Vol. 5, No. 6, June 2024
E-ISSN: 2723-6692
P-ISSN: 2723-6595
http://jiss.publikasiindonesia.id/
Jurnal Indonesia Sosial Sains, Vol. 5, No. 6, June 2024 1477
Analysis of Demographic Factors Affecting Mental Health Among
Workers at PT X Mining Company in 2023
*
Eko Susanto, Mila Tejamaya
Universitas Indonesia, Depok, Indonesia
Email: ekosusanto.k3@gmail.com, tejamaya@ui.ac.id
Correspondence: ekosusanto.k3@gmail.com
*
KEYWORDS
ABSTRACT
mental healt;, DASS-21;
mining industry;
depression; anxiety; stress.
The mining industry is closely related to high-risk health and safety,
including mental health. This study aims to investigate the
association of demographic variables (age, length of service, gender,
education level, employment status, and work location), on mental
health symptoms in workers in mining companies PT X. The DASS-
21 instrumentation was used to determine mental health symptoms
based on levels of depression, anxiety, and stress. The number of
respondents in this study was 764 employees were participated and
it was found that 71.2% of respondents did not experience mental
health problems, 15.3% experienced mild mental health symptoms,
10.4% moderate, and 3.1% severe mental health symptoms. There
is a significant relationship between the age variable and the level of
depression (p-value 0.04), the significant relationship between age,
education level, length of service, gender, and the level of anxiety (p-
value 0.04; 0.005; 0.000; dan 0.007), as well as the relationship
between age and level of education and stress in workers (p-value
0.000; dan 0.016). From the research, it can be concluded that the
older the worker, the lower the level of depression, anxiety, and
work stress. Male employees have lower levels of anxiety and stress
than women, and a higher level of education plays a role in
increasing anxiety and stress in workers.
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
1. Introduction
The business processes of mining represent one of the highest-risk work sectors compared to
other business activities worldwide and require substantial funding (Saleh & Wahyu, 2019). This aligns
with a series of high-load work conditions characterized by high-risk working environments and
generally remote work areas, high production targets, shift work schedules, and job tension related
to complex regulations and work processes (Tubis et al., 2020). Consequently, the mining business
processes can adversely impact workers' safety and health, leading to illnesses, disabilities, and even
workplace fatalities. Technological advancements, impacting work process developments without
adequate preparation for physical, technical, or mental competence, can result in workplace diseases
or accidents. In other words, industrialization is a double-edged sword; it aids in economic, health,
and welfare improvements but also causes disabilities or deaths (Matamala Pizarro & Aguayo Fuenzalida,
2021).
Mental health is a state of well-being in which an individual realizes their abilities, can manage
stress, work productively, and contribute to their community. Good mental health is a condition when
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a person's inner self is in a state of peace and calm, allowing them to enjoy daily life and appreciate
the people around them. According to research conducted by Firoozi in 2015, depression and stress
rank as the second most common health disorders among workers after heart disease in the
workplace (Firoozi chahak et al., 2015). This is more evident in developing countries, where there is
often excessive work pressure to increase production without adhering to occupational safety
regulations such as work procedures, working hours, worker training, proper use of personal
protective equipment, and the lack of occupational health service systems compared to developed
countries. Data from WHO in 2019 shows that around 300 million people worldwide have
experienced depression. In Asia, mental health issues are the second-largest contributor to years lost
due to disability. This is marked by the increasing number of adults diagnosed with mental illnesses
each year: from 4% reported in Singapore to 20% in other countries such as Vietnam, Thailand, New
Zealand, and Australia. In China, India, Japan, South Korea, Thailand, and Malaysia, the prevalence of
mental health disorders is also rising. Meanwhile, data indicates 15.6 million diagnosed cases of
mental health issues in Indonesia. Other data from the Ministry of Health of the Republic of Indonesia
in 2023 shows that 6.1% of Indonesians aged 15 and older experience mental health disorders
(Ayuningtyas et al., 2018).
The mining industry in Indonesia is currently experiencing a phase of high production demands
to support national development. Studies indicate several accidents and occupational diseases in
mining operational areas related to workers' mental health issues. Data from various studies show
that 25.8% of miners in a subject study reported injuries in the past year. This results in an incidence
rate equivalent to 19.67 injuries per 200,000 work hours and almost 26.9% to 35.8% of moderate to
severe absenteeism cases. Additionally, there is an indication of increased symptoms of low back pain
(LBP), estimated to cause 805 lost workday cases due to LBP in a year, reducing company productivity
by USD 209,300 and national annual productivity by USD 200 million (Matamala Pizarro & Aguayo
Fuenzalida, 2021).
Demographic factors are the factors within the population structure of an area and its
development, such as gender, age group, education level, type of job, marital status, and so on (Hanum,
2018). Demographic conditions are associated with disparities in mental health status, such as
education status contributing to determining job type (Fiori et al., 2016). Other factors, such as
gender, length of employment, and age group, also play roles in determining mental health, especially
related to mining work where seniority and male workers significantly influence job priorities and
status (Liu et al., 2015). Therefore, the author conducted this study to determine the mental health
levels of mining industry workers and the demographic factors affecting mental health among PT X
mining workers.
2. Materials and Methods
This study is cross-sectional research with a quantitative analysis method to examine the
relationship between workers' demographic factors and the levels of depression, anxiety, and stress
among operational and non-operational division workers at PT X mining company. The research uses
the 21-item Depression Anxiety and Stress Scales (DASS-21) questionnaire, which has been
translated into Indonesian and administered through the MS Forms application. The questionnaire
assesses three types of mental health disorders: depression (dysphoria, hopelessness, devaluation of
life, self-criticism, lack of interest/involvement, anhedonia, and inertia); anxiety (autonomic arousal,
skeletal muscle effects, situational anxiety, and subjective experience of anxious affect); and stress
(difficulty relaxing, nervous arousal, and being easily upset/agitated, irritable/over-reactive, and
impatient). There are five rating scales: normal, mild, moderate, severe, and extremely severe (see
Table 1).
The relationship between mental health disorders and demographic factors (age, education
level, work location, gender, length of employment, and employment status) is analyzed using the chi-
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square test. To determine the variables most affecting the respondents' mental health, linear
regression analysis is used. A p-value <0.05 indicates a relationship between variables, while the sign
in the regression test indicates the influence of demographic factors on mental health disorders. The
r-square value indicates the extent of the influence of each demographic variable on mental health
symptoms.
This study was conducted from February 1 to February 28, 2023, with the population
comprising all permanent employees of PT X mining company working in Mimika Regency. PT X
mining company had a population of 29,439 employees during the study period. Most of the workers
are contractors, accounting for 75% of the total worker population, and the work locations are
divided into two major areas: highlands and lowlands. The research sample was determined using
simple random sampling with a 95% confidence level and a 5% margin of error. The minimum sample
size calculated was 380 workers.
Table 1 Recommended Severity Rankings for DASS21 Sub-scales in Indonesia
Depresion
Anxiety
Stress
Normal
0-9
0-7
0-14
Mild
10-13
8-9
15-18
Middle
14-20
10-14
19-25
Severe
21-27
15-19
26-33
Very Severe
28+
20+
34+
3. Result and Discussion
Respondent Characteristics
The data collection resulted in 764 total respondents who completed and validly submitted the
online questionnaire. Each sample represented the work location, with 466 respondents working in
the highland areas and 298 respondents working in the lowland areas. The average age distribution
of the respondents was 38 ± 9.03 years. The variable of respondents' work tenure ranged from 9.8 ±
7.6 years, indicating a diverse range of work experience from under 5 years to over 30 years.
Based on the education level category, 32% of the respondents were high school graduates or
below, while 68% were higher education graduates. The distribution of work locations showed that
61% of respondents worked in highland areas and 39% in lowland areas. In terms of gender, 71% of
the respondents were male, and 29% were female, reflecting the physical demands of mining work,
which is predominantly male-dominated. Regarding employment status, 37% of the respondents
were permanent employees of PT X, while 63% were contractors from PT X.
Table 2 Frequency of Depression, Anxiety, and Stress Among Study Respondents
Mental
Health
Symptom
s
Frekuency (N=764)
Normal
Mild
Middle
Severe
Very
Severe
Total Mental
Health
Symptoms
n
%
n
%
n
%
n
%
n
%
n
%
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Depresion
606
79.32%
80
10.47%
63
8.25%
15
1.96%
0
0
158
20.68%
Anxiety
509
66.62%
74
9.69%
134
17.54%
47
6.15%
0
0
255
33.38%
Stress
517
67.67%
197
25.79%
41
5.37%
9
1.18%
0
0
247
32.33%
Prevalence of Depression, Anxiety, and Stress among PT X Workers
The study found a 20.68% prevalence of depression among PT X workers, with 10.47%
experiencing mild depression, 8.25% moderate depression, and 2% severe depression; no
respondents experienced extremely severe depression. Regarding age, 8.23% of respondents in early
adulthood (18-40 years) and 9.82% in middle adulthood (41-60 years) experienced depression.
Regarding education level, 5.75% of respondents with high school education or below experienced
depression, and 14.92% of respondents with higher education experienced depression symptoms.
In terms of gender, 14.53% of the respondents experiencing depression were male, and 6.16%
were female. Regarding work location, 14.14% of respondents working in the highlands experienced
anxiety, and 6.54% of employees working in the lowlands experienced anxiety. Based on work tenure,
5.63% of respondents with less than 5 years of service, 7.45% with 5-10 years, and 7.6% with more
than 10 years of service experienced depression. The depression rate was 8.38% among permanent
employees, while 12.3% of the respondents experiencing depression were contractors.
Table 3 Descriptive Indicators of Depression Based on Demographic Data
Demographic
Characteristics
Depression Level
p-value
Not depressed
Mild
Middle
High
No
%
No
%
No
%
No
%
Age
Early
Adulthood
235
30.76%
34
4.45%
22
2.88%
7
0.92%
0.040
Middle
Adulthood
359
46.99%
46
6.02%
22
2.88%
7
0.92%
Late
Adulthood
12
1.57%
0
0.00%
0
0.00%
0
0.00%
Education
High School
or Below
197
25.79%
26
3.40%
15
1.96%
3
0.39%
0.218
Diploma
44
5.76%
6
0.79%
4
0.52%
0
0.00%
Bachelor's
Degree
313
40.97%
43
5.63%
36
4.71%
11
1.44%
Master's
Degree
52
6.81%
5
0.65%
8
1.05%
1
0.13%
Worl Locat
Highlands
358
46.86%
54
7.07%
44
5.76%
10
1.31%
0.469
Lowlands
248
32.46%
26
3.40%
19
2.49%
5
0.65%
Gender
Male
463
60.60%
60
7.85%
42
5.50%
9
1.18%
0.311
Female
143
18.72%
20
2.62%
21
2.75%
6
0.79%
Years of
Service
Less than 5
years
191
25.00%
21
2.75%
18
2.36%
4
0.52%
0.767
5 - 10 Years
156
20.42%
27
3.53%
26
3.40%
4
0.52%
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11 - 20 Years
191
25.00%
24
3.14%
17
2.23%
4
0.52%
More than 20
years
68
8.90%
8
1.05%
2
0.26%
3
0.39%
Employmen
t Status
Permanent
Employee
218
28.53%
25
3.27%
30
3.93%
9
1.18%
0.092
Contractor
388
50.79%
55
7.20%
33
4.32%
6
0.79%
The study found a 33.38% prevalence of anxiety among PT X workers, with 9.69% experiencing
mild anxiety, 17.54% moderate anxiety, 6.15% severe anxiety, and no extremely severe anxiety
detected. Regarding age, 18.32% of respondents in early adulthood (18-40 years) experienced
anxiety, 14.53% in middle adulthood (41-60 years), and 1.57% in late adulthood (above 60 years).
Regarding education level, 7.98% of respondents with high school education or below experienced
anxiety, while 25.4% with higher education experienced anxiety symptoms.
In terms of gender, 21.72% of the respondents experiencing anxiety were male, and 11.66%
were female. Regarding work location, 22.51% of respondents working in the highlands experienced
anxiety, and 10.87% of employees working in the lowlands experienced anxiety. Based on work
tenure, 11.12% of respondents with less than 5 years of service, 10.61% with 5-10 years, and 11.11%
with more than 10 years of service experienced anxiety. The anxiety rate was 12.96% among
permanent employees, while 20.24% of the respondents experiencing anxiety were contractors.
Table 4 Descriptive Indicators of Anxiety Based on Demographic Data
Demographic
Characteristics
Anxiety Level
p-value
Not depressed
Mild
Middle
High
No
%
No
%
No
%
No
%
Age
Early
Adulthood
178
23.30%
38
4.97%
68
8.90%
34
4.45%
0.040
Middle
Adulthood
319
41.75%
36
4.71%
66
8.64%
9
1.18%
Late
Adulthood
12
1.57%
0
0.00%
0
0.00%
0
0.00%
Education
High School
or Below
180
23.56%
15
1.96%
35
4.58%
11
1.44%
0.005
Diploma
39
5.10%
7
0.92%
5
0.65%
3
0.39%
Bachelor's
Degree
247
32.33%
49
6.41%
78
10.21%
29
3.80%
Master's
Degree
43
5.63%
5
0.65%
14
1.83%
4
0.52%
Worl Locat
Highlands
294
38.48%
48
6.28%
90
11.78%
34
4.45%
0.079
Lowlands
215
28.14%
26
3.40%
44
5.76%
13
1.70%
Gender
Male
408
53.40%
49
6.41%
91
11.91%
26
3.40%
0.000
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Female
101
13.22%
25
3.27%
43
5.63%
21
2.75%
Years of
Service
Less than 5
years
149
19.50%
27
3.53%
37
4.84%
21
2.75%
0.007
5 - 10 Years
132
17.28%
20
2.62%
44
5.76%
17
2.23%
11 - 20 Years
165
21.60%
21
2.75%
44
5.76%
6
0.79%
More than
20 years
63
8.25%
6
0.79%
9
1.18%
3
0.39%
Employment
Status
Permanent
Employee
183
23.95%
31
4.06%
52
6.81%
16
2.09%
0.807
Contractor
326
42.67%
43
5.63%
82
10.73%
31
4.06%
Prevalence of Stress Among PT X Workers
The research results show that the prevalence of stress among PT X workers is 32.33%, with
25.79% experiencing mild stress, 5.73% moderate stress, 1.18% severe stress, and no cases of
extremely severe stress detected. Based on age, 14.53% of respondents in early adulthood (18–40
years) experienced stress, 17.54% in midlife (41–60 years), and 0.26% in late adulthood (over 60
years). Based on education level, 8.64% of respondents with high school education or lower
experienced stress, while 23.7% of those with higher education experienced stress symptoms.
Classification of anxiety based on gender: 22.12% of respondents experiencing anxiety are
male, and 10.20% of respondents are female. Based on work location: 20.02% of respondents
working in highland areas experience anxiety, while 11.91% of employees working in lowland areas
experience anxiety. Based on years of service: 7.72% of respondents with less than 5 years of service
experience anxiety, 10.46% of respondents with 5-10 years of service experience anxiety, and
14.26% of respondents with more than 10 years of service experience anxiety. The level of anxiety
is 12.96% among permanent employees, while 19.38% of the anxiety level is from respondents who
are contractor employees.
Table 5 Descriptive Indicators of Work Stress Based on Demographic Data
Demographic
Characteristics
Stress Level
p-value
Not depressed
Mild
Middle
High
No
%
No
%
No
%
No
%
Age
Early
Adulthood
207
27.09%
83
10.86%
21
2.75%
7
0.92%
0.000
Middle
Adulthood
300
39.27%
112
14.66%
20
2.62%
2
0.26%
Late
Adulthood
10
1.31%
2
0.26%
0
0.00%
0
0.00%
Education
High School
or Below
175
22.91%
51
6.68%
12
1.57%
3
0.39%
0.711
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Diploma
38
4.97%
14
1.83%
2
0.26%
0
0.00%
Bachelor's
Degree
258
33.77%
118
15.45%
21
2.75%
6
0.79%
Master's
Degree
46
6.02%
14
1.83%
6
0.79%
0
0.00%
Worl Locat
Highlands
312
40.84%
117
15.31%
31
4.06%
5
0.65%
0.281
Lowlands
205
26.83%
80
10.47%
9
1.18%
2
0.26%
Gender
Male
405
53.01%
136
17.80%
27
3.53%
6
0.79%
0.016
Female
112
14.66%
61
7.98%
14
1.83%
3
0.39%
Years of
Service
Less than 5
years
175
22.91%
47
6.15%
9
1.18%
3
0.39%
0.834
5 - 10 Years
133
17.41%
61
7.98%
15
1.96%
4
0.52%
11 - 20 Years
146
19.11%
75
9.82%
14
1.83%
1
0.13%
More than
20 years
63
8.25%
14
1.83%
4
0.52%
1
0.13%
Employment
Status
Permanent
Employee
183
23.95%
79
10.34%
17
2.23%
3
0.39%
0.987
Contractor
334
43.72%
118
15.45%
24
3.14%
6
0.79%
Relationship Between Demographic Factors and Mental Health
Table 3 shows the relationship between demographic variables and depression levels among
respondents. Only age shows a significant relationship with depression levels (p=0.04). Other
demographic variables, including education level, work location, gender, work duration, and
employment status, do not show a significant relationship in statistical analysis.
Table 4 shows the relationship between demographic variables and anxiety levels among
respondents. Age, education level, gender, and work duration variables show a significant
relationship with anxiety levels (p ≤ 0.05). Work location and employment status variables do not
show a significant relationship in statistical analysis.
Table 5 shows the relationship between demographic variables and stress levels among
respondents. Age and gender variables show a significant relationship with stress levels (p ≤ 0.05).
Education level, work location, work duration, and employment status variables do not show a
significant relationship in statistical analysis.
Table 6 shows the results of the multivariate analysis of demographic variables of workers
with mental health symptoms. The variable of age (sig = 0.000) is the only variable that has an
influence on increasing the occurrence of depression in workers by 1.5%. Other variables such as
education, work location, gender, years of service, and employment status do not have an influence
on causing an increase in depression in the workplace. In the multivariate analysis related to the
influence on anxiety among workers, the variables of age, education, gender, and years of service
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have an influence on increasing anxiety among workers (sig ≤ 0.05). Age has an influence on
increasing anxiety by 3% in the population, followed by gender which can increase by 2.6%,
education level has an influence of 1.2% on the anxiety levels of workers, and years of service have
an influence of less than 1%. In the multivariate analysis related to stress levels among workers, the
variables of age and gender (sig ≤ 0.05) have an influence of less than 1% related to the increase in
work stress among workers.
Discussion
The results of this study show that, in general, the mental health condition of the workers in the
study is normal, without mental health issues such as depression, anxiety, and stress. However,
around 20.68% are indicated to have depression, 33.38% anxiety, and 32.33% stress with varying
levels of mental disorder (low, moderate, and high). These results differ when compared to a study
conducted on mine workers in remote areas of Australia, which showed higher levels of depression
at 28.3%, and lower levels of anxiety and stress at 22.3% and 19.4%, respectively (Vojnovic & Bahn,
2015). Two studies conducted on mine workers in China showed depression rates of 62.8% and
26.5%, which are higher compared to this study (Joaquim et al., 2018; Liu et al., 2014). Another study
on mine workers in southern Brazil showed that only 3.5% of respondents experienced depression
and 13% experienced anxiety, which are lower compared to this study (Joaquim et al., 2018). Other
studies by Velander (2010), Keown (2005), Bowers (2015), and Miller (2014) reported mental health
issues among respondents ranging from 24.5% to 33%. From comparing this study with similar
studies in the same industry, it can be concluded that the mental health symptoms level in this study
is consistent with others. This consistency is due to similar demographic factors.
This study also identifies significant variables affecting the levels of depression, anxiety, and
stress among workers in PT X mining company. The variable that directly affects all three aspects of
mental health (depression, anxiety, and stress) is age. According to a study by Ferraro & Wilkinson
(1992) in the Handbook of Sociology of Mental Health, mental health levels tend to increase from ages
18 to 40 and decrease above age 40. This study also aligns with the finding that as workers age, they
exhibit better mental health symptoms (Ferraro & Wilkinson, 2013). This is due to life experience and
a more mature level of maturity in solving problems (Spoorthy et al., 2020). Additionally, age is the
demographic factor with the greatest influence on determining mental health levels, as older
individuals tend to have improved cognitive and emotional control abilities (Höglund et al., 2020).
In this study, anxiety levels among workers are also influenced by gender and education levels.
The study found that female workers have higher anxiety levels compared to male workers. According
to research by Eaton (2011), women are more likely to internalize emotions compared to men (Eaton
et al., 2012). This self-internalization leads women with mental health issues to withdraw, experience
loneliness, and ruminate on their problems. This differs from male workers, who tend to be more
aggressive, impulsive, and coercive, thus more easily expressing their pressures and coping with
mental health issues (Ma et al., 2019). Another factor related to higher anxiety levels in female
workers in the mining sector is the difficulty in adapting to living in remote areas away from their
families (Eiter et al., 2023).
The education level variable also influences the occurrence of anxiety among workers in this
study. The research shows that workers with higher education levels have higher anxiety levels
compared to those with lower education levels. According to a literature review by Asare-Doku et al.
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(2020), there is an influence of education level on mental health status; higher education levels are
associated with higher positions and greater, more complex responsibilities, leading to increased
work pressure as a cause of mental disorders among workers. In the context of the company where
the study was conducted, the company is undergoing a transition where several new employees with
higher education levels hold more complex positions and projects, resulting in higher anxiety levels.
Furthermore, higher education levels are related to higher expectations of the work being done,
leading to decreased mental health when reality does not meet expectations (Cohen et al., 2020).
The study also shows that age and education levels influence stress levels among workers.
Groups with higher education levels tend to have higher work stress levels compared to groups with
lower education levels. This is inconsistent with the study by Lunau in 2015, which found that
workers with lower education levels have consistently higher work stress levels across various
European studies. This is because education level is related to better skills and knowledge of work
methods compared to workers with lower education levels (Lunau et al., 2015). In practice,
workplace skills and knowledge are not only obtained through formal education but also through
training and on-the-job practice, making workers more accustomed to meeting expected work
standards. Additionally, there are common practices in companies to assign more analytical and novel
tasks to younger workers with higher education levels, while senior workers are given more routine
tasks, resulting in significant differences in work stress related to education level (Bhui et al., 2016).
Limitations of the Study
This study only considers the influence of a limited range of demographic factors, including age,
education level, work location, gender, years of service, and employment status. Based on various
references, other variables such as work shifts, employment level, and direct factors affecting mental
health, such as disagreement and uncertainty, role clarity, supervisor support, workload, and work
hours, should also be considered to identify the most significant influences on mental health
symptoms among workers. Additionally, the cross-sectional nature of the study with a short
timeframe and unbalanced sample proportion due to voluntary questionnaires means not all
managerial levels and workers are covered, which provides an opportunity for improvement in future
studies.
4. Conclusion
Workers at PT X are identified to have mental health issues, including depression, anxiety, and
stress. Various demographic factors show a relationship with mental health complaints. Age is related
to all three mental health issues, while gender affects anxiety and stress, and education level and years
of service are related to anxiety. Recommendations to reduce mental health issues in the study
location include raising worker awareness through mental health education programs. Education
through socialization can increase workers' awareness of early mental health symptoms and seek
medical help promptly. Additionally, increasing the number of psychiatrists as consultants for
workers' mental health should be considered. The company should also create a comprehensive
mental health management program involving worker participation, management, HR, medical
personnel, and occupational health.
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