Association between occupational health literacy and occupational stress among workers in metal mining, metallurgy and non-metallic manufacturing in Gansu,China

Association between occupational health literacy and occupational stress among workers in metal mining, metallurgy and non-metallic manufacturing in Gansu,China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association between occupational health literacy and occupational stress among workers in metal mining, metallurgy and non-metallic manufacturing in Gansu,China Haiya Zhang, Wenli Zhao, Yuhong He, Jialong Wu, Jianyun Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6962822/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Nov, 2025 Read the published version in BMC Public Health → Version 1 posted 10 You are reading this latest preprint version Abstract Background Low levels of health literacy (HL) have been consistently associated with adverse mental health outcomes, including depression and anxiety; however, there is currently a lack of evidence establishing a connection between HL and occupational stress. This study aims to investigate the influence of occupational health literacy (OHL) on occupational stress, thereby providing a scientific foundation for mitigating occupational stress among workers in the industrial production sector. Methods The research involved a sample of 3,772 workers from the metal mining, metallurgy, and non-metallic mineral products industries in Gansu Province. The Individual Questionnaire of the National Key Population Occupational Health Literacy Monitoring Survey (IQ-NKPOHLMS) was employed to evaluate the workers' personal OHL, while the Core Occupational Stress Scale (COSS) was utilized to measure occupational stress. To analyze the association, weighted logistic regression models, restricted cubic splines (RCS), and subgroup analyses were conducted. Results The findings from the weighted logistic regression indicated that for each 1-point increase in OHL score, the likelihood of experiencing occupational stress decreased by 2%. Workers with a personal OHL score of 80% or higher exhibited a significantly reduced risk of occupational stress. The RCS analysis revealed a linear dose-response relationship between OHL and occupational stress. Furthermore, working hours emerged as a significant effect modifier, suggesting that longer working hours may amplify the relationship between OHL and occupational stress. Conclusion There exists a negative correlation between OHL and occupational stress, particularly evident among workers with extended working hours. Consequently, we advocate for the enhancement of OHL as a strategy to alleviate occupational stress. Occupational health literacy Health literacy Occupational stress Mental health Longer working hours Figures Figure 1 Figure 2 Figure 3 Backgroud The rapid transformation of the global economy, coupled with advancements in technology, has resulted in substantial changes to the work patterns of various occupational groups. While these developments offer opportunities for both society and individuals, they also pose significant challenges to the mental health of the workforce [ 1 ]. Occupational stress has emerged as a critical concern, becoming a central focus of public health research both nationally and internationally in recent years [ 2 , 3 ]. Occupational stress is defined as detrimental physical and emotional responses that occur when job demands exceed an individual's capabilities, resources, or needs [ 4 ]. Epidemiological evidence suggests that prolonged exposure to occupational stress can lead to various impairments in both physical and mental health, including conditions such as depression [ 5 ], anxiety [ 6 ], insomnia [ 7 ], musculoskeletal disorders [ 8 ], and cardiovascular diseases [ 9 ]. Previous research on occupational stress has predominantly focused on specific professional groups, including healthcare providers and educators [ 10 – 12 ], while relatively little attention has been directed toward workers in traditional industries, such as manufacturing and mining. Employees in these sectors are particularly vulnerable to mental health issues, including occupational stress, due to factors such as high labor intensity, substandard working conditions, repetitive tasks, and exposure to occupational hazards like dust and noise [ 13 , 14 ]. A national surveillance study among electronics manufacturing workers indicated an occupational stress prevalence rate of 19.5% [ 15 ]. In contrast, the prevalence of occupational stress among coal mining workers ranges from 38–53% [ 16 , 17 ]. These elevated rates contribute to various health issues and economic burdens at the societal, organizational, industrial, and individual levels, highlighting the necessity of investigating the determinants of occupational stress and implementing targeted psychological interventions. Individual factors such as education, income, weekly working hours, and overtime significantly influence occupational stress [ 13 , 18 ]. Recent studies also suggest that mental health literacy (HL) may play a role in shaping workers' experiences of occupational stress [ 19 – 21 ]. Health literacy (HL) is defined as an individual's ability to access, comprehend, evaluate, and effectively utilize health-related information, thereby enabling them to engage in behaviors that promote their health [ 22 ]. Over the past decade, as the emphasis has shifted from disease management to comprehensive health promotion, HL has attracted increasing scholarly attention and has been incorporated into national health policies [ 23 – 25 ]. HL is closely linked to health outcomes; individuals with low levels of HL often demonstrate diminished abilities to access and utilize health information, make informed health decisions, and adopt healthy lifestyles, which can lead to negative health consequences [ 23 , 26 – 28 ]. Research indicates a strong association between HL and workers' occupational capabilities and work-related illnesses [ 29 , 30 ]. Furthermore, enhancing HL has been shown to positively impact employees' mental health [ 31 ]. However, the existence of a direct relationship between HL and occupational stress remains to be fully elucidated. The present study investigates the levels of occupational health literacy (OHL) and the occupational stress experienced by employees in three specific industries—metal mining, metallurgy, and non-metallic mineral products—within Gansu Province. Additionally, it aims to explore the interplay between OHL and occupational stress. In this regard, the following hypotheses are posited: A correlation, whether positive or negative, may exist between OHL and occupational stress. Various confounding factors may serve as modifiers that influence the relationship between OHL and occupational stress. To the best of our knowledge, this research represents the inaugural examination of the relationship between OHL and occupational stress. The anticipated outcomes are expected to yield new evidence that could enhance worker health in industrial production environments and provide critical insights for mitigating occupational stress. Method Study Population From May to December 2024, a stratified cluster random sampling approach was utilized to survey workers in three distinct industries within Gansu Province: metal mining, metallurgy, and non-metallic mineral production. Enterprises were classified according to the National Bureau of Statistics' "Classification Method for Large, Medium, Small, and Micro Enterprises (2017)" based on employee count. Specifically, enterprises with fewer than 20 employees were designated as micro enterprises; those with 20 to 300 employees as small enterprises; those with 300 to 1000 employees as medium enterprises; and those with over 1000 employees as large enterprises. The sampling process involved stratification by enterprise size, with a random selection of 8–15% of enterprises from each category. The sampling framework mandated that large enterprises account for 10% of the sample, while small and micro enterprises should collectively represent 90%. The number of workers surveyed per enterprise was determined as follows: for large enterprises, 80 to 160 workers; for medium enterprises, 40 to 60 workers; and for small and micro enterprises, 10 to 40 workers. Ultimately, the study encompassed two large enterprises, five medium-sized enterprises, and between ten to twenty small or micro enterprises, culminating in a total of seventy-one participating organizations across the three sectors. Inclusion criteria for study participants required individuals to be aged between 16 and 59 years, possess work experience exceeding six months, and have no history of mental illness. The study received ethical approval from the Ethics Review Committee at the Gansu Provincial Center for Disease Control and Prevention (Ethics No. : 2024066), ensuring that all participants provided informed consent voluntarily. A total of 3,772 workers were included in this study, as depicted in Fig. 1 . Assessment of Occupational Stress Occupational stress was assessed through self-reporting using the "Core Occupational Stress Scale" (COSS), developed by the National Institute of Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention. This scale comprises four dimensions: social support (5 items), organization and rewards (6 items), demands and contributions (4 items), and autonomy (2 items), resulting in a total of 17 items. Each item is rated on a 5-point Likert scale, ranging from "strongly disagree" to "strongly agree." The overall occupational stress score is calculated using the following formula: Total Occupational Stress Score = (6-B1) + (6-B2) + (6-B3) + (6-B4) + (6-B5) + B6 + B7 + B8 + B9 + B10 + B11 + B12 + B13 + B14 + B15 + (6-B16) + (6-B17). A cumulative score of 50 or higher indicates the presence of occupational stress. In this study, the Cronbach's α coefficients for the overall scale and each dimension were found to be 0.776, 0.897, 0.802, 0.831, and 0.904, respectively, indicating strong reliability for the employed scale. Measurement of OHL The assessment of OHL was conducted through the "Individual Questionnaire of the National Key Population Occupational Health Literacy Monitoring Survey" (IQ-NKPOHLMS). This evaluation encompasses four dimensions: knowledge of occupational health legislation (11 items), fundamental understanding of occupational health protection (14 items), essential skills for occupational health protection (4 items), and healthy work practices and behaviors (12 items), culminating in a total of 41 questions. The results derived from the questionnaire were analyzed in accordance with the "2022 Calculation Standards for Occupational Health Literacy Levels of Key Populations," as established by the National Institute of Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention. The OHL score was calculated using the formula: OHL Score = (Total Correct Answers / Total Questions) * 100%. A score of 80.0% or higher is considered indicative of adequate OHL. Variables The variables examined in this study included demographic and occupational information, which were gathered through a self-administered online questionnaire. Marital status was categorized into three groups: unmarried, married, and other. Educational attainment was classified as junior high school or below, high school, college, and undergraduate or higher. Monthly income (in Yuan) was segmented into categories: ≤3000, 3000–5000, 5000–7000, and ≥ 7000. Weekly work hours were classified as ≤ 40 hours or > 40 hours. Night work was defined dichotomously as “yes” or “no,” with “yes” indicating employment during the hours of 12:00 AM to 5:00 AM. Statistical Analysis Categorical variables were summarized using frequencies and percentages, and group differences were assessed using the chi-square test. Continuous variables were described using medians and interquartile ranges (IQR) based on their distributional characteristics, with group differences evaluated through nonparametric tests. A weighted logistic regression model was employed to investigate the independent association between occupational stress and OHL. Three hierarchical regression models were developed: Model 1 served as the unadjusted basic model; Model 2 adjusted for demographic covariates (age, gender, ethnicity, marital status, education, household registration); and Model 3 further incorporated occupational-related factors (seniority, industry, enterprise size, income, work hours, night shifts). Restricted cubic splines (RCS) were utilized to explore potential non-linear relationships between continuous predictors and outcome variables. Subgroup analyses were conducted to assess the robustness and consistency of findings across various demographic subgroups, with results illustrated in forest plots. All statistical analyses were performed using SPSS version 26.0 and R version 4.4.2, with a significance threshold established at p < 0.05. Results Basic characteristics In this study, we included 3,772 workers with a median age of 39.4 years (IQR = 17.0). The present study encompassed a cohort of 3,772 workers, with a median age of 39.4 years (interquartile range = 17.0). The prevalence of occupational stress within this population was identified at 30.7%. Notable differences were observed between workers experiencing occupational stress and those who were not, with respect to various factors including gender, educational attainment, household registration status, duration of employment, industry type, enterprise size, income, working hours, and engagement in night shift work. Workers classified within the occupational stress group were predominantly male, held urban household registration, participated in night shifts or overtime, were employed by larger enterprises, and possessed considerable work experience. In comparison to their counterparts without occupational stress, individuals experiencing occupational stress demonstrated lower scores in occupational health literacy (OHL), income levels, and educational qualifications. (Table 1) Table 1.All characteristic of the particpants (grouped by the occupational stress or not ) Characteristic Overall With OS Without OS p Value n=3772 n=1157 n=2615 OHL score a 81.8(21.3) 78.9(22.8) 83.3(20.3) <0.001 Occupational health literacy b <0.001 no 1673（44.4） 595（51.4） 1078（41.2） yes 2099（55.6） 562（48.6） 1537（58.8） Demography: Age a ,years 39.4(17.0) 39.7(16.5) 39.2(17.1) 0.581 Age groups b ,years 0.518 16~<30 years old 732(19.4) 210(18.2) 522(20.0) 30~<40 years old 1217(32.3) 376(32.5) 841(32.2) 40~<50 years old 1015(26.9) 325(28.1) 690(26.4) ≥50 years old 808(21.4) 246(21.3) 562(21.5) Gender b <0.001 male 3032(80.4) 982(84.9) 2050(78.4) female 740(19.6) 175(15.1) 565(21.6) Ethnicity b 0.987 han 3563(94.5) 1093(94.5) 2470(94.5) minority 209(5.5) 64(5.5) 145(5.5) Marital status b 0.432 unmarried 585(15.5) 168(14.5) 417(15.9) married 3050(80.9) 943(81.5) 2107(80.6) other 137(3.6) 46(4.0) 91(3.5) Education b junior high school 1292(34.3) 403(34.8) 889(34.0) 0.041 high school 1064(28.2) 328(28.3) 736(28.1) college 920(24.4) 300(25.9) 620(23.7) undergraduate 496(13.1) 126(10.9) 370(14.1) Household registration b 0.006 urban 1908(50.6) 624(53.9) 1284(49.1) rural 1864(49.4) 533(46.1) 1331(50.9) Occupational characteristics: Seniority a ,years 5.1(11.0) 6.3(11.9) 4.8(10.7) <0.001 Seniority groups b ,years <0.001 <1 548(14.5) 127(11.0) 421(16.1) 1~<5 1291(34.2) 381(32.9) 910(34.8) 5~<10 655(17.4) 210(18.2) 445(17.0) 10~=20 484(12.8) 171(14.8) 313(12.0) Industry b <0.001 mining 1298(34.4) 342(29.6) 956(35.5) metallurgy 1308(34.7) 410(35.4) 898(33.8) non-metallic mineral products 1166(30.9) 405(35.0) 761(30.7) Enterprise size b <0.001 micro 1797(47.6) 485(41.9) 1312(50.2) middle 1260(33.4) 410(35.4) 850(32.5) large 715(19.0) 262(22.6) 453(17.3) Income,yuan/month b 0.002 ≤3000 514(13.6) 194(16.8) 320(12.2) 3001~<5000 1690(44.8) 504(43.6) 1186(45.4) 5001~40 2910(77.1) 927(80.1) 1983(75.8) Night work b <0.001 no 1415(37.5) 285(24.6) 1130(43.2) yes 2357(62.5) 872(75.4) 1485(56.8) Abbreviations: OS, occupational stress; OHL, Occupational health literacy The signiffcance of bold is P < 0.05 Note:a:median (IQR) is used to describe this variable;b:N (%) is used to describe this variable; P value reffects the difference between the two groups (With OS, Without OS) Association between OHL and occupational stress The investigation into the relationship between OHL and occupational stress was conducted utilizing weighted logistic regression models, with stepwise adjustments for potential confounding variables. Both continuous and categorical models indicated a significant association between OHL and occupational stress. In the initial Model 1 (unadjusted), higher OHL scores correlated with a diminished likelihood of experiencing occupational stress. This association persisted in Model 2, which accounted for demographic variables. Furthermore, in Model 3, which included additional occupational factors, the results continued to demonstrate that elevated OHL scores were associated with a reduced risk of occupational stress. (Table 2) Table 2.Associations between OHL and OS (N = 3772) Occupational health literacy score Occupational health literacy no yes estimate(95%CI) estimate(95%CI) occupational stress(OR) Model 1 a 0.980(0.975,0.984) reference 0.662(0.576,0.761) Model 2 a 0.978(0.973,0.983) reference 0.653(0.568,0.752) Model 3 a 0.981(0.976,0.985) reference 0.684(0.589,0.793) Note:Model 1 was unadjusted. Model 2 was adjusted for age, gender, ethnicity, marital status, education and household registration. Model 3 was adjusted for age, gender, ethnicity, marital status, education and household registration, seniority, industry, enterprise size, income, work time, night work. Potential nonlinear relationship between OHL and occupational stress symptoms Results from restricted cubic splines (RCS) did not reveal any significant nonlinear relationship between OHL and occupational stress. As illustrated in Figure 2, Models 1, 2, and 3 consistently exhibited a linear dose-response relationship, wherein occupational stress decreased sharply with increasing OHL scores, followed by a gradual deceleration and eventual plateau. The statistical significance for the overall model was established (Model 1: P for overall < 0.001, P for nonlinear = 0.0692; Model 2: P for overall < 0.001, P for nonlinear = 0.0927; Model 3: P for overall < 0.001, P for nonlinear = 0.2715). Additionally, a significant enhancement in protection against occupational stress was noted when OHL scores surpassed 81.6 points. In conclusion, workers with elevated OHL scores exhibited a markedly reduced risk of occupational stress. (Fig. 2) Subgroup analysis Subgroup analyses were performed for variables that demonstrated statistical significance in the multivariate weighted logistic regression model, specifically gender, seniority, industry, enterprise size, income, working hours, and night shifts. Figure 3 provides further insight into the influence of OHL scores on occupational stress across various subgroups. The analysis revealed that reductions in OHL scores were significantly correlated with an increased risk of occupational stress within these subgroups, with this association remaining consistent across all categories. Notably, the relationship between OHL and occupational stress was particularly pronounced among workers engaged in overtime ( P for interaction 0.05 ). (Fig. 3) Discussion This study represents the inaugural investigation into the relationship between OHL and occupational stress within labor groups across three industries in Gansu Province, utilizing the IQ-NKPOHLMS as a measurement tool. The results indicate a significant correlation between OHL and occupational stress, revealing that as OHL improves, the risk of occupational stress diminishes progressively. Additionally, the duration of employment was identified as a significant effect modifier, suggesting that it may amplify the strength of the association between exposure and outcomes. Currently, research on OHL is relatively nascent, characterized by a lack of a standardized definition or assessment instrument. Some scholars have sought to address this gap by developing assessment methods specifically designed for occupational populations, building upon general HL assessment tools. For example, CHO et al. [32] conducted a health literacy survey among Korean workers utilizing the Korean version of the Health Literacy Questionnaire alongside the Socioeconomic Status and Working Environment Questionnaire, highlighting the impact of social determinants on workers' health literacy. Similarly, Weeraporn Suthakorn et al. [33] integrated health literacy theory within the Thai cultural context, employing in-depth interviews and literature reviews to create the Thai Occupational Health Literacy Scale for Informal Workers, which was subsequently used to assess the OHL of 400 informal workers. These studies effectively merge health literacy assessments with occupational characteristics, such as working environments, behavioral habits, and safety training, thereby providing preliminary insights into the evaluation of OHL. The National Institute of Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention has defined "occupational health literacy" as the awareness and ability of workers to acquire essential occupational health knowledge, engage in healthy working practices and lifestyles, and effectively mitigate risks associated with occupational diseases and work-related illnesses, thus promoting and safeguarding their health. In alignment with this definition and taking into account the specific work characteristics of employees, the institute developed the "IQ-NKPOHLMS." This questionnaire comprises four sections: occupational health legal knowledge, fundamental occupational health protection knowledge, basic occupational health protection skills, and healthy working methods and behaviors. This framework represents an expansion of the OHL definition, facilitating more comprehensive and precise assessments of workers' OHL levels. Malene et al. [20] conducted a qualitative interview-based study involving medical personnel at a general hospital in Norway. The findings suggested that targeted interventions could improve HL and its sensitivity, thereby alleviating work-related stress. Despite the qualitative nature of the research and the absence of extensive quantitative data, the study underscored the significant relationship between HL and occupational stress. A longitudinal cohort study conducted over four years in Germany revealed a negative correlation between HL and mental health outcomes [34,35]. The initial follow-up in 2019 (T1) indicated that trainees with inadequate HL had a 110% increased likelihood of experiencing adverse mental health outcomes, while those with severely inadequate HL faced a risk increase of up to 230% [34]. The second follow-up in 2021 (T3) demonstrated that, although the longitudinal relationship between HL and mental health did not achieve statistical significance, cross-sectional analyses indicated a notable decline in mental health among individuals with insufficient HL (OR = 3.2, 95% CI: 1.07 - 9.49) [35]. Our research corroborated this correlation, as both weighted logistic regression models and RCS analyses confirmed the association between OHL and occupational stress. Specifically, our results revealed a negative correlation between OHL and occupational stress, indicating that higher levels of OHL are associated with a reduced risk of occupational stress. Workers with adequate OHL experienced a 32% decrease in the risk of occupational stress. Numerous studies have indicated that HL may mitigate occupational stress by enhancing individuals' self-awareness regarding health and encouraging the adoption of healthy behaviors. For example, Yuki SATO et al. [21] conducted research among nurses and caregivers, demonstrating that elevated health literacy is significantly correlated with improved health behaviors, such as taking timely breaks when fatigued, adjusting work rhythms, maintaining a work-life balance, and performing regular self-examinations. These health-promoting behaviors were more prevalent among caregivers with higher levels of health literacy, who also reported lower psychological and occupational stress scores, suggesting an enhancement in mental health status. Clearly, these healthy behaviors are instrumental in alleviating workplace stress and promoting mental well-being. In conjunction with the OHL questionnaire employed in our study, which encompasses essential occupational health knowledge and integrates protective skills and healthy behavior patterns, the former enhances workers' health self-awareness, while the latter directs them towards adopting a healthy lifestyle, thereby potentially reducing the incidence of occupational stress. This may elucidate a possible mechanism linking OHL to occupational stress. In this research, a comparison was made between workers with weekly working hours of 40 or fewer and those exceeding 40 hours, revealing a more pronounced association between OHL and occupational stress among the latter group. Numerous studies have established that prolonged working hours are a significant risk factor for occupational stress [15,18,36,37]. As the number of working hours increases, particularly with overtime, the likelihood of experiencing occupational stress escalates considerably. Specifically, when weekly working hours exceed 40, the risk of occupational stress increases by 90%, and when they surpass 60 hours, the risk further escalates to 170% [36]. Extended working hours inevitably reduce the time available for leisure and personal activities, which may influence occupational stress through several mechanisms. First, excessive working hours can lead to reduced sleep duration, resulting in sleep deprivation that may activate the hypothalamic-pituitary-adrenal axis, thereby inducing occupational stress [37]. Second, prolonged working hours limit the availability of free time for engaging in activities that foster knowledge and skill acquisition related to OHL. The moderating effect of weekly working hours on the relationship between OHL and occupational stress identified in this study may be closely associated with the indirect effects stemming from extended working hours. Our findings illuminate the potential moderating role of working hours in the relationship between OHL and occupational stress, providing a novel perspective for further investigation into this association. As previously noted, individual factors significantly contribute to the incidence of occupational stress, with gender being a notable variable. Our findings indicate that men are at a considerably higher risk of experiencing occupational stress compared to women, which is consistent with prior research [13,15]. Furthermore, workers with longer working hours demonstrate a significantly elevated risk of occupational stress relative to those with shorter hours, corroborating earlier conclusions [13,36]. Economic income is a critical source of occupational stress [38], as higher income levels can alleviate the imbalances associated with high-intensity and high-load work, thereby reducing occupational stress levels. Additionally, night and shift work patterns can disrupt normal sleep and circadian rhythms, negatively impacting workers' mental health [39]. This study also highlights variations in the risk of occupational stress among workers across different industries and enterprise sizes, which may be attributed to disparities in production environments and work systems. This study acknowledges several limitations. First, as a cross-sectional study, it cannot definitively establish causal relationships between workers' OHL and occupational stress. Second, due to limitations in survey conditions, data regarding occupational hazard factors and their intensities to which workers are exposed could not be collected, preventing an assessment of the potential impact of such factors (e.g., dust and noise) on occupational stress. Third, while the concept of OHL in this study encompasses multiple dimensions, including occupational health knowledge, occupational protection skills, and healthy behaviors/lifestyles, the strength of the association between each dimension and occupational stress has not been analyzed in greater detail. Conclusion The influence of health literacy on mental health has garnered considerable interest in recent years. This study presents limited, yet meaningful, evidence concerning the relationship between occupational health literacy and occupational stress. The findings indicate a notable negative correlation between these two variables. Given the extensive array of detrimental health outcomes associated with occupational stress, it is proposed that enhancing occupational health literacy may mitigate occupational stress and promote better mental health. Future research should involve larger cohort studies to yield more comprehensive evidence and to further elucidate the underlying mechanisms connecting occupational health literacy and occupational stress. Abbreviations HL Health literacy OHL Occupational health literacy COSS Core occupational stress scale IQ-NKPOHLMS National key population occupational health literacy monitoring survey IQR Interquartile ranges RCS Restricted cubic splines Declarations Acknowledgments Thanks to the experts from the Institute of Occupational Health and Poison Control of the Chinese Center for Disease Control and Prevention for their guidance and help. Thank you also to all participants who helped to obtain written informed consent regarding the survey and to distribute the questionnaire to the subjects. Author contributions HYZ: Data collection and analysis, Conceptualization, Methodology, Writing–review & editing. WLZ: Conceptualization, Methodology, Writing–review & editing, Funding acquisition. YHH, JLW: Conceptualization, Methodology. JYS: Conceptualization, Supervision, Methodology, Resources. All authors have read and agreed to the published version of the manuscript. Funding We gratefully acknowledge funding from the Gansu Provincial Science and Technology Program (Grant No.: 20JR10RA420). Data availability The corresponding author can provide the data supporting the study's conclusions upon request. Ethics approval and consent to participate This study was conducted in strict accordance with the Declaration of Helsinki and approved by the Ethics Review Committee of the Gansu Provincial Center for Disease Control and Prevention (ethics number: 2024066), and the study subjects voluntarily participated and obtained informed consent. Consent for publication Not applicable. Competing interests The authors declare no conficts of interest. 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Impact of health literacy on health practices in the working life of young Japanese nurses and care workers. Ind Health. 2021;59(3):171–9. https://doi.org/10.2486/indhealth.2020-0218 . Nutbeam D, Lloyd JE. Understanding and Responding to Health Literacy as a Social Determinant of Health. Annu Rev Public Health. 2021;42:159–73. https://doi.org/10.1146/annurev-publhealth-090419-102529 . Bostock S, Steptoe A. Association between low functional health literacy and mortality in older adults: longitudinal cohort study. BMJ. 2012;344:e1602. https://doi.org/10.1136/bmj.e1602 . Mei X, Zhong Q, Chen G, Huang Y, Li J. Exploring health literacy in Wuhan, China: a cross-sectional analysis. BMC Public Health. 2020;20(1):1417. https://doi.org/10.1186/s12889-020-09520-9 . Alijanzadeh M, Yahaghi R, Rahmani J, Yazdi N, Jafari E, Alijani H, Zamani N, Fotuhi R, Taherkhani E, Buchali Z, Zarenejad M, Mahmoudi N, Shahmahdi N, Poorzolfaghar L, Ahmadizade S, Shahbazkhania A, Gozal D, Lin CY, Pakpour AH. Sleep hygiene behaviours mediate the association between health/e-health literacy and mental wellbeing. Health Expect. 2023;26(6):2349–60. https://doi.org/10.1111/hex.13837 . Marciano L, Camerini AL, Schulz PJ. The Role of Health Literacy in Diabetes Knowledge, Self-Care, and Glycemic Control: a Meta-analysis. J Gen Intern Med. 2019;34(6):1007–17. https://doi.org/10.1007/s11606-019-04832-y . Fleary SA, Joseph P, Pappagianopoulos JE. Adolescent health literacy and health behaviors: A systematic review. J Adolesc. 2018;62:116–27. https://doi.org/10.1016/j.adolescence.2017.11.010 . Zhang Y, Xu P, Sun Q, Baral S, Xi L, Wang D. Factors influencing the e-health literacy in cancer patients: a systematic review. J Cancer Surviv. 2023;17(2):425–40. https://doi.org/10.1007/s11764-022-01260-6 . Friedrich J, Rupp M, Feng YS et al. Occupational health literacy and work ability: a moderation analysis including interpersonal and organizational factors in healthy organizations[J]. Front Public Health,2024,12:1243138. https://doi.org/10.3389/fpubh.2024.1243138 Larsen AK, Thygesen LC, Mortensen OS, Punnett L, Jørgensen MB. The effect of strengthening health literacy in nursing homes on employee pain and consequences of pain – a stepped-wedge intervention trial. Scand J Work Environ Health. 2019;45(4):386–95. https://doi.org/10.5271/sjweh.3801 . Lindert L, Choi KA, Pfaff H, Zeike S. Health literacy at work - individual and organizational health literacy, health supporting leadership and employee wellbeing. BMC Health Serv Res. 2023;23(1):736. https://doi.org/10.1186/s12913-023-09766-0 . Cho M, Lee H, Lee YM, et al. Psychometric properties of the Korean version of the Health Literacy on Social Determinants of Health Questionnaire (K-HL-SDHQ). PLoS ONE. 2019;14(11):e0224557. https://doi.org/10.1371/journal.pone.0224557 . Suthakorn W, Songkham W, Tantranont K, Srisuphan W, Sakarinkhul P, Dhatsuwan J. Scale Development and Validation to Measure Occupational Health Literacy Among Thai Informal Workers. Saf Health Work. 2020;11(4):526–32. https://doi.org/10.1016/j.shaw.2020.06.003 . Koch P, Schillmöller Z, Nienhaus A. How Does Health Literacy Modify Indicators of Health Behaviour and of Health? A Longitudinal Study with Trainees in North Germany. Healthc (Basel). 2021;10(1):2. https://doi.org/10.3390/healthcare10010002 . Koch P, Kersten JF, Nienhaus A. Monitoring a cohort of trainees: changes over time and associations between health literacy, health behaviour and health. J Occup Med Toxicol. 2023;18(1):18. https://doi.org/10.1186/s12995-023-00387-1 . Zheng B, Chen F, Wang J, et al. The Prevalence and Correlated Factors of Occupational Stress, Cumulative Fatigue, and Musculoskeletal Disorders among Information Technology Workers: A Cross-Sectional Study in Chongqing, China. Healthc (Basel). 2023;11(16):2322. https://doi.org/10.3390/healthcare11162322 . Hong Y, Zhang Y, Xue P, et al. The Influence of Long Working Hours, Occupational Stress, and Well-Being on Depression Among Couriers in Zhejiang, China. Front Psychol. 2022;13:928928. https://doi.org/10.3389/fpsyg.2022.928928 . Samuel LJ, Dwivedi P, Hladek M, et al. The effect of COVID-19 pandemic-related financial challenges on mental health and well-being among US older adults. J Am Geriatr Soc. 2022;70(6):1629–41. https://doi.org/10.1111/jgs.17808 . Torquati L, Mielke GI, Brown WJ, Burton NW, Kolbe-Alexander TL. Shift Work and Poor Mental Health: A Meta-Analysis of Longitudinal Studies. Am J Public Health. 2019;109(11):e13–20. https://doi.org/10.2105/AJPH.2019.305278 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 25 Nov, 2025 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 16 Sep, 2025 Reviews received at journal 16 Sep, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviews received at journal 31 Jul, 2025 Reviewers agreed at journal 08 Jul, 2025 Reviewers invited by journal 08 Jul, 2025 Editor invited by journal 27 Jun, 2025 Editor assigned by journal 26 Jun, 2025 Submission checks completed at journal 26 Jun, 2025 First submitted to journal 24 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6962822","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482348864,"identity":"e3b21694-7f05-4665-95e1-44635198e5f1","order_by":0,"name":"Haiya Zhang","email":"","orcid":"","institution":"Gansu Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Haiya","middleName":"","lastName":"Zhang","suffix":""},{"id":482348865,"identity":"473fdf88-21ba-4971-8425-758a9d6d91a2","order_by":1,"name":"Wenli Zhao","email":"","orcid":"","institution":"Gansu Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Wenli","middleName":"","lastName":"Zhao","suffix":""},{"id":482348866,"identity":"2ccc4528-5c87-4fa2-b378-07a87a1aca3d","order_by":2,"name":"Yuhong He","email":"","orcid":"","institution":"Gansu Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yuhong","middleName":"","lastName":"He","suffix":""},{"id":482348867,"identity":"5025ee7a-d637-4750-81b7-ae5e18b42b4e","order_by":3,"name":"Jialong Wu","email":"","orcid":"","institution":"Gansu Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Jialong","middleName":"","lastName":"Wu","suffix":""},{"id":482348868,"identity":"1a53d0f6-f46d-44ee-8646-d7c1a0b088e8","order_by":4,"name":"Jianyun Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYBACefnHBx9IGNjIsbE3EKnFsCEt2cCiIs2Yn+cAsdYcyDGTqDhzOHHmjAQidTA2HEuTuNl2mHHDzccbbzDU2EQT1MLO2HzYcmZbOrPB7bRiC4ZjabkNBG1pZku8LdlmzWZwG+hCxobDhLUwHOMxkP7bxsxjcPMMsVrO8BhJSJxxlpCcwUOkFsMZbMkGEhVpBvw8QL8kEOMXeQlmcFTWt7Ef3njjQ40NEQ5DAgYSCaQoh2ghVccoGAWjYBSMDAAA/nZADS0XYC8AAAAASUVORK5CYII=","orcid":"","institution":"Gansu Center for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"Jianyun","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2025-06-24 07:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6962822/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6962822/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-025-25511-0","type":"published","date":"2025-11-25T15:56:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86411426,"identity":"233fb52a-7285-40f0-88f2-b3461ca8d055","added_by":"auto","created_at":"2025-07-10 10:39:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":90544,"visible":true,"origin":"","legend":"\u003cp\u003eflow chart of sample selection\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6962822/v1/ad70406020a7339c966d970a.png"},{"id":86409639,"identity":"e5899af1-cd7e-49f7-aaad-0b6893dc8fc9","added_by":"auto","created_at":"2025-07-10 10:31:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":162769,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline for testing the hypothesis of non-linear correlation between Occupational health literacy score and Occupational stress.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6962822/v1/41fdb70fcae172c370c7c402.png"},{"id":86411427,"identity":"3382ef14-729e-4d28-a7d2-6254ab2c0a54","added_by":"auto","created_at":"2025-07-10 10:39:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":316296,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction analysis of associations between Occupational health literacy and Occupational stress among different subgroups. Note: Adjusted for gender, industry, seniority groups, enterprise size, income, work time, nigh twork.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6962822/v1/dc78480b22e64d6173b44512.png"},{"id":97178220,"identity":"a0ddf773-cb22-4649-85cb-c6667b0df4fe","added_by":"auto","created_at":"2025-12-01 16:01:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1268168,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6962822/v1/0956b600-ef79-452f-917b-1dd3e48c6f9b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between occupational health literacy and occupational stress among workers in metal mining, metallurgy and non-metallic manufacturing in Gansu,China","fulltext":[{"header":"Backgroud","content":"\u003cp\u003eThe rapid transformation of the global economy, coupled with advancements in technology, has resulted in substantial changes to the work patterns of various occupational groups. While these developments offer opportunities for both society and individuals, they also pose significant challenges to the mental health of the workforce [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Occupational stress has emerged as a critical concern, becoming a central focus of public health research both nationally and internationally in recent years [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Occupational stress is defined as detrimental physical and emotional responses that occur when job demands exceed an individual's capabilities, resources, or needs [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Epidemiological evidence suggests that prolonged exposure to occupational stress can lead to various impairments in both physical and mental health, including conditions such as depression [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], anxiety [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], insomnia [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], musculoskeletal disorders [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and cardiovascular diseases [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrevious research on occupational stress has predominantly focused on specific professional groups, including healthcare providers and educators [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], while relatively little attention has been directed toward workers in traditional industries, such as manufacturing and mining. Employees in these sectors are particularly vulnerable to mental health issues, including occupational stress, due to factors such as high labor intensity, substandard working conditions, repetitive tasks, and exposure to occupational hazards like dust and noise [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A national surveillance study among electronics manufacturing workers indicated an occupational stress prevalence rate of 19.5% [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In contrast, the prevalence of occupational stress among coal mining workers ranges from 38\u0026ndash;53% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These elevated rates contribute to various health issues and economic burdens at the societal, organizational, industrial, and individual levels, highlighting the necessity of investigating the determinants of occupational stress and implementing targeted psychological interventions. Individual factors such as education, income, weekly working hours, and overtime significantly influence occupational stress [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Recent studies also suggest that mental health literacy (HL) may play a role in shaping workers' experiences of occupational stress [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHealth literacy (HL) is defined as an individual's ability to access, comprehend, evaluate, and effectively utilize health-related information, thereby enabling them to engage in behaviors that promote their health [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Over the past decade, as the emphasis has shifted from disease management to comprehensive health promotion, HL has attracted increasing scholarly attention and has been incorporated into national health policies [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. HL is closely linked to health outcomes; individuals with low levels of HL often demonstrate diminished abilities to access and utilize health information, make informed health decisions, and adopt healthy lifestyles, which can lead to negative health consequences [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Research indicates a strong association between HL and workers' occupational capabilities and work-related illnesses [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, enhancing HL has been shown to positively impact employees' mental health [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, the existence of a direct relationship between HL and occupational stress remains to be fully elucidated.\u003c/p\u003e\u003cp\u003eThe present study investigates the levels of occupational health literacy (OHL) and the occupational stress experienced by employees in three specific industries\u0026mdash;metal mining, metallurgy, and non-metallic mineral products\u0026mdash;within Gansu Province. Additionally, it aims to explore the interplay between OHL and occupational stress. In this regard, the following hypotheses are posited:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eA correlation, whether positive or negative, may exist between OHL and occupational stress.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eVarious confounding factors may serve as modifiers that influence the relationship between OHL and occupational stress.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, this research represents the inaugural examination of the relationship between OHL and occupational stress. The anticipated outcomes are expected to yield new evidence that could enhance worker health in industrial production environments and provide critical insights for mitigating occupational stress.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Population\u003c/h2\u003e\u003cp\u003eFrom May to December 2024, a stratified cluster random sampling approach was utilized to survey workers in three distinct industries within Gansu Province: metal mining, metallurgy, and non-metallic mineral production. Enterprises were classified according to the National Bureau of Statistics' \"Classification Method for Large, Medium, Small, and Micro Enterprises (2017)\" based on employee count. Specifically, enterprises with fewer than 20 employees were designated as micro enterprises; those with 20 to 300 employees as small enterprises; those with 300 to 1000 employees as medium enterprises; and those with over 1000 employees as large enterprises. The sampling process involved stratification by enterprise size, with a random selection of 8\u0026ndash;15% of enterprises from each category. The sampling framework mandated that large enterprises account for 10% of the sample, while small and micro enterprises should collectively represent 90%. The number of workers surveyed per enterprise was determined as follows: for large enterprises, 80 to 160 workers; for medium enterprises, 40 to 60 workers; and for small and micro enterprises, 10 to 40 workers. Ultimately, the study encompassed two large enterprises, five medium-sized enterprises, and between ten to twenty small or micro enterprises, culminating in a total of seventy-one participating organizations across the three sectors.\u003c/p\u003e\u003cp\u003eInclusion criteria for study participants required individuals to be aged between 16 and 59 years, possess work experience exceeding six months, and have no history of mental illness. The study received ethical approval from the Ethics Review Committee at the Gansu Provincial Center for Disease Control and Prevention (Ethics No. : 2024066), ensuring that all participants provided informed consent voluntarily. A total of 3,772 workers were included in this study, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssessment of Occupational Stress\u003c/h3\u003e\n\u003cp\u003eOccupational stress was assessed through self-reporting using the \"Core Occupational Stress Scale\" (COSS), developed by the National Institute of Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention. This scale comprises four dimensions: social support (5 items), organization and rewards (6 items), demands and contributions (4 items), and autonomy (2 items), resulting in a total of 17 items. Each item is rated on a 5-point Likert scale, ranging from \"strongly disagree\" to \"strongly agree.\" The overall occupational stress score is calculated using the following formula: Total Occupational Stress Score = (6-B1) + (6-B2) + (6-B3) + (6-B4) + (6-B5)\u0026thinsp;+\u0026thinsp;B6\u0026thinsp;+\u0026thinsp;B7\u0026thinsp;+\u0026thinsp;B8\u0026thinsp;+\u0026thinsp;B9\u0026thinsp;+\u0026thinsp;B10\u0026thinsp;+\u0026thinsp;B11\u0026thinsp;+\u0026thinsp;B12\u0026thinsp;+\u0026thinsp;B13\u0026thinsp;+\u0026thinsp;B14\u0026thinsp;+\u0026thinsp;B15 + (6-B16) + (6-B17). A cumulative score of 50 or higher indicates the presence of occupational stress. In this study, the Cronbach's α coefficients for the overall scale and each dimension were found to be 0.776, 0.897, 0.802, 0.831, and 0.904, respectively, indicating strong reliability for the employed scale.\u003c/p\u003e\n\u003ch3\u003eMeasurement of OHL\u003c/h3\u003e\n\u003cp\u003eThe assessment of OHL was conducted through the \"Individual Questionnaire of the National Key Population Occupational Health Literacy Monitoring Survey\" (IQ-NKPOHLMS). This evaluation encompasses four dimensions: knowledge of occupational health legislation (11 items), fundamental understanding of occupational health protection (14 items), essential skills for occupational health protection (4 items), and healthy work practices and behaviors (12 items), culminating in a total of 41 questions. The results derived from the questionnaire were analyzed in accordance with the \"2022 Calculation Standards for Occupational Health Literacy Levels of Key Populations,\" as established by the National Institute of Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention. The OHL score was calculated using the formula: OHL Score = (Total Correct Answers / Total Questions) * 100%. A score of 80.0% or higher is considered indicative of adequate OHL.\u003c/p\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eThe variables examined in this study included demographic and occupational information, which were gathered through a self-administered online questionnaire. Marital status was categorized into three groups: unmarried, married, and other. Educational attainment was classified as junior high school or below, high school, college, and undergraduate or higher. Monthly income (in Yuan) was segmented into categories: \u0026le;3000, 3000\u0026ndash;5000, 5000\u0026ndash;7000, and \u0026ge;\u0026thinsp;7000. Weekly work hours were classified as \u0026le;\u0026thinsp;40 hours or \u0026gt;\u0026thinsp;40 hours. Night work was defined dichotomously as \u0026ldquo;yes\u0026rdquo; or \u0026ldquo;no,\u0026rdquo; with \u0026ldquo;yes\u0026rdquo; indicating employment during the hours of 12:00 AM to 5:00 AM.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eCategorical variables were summarized using frequencies and percentages, and group differences were assessed using the chi-square test. Continuous variables were described using medians and interquartile ranges (IQR) based on their distributional characteristics, with group differences evaluated through nonparametric tests. A weighted logistic regression model was employed to investigate the independent association between occupational stress and OHL. Three hierarchical regression models were developed: Model 1 served as the unadjusted basic model; Model 2 adjusted for demographic covariates (age, gender, ethnicity, marital status, education, household registration); and Model 3 further incorporated occupational-related factors (seniority, industry, enterprise size, income, work hours, night shifts). Restricted cubic splines (RCS) were utilized to explore potential non-linear relationships between continuous predictors and outcome variables. Subgroup analyses were conducted to assess the robustness and consistency of findings across various demographic subgroups, with results illustrated in forest plots. All statistical analyses were performed using SPSS version 26.0 and R version 4.4.2, with a significance threshold established at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBasic characteristics\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, we included 3,772 workers with a median age of 39.4 years (IQR = 17.0). The present study encompassed a cohort of 3,772 workers, with a median age of 39.4 years (interquartile range = 17.0). The prevalence of occupational stress within this population was identified at 30.7%. Notable differences were observed between workers experiencing occupational stress and those who were not, with respect to various factors including gender, educational attainment, household registration status, duration of employment, industry type, enterprise size, income, working hours, and engagement in night shift work. Workers classified within the occupational stress group were predominantly male, held urban household registration, participated in night shifts or overtime, were employed by larger enterprises, and possessed considerable work experience. In comparison to their counterparts without occupational stress, individuals experiencing occupational stress demonstrated lower scores in occupational health literacy (OHL), income levels, and educational qualifications. (Table 1)\u003c/p\u003e\n\u003cp\u003eTable 1.All characteristic of the particpants (grouped by the occupational stress or not )\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"582\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWith OS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWithout OS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ep Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003en=3772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003en=1157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003en=2615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOHL score\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81.8(21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78.9(22.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e83.3(20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOccupational health literacy\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1673（44.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e595（51.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1078（41.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2099（55.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e562（48.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1537（58.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDemography:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003csup\u003ea\u003c/sup\u003e,years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.4(17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.7(16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.2(17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge groups\u003csup\u003eb\u003c/sup\u003e,years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e16~\u0026lt;30 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e732(19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e210(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e522(20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e30~\u0026lt;40 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1217(32.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e376(32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e841(32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e40~\u0026lt;50 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1015(26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e325(28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e690(26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;50 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e808(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e246(21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e562(21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3032(80.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e982(84.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2050(78.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e740(19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e175(15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e565(21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEthnicity\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ehan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3563(94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1093(94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2470(94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eminority\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e209(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e145(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMarital status\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eunmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e585(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e168(14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e417(15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3050(80.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e943(81.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2107(80.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eother\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46(4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ejunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1292(34.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e403(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e889(34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ehigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1064(28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e328(28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e736(28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ecollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e920(24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e300(25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e620(23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eundergraduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e496(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e126(10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e370(14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHousehold registration\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eurban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1908(50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e624(53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1284(49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003erural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1864(49.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e533(46.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1331(50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOccupational characteristics:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSeniority\u003csup\u003ea\u003c/sup\u003e,years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.1(11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.3(11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.8(10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSeniority groups\u003csup\u003eb\u003c/sup\u003e,years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e548(14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e127(11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e421(16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1~\u0026lt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1291(34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e381(32.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e910(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e5~\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e655(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e210(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e445(17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e10~\u0026lt;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e794(21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e268(23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e526(20.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;=20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e484(12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e171(14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e313(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIndustry\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1298(34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e342(29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e956(35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emetallurgy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1308(34.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e410(35.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e898(33.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003enon-metallic mineral products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1166(30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e405(35.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e761(30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEnterprise size\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emicro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1797(47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e485(41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1312(50.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1260(33.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e410(35.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e850(32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003elarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e715(19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e262(22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e453(17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIncome,yuan/month\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;3000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e514(13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e194(16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e320(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3001~\u0026lt;5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1690(44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e504(43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1186(45.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e5001~\u0026lt;7000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1124(29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e334(28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e790(30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;7000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e444(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e319(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWork time,hours/week\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e862(22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e230(19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e632(24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2910(77.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e927(80.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1983(75.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNight work\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1415(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e285(24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1130(43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2357(62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e872(75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1485(56.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: OS, occupational stress; OHL, Occupational health literacy\u003c/p\u003e\n\u003cp\u003eThe signiffcance of bold is P \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003eNote:a:median (IQR) is used to describe this variable;b:N (%) is used to describe this variable; P value reffects the difference between the two groups (With OS, Without OS)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between OHL and occupational stress\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe investigation into the relationship between OHL and occupational stress was conducted utilizing weighted logistic regression models, with stepwise adjustments for potential confounding variables. Both continuous and categorical models indicated a significant association between OHL and occupational stress. In the initial Model 1 (unadjusted), higher OHL scores correlated with a diminished likelihood of experiencing occupational stress. This association persisted in Model 2, which accounted for demographic variables. Furthermore, in Model 3, which included additional occupational factors, the results continued to demonstrate that elevated OHL scores were associated with a reduced risk of occupational stress. (Table 2)\u003c/p\u003e\n\u003cp\u003eTable 2.Associations between OHL and OS (N = 3772)\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOccupational health literacy score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eOccupational health literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eestimate(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eestimate(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eoccupational stress(OR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.980(0.975,0.984)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.662(0.576,0.761)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.978(0.973,0.983)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.653(0.568,0.752)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 3\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.981(0.976,0.985)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.684(0.589,0.793)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote:Model 1 was unadjusted. Model 2 was adjusted for age, gender, ethnicity, marital status, education and household registration. Model 3 was adjusted for age, gender, ethnicity, marital status, education and household registration, seniority, industry, enterprise size, income, work time, night work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePotential nonlinear relationship between OHL and occupational stress symptoms\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults from restricted cubic splines (RCS) did not reveal any significant nonlinear relationship between OHL and occupational stress. As illustrated in Figure 2, Models 1, 2, and 3 consistently exhibited a linear dose-response relationship, wherein occupational stress decreased sharply with increasing OHL scores, followed by a gradual deceleration and eventual plateau. The statistical significance for the overall model was established (Model 1: \u003cem\u003eP \u003csub\u003efor overall\u003c/sub\u003e\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003eP \u003csub\u003efor nonlinear\u003c/sub\u003e\u003c/em\u003e = 0.0692; Model 2: \u003cem\u003eP \u003csub\u003efor overall\u003c/sub\u003e\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003eP \u003csub\u003efor nonlinear\u003c/sub\u003e\u003c/em\u003e = 0.0927; Model 3: \u003cem\u003eP \u003csub\u003efor overall\u003c/sub\u003e\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003eP \u003csub\u003efor nonlinear\u003c/sub\u003e\u003c/em\u003e = 0.2715). Additionally, a significant enhancement in protection against occupational stress was noted when OHL scores surpassed 81.6 points. In conclusion, workers with elevated OHL scores exhibited a markedly reduced risk of occupational stress. (Fig. 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubgroup analysis\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubgroup analyses were performed for variables that demonstrated statistical significance in the multivariate weighted logistic regression model, specifically gender, seniority, industry, enterprise size, income, working hours, and night shifts. Figure 3 provides further insight into the influence of OHL scores on occupational stress across various subgroups. The analysis revealed that reductions in OHL scores were significantly correlated with an increased risk of occupational stress within these subgroups, with this association remaining consistent across all categories. Notably, the relationship between OHL and occupational stress was particularly pronounced among workers engaged in overtime (\u003cem\u003eP \u003csub\u003efor interaction\u003c/sub\u003e\u003c/em\u003e \u0026lt; 0.001). However, no statistically significant interactions were identified for gender, seniority, industry, firm size, income, night shifts, and occupational stress (\u003cem\u003eP\u003csub\u003e-values for interaction\u003c/sub\u003e \u0026gt; 0.05\u003c/em\u003e). (Fig. 3)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study represents the inaugural investigation into the relationship between OHL and occupational stress within labor groups across three industries in Gansu Province, utilizing the IQ-NKPOHLMS as a measurement tool. The results indicate a significant correlation between OHL and occupational stress, revealing that as OHL improves, the risk of occupational stress diminishes progressively. Additionally, the duration of employment was identified as a significant effect modifier, suggesting that it may amplify the strength of the association between exposure and outcomes.\u003c/p\u003e\n\u003cp\u003eCurrently, research on OHL is relatively nascent, characterized by a lack of a standardized definition or assessment instrument. Some scholars have sought to address this gap by developing assessment methods specifically designed for occupational populations, building upon general HL assessment tools. For example, CHO et al. [32] conducted a health literacy survey among Korean workers utilizing the Korean version of the Health Literacy Questionnaire alongside the Socioeconomic Status and Working Environment Questionnaire, highlighting the impact of social determinants on workers' health literacy. Similarly, Weeraporn Suthakorn et al. [33] integrated health literacy theory within the Thai cultural context, employing in-depth interviews and literature reviews to create the Thai Occupational Health Literacy Scale for Informal Workers, which was subsequently used to assess the OHL of 400 informal workers. These studies effectively merge health literacy assessments with occupational characteristics, such as working environments, behavioral habits, and safety training, thereby providing preliminary insights into the evaluation of OHL.\u003c/p\u003e\n\u003cp\u003eThe National Institute of Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention has defined \"occupational health literacy\" as the awareness and ability of workers to acquire essential occupational health knowledge, engage in healthy working practices and lifestyles, and effectively mitigate risks associated with occupational diseases and work-related illnesses, thus promoting and safeguarding their health. In alignment with this definition and taking into account the specific work characteristics of employees, the institute developed the \"IQ-NKPOHLMS.\" This questionnaire comprises four sections: occupational health legal knowledge, fundamental occupational health protection knowledge, basic occupational health protection skills, and healthy working methods and behaviors. This framework represents an expansion of the OHL definition, facilitating more comprehensive and precise assessments of workers' OHL levels.\u003c/p\u003e\n\u003cp\u003eMalene et al. [20] conducted a qualitative interview-based study involving medical personnel at a general hospital in Norway. The findings suggested that targeted interventions could improve HL and its sensitivity, thereby alleviating work-related stress. Despite the qualitative nature of the research and the absence of extensive quantitative data, the study underscored the significant relationship between HL and occupational stress. A longitudinal cohort study conducted over four years in Germany revealed a negative correlation between HL and mental health outcomes [34,35]. The initial follow-up in 2019 (T1) indicated that trainees with inadequate HL had a 110% increased likelihood of experiencing adverse mental health outcomes, while those with severely inadequate HL faced a risk increase of up to 230% [34]. The second follow-up in 2021 (T3) demonstrated that, although the longitudinal relationship between HL and mental health did not achieve statistical significance, cross-sectional analyses indicated a notable decline in mental health among individuals with insufficient HL (OR = 3.2, 95% CI: 1.07 - 9.49) [35]. Our research corroborated this correlation, as both weighted logistic regression models and RCS analyses confirmed the association between OHL and occupational stress. Specifically, our results revealed a negative correlation between OHL and occupational stress, indicating that higher levels of OHL are associated with a reduced risk of occupational stress. Workers with adequate OHL experienced a 32% decrease in the risk of occupational stress.\u003c/p\u003e\n\u003cp\u003eNumerous studies have indicated that HL may mitigate occupational stress by enhancing individuals' self-awareness regarding health and encouraging the adoption of healthy behaviors. For example, Yuki SATO et al. [21] conducted research among nurses and caregivers, demonstrating that elevated health literacy is significantly correlated with improved health behaviors, such as taking timely breaks when fatigued, adjusting work rhythms, maintaining a work-life balance, and performing regular self-examinations. These health-promoting behaviors were more prevalent among caregivers with higher levels of health literacy, who also reported lower psychological and occupational stress scores, suggesting an enhancement in mental health status. Clearly, these healthy behaviors are instrumental in alleviating workplace stress and promoting mental well-being. In conjunction with the OHL questionnaire employed in our study, which encompasses essential occupational health knowledge and integrates protective skills and healthy behavior patterns, the former enhances workers' health self-awareness, while the latter directs them towards adopting a healthy lifestyle, thereby potentially reducing the incidence of occupational stress. This may elucidate a possible mechanism linking OHL to occupational stress.\u003c/p\u003e\n\u003cp\u003eIn this research, a comparison was made between workers with weekly working hours of 40 or fewer and those exceeding 40 hours, revealing a more pronounced association between OHL and occupational stress among the latter group. Numerous studies have established that prolonged working hours are a significant risk factor for occupational stress [15,18,36,37]. As the number of working hours increases, particularly with overtime, the likelihood of experiencing occupational stress escalates considerably. Specifically, when weekly working hours exceed 40, the risk of occupational stress increases by 90%, and when they surpass 60 hours, the risk further escalates to 170% [36]. Extended working hours inevitably reduce the time available for leisure and personal activities, which may influence occupational stress through several mechanisms. First, excessive working hours can lead to reduced sleep duration, resulting in sleep deprivation that may activate the hypothalamic-pituitary-adrenal axis, thereby inducing occupational stress [37]. Second, prolonged working hours limit the availability of free time for engaging in activities that foster knowledge and skill acquisition related to OHL. The moderating effect of weekly working hours on the relationship between OHL and occupational stress identified in this study may be closely associated with the indirect effects stemming from extended working hours. Our findings illuminate the potential moderating role of working hours in the relationship between OHL and occupational stress, providing a novel perspective for further investigation into this association.\u003c/p\u003e\n\u003cp\u003eAs previously noted, individual factors significantly contribute to the incidence of occupational stress, with gender being a notable variable. Our findings indicate that men are at a considerably higher risk of experiencing occupational stress compared to women, which is consistent with prior research [13,15]. Furthermore, workers with longer working hours demonstrate a significantly elevated risk of occupational stress relative to those with shorter hours, corroborating earlier conclusions [13,36]. Economic income is a critical source of occupational stress [38], as higher income levels can alleviate the imbalances associated with high-intensity and high-load work, thereby reducing occupational stress levels. Additionally, night and shift work patterns can disrupt normal sleep and circadian rhythms, negatively impacting workers' mental health [39]. This study also highlights variations in the risk of occupational stress among workers across different industries and enterprise sizes, which may be attributed to disparities in production environments and work systems.\u003c/p\u003e\n\u003cp\u003eThis study acknowledges several limitations. First, as a cross-sectional study, it cannot definitively establish causal relationships between workers' OHL and occupational stress. Second, due to limitations in survey conditions, data regarding occupational hazard factors and their intensities to which workers are exposed could not be collected, preventing an assessment of the potential impact of such factors (e.g., dust and noise) on occupational stress. Third, while the concept of OHL in this study encompasses multiple dimensions, including occupational health knowledge, occupational protection skills, and healthy behaviors/lifestyles, the strength of the association between each dimension and occupational stress has not been analyzed in greater detail.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe influence of health literacy on mental health has garnered considerable interest in recent years. This study presents limited, yet meaningful, evidence concerning the relationship between occupational health literacy and occupational stress. The findings indicate a notable negative correlation between these two variables. Given the extensive array of detrimental health outcomes associated with occupational stress, it is proposed that enhancing occupational health literacy may mitigate occupational stress and promote better mental health. Future research should involve larger cohort studies to yield more comprehensive evidence and to further elucidate the underlying mechanisms connecting occupational health literacy and occupational stress.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Health literacy\u003c/p\u003e\n\u003cp\u003eOHL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Occupational health literacy\u003c/p\u003e\n\u003cp\u003eCOSS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Core occupational stress scale\u003c/p\u003e\n\u003cp\u003eIQ-NKPOHLMS \u0026nbsp; National key population occupational health literacy monitoring survey\u003c/p\u003e\n\u003cp\u003eIQR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Interquartile ranges\u003c/p\u003e\n\u003cp\u003eRCS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Restricted cubic splines\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThanks to the experts from the Institute of Occupational Health and Poison Control of the Chinese Center for Disease Control and Prevention for their guidance and help. Thank you also to all participants who helped to obtain written informed consent regarding the survey and to distribute the questionnaire to the subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHYZ: Data collection and analysis, Conceptualization, Methodology, Writing\u0026ndash;review \u0026amp; editing. WLZ: Conceptualization, Methodology, Writing\u0026ndash;review \u0026amp; editing, Funding acquisition. YHH, JLW: Conceptualization, Methodology. JYS: Conceptualization, Supervision, Methodology, Resources. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge funding from the Gansu Provincial Science and Technology Program (Grant No.: 20JR10RA420).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding author can provide the data supporting the study\u0026apos;s conclusions upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in strict accordance with the Declaration of Helsinki and approved by the Ethics Review Committee of the Gansu Provincial Center for Disease Control and Prevention (ethics number: 2024066), and the study subjects voluntarily participated and obtained informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conficts of interest.\u003c/p\u003e\n\u003cp\u003eAuthor details\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Occupational Health, Gansu Center for Disease Control and Prevention, Lanzhou, 730000, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eGansu Center for Disease Control and Prevention, Lanzhou, 730000, China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLeso V, Fontana L, Iavicoli I. 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Am J Public Health. 2019;109(11):e13\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2105/AJPH.2019.305278\u003c/span\u003e\u003cspan address=\"10.2105/AJPH.2019.305278\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Occupational health literacy, Health literacy, Occupational stress, Mental health, Longer working hours","lastPublishedDoi":"10.21203/rs.3.rs-6962822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6962822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e Low levels of health literacy (HL) have been consistently associated with adverse mental health outcomes, including depression and anxiety; however, there is currently a lack of evidence establishing a connection between HL and occupational stress. This study aims to investigate the influence of occupational health literacy (OHL) on occupational stress, thereby providing a scientific foundation for mitigating occupational stress among workers in the industrial production sector.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e The research involved a sample of 3,772 workers from the metal mining, metallurgy, and non-metallic mineral products industries in Gansu Province. The Individual Questionnaire of the National Key Population Occupational Health Literacy Monitoring Survey (IQ-NKPOHLMS) was employed to evaluate the workers' personal OHL, while the Core Occupational Stress Scale (COSS) was utilized to measure occupational stress. To analyze the association, weighted logistic regression models, restricted cubic splines (RCS), and subgroup analyses were conducted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eThe findings from the weighted logistic regression indicated that for each 1-point increase in OHL score, the likelihood of experiencing occupational stress decreased by 2%. Workers with a personal OHL score of 80% or higher exhibited a significantly reduced risk of occupational stress. The RCS analysis revealed a linear dose-response relationship between OHL and occupational stress. Furthermore, working hours emerged as a significant effect modifier, suggesting that longer working hours may amplify the relationship between OHL and occupational stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e There exists a negative correlation between OHL and occupational stress, particularly evident among workers with extended working hours. Consequently, we advocate for the enhancement of OHL as a strategy to alleviate occupational stress.\u003c/p\u003e","manuscriptTitle":"Association between occupational health literacy and occupational stress among workers in metal mining, metallurgy and non-metallic manufacturing in Gansu,China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-10 10:31:06","doi":"10.21203/rs.3.rs-6962822/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-16T18:13:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-16T06:41:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9069800160194416473970411264728163735","date":"2025-09-16T06:01:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-31T14:18:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"335045323900074167181341455811810441185","date":"2025-07-08T11:32:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-08T11:19:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-27T07:24:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-26T23:39:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-26T23:37:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-06-24T07:28:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fbf2bf4c-07ad-4a60-a48d-beed4c4d33cd","owner":[],"postedDate":"July 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T15:59:12+00:00","versionOfRecord":{"articleIdentity":"rs-6962822","link":"https://doi.org/10.1186/s12889-025-25511-0","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-11-25 15:56:51","publishedOnDateReadable":"November 25th, 2025"},"versionCreatedAt":"2025-07-10 10:31:06","video":"","vorDoi":"10.1186/s12889-025-25511-0","vorDoiUrl":"https://doi.org/10.1186/s12889-025-25511-0","workflowStages":[]},"version":"v1","identity":"rs-6962822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6962822","identity":"rs-6962822","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}