STRENGTHS AND LIMITATIONS OF THIS STUDY

The study boasts a substantial sample size of 5738 railway locomotive stewards, enhancing the statistical power and generalisability of the findings to this occupational group. Including railway locomotive stewards from multiple depots ensures a diverse population representation, capturing potential variations in work environments and stressors.

This study has a cross-sectional design, which restricts our ability to establish causal relationships between effort–reward imbalance (ERI) and sleep quality.

Relying on self-reported data might introduce response bias, as participants may under-report or over-report their experiences.

The study focused on a specific group within a single organisation, limiting the generalisability of the findings to other populations or settings.

Potential confounding factors, such as personal lifestyle choices or pre-existing health conditions, were not fully controlled, which might have influenced the results.

Introduction

Sleep disorders encompass a range of conditions that disrupt the normal sleep patterns. These disorders can manifest as difficulty falling asleep, staying asleepor experiencing restorative sleep.1Common sleep disorders include insomnia, sleep apnoea, restless legs syndromeand circadian rhythm sleep disorders.2The consequences of these disorders are significant and can lead to daytime sleepiness, impaired cognitive functionand increased risk of chronic health problems.3Sleep disorders, an important risk factor causing psychological and physical fatigue,4are particularly important for those working in the railway system,characterisedby a heavy workload, compact operating proceduresand highly concentrated attention.5Therefore, it is essential to identify and assess the factors affecting sleep quality and provide effective interventions.

When considering the health status of railway locomotive stewards, it is essential to acknowledge the multiple stressors they face. With the development of the national railway, the increase in locomotive running speeds, and the heightened standards for work quality, the operational demands have become more stringent.6 Due to their challenging work environment, railway locomotive stewards are a focus of health departments as their well-being directly affects railway safety. Continuous noise and vibration from locomotives may impair hearing and disrupt sleep, highlighting their vulnerability in this demanding occupation. In addition, the variability and instability of their working environment have a crucial role. Due to the long-distance and cross-regional nature of the railway routes, stewards are often required to adjust to different work locations, which can disrupt their regular sleep patterns. The work hours also contribute to sleep disturbances.7 Stewards frequently must work at night or extend their shifts, which tends to disrupt their natural circadian rhythms.8 9 Considering these numerous influencing factors, the sleep quality of railway workers is a matter of great concern. While they grapple with the demands of their job, the impact on their sleep is an issue that cannot be overlooked. Given the direct connection between a steward’s well-being and the safety of railway operations, understanding and improving their sleep quality will be beneficial for their health and crucial for maintaining the high safety standards required in railway transportation.10

Numerous scholars worldwide have investigated occupational stress and sleep quality across different occupational populations.11 The effort–reward imbalance (ERI) model, a widely acknowledged framework in occupational health, is extensively used in assessing work tension and occupational stress.12–14 This model evaluates the balance between the efforts made by employees and the rewards they receive. It has been empirically linked to cardiovascular diseases, depression, pain and other diseases, as well as symptoms in several studies.15–17 ERI can be associated with work-related stress and depressive and anxiety symptoms.18–20 Mental health issues can be a risk factor for harm and accidents in hazardous work environments.21 22 Hence, identifying and controlling the factors affecting mental health in railway locomotives has public health significance.

However, the application of the ERI model in studying the sleep quality of railway locomotive stewards remains relatively unexplored. Hence, this study aimed to evaluate the correlation between ERI and sleep quality among railway locomotive stewards. The hypothesis was that ERI was associated with sleep disturbances in railway locomotive stewards.

MethodsStudy design and populations

This cross-sectional study enrolled railway locomotive stewards from the Lanzhou Bureau Group, China Railway, between July and August 2022. Workers from the Lanzhou Railway Bureau of China Railway (Lanzhou West Locomotive Depot, Jiayuguan Locomotive Depotand Yingshuiqiao Locomotive Depot) were enrolled through convenience sampling from all three locomotive depots of Lanzhou Railway Bureau. The potential participants were selected according to the predefined inclusion and exclusion criteria. The inclusion criteria were (1) on-the-job employees engaged in railway locomotive operation driving, (2) participants aged≥18yearsand with≥1yearof experienceand (3) participants who gave informed consent and participated in this survey voluntarily. The exclusion criteria were (1) individuals taking psychotropic drugs for a long time or who could not complete the questionnaire independently due to organic brain lesions, (2) participants who had suffered major mental trauma within the6monthsbefore the surveyor (3) participants who did not cooperate with thesurvey.

Questionnaires

The demographic characteristics that may affect the sleep conditions of railway locomotive stewards were initially identified by consulting relevant data. The questionnaire was designed to collect demographic information, including age, gender, type of work, types of railway locomotives on duty, education, marital status, working seniority, number of jobs changed in the last 5 years, whether or not they worked in shifts, weekly working hours, types of contracts and professional title.

ERI Questionnaire

The Chinese version of theEffort-Reward Imbalance（ERI）Questionnairedeveloped byLiet al 23was used. The scale consists of 23 questions about effort–reward and overcommitment. Items #1–17were rated on a 5-point Likert scale, with a total effort score ranging from6to30points and a total reward score ranging from11to55points. Items #18–23measured commitment using a 4-point scale(1–4points each), with a total overcommitment score ranging from6to24points.24The Cronbach’s alpha coefficients for the three subscales of effort, rewardand overcommitment were 0.798, 0.856and 0.823, respectively, indicating that the internal consistency of the questionnaire was good. The weighted ratio proposed bySiegristwas used to calculate the sense of ERI,15where ERI=(total effort score/total reward score)×(total reward items/total effort items), with ERI>1for higheffort/lowreward,ERI=1for an effort–reward balanceand ERI<1for loweffort/highreward. Based on the categorisation ofChen Siluet al,25one-third of the individuals with the top total overcommitment score were taken as high overcommitment,that is,>18indicated high overcommitmentand≤18indicated low overcommitment.

Pittsburgh Sleep Quality Index Scale

Pittsburgh Sleep Quality Index (PSQI) consists of 19 self-assessed and 5 other-assessed items, which are used to evaluate the sleep quality of the study participants during the last month.26 Items #19 and #5 were not involved in the scoring, and the remaining items included seven aspects of sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disorders, hypnotics use and daytime dysfunction. A 0–3 scale was used, with ‘0’ indicating without difficulty and ‘3’ meaning very difficult. The total score ranged from 0 to 21, with a score of >14 indicating poor sleep quality, 8–14 indicating fair sleep quality and <8 indicating good sleep quality. The total score of the PSQI scale equalled the sum of the dimension scores, and Cronbach’s alpha coefficient for this scale was 0.879.

Sample size calculation

Sample size estimation was carried out using Gpower V.3.1 software, taking a moderate effect size of 0.15, a permissible error α of 0.05, a two-sided 95% for test efficacy 1−β and a maximum number of independent variables of 15. Hence, the minimum total sample size was estimated to be 567 cases (figure 1), but this study enrolled all willing and eligible individuals.

Figure 1

Sample size estimation chart made using Gpower V.3.1.

Quality control

Before the investigation, the project team obtained support from each locomotive depot’s management and supervisory departments. A dedicated person was identified at each depot to cooperate with the investigation work. The investigator conveyed the purpose, content and inclusion/exclusion criteria of the study to the responsible persons of each locomotive depot, and they communicated to all eligible crew members. Subsequently, the responsible persons established a survey group on WeChat. The survey was administered using the Wenjuanxing online survey platform. QR codes were generated and shared online through the WeChat groups to answer the questionnaires.

In addition, before the survey, the investigators were professionally trained, received unified instructions and agreed with the surveyed unit to investigate the on-site survey questionnaire’s time, place and filling methods. The survey respondents were introduced to the purpose of the survey, the content and filling requirements, etc. All the respondents’ concerns were addressed, emphasising that questionnaires were anonymous, which helped gain the respondents’ trust and obtain informed consent. In order to reduce the survey bias, the faculty members of the university responsible for teaching and research in health statistics and epidemiology, and with rich experience in data analysis and processing, as well as quality control of on-site surveys, verified and analysed the collected questionnaires. Questionnaires with an answer time of <30 min, incomplete answers and severe logical errors were excluded. The original questionnaire for this study consisted of 4 scales with a total of 180 questions. Only the results of two scales were used for analysis in the article. According to the estimated time to read and understand all 180 questions, if the answer time was <30 min, it hinted that the participants randomly chose answers without reading or understanding the questions.

Statistical analysis

SPSS V.25.0 (IBM) was used for statistical analysis. Continuous data were expressed as mean±SD; two groups were compared using Student’s t-test and multiple group comparisons were analysed using the one-way analysis of variance (ANOVA). Categorical count data were expressed as n (%). The association between ERI and sleep quality was analysed using Spearman correlation analysis. Regression analyses were performed using sleep quality grading as the dependent variable and demographic characteristics with statistically significant differences between the degree of ERI and the PSQI scores in the one-way ANOVA as the independent variables. The results of the parallel test were p<0.01, which indicated that the data were unsuitable for the sequential logistic regression analysis. Therefore, stepwise multivariable logistic regression analysis was performed to analyse the main risk factors for sleep quality. Two-sided p values <0.05 were considered statistically significant.

Results

The study initially surveyed 6219 participants, but 397 were excluded due to answer times <30 min and 84 due to severe logical errors. Finally, 5738 valid questionnaires were included, with a response rate of 92.27%. Among them, 1931 respondents were from the Lanzhou West Locomotive Depot, 1357 from the Jiayuguan Locomotive Depot, and 2450 from the Yingshuiqiao Locomotive Depot. The participants were 30.85±6.91 years old. There were 4433 electric locomotive drivers (77.26%), 928 diesel locomotive drivers (16.17%) and 377 railway locomotive stewards (6.57%). There were 1157 respondents with a high school diploma or less (20.17%), 3526 with a college degree (61.45%), 643 with a bachelor’s degree (11.21%) and 12 with a master’s degree or higher (0.21%). Regarding working seniority, 998 respondents were intermediate workers (17.39%), and 3688 were senior workers (64.27%). There were 1924 respondents (33.53%) with <5 years of working experience and 2227 people (38.81%) with >20 years of working experience. In addition, 3294 respondents (57.41%) worked >50 hours weekly, and 4450 (77.55%) were required to work shifts and had night shift work.

Among all participants, the PSQI score was 11.52±3.95; 2304 had good sleep quality, 1590 had fair sleep quality, and 1844 had poor sleep quality. The PSQI scores were significantly higher (p<0.05) for those working in Jiayuguan Locomotive Depot, 30–40 years old, electric locomotive drivers, types of railway locomotives on duty, master degree or above, 6–10 years of working experience, working >50 hours weekly and senior workers (table 1).

Table 1

Comparison of total sleep quality index scores under different demographic characteristics

High-overcommitment participants were more likely to have significantly higher PSQI than the low-overcommitment participants (p<0.001). High-effort/low-reward participants were more likely to have significantly higher PSQI than the low-effort/high-reward and effort-reward balance participants (p<0.001) (table 2).

Table 2

Comparison of total sleep quality index scores of railway locomotive stewards at different degrees of effort–reward imbalance perception

There was a significant positive correlation between the sense of ERI and overcommitment scores and the five dimensions of sleep quality, sleep latency, sleep disorders, use of hypnotics, and daytime dysfunction, and the total score of the PSQI (all p<0.01) (table 3).

Table 3

Correlation analysis between effort–reward imbalance and sleep quality dimensions (r value)

Stepwise multivariable logistic regression analysis showed that, compared with poor sleep quality, Jiayuguan Locomotive Depot workers (OR 0.775, 95% CI 0.587 to 0.971, p=0.028), electric locomotive drivers (OR=0.499, 95% CI 0.316 to 0.786, p=0.003), passenger train locomotive drivers (OR 0.209, 95% CI 1.313 to 3.337, p=0.002), working <40 hours weekly (OR 2.291, 95% CI 1.686 to 3.112, p<0.001), working 40–50 hours weekly (OR 1.602, 95% CI 1.299 to 1.977, p<0.001), senior titles (OR 0.727, 95% CI 0.570 to 0.928, p=0.010), high effort/low reward (OR 2.812, 95% CI 2.218 to 3.564, p<0.001) and low overcommitment (OR 5.848, 95% CI 4.710 to 7.261, p<0.001) were independently associated with fair sleep quality. In addition, electric locomotive drivers (OR 0.535, 95% CI 0.364 to 0.787, p=0.001), diesel locomotive drivers (OR 0.567, 95% CI 0.348 to 0.924, p=0.023), passenger train locomotive drivers (OR 1.471, 95% CI 1.005 to 2.155, p=0.047), working <40 hours weekly (OR 1.549, 95% CI 1.196 to 2.006, p=0.001), working 40–50 hours weekly (OR 1.340, 95% CI 1.141 to 1.574, p<0.001), high school diploma or less (OR 1.448, 95% CI 1.062 to 1.975, p=0.019), high effort/low reward (OR 1.237, 95% CI 1.006 to 1.521, p=0.044), balanced effort reward (OR 0.653, 95% CI 0.478 to 0.892, p=0.007) and low overcommitment (OR 2.553, 95% CI 2.224 to 2.931, p<0.001) were independently associated with good sleep quality (table 4).

Table 4

Stepwise multivariable logistic regression analysis for sleep quality

Discussion

This study revealed that the proportion of railway locomotive stewards in the ERI was acceptable, but the overall sleep conditions were not optimistic. The sense of ERI and overcommitment scores were correlated with each dimension of sleep quality. Although the study was cross-sectional and causality could not be analysed, the results may help the department managers improve their management system, rationalise the workflow, optimise the labour conditions and improve the working environment to help improve ERI.

These findings show that the effort of the majority of the survey respondents was higher than the reward. In addition, the groups with fair and poor sleep conditions occupied the largest proportion, showing that the ERI of the railway locomotive steward was severe, and the sleep conditions were also unsatisfactory. The ERI and overcommitment scores were higher than those reported by Gao et al 27 when studying nurses but closer to the results of Qian28 in their study of work-related stress in railway locomotive stewards. It suggests that the ERI of the railway locomotive stewards may be higher than for other occupations, which might be due to the nature of the work they are engaged in, the working environment they are working in and the management mechanisms. The sleep quality score observed here was lower than reported by Lu Feng et al 29 on some railway locomotive stewards in Zhengzhou City, and the proportion of fair and poor sleep quality was lower than reported by Haiming30 on the sleep conditions of railway locomotive stewards in the Bureau Group Corporation of China Railway. Nonetheless, the results are consistent with those of the survey of railway locomotive stewards in Bureau Group Corporation of Northwest China Railway by Liu Rui and Yuzhen. 31 The geographical differences in sleep quality are related to the transportation tasks undertaken by different Bureau Group of China Railway. The large gap between the work-related intensity and stress of railway locomotive stewards caused by the different flow of people is probably related to the different Bureau Groups of China Railway.

A previous study32 has shown that the population with ERI generally has relatively lower income, higher educational requirements for jobs and heavy workloads. The role of railway locomotive stewards, which is inherently risky and often necessitates shift and night work, leads to irregular lifestyles. It is compounded by the need to continually update their skills with new technologies in the railway system, increasing their work investment and expectations for adequate rewards. However, the actual rewards received frequently fall short of these heightened expectations, placing a majority in a state of high–effort/low–reward imbalance. Interestingly, the survey results revealed that the proportion of high overcommitment among these workers was not as significant as expected in such a demanding work environment. Overcommitment is another important concept in the ERI evaluation model, which focuses on measuring the way individuals respond to the demands of their work, referring to a set of attitudes, behaviours and emotions arising when individuals work excessively hard and have a strong need to be appreciated and respected.33 The results of this survey suggested that a high-effort/low-reward work state was more likely to produce low overcommitment or could be the leading cause of railway locomotive stewards experiencing job burn-out.

The correlation analysis showed a significant positive correlation (p<0.01) between the sense of ERI and overcommitment scores of railway locomotive stewards and the five dimensions of sleep quality, sleep latency, sleep disorders, use of hypnotics and daytime dysfunction, as well as the total score of the PSQI, which means that the more severe the sense of ERI, the more overcommitment to the job and the poorer the sleep quality. After controlling for demographic variables, high effort/low reward and overcommitment were the main risk factors for sleep quality among railway locomotive stewards (all p<0.01), indicating that both the continuous high effort/low reward state and the personal depletion caused by overcommitment could negatively affect sleep quality, which is consistent with the findings of Guangchao et al,34 Wu Hui et al 35 and Gu Kunpeng et al. 36 When there is an imbalance between effort and reward, individual work enthusiasm decreases. They cannot cope well with high-intensity or technical work, leading to decreased sleep quality and increased sleep scores.37 On the other hand, enhanced support and affirmation at work, both material and psychological, can improve sleep quality. Due to their work’s technical and risky nature, railway locomotive stewards invest substantial time and energy in their work, facing challenges from constant changes in railway technology. Compared with other industries, this heightened complexity and lack of control in their work likely exacerbate occupational stress, negatively impacting their sleep quality. This effect, combined with ERI, may escalate the risk of sleep disorders among these workers.

Research on the relationship between occupational stress and sleep quality in China and internationally is mainly focused on occupations with excessive workloads and high-stress levels, such as social service industries, field operations, and industrial and mining employment. The previous studies on train attendants mainly analysed the impact of occupational stress on physical and mental health, and few reports separately explore the mechanism of occupational stress on sleep quality.29–31 The previous studies mainly focused on areas with developed railway transportation, such as Northeast and North China, with only occasional reports on Qinghai and Xinjiang in Northwest China. Lanzhou Railway Bureau Group is located in Gansu Province and is one of the largest transportation companies in Northwest China. This study focused on all locomotive crew members of Lanzhou Railway Bureau, and the sample has a certain representativeness. The results can provide a scientific basis for the formulation and implementation of policies by the railway department in the northwest region.

This study has some limitations. First, this study had a cross-sectional design, which prevents establishing causal relationships between ERI and sleep quality. Second, relying on self-reported data might introduce response bias, as participants may under-report or over-report their experiences. Third, the study focused on a specific group within a single organisation, limiting the generalisability of the findings to other populations or settings. Finally, potential confounding factors, such as personal lifestyle choices or pre-existing health conditions, were not fully controlled, which might have influenced the results. Future research could benefit from a longitudinal design and a more diverse sample to address these limitations.

In conclusion, many railway locomotive stewards are in a high-effort/low-reward imbalance state, with suboptimal overall sleep conditions. ERI was correlated with sleep quality. Relevant departments should improve their work management system, optimise the incentive mechanism, and carry out occupational hygiene and health education to improve the sleep quality of their workers.

Data availability statement

All data relevant to the study are included in the article or uploaded as online supplemental information.

Ethics statementsPatient consent for publication

Not applicable.

Ethics approval

This study involves human participants and was approved by the Ethics Committee of the School of Public Health, Lanzhou University (No. IRB22053101). Participants gave informed consent to participate in the study before taking part.