# The Status of Occupational Burnout and Its Influence on the Psychological Health of Factory Workers and Miners in Wulumuqi, China

Authors: Yaoqin Lu; Zhe Zhang; Sunyujie Gao; Huan Yan; Lijiang Zhang; Jiwen Liu
Journal: BioMed Research International
 (2020)

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## Abstract

The purpose of this study was to investigate the status of occupational burnout and its influence on the psychological health of factory workers and miners, in order to provide theoretical basis and reference for alleviating occupational burnout and promoting psychological health. The cross-sectional study investigated 6130 factory workers and miners with online questionnaire; the Chinese Maslach Burnout Inventory (CMBI) and Symptom Check List-90 (SCL-90) were used. In total, 6120 valid questionnaires were collected; effectiveness was 99.8%. The percentage of the factory workers and miners suffering from occupational burnout was 85.98% and psychological health problems was 38.27%. A statistically significant difference was observed in relation to the prevalence of occupational burnout among factory workers and miners of different sex, education level, labor contracts, work schedule, monthly incomes, weight, hypertension, age, working years, working hours per day, working hours per week, coal dust, silica dust, asbestos dust, benzene, lead, and noise. The detection rate of psychological health was higher for males than females. The detection rate of psychological health was higher for working days per week less than 5 days than more than 5 days. The detection rate of psychological health with high school education, senior professional title, night shift, divorced, monthly income less than 3000 yuan, weight more than 75 kg, age more than 45 years, and working years between 25 and 30 years was higher than that of the other groups. The results showed that sex, education level, professional title, work schedule, monthly income, hypertension, age, working years, asbestos dust, benzene, and occupational burnout affected psychological health among factory workers and miners. Factory workers and miners had high levels of occupational burnout, and occupational burnout was a risk factor that can lead to psychological health.


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## Body

## 1. Introduction

Occupational burnout refers to physical or mental exhaustion caused by overwork or stress [1]; it also can be described as a psychological syndrome characterized by exhaustion, cynicism, depersonalization, and reduced professional efficacy [2]. With the development of society and the increase of life pressure, people bear more and more pressure from society, work, and life. Occupational burnout has been regarded the crisis and illness in modern society and life.Occupational stress, lifestyle, and personal relaxation have been shown to contribute to the development of occupational burnout and cause a series of psychological problems [3–5]. Previous literature review of studies in different occupational groups has indicated that classic risk factors such as high demands, low job control, high job strain, low reward, and job insecurity increased the risk for developing burnout [6]. Several studies have showed the effects of occupational burnout on psychological health, such as neurasthenia, anxiety disorder, and depression [7, 8]. But other surveys did not find the correlation between occupational burnout and psychological health [9, 10]. Thus, the relationship of occupational burnout and mental health needs to be further explored.Factory workers and miners belong to a special occupational group who work in high-tension conditions, and a demanding work environment with dust, chemical factors, physical factors, and biological factors can detrimentally affect employees’ psychological health, leading to job stress and burnout [11]. There is a lack of research about the association between occupational burnout and individual characteristics or occupational hazards of factory workers and miners. Therefore, this study administered a questionnaire survey to factory workers and miners in Wulumuqi, China, to investigate the status of occupational burnout and its influence on psychological health, in order to provide theoretical basis and reference for alleviating occupational burnout and promoting psychological health.


## 2. Materials and Methods

### 2.1. Participants

This survey was carried out from January to May 2019. Workers on the occupational exposures of coal dust, silica dust, asbestos dust, benzene, lead, noise, and Brucella in factories and mines in Urumqi, China, were investigated. A total of 6500 factory workers and miners were initially selected using a cluster sampling method. Participants without the occupational exposures according to their working environment were excluded. Those with work experience less than one year or taking psychoactive drugs were also excluded. According to the inclusion and exclusion criteria, 6130 participants were included in this survey. The cross-sectional study was conducted by online questionnaire using a mobile phone. The respondents volunteered to participate in the survey, and the written informed consent was provided. Finally, 6120 questionnaires were collected and 10 copies of continuous answer questionnaires were excluded. The effectiveness was 99.8%.


### 2.2. Chinese Maslach Burnout Inventory (CMBI)

The Chinese Maslach Burnout Inventory (CMBI) was established by Li Yongxin which was based on Maslach Burnout Inventory (MBI). The Cronbachα for the CMBI was 0.88, split-half reliability coefficient was 0.84, and KMO was 0.91, respectively. The CMBI consisted of 15 items about three dimensions: emotional exhaustion, depersonalization, and reduced personal accomplishment; subjects responded to each item ranging from 1 (completely fitting) to 7 (completely unfitting). According to the critical values (emotionalexhaustion≥25, depersonalization≥11, and reducedpersonalaccomplishment≥16), occupational burnout was divided into four levels: none (subjects’ scores on three factors were lower than the critical value), mild (subjects’ scores on any one factor were equal to or higher than the critical value), moderate (subjects’ scores on any two factors were equal to or higher than the critical value), and severe (subjects’ scores on three factors were equal to or higher than the critical value) [12–15].


### 2.3. Symptom Check List-90 (SCL-90)

The Symptom Check List-90 (SCL-90) was established by L.R. Derogatis in 1975 and widely used in psychiatric outpatient examination because of its high authenticity in evaluating various mental health surveys [16, 17]. The Cronbach α for the SCL-90 was 0.99, split-half reliability coefficient was 0.98, and KMO was 0.99, respectively. There were 9 dimensions (including 90 items) in SCL-90, and each item was assigned a score ranging from 1 (not have) to 5 (serious). The 9 dimensions were somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, phobia, paranoid ideation, and psychosis. The higher score showed a worse psychological symptom. The result was positive, and further examination was needed, when the total score was more than 160, or any item score was more than 2, or the number of positive items was more than 43 [18].


### 2.4. Quality Control

All the investigators were trained before the survey. In order to ensure the completeness of the online questionnaire, each item was set as required. If there was any missing value, the questionnaire cannot be submitted. The validity analysis of the data was completed by senior data analysts.We facilitated the preinvestigation before the formal investigate, in order to train investigators and foster cooperation. We contacted face-to-face interviews with each participant to complete the online questionnaire and solve their concerns timely.


### 2.5. Statistical Methods

The results were analyzed by R software (Version: 3.5.2). A chi-squared test was used for the counting data; multiple logistic regression analysis was used to estimate the relationship between multiple factors. The significance level (α) was set at 0.05.


## 2.1. Participants

This survey was carried out from January to May 2019. Workers on the occupational exposures of coal dust, silica dust, asbestos dust, benzene, lead, noise, and Brucella in factories and mines in Urumqi, China, were investigated. A total of 6500 factory workers and miners were initially selected using a cluster sampling method. Participants without the occupational exposures according to their working environment were excluded. Those with work experience less than one year or taking psychoactive drugs were also excluded. According to the inclusion and exclusion criteria, 6130 participants were included in this survey. The cross-sectional study was conducted by online questionnaire using a mobile phone. The respondents volunteered to participate in the survey, and the written informed consent was provided. Finally, 6120 questionnaires were collected and 10 copies of continuous answer questionnaires were excluded. The effectiveness was 99.8%.


## 2.2. Chinese Maslach Burnout Inventory (CMBI)

The Chinese Maslach Burnout Inventory (CMBI) was established by Li Yongxin which was based on Maslach Burnout Inventory (MBI). The Cronbachα for the CMBI was 0.88, split-half reliability coefficient was 0.84, and KMO was 0.91, respectively. The CMBI consisted of 15 items about three dimensions: emotional exhaustion, depersonalization, and reduced personal accomplishment; subjects responded to each item ranging from 1 (completely fitting) to 7 (completely unfitting). According to the critical values (emotionalexhaustion≥25, depersonalization≥11, and reducedpersonalaccomplishment≥16), occupational burnout was divided into four levels: none (subjects’ scores on three factors were lower than the critical value), mild (subjects’ scores on any one factor were equal to or higher than the critical value), moderate (subjects’ scores on any two factors were equal to or higher than the critical value), and severe (subjects’ scores on three factors were equal to or higher than the critical value) [12–15].


## 2.3. Symptom Check List-90 (SCL-90)

The Symptom Check List-90 (SCL-90) was established by L.R. Derogatis in 1975 and widely used in psychiatric outpatient examination because of its high authenticity in evaluating various mental health surveys [16, 17]. The Cronbach α for the SCL-90 was 0.99, split-half reliability coefficient was 0.98, and KMO was 0.99, respectively. There were 9 dimensions (including 90 items) in SCL-90, and each item was assigned a score ranging from 1 (not have) to 5 (serious). The 9 dimensions were somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, phobia, paranoid ideation, and psychosis. The higher score showed a worse psychological symptom. The result was positive, and further examination was needed, when the total score was more than 160, or any item score was more than 2, or the number of positive items was more than 43 [18].


## 2.4. Quality Control

All the investigators were trained before the survey. In order to ensure the completeness of the online questionnaire, each item was set as required. If there was any missing value, the questionnaire cannot be submitted. The validity analysis of the data was completed by senior data analysts.We facilitated the preinvestigation before the formal investigate, in order to train investigators and foster cooperation. We contacted face-to-face interviews with each participant to complete the online questionnaire and solve their concerns timely.


## 2.5. Statistical Methods

The results were analyzed by R software (Version: 3.5.2). A chi-squared test was used for the counting data; multiple logistic regression analysis was used to estimate the relationship between multiple factors. The significance level (α) was set at 0.05.


## 3. Results

### 3.1. General Demographic Characteristics of Factory Workers and Miners

Among the 6120 workers and miners, 4017 were men (65.64%) and 2103 were women (34.36%); 1220 had hypertension (19.93%) and 364 had diabetes (5.95%). Exposure to coal dust, silica dust, asbestos dust, benzene dust, lead, noise, and brucellosis accounted for 1446 (23.63%), 622 (10.16%), 935 (15.28%), 1947 (31.81%), 353 (5.77%), 4545 (74.26%), and 108 (1.76%), respectively (Table1).Table 1
Characteristics of the factory workers and miners.
Items
Groups
Case number
Percentage (%)
Sex
Male
4017
65.64
Female
2103
34.36
Ethnicity
Han
5016
81.96
Other
1104
18.04
Education level
Junior high school and below
652
10.65
High school
1227
20.05
Junior college
2722
44.48
Bachelor’s degree or above
1519
24.82
Labor contracts
Signed
5896
96.34
Unsigned
224
3.66
Professional title
No
2349
38.38
Primary
1326
21.67
Middle
1483
24.23
Senior
962
15.72
Work schedule
Day shift
3289
53.74
Night shift
201
3.28
Shift
1897
31.00
Day and night shifts
733
11.98
Marital status
Unmarried
857
14.00
Married
4864
79.48
Divorced
357
5.83
Widowed
42
0.69
Monthly income (yuan)
<3000
1656
27.06
3000~
2093
34.20
4000~
1329
21.72
5000~
659
10.77
6000~
205
3.35
7000~
86
1.41
8000~
92
1.50
Weight (kg)
<55
840
13.73
55~
1571
25.67
65~
1780
29.08
75~
1929
31.52
Chronic disease
Diabetes
364
5.95
Hypertension
1220
19.93
Age (years)
<25
319
5.21
25~
634
10.36
30~
790
12.91
35~
704
11.50
40~
723
11.81
45~
2950
48.20
Working years (years)
~5
920
15.03
5~
831
13.58
10~
840
13.73
15~
319
5.21
20~
695
11.36
25~
1266
20.69
30~
1249
20.41
Working hours per day (hours)
≤7
975
15.93
>7
5145
84.07
Working days per week (days)
≤5
4006
65.46
>5
2114
34.54
Occupational hazard factors
Coal dust
1446
23.63
Silica dust
622
10.16
Asbestos dust
935
15.28
Benzene
1947
31.81
Lead
353
5.77
Noise
4545
74.26
Brucellosis
108
1.76


### 3.2. Comparison of Occupational Burnout Levels in Different Populations

The survey results showed that 85.98% of workers and miners experienced occupational burnout in varying degrees. There were statistically significant differences in sex (P<0.001), education level (P<0.001), labor contracts (P<0.001), work schedule (P<0.001), monthly incomes (P=0.019), weight (P<0.001), hypertension (P<0.001), age (P<0.001), working years (P<0.001), working hours per day (P<0.001), working hours per week (P=0.001), coal dust (P<0.001), silica dust (P<0.001), asbestos dust (P<0.001), benzene (P<0.001), lead (P=0.003), and noise (P<0.05) (Table 2).Table 2
Comparison of occupational burnout levels in different populations.
Items
Groups
CMBI
CMBI detection rate (%)
Chi-squared value
P value
No
Mild
Moderate
Severe
Sex
Male
548
1371
1699
399
0.86
24.078
<0.001
Female
310
831
785
177
0.85
Ethnicity
Han
700
1794
2042
480
0.86
1.274
0.735
Other
158
408
442
96
0.86
Education level
Junior high school and below
68
346
209
29
0.90
121.637
<0.001
High school
144
433
519
131
0.88
Junior college
386
926
1162
248
0.86
Bachelor’s degree or above
260
497
594
168
0.83
Labor contracts
Signed
839
2069
2417
571
0.86
59.719
<0.001
Unsigned
19
133
67
5
0.86
Professional title
No
334
868
934
213
0.86
9.941
0.355
Primary
183
488
540
115
0.85
Middle
201
507
610
165
0.86
Senior
140
339
400
83
0.86
Work schedule
Day shift
524
1252
1267
246
0.84
69.783
<0.001
Night shift
19
64
91
27
0.91
Shift
235
620
813
229
0.88
Day and night shifts
80
266
313
74
0.89
Marital status
Unmarried
120
342
333
62
0.86
14.988
0.091
Married
683
1715
1986
480
0.86
Divorced
51
125
152
29
0.86
Widowed
4
20
13
5
0.90
Monthly income (yuan)
<3000
218
598
686
154
0.87
32.453
0.019
3000~
271
725
892
205
0.87
4000~
190
499
512
128
0.86
5000~
118
225
256
60
0.82
6000~
34
72
81
18
0.83
7000~
16
40
23
7
0.81
8000~
11
43
34
4
0.88
Weight (kg)
<55
118
371
298
53
0.86
57.312
<0.001
55~
211
610
616
134
0.87
65~
253
596
763
168
0.86
75~
276
625
807
221
0.86
Diabetes
Yes
50
122
148
44
0.90
3.621
0.305
No
808
2080
2336
532
0.86
Hypertension
Yes
148
360
539
173
0.88
63.275
<0.001
No
710
1842
1945
403
0.86
Age (years)
<25
39
152
117
11
0.88
57.433
<0.001
25~
97
261
242
34
0.85
30~
102
270
334
84
0.87
35~
112
232
279
81
0.84
40~
105
259
285
74
0.85
45~
403
1028
1227
292
0.86
Working years (years)
~5
138
448
295
39
0.85
133.982
<0.001
5~
112
315
339
65
0.87
10~
103
284
358
95
0.88
15~
53
106
127
33
0.83
20~
91
239
287
78
0.87
25~
163
425
521
157
0.87
30~
198
385
557
109
0.84
Working hours per day (hours)
≤7
179
339
384
73
0.82
21.028
<0.001
>7
679
1863
2100
503
0.87
Working days per week (days)
≤5
606
1383
1641
376
0.85
17.405
0.001
>5
252
819
843
200
0.88
Coal dust
Yes
181
476
624
165
0.87
19.090
<0.001
No
677
1726
1860
411
0.86
Silica dust
Yes
55
208
275
84
0.87
29.043
<0.001
No
803
1994
2209
492
0.86
Asbestos dust
Yes
105
268
414
148
0.91
74.537
<0.001
No
753
1934
2070
428
0.85
Benzene
Yes
237
592
856
262
0.89
89.269
<0.001
No
621
1610
1628
314
0.85
Lead
Yes
37
108
163
45
0.88
13.676
0.003
No
821
2094
2321
531
0.85
Noise
Yes
590
1553
1935
467
0.87
60.824
<0.001
No
268
649
549
109
0.83
Brucellosis
Yes
14
42
37
15
0.87
3.772
0.287
No
844
2160
2447
561
0.86


### 3.3. Comparison of Psychological Health in Different Populations

The results showed that the detection rate of psychological health was higher for males than females (P=0.003). The detection rate of psychological health was higher for working days per week less than 5 days than more than 5 days (P=0.029). The detection rate of psychological health with high school education (P<0.001), senior professional title (P<0.001), night shift (P<0.001), divorced (P<0.001), monthly income less than 3000 yuan (P<0.001), weight more than 75 kg (P<0.001), age more than 45 years (P<0.001), and working years between 25 and 30 years (P<0.001) was higher than that of the other groups. The psychological health was related to the workers and miners who had diabetes (P<0.001), hypertension (P<0.001), and exposure to coal dust (P<0.001), silica dust (P<0.001), asbestos dust (P<0.001), benzene (P<0.001), lead (P<0.001), and noise (P<0.001) (Table 3).Table 3
Comparison of psychological health in different populations.
Items
Groups
SCL-90
SCL detection rate (%)
Chi-squared value
P value
-
+
Sex
Male
2426
1591
39.61
8.70
0.003
Female
1352
751
35.71
Ethnicity
Han
3088
1928
38.44
0.30
0.585
Other
690
414
37.50
Education level
Junior high school and below
516
136
20.86
93.95
<0.001
High school
727
500
40.75
Junior college
1620
1102
40.48
Bachelor’s degree or above
915
604
39.76
Professional title
No
1514
835
35.55
45.01
<0.001
Primary
873
453
34.16
Middle
867
616
41.54
Senior
524
438
45.53
Work schedule
Day shift
2159
1130
34.36
46.62
<0.001
Night shift
111
90
44.78
Shift
1093
804
42.38
Day and night shifts
415
318
43.38
Marital status
Unmarried
624
233
27.19
54.31
<0.001
Married
2928
1936
39.80
Divorced
200
157
43.98
Widowed
26
16
38.10
Monthly income (yuan)
<3000
970
686
41.43
45.52
<0.001
3000~
1234
859
41.04
4000~
846
483
36.34
5000~
458
201
30.50
6000~
142
63
30.73
7000~
61
25
29.07
8000~
67
25
27.17
Weight (kg)
<55
581
259
30.83
49.11
<0.001
55~
1016
555
35.33
65~
1094
686
38.54
75~
1087
842
43.65
Diabetes
Yes
186
178
48.90
18.05
<0.001
No
3592
2164
37.60
Hypertension
Yes
557
663
54.34
165.85
<0.001
No
3221
1679
34.27
Age (years)
<25
257
62
19.44
136.33
<0.001
25~
463
171
26.97
30~
537
253
32.03
35~
425
279
39.63
40~
443
280
38.73
45~
1653
1297
43.97
Working years (years)
~5
746
174
18.91
267.53
<0.001
5~
575
256
30.81
10~
540
300
35.71
15~
196
123
38.56
20~
385
310
44.60
25~
636
630
49.76
30~
700
549
43.96
Working hours per day (hours)
≤7
599
376
38.56
0.03
0.864
>7
3179
1966
38.21
Working days per week (days)
≤5
2433
1573
39.27
4.77
0.029
>5
1345
769
36.38
Coal dust
Yes
809
637
44.05
26.50
<0.001
No
2969
1705
36.48
Silica dust
Yes
307
315
50.64
44.30
<0.001
No
3471
2027
36.87
Asbestos dust
Yes
427
508
54.33
119.75
<0.001
No
3351
1834
35.37
Benzene
Yes
999
948
48.69
130.65
<0.001
No
2779
1394
33.41
Lead
Yes
177
176
49.86
20.79
<0.001
No
3601
2166
37.56
Noise
Yes
2698
1847
40.64
41.61
<0.001
No
1080
495
31.43
Brucellosis
Yes
57
51
47.22
3.36
0.067
No
3721
2291
38.11


### 3.4. Exploration of Factors Influencing Psychological Health

Multiple logistic regression analysis was used to analyze the effects of different characteristics and occupational burnout on the psychological health of factory workers and miners. All the independent variables in the logistic regression were stratified. The results showed that education level of junior college and higher (P<0.001), work schedule of shift and day and night shift (P<0.001), monthly income (except for 7000~) (P<0.005), hypertension (P<0.001), working years (P<0.005), asbestos dust (P<0.001), benzene (P=0.021), and occupational burnout (P<0.001) affected psychological health of factory workers and miners. Higher education, shift work or day and night shift, lower income, hypertension, longer working years, exposure to asbestos dust and benzene, and occupational burnout were risk factors related to poorer psychological health (Table 4).Table 4
Effects of psychological health-related factors among workers and miners according to the results of the multiple logistic regression analysis.
Variable
Groups
β (95% CI)
S.E.
OR (95% CI)
Wald
P value
Intercept
-3.76 (-4.34, -3.18)
0.30
0.02 (0.01, 0.04)
-12.709
0.000
Sex
Male
—
—
—
—
—
Female
0.09 (-0.05, 0.23)
0.07
1.09 (0.95, 1.26)
1.206
0.228
Ethnicity
Han
—
—
—
—
—
Other
0.02 (-0.14, 0.17)
0.08
1.02 (0.87, 1.19)
0.213
0.831
Education level
Junior high school and below
—
—
—
—
—
High school
0.26 (-0.00, 0.52)
0.13
1.30 (1.00, 1.69)
1.943
0.052
Junior college
0.59 (0.34, 0.83)
0.13
1.80 (1.41, 2.30)
4.668
0.000
Bachelor’s degree or above
0.71 (0.45, 0.98)
0.14
2.03 (1.56, 2.66)
5.245
0.000
Professional title
No
—
—
—
—
—
Primary
0.08 (-0.09, 0.25)
0.09
1.08 (0.92, 1.29)
0.968
0.333
Middle
0.13 (-0.03, 0.29)
0.08
1.14 (0.97, 1.33)
1.563
0.118
Senior
0.17 (-0.01, 0.35)
0.09
1.19 (0.99, 1.42)
1.891
0.059
Work schedule
Day shift
—
—
—
—
—
Night shift
0.31 (-0.03, 0.65)
0.17
1.36 (0.97, 1.91)
1.782
0.075
Shift
0.32 (0.17, 0.47)
0.07
1.38 (1.19, 1.59)
4.312
0.000
Day and night shifts
0.42 (0.23, 0.62)
0.10
1.52 (1.26, 1.86)
4.270
0.000
Marital status
Unmarried
—
—
—
—
—
Married
0.07 (-0.17, 0.30)
0.12
1.07 (0.85, 1.35)
0.565
0.572
Divorced
0.16 (-0.17, 0.49)
0.17
1.17 (0.85, 1.64)
0.971
0.332
Widowed
-0.02 (-0.76, 0.72)
0.38
0.98 (0.47, 2.06)
-0.051
0.960
Monthly income (yuan)
<3000
—
—
—
—
—
3000~
-0.18 (-0.33, -0.03)
0.08
0.84 (0.72, 0.97)
-2.305
0.021
4000~
-0.30 (-0.48, -0.12)
0.09
0.74 (0.62, 0.89)
-3.272
0.001
5000~
-0.58 (-0.82, -0.34)
0.12
0.56 (0.44, 0.71)
-4.831
0.000
6000~
-0.55 (-0.92, -0.18)
0.19
0.58 (0.40, 0.84)
-2.917
0.004
7000~
-0.44 (-1.00, 0.11)
0.28
0.64 (0.37, 1.12)
-1.566
0.117
8000~
-0.59 (-1.11, -0.06)
0.27
0.55 (0.33, 0.94)
-2.189
0.029
Diabetes
No
—
—
—
—
—
Yes
0.52 (0.37, 0.67)
0.08
1.23 (0.96, 1.58)
1.638
0.101
Hypertension
No
—
—
—
—
—
Yes
0.21 (-0.04, 0.46)
0.13
1.68 (1.44, 1.96)
6.656
0.000
Age (years)
<25
—
—
—
—
—
25~
0.14 (-0.25, 0.53)
0.20
1.15 (0.78, 1.69)
0.714
0.475
30~
-0.01 (-0.43, 0.41)
0.21
0.99 (0.65, 1.51)
-0.045
0.964
35~
0.26 (-0.17, 0.70)
0.22
1.30 (0.84, 2.01)
1.181
0.238
40~
0.09 (-0.36, 0.53)
0.23
1.09 (0.70, 1.71)
0.376
0.707
45~
0.20 (-0.25, 0.64)
0.22
1.22 (0.78, 1.89)
0.870
0.384
Working years (years)
~5
—
—
—
—
—
5~
0.34 (0.08, 0.61)
0.14
1.40 (1.08, 1.84)
2.517
0.012
10~
0.37 (0.08, 0.66)
0.15
1.45 (1.08, 1.93)
2.483
0.013
15~
0.51 (0.15, 0.88)
0.19
1.67 (1.16, 2.41)
2.764
0.006
20~
0.79 (0.47, 1.12)
0.17
2.20 (1.59, 3.06)
4.768
0.000
25~
0.87 (0.54, 1.19)
0.17
2.39 (1.72, 3.30)
5.239
0.000
30~
0.68 (0.36, 1.01)
0.17
1.97 (1.43, 2.75)
4.093
0.000
Working hours per day (hours)
≤7
—
—
—
—
—
>7
0.07 (-0.10, 0.25)
0.09
1.07 (0.90, 1.28)
0.834
0.404
Working days per week (days)
≤5
—
—
—
—
—
>5
0.13 (-0.01, 0.26)
0.07
1.14 (0.99, 1.29)
1.877
0.060
Coal dust
No
—
—
—
—
—
Yes
0.12 (-0.03, 0.27)
0.08
1.13 (0.97, 1.31)
1.589
0.112
Silica dust
No
—
—
—
—
—
Yes
0.19 (-0.02, 0.39)
0.11
1.21 (0.98, 1.48)
1.747
0.081
Asbestos dust
No
—
—
—
—
—
Yes
0.39 (0.21, 0.57)
0.09
1.48 (1.23, 1.77)
4.186
0.000
Benzene
No
—
—
—
—
—
Yes
0.16 (0.02, 0.30)
0.07
1.17 (1.02, 1.34)
2.311
0.021
Lead
No
—
—
—
—
—
Yes
-0.15 (-0.42, 0.12)
0.14
0.86 (0.66, 1.12)
-1.108
0.268
Noise
No
—
—
—
—
—
Yes
0.13 (-0.02, 0.27)
0.07
1.14 (0.98, 1.31)
1.751
0.080
Brucellosis
No
—
—
—
—
—
Yes
0.26 (-0.21, 0.72)
0.24
1.30 (0.81, 2.05)
1.077
0.281
CMBI
None
—
—
—
—
—
Mild
0.36 (0.15, 0.56)
0.11
1.43 (1.16, 1.75)
3.373
0.001
Moderate
1.34 (1.14, 1.53)
0.10
3.82 (3.12, 4.63)
13.282
0.000
Severe
3.24 (2.93, 3.54)
0.16
25.53 (18.80, 34.63)
20.774
0.000


## 3.1. General Demographic Characteristics of Factory Workers and Miners

Among the 6120 workers and miners, 4017 were men (65.64%) and 2103 were women (34.36%); 1220 had hypertension (19.93%) and 364 had diabetes (5.95%). Exposure to coal dust, silica dust, asbestos dust, benzene dust, lead, noise, and brucellosis accounted for 1446 (23.63%), 622 (10.16%), 935 (15.28%), 1947 (31.81%), 353 (5.77%), 4545 (74.26%), and 108 (1.76%), respectively (Table1).Table 1
Characteristics of the factory workers and miners.
Items
Groups
Case number
Percentage (%)
Sex
Male
4017
65.64
Female
2103
34.36
Ethnicity
Han
5016
81.96
Other
1104
18.04
Education level
Junior high school and below
652
10.65
High school
1227
20.05
Junior college
2722
44.48
Bachelor’s degree or above
1519
24.82
Labor contracts
Signed
5896
96.34
Unsigned
224
3.66
Professional title
No
2349
38.38
Primary
1326
21.67
Middle
1483
24.23
Senior
962
15.72
Work schedule
Day shift
3289
53.74
Night shift
201
3.28
Shift
1897
31.00
Day and night shifts
733
11.98
Marital status
Unmarried
857
14.00
Married
4864
79.48
Divorced
357
5.83
Widowed
42
0.69
Monthly income (yuan)
<3000
1656
27.06
3000~
2093
34.20
4000~
1329
21.72
5000~
659
10.77
6000~
205
3.35
7000~
86
1.41
8000~
92
1.50
Weight (kg)
<55
840
13.73
55~
1571
25.67
65~
1780
29.08
75~
1929
31.52
Chronic disease
Diabetes
364
5.95
Hypertension
1220
19.93
Age (years)
<25
319
5.21
25~
634
10.36
30~
790
12.91
35~
704
11.50
40~
723
11.81
45~
2950
48.20
Working years (years)
~5
920
15.03
5~
831
13.58
10~
840
13.73
15~
319
5.21
20~
695
11.36
25~
1266
20.69
30~
1249
20.41
Working hours per day (hours)
≤7
975
15.93
>7
5145
84.07
Working days per week (days)
≤5
4006
65.46
>5
2114
34.54
Occupational hazard factors
Coal dust
1446
23.63
Silica dust
622
10.16
Asbestos dust
935
15.28
Benzene
1947
31.81
Lead
353
5.77
Noise
4545
74.26
Brucellosis
108
1.76


## 3.2. Comparison of Occupational Burnout Levels in Different Populations

The survey results showed that 85.98% of workers and miners experienced occupational burnout in varying degrees. There were statistically significant differences in sex (P<0.001), education level (P<0.001), labor contracts (P<0.001), work schedule (P<0.001), monthly incomes (P=0.019), weight (P<0.001), hypertension (P<0.001), age (P<0.001), working years (P<0.001), working hours per day (P<0.001), working hours per week (P=0.001), coal dust (P<0.001), silica dust (P<0.001), asbestos dust (P<0.001), benzene (P<0.001), lead (P=0.003), and noise (P<0.05) (Table 2).Table 2
Comparison of occupational burnout levels in different populations.
Items
Groups
CMBI
CMBI detection rate (%)
Chi-squared value
P value
No
Mild
Moderate
Severe
Sex
Male
548
1371
1699
399
0.86
24.078
<0.001
Female
310
831
785
177
0.85
Ethnicity
Han
700
1794
2042
480
0.86
1.274
0.735
Other
158
408
442
96
0.86
Education level
Junior high school and below
68
346
209
29
0.90
121.637
<0.001
High school
144
433
519
131
0.88
Junior college
386
926
1162
248
0.86
Bachelor’s degree or above
260
497
594
168
0.83
Labor contracts
Signed
839
2069
2417
571
0.86
59.719
<0.001
Unsigned
19
133
67
5
0.86
Professional title
No
334
868
934
213
0.86
9.941
0.355
Primary
183
488
540
115
0.85
Middle
201
507
610
165
0.86
Senior
140
339
400
83
0.86
Work schedule
Day shift
524
1252
1267
246
0.84
69.783
<0.001
Night shift
19
64
91
27
0.91
Shift
235
620
813
229
0.88
Day and night shifts
80
266
313
74
0.89
Marital status
Unmarried
120
342
333
62
0.86
14.988
0.091
Married
683
1715
1986
480
0.86
Divorced
51
125
152
29
0.86
Widowed
4
20
13
5
0.90
Monthly income (yuan)
<3000
218
598
686
154
0.87
32.453
0.019
3000~
271
725
892
205
0.87
4000~
190
499
512
128
0.86
5000~
118
225
256
60
0.82
6000~
34
72
81
18
0.83
7000~
16
40
23
7
0.81
8000~
11
43
34
4
0.88
Weight (kg)
<55
118
371
298
53
0.86
57.312
<0.001
55~
211
610
616
134
0.87
65~
253
596
763
168
0.86
75~
276
625
807
221
0.86
Diabetes
Yes
50
122
148
44
0.90
3.621
0.305
No
808
2080
2336
532
0.86
Hypertension
Yes
148
360
539
173
0.88
63.275
<0.001
No
710
1842
1945
403
0.86
Age (years)
<25
39
152
117
11
0.88
57.433
<0.001
25~
97
261
242
34
0.85
30~
102
270
334
84
0.87
35~
112
232
279
81
0.84
40~
105
259
285
74
0.85
45~
403
1028
1227
292
0.86
Working years (years)
~5
138
448
295
39
0.85
133.982
<0.001
5~
112
315
339
65
0.87
10~
103
284
358
95
0.88
15~
53
106
127
33
0.83
20~
91
239
287
78
0.87
25~
163
425
521
157
0.87
30~
198
385
557
109
0.84
Working hours per day (hours)
≤7
179
339
384
73
0.82
21.028
<0.001
>7
679
1863
2100
503
0.87
Working days per week (days)
≤5
606
1383
1641
376
0.85
17.405
0.001
>5
252
819
843
200
0.88
Coal dust
Yes
181
476
624
165
0.87
19.090
<0.001
No
677
1726
1860
411
0.86
Silica dust
Yes
55
208
275
84
0.87
29.043
<0.001
No
803
1994
2209
492
0.86
Asbestos dust
Yes
105
268
414
148
0.91
74.537
<0.001
No
753
1934
2070
428
0.85
Benzene
Yes
237
592
856
262
0.89
89.269
<0.001
No
621
1610
1628
314
0.85
Lead
Yes
37
108
163
45
0.88
13.676
0.003
No
821
2094
2321
531
0.85
Noise
Yes
590
1553
1935
467
0.87
60.824
<0.001
No
268
649
549
109
0.83
Brucellosis
Yes
14
42
37
15
0.87
3.772
0.287
No
844
2160
2447
561
0.86


## 3.3. Comparison of Psychological Health in Different Populations

The results showed that the detection rate of psychological health was higher for males than females (P=0.003). The detection rate of psychological health was higher for working days per week less than 5 days than more than 5 days (P=0.029). The detection rate of psychological health with high school education (P<0.001), senior professional title (P<0.001), night shift (P<0.001), divorced (P<0.001), monthly income less than 3000 yuan (P<0.001), weight more than 75 kg (P<0.001), age more than 45 years (P<0.001), and working years between 25 and 30 years (P<0.001) was higher than that of the other groups. The psychological health was related to the workers and miners who had diabetes (P<0.001), hypertension (P<0.001), and exposure to coal dust (P<0.001), silica dust (P<0.001), asbestos dust (P<0.001), benzene (P<0.001), lead (P<0.001), and noise (P<0.001) (Table 3).Table 3
Comparison of psychological health in different populations.
Items
Groups
SCL-90
SCL detection rate (%)
Chi-squared value
P value
-
+
Sex
Male
2426
1591
39.61
8.70
0.003
Female
1352
751
35.71
Ethnicity
Han
3088
1928
38.44
0.30
0.585
Other
690
414
37.50
Education level
Junior high school and below
516
136
20.86
93.95
<0.001
High school
727
500
40.75
Junior college
1620
1102
40.48
Bachelor’s degree or above
915
604
39.76
Professional title
No
1514
835
35.55
45.01
<0.001
Primary
873
453
34.16
Middle
867
616
41.54
Senior
524
438
45.53
Work schedule
Day shift
2159
1130
34.36
46.62
<0.001
Night shift
111
90
44.78
Shift
1093
804
42.38
Day and night shifts
415
318
43.38
Marital status
Unmarried
624
233
27.19
54.31
<0.001
Married
2928
1936
39.80
Divorced
200
157
43.98
Widowed
26
16
38.10
Monthly income (yuan)
<3000
970
686
41.43
45.52
<0.001
3000~
1234
859
41.04
4000~
846
483
36.34
5000~
458
201
30.50
6000~
142
63
30.73
7000~
61
25
29.07
8000~
67
25
27.17
Weight (kg)
<55
581
259
30.83
49.11
<0.001
55~
1016
555
35.33
65~
1094
686
38.54
75~
1087
842
43.65
Diabetes
Yes
186
178
48.90
18.05
<0.001
No
3592
2164
37.60
Hypertension
Yes
557
663
54.34
165.85
<0.001
No
3221
1679
34.27
Age (years)
<25
257
62
19.44
136.33
<0.001
25~
463
171
26.97
30~
537
253
32.03
35~
425
279
39.63
40~
443
280
38.73
45~
1653
1297
43.97
Working years (years)
~5
746
174
18.91
267.53
<0.001
5~
575
256
30.81
10~
540
300
35.71
15~
196
123
38.56
20~
385
310
44.60
25~
636
630
49.76
30~
700
549
43.96
Working hours per day (hours)
≤7
599
376
38.56
0.03
0.864
>7
3179
1966
38.21
Working days per week (days)
≤5
2433
1573
39.27
4.77
0.029
>5
1345
769
36.38
Coal dust
Yes
809
637
44.05
26.50
<0.001
No
2969
1705
36.48
Silica dust
Yes
307
315
50.64
44.30
<0.001
No
3471
2027
36.87
Asbestos dust
Yes
427
508
54.33
119.75
<0.001
No
3351
1834
35.37
Benzene
Yes
999
948
48.69
130.65
<0.001
No
2779
1394
33.41
Lead
Yes
177
176
49.86
20.79
<0.001
No
3601
2166
37.56
Noise
Yes
2698
1847
40.64
41.61
<0.001
No
1080
495
31.43
Brucellosis
Yes
57
51
47.22
3.36
0.067
No
3721
2291
38.11


## 3.4. Exploration of Factors Influencing Psychological Health

Multiple logistic regression analysis was used to analyze the effects of different characteristics and occupational burnout on the psychological health of factory workers and miners. All the independent variables in the logistic regression were stratified. The results showed that education level of junior college and higher (P<0.001), work schedule of shift and day and night shift (P<0.001), monthly income (except for 7000~) (P<0.005), hypertension (P<0.001), working years (P<0.005), asbestos dust (P<0.001), benzene (P=0.021), and occupational burnout (P<0.001) affected psychological health of factory workers and miners. Higher education, shift work or day and night shift, lower income, hypertension, longer working years, exposure to asbestos dust and benzene, and occupational burnout were risk factors related to poorer psychological health (Table 4).Table 4
Effects of psychological health-related factors among workers and miners according to the results of the multiple logistic regression analysis.
Variable
Groups
β (95% CI)
S.E.
OR (95% CI)
Wald
P value
Intercept
-3.76 (-4.34, -3.18)
0.30
0.02 (0.01, 0.04)
-12.709
0.000
Sex
Male
—
—
—
—
—
Female
0.09 (-0.05, 0.23)
0.07
1.09 (0.95, 1.26)
1.206
0.228
Ethnicity
Han
—
—
—
—
—
Other
0.02 (-0.14, 0.17)
0.08
1.02 (0.87, 1.19)
0.213
0.831
Education level
Junior high school and below
—
—
—
—
—
High school
0.26 (-0.00, 0.52)
0.13
1.30 (1.00, 1.69)
1.943
0.052
Junior college
0.59 (0.34, 0.83)
0.13
1.80 (1.41, 2.30)
4.668
0.000
Bachelor’s degree or above
0.71 (0.45, 0.98)
0.14
2.03 (1.56, 2.66)
5.245
0.000
Professional title
No
—
—
—
—
—
Primary
0.08 (-0.09, 0.25)
0.09
1.08 (0.92, 1.29)
0.968
0.333
Middle
0.13 (-0.03, 0.29)
0.08
1.14 (0.97, 1.33)
1.563
0.118
Senior
0.17 (-0.01, 0.35)
0.09
1.19 (0.99, 1.42)
1.891
0.059
Work schedule
Day shift
—
—
—
—
—
Night shift
0.31 (-0.03, 0.65)
0.17
1.36 (0.97, 1.91)
1.782
0.075
Shift
0.32 (0.17, 0.47)
0.07
1.38 (1.19, 1.59)
4.312
0.000
Day and night shifts
0.42 (0.23, 0.62)
0.10
1.52 (1.26, 1.86)
4.270
0.000
Marital status
Unmarried
—
—
—
—
—
Married
0.07 (-0.17, 0.30)
0.12
1.07 (0.85, 1.35)
0.565
0.572
Divorced
0.16 (-0.17, 0.49)
0.17
1.17 (0.85, 1.64)
0.971
0.332
Widowed
-0.02 (-0.76, 0.72)
0.38
0.98 (0.47, 2.06)
-0.051
0.960
Monthly income (yuan)
<3000
—
—
—
—
—
3000~
-0.18 (-0.33, -0.03)
0.08
0.84 (0.72, 0.97)
-2.305
0.021
4000~
-0.30 (-0.48, -0.12)
0.09
0.74 (0.62, 0.89)
-3.272
0.001
5000~
-0.58 (-0.82, -0.34)
0.12
0.56 (0.44, 0.71)
-4.831
0.000
6000~
-0.55 (-0.92, -0.18)
0.19
0.58 (0.40, 0.84)
-2.917
0.004
7000~
-0.44 (-1.00, 0.11)
0.28
0.64 (0.37, 1.12)
-1.566
0.117
8000~
-0.59 (-1.11, -0.06)
0.27
0.55 (0.33, 0.94)
-2.189
0.029
Diabetes
No
—
—
—
—
—
Yes
0.52 (0.37, 0.67)
0.08
1.23 (0.96, 1.58)
1.638
0.101
Hypertension
No
—
—
—
—
—
Yes
0.21 (-0.04, 0.46)
0.13
1.68 (1.44, 1.96)
6.656
0.000
Age (years)
<25
—
—
—
—
—
25~
0.14 (-0.25, 0.53)
0.20
1.15 (0.78, 1.69)
0.714
0.475
30~
-0.01 (-0.43, 0.41)
0.21
0.99 (0.65, 1.51)
-0.045
0.964
35~
0.26 (-0.17, 0.70)
0.22
1.30 (0.84, 2.01)
1.181
0.238
40~
0.09 (-0.36, 0.53)
0.23
1.09 (0.70, 1.71)
0.376
0.707
45~
0.20 (-0.25, 0.64)
0.22
1.22 (0.78, 1.89)
0.870
0.384
Working years (years)
~5
—
—
—
—
—
5~
0.34 (0.08, 0.61)
0.14
1.40 (1.08, 1.84)
2.517
0.012
10~
0.37 (0.08, 0.66)
0.15
1.45 (1.08, 1.93)
2.483
0.013
15~
0.51 (0.15, 0.88)
0.19
1.67 (1.16, 2.41)
2.764
0.006
20~
0.79 (0.47, 1.12)
0.17
2.20 (1.59, 3.06)
4.768
0.000
25~
0.87 (0.54, 1.19)
0.17
2.39 (1.72, 3.30)
5.239
0.000
30~
0.68 (0.36, 1.01)
0.17
1.97 (1.43, 2.75)
4.093
0.000
Working hours per day (hours)
≤7
—
—
—
—
—
>7
0.07 (-0.10, 0.25)
0.09
1.07 (0.90, 1.28)
0.834
0.404
Working days per week (days)
≤5
—
—
—
—
—
>5
0.13 (-0.01, 0.26)
0.07
1.14 (0.99, 1.29)
1.877
0.060
Coal dust
No
—
—
—
—
—
Yes
0.12 (-0.03, 0.27)
0.08
1.13 (0.97, 1.31)
1.589
0.112
Silica dust
No
—
—
—
—
—
Yes
0.19 (-0.02, 0.39)
0.11
1.21 (0.98, 1.48)
1.747
0.081
Asbestos dust
No
—
—
—
—
—
Yes
0.39 (0.21, 0.57)
0.09
1.48 (1.23, 1.77)
4.186
0.000
Benzene
No
—
—
—
—
—
Yes
0.16 (0.02, 0.30)
0.07
1.17 (1.02, 1.34)
2.311
0.021
Lead
No
—
—
—
—
—
Yes
-0.15 (-0.42, 0.12)
0.14
0.86 (0.66, 1.12)
-1.108
0.268
Noise
No
—
—
—
—
—
Yes
0.13 (-0.02, 0.27)
0.07
1.14 (0.98, 1.31)
1.751
0.080
Brucellosis
No
—
—
—
—
—
Yes
0.26 (-0.21, 0.72)
0.24
1.30 (0.81, 2.05)
1.077
0.281
CMBI
None
—
—
—
—
—
Mild
0.36 (0.15, 0.56)
0.11
1.43 (1.16, 1.75)
3.373
0.001
Moderate
1.34 (1.14, 1.53)
0.10
3.82 (3.12, 4.63)
13.282
0.000
Severe
3.24 (2.93, 3.54)
0.16
25.53 (18.80, 34.63)
20.774
0.000


## 4. Discussion

Occupational burnout is a state of pressure that is a significant issue worldwide which is related to efficiency and quality of work, and it is also regarded as particularly harmful to the social psychological of the working population [19, 20]. A study conducted by Inger et al. examined the occupational burnout of southern Sweden teachers and found that 46.8% teachers suffered from burnout [21]. Guan et al. found that the rate of occupational burnout among civil servants was 45.0% [22]. A survey in China had revealed that the prevalence of occupational burnout in the military was 88.14% [23, 24]. While occupational burnout can affect physical and psychological health, it also adversely impacts upon the working ability and quality.Factory workers and miners belong to a special professional group, whose mental health is closely related to the development of the industry. However, the workers and miners’ social status is low, and they work hard but the income is relatively low [19]. Long periods of heavy work caused them to languish and burnout. And they often worked in a special environment of high temperature, high pressure, darkness, or dust; some studies already proved that people living in harsh environments have a higher risk of developing mental illnesses, and the special environments affect the degree of job burnout [25–28]. Our research presented here revealed that 85.98% of factory workers and miners experience occupational burnout, reminding that occupational burnout is prevalent among this particular working group. The higher the level of occupational burnout, the poorer the psychological health of factory workers and miners, suggesting that occupational burnout is a risk factor that can influence psychological health.This survey investigated occupational burnout levels among factory workers and miners. The occupational burnout level of night shift workers was higher than that of others, which may due to long-term working at night causing night and day reversal and lack of rest, thereby resulting in fatigue. Chronic diseases such as hypertension could cause changes in the body’s functioning that can make workers feel more tired at work. People under 30 years old or with less than 10 working years were more likely to develop occupational burnout. Most of them had acquired professional skills and had good stamina so that they were more eager to seek promotion opportunity or to increase their personal income [29]. Workers who worked more than 7 hours per day or more than 5 days per week need to maintain a high level of stress, and lack of time of recreation, leisure, and relaxation increased their burnout levels, which might enhance the risk of mental health problems [30, 31]. Long-term occupational exposure to coal dust, silica dust, asbestos dust, benzene, lead, and noise would cause varying degrees of pulmonary diseases and other illness, thereby affecting respiration and body metabolism, which makes them prone to fatigue and tired.The study found that education level had influence on psychological health; the risks of psychological health problems at junior college and bachelor’s degree or above were 1.80 times and 2.03 times that of junior high school and below, respectively. Maslach’ study had showed that people who had higher education may have more self-expectation and social expectation [32]. When the job cannot meet one’s personal needs and expectation, one may experience strain response such as job satisfaction drops, occupational burnout, and mental illness [33–35]. Work schedule was a risk factor related to poor psychological health, particularly at shift and day and night shift. The risk of psychological health problems increased with changing a way of work schedule and/or of day and night shifts was the highest. The long-term day and night shifts made workers’ day and night reversed, resulting in the different physical functions and thereby leading to mental illness. Khajehnasiri et al.’s research also showed that shift workers had a high level of stress and depressive symptoms [36]. The influence of marital status on psychological health was statistically significant in univariate analysis, but not in multiple logistic regression analysis, which meant marital status was not an independent risk factor of psychological health. But some studies confirmed the correlation of divorce and psychological problems due to lack of a sense of family and kinship [37, 38]. Due to the poor physical health, workers with hypertension were liable to suffer from cardiovascular diseases and thereby have some psychological changes, which was consistent with other studies [39]. The influence of occupational burnout at any level on psychological health was statistically significant, and the risks of psychological health problems increased 1.43 times, 3.82 times, and 25.53 times with aggravating occupational burnout level, respectively. According to psychological theories, excess psychological stress could decline psychological function (such as distracted attention and reduced working will and desire) and cause negative physiological responses (such as declined strength, stiffened body, and disorders in sense and memory) [40]. The higher the occupational burnout, the more significant the adverse physiological function and psychological reaction, leading to increasing the possibility of work errors. When workers and miners can no longer utilize their internal and social resources to relieve their psychological burden caused by work errors, their psychological balance will be disturbed, resulting in emotional fluctuations and psychological health problems [41].It reminded that reasonable arrangement of work shift, promotion of occupational personal protection and health education, guidance to spare time arrangement of workers, enhancement of disease prevention, and psychological counseling should be taken into consideration to keep physical and mental health of factory workers and miners.The present survey used online questionnaire; compared with paper questionnaire, the recovery rate was higher, but there were still repeated answers and cross-sectional investigation cannot establish a causal relationship between diseases; in the future, further studies will continue to explore the relationship between the factors and diseases by using cohort studies.


## 5. Conclusion

In conclusion, this survey found that the factory workers and miners generally suffered from occupational burnout, and sex, education level, professional title, work schedule, monthly income, hypertension, age, working years, asbestos dust, and benzene were related risk factors. In addition, occupational burnout influenced the psychological health. Measures need to be taken to ease occupational burnout among factory workers and miners in order to improve their psychological health.



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*Source: 6890186-2020-02-28.xml*