Investigation of the association between ergonomic conditions of nursing workstations and the risk of musculoskeletal disorders among nurses: a case study in selected hospitals of Shahid Beheshti University of medical sciences

Abstract

Background

Work-related Musculoskeletal Disorders (WMSDs) have been identified as the most common occupational health problem among nurses. Therefore, given the critical role of nurses in the healthcare system, this study investigates the importance of the ergonomic design of nursing workstations in reducing musculoskeletal disorders among nurses.

Methods

In this cross-sectional analytical study conducted in 2024, nursing workstations and nurses working in two selected hospitals in Iran were studied using a census method. This study involved 76 nurses across 32 workstations, and data related to the nurses and workstations were collected using a demographic/occupational characteristics checklist, the Ergonomic Screening and Prioritization Tool (ESPT), and the Nurse Station Ergonomic Assessment (NSEA) tool. Data analysis was performed using SPSS software version 26.

Results

The mean ESPT risk scores were 23.45 for men, 18.77 for women, and 19.45 overall for the studied nurses, indicating a medium risk level. The mean total NSEA score was 45.09 for men, 43.21 for women, and 43.49 overall for nurses working at the nurse stations. A significant negative correlation (r = -0.434) (p-value < 0.05) was also observed between the ergonomic assessment score of the stations and the risk of musculoskeletal disorders, indicating the positive impact of improving ergonomic conditions on reducing the risk of these disorders. Furthermore, the results showed that variables such as gender, weight, working hours, employment status, and workplace ergonomic conditions are all important determining factors in the occurrence of musculoskeletal disorders among nurses.

Conclusion

By focusing on the eight domains of the NSEA tool, targeted interventions can be designed and implemented in each section to gradually achieve ideal conditions. For example, measures such as using ergonomic and adjustable equipment tailored to nurses’ body dimensions and redesigning the layout of workstations can promote nurses’ health. Therefore, it is recommended that healthcare administrators and policymakers prioritize the continuous assessment and optimization of ergonomic conditions in hospital occupational safety and health programs. Overall, these results further reveal the necessity for serious investment in optimizing the ergonomic standards of nursing workstations.

Background

Ergonomics examines the interaction between individuals and work systems. This science has a multidisciplinary approach, supported by three groups of related factors. In fact, ergonomics encompasses physical, cognitive, and organizational aspects. Physical factors address issues related to workplace layout and the optimization of efficiency and effectiveness. Cognitive factors focus on mental processes and engage the senses. Organizational factors are also highly important for managing work responsibilities, work procedures, and communication processes [1].

In today’s world, with the increasing population and the growing need for healthcare services, the role of nurses as one of the fundamental pillars of health systems is of particular importance. The quality of healthcare in hospitals also largely depends on teamwork. Factors such as the location, design, and layout of nurse stations, ease of access, visibility, and furnishings play a key role in facilitating this cooperation [2]. The nurse station is also recognized as one of the most important interactive spaces in hospital. Numerous studies have shown that the design of nurse stations, alongside work processes, technological facilities, and organizational culture, can have significant impacts on the health, satisfaction, well-being, and efficiency of nursing staff, reduce work-related stress, and enhance the safety and quality of services provided to patients [3–6]. Nurses are not only responsible for providing specialized care to patients but are also exposed to significant physical and psychological pressures resulting from inappropriate working conditions [7]. One study mentioned that if the physical work environment is poorly designed (i.e., the design, structure, and organization of nursing workstations), healthcare workers are at risk of musculoskeletal injuries [8]. Also, while part of the injuries are due to the physical demands of patient care, numerous factors, including poor air quality, excessive noise, crowded workstations, and inadequate lighting, also contribute to these problems [9]. Research has shown that one of the most important strategies for reducing musculoskeletal disorsers in work environments is paying attention to the characteristics of the workstation and designing the workplace ergonomically [10]. Therefore, assessing the ergonomic status of these stations using standardized tools like NSEA1 can help design and implement effective ergonomic interventions [1]. In fact, NSEA is a quick and simple tool for managers to ensure compliance with legal requirements and promote best practices in workplace design standards in hospitals. This tool has good psychometric properties and can be used to identify challenges for those working in hospital wards and support the implementation of targeted interventions to improve human-environment interactions [1].

Work-related musculoskeletal disorders are recognized as symptoms arising from occupational risk factors, such as persistent pain in the body’s structures, including: bones, nerves, tendons, joints, ligaments, and even the circulatory system [11]. Work-related Musculoskeletal Disorders (WMSDs) have been identified as the most common occupational health problem among nurses [9, 11–14], and a systematic review of 34 articles concluded that the prevalence of WMSDs in nurses ranges from 33% to 88% [15]. Its prevalence is also very high among Iranian nurses [16]. A study in Iran estimates that 33% of all sick leave cases among nurses are related to musculoskeletal disorders [17]. The high rate of musculoskeletal disorders, especially low back pain, has been reported as one of the major impacts of WMSDs among nurses [8, 18, 19]. Therefore, preventing these disorders can easily lead to high productivity, job satisfaction, and workplace safety [20]. Nurses, in particular, show the highest prevalence of WMSD due to the physical demands of their job tasks. Repetitive work tasks, awkward body postures such as bending, stooping, and reaching, combined with physically strenuous activities like lifting, transferring, and repositioning patients can lead to WMSD [9, 21]. In general, nurses’ work in hospitals involves short deadlines for task completion, stress and anxiety, shift work, long working hours, etc. Methods for assessing musculoskeletal disorders, based on their characteristics and type of application, lead to the identification of high-risk tasks and their associated factors, providing intervention priorities for reducing or eliminating risk factors. Since MSD risk assessment methods do not provide a comprehensive assessment of the factors contributing to WMSDs [16], there is a need for a comprehensive and easy-to-use tool for a complete risk assessment, such as the ESPT2 technique. This pen-and-paper technique was developed by the North Carolina Ergonomics Center to identify the level of ergonomic stressors, risk assessment, screening, and prioritization of jobs or tasks [22]. By assessing the level of risk for work-related musculoskeletal disorders in nurses, actions can be taken to reduce or eliminate these problems by examining the nature and location of these issues in the workplace for the prevention of ergonomic risks.

The overall objective of this study is to ergonomically assess nursing workstations using the NSEA tool, screen and prioritize them, as well as assess the level of musculoskeletal disorder risk in nurses using ESPT, and to investigate the correlation and relationship between these two. The results of this assessment can contribute to the development of guidelines and protocols for ergonomic design in hospitals, which will not only improve nurse efficiency but also enhance the patient satisfaction.

Methods

Study design

This cross-sectional analytical study was conducted in 2024 with the aim of ergonomically assessing, screening, and prioritizing nurse stations, as well as evaluating the level of risk for musculoskeletal disorders among nurses in selected hospitals affiliated with Shahid Beheshti University of Medical Sciences, Iran. After the project was approved and the necessary permits, coordination was made with the hospitals, and the required correspondence was completed.

Participants

A census method was used to obtain the samples, and all nurses working at the nurse stations were included in the study. These nurses were selected as participants due to their exposure to various work postures that could potentially lead to musculoskeletal disorders. They worked in the following departments: General Surgery, Gastroenterology, Endocrinology, Oncology, Hematology, Critical Care (ICU and CCU), Vascular Surgery, Organ Transplantation, Bone Marrow Transplantation, Psychology, Cardiology, Neurology and Urology, Stereotaxic, Post, Gynecology and Obstetrics, Pediatrics, SCU and NICU, Internal Medicine, Neurosurgery, Orthopedics, Kidney Transplantation, Day Care, and Oral and Maxillofacial Surgery. Inclusion criteria consisted of willingness to participate in the study. Exclusion criteria included participants’ unwillingness to continue cooperation or leave the nursing profession during the study. Additionally, individuals must not have had any congenital musculoskeletal disorders or a history of specific underlying diseases (inflammatory joint diseases, gout, etc.), must not have had a history of surgery, or sustained an injury in a non-occupational accident. They also must not have had a second job. To adhere to ethical considerations, full explanations regarding the study procedure were provided before the study began.

The number of observers was set at two, who were occupational health engineers. These individuals were selected with a minimum of two years of experience in assessing the risk of musculoskeletal disorders and were trained in the assessment methods during a three-hour training session.

Data collection tools

In this study, data related to the nurses and workstations were collected using: (1) demographic/occupational characteristics checklist, (2) The Ergonomic Screening and Prioritization Tool (ESPT), and (3) The Nursing Station Ergonomic Assessment (NSEA) tool.

1. Demographic/Occupational Characteristics Checklist

The checklist included the following items: gender (male, female), age (years), height (cm), weight (kg), work experience (years), working hours, marital status (single/married), and type of employment status (permanent and contractual, contract-based, plan-based, Other.).

• 2. Ergonomic Screening and Prioritization Tool (ESPT)

This tool was developed by the North Carolina Ergonomics Center. In this method, 10 key body regions (neck, back, right and left shoulder, right and left elbow, right and left hand/wrist, right and left leg) that are at risk of musculoskeletal injuries are assessed [22]. Figure 1 shows the 10 key body regions evaluated in this method. To calculate the score, the variables “Motion,” “Force,” and “Posture” are used. This means the aforementioned variables are rated for each of the 10 body regions, then combined via a matrix to yield its score. Finally, these scores are summed to obtain a final risk level score. The minimum and maximum total scores an individual can have are 10 and 40, respectively. If the total body score is less than or equal to 16, the task is considered low-risk; if the total body score is between 16 and 24, it is medium-risk; and if it is equal to or greater than 25, it is considered a high-risk task. Tasks that receive a medium or high score require more detailed examination [22]. The Ergonomic Screening and Prioritization Tool (ESPT) has demonstrated high reliability and validity in assessing musculoskeletal disorders among nurses, with intraclass correlation coefficients (ICC) exceeding 0.9 [16].

Fig. 1.

The 10 areas assessed in the ESPT method. Note: F = force; M = motion; P = posture. In the matrix: L = low risk; M = medium risk; H = high risk [22]

Below, the method for assessing and scoring the “Motion,” “Force,” and “Posture” variables in the ESPT method is described.

1. Motion Assessment: Based on the entire set of tasks, the assessment of motions for each body part is performed according to Fig. 2.

2. Force Assessment: Based on the worst task, the force assessment is performed according to Fig. 3.

3. Posture Assessment: Based on the worst task, the posture assessment is performed according to Fig. 4.

Fig. 2.

Motion ratings in the ESPT method [23]

Fig. 3.

Force ratings in the ESPT method. Note: MVC = Maximum Voluntary Contraction [22]

Fig. 4.

Posture ratings in the ESPT method [22]

The “Motion,” “Force,” and “Posture” variables are combined using the relevant matrix (Fig. 1) and then obtain job total score in the ESPT method (Fig. 5).

Fig. 5.

Calculation of risk score/level in the ESPT method [22]

• 3. Nursing Station Ergonomic Assessment (NSEA) Checklist

The Nursing Station Ergonomic Assessment (NSEA) tool possesses good psychometric properties. Its validity was assessed using formal and content validity in the study by Choobineh et al. in 2021 [1]. The NSEA provided eight domains and 64 items: Layout and Location (7 items), Workspace (11 items), Security-Safety (5 items), Environmental Conditions (8 items), Counter (8 items), Chair (13 items), Desk (9 items), and Monitor (3 items) [1]. The items in the tool are evidenced based. The scoring method for this checklist is based on “Yes” and “No” responses. The target for any nurse workstation would be that all 64 items are endorsed “yes”. The total number of “Yes” responses will ultimately be determined. This ensures compliance with ergonomic standards and supports workplace health. Scores were categorized as Low (< 32, indicating poor ergonomic conditions), Moderate (32–48, fair conditions), or High (>48, good conditions), based on tertial distribution adapted from validation studies [1].

Statistical analysis

Statistical analyses were performed using SPSS software (version 26; IBM Corp., Armonk, NY, USA). The Kolmogorov-Smirnov test was employed to assess data normality, with a significance level of p > 0.05 indicating a normal distribution. Descriptive statistics were presented as mean ± standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. Comparative analyses between male and female groups were conducted using independent samples t-tests for continuous variables and chi-square tests for categorical variables. Pearson correlation coefficients were utilized to evaluate the relationships among risk scores, ergonomic scores, and associated sub-factors, with statistical significance determined at the 95% confidence interval (p < 0.05). Ordinal logistic regression with a logit link function was applied to investigate the association between musculoskeletal disorder risk levels (ordinal outcome) and ergonomic scores. This model was adjusted for confounding variables, including age, sex, marital status, height, weight, job type, professional experience, and daily working hours. Regression coefficients reflected the change in log-odds of transitioning to a higher risk category per unit increase in the predictor variable. All hypothesis tests were two-tailed, with statistical significance defined as p < 0.05. The proportional odds assumption was verified using the Brant test (p > 0.05). Multicollinearity was assessed via VIF (< 5 threshold); no issues were found. Also Inter-rater reliability was assessed via ICC (0.87) for scores and Kappa (0.82) for items, following a 3-hour training calibration session.

Results

In this study, 76 nurses across 32 stations were evaluated. Table 1 presents the demographic/occupational characteristics of the nurses by gender and for all nurses in the workstations.

Table 1.

Description of Demographic/Occupational characteristics by gender and total number of nurses in the workstations

Variable	Men (n = 11) Mean (Standard deviation)	Women (n = 65) Mean (Standard deviation)	Total (76) Mean (%)	P-value
Age	29.91(5.52)	35.78(9.00)	34.93(8.81)	0.040
Height	175.64(5.80)	159.43(21.06)	161.78(20.39)	0.014
Weight	75.55(12.78)	65.40(15.44)	66.87(15.34)	0.043
Marital				0.042
Single	10(90.9)	36(55.4)	46(60.5)
Married	1(9.1)	29(44.6)	30(39.5)
Employment status type				0.687
Permanent	6(54.5)	45(69.2)	51(67.1)
Contract-based	1(9.1)	7(10.8)	8(10.5)
Plan-based	2(18.2)	7(10.8)	9(11.8)
Other	2(18.2)	6(9.2)	8(10.5)
Work experience (years)	11.82(17.89)	12.54(9.07)	12.43(10.63)	0.837
Daily working hours	10.55(3.41)	9.54(2.90)	9.68(3.05)	0.315

Inter-rater reliability was assessed using post-test ICC for continuous scores (ESPT/NSEA) and Cohen’s kappa for categorical items. ICC = 0.87 (good agreement); kappa = 0.82 (strong).

The Kolmogorov-Smirnov test was used to assess the normality of the quantitative variables in the study. The results indicated that all variables followed a normal distribution (p > 0.05), which allowed for the use of parametric tests in the analysis. Table 1 revealed significant gender differences among nurses working at the workstations. As observed, the majority of nurses were female (85.52%). Females were on average significantly older than males (35.78 vs. 29.91 years). This age difference corresponded with expected variations in basic anthropometric traits. Males were also significantly taller (175.64 vs. 159.43 cm) and heavier (75.55 vs. 65.4 kg). The high standard deviation in female height indicated greater variability within this group.

A significant difference was observed in marital status. The majority of males (90.9%) were single, whereas only 55.4% of females were single. 44.6% of females were married compared to only 9.1% of males. No significant gender difference was observed regarding employment status type. Both groups primarily consisted of permanent employees, indicating similar professional standing.

Further similarities were found in work experience and daily working hours. Males had an average work experience of 17.89 years, while females had 12.54 years of experience. The wide standard deviation in male work experience suggested significant variability within this group. Similarly, males worked 10.55 h per day, while females worked 9.54 h.

High variance in male work experience (SD = 17.89) was reviewed; outliers were valid and did not skew results (Cook’s distance < 1).

According to Table 2, the statistical analysis revealed a significant gender difference in the risk of developing musculoskeletal disorders. Males exhibited higher mean musculoskeletal disorder risk scores (ESPT) (23.45) and were significantly more likely to fall into the medium and high-risk categories. The mean risk scores for females were 18.77, and for the entire studied nurse population, it was 19.45, both corresponding to a medium risk level. The mean total NSEA score was 45.09 for males, 43.21 for females, and 43.49 for all nurses working at the nurse stations. Furthermore, the distribution across the levels of ergonomic condition assessment was statistically comparable (p = 0.314).

Table 2.

Results of the ergonomic condition assessment of workstations (NSEA) and the ergonomic screening and prioritization tool (ESPT)

Variable	Men (n = 11) Mean (Standard deviation)	Women (n = 65) Mean (Standard deviation)	Total (76) Mean (%)	P-value
ESPT Results				0.023
Low	3(27.3)	30(46.2)	33(43.4)
Moderate	4(36.4)	30(46.2)	34(44.7)
High	4(36.4)	5(7.7)	9(11.8)
ESPT Risk Score	23.45(8.75)	18.77(5.28)	19.45(6.06)	0.017
NSEA Results				0.421
Low	1(9.1)	3(4.6)	4(5.3)
Moderate	8(72.7)	57(87.7)	65(85.5)
High	2(18.2)	5(7.7)	7(9.2)
Total NSEA Score	45.09(6.10)	43.21(5.60)	43.49(5.67)	0.314

Table 3 reveals a clear pattern of negative correlations between the ESPT risk score and most other variables of the NSEA ergonomic condition assessment tool. Notably, a moderate and statistically significant negative correlation was observed between the risk score for musculoskeletal disorders and the overall ergonomic condition score of the workstation (r = -0.434*), indicating that as the ergonomic environment improves, the risk of musculoskeletal disorders decreases. This inverse relationship was particularly pronounced with Layout and Location (r = -0.338*). Other factors such as Workspace, Security-Safety, Environmental Conditions, Counter, Chair, Desk, and Monitor also showed negative (though not statistically significant) correlations, collectively supporting the trend that lower ratings in these areas are associated with higher musculoskeletal risks.

Table 3.

Correlation analysis between musculoskeletal disorder risk scores and ergonomic workstation condition assessment results

Variable	ESPT risk score	Ergonomic	Layout and location	Work space	Security safety	Environmental conditions	Counter	Chair	Desk	Monitor
ESPT Risk Score	1	-0.434*	-0.338*	-0.128	-0.188	-0.285	-0.241	-0.132	-0.182	-0.242
Total NSEA Score		1	0.577*	0.407*	0.616*	0.773*	0.544*	0.515*	-0.184	0.170
Layout and Location			1	0.067	0.566	0.440	0.130	0.410	-0.221	-0.111
Work Space				1	0.286	0.352*	0.022	-0.224	-0.127	-0.278
Security Safety					1	0.360*	-0.040	0.077	-0.186	0.190
Environmental Conditions						1	0.368*	0.419*	0.334*	-0.237
Counter							1	0.264	0.345*	0.007
Chair								1	-0.348*	0.078
Desk									1	0.349*
Monitor										1

* Significance at the 95% confidence interval

The ergonomic assessment demonstrated strong internal consistency, as evidenced by significant positive correlations among its subcomponents. The overall ergonomic score showed highly significant positive correlations with Environmental Conditions (r = 0.773*), Security-Safety (r = 0.616*), Layout and Location (r = 0.577*), Counter (r = 0.544*), Chair (r = 0.515*), and Workspace (r = 0.407*). This pattern confirms the ergonomic score as a coherent composite measure, where improvement in one domain often aligns with improvements in others.

A deeper analysis of the sub-factors highlighted specific associations. Security-Safety had significant correlations with Layout and Location (r = 0.566*) and Environmental Conditions (r = 0.360*). Similarly, Environmental Conditions showed significant correlations with Workspace, Counter, Chair, and Desk. Interestingly, Chair exhibited a significant negative correlation with Desk, while Desk and Monitor showed a significant positive correlation. Figure 6 also displays the correlation matrix between the variables.

Fig. 6.

Heatmap of the correlation matrix between the assessed variables

Table 4 presents the results of the ordinal logistic regression analysis examining the relationship between the risk of musculoskeletal disorders and the ergonomic workstation condition assessment scores, while accounting for potential confounding factors. According to the obtained results, a significant positive association was identified between body weight and the musculoskeletal disorder risk score (β = 0.379, p = 0.007), indicating that individuals with higher weight are more likely to develop musculoskeletal disorders. Similarly, longer working hours showed a strong positive relationship with an increased level of musculoskeletal disorder risk (β = 0.478, p = 0.004), highlighting the contribution of longer workdays to musculoskeletal risks. Conversely, the NSEA ergonomic condition assessment scores showed a significant negative association with the level of musculoskeletal disorder risk (β = -0.461, p = 0.028), indicating that better ergonomic conditions are associated with a reduced risk of musculoskeletal disorders.

Table 4.

Investigation of the association between the risk of musculoskeletal disorders and the ergonomic condition assessment score, while adjusting for confounding factors through ordinal logistic regression

Predictor	β (Logit)	SE	OR = e^β	95% CI (Lower–Upper)	p-value
Age (years)	0.034	0.049	1.035	0.941–1.138	0.483
Sex (Ref: Women)
Men	2.810	0.910	16.60	2.79–98.72	0.002
Marital Status (Ref: Married)
Single	-0.723	0.597	0.485	0.151–1.562	0.220
Height (cm)	-0.003	0.021	0.997	0.958–1.038	0.891
Weight (kg)	0.379	0.029	1.461	1.380–1.546	0.007
Employment Status (Ref: Other)
Permanent	-0.813	0.865	0.443	0.079–2.478	0.347
Contract-based	-0.868	1.170	0.420	0.042–4.198	0.458
Plan-based	-2.371	1.125	0.093	0.010–0.840	0.035
Work Experience (years)	-0.051	0.039	0.950	0.881–1.025	0.190
Daily Working Hours	0.478	0.097	1.613	1.334–1.950	0.004
Total NSEA Score (per 1-unit increase)	-0.461	0.049	0.631	0.573–0.694	0.028

Gender emerged as a significant predictor, with males reporting a higher level of musculoskeletal disorder risk compared to females (β = 2.814, p = 0.002). This gender disparity persisted even after adjusting for other variables. Employment type was also significant, as nurses with plan-based employment showed a lower risk level compared to other employment categories. In contrast, several variables—including age, height, work experience, and marital status—did not show a statistically significant association with the level of musculoskeletal disorder risk in this multivariate model.

In Fig. 7, the effects are presented as a forest plot. Statistically significant variables are shown in blue, while non-significant variables are shown in black, and their confidence intervals cross the zero line.

Fig. 7.

Forest Plot of the Ordinal Logistic Regression

The ordinal logistic regression model satisfied the proportional odds assumption (Brant test: χ² = 12.47, p = 0.412).

Discussion

The overall objective of this study was to ergonomically assess nurse stations using the NSEA tool, as well as assess the level of musculoskeletal disorder risk among nurses using ESPT and investigate the correlation and relationship between these two. The findings of the present research provide important insights into gender differences, the role of occupational and demographic factors, and the critical impact of ergonomic workplace design on nurse health.

According to the results of the ESPT tool, exposure to musculoskeletal disorder risk factors was at a medium level among most of the studied nurses and at a medium to high-risk level among males. These findings are consistent with the results of other studies, including Zare and Zolfaghari [23], Karimian et al. [24], and Afshari et al. [25], which have reported high risk levels in nursing tasks. Indeed, the results of this study align with those of other authors indicating a high frequency of musculoskeletal complaints among hospital nurses [15, 26].

In the ergonomic assessment of nursing workstations using the NSEA tool, the mean ergonomic score obtained was 45.09 for males, 43.21 for females, and 43.49 for the entire studied nurse population. The study by Rokni et al. [27] and Massoud [28] evaluated the ergonomic conditions of nurses’ work environments in terms of indicators such as lighting, ventilation, ambient temperature, equipment quality, and workspace as poor and inadequate. The findings indicate that assessing workplace ergonomic conditions is multidimensional, encompassing environmental physical quality, equipment use, and the application of ergonomic principles in patient handling and work breaks [29].

Given that the NSEA tool evaluates eight key domains—Layout and Location, Workspace, Security-Safety, Environmental Conditions, Counter, Chair, Desk, and Monitor—the obtained results indicated that 43 out of the 64 assessed items met favorable ergonomic conditions, while 21 subdomains exhibited unfavorable conditions. These findings enable precise identification of problems and support the improvement of ergonomics in nurse stations. By focusing on these eight domains, targeted interventions can be designed and implemented for each section to gradually achieve ideal conditions.

To optimize nurse stations, ergonomic interventions should target key domains. In “Environmental Conditions”, adjusting illumination, maintaining permissible noise levels, and stabilizing ambient temperature (23–25 °C) can prevent errors and reduce stress [9, 30]. For “Workspace and Layout”, redesigning to reduce clutter and congestion, alongside implementing strategically placed, adjustable furniture (e.g., height-adjustable desks), is crucial to prevent musculoskeletal disorders and improve movement [9, 31–33]. “Counters, Desks, and Monitors” must adhere to anatomical principles, with equipment heights adjusted to standard to minimize neck and back strain. Finally, in the “Security-Safety” domain, keeping pathways clear and safety equipment accessible is essential for accident prevention. This comprehensive, NSEA-based approach across all domains fosters a safer, more efficient workspace and enhances healthcare delivery.

The total NSEA score showed a highly significant positive correlation with Environmental Conditions (r = 0.773), Security-Safety (r = 0.616), Layout and Location (r = 0.577), Counter (r = 0.544), Chair (r = 0.515), and Workspace (r = 0.407). An interesting finding was the negative correlation between Chair and Desk (r = -0.348), which may indicate that in the assessed stations, the desks and chairs were not designed to be used compatibly. For example, their height or position might not be adjustable, leading to awkward body postures.

Additionally, a statistically significant correlation was observed between the risk score for musculoskeletal disorders and the overall ergonomic condition score of the workstation (r = -0.434), indicating that improvements in the ergonomic environment are associated with a reduced risk of musculoskeletal disorders. This inverse relationship was particularly stronger with Layout and Location, underscoring the importance of spatial organization in mitigating musculoskeletal risks. This result demonstrates that ergonomic investment in workstations directly improves nurse comfort and physical health, potentially reducing musculoskeletal disorders.

According to the study results, employment type, gender, body weight, and daily working hours had a significant relationship with the level of risk for musculoskeletal disorders, while no association was found with other variables. Some epidemiological studies have also shown a link between occupational factors and work-related musculoskeletal disorders (WMSDs). The 2019 study by Ghodusi Borujeni et al. found no significant relationship between marital status, second job, work system, place of residence, and education level with WMSDs [34], which is consistent with the present study.

Although the study population consisted predominantly of females, males had a higher risk score (23.45 vs. 18.77) and were more likely to fall into the high-risk category (36.4% vs. 7.7%). This finding, which remained significant even after adjusting for other factors in the ordinal logistic regression model, could be due to several reasons. First, males may be employed in more physically demanding and stressful departments or tasks. Second, anthropometric differences (greater height and weight in males), although adjusted for in the model, may still interact with workstation designs that are often standardized and not tailored to a wide range of body sizes, making them less suitable for males. This highlights the need for qualitative research to better understand the reasons behind this disparity. Other studies, such as the 2017 study by Ribeiro Master et al. [35] and the 2019 study by Raju et al. [36], reported a higher prevalence of musculoskeletal disorders among females.

The results of the study indicated that long working hours and body weight are also associated factors in the development of musculoskeletal disorders, which aligns with the findings of other authors [19, 29, 37, 38]. In the study by SoltanZadeh et al. in 2022, a higher body mass index had the greatest impact on the prevalence of musculoskeletal disorders [39]. Similarly, the study by Raju et al. in 2019 [36] and Ribeiro Master et al. in 2017 [35] reported an increase in the frequency of musculoskeletal symptoms in each body region with a higher body mass index, which is consistent with the present study. It should be noted that excess weight is associated with a decline in motor function and physical capacity, which may lead to poorer work techniques and, consequently, a higher prevalence of musculoskeletal disorders [29].

On the other hand, musculoskeletal complaints among nurses are influenced by work organization (weekly working hours, daily working hours, and overtime), among other factors [40]. Working fewer than 8 h is considered a protective factor, reflecting the benefits of shorter work shifts in reducing cumulative physical strain [21]. The study by López-Aragón et al. (2017) also demonstrates an inverse relationship between working hours and the prevalence of musculoskeletal disorders [41]. In the study by SoltanZadeh et al. in 2022, weekly working hours had the greatest impact on the prevalence of musculoskeletal disorders [39]. The study by Ghodusi Borujeni et al. in 2019 also showed a positive correlation between knee and wrist pain and weekly working hours [34].

Overall, increased working hours prolong exposure to physical stressors and shorten the body’s recovery and repair time. Additionally, higher body weight can exert greater mechanical load on joints, particularly in the lower back and knees. This effect is more pronounced in physically demanding and standing professions, such as nursing.

According to the results of this study, greater efforts are required to prevent WMSDs among nurses to improve their quality of life in the workplace [42]. It can be said that preventing work-related musculoskeletal disorders necessitates analyzing the clinical environment where nursing care is provided and identifying risk factors, as reducing them requires targeted interventions [43]. This study has several limitations. First, the cross-sectional design precludes the establishment of causal relationships between the ergonomic factors and the reported outcomes. Second, the generalizability of the findings may be limited as the data were collected from a single institution, and the results might not be fully applicable to other healthcare settings with different infrastructures and work cultures. A further critical limitation is the small sample size, particularly the severe gender imbalance with a small subgroup of male nurses (n = 11). This likely affected the statistical power and reliability of the gender-based comparative analyses. The small male subgroup may introduce variance and bias, potentially inflating p-values for gender differences. Potential outliers in small subgroups (e.g., male work experience) may affect precision. Therefore, it is recommended that future longitudinal or interventional studies, with larger sample sizes and balanced recruitment across multiple centers, be conducted to confirm these findings and allow for robust subgroup comparisons.

Overall, the key findings of this research can be summarized along the following axes:

1. Improvements in workstation design—including factors such as layout, workspace, environmental conditions, and furniture—are an effective strategy for reducing the physical burden on nurses and consequently lowering the risk of WMSDs.

2. Despite being a minority, male nurses had significantly higher ergonomic risk scores, even after adjustment, highlighting a need to investigate causes like task allocation or equipment mismatch.

3. Factors such as long working hours, employment type, and higher body weight were identified as independent predictors of increased risk. These results emphasize the importance of managing work hours and promoting a healthy lifestyle alongside improving the physical work environment.

4. The strong correlation between the various subscales of the ergonomic tool (NSEA) indicates that workstation enhancement should be considered in an integrated and comprehensive manner, as improvement in one area (e.g., environmental conditions) is often associated with improvement in others (e.g., safety).

Practical implications

Based on the findings of this study, improving the ergonomic conditions of nursing workstations has been identified as an effective and essential strategy for reducing the risk of work-related musculoskeletal disorders (WMSDs) in this high-risk profession. To achieve this goal, implementing structured interventions at several key levels is recommended:

1. Regular and Systematic Assessment: Conducting periodic assessments using standardized tools such as NSEA is essential to identify high-risk workstations and continuously monitor improvements. These assessments should cover all eight domains, including Layout and Location, Workspace, Security-Safety, Environmental Conditions, Counter, Chair, Desk, and Monitor.

2. Implementation of Targeted Interventions in Workplace Design: Investing in ergonomic equipment, including adjustable chairs and desks, and optimizing workspace layout to reduce clutter and ensure smooth movement pathways are top priorities. Additionally, controlling environmental factors such as lighting, noise levels, and temperature within standard ranges plays a key role in reducing physical and psychological strain.

3. Development of Comprehensive Training Programs: Formulating and implementing ongoing training programs to enhance nurses’ awareness of ergonomic principles and how to adjust workstations to meet individual needs is one of the most fundamental measures. This training should include the correct use of equipment and identification of risk factors.

4. Reevaluation of Work Time Management: Redefining long working hours and incorporating short, effective breaks during shifts is recommended to reduce cumulative fatigue and prevent excessive strain on the musculoskeletal system.

5. Workstation design should accommodate individual differences, including gender-based anatomical variations, weight, and work experience, as these factors influenced risk levels.

Implementing these recommendations will not only enhance the health and well-being of nurses and reduce occupational absenteeism but will also yield organizational and systemic benefits by increasing productivity and service quality. This study emphasizes the importance of an integrated and comprehensive approach to improving the nursing work environment, where enhancements in any one ergonomic domain will consequently strengthen others.

Conclusion

This study investigated the relationship between nurses’ individual-occupational characteristics, the ergonomic conditions of workstations, and the risk of WMSDs. Overall, the study emphasizes that gender, body weight, working hours, and workplace ergonomic conditions play significant roles in the risk of developing WMSDs among nurses. The findings indicate that higher body weight, longer working hours, and employment type are associated with an increased risk of these disorders.

The results of this study highlight the necessity of investing in the optimization of ergonomic conditions in nursing workstations it is recommended that healthcare administrators and policymakers prioritize the continuous assessment and optimization of ergonomic conditions within hospital occupational safety and health programs.

Author contributions

AT and ASS conceptualized the study. Data collection was supervised by AB and MD and analysis was conducted by KO. The manuscript was conceptualized by AT, ASS. All authors contributed to revising the manuscript and approval of the final version. All authors read and approved the final manuscript.

Funding

This study was financially supported by Shahid Beheshti University of Medical Sciences, Iran.

Data availability

Not applicable.

Declarations

Ethics approval and consent to participate

Approval for the study was obtained from the Shahid Beheshti University of Medical Sciences Research Ethics Committee (Ethic No. IR.SBMU.PHNS. REC.1403.189). Each participant entered the research after completing the written consent form to conduct this research. An informed consent form was obtained from all participants. All participants signed the informed consent form and were explained the experimental procedure prior to the study onset. Participants names were then masked using a numerical code after data collection to maintain confidentiality. All experiments were performed in accordance with relevant guidelines and regulations (such as the Declaration of Helsinki). Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.