Association between Noise Exposure and Occupational Stress among Coal Miners

Abstract

Background:

Detrimental occupational environmental exposure constitutes a significant external factor influencing occupational stress. This study aimed to examine the correlation between noise exposure and the risk of occupational stress in coal miners.

Methods:

This cross-sectional study employed data from a specialized occupational health survey conducted in 2023 at a large-scale coal mine in Gansu Province, China, an industry distinguished by elevated noise exposure levels. A total of 447 qualified participants were included in the final analysis. The correlation between noise exposure and occupational stress was examined using binary logistic regression. A restricted cubic spline (RCS) model was utilized to investigate the dose–response connection between these two variables. Subgroup analyses were conducted to explore the association across various population strata.

Results:

This study indicates that the prevalence of occupational stress is 48.99%. Statistically significant differences were observed between the occupational stress group and the non-occupational stress group regarding age, gender, physical exercise, type of employment, duration of service, and noise exposure level (all P < 0.05). Following the adjustment for multiple confounding variables, multivariate logistic regression analysis indicated that noise exposure was a significant independent risk factor for occupational stress (P = 0.003). RCS analysis further confirmed a dose–response association between noise exposure and occupational stress, demonstrating that the risk of occupational stress rose progressively with escalating noise exposure intensity. Subgroup analysis not only validated this positive link but also established a robust correlation between noise exposure and occupational stress (odds ratio = 2.560, 95% confidence intervals: 1.550–4.230, P < 0.001).

Conclusion:

This study’s results indicate that prolonged noise exposure among coal miners correlates with an elevated risk of occupational stress. These findings may assist in formulating health management strategies for individuals with varying degrees of noise exposure.

KEY MESSAGES

• (1)This cross-sectional study identified a high prevalence of occupational stress among coal miners, indicating a notable substantial occupational health risk for this occupational group.
• (2)The findings confirm a significant positive association between high noise exposure and a substantially increased risk of occupational stress in coal miners.
• (3)It is advisable to strengthen noise-related protective measures and implement comprehensive dynamic monitoring of noise levels in mining workplaces; these measures are expected to effectively alleviate the burden of occupational stress and safeguard the physical and mental health of coal miners.

Introduction

Occupational stress has become a critical public health issue of global concern. It denotes a psychophysiological condition wherein an individual’s abilities, resources, or support systems are inadequate to cope with job-related demands, thereby eliciting negative psychological, physiological, and physical reactions, along with a range of harmful consequences.[1] Despite significant progress in occupational health psychology concerning the relationship between job strain and health, the precise influence of physical workplace environmental factors, particularly noise, in the development and progression of occupational stress remains relatively underinvestigated.

Noise pollution constitutes a widespread occupational environmental risk. Prolonged exposure to noise can result in degenerative damage to auditory hair cells or neurons, culminating in irreversible hearing loss, particularly with chronic, recurrent exposure. Significantly, such auditory damage is predominantly irreversible upon occurrence. It not only severely diminishes patients’ quality of daily life but also imposes extensive and deep negative effects on broader socioeconomic systems.[2]

Noise is often defined as any undesirable, unpleasant, irritating, or detrimental mechanical vibration conveyed through a medium. Its harmful consequences transcend auditory impairment, impacting other physiological systems, including the neurological, cardiovascular, and endocrine systems. Moreover, noise exposure significantly impacts psychological well-being and behavioral safety.[3] While the underlying mechanisms remain incompletely understood, existing evidence indicates that chronic noise exposure may contribute to the onset and advancement of cardiovascular diseases by eliciting prolonged stress responses, enhancing the secretion of stress hormones, and consequently triggering a series of pathophysiological alterations.[4,5] Extended exposure to high-noise situations may create chronic stress, exacerbating occupational stress in susceptible individuals.

Noise during coal processing mostly originates from the operation of various production-line machinery. From a physical perspective, such noise results from the superposition and erratic interaction of several sound waves. Principal sources encompass the dynamic elements of machinery and processing activities, including crushing or grinding.[6] Humans cannot genuinely acclimate to noise, and its detrimental effects generally compound with extended exposure. In industrial environments, such as coal processing, high-intensity noise pollution presents significant health hazards, including long-term hearing impairment and indirect safety-related accidents, while also severely hindering workers’ auditory function and verbal communication skills. Such impairment frequently results in an inability to recognize warning signals, markedly elevating the danger of operational errors and safety mishaps. Moreover, the necessity to elevate voice intensity for communication in high-noise settings exacerbates physiological strain and psychological stress among employees.[7,8]

While comprehensive studies have established that psychosocial factors, such as job discontent and an increased sense of responsibility, are significant contributors to occupational stress,[9] the influence of physical conditions in the workplace, especially occupational noise, remains underexplored. Current research predominantly emphasizes the terminal effects of noise exposure (e.g., auditory impairment or cardiovascular consequences), with insufficient focus on its function as a chronic stressor in the emergence of psychological stress. To address this gap, this study examines the relationship between occupational noise exposure and the risk of occupational stress in coal miners. We put up the subsequent hypotheses:

H1: A substantial positive correlation appears between occupational noise exposure levels and occupational stress ratings in coal miners.

H2: The risk of occupational stress and the strength of the correlation with noise exposure differ among coal miners of various work classifications.

MATERIALS AND METHODS

Study Design

This study utilized a cross-sectional methodology, collecting data from 447 coal miners employed by a major coal mining company in Gansu Province between July and October 2023. This study surveyed a total of 516 workers. After verification, 69 questionnaires were discarded due to missing critical information or logical flaws in responses, resulting in 447 participants being included for statistical analysis. The Medical Ethics Committee of the Institute of Occupational Health and Poisoning Control, Chinese Center for Disease Control and Prevention, accepted the study protocol (Approval No.: NIOHP202324).

Inclusion and Exclusion Criteria

Inclusion criteria were as follows: (1) employees in underground or surface production roles at the coal mining enterprise, with a minimum of 1 year of employment; (2) aged 20–60 years, representing the principal working-age demographic in the coal mining sector; (3) no significant job transfers or role alterations within the preceding 6 months; (4) provided written informed consent and voluntarily consented to participate in the study.

Exclusion criteria were as follows: (1) individuals with severe cardiovascular diseases, clinically verified psychological or psychiatric disorders (e.g., major depressive disorder, generalized anxiety disorder), or diagnosed hearing impairment; (2) individuals with communication challenges or inability to comprehend the survey material; (3) incomplete questionnaires or those containing logically inconsistent responses were excluded upon verification.

Noise Data Collection

Workplace noise levels were assessed in strict compliance with the National Standard of the People’s Republic of China “Classification of Occupational Hazards at Workplaces—Part 4: Noise” (GBZ/T 229.4-2012).[10] Representative sampling points were established in each working environment for coal miners, based on the distribution of primary activity areas and potential noise sources. For fixed positions, such as shearer operating points, sampling points were allocated according to sound field uniformity, with a minimum of 3 points for uniform sound fields and additional points for non-uniform sound fields. For mobile positions, such as inspection workers, noise exposure was monitored using individual noise dosimeters. During measurements, the microphone height was meticulously established in accordance with the standard (1.50 m for standing positions and 1.10 m for sitting positions), and the instrument was directed toward the primary sound source. Individual noise dosimeters were employed to gather noise exposure data. This standard defines noise-exposed work as tasks conducted in an environment where excessive sound may compromise hearing, harm health, or induce other detrimental effects, specifically, where the equivalent continuous A-weighted sound pressure level (LAeq) is ≥80 dB(A) over an 8-hour workday or 40-hour workweek. Utilizing these measures, the 8-hour equivalent noise exposure level (LAeq, 8h) was computed for each worker, and a systematic database of occupational noise exposure was established for further study and assessment.

General Information

This study utilized a standardized Health Status Questionnaire for Workers in Noise-Exposed Industries, created by the National Institute of Occupational Health, Chinese Center for Disease Control and Prevention, to gather data on the demographic characteristics, lifestyle habits, and psychological health status of coal miners in Gansu Province. Demographic information encompassed age, sex, body mass index (BMI), marital status, and educational attainment. Lifestyle factors included smoking status, alcohol use, and physical activity behaviors. Psychological health evaluations encompassed occupational stress, anxiety, and depression. Occupational safety concentrates on examining the use of personal protective equipment, including anti-noise earplugs and dust masks.

Occupational Stress

This study employed the standardized Core Occupational Stress Scale (COSS), created by the National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, to evaluate occupational stress in coal miners. The measure consists of 17 items that encompass four principal dimensions: social support, organizational rewards, work demands and effort, and work autonomy. Each topic is evaluated using a 5-point Likert scale, with responses spanning from “strongly disagree” (1 point) to “strongly agree” (5 points). The total score is calculated by aggregating the scores of all items; occupational stress is deemed present when the total score reaches 50 or higher, with higher scores signifying more severe levels of occupational stress.[11] The cumulative COSS of Cronbach α coefficients was 0.779.[12]

Anxiety and Depression Levels

The Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) were utilized to evaluate anxiety and depression symptoms in coal miners. Each of the two scales consists of 20 items, comprising 15 positively scored items and 5 reverse-scored items. Both utilize a 4-point rating scale predicated on symptom frequency. The initial total score is calculated by aggregating the scores of all items; this score is subsequently transformed into a standard score by multiplying it by 1.25 and rounding the outcome to the nearest integer. According to Chinese norms, an SAS standard score ≥50 signifies the presence of anxiety symptoms, while a score of <50 indicates the absence of clinical anxiety. For the SDS, a standard score of ≥53 signifies depressive symptoms, whereas a score below 53 is considered normal.[13] The Cronbach α coefficients for the SAS and SDS were 0.945 and 0.905, respectively, while their Guttman split-half coefficients were 0.927 and 0.837, respectively.[14]

Statistical Methods

Continuous variables were assessed for normality via the Shapiro-Wilk test and are presented as mean ± standard deviation (x̄±s) if normally distributed, or median (interquartile range [IQR] if not. Categorical variables are summarized as n (%). Comparisons between groups were conducted using independent samples t-tests (for normally distributed, homoscedastic continuous variables, confirmed by Levene’s test) or chi-square tests. All statistical analyses were conducted using two-tailed tests. Multicollinearity among independent variables was evaluated by variance inflation factors (VIF), where a VIF of <10 signifies the absence of significant multicollinearity.

Binary logistic regression was utilized to investigate the relationship between noise exposure and the risk of occupational stress. The equivalent noise exposure level was classified into four quartile groups (considered as an ordinal variable), and three sequential models were developed: Model 1 was crude; Model 2 was adjusted for demographic variables (sex, age, BMI, education level, and marital status); and Model 3 included additional adjustments for smoking status, alcohol consumption, physical exercise habits, job type, employment tenure, and use of protective equipment, building upon Model 2. To evaluate dose–response trends, the median value of each quartile group was incorporated as a continuous variable in the regression model to analyze trends.

Furthermore, restricted cubic splines (RCSs) were employed to investigate the potential nonlinear correlation between noise exposure level and the probability of occupational stress, adjusting for all factors in Model 3; matching curves were produced to illustrate this link.

Subgroup analyses were performed utilizing multivariate logistic regression, categorized by sex (male, female), age (<40, ≥40), BMI (<24, ≥24), education level (senior high school, associate degree, bachelor’s degree), marital status (no spouse, having a spouse), smoking (no, yes), drinking (no, yes), physical exercise (no, 1–2 times, 3–4 times, 5 times or more), job type (office workers, ground workers, underground workers), employment tenure (<10, ≥10), and hearing protection devices (no, yes). Interaction variables between noise exposure and each stratifying variable were integrated into the overall model to assess effect modification. All results are reported as odds ratios (OR) with 95% confidence intervals (95% CI), along with P-values and interaction P-values. All statistical analyses were conducted using R software (Version 4.3.1; R Foundation for Statistical Computing, Vienna, Austria), and all figures were produced with the same software.

RESULTS

General Data

A total of 447 coal miners participated in this study, of whom 219 (48.99%) were identified as experiencing occupational stress. The occupational stress group exhibited a mean score of 55.05 ± 4.63, whereas the non-occupational stress group (n = 228) demonstrated a mean score of 41.13 ± 6.77. Among all participants, 247 (55.26%) were males and 200 (44.74%) were females; within the occupational stress group, the males’ and females’ proportions were 54.25% and 42.50%, respectively. The mean age of the study population was 38.02 ± 7.21 years, with an average employment tenure of 13.21 ± 7.96 years. The average equivalent noise exposure level was 74.20 ± 6.71 dB(A) in the occupational stress group and 72.31 ± 6.32 dB(A) in the non-occupational stress group, resulting in an overall mean of 73.24 ± 6.61 dB(A) for all participants. There were 364 (81.43%) cases with sound levels below 80 dB(A), 56 (12.53%) cases with sound levels between 80 and 85 dB(A), and 27 (6.04 %) cases with sound levels beyond 85 dB(A). There were 76 (17.00%) office workers, 242 (54.14%) ground workers, and 129 (28.86%) underground workers. Within the occupational stress category, the percentages of office workers, ground workers, and subterranean workers were 38.16%, 46.70%, and 59.69%, respectively. Concerning educational attainment, 59.51% (n = 266) of participants possessed an associate degree or more, and the predominant marital status was married (89.93%, n = 402). For lifestyle indicators, 34.00% (n = 152) were smokers, 37.36% (n = 167) used alcohol, and 55.93% (n = 250) participated in physical activity 1–2 times weekly. Regarding workplace safety, 46.09% (n = 206) of employees indicated the utilization of hearing protection devices. The average standardized scores for mental health markers were 46.35 ± 11.91 for the SAS and 54.12 ± 10.87 for the SDS.

Intergroup analyses revealed statistically significant differences in age, gender, physical exercise, noise, job type, woke age, and SAS and SDS scores between the occupational stress group (n = 219) and the non-occupational stress group (n = 228) (all P < 0.05). In contrast, no substantial variations were observed in BMI, educational attainment, marital status, smoking, drinking, or use of hearing protection devices [Table 1].

Table 1.

Comparison of general data between the non-occupational stress group and occupational stress groups

General data	Total sample (n = 447)	Non-occupational stress group (n = 228)	Occupational stress group (n = 219)	P
Age	38.02 ± 7.21	39.48 ± 7.08	36.49 ± 7.04	<0.001
BMI, Mean (kg/m2)	23.46 ± 3.21	23.24 ± 3.15	23.69 ± 3.26	0.097
Gender				0.018
Male	247	113 (45.75)	134 (54.25)
Female	200	115 (57.50)	85 (42.50)
Education level				0.640
Senior High School	181	89 (49.17)	92 (50.83)
Associate Degree	166	84 (50.60)	82 (49.40)
Bachelor’s Degree	100	55 (55.00)	45 (45.00)
Marital status				0.086
No spouse	45	17 (37.78)	28 (62.22)
Having a spouse	402	211 (52.49)	191 (47.51)
Smoking				0.160
No	295	158 (53.56)	137 (46.44)
Yes	152	70 (46.05)	82 (53.95)
Drinking				0.600
No	280	146 (52.14)	134 (47.86)
Yes	167	82 (49.10)	85 (50.90)
Physical exercise				0.015
No	74	28 (37.84)	46 (62.16)
1–2 times	250	125 (50.00)	125 (50.00)
3–4 times	70	41 (58.57)	29 (41.43)
5 times or more	53	34 (64.15)	19 (35.85)
Job type				0.007
Office workers	76	47(61.84)	29 (38.16)
Ground workers	242	129(53.30)	113(46.70)
Underground workers	129	52(40.31)	77(59.69)
Hearing protection devices				0.936
No	241	122 (50.62)	119 (49.38)
Yes	206	106 (51.46)	100 (48.54)
Noise (dB(A))	73.24±6.61	72.31±6.34	74.20±6.76	<0.001
Employment tenure	13.21±7.96	13.79±8.15	12.61±7.73	0.021
SAS score	46.35±11.91	41.94±10.80	50.94±11.28	<0.001
SDS score	54.12±10.87	50.33±11.09	58.05±9.12	<0.001

Notes: BMI, body mass index; SAS, Self-Rating Anxiety Scale; SDS, Self-Rating Depression Scale.

Logistic Regression Analysis of Noise and Occupational Stress

Table 2 displays the findings of the logistic regression analysis investigating the relationship between noise exposure and occupational stress. Before the analysis, multicollinearity diagnostics were performed on all independent variables; the VIF for each variable was below 5, signifying the absence of significant multicollinearity. Utilizing the Q1 noise exposure group as the reference, the fully adjusted model (Model 3) indicated that the risk of occupational stress in the Q2, Q3, and Q4 groups was 0.904 times (OR = 0.904, 95% CI: 0.494–1.653, P = 0.743), 1.436 times (OR = 1.436, 95% CI: 0.831–2.495, P = 0.196), and 2.559 times (OR = 2.559, 95% CI: 1.368–4.872, P = 0.004) that of the Q1 group, respectively. All three models demonstrated a statistically significant increase in the risk of occupational stress with higher quartiles of noise exposure (P for trend < 0.05).

Table 2.

Correlation between noise exposure and occupational stress

Noise IQR(dB(A))	Model 1 OR (95%CI)	P	Model 2 OR (95%CI)	P	Model 3 OR (95%CI)	P
Q1(64,69)	Ref		Ref		Ref
Q2(69,71)	0.872(0.521–1.457)	0.601	0.806(0.451–1.435)	0.463	0.904(0.494∼1.653)	0.743
Q3(71,76)	1.329(0.503–2.208)	0.270	1.373(0.808–2.340)	0.242	1.436(0.831∼2.495)	0.196
Q4(76,98)	2.761(1.553–4.997)	<0.001	2.682(1.471∼4.976)	<0.001	2.559(1.368∼4.872)	0.004
P for trend	<0.001		<0.001		0.003

Notes: CI, confidence interval; IQR, interquartile range; OR, odds ratio.

Nonlinear Relationship between Noise and Occupational Stress

[Figure 1] illustrates the outcomes of the RCS regression analysis. No significant nonlinear connection was detected between noise exposure and the likelihood of occupational stress among all individuals (overall P = 0.039, nonlinear P = 0.364). An evident upward trend in the risk of occupational stress was observed with escalating levels of noise exposure.

Figure 1.

Through the restricted cubic spline regression model, a dose–response relationship between noise and occupational stress was observed. The solid line represents the OR, and the shadow area represents the 95% CI.

Subgroup Analysis

Subgroup analysis revealed a strong positive correlation between noise exposure and occupational stress (overall OR = 2.56, 95% CI: 1.55–4.23), with notable variation among population subgroups categorized by various characteristics. This positive association was especially evident in the following subgroups: younger individuals (<40 years), males, participants with a lower BMI (<24 kg/m²), those with higher education (associate degree or above), married individuals, both smokers and non-smokers, non-alcohol consumers, regular exercisers (1–2 times/week), individuals with shorter work tenure (<10 years), underground workers, and those utilizing protective equipment.

Educational attainment demonstrated a distinct “dose–response” gradient: as educational levels increased from senior high school to associate degree and subsequently to bachelor’s degree, the OR escalated from a non-significant 1.89 (OR = 1.89, P = 0.090) to 2.87 (OR = 2.87, P = 0.015) and 4.12 (OR = 4.12, P = 0.023), respectively. Despite the variation in impact sizes among subgroups, all interaction tests yielded non-significant results (P for interaction >0.05). This indicates that the impact of noise exposure on occupational stress is uniform among subgroups with varying characteristics. Comprehensive results are illustrated in [Figure 2].

Figure 2.

Subgroup analysis of the correlation between noise and occupational stress.

DISCUSSION

This study identified a significant positive correlation between elevated noise exposure levels and a heightened risk of occupational stress, with the intensity of this correlation varying among subgroups categorized by age, gender, and other demographic or occupational variables. After adjusting for several potential confounders, noise exposure remained independently linked to an increased incidence of occupational stress, indicating that noise may serve as a significant risk factor for occupational stress among coal miners.

In workplace environments, noise constitutes a prevalent physical hazard that can lead to hearing loss,[15] while simultaneously serving as a catalyst for occupational stress via a complex multi-system pathway involving intricate interactions among physiological regulatory mechanisms, psychological response processes, and behavioral adaptation patterns.[16] Chronic irritation and sleep disturbance are significant factors in the onset and advancement of noise-related non-communicable diseases, affecting several aspects of physiological and psychological health.[17] Occupational stress is frequently associated with the activation of particular neuroendocrine pathways.[18] As a common environmental stressor, noise can provoke a systemic stress response marked by the simultaneous activation of the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic nervous system. This mechanism may occur via two distinct pathways: firstly, prolonged exposure to high-intensity noise directly increases stress hormone levels, indicating HPA axis activation; secondly, communication challenges and diminished work efficiency due to noise interference indirectly intensify the psychological burden, thereby establishing a detrimental cycle between physiological and psychological stress responses.[19,20]

The subgroup analysis in this study indicated that while effect estimates varied significantly among demographic characteristics, none of the interaction tests achieved statistical significance (P for interaction >0.05). This indicates that we cannot definitively ascertain statistically significant differences in the strength of the association between noise exposure and occupational stress across these populations. Nevertheless, the identified tendencies provide significant insights for targeted preventative initiatives. The correlation between noise exposure and occupational stress was more evident in participants under 40 years of age, while no significant correlation was observed in those aged 40 or older. This discrepancy may be ascribed to the diminished long-term adaptation to professional tasks in younger individuals, rendering them more vulnerable to heightened cognitive burden and emotional strain induced by noise interference.[21,22] A significant correlation between noise exposure and occupational stress was identified in those with an associate degree or higher, while no such effect was observed in workers with a high school education or lower. This disparity may pertain to increased understanding of workplace health hazards and a heightened recognition of the long-term health effects of noise among better-educated employees. The adverse cognitive evaluation of noise may intensify psychological stress responses.[23,24] Marital status proved to be a significant factor: a more pronounced correlation between noise exposure and occupational stress was identified in married individuals. Increased economic and familial obligations may intensify stress responses in this demographic, as workplace noise is regarded not only as a health hazard but also as a potential threat to domestic stability. The combination of these two stressors is likely to create psychological tension.[25] In contrast to ground and office workers, underground workers face chronic exposure to elevated noise levels and operate within a high-risk, high-burden environment marked by various stressors, including confined spaces, insufficient ventilation, low visibility, and elevated safety accident risks. The combined impact of these factors considerably intensifies workers’ psychological strain.[26] In conclusion, although no statistically significant interactions were identified in the subgroup analyses of this investigation, the discerned trend patterns possess evident public health implications. Initially, delineating the population experiencing occupational stress is essential for contextualizing the results of our study. Secondly, the continuous correlation between noise exposure and occupational stress observed across several subgroups enhances the validity of our primary findings. Thirdly, even without substantial interaction effects, examining pattern characteristics within subgroups might yield valuable hypotheses for future studies on effect modification with higher sample sizes.

These findings underscore the importance of integrating relevant individual characteristics, such as age, marital status, educational level, and anxiety or depression status, into both noise-related research on coal miners and the design of targeted intervention strategies. This method will enable the development of more specific and tailored health promotion strategies and disease prevention efforts for subpopulations with unique noise exposure-related risk characteristics.

Based on the aforementioned findings, we offer the following actionable strategies for coal mining enterprises: primarily, systematic noise control should be included in the occupational health and safety management system, and both engineering protective measures and administrative controls should be enforced for roles whose equivalent noise exposure levels meet or surpass 80 dB(A). Secondly, specialized noise-related health literacy education should be provided to groups with high noise exposure intensity, particularly targeting coal mine underground workers, and should emphasize the correct use of personal protective equipment and the underlying scientific protective mechanisms. Moreover, systematic evaluations of occupational stress should be incorporated into routine health examination protocols for coal miners, thereby creating a proactive psychological monitoring system to serve as an early warning mechanism for workers consistently exposed to occupational noise levels surpassing 75 dB(A).

Limitations

This study is subject to several limitations that should be noted. First, the limited sample size and the concentration of participants in a specific occupational role (primarily coal miners) may constrain the generalizability of the findings to other industries or a broader working population. Second, potential confounding variables, such as concurrent exposure to dust and vibration, were not fully adjusted for, which may have introduced residual confounding into the model estimates. Furthermore, the cross-sectional design precludes any causal inference between noise exposure and occupational stress, as the data only represent a single snapshot in time. Future large-scale prospective studies, preferably conducted within coal mining populations, are warranted to verify and elucidate the causal pathways.

CONCLUSION

This study demonstrates a significant positive correlation between workplace noise exposure and occupational stress risk, with higher-intensity exposure leading to a marked increase in incidence. These results not only provide empirical evidence for the early identification and targeted intervention of occupational stress but also establish a theoretical foundation for formulating scientifically grounded preventive strategies. Consequently, the findings hold substantial practical significance for advancing psychological health initiatives among occupational groups.

Availability of Data and Materials

The data used and analyzed in this study are available from the corresponding author upon reasonable request.

Author Contributions

WenQi Jiang: Methodology, Writing-Original Draft. XueFei Li and ChangYan Yu: Resources, Editing. ZhenXia Kou and ShuLin Wang: Data Curation, Investigation. All authors participated fully in the work, take public responsibility for appropriate portions of the content, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or completeness of any part of the work are appropriately investigated and resolved.

Ethics Approval and Consent to Participate

The study protocol was approved by the Medical Ethics Committee of the Occupational Health and Poisoning Control Institute of the Chinese Center for Disease Control and Prevention, with the approval number of NIOHP202324. All patients provided their signed consent after being informed.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding Statement

None.