Work-related Musculoskeletal Disorders (WMSDs) and Quality of Life (QoL) among the construction workers in the United Arab Emirates.

Wajiha Anwar; Fatima Abdul Rashid; Animesh Hazari; Praveen Kumar Kandakurti

doi:10.12688/f1000research.160557.1

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Research Article

Work-related Musculoskeletal Disorders (WMSDs) and Quality of Life (QoL) among the construction workers in the United Arab Emirates.

[version 1; peer review: awaiting peer review]

Wajiha Anwar¹, Fatima Abdul Rashid¹, Animesh Hazari ¹, Praveen Kumar Kandakurti ¹

PUBLISHED 14 Jan 2025

Author details Author details

¹ College of Health Sciences, GULF MEDICAL UNIVERSITY, Ajman, United Arab Emirates

Wajiha Anwar
Roles: Conceptualization, Data Curation, Investigation, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Fatima Abdul Rashid
Roles: Conceptualization, Data Curation, Investigation, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Animesh Hazari
Roles: Conceptualization, Data Curation, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Praveen Kumar Kandakurti
Roles: Conceptualization, Data Curation, Project Administration, Resources, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS AWAITING PEER REVIEW

Abstract

Background

The United Arab Emirates (UAE) construction industry has rapidly expanded, but construction work, by its nature, poses a high risk of work-related musculoskeletal disorders (WMSDs). These disorders significantly impact quality of life (QoL) and productivity and lead to disability and absenteeism.

Aims and Objectives

The study aims to determine the prevalence of WMSDs among UAE construction workers using the Nordic Musculoskeletal Questionnaire (NMQ) and assess their QoL using the Short-Form (SF-36) survey. Additionally, it aims to explore factors associated with WMSDs and QoL among construction workers in the United Arab Emirates.

Methods

This study is a cross-sectional, survey-based design conducted from July 2023 to May 2024 in the United Arab Emirates. The study included male construction workers aged 18-50 with at least 1 year of experience. Participants were recruited using a combination of convenience and purposive sampling methods. The data were collected via paper-based forms using the SF-36 and NMQ questionnaires. The study instruments were chosen after reviewing relevant literature to ensure minimal measurement bias. Statistical methods included descriptive statistics, tests for normality, and Pearson’s correlation test with a significance level of p <0.05.

Results

A total of 346 construction workers were accessed and the study found an 81.8% 12-month WMSD prevalence, most commonly affecting the lower back (44.8%), neck (45.1%), and shoulders (37.9%). Additionally, 70.5% reported pain-related limitations, and 63.6% experienced pain in the past week. SF-36 scores were lowest for role limitations due to physical health (30.33) and emotional problems (33.43), with an overall mean of 52.27 out of 100.

Conclusion

The study found a high prevalence of WMSD in construction workers and moderate quality of life scores. These findings highlight the urgent need to prioritize construction worker health through targeted interventions.

Keywords

Work-related Musculoskeletal Disorders, Quality of life, Construction Workers, United Arab Emirates, Rehabilitation

Corresponding authors: Animesh Hazari, Praveen Kumar Kandakurti

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2025 Anwar W et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Anwar W, Rashid FA, Hazari A and Kandakurti PK. Work-related Musculoskeletal Disorders (WMSDs) and Quality of Life (QoL) among the construction workers in the United Arab Emirates. [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:80 (https://doi.org/10.12688/f1000research.160557.1) First published: 14 Jan 2025, 14:80 (https://doi.org/10.12688/f1000research.160557.1) Latest published: 14 Jan 2025, 14:80 (https://doi.org/10.12688/f1000research.160557.1)

Introduction

In the UAE, the construction sector has grown steadily over the past 20 years and is regarded as the primary driver of economic expansion. Building projects supply the sites infrastructure, which is essential to the development of the economic contributing aspects. It was anticipated that the construction industry in the United Arab Emirates employed around 1.6 million people in 2021.¹ The UAE has several projects and strategies under process that promise great economic gain but require a large labor force for their work completion. Construction of these progressive projects increases the workload and demands more construction workers. Understanding this demand and the contribution of construction workers to the economy, the safety and health of the workers must be maintained for projects to continue.² In the Arabian Gulf region, sweltering and humid weather conditions were noted to be a major concern and in UAE specifically, the hydration and physiological impacts of heat stress on construction workers have concluded that loss of fluids from the human body due to this heat leads to increased heart rate, breathing rate, and core body temperature.^3,4 The impact of such weather conditions can be extended to include a high risk of physical, psychological, and mental distress which all together reduce the QoL.⁵

As per the literature, the primary contributory factor causing productivity loss in construction workers is WMSDs.⁵ WMSDs are conditions in which the work environment contributes significantly to injuries, disorders, or conditions that may worsen or persist longer due to the nature of the work.⁶ While it is appreciated that continuous efforts are made to ensure the safety of its operations, the nature of the job still renders it to be a hazardous occupation, where the prevalence of WMSDs is high, affecting QoL significantly further resulting in productivity loss, permanent disability, and absenteeism.⁶ Additionally, Musculoskeletal disorders (MSDs) impose a negative impact on activities of daily living (ADLs), which slows down economic growth and workers’ QoL.⁷

QoL is a broad concept that forecasts an individual’s degree of freedom, social relationships, physical and mental health, and interaction with important environmental factors. Approximately 80,000 workers in the United Kingdom’s construction sector suffered from a work-related sickness annually, according to health and safety data from 2017. Most work-related disorders (65%) were musculoskeletal issues, with stress, depression, anxiety, and other illnesses (5%), which are critical areas for quality of life, coming in second and third.⁸ Recent research indicates that in Pakistan, Southeastern Ethiopia, India, Iran, and China, the prevalence of WMSDs among construction workers was 59.6%, 43.9%, 80%, 53.3%, and 23.4%, respectively.^9–12 However, there is a lack of evidence on the QoL and WMSD domains among construction workers in the UAE, highlighting the necessity of carrying out the study.

Perceived QoL and WMSDs have been proven to be significant predictors of physical sickness and psychological illnesses in the long term.¹¹ Understanding and improving health status among populations such as construction workers, and investigating WMSDs and QoL among them is a crucial step.¹¹ This would allow us to comprehend the WMSDs and QoL domains that are stronger and weaker for construction workers in the UAE, and as a result, develop or alter our tactics to address the associated health and safety problems. Therefore, the proposed study aims to identify WMSDs among construction workers and their effect on the QoL under the following objectives.

Primary objectives

• To determine the prevalence of WMSDs among UAE construction workers using the NMQ.
• To evaluate the QoL of UAE construction workers using the SF-36 survey.

Secondary objective

• To investigate the Sociodemographic characteristics associated with pain comprising WMSDs among UAE construction workers.

Methods

Study design and setting

A cross-sectional, survey-based study was conducted from July 2023 to May 2024 in the UAE. The study was conducted across various construction sites and companies in 5 Emirates of the UAE (Sharjah, Ajman, Ras Al Khaimah, Dubai, Umm Al Quwain) and the response from 13 major construction companies in these regions.

Sample size and participants

A total of 346 participants were calculated for statistical significance at 95% Confidence Interval (CI) using the following formula:

n = Z 2 P (1 - P) / d 2

where, a prevalence rate (P) of 48% for WMSD was taken from a previous study conducted in Saudi Arabia,¹² Z = 1.96, d = 5.5, and 20% non-respondent rate (n=30).

While, 401 participants were approached among which, 26 participants returned incomplete surveys, 21 participants refused to consent, and 8 participants gave biased responses as they responded without reading.

Inclusion criteria

Male construction workers aged 18 to 50 years with at least 1 year of experience in the industry were eligible for inclusion in the study.¹³ In this study, the term “Construction Workers” refers only to those who work as laborers and cover several responsibilities for completing tasks on a construction site according to blueprints to create structurally sound buildings and other structures. Their duties included erecting scaffolding, unloading construction materials, and operating heavy machinery to pour concrete and demolish buildings, which are highly physically and emotionally demanding.

Sampling method

Participants were selected using a combination of convenience and purposive sampling methods. This combination was chosen to ensure a diverse representation of workers while targeting those who would provide relevant data. We ensured that workers who were not willing to participate or those having pre-existing musculoskeletal, disabilities or underlying conditions that would affect their work nature directly or indirectly were excluded.

Outcome variables, measures, and procedures

One of the researchers collected data via paper-based forms during the onsite visit. To ensure minimal measurement bias, the pre-validated translations of the questionnaire were taken from the literature. The tool was translated into Hindi, Arabic, and Urdu, and validated by language and subject experts.¹⁴ This validation process involved a focused group of two independent translators who translated the original document into the target language, followed by a third linguist who merged the best elements into a unified version for consistency. This reconciled translation was then back-translated into the original language by another independent translator to identify discrepancies. A subject expert reviewed the back-translated content for accuracy and cultural relevance. Finally, we conducted interviews with a sample of construction workers to assess their understanding, leading to further refinements that were needed.^15,16

The study instruments used for this research were the SF-36¹⁷ and NMQ.¹⁸

SF 36 comprises 36 questions that cover eight domains of health. The Nordic Musculoskeletal Questionnaire (NMQ) identifies musculoskeletal pain and activity prevention in 9 body regions. Respondents were asked if they had experienced musculoskeletal pain that had limited regular activity in the last year and the previous seven days. To minimize potential sources of bias, all participants were assessed in their workplace, where they were likely to feel more comfortable and at ease.

Statistical methods

The statistical analysis was performed using the SPSS software package v 29. The descriptive statistics were calculated to summarize the demographic characteristics. Tests for normality were conducted following which correlation between the factors (including age, BMI, smoking status, physical activity, and years of experience) and prevalence of WMSD and SF-36 score was done using Pearson’s correlation test. The level of statistical significance was set at p < 0.05.

Results

The mean age of the participants was 38.62 years (SD = 9.06), with a range of 24 to 54 years. The average Body Mass Index (BMI) was 27.68 (SD = 4.50), ranging from 20 to 40. The mean years of experience in the construction industry was 10.76 years (SD = 5.64), with a range of 2 to 31 years.

Regarding education levels, 26.9% (n = 93) of the workers had an education level higher than or equal to university, 24.9% (n = 86) completed high school, 26.3% (n = 91) completed middle school, and 22.0% (n = 76) had education lower than or equal to elementary school. In terms of smoking status, a majority of 69.6% (n = 241) were smokers, while 30.3% (n = 105) were non-smokers. Physical activity levels among the workers varied: 29.8% (n = 103) reported no physical activity, 28.6% (n = 99) engaged in 2-4 hours of physical activity per week, 22.5% (n = 78) engaged in 5-7 hours per week, and 19.1% (n = 68) engaged in more than 7 hours per week. These sociodemographic characteristics are summarized in Table 1.

Table 1. Sociodemographic characteristics of construction workers (N=346).

Variable	Mean ± SD	Min-Max
Age	38.62 ± 9.06	24-54
BMI	27.68 ± 4.50	20-40
Years of experience	10.76 ± 5.64	2-31

Variable	Frequency (%)
Education
Higher than or equal to the university	93 (26.9)
High school	86 (24.9)
Middle school	91 (26.3)
Lower than or equal to elementary school	76 (22.0)
Smoking Status
Non-smoker	105 (30.3)
Smoker	241 (69.6)
Physical activity
None	103 (29.8)
2-4 h/day	99 (28.6)
5–7 h/day	78 (22.5)
≥7 h/day	68 (19.1)

The prevalence of work-related musculoskeletal disorders (WMSDs) in the past 12 months was notably high, with 81.8% (n = 283) of workers reporting pain. Specific prevalence rates for different body regions were neck pain in 45.1% (n = 156), shoulder pain in 37.9% (n = 131) with 30.6% (n = 106) reporting right shoulder pain, 3.5% (n = 12) left shoulder pain, and 3.8% (n = 13) pain in both shoulders. Elbow pain was reported by 17.6% (n = 61), with 8.4% (n = 29) experiencing right elbow pain and 9.2% (n = 31) pain in both elbows. Wrist/hand pain affected 19.4% (n = 67), with 16.8% (n = 58) reporting right wrist/hand pain, 1.2% (n = 4) left wrist/hand pain, and 1.4% (n = 5) pain in both wrists/hands. Upper back pain was reported at 26.0% (n = 92), and lower back pain by 44.8% (n = 155). Hip/thigh pain was reported at 23.1% (n = 80), with 16.2% (n = 56) reporting right hip/thigh pain. Knee pain was reported by 28.3% (n = 98), with 26.9% (n = 93) experiencing right knee pain and 1.4% (n = 5) left knee pain. Ankle/foot pain was reported at 9.8% (n = 34), all of whom experienced right ankle/foot pain.

The pain-related limitation was reported by 70.5% (n = 244) of the participants. The prevalence of limitation at work due to pain in specific body regions was as follows: neck pain in 33.2% (n = 115), shoulder pain in 22.3% (n = 77), elbow pain in 9.2% (n = 32), wrist/hand pain in 15.9% (n = 55), upper back pain in 15.3% (n = 53), lower back pain in 33.8% (n = 117), hip/thigh pain in 8.7% (n = 30), knee pain in 17.3% (n = 60), and ankle/foot pain in 4.9% (n = 17).

In the past week, 63.6% (n = 220) of the participants reported experiencing pain. The distribution of pain in different body regions was: neck pain in 25.7% (n = 89), shoulder pain in 24.0% (n = 83), elbow pain in 13.9% (n = 48), wrist/hand pain in 10.6% (n = 37), upper back pain in 17.9% (n = 62), lower back pain in 29.2% (n = 101), hip/thigh pain in 6.9% (n = 24), knee pain in 15.6% (n = 54), and ankle/foot pain in 4.9% (n = 17). This data is summarized in Table 2 and illustrated in Figure 1, Figure 2, and Figure 3.

Table 2. Prevalence of WMSD in Construction Workers (N=346).

Variable	12 Months Prevalence	Limitation due to pain	Prevalence of pain in 7 days
Variable	Frequency (%)	Frequency (%)	Frequency (%)
Total Prevalence	283 (81.8)	244 (70.5)	220 (63.6)
Neck	156 (45.1)	115 (33.2)	89 (25.7)
Shoulder	131 (37.9)	77 (22.3)	83 (24.0)
Right	106 (30.6)
Left	12 (3.5)
Both	13 (3.8)
Elbows	61 (17.6)	32 (9.2)	48 (13.9)
Right	29 (8.4)
Left	-
Both	31 (9.2)
Wrist/Hands	67 (19.4)	55 (15.9)	37 (10.6)
Right	58 (16.8)
Left	4 (1.2)
Both	5 (1.4)
Upper Back	92 (26)	53 (15.3)	62 (17.9)
Lower Back	155 (44.8)	117 (33.8)	101 (29.2)
One or Both Hip/Thigh	80 (23.1)	30 (8.7)	24 (6.9)
One or Both Knee	98 (28.3)	60 (17.3)	54 (15.6)
One or Both Ankle/Feet	34 (9.8)	17 (4.9)	17 (4.9)

Figure 1. Prevalence of NMQ.

Figure 2. Limitation due to pain.

Figure 3. 7-day prevalence of NMQ.

The illustration displays 12-month prevalence of musculoskeletal disorders by body area including the neck (150), shoulders (100), and lower back (90). With only 20 instances, the ankles and feet had the lowest prevalence.

The chart shows limitations due to pain by body region. The total limitation were seen for 230 cases, inlcuding the neck (90), shoulder (60), and lower back (70). The lowest limitations are in the elbow (10) and ankle/feet (10) areas.

The chart shows 7-day prevalence of musculoskeletal issues by body region. Total prevalence was present in 220 cases including the neck (70), shoulder (60), and lower back (60). The lowest prevalence was in the ankle/feet (10).

The SF-36 health survey scores were as follows: the mean score for physical functioning was 59.51 (SD = 21.42), role limitations due to physical health was 30.33 (SD = 37.63), role limitations due to emotional problems was 33.43 (SD = 41.47), energy/fatigue was 56.38 (SD = 14.47), emotional well-being was 58.02 (SD = 17.12), social functioning was 62.65 (SD = 19.41), pain was 62.75 (SD = 18.89), and general health was 55.14 (SD = 14.57). The total SF-36 score ranged from 28.56 to 90.65, with a mean of 52.27 (SD = 15.07). These scores are detailed in Table 3.

Table 3. SF-36 health survey scores (n=346).

Variable	Mean ± SD	Min-Max
Physical functioning	59.51 ± 21.42	0-100
Role limitations due to physical health	30.33 ± 37.63	0-100
Role limitations due to emotional problems	33.43 ± 41.47	0-100
Energy/fatigue	56.38 ± 14.47	25-100
Emotional well-being	58.02 ± 17.12	28-100
Social functioning	62.65 ± 19.41	12.5-100
Pain	62.75 ± 18.89	22.5-100
General health	55.14 ± 14.57	29.17-100
SF-36 Total	52.27 ± 15.07	28.56-90.65

Correlation analysis between demographic factors and the prevalence of pain revealed significant associations for several variables as illustrated in Figure 4. Age significantly and strongly correlated with neck pain (r = .792, p = .046) but not with pain in other body regions. BMI was significantly and strongly correlated with low back pain (r = .727, p = .048) and knee pain (r = .781, p = .036) but showed no significant correlations with pain in other regions. Education level did not show significant correlations with pain in any body region, however, there was a significant positive correlation with QoL (r = .818, p= .039). Smoking status and physical activity significantly correlated with neck pain (r = .613, p = .031) and (r = .262, p = .018) respectively. Additionally, physical activity significantly correlated with lower back pain (r = .727, p = .048). Years of experience were significantly correlated with neck pain (r = .294, p = .008). The SF-36 total score was significantly correlated with BMI (r = .188, p = .093). These findings are summarized in Table 4.

Figure 4. Heat Map for correlation between demographic factors and prevalence of pain.

Table 4. Correlation between demographic factors and prevalence of pain.

Variable		Age	BMI	Education	Smoking	PA	YoE
Neck	R	.792	.055	.016	.613	.262	.294
Neck	p	.046*	.624	.887	.031*	.018*	.008*
Shoulder	R	.79	.058	.002	.092	.049	-.030
Shoulder	p	.486	.610	.989	.414	.662	.793
Elbows	R	.078	.026	.092	.081	.137	.071
Elbows	p	.491	.817	.415	.473	.221	.530
Wrist/Hand	R	.139	.060	.167	.147	.073	-.140
Wrist/Hand	p	.214	.059	.136	.189	.519	.213
Upper Back	R	.054	.643	.214	.035	.088	.070
Upper Back	p	.632	.578	.055	.753	.435	.536
Lower Back	R	.083	.727	.107	.135	.044	-.002
Lower Back	p	.464	.048*	.340	.229	.695	.983
One or Both Hip/Thigh	R	.095	.683	.075	.045	.081	.058
One or Both Hip/Thigh	p	.402	.466	.506	.692	.476	.608
One or Both Knee	R	.028	.781	.081	.110	.077	.040
One or Both Knee	p	.804	.036*	.470	.329	.492	.725
One or Both Ankle/Feet	R	.030	.310	.145	.087	.180	-.026
One or Both Ankle/Feet	p	.789	.485	.196	.441	.107	.820
SF-36 Total	R	.183	.069	.818	.031	.101	.185
SF-36 Total	p	.101	.541	.039*	.786	.369	-.098

* Statistically significant.

The important points in this heat map are as follows: age with neck pain (r = .792), BMI with low back pain (r = .727), BMI with knee pain (r = .781), education level with QoL (r = .818), and smoking status with neck pain (r = .613). These values indicate strong associations between the variables, which can be visually represented in a heat map to highlight the strength of these relationships.

Discussions

Prevalence of WMSDs

The study found a high prevalence of WMSDs, with 81.8% of the participants reporting musculoskeletal problems in the past 12 months. This is consistent with the findings of previous studies conducted among construction workers in various countries. A study in Saudi Arabia reported a WMSD pain prevalence of 84 % among construction workers, these results may be due to a similar geographical region, and environmental factors such as the climate.^12,19 A systematic review found that the prevalence of WMSDs among construction workers ranged from 40% to 93%, with the lower back, knees, and shoulders being the most affected body regions.²⁰ The high prevalence of WMSDs in the current study can be attributed to the physically demanding nature of construction work, which involves lifting heavy materials, working in awkward postures, and operating heavy machinery. Another study by Yu-Chi Lee et.al concluded that the prevalence of self-reported symptoms of work-related musculoskeletal diseases (WMSDs) was 57.9% among construction workers in South China. Due to differing samples and data collection techniques, this rate was higher than in Hong Kong (41%) and mainland China (23.4%) but lower than in Korea (87%), Southeastern Ethiopia (43.9%), and India (80%). The most affected areas were the neck (24.7%), shoulders (22.1%), upper back (13.4%), and lower back (12.6%) which is in consensus with our study.²¹ Our study found that the most affected body regions were the neck (45.1%), lower back (44.8%), and shoulders (37.9%). These findings are consistent with the existing literature, which has consistently identified the lower back, shoulders, and neck as the most prevalent sites of musculoskeletal pain among construction workers.^6,20 The shoulder and neck pain may be related to the overhead work, vibrating tools, and the awkward postures adopted by construction workers.²²

Effects on quality of life

The study also explored the effects of WMSDs on the participants’ quality of life. The mean SF-36 total score was 52.27, indicating a relatively moderate overall QoL among the construction workers and better compared to other countries. This is due to the UAE’s higher standard of living and easier access to facilities like food, transport, entertainment, etc. However, the findings from previous studies have reported poorer QoL among construction workers compared to the general population.²³ The lower scores in the physical functioning, role limitations due to physical health, and pain domains of the SF-36 suggest that the WMSDs experienced by the workers significantly impacted their physical well-being and daily activities. A study in Malaysia found that construction workers had significantly lower scores in the physical, psychological, and social domains of the WHOQOL-BREF scale compared to the general population.²⁴ Similar to this, an Indian study found that migrant construction workers’ quality of life (QoL) was lower in the physical, social, and psychological domains but higher in the environmental domain than in earlier studies.²⁵ The poor QoL among construction workers can be attributed to the physically demanding nature of their work, lack of access to healthcare, and poor living conditions, which are common in this population.²⁵

Factors associated with WMSDs and QoL

Age, exercise, job experience, work position, fatigue, and poor ergonomics are factors that could affect WMSDs.^26,27 The prevalence of WMSDs and QoL among construction workers were found to be associated with several of factors. The prevalence of pain in different body parts was shown to be higher in those who were older, smoked, and engaged in less physical activity. These findings align with the existing literature, which has consistently reported that older age, smoking, and physical inactivity are risk factors for the development of WMSDs among construction workers^26–28

Interestingly, the study also found a significant association between higher educational level and better overall QoL, as measured by the SF-36 total score. This suggests that construction workers with higher educational attainment may have better access to resources, knowledge, and coping strategies to manage their health and well-being. This is supported by a study in Malaysia, which found that higher education was associated with better QoL among construction workers.²⁴ While physical activity seemed to lower risk, older workers, those with more work experience, and those who were more fatigued were more susceptible.¹²

Limitations and implications of the study

The large sample size and the inclusion of construction workers from multiple emirates in the UAE also contribute to the robustness of the findings. However, the cross-sectional design of the study limits the ability to establish causal relationships between the variables over time and hence future researcher should consider longitudinal studies to better understand the temporal relationships between risk factors, WMSDs, and QoL among construction workers in the UAE. Additionally, qualitative studies could provide deeper insights into the lived experiences and coping strategies of this population.

The occupational health and well-being of construction workers in the United Arab Emirates may be enhanced by interventions that focus on modifiable risk factors, such as physical exercise and quitting smoking. To enhance monitoring and resource allocation, WMSDs should also be recognized as a significant occupational health issue and added to national occupational disease lists.

A national monitoring system should be set up to monitor WMSDs. Employer documentation and injury data should be included to identify trends and inform policy decisions. Long-term preventative initiatives will also benefit from supporting research and development for novel solutions, such as ergonomic equipment and technologies like biological exoskeletons.

Comprehensive ergonomic training programs that emphasize safe lifting practices and the use of assistive devices should be put in place for employees and supervisors at the workplace level. To lessen physical strain, construction sites should use mechanical aids like hoists and lifts. To detect ergonomic hazards, regular risk assessments should be required. Worker feedback should also be incorporated to guarantee that effective changes are implemented along with regular breaks and exercise can minimize weariness, and a collaborative safety culture will enable employees to report risks and make suggestions for changes. Furthermore, adjusting job assignments to each employee’s capabilities and streamlining site layouts can reduce stress even more and improve workplace safety in general. By placing these suggestions into practice, WMSD incidence could be greatly decreased, and construction workers’ quality of life can improve.

Conclusion

The present study highlights the high prevalence of WMSDs and the associated changes in quality of life among construction workers in the UAE. The findings underscore the need for targeted interventions and policies to address the occupational health challenges faced by this vulnerable population. Specifically, policymakers should implement ergonomic standards, establish a national surveillance system for WMSDs, and promote research on innovative prevention strategies. Additionally, construction companies should adopt comprehensive ergonomic training programs and provide access to mechanical aids to reduce physical strain.

Promoting ergonomic practices, providing access to healthcare services, and implementing educational programs on injury prevention and health management could contribute to improving the overall well-being of construction workers in the UAE. Furthermore, this study calls for further research to explore the long-term effects of WMSDs on quality of life and the effectiveness of specific workplace interventions. The implications of this research extend beyond the UAE, highlighting the need for similar studies in other regions to address the global challenge of WMSDs in the construction industry. Ultimately, improving the health and well-being of construction workers is not only essential for individual workers but also for enhancing productivity and safety in the industry as a whole.

Declarations

Ethics approval and consent to participate

The study was conducted in line with the Declaration of Helsinki for human participants, and received approval from the Institutional Review Board of Gulf Medical University, Thumbay University Hospital (IRB-COHS-STD-84-May-2023) on May 12^th, 2023. Additionally, this study obtained approval from the Ministry of Health and Prevention Research Ethics Committee, United Arab Emirates with Reference No: MOHAP/DXB-REC/J.J.J/No.68/2023.

Consent for participate

A written informed consent was taken from all participants for their voluntary participation in the study prior to data collection explaining the possible use of the data for research and publication without revealing their identity.

Authors’ contributions

WA - Wajiha Anwar - conceptualization, data curation, investigation, methodology, manuscript writing and revision

FR - Fatima Abdul Rashid - conceptualization, data curation, investigation, methodology, manuscript writing and revision

AH - Animesh Hazari - supervision, conceptualization, data curation, methodology, manuscript writing and revision

PK - Praveen Kumar Kandakurti - supervision, conceptualization, data curation, methodology, resources, manuscript writing and revision

Availability of data and materials

Underlying data

Figshare: WRMSDs data, https://doi.org/10.6084/m9.figshare.28106390.v2.²⁹

This project contains the following underlying data:

• [Wajiha Data entry] (Demographics, raw data for analysis).

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Extended data

Figshare: WRMSDs data, https://doi.org/10.6084/m9.figshare.28106390.v2.²⁹

This project contains the following underlying data:

• ENGLISH FORM_mergerd.pdf
• STROBE-WRMDs.docx

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Acknowledgments

We would like to acknowledge the Research Ethics Committee from the Ministry of Health and Prevention, UAE for providing the necessary ethical approval. In addition, we are thankful to Dr. Anjali Rajan and Ms. Sameena Sajid for helping with the validation of the translated tools as well as Muhammed Awais Anwar, Leena Kumar, Nuha Adam, and Athira George for their contribution to data collection.

References

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2. Alhelo AA, Alzubaidi R, Rashid H: A Framework Supporting Health and Safety Practices in the United Arab Emirates’ Construction Projects. Sustain. 2023 Jan 13 [cited 2024 Aug 20]; 15(2): 1587. Publisher Full Text Reference Source
3. Abdussalam Shibani: (PDF) Health and safety influence on the construction project performance in United Arab Emirates (UAE).[cited 2024 Aug 20]. Reference Source
4. Moohialdin A, Trigunarsyah B, Islam MS, et al.: Physiological impacts on construction workers under extremely hot and humid weather. Int. Arch. Occup. Environ. Health. 2022 Mar 1 [cited 2024 Aug 20]; 95(2): 315–29. PubMed Abstract | Publisher Full Text
5. Samanta S, Gochhayat J: Critique on occupational safety and health in construction sector: An Indian perspective. Mater. Today Proc. 2023 Jan 1; 80: 3016–3021. Publisher Full Text
6. Centers for Disease Control and Prevention: Evaluation Measures: Musculoskeletal Disorders. Centers for Disease Control and Prevention; [cited 2024 Aug 20]. Reference Source
7. Prabhu S, Jain D, Desai M: QUALITY OF LIFE IN CONSTRUCTION SITE WORKERS. Indian J. Sci. Res. 2019 Jan 1 [cited 2024 Aug 20]; 9(2): 97–102. Publisher Full Text Reference Source
8. Jones W, Gibb A, Haslam R, et al.: Work-related ill-health in construction: The importance of scope, ownership and understanding. Saf. Sci. 2019 Dec 1; 120: 538–550. Publisher Full Text
9. Kashif M, Albalwi A, Raqib A, et al.: Work-related musculoskeletal disorders among Pakistani construction workers: Prevalence, characteristics, and associated risk factors. Work. 2022 Jan 1; 72(1): 119–126. PubMed Abstract | Publisher Full Text
10. Rahman MS, Sakamoto J: The risk factors for the prevalence of work-related musculoskeletal disorders among construction workers: a review. J. Appl. Res. Ind. Eng. 2024 Jun 1 [cited 2024 Aug 20]; 11(2): 155–165. Reference Source
11. Saleemi MA: Quality of life in construction workers of Lahore, Pakistan. Rawal Med. J. 47(1).
12. Alghadir A, Anwer S: Prevalence of Musculoskeletal Pain in Construction Workers in Saudi Arabia. Sci. World J. 2015 Jan 1 [cited 2024 Aug 20]; 2015(1): 529873. PubMed Abstract | Publisher Full Text | Free Full Text
13. Zabeer S, Inbaraj LR, George CE, et al.: Quality of life among migrant construction workers in Bangalore city: A cross-sectional study. J. Family Med. Prim. Care. 2019 [cited 2024 Aug 20]; 8(2): 437–442. PubMed Abstract | Publisher Full Text
14. Gupta G: Cronicon Reliability and Validity of Hindi Version of Nordic Musculoskeletal Questionnaire.
15. Tsang S, Royse CF, Terkawi AS: Guidelines for developing, translating, and validating a questionnaire in perioperative and pain medicine. Saudi J. Anaesth. 2017 May 1 [cited 2024 Aug 20]; 11(Suppl 1): S80–S89. PubMed Abstract | Publisher Full Text
16. Shalev L, Helfrich CD, Ellen M, et al.: Bridging language barriers in developing valid health policy research tools: insights from the translation and validation process of the SHEMESH questionnaire. Isr. J. Health Policy Res. 2023 Dec 1 [cited 2024 Aug 20]; 12(1): 10–36. PubMed Abstract | Publisher Full Text | Free Full Text
17. Lins L, Carvalho FM: SF-36 total score as a single measure of health-related quality of life: Scoping review. SAGE Open Med. 2016 [cited 2024 Aug 20]; 4. PubMed Abstract | Publisher Full Text | Free Full Text
18. Chairani A(A): VALIDITY AND RELIABILITY TEST OF THE NORDIC MUSCULOSKELETAL QUESTIONNAIRE WITH FORMAL AND INFORMAL SECTOR WORKERS. 7th Int. Conf. Public Heal. 2020. 2020 Nov 19 [cited 2024 Aug 20]; 100–106. Reference Source
19. Shaikh R: Socioeconomic Status, Smoking, Alcohol use, Physical Activity, and Dietary Behavior as Determinants of Obesity and Body Mass Index in the United States: Findings from the National Health Interview Survey. Int. J. MCH AIDS. 2015; 4(1): 22–34. PubMed Abstract | Publisher Full Text | Free Full Text
20. Aghilinejad M, Choobineh AR, Sadeghi Z, et al.: Prevalence of Musculoskeletal Disorders among Iranian Steel Workers. Iran Red Crescent Med. J. 2012 [cited 2024 Aug 20]; 14(4): 198–203. PubMed Abstract
21. Lee YC, Hong X, Man SS: Prevalence and Associated Factors of Work-Related Musculoskeletal Disorders Symptoms among Construction Workers: A Cross-Sectional Study in South China. Int. J. Environ. Res. Public Health. 2023 Mar 6 [cited 2024 Aug 20]; 20(5): 4653. PubMed Abstract | Publisher Full Text | Free Full Text Reference Source
22. Ding X, Guan Z, Liu N, et al.: Prevalence and risk factors of work-related musculoskeletal disorders among emerging manufacturing workers in Beijing, China. Front. Med. 2023 [cited 2024 Aug 20]; 10. PubMed Abstract | Publisher Full Text | Free Full Text
23. Abledu KJ: Multiple Logistic Regression Analysis of Predictors of Musculoskeletal Disorders and Disability among Bank Workers in Kumasi, Ghana. J. Ergon. 2012; 02(04). Publisher Full Text
24. Bin ZH, Rahim AA: Study of Quality Living Environment for Temporary Construction Workers’ Accommodation in Malaysia. Int. J. Environ. Archit. Soc. 2021 Aug 31; 1(02): 64–72. Publisher Full Text
25. Umer W, Antwi-Afari MF, Li H, et al.: The prevalence of musculoskeletal symptoms in the construction industry: a systematic review and meta-analysis. Int. Arch. Occup. Environ. Health. 2018 Feb 1; 91(2): 125–144. PubMed Abstract | Publisher Full Text
26. Tao Y, Hu H, Xue J, et al.: Evaluation of Ergonomic Risks for Construction Workers Based on Multicriteria Decision Framework with the Integration of Spherical Fuzzy Set and Alternative Queuing Method. Sustainability. 2024 May 8; 16(10): 3950. Publisher Full Text Reference Source
27. Kim IJ: An ergonomic focus evaluation of work-related musculoskeletal disorders amongst operators in the UAE network control centres. Heliyon. 2023 Oct 1 [cited 2024 Aug 20]; 9(10): e21140. PubMed Abstract | Publisher Full Text | Free Full Text
28. Viester L, Verhagen EA, Hengel KMO, et al.: The relation between body mass index and musculoskeletal symptoms in the working population. BMC Musculoskelet. Disord. 2013 Aug 12 [cited 2024 Aug 20]; 14(1): 1–9. PubMed Abstract | Publisher Full Text | Free Full Text
29. Animesh H: WRMSDs data. Dataset. figshare. 2024. Publisher Full Text

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Author details Author details

¹ College of Health Sciences, GULF MEDICAL UNIVERSITY, Ajman, United Arab Emirates

Wajiha Anwar
Roles: Conceptualization, Data Curation, Investigation, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Fatima Abdul Rashid
Roles: Conceptualization, Data Curation, Investigation, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Animesh Hazari
Roles: Conceptualization, Data Curation, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Praveen Kumar Kandakurti
Roles: Conceptualization, Data Curation, Project Administration, Resources, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

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Anwar W, Rashid FA, Hazari A and Kandakurti PK. Work-related Musculoskeletal Disorders (WMSDs) and Quality of Life (QoL) among the construction workers in the United Arab Emirates. [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:80 (https://doi.org/10.12688/f1000research.160557.1)

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[1] 1. UAE: Number of construction workers by sector. Statista; [cited 2024 Aug 20]. Reference Source

[2] 2. Alhelo AA, Alzubaidi R, Rashid H: A Framework Supporting Health and Safety Practices in the United Arab Emirates’ Construction Projects. Sustain. 2023 Jan 13 [cited 2024 Aug 20]; 15(2): 1587. Publisher Full Text Reference Source

[3] 3. Abdussalam Shibani: (PDF) Health and safety influence on the construction project performance in United Arab Emirates (UAE).[cited 2024 Aug 20]. Reference Source

[4] 4. Moohialdin A, Trigunarsyah B, Islam MS, et al.: Physiological impacts on construction workers under extremely hot and humid weather. Int. Arch. Occup. Environ. Health. 2022 Mar 1 [cited 2024 Aug 20]; 95(2): 315–29. PubMed Abstract | Publisher Full Text

[5] 5. Samanta S, Gochhayat J: Critique on occupational safety and health in construction sector: An Indian perspective. Mater. Today Proc. 2023 Jan 1; 80: 3016–3021. Publisher Full Text

[6] 6. Centers for Disease Control and Prevention: Evaluation Measures: Musculoskeletal Disorders. Centers for Disease Control and Prevention; [cited 2024 Aug 20]. Reference Source

[7] 7. Prabhu S, Jain D, Desai M: QUALITY OF LIFE IN CONSTRUCTION SITE WORKERS. Indian J. Sci. Res. 2019 Jan 1 [cited 2024 Aug 20]; 9(2): 97–102. Publisher Full Text Reference Source

[8] 8. Jones W, Gibb A, Haslam R, et al.: Work-related ill-health in construction: The importance of scope, ownership and understanding. Saf. Sci. 2019 Dec 1; 120: 538–550. Publisher Full Text

[9] 9. Kashif M, Albalwi A, Raqib A, et al.: Work-related musculoskeletal disorders among Pakistani construction workers: Prevalence, characteristics, and associated risk factors. Work. 2022 Jan 1; 72(1): 119–126. PubMed Abstract | Publisher Full Text

[10] 10. Rahman MS, Sakamoto J: The risk factors for the prevalence of work-related musculoskeletal disorders among construction workers: a review. J. Appl. Res. Ind. Eng. 2024 Jun 1 [cited 2024 Aug 20]; 11(2): 155–165. Reference Source

[11] 11. Saleemi MA: Quality of life in construction workers of Lahore, Pakistan. Rawal Med. J. 47(1).

[12] 12. Alghadir A, Anwer S: Prevalence of Musculoskeletal Pain in Construction Workers in Saudi Arabia. Sci. World J. 2015 Jan 1 [cited 2024 Aug 20]; 2015(1): 529873. PubMed Abstract | Publisher Full Text | Free Full Text

[13] 13. Zabeer S, Inbaraj LR, George CE, et al.: Quality of life among migrant construction workers in Bangalore city: A cross-sectional study. J. Family Med. Prim. Care. 2019 [cited 2024 Aug 20]; 8(2): 437–442. PubMed Abstract | Publisher Full Text

[14] 14. Gupta G: Cronicon Reliability and Validity of Hindi Version of Nordic Musculoskeletal Questionnaire.

[15] 15. Tsang S, Royse CF, Terkawi AS: Guidelines for developing, translating, and validating a questionnaire in perioperative and pain medicine. Saudi J. Anaesth. 2017 May 1 [cited 2024 Aug 20]; 11(Suppl 1): S80–S89. PubMed Abstract | Publisher Full Text

[16] 16. Shalev L, Helfrich CD, Ellen M, et al.: Bridging language barriers in developing valid health policy research tools: insights from the translation and validation process of the SHEMESH questionnaire. Isr. J. Health Policy Res. 2023 Dec 1 [cited 2024 Aug 20]; 12(1): 10–36. PubMed Abstract | Publisher Full Text | Free Full Text

[17] 17. Lins L, Carvalho FM: SF-36 total score as a single measure of health-related quality of life: Scoping review. SAGE Open Med. 2016 [cited 2024 Aug 20]; 4. PubMed Abstract | Publisher Full Text | Free Full Text

[18] 18. Chairani A(A): VALIDITY AND RELIABILITY TEST OF THE NORDIC MUSCULOSKELETAL QUESTIONNAIRE WITH FORMAL AND INFORMAL SECTOR WORKERS. 7th Int. Conf. Public Heal. 2020. 2020 Nov 19 [cited 2024 Aug 20]; 100–106. Reference Source

[19] 19. Shaikh R: Socioeconomic Status, Smoking, Alcohol use, Physical Activity, and Dietary Behavior as Determinants of Obesity and Body Mass Index in the United States: Findings from the National Health Interview Survey. Int. J. MCH AIDS. 2015; 4(1): 22–34. PubMed Abstract | Publisher Full Text | Free Full Text

[20] 20. Aghilinejad M, Choobineh AR, Sadeghi Z, et al.: Prevalence of Musculoskeletal Disorders among Iranian Steel Workers. Iran Red Crescent Med. J. 2012 [cited 2024 Aug 20]; 14(4): 198–203. PubMed Abstract

[21] 21. Lee YC, Hong X, Man SS: Prevalence and Associated Factors of Work-Related Musculoskeletal Disorders Symptoms among Construction Workers: A Cross-Sectional Study in South China. Int. J. Environ. Res. Public Health. 2023 Mar 6 [cited 2024 Aug 20]; 20(5): 4653. PubMed Abstract | Publisher Full Text | Free Full Text Reference Source

[22] 22. Ding X, Guan Z, Liu N, et al.: Prevalence and risk factors of work-related musculoskeletal disorders among emerging manufacturing workers in Beijing, China. Front. Med. 2023 [cited 2024 Aug 20]; 10. PubMed Abstract | Publisher Full Text | Free Full Text

[23] 23. Abledu KJ: Multiple Logistic Regression Analysis of Predictors of Musculoskeletal Disorders and Disability among Bank Workers in Kumasi, Ghana. J. Ergon. 2012; 02(04). Publisher Full Text

[24] 24. Bin ZH, Rahim AA: Study of Quality Living Environment for Temporary Construction Workers’ Accommodation in Malaysia. Int. J. Environ. Archit. Soc. 2021 Aug 31; 1(02): 64–72. Publisher Full Text

[25] 25. Umer W, Antwi-Afari MF, Li H, et al.: The prevalence of musculoskeletal symptoms in the construction industry: a systematic review and meta-analysis. Int. Arch. Occup. Environ. Health. 2018 Feb 1; 91(2): 125–144. PubMed Abstract | Publisher Full Text

[26] 26. Tao Y, Hu H, Xue J, et al.: Evaluation of Ergonomic Risks for Construction Workers Based on Multicriteria Decision Framework with the Integration of Spherical Fuzzy Set and Alternative Queuing Method. Sustainability. 2024 May 8; 16(10): 3950. Publisher Full Text Reference Source

[27] 27. Kim IJ: An ergonomic focus evaluation of work-related musculoskeletal disorders amongst operators in the UAE network control centres. Heliyon. 2023 Oct 1 [cited 2024 Aug 20]; 9(10): e21140. PubMed Abstract | Publisher Full Text | Free Full Text

[28] 28. Viester L, Verhagen EA, Hengel KMO, et al.: The relation between body mass index and musculoskeletal symptoms in the working population. BMC Musculoskelet. Disord. 2013 Aug 12 [cited 2024 Aug 20]; 14(1): 1–9. PubMed Abstract | Publisher Full Text | Free Full Text

[29] 29. Animesh H: WRMSDs data. Dataset. figshare. 2024. Publisher Full Text

Work-related Musculoskeletal Disorders (WMSDs) and Quality of Life (QoL) among the construction workers in the United Arab Emirates.

Abstract

Background

Aims and Objectives

Methods

Results

Conclusion

Keywords

Introduction

Primary objectives

Secondary objective

Methods

Study design and setting

Sample size and participants

Inclusion criteria

Sampling method

Outcome variables, measures, and procedures

Statistical methods

Results

Table 1. Sociodemographic characteristics of construction workers (N=346).

Table 2. Prevalence of WMSD in Construction Workers (N=346).

Figure 1. Prevalence of NMQ.

Figure 2. Limitation due to pain.

Figure 3. 7-day prevalence of NMQ.

Table 3. SF-36 health survey scores (n=346).

Figure 4. Heat Map for correlation between demographic factors and prevalence of pain.

Table 4. Correlation between demographic factors and prevalence of pain.

Discussions

Prevalence of WMSDs

Effects on quality of life

Factors associated with WMSDs and QoL

Limitations and implications of the study

Conclusion

Declarations

Ethics approval and consent to participate

Consent for participate

Authors’ contributions

Availability of data and materials

Underlying data

Extended data

Acknowledgments

References

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