hearing impairment was particularly high for low educational attainment (p < 0.001), others (separated, death of spouse, divorced) marital status (p < 0.001), manual job (p < 0.001), and shift work (p = 0.012). The prevalences of hearing impairment by average weekly working hours showed no significant difference in both low and high frequencies (low frequency: p = 0.740, high frequency: p = 0.226).

The prevalences of hearing impairment in female in both low and high frequencies increased by age (low frequency: p < 0.001, high frequency: p < 0.001), low educational attainment (low frequency: p < 0.001, high frequency: p < 0,001), and manual job (low frequency: p < 0.001, high frequency: p < 0.001). The characteristics showing any association with hearing impairment in only high frequency were non-drinkers (p = 0.044), others (separated, death of spouse, divorced) marital status (p < 0.001), and shift work (p = 0.041). The prevalences of hearing impairment by average weekly working hours in both low and high frequencies increased significantly as the average weekly working hours increased (low frequency: p = 0.014, high frequency: p < 0.001).

The association between working hours and hearing impairment

To find out the association between average weekly working hours and hearing impairment, logistic regression was applied based on the group working 40 h and lower after gender stratification and presented in Table 5. For male workers, ORs of low and high frequencies hearing impairment with increased working hours were not consistent and statistically insignificant in the crude model with no adjustments with related factors. On the other hand, in the final model after controlling for age, BMI, socio-economic status, health-related behavior characteristics, and occupational characteristic variables, the risk of low and high frequencies hearing impairment in the group working more than 40 to 48 h, group working more than 48 to 60 h, and group working more than 60 h increased compared to the group working 40 h and lower without statistical significance.
Table 5

Odds ratios (OR) and 95 % confidence intervals (CI) for hearing impairment by gender according to weekly working hours

Weekly working hours

Male

Female

Low frequency hearing impairment

High frequency hearing impairment

Low frequency hearing impairment

High frequency hearing impairment

Model 1a

  ≤ 40

1.00

1.00

1.00

1.00

 40 < x ≤ 48

1.52(0.52–4.39)

1.33(0.8–2.22)

1.05(0.35–3.14)

1.13(0.61–2.09)

 48 < x ≤ 60

0.88(0.30–2.56)

0.99(0.59–1.64)

2.92(0.85–10.06)

2.62(1.34–5.15)

  > 60

1.23(0.38–4.03)

1.69(0.96–2.97)

5.64(1.65–19.34)

4.91(2.06–11.68)

Model 2b

  ≤ 40

1.00

1.00

1.00

1.00

 40 < x ≤ 48

1.83(0.61–5.45)

1.77(0.99–3.18)

1.49(0.46–4.89)

1.44(0.74–2.78)

 48 < x ≤ 60

1.12(0.40–3.13)

1.45(0.84–2.49)

3.55(0.84–14.95)

3.84(1.82–8.1)

  > 60

1.13(0.36–3.55)

1.70(0.87–3.31)

4.24(1.05–17.14)

5.12(1.85–14.18)

Model 3c

  ≤ 40

1.00

1.00

1.00

1.00

 40 < x ≤ 48

1.79(0.65–4.98)

1.71(0.95–3.08)

1.22(0.36–4.13)

1.28(0.65–2.54)

 48 < x ≤ 60

1.10(0.44–2.77)

1.34(0.77–2.33)

2.93(0.54–15.74)

3.53(1.57–7.95)

  > 60

1.22(0.31–4.86)

1.61(0.80–3.22)

4.22(1.09–16.27)

4.49(1.73–11.67)

aModel 1 : crude model

bModel 2 : adjusted with age, BMI and socioeconomic status (education, marital status and household income)

cModel 3 : Model2 + health-related behavioral characteristics (smoking, alcohol intake and exercise) and occupational characteristics (job type, shift work)

For female workers, in the crude model without controlling for any related factors, ORs of both low and high frequencies hearing impairment showed a dose-response relationship with increasing average weekly working hours. In particular, OR of low frequency hearing impairment was significantly highest in the group working more than 60 h recording 5.64 (95 % confidence interval (CI) 1.65–19.34), while OR of high frequency hearing impairment for the group working more than 48 to 60 h was 2.62 (95 % CI 1.34–5.15) and that in the group working more than 60 h was 4.91 (95 % CI 2.06–11.68). Also, in the final model after controlling for all related factors, the dose-response relationship was maintained between average weekly working hours and hearing impairment and ORs of low and high frequencies hearing impairment in the group working more than 60 h was 4.22 (95 % CI 1.09–16.27) and 4.49 (95 % CI 1.73–11.67) with statistical significance.

Discussion

This study explored the risk of hearing impairment resulting from long working hours unexposed to occupational and environmental noise in Korean full-time wage workers based on the data from the fifth KNHANES. The risk of hearing impairment in female workers increased significantly in low and high frequencies while there was no significant result in male workers. Besides, a dose-response relationship was observed between average weekly working hours and the risk of low and high frequencies hearing impairment based on the group working 40 h and lower in female workers. The risk of hearing impairment significantly increased especially when the average weekly working hours exceeded 60 h in low frequency and exceeded 48 h in high frequency.

In the previous studies, the prevalence of hearing impairment was low in female workers [11] because the male workers are considered to be exposed more to noise than female workers in a working environment [36]. However, in this study, we explored the prevalence of hearing impairment in workers unexposed to occupational and environmental noise and the results still showed a low prevalence rate in female workers (male 28.6 % vs female 11.1 % in high frequency). The hearing protection effect of estrogen has been presented as the mechanism explaining this result. A large cohort study showed that elderly women have better hearing than elderly men and the protection effect of estrogen could be confirmed through study outcomes showing increased occurrence of hearing impairment in women with Tuner’s syndrome which prevent the production of estrogen due to ovarian dysgenesis [37].

Although the prevalence of hearing impairment was low in female workers in this study, the association between long working hours and hearing impairment was significantly high in female workers. These results are consistent with the outcomes of previous studies showing that the negative impact on health of long working hours is greater for female than male workers [38]. The gender difference could be explained by the possibility that their working conditions are differ due to difference of positions and job roles, although their occupation and working hours are the same. Even if their working conditions are the same, women could be exposed to more stress because of lower aerobic capacity and muscle force, gender segregation or relatively low wages [39]. Moreover, even if female workers are exposed to the same stress level, the impacts may be different by gender. Such difference between genders is supported by the evidence showing that male released stress quickly after work whereas the stress level in female during work was maintained even after work [40], because women performed more unpaid work for family demands, such as, housework and childcare compared to men. According to the time spent in unpaid work announced by OECD in 2015, women had 1.96 times more work than men on the average in OECD member countries, but in Korea, the figure recorded 5.05 times showing the highest concentration rate of unpaid work in women among the OECD member countries [41]. Through such results, it can be suggested that the impact on health caused by chronic cumulative stress can be more negative when working long hours in both paid and unpaid works for Korean female workers.

The mechanisms of long working hours raising the risk of hearing impairment can be explained by several aspects. First suggesting mechanism is the activation of the sympathetic nervous system caused by long working hours, changing and damaging the function of the cochlear blood flow [42]. The cochlea is vulnerable to ischemic changes because blood flow is supplied solely by the labyrinthine artery without the collateral circulation [43]. The function of the cochlea can be damaged if such ischemic changes occur in the stria vascularis of the external wall which plays an important role in maintaining cochlear homeostasis [28]. Animal test results show that the cochlear perilymphatic PO2 drops an average of 40 % when the cochlear blood flow is reduced up to 35 % and a significant hearing impairment occurs [44]. Also, the spiral modular artery branching off from the labyrinthine artery which provides blood flow to the external wall of the cochlea is rich in myofibril and locates along the sympathetic nervous system. This indicates that various internal and external factors constrict the blood vessels through sympathetic nerves and may cause ischemic changes to the external wall of the cochlea [45]. Juhn et al. reported that regular epinephrine injections had an impact on the cochlear homeostasis in an animal test using chinchillas and hearing impairment got worse in proportion to the total administration period [46]. Also, Horner et al. reported that the level of temporary hearing impairment caused by noise was reduced when a guinea pig was exposed to noise after removing the superior cervical ganglion, one of the main sympathetic nerves [47]. Through these study results, it is suggested that excessive sympathetic nerve acceleration may bring about changes in the cochlear homeostasis through ischemic changes, causing hearing impairment. In addition, hearing impairment caused by such ischemic changes can get worse due to high metabolic activity of cochlear hair cells [43].

Another mechanism of long working hours causing hearing impairment can be explained through oxidative stress. Oxidative stress is an element which can create pathophysiology of hearing impairment, damage the DNA, and have a negative impact on hearing impairment by damaging the cochlear hair cells through protein and lipid degradation and increased apoptosis [48]. There is a possibility that such oxidative stress which triggers hearing impairment can also be produced by long working hours. In a study conducted on hospital workers comparing the level of oxidative stress in blood before and after long working hours, it was confirmed that the level of oxidative stress after work increased significantly with an explanation that oxidative stress increase can be caused through continuous physical activity, mental stress, and anxiety or drowsiness [49]. Based on these, oxidative stress produced by long working hours can be suggested as having an impact on hearing impairment.

On the other hand, some animal studies present the outcome that short-term stress can show a hearing protection effect based on the explanation that glucocorticoid is produced through hypothalamic-pituitary-adrenal axis (HPA axis) and the glucocorticoid receptor (GR) which becomes activated as a result of this will start working by using heat shock proteins and antioxidants as mediators [50]. In a recent study on stress, the active process of environmental adaptation in response to such stress was defined as allostasis and it was explained that allostatic load is produced during this process [51]. Although this allostatic load can protect the body temporarily and help in adaption, it has a chance of causing diseases as pathophysiological changes occur with long-term existence. Previous studies have already found that long hours of GR activation resulting from stress may bring about negative changes in the central nervous system, such as, the prefrontal cortex [52, 53] and this change in the central nervous system will disturb the central auditory processing and interpretation, causing a negative effect on hearing. Therefore, there is a limitation to prove the hearing protection effect of stress with just the studies analyzing the effects of short-term stress.

In this study, the association between long working hours and hearing impairment was observed significantly in low frequency as well as in high frequency. Considering that hearing impairment by the major causes, such as age increase and noise exposure, was mainly observed in high frequency, it can be suggested that another pathological mechanism of hearing impairment may exist which is different from the mechanism of hearing impairment resulting from age increase or noise exposure. In a previous study, authors classified presbycusis as sensory, neural, strial, and cochlear conductive types according to pathogenesis. They reported that strial type was characterized by flat loss on pure tone audiometry and associated with ischemic changes of stria vascularis supplying the cochlea [54]. Especially, because this strial capillary network exists abundantly at the base of the cochlea rather than the apex, the apex of cochlea is relatively vulnerable to ischemic changes than the base. Therefore, this distribution of blood flow results in hearing impairment caused by ischemic changes typically present not only in high frequency but also in low frequency [55]. This supports that well-known cerebro-cardiovascular risk factors, such as smoking and diabetes, may cause hearing impairment across the entire frequency [12]. Like the cerebro-cardiovascular risk factors, long working hours is also believed to bring about ischemic changes through hyperactivity of sympathetic nervous system, causing hearing impairment in low frequency as well as high frequency through a similar pathological mechanism.

Although this study presents that long working hours may cause hearing impairment, another Korean study analyzing the association between stress and hearing impairment reported that there was no significant difference in the level of stress and hearing [56]. However, the study population of this study was college students who visited the hospital for a physical examination, showing limitation in judging the effect of exposure to chronic stress in the working environment because there was the problem of the overall stress level of the study participants being low. On the other hand, a Swedish study analyzing the association among job stress, long-term stress, and hearing impairment through the SLOSH data presented that the hearing problem increased significantly with increased stress with a dose-response relationship and the result was consistent with this study [15].

As far as we know, this study is the first study to explore the association between long working hours and hearing impairment in noise unexposed workers. This study secures representativeness and credibility using the data from the fifth KNHANES, performing hearing test and interviewing by trained researchers. This study aimed to reveal the association between long working hours and hearing impairment after controlling several related factors, such as, age, BMI, socio-economic status, health-related behavioral, and occupational characteristics, excluding not only noise exposure in the working area but also the possibility of noise exposure in everyday life, such as, the use of earphones at noisy places. Nevertheless, this study had some limitations as follows. Firstly, there was the limitation of not being able to include the past work history of the study population. Secondly, information bias may exist because the study relied on the self-reported survey instead of not measuring the actual level of noise exposure. Furthermore, study participants could not recall the whole exposure history to noise in their lifetime. Therefore, there may be a possibility that the association between long working hours and hearing impairment in this study has been biased. Thirdly, this study did not include all of the factors that could lead to hearing impairment like the histories of congenital diseases, middle ear diseases and exposures to physical trauma, medication, and toxic substances because these information was not surveyed in the original dataset, KNHANES. Fourthly, this study could not confirm the causal relationship that long working hours may cause hearing impairment because this study has a cross-sectional design.

In order to overcome the limitations of this study, a cohort study can be performed on selected workers unexposed to occupational and environmental noise through not only thorough history taking of work history, past medical history, exposures to noise, physical trauma, medication, and toxic substances, but also noise measurement of the working places and other additional tests to exclude middle ear diseases.

Conclusions

The association between long working hours and hearing impairment in both low and high frequencies was significant in Korean female workers with a dose-response relationship. The findings of this study may add some evidence to the body of knowledge of the risk of long working hours, one of well-known risk factors of health. Therefore, the law to change the culture of long working hours should be enacted in order to protect the workers’ health and improve the quality of life in Korean workers.

Abbreviations

BMI: 

Body mass index

CI: 

Confidence interval

GR: 

Glucocorticoid receptor

HPA: 

Hypothalamic-pituitary-adrenal axis

ILO: 

International labor organization

KNHANES: 

Korea National Health and Nutrition Examination Survey

OECD: 

Organization for economic cooperation and development

OR: 

Odds ratio

SLOSH: 

Swedish longitudinal occupational survey of health

WHO: 

World Health Organization

Declarations

Acknowledgements

There is no conflict of interest or financial support to declare.

Availability of data and material

The data of the KNHANES V is opened to the public, therefore, any researcher can be obtained after request from the website https://knhanes.cdc.go.kr/knhanes/eng/index.do.

Funding

Not applicable.

Authors’ contributions

JWP designed this study and wrote a draft of this manuscript. JSP, SK, and MP analyzed the data, interpreted the results, and gave some comments about the manuscript. HC did technical supports. SL did critical revision of this manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

This study used the open data of the Fifth Korea National Health and Nutrition Examination Survey (KNHANES V), 2010–2012, Korea Centers for Disease Control and Prevention (KCDC). All study participants of the KNHANES V agreed to participate the survey and signed a consent. The KNHANES V has been approved by the Institutional Review Board (IRB) of the KCDC. The approval number of first year (2010) is 2010-02CON-21-C, 2011-02CON-06-C in second year (2011), and 2012-01EXP-01-2C in third year (2012).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Occupational and Environmental Medicine, Kyung Hee University Hospital
(2)
Department of Occupational and Environmental Medicine, School of Medicine Kyung Hee University

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