Abstract
Background
The job of truck driving exposes the drivers to various risk factors of musculoskeletal disorders (MSDs) due to unfavorable working conditions. Hence, this research was conducted to investigate the frequency of MSDs among individuals working as truck drivers.
Materials and methods
The present research followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, and its protocol was registered in international prospective register of systematic review (PROSPERO) under the code CRD42024507985. Databases such as PubMed, Scopus, Web of Science, Science Direct, SID, ISC, and Google Scholar were searched without time restrictions until February 7th, 2024 to identify relevant articles. Meta-analysis was conducted using a random effects model, and heterogeneity between studies was evaluated using the I2 index. Additionally, STATA (version 14) was utilized for conducting data analysis.
Results
In the initial search, 678 articles were identified. After removing duplicates and articles unrelated to the research objective and inclusion criteria, 15 articles were included in the meta-analysis, involving 2,662 truck drivers. The findings from the research show that 61.75% of truck drivers have musculoskeletal disorders (MSDs) (95% CI: 46.98–76.52, I2 = 96%, P < 0.001). Additionally, the prevalence of MSDs in various parts of the body was estimated as follows: shoulder (31.5%), neck (25.79%), lower back (23.46%), knee (22.26%), ankle (20.46%), wrist (20.25%), upper back (18.65%), elbow (11.91%), and hip (7.50%).
Conclusion
According to the study findings, the prevalence of MSDs among truck drivers is relatively high, and several risk factors contribute to these disorders. Therefore, to decrease the prevalence of MSDs among truck drivers, it is recommended to develop and implement essential training programs, ergonomic interventions, and regular evaluations of the work environment.
Keywords: Musculoskeletal disorders, Truck drivers, Risk factors, Prevention, Ergonomics
Introduction
Work-related musculoskeletal disorders (WMSDs) refer to skeletal-muscular disorders (affecting bones, muscles, nerves, tendons, and other soft tissues) that are mainly triggered or exacerbated by the job or the working conditions. These disorders significantly impact job-related issues in many working populations by increasing compensation and health costs, reducing productivity, and diminishing quality of life [1].
Transport is considered one of the largest industries globally [2]. Professional drivers of heavy vehicles, buses, taxis, and other vehicles rely on these vehicles for their livelihoods [3]. Heavy vehicles, such as trucks, cranes, forklifts, and tractors, are designed for specialized and heavy tasks like transportation, agriculture, and construction activities. The nature of the truck drivers’ job exposes them to numerous WMSDs risk factors due to adverse working conditions [4]. Among these risk factors are long-term static postures [5], awkward postures (such as turning the neck and trunk forward and sideways), whole-body vibration, intense shaking, manual handling of loads such as pulling, lifting, and carrying, as well as psychological factors (e.g., lack of job satisfaction) [4]. Additionally, truck drivers are exposed to stressful work conditions, extended periods of driving, irregular sleep schedules, and persistent tiredness, and more [6]. Studies have shown that individual factors, including gender, age, and body mass index (BMI) [7, 8], can also exacerbate the risk of WMSDs among drivers [9].
The review of studies indicates that the health of professional drivers has received significant attention in recent decades, leading to numerous studies on the prevalence of WMSDs among them. In a review study involving professional drivers, back pain was identified as the most common symptom of MSDs in this population, particularly among truck, bus, and taxi drivers. Additionally, factors such as prolonged sitting, work history, vehicle vibration, and car ergonomics were reported as risk factors for MSDs [10]. The findings of Pradeepkumar et al.‘s study revealed that approximately 55.8% of bus drivers have experienced WMSDs [11]. Some researchers indicated that prolonged sitting and exposure to whole-body vibration while driving are tightly linked to the prevalence of MSDs among professional drivers [12]. Another study reported that MSDs are among the most significant occupational health issues for truck drivers worldwide, leading to symptoms such as discomfort and pain, affecting various regions of the body, including the neck, upper limbs, upper and lower back, and legs [7].
Considering the significance of MSDs among various occupational groups, it appears essential to conduct epidemiological studies on the prevalence of MSDs among different occupational populations. Moreover, according to researchers and analysts, truck driving is ranked as one of the most hazardous jobs in the world [13]. Although extensive studies have examined the prevalence of MSDs among truck drivers, there has not yet been a comprehensive study on the overall prevalence of MSDs and their various types among truck drivers according to our current knowledge. Reviews indicate that various studies have been conducted with different sample sizes in different countries. However, a meta-analysis study that combines data from different sources can enhance the accuracy of the results. In fact, the results of a meta-analysis examining the overall prevalence and types of MSDs among truck drivers could help public health policymakers make more informed decisions regarding resource allocation and planning for the prevention and treatment of these disorders. Therefore, this study was designed with the review question, “What is the prevalence of musculoskeletal disorders among truck drivers?” It was conducted using a systematic review and meta-analysis approach. The objectives of the current study are outlined below:
To investigate MSDs among truck drivers.
To determine the prevalence of low back pain among truck drivers.
To determine the prevalence of neck pain among truck drivers.
To determine the prevalence of pain in the back among truck drivers.
To determine the prevalence of pain in the upper limbs among truck drivers.
To determine the prevalence of pain in the lower limbs among truck drivers.
The results of this systematic review and meta-analysis are likely to not only provide an important information resource on MSDs among truck drivers, but also enhance the knowledge of occupational health managers in planning training and implementing ergonomic interventions. Consequently, this study could help prevent MSDs among truck drivers.
Materials and methods
In this study, a systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [14]. The present study protocol was registered with the code CRD42024507985 in the International Prospective Register of Systematic Reviews (PROSPERO). Various stages of the study, including the search strategy, screening, study selection, quality assessment, and data extraction, were carried out in accordance with the PRISMA protocol. Two researchers carried out the three stages of study selection, qualitative assessment, and data extraction independently, and any disagreements between them were resolved through group discussion.
Information sources and search strategy
In the present study, information sources, such as PubMed, Scopus, Web of Science, Science Direct, SID, ISC, Google Scholar, conference and congress articles, as well as the reference lists of selected articles and systematic review studies, were utilized for searching and extracting relevant studies. To acquire appropriate keywords, Medical Subject Heading (MeSH) terms, keywords from related articles, and consultation with scientific experts were considered. Valid keywords were utilized to create search strategies across different databases, and keywords were combined using both operators and search fields. The keywords are as follows:
Truck driving*”, “Truck drivers*”, “Professional drivers*”, “Professional truck drivers*”, “Musculoskeletal symptom*”, “Musculoskeletal disease*”, “Musculoskeletal disorder*”, “Musculoskeletal pain*”, “Musculoskeletal complaint*”, “Work related Musculoskeletal disorder*”, “MSDs”, “WRMSDs”, “Muscle strain*”, “Musculoskeletal problem*”, “Muscle problem*”, “Elbow pain*”, “Neck pain*”, “Arthritis joint*”, “Arthritis bone*”, “Shoulder pain*”, “Dysfunction*”, “Back pain*”, “Hand pain*.
The period considered for the searches was until February 7th, 2024 and no time limit was imposed. Table 1 displays the search strategy across various databases.
Table 1.
Search strategy in different types of databases
| Database | Search strategy | Results |
|---|---|---|
| PubMed | ((“Truck driving*” OR “Truck drivers*” OR “Professional drivers*” OR “Professional truck drivers*”) AND (“Musculoskeletal symptom*” OR “Musculoskeletal disease*” OR “Musculoskeletal disorder*” OR “Musculoskeletal pain*” OR “Musculoskeletal complaint*” OR “Work related Musculoskeletal disorder*” OR “MSDs” OR “WRMSDs” OR “Muscle strain*” OR “Musculoskeletal problem*” OR “Muscle problem*” OR “Elbow pain*” OR “Neck pain*” OR “Arthritis joint*” OR “Arthritis bone*” OR “Shoulder pain*” OR “Dysfunction*” OR “Back pain*” OR “Hand pain*”)) | 131 |
| Scopus | (((TITLE-ABS-KEY(“Truck driving *”) OR TITLE-ABS-KEY(“Truck drivers *”) OR TITLE-ABS-KEY(“Professional drivers *”) OR TITLE-ABS-KEY(“Professional truck drivers *”)) AND (ALL(“Musculoskeletal symptom*”) OR ALL(“Musculoskeletal disease*”) OR ALL(“Musculoskeletal disorder*”) OR ALL(“Musculoskeletal pain*”) OR ALL(“Musculoskeletal complaint*”) OR ALL(“Work related Musculoskeletal disorder*”) OR ALL(“MSDs”) OR ALL(“WRMSDs”) OR ALL(“Muscle strain*”) OR ALL(“Musculoskeletal problem *”) OR ALL(“Muscle problem*”) OR ALL(“Elbow pain*”) OR ALL(“Neck pain*”) OR ALL(“Arthritis joint*”) OR ALL(“Arthritis bone *”) OR ALL(“Shoulder pain*”) OR ALL(“Dysfunction*”) OR ALL(“Back pain*”) OR ALL(“Hand pain*”)))) | 496 |
| Web Of Science (WOS) | (((TS=(“Truck driving*”) OR TS=(“Truck drivers*”) OR TS=(“Professional drivers*”) OR TS=(“ Professional truck drivers*”)) AND ( TS=(“Musculoskeletal symptom*”) OR TS=(“Musculoskeletal disease*”) OR TS=(“Musculoskeletal disorder*”) OR TS=(“Musculoskeletal pain*”) OR TS=(“Musculoskeletal complaint*”) OR TS=(“Work related Musculoskeletal disorder*”) OR TS=(“MSDs”) OR TS=(“WRMSDs”) OR TS=(“Muscle strain*”) OR TS=(“Musculoskeletal problem*”) OR TS=(“Muscle problem*”) OR TS=(“Elbow pain*”) OR TS=(“Neck pain*”) OR TS=(“Arthritis joint*”) OR TS=(“Arthritis bone*”) OR TS=(“Shoulder pain*”) OR TS=(“Dysfunction*”) OR TS=(“Back pain*”) OR TS=(“Hand pain*”)))) | 203 |
| 830 |
Inclusion criteria
The criteria for inclusion were determined using the PECO (Population, Exposure, Comparison, Outcome) framework, which stands for population (truck drivers), exposure (driving a vehicle), comparison (Any), and outcome (MSDs). As a result, in the present study, all studies that reported the prevalence of MSDs among truck drivers were included.
Exclusion criteria
Items such as case reports, non-English papers, interventional and review researches, reports on the prevalence of MSDs caused by accidents, and letters to the editor were excluded from the research.
It should be noted that in present study, MSDs refer to disorders related to muscles, nerves, tendons, ligaments, joints, cartilage, and intervertebral discs that occur over time due to factors such as poor posture, repetitive movements, and other similar causes. Musculoskeletal injuries resulting from slips, falls, accidents involving motor vehicles, or similar incidents were not examined in this study, and studies reporting such injuries were excluded. In this way, only studies that utilized MSD assessment tools were considered. Therefore, studies that assessed these disorders through Nordic questionnaires, Cornell questionnaires, or self-administered questionnaires were included in the present review study.
Selection of studies
After conducting the search, all articles were imported into EndNote X7 software to manage the search results. Following the removal of duplicates, the titles and abstracts of the articles were screened based on the eligibility criteria, and potentially relevant articles were initially identified. In the subsequent step, two researchers independently conducted a detailed review of the full text of the primary potentially relevant articles. Next, the studies meeting the inclusion criteria were selected.
Qualitative assessment and data extraction
In this phase of the study, two researchers (ST and FM) independently assessed the quality of the selected studies, and any disagreement between them was resolved by including a third person (ZZ). For this purpose, the Appraisal tool for Cross-Sectional Studies (AXIS) [15], which provides a score ranging from 0 to 20, was utilized. Subsequently, articles with a score of 12 and above were considered for meta-analysis. In terms of data extraction, the two researchers (ST and FM) independently extracted certain characteristics of each study, including the name of the first author, the average age of the studied population, the size of the study sample, data collection tools, the number of men and women (if applicable), and the prevalence of MSDs (both overall and body-region-specific prevalence). These extracted features were then recorded in a pre-designed checklist. Any disputes between the two researchers were resolved with the involvement of a third party (ZZ).
Statistical analysis
To combine the prevalence of MSDs from different studies, a weighted average was utilized, and the variance of each study was calculated using the binomial distribution. The inverse variance of each study was taken into account for weighting in the analysis. Meta-analysis was conducted using a random effects model. The degree of heterogeneity between studies was assessed using the I2 index, which categorizes heterogeneity into four ranges: less than 25% (no heterogeneity), 25–50% (moderate heterogeneity), 50–75% (high heterogeneity), and above 75% (very high heterogeneity) [16]. Subsequently, publication bias was evaluated using Begg’s test. The data from the present study were then analyzed via STATA (version 14).
Results
Systematic review results
Based on the initial search in information sources, 678 articles were found among which 563 articles were reviewed after eliminating duplicates. Then, 46 studies identified during the screening process were chosen for a more comprehensive examination of the full text. After reviewing the full text of the articles, 15 studies were chosen and qualitatively evaluated. Subsequently, the chosen studies, as depicted in Fig. 1, proceeded to the meta-analysis step. In this research, the prevalence of MSDs was examined among a total of 2,662 truck drivers. Moreover, 7 studies out of 15 focused on the overall prevalence of MSDs with a sample size of 904 truck drivers. Table 2 shows the characteristics of selected studies.
Fig. 1.
Flowchart of the study extraction process based on PRISMA
Table 2.
Characteristics of studies selected for meta-analysis
| First author/Year | Country | Sample size | Total prevalence of MSDs | Prevalence of MSDs | Tools * | Quality assessment score |
|---|---|---|---|---|---|---|
| Sa-ngiamsak (2022) [19] | Thailand | 25 | 88% | Lower back: 72% | NMQ | 14 |
| Shoulder:20% | ||||||
| Elbows: 8% | ||||||
| Wrist/hand: 12% | ||||||
| Hips/thighs: 24% | ||||||
| Ankles/feet: 24% | ||||||
| Upper back:16% | ||||||
| Neck: 32% | ||||||
| Knees: 28% | ||||||
| Aliabadi (2022) [5] | Iran | 65 | NR | Neck: 22.78% | CMDQ | 15 |
| Lower back: 17.32% | ||||||
| Right knee: 12.64% | ||||||
| Left knee: 10.87% | ||||||
| Upper arms: 0.15% | ||||||
| Lower arms: 0.17% | ||||||
| Right thigh: 0.57% | ||||||
| Kumar (2021) [20] | India | 161 | 42% | Neck: 24% | Self-administered questionnaire | 15 |
| Shoulder: 25.25% | ||||||
| Arms: 18.75% | ||||||
| Legs: 24.5% | ||||||
| Upper back: 28% | ||||||
| Lower back: 45.25% | ||||||
| Sekkay (2021) [21] | Canada | 123 | 43.1% | Neck: 14.6% | NMQ | 17 |
| Shoulders: 20.3% | ||||||
| Upper back: 6.5% | ||||||
| Arms: 8.1% | ||||||
| Elbows: 5.7% | ||||||
| Lower back: 21.1% | ||||||
| Forearm, wrist/hand: 12.2% | ||||||
| Hips/thighs: 8.9% | ||||||
| Knees: 7.3% | ||||||
| Legs, calves: 3.3% | ||||||
| Ankles/feet: 5.7% | ||||||
| Yosef (2019) [6] | Ethiopia | 442 | NR | Lower back: 65% | NMQ | 20 |
| Gumasing (2018) [22] | Philippines | 300 | NR | Upper back: 21.55% | CMDQ | 17 |
| Shoulder (right): 14.37% | ||||||
| Lower back: 12.52% | ||||||
| Upper arm (right): 10.20% | ||||||
| Neck: 9.38% | ||||||
| Hip/buttocks: 6.64% | ||||||
| Lower leg (right): 2.96% | ||||||
| Thigh (left): 2.70% | ||||||
| Shoulder (left): 2.67% | ||||||
| Lower leg (left): 2.61% | ||||||
| Forearm (right): 2.45% | ||||||
| Knee (left): 2.42% | ||||||
| Thigh (right): 2.16% | ||||||
| Upper arm (left): 2.10% | ||||||
| Wrist (right): 1.97% | ||||||
| Knee (right): 1.72% | ||||||
| Wrist (left): 1.02% | ||||||
| Forearm (left): 0.57% | ||||||
| Sekkay (2018) [23] | Canada | 123 | 43.1% | Neck: 14.6% | NMQ | 18 |
| Shoulders: 20.3% | ||||||
| Upper back: 6.5% | ||||||
| Arms: 8.1% | ||||||
| Elbows: 5.7% | ||||||
| Lower back: 21.1% | ||||||
| Forearm, wrist/hand: 12.2% | ||||||
| Hips/thighs: 8.9% | ||||||
| Knees: 7.3% | ||||||
| Legs, calves: 3.3% | ||||||
| Senthanar (2018) [9] | Canada | 107 | 57% | Shoulder: 54% | NMQ | 17 |
| Wrists/hand: 44% | ||||||
| Upper back: 39% | ||||||
| Lower back: 80% | ||||||
| Legs/feet: 41% | ||||||
| Kim (2016) [24] | USA | 69 | NR | Neck: 50.7% | NMQ | 17 |
| Shoulder: 55.1% | ||||||
| Wrist/forearm: 36.2% | ||||||
| Low back: 72.5% | ||||||
| Knee: 42% | ||||||
| Ankle/feet:31.9% | ||||||
| Leg/sciatica: 26.1% | ||||||
| Abolfazl Mozafari (2014) [25] | Iran | 173 | 78.6% | Lumbar: 24.3% | NMQ | 18 |
| One or both hip: 5.8% | ||||||
| Neck: 27.2% | ||||||
| Shoulder: 14.5% | ||||||
| Elbow: 5.2% | ||||||
| Wrist/hand: 8.1% | ||||||
| One or both knee: 19.1% | ||||||
| One or both ankle: 4% | ||||||
| Upper back: 15.6% | ||||||
| Bovenzi (2010) [13] | Italy | 202 | NR | Lower back: 38.6% | NMQ | 17 |
| Robb (2007) [26] | UK | 192 | 81% | Lower back: 60% | NMQ | 19 |
| Shoulder: 39% | ||||||
| Knee: 35% | ||||||
| Neck: 34% | ||||||
| Andrusaitis (2006) [27] | Brazil | 410 | NR | Lower back: 59% | Self-administered questionnaire | 17 |
| Miyamoto (2000) [28] | Japan | 153 | NR | Lower back: 50.3% | Self-administered questionnaire | 16 |
| Magnusson (1996) [8] | Sweden | 117 | NR | Shoulder: 37% | NMQ | 18 |
| Neck: 36% | ||||||
| Lower back: 56% |
*NMQ: Nordic Musculoskeletal Questionnaire, CMDQ: Cornell Musculoskeletal Discomfort Questionnaire
NR: Not Reported
All the initial studies were cross-sectional. It is worth noting that the tool used to assess MSDs in most of the early studies was the Nordic questionnaire, which has acceptable validity in the field of MSDs assessment [17]. Two studies also utilized the Cornell questionnaire, which has also been validated [18]. However, some studies employed various Self-administered questionnaires. Due to the diversity of tools, subgroup analysis was not possible. Nonetheless, the prevalence of MSDs reported in all studies was estimated through self-reporting, which could be considered a limitation of the study.
Meta-analysis results
The meta-analysis findings showed that the prevalence of MSDs among truck drivers (defined as experiencing pain in at least one region of the body) is 61.75% (95% CI: 46.98–76.52, I2 = 96%, P < 0.001). According to the I2 index, there is very high heterogeneity among the reviewed studies (Fig. 2). The overall I² results indicate that there is a very high level of heterogeneity among the studies reporting the overall prevalence of MSDs. Additionally, as shown in Fig. 3, the publication bias in the prevalence of overall MSDs among truck drivers is deemed insignificant based on the results of Begg’s test (P = 0.764) and Egger’s test (P = 0.345).
Fig. 2.
The overall prevalence of MSDs among truck drivers and the 95% confidence interval for each of the reviewed studies and all studies
Fig. 3.
Publication bias based on Begg’s test for overall prevalence of MSDs among truck drivers
Based on the results of the subgroup analysis, which assesses the prevalence of MSDs across different body regions in Table 3, the highest and lowest prevalence rates are observed in the shoulder at 31.5% (95% CI: 22.25–40.75, I2 = 92%, P < 0.001) and the hip at 7.50% (95% CI: 5.15–9.86, I2 = 27.5%, P = 0.238), respectively. The results in Table 3 also indicate that the values of I2 are notably high for the ankle, knee, upper back, shoulder, wrist, and neck regions. Furthermore, based on Begg’s test, the publication bias in the prevalence of MSDs among truck drivers was significant only for the neck and elbow regions. The I² results for different body regions also indicate that the studies reporting the prevalence of MSDs in the lower back were without heterogeneity. The level of heterogeneity in studies reporting the prevalence of MSDs for the hip was moderate. Additionally, the studies reporting MSDs in other regions showed very high heterogeneity.
Table 3.
Summary of meta-analysis results related to different body regions
| MSDs | Number of studies | Sample size | Prevalence of MSDs | 95% CI | I2 | Begg’s test | Egger’s test |
|---|---|---|---|---|---|---|---|
| Shoulder | 9 | 1090 | 31.5% | 22.25- 40.75% | 92% | P = 0.175 | P = 0.104 |
| Neck | 10 | 1348 | 25.79% | 18.15- 33.43% | 91.7% | P = 0.032* | P = 0.008* |
|
Lower back |
15 | 2662 | 23.46% | 9.29- 37.64% | 0.0% | P = 0.553 | P = 0.346 |
| Knee | 6 | 705 | 22.26% | 11.37- 33.16% | 93.7% | P = 0.133 | P = 0.120 |
| Ankle | 6 | 658 | 20.46% | 9.77- 31.16% | 95.4% | P = 0.573 | P = 0.024* |
| Wrist | 6 | 620 | 20.25% | 10.13- 30.37% | 92% | P = 0.133 | P = 0.105 |
|
Upper back |
7 | 1012 | 18.65% | 10.70- 26.61% | 92.1% | P = 0.133 | P = 0.171 |
| Elbow | 6 | 674 | 11.91% | 5.65- 18.17% | 87.8% | P = 0.024* | P = 0.081 |
| Hip | 5 | 744 | 7.50% | 5.15- 9.86% | 27.5% | P = 0.086 | P = 0.014* |
CI: Confidence Interval; I2: I Squared
Significant differences (P < 0.05) are indicated by an asterisk (*).
Discussion
In the present study, 15 studies were chosen for meta-analysis to investigate the prevalence of MSDs among truck drivers. The meta-analysis results indicated an 61.75% prevalence of MSDs among truck drivers. Additionally, the prevalence rates of MSDs in various body regions such as shoulder (31.5%), neck (25.79%), lower back (23.46%), knee (22.26%), ankle (20.46%), wrist (20.25%), upper back (18.65%), elbow (11.91%), and hip (7.50%) were determined. As per the findings, the shoulder region exhibited the highest prevalence of MSDs. Among the reviewed studies, the smallest sample size was 25 participants, and the largest sample size was 442 participants. Although initial studies showed heterogeneity due to sample size, a random-effects model was used in the meta-analysis to reduce these heterogeneities.
Among sedentary occupations, numerous studies have been conducted to explore the prevalence of MSDs. A review study revealed a global MSDs prevalence for professional drivers ranging from 43.1 to 93%, with the highest prevalence observed in the lower back region (53%) [29]. Another review study by Cardoso and Matos indicated a high prevalence of MSDs among bus drivers in various countries, with the lower back region exhibiting the highest prevalence [30]. In a review study involving dental health professionals, the prevalence of MSDs ranged from 39 to 95%, with the highest reported pain in the neck region (88.3%) and lower back (15.7–86%) [31]. Also, a group of researchers stated that the prevalence of MSDs among bank employees ranges from 60 to 80%. The nature of these employees’ jobs is such that their sedentary and long-term sitting behaviors can increase the risk of MSDs [32]. Therefore, the relatively high prevalence of MSDs among truck drivers was not far from expected, considering the nature of a similar job.
In a review study, researchers revealed that the prevalence of MSDs among orthopedic surgeons was 73.8% [33]. In Sun et al.‘s study, the yearly occurrence of WMSDs among nurses was documented as 77.2%, with the lower back, neck, and shoulders exhibiting the highest prevalence rates [34]. According to findings from another meta-analysis study, researchers indicated that the overall prevalence of MSDs among firefighters was 46.39%, with the back being the most commonly pain-affected region [35]. Compared to the findings of the present study, the results of the mentioned studies indicate that the prevalence of MSDs among truck drivers is higher than that among firefighters. However, compared to the prevalence of these disorders among nurses and orthopedic surgeons, there is not much difference.
To reduce the prevalence of MSDs among professional drivers, including truck drivers, it may be effective to identify and mitigate the risk factors that contribute to MSDs. Previous studies have reported several risk factors in this context. Some studies have highlighted long working hours, whole body vibration, prolonged sitting in awkward or tense positions, and vigorous activities, such as manual handling of loads, as factors contributing to MSDs occurrence [9]. Furthermore, the ergonomic characteristics of vehicles, including mismatches between the anthropometric characteristics of drivers and seat dimensions, can lead to musculoskeletal discomfort in the shoulder, neck, and knee regions [36]. Some studies have identified factors such as poor road quality, increased traffic, high job demands, and time constraints as exacerbating factors for job-related diseases [37, 38]. Other factors, such as speed bumps and seat slide during vehicle acceleration, also contribute to MSDs [38].
Overall, the review of studies indicates that although driver workstations have become somewhat more ergonomic due to improvements in seating and equipment, the results of evaluations at various time points still show that a high prevalence of MSDs is reported in newer studies. One significant reason for this phenomenon may be that the primary risk factor for the development of MSDs in this occupational group is prolonged sitting (static workload) and the lack of physical activity among drivers. Additionally, interventions aimed at improving workstation ergonomics can partially help prevent MSDs among drivers, but they cannot fully guarantee proper sitting behavior [39, 40].
In addition to physical ergonomic risk factors, individual and psychosocial risk factors can also play a role in the prevalence of MSDs. Varela-Mato et al. reported that poor sleep quality, anxiety, and depression as psychosocial factors can increase the risk of MSDs among heavy vehicle drivers [41]. Other studies have indicated that individual factors including age, sex, and BMI [7, 8], as well as individual behaviors such as smoking and inappropriate diets, can exacerbate the mechanical stress on skeletal-muscular structures among truck drivers [9].
Considering the relatively high prevalence of MSDs among truck drivers and the importance of maintaining musculoskeletal health to ensure work ability, it is recommended to consider solutions such as periodic screening programs related to the prevalence of MSDs. Additionally, identifying and evaluating ergonomic risk factors of the job and designing relevant training programs and ergonomic interventions should be considered to reduce MSDs among truck drivers. The results of this study, as an important source of information in the field of MSDs, may be an important step towards designing and implementing preventive programs for these disorders among truck drivers.
This study had some limitations among which we can highlight the heterogeneity among the studies that may be related to the tools, sample size, and different cut-off points in the original studies. Another limitation was the inability to report the rate of MSDs separately for men and females due to the lack of gender-based MSDs rate reporting in the original studies. Additionally, it was not feasible to conduct subgroup analysis based on the tools due to the limited number of instruments examined for MSDs.
Conclusion
The results of this study indicate that truck drivers are at a relatively high risk for the prevalence of MSDs. The overall prevalence of MSDs among truck drivers is 61.75%, with the highest prevalence occurring in the shoulder region at 31.5%. The high prevalence of MSDs can lead to significant human and financial losses, including loss of work time, increased medical expenses, workforce injuries, and job burnout. Therefore, to prevent or reduce MSDs, it is recommended to implement appropriate ergonomic intervention programs at the workstation as well as educational programs. These measures may include training in proper postural behaviors while driving, providing suitable corrective exercises, and creating an ergonomic workstation, such as improving the ergonomic features of the cabin space, steering wheel, seats, and other factors. Additionally, policymakers, health professionals, drivers, and other stakeholders should collaborate in addressing MSDs among this population. It is suggested that future studies focus on identifying ergonomic risk factors associated with truck driving and designing ergonomic interventions for this group. Implementing these measures may be effective in reducing the prevalence of MSDs among this occupational group.
Acknowledgements
All authors thank the Student Research Committee at Kerman University of Medical Sciences. The research project from which this article was derived was supported by this research center.
Abbreviations
- MSDs
Musculoskeletal Disorders
- PRISMA
Preferred Reporting Systematic Reviews and Meta-Analyses
- MeSH
Medical Subject Headings
- WOS
Web Of Science
- NMQ
Nordic musculoskeletal questionnaire
- CMDQ
Cornell Musculoskeletal Discomfort Questionnaire
- CI
Confidence Interval
Author contributions
HM and ST managed the project. HM, ST, and FM developed the inclusion criteria, screen titles, and abstract. Screening, qualitative assessment and data extraction were done by FM, ZZ and AB. ER, as a statistician, performed the statistical analyses. The final version was read and approved by all authors.
Funding
Not applicable.
Data availability
This study is a systematic review and a meta-analysis. all the data sourced from the articles listed in the tables within the manuscript.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Yasobant S, Chandran M, Reddy EM. Are bus drivers at an increased risk for developing musculoskeletal disorders. Ergon risk Assess Study J Ergon. 2015;2015.
- 2.Onawumi AS, Ajayeoba AO, Fajobi MO. Ergonomic Assessment And Driving Experience of Taxicab Operators In Nigeria.
- 3.Rosenbloom T. Professional drivers. Handbook of traffic psychology. Elsevier; 2011. pp. 389–99.
- 4.Waters T, Genaidy A, Viruet HB, Makola M. The impact of operating heavy equipment vehicles on lower back disorders. Ergonomics. 2008;51:602–36. [DOI] [PubMed] [Google Scholar]
- 5.Aliabadi M, Darvishi E, Farhadian M, Rahmani R, Shafiee Motlagh M, Mahdavi N. An investigation of musculoskeletal discomforts among mining truck drivers with respect to human vibration and awkward body posture using random forest algorithm. Hum Factors Ergon Manuf Serv Ind. 2022;32:482–93. [Google Scholar]
- 6.Yosef T, Belachew A, Tefera Y. Magnitude and contributing factors of low back pain among long distance truck drivers at Modjo dry port, Ethiopia: a cross-sectional study. J Environ Public Health. 2019;2019. [DOI] [PMC free article] [PubMed]
- 7.Massaccesi M, Pagnotta A, Soccetti A, Masali M, Masiero C, Greco F. Investigation of work-related disorders in truck drivers using RULA method. Appl Ergon. 2003;34:303–7. [DOI] [PubMed] [Google Scholar]
- 8.Magnusson ML, Pope MH, Wilder DG, Areskoug B. Are occupational drivers at an increased risk for developing musculoskeletal disorders? Spine (Phila Pa 1976). 1996;21:710–7. [DOI] [PubMed]
- 9.Senthanar S, Bigelow PL. Factors associated with musculoskeletal pain and discomfort among Canadian truck drivers: a cross-sectional study of worker perspectives. J Transp Heal. 2018;11:244–52. [Google Scholar]
- 10.Pickard O, Burton P, Yamada H, Schram B, Canetti EFD, Orr R. Musculoskeletal Disorders Associated with Occupational Driving: a systematic review spanning 2006–2021. Int J Environ Res Public Health. 2022;19:6837. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Pradeepkumar H, Sakthivel G, Shankar S. Prevalence of work related musculoskeletal disorders among occupational bus drivers of Karnataka, South India. Work. 2020;66:73–84. [DOI] [PubMed] [Google Scholar]
- 12.Asli K. Risk factors Associated with Musculoskeletal disorders among Professional drivers in Asian countries: a systematic review. J Sains Kesihat Malaysia. 2023;21:143–55. [Google Scholar]
- 13.Bovenzi M. A longitudinal study of low back pain and daily vibration exposure in professional drivers. Ind Health. 2010;48:584–95. [DOI] [PubMed] [Google Scholar]
- 14.Mother D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Downes MJ, Brennan ML, Williams HC, Dean RS. Development of a critical appraisal tool to assess the quality of cross-sectional studies (AXIS). BMJ Open. 2016;6. [DOI] [PMC free article] [PubMed]
- 16.Orlewski J, Orlewska E. Effects of genetic polymorphisms of glutathione S-transferase genes (GSTM1, GSTT1, GSTP1) on the risk of diabetic nephropathy: a meta-analysis. Pol Arch Med Wewn. 2015;125:649–58. [DOI] [PubMed] [Google Scholar]
- 17.Kuorinka I, Jonsson B, Kilbom A, Vinterberg H, Biering-Sørensen F, Andersson G, et al. Standardised nordic questionnaires for the analysis of musculoskeletal symptoms. Appl Ergon. 1987;18:233–7. [DOI] [PubMed] [Google Scholar]
- 18.Hedge A, Morimoto S, Mccrobie D. Effects of keyboard tray geometry on upper body posture and comfort. Ergonomics. 1999;42:1333–49. [DOI] [PubMed] [Google Scholar]
- 19.Sa-Ngiamsak T, Thetkathuek A. Short-distance versus long-distance deep-seaport container truck drivers’ prevalence and perceived discomfort of musculoskeletal symptoms in the Thailand Eastern Economic Corridor. Int J Occup Saf Ergon. 2022;28:1779–86. [DOI] [PubMed] [Google Scholar]
- 20.Kumar R, Sharma R, Kumar V, Khan AA. Relation of work stressors and work-related MSDs among Indian heavy vehicle drivers. Indian J Occup Environ Med. 2021;25:198. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Sekkay F, Imbeau D, Chinniah Y, Dubé P-A, de Marcellis-Warin N, Beauregard N, et al. Ergonomic Assessment of exposure to Musculoskeletal disorders risk factors among Canadian Truck drivers. Congress of the International Ergonomics Association. Springer; 2021. pp. 829–36.
- 22.Gumasing MJJ, Pacheco MEG. Predictive model on the severity of musculoskeletal disorder and accidents of truck drivers in the Philippines. In: 2nd European Conference on Industrial Engineering and Operations Management (IEOM). 2018. pp. 26–7.
- 23.Sekkay F, Imbeau D, Chinniah Y, Dubé P-A, de Marcellis-Warin N, Beauregard N, et al. Risk factors associated with self-reported musculoskeletal pain among short and long distance industrial gas delivery truck drivers. Appl Ergon. 2018;72:69–87. [DOI] [PubMed] [Google Scholar]
- 24.Kim JH, Zigman M, Aulck LS, Ibbotson JA, Dennerlein JT, Johnson PW. Whole body vibration exposures and health status among professional truck drivers: a cross-sectional analysis. Ann Occup Hyg. 2016;60:936–48. [DOI] [PubMed] [Google Scholar]
- 25.Mozafari A, Najafi M, Vahedian M, Mohebi S. Assessment of musculoskeletal disorders between lorry drivers in Qom, Iran. Galen Med J. 2014;3:e140–140. [Google Scholar]
- 26.Robb MJM, Mansfield NJ. Self-reported musculoskeletal problems amongst professional truck drivers. Ergonomics. 2007;50:814–27. [DOI] [PubMed] [Google Scholar]
- 27.Andrusaitis SF, Oliveira RP, Barros Filho TEP. Study of the prevalence and risk factors for low back pain in truck drivers in the state of São Paulo, Brazil. Clinics. 2006;61:503–10. [DOI] [PubMed] [Google Scholar]
- 28.Miyamoto M, Shirai Y, Nakayama Y, Gembun Y, Kaneda K. An epidemiologic study of occupational low back pain in truck drivers. J Nippon Med Sch. 2000;67:186–90. [DOI] [PubMed] [Google Scholar]
- 29.Joseph L, Standen M, Paungmali A, Kuisma R, Sitilertpisan P, Pirunsan U. Prevalence of musculoskeletal pain among professional drivers: a systematic review. J Occup Health. 2020;62:e12150. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Cardoso A, Matos ML. The prevalence of work-related musculoskeletal disorders (wmsds) in professional bus drivers—a systematic review. Occup Saf Hyg V. 2017;:211–4.
- 31.Subedi S. Prevalence of Musculoskeletal disorders (MSDs) among Dental Health professionals: a review of the literature. Va J Public Heal. 2020;4:5. [Google Scholar]
- 32.Guduru RKR, Domeika A, Obcarskas L, Ylaite B. The ergonomic association between shoulder, neck/head disorders and sedentary activity: A systematic review. J Healthc Eng. 2022;2022. [DOI] [PMC free article] [PubMed]
- 33.Vasireddi N, Vasireddi N, Shah A, Moyal A, Ng M, Seshadri D, et al. 63. Prevalence of work-related musculoskeletal disorders among orthopedic surgeons: a systematic review and meta-analysis. Spine J. 2023;23:S32. [Google Scholar]
- 34.Sun W, Yin L, Zhang T, Zhang H, Zhang R, Cai W. Prevalence of work-related Musculoskeletal disorders among nurses: a Meta-analysis. Iran J Public Health. 2023;52:463. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Tahernejad S, Farahi-Ashtiani I, Veisani Y, Ghaffari S, Sahebi A, Makki F. A systematic review and meta-analysis of musculoskeletal disorders among firefighters. J Saf Res. 2023. [DOI] [PubMed]
- 36.Szeto GPY, Lam P. Work-related musculoskeletal disorders in urban bus drivers of Hong Kong. J Occup Rehabil. 2007;17:181–98. [DOI] [PubMed] [Google Scholar]
- 37.Maduagwu SM, Galadima NM, Umeonwuka CI, Ishaku CM, Akanbi OO, Jaiyeola OA, et al. Work-related musculoskeletal disorders among occupational drivers in Mubi, Nigeria. Int J Occup Saf Ergon. 2022;28:572–80. [DOI] [PubMed] [Google Scholar]
- 38.Araújo AV, Arcanjo GS, Fernandes H, Arcanjo GS. Ergonomic work analysis: a case study of bus drivers in the private collective transportation sector. Work. 2018;60:41–7. [DOI] [PubMed] [Google Scholar]
- 39.Tahernejad S, Choobineh A, Razeghi M, Abdoli-Eramaki M, Parsaei H, Daneshmandi H, et al. Investigation of office workers’ sitting behaviors in an ergonomically adjusted workstation. Int J Occup Saf Ergon. 2022;28:2346–54. [DOI] [PubMed] [Google Scholar]
- 40.Tahernejad S, Razeghi M, Abdoli-Eramaki M, Parsaei H, Seif M, Choobineh A. Recommended maximum holding time of common static sitting postures of office workers. Int J Occup Saf Ergon. 2023;29:847–54. [DOI] [PubMed] [Google Scholar]
- 41.Varela-Mato V, Clemes SA, King J, Munir F. Associations between musculoskeletal conditions risk, sedentary behavior, sleep, and markers of mental health: a cross-sectional observational study in heavy goods vehicle drivers. Musculoskeletal conditions risk in HGV drivers. J Occup Environ Med. 2019;61:437–43. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
This study is a systematic review and a meta-analysis. all the data sourced from the articles listed in the tables within the manuscript.