Abstract
BACKGROUND:
It is generally agreed that musculoskeletal disorders (MSDs) are a severe health concern, particularly for agricultural laborers.
OBJECTIVES:
The study aimed to identify risk factors and work-related disorders among agricultural workers at Amirkabir agro-industry company in Iran.
METHOD:
A total of 158 workers, of which 66 were manual harvesting workers (four postures), 40 were fertilizer transportation workers (three postures), and 52 were spraying workers (one posture), were included in the study. The research used questionnaires to collect data, and the postures were analyzed using 3DSSPP software. Related risk factors such as age, body mass index, work experience, working hours, and sports activity were analyzed.
RESULTS:
The incidence rate of lower back pain (94%), knee pain (82%), neck pain (69%), upper-back (63%), and shoulder (63%) were calculated. The logistic regression revealed that working hours and sports activities are significantly correlated to the wrist/hand and neck MSD with 5.62 and 6.38 times more likely among manual harvesting workers. The 3DSSPP software estimated that the lower back pain, especially in the first posture, for manure transportation workers was very high. Maximum L5-S1 compression, shear, and moment forces in the first posture among manure transportation workers were 7113 N and 472 N, -381 N-m, respectively.
CONCLUSION:
The 3DSSPP results also illustrated that compression, shear, and moment forces exceeded the NIOSH limit for the other postures. After interventions, compression, shear, and moment forces among all farm workers decreased. These findings emphasize that farm workers need to be under surveillance continuously at their workstations where interventions and improvement in specific tasks are required.
Introduction
Musculoskeletal disorders (MSDs) are considered as a fundamental well-being issue in almost all countries and occupations, especially among workers in the agricultural sector [1]. The symptoms of work-related musculoskeletal disorders (WMSDs) are sickness, stress, and a remarkable reduction in the ability to perform physical activities [2, 3], which are the leading causes of low productivity at work [4]. The economic expenditures associated with the prevalence of MSDs are staggering, and this daunting problem is likely to worsen in the not-too-distant future [5–7]. Many researchers contend that this widespread issue has become a national priority, no matter how developed a country is and no matter the standard of living [6, 8].
Non-mechanistic methods account for an essential part of planting and harvesting in sugarcane cultivation, which has caused MSD occurrences. Various surveys have been carried out to study the prevalence of MSDs among farmers of many crops [9–18]. However, little or no information was available regarding MSDs in Western Asian sugar production, especially in Iran, where the sugar production industry heavily relied on non-mechanistic processes [19]. As with any complex condition, research regarding the risk factors related to these complaints in a particular group of workers in the agricultural industry, such as manual harvesting workers, fertilizer transportation workers, and spraying workers, is far less advanced. Although some authors acknowledge that farmers in these agricultural sectors are forced to work in awkward positions for extended periods [18–21], none of the studies examined biomechanical evaluation directly and simultaneously. For instance, Acosta-Leon et al. found different hazard factors related to adverse safety and health outcomes among Hispanic workers in the U.S [24]. Work postures, working conditions, and MSDs were all assessed in agricultural sector [18]. Moreover, MSDs have occurred among 92% of workers in Almeria (Spain), which has the highest concentration of greenhouse crops in Europe. The agricultural sector employs 55,000 people, and more than half of them have had to change their jobs or tasks due to MSDs [22]. Workers involved in agriculture and food production have now been shown to be much more prone to physical issues [25]. Wenig et al. estimated the total cost of back pain in Germany. The study revealed that the cost of MSDs is around 49 billion EUR [26]. On the other hand, some research conducted across the European Union confirmed that MSDs are the leading cause of work disability, absence from work, and productivity loss [27]. Nonetheless, compression, shear, and moment forces acting on the spine were ignored. More importantly, few studies have suggested ergonomic corrections for agricultural workers, such as personal devices and/or special supporting machines for relieving lower back problems despite the high rate of occurrence of MSDs [23]. To tackle the prevalence of MSDs and to find a solution to these daunting consequences, it is essential to take preventative measures against hazard factors and use biomechanical methods to identify MSDs in a particular job category.
Few studies examine agricultural workers’ working conditions, job postures, musculoskeletal disorders, and low back pain in the interest of ensuring a safe workplace. Statistical models, biomechanical software, and questionnaires are useful for finding MSDs and help to identify and organize agricultural sectors and create new approaches to alleviate those complaints. The findings in this area will aid in the discovery and advancement of solutions to such agricultural sector-specific problems. The three techniques described above are highly effective at identifying musculoskeletal problems. Additionally, these techniques can be used to identify and categorize various agricultural sectors and to develop novel approaches to resolving those complaints.
Based on the above literature, this study aimed to examine the prevalence of MSDs among sugarcane industry workers in Ahvaz, Iran. Firstly, the extent, intensity, career interference, and potential effects on musculoskeletal symptoms among agricultural workers (manual harvesting, fertilizer transportation, and spraying workers) were identified. Secondly, the relationships between MSDs and hazard factors such as work-related factors, awkward postures, and socio-demographic data were explored. Moreover, compression, shear, and moment forces were calculated according to their postures. The outcome of the investigation into this field will suggest a plan of action by which the prevalence of MSDs can be diminished, and work productivity will be improved.
Materials and methods
Study area and population
This study was conducted to recognize the occurrence of MSDs and related hazard factors. The 3DSSPP software was used to find musculoskeletal pain among farm workers. A sample of 158 workers at Amirkabir agro-industry company in Ahvaz, Iran (Fig. 1) was selected. After selecting an agro-industry company, the required number of study participants (48 participants) was found using the probability proportion to size sampling technique. A pilot study was conducted on a sample of 30 workers and used a 95% confidence interval, 80% power, and two-tailed tests to find the proportion. The G-Power software program calculated the sample size to be 158. Three occupations were determined, including manual harvesting (to harvest the remaining sugarcane with a sickle), spraying, and fertilizer transportation (moving the manure). The study’s inclusion criteria were at least a year of work experience, and exclusion criteria included any chronic congenital discomfort or injuries from an accident or other factors outside the workplace.
Typical working postures of the sugar production workers.
A self-modified questionnaire was given to all farm workers who were appropriate to participate in this study. The participation rate among sugar production workers was 100%. The survey was a self-administered questionnaire that contained three sections: sociodemographic data, work-related details, and various types of musculoskeletal problems. The first part included social demographic information, including age, BMI, height, weight, and education. Secondly, information related to work characteristics, such as working hours (day), working experience (year), sleeping hours, and sports activities, was collected. The third part was the standardized Nordic Musculoskeletal Questionnaire (NMQ) following Kuorinka et al., 1987, which assessed MSDs in different body parts over 12 months and seven days [28]. The NMQ was divided into nine parts of the body, including neck pain, shoulder pain, elbow pain, wrist/hand pain, upper and lower back pain, hip/thigh pain, knee pain, and ankle/feet pain. The validity of the questionnaire was obtained by holding a panel of ten experts (CVI > 0.81, CVR > 0.77). The questionnaire reliability was achieved by conducting a pilot study among 20 similar sample individuals. Retesting and Cronbach’s alpha were 0.89 and 0.99, respectively.
Risk assessment methods
Software that focuses on biomechanical modeling can estimate loads based on the structures of different body parts. For example, the Linked-Segment Biomechanical Model (LSBM), the Hand-Calculation Back Compressive Force, the Anybody Modeling System (AnyBody Technology, Aalborg, Denmark), and the University of Michigan’s 3D Static Strength Prediction Program (3DSSPP) were used [29–32]. The 3D Static Strength Prediction Program (3DSSPP) from the University of Michigan was used to assess musculoskeletal problems. The inputs were weight, height, loads, and angles. The outputs were compression, shear, and moment forces. The ImageJ software was used to calculate angles and increase the accuracy of pictures in different postures. For the manual harvesting task, four movements, including lifting the cane, preparing for cutting, manual harvesting, and carrying the cane, were selected. Lifting, transporting, and laying bags on the ground were all noted as three movements in the fertilizer transportation task. There was only one step to complete in order to perform the farm spraying task (Fig. 2). These three work tasks each dealt with a maximum weight of 5.4 kg, 25 kg, and 15 kg, respectively. In order to tackle this serious issue, two possible solutions were evaluated. An extra worker was added to carry fertilizer, which results in less loading. The load on both manual harvesting and spraying work was reduced to diminish the pressure on these workers. The maximum weight of each task reached 2.4 kg, 16.6 kg, and 7.5 kg, respectively.
Schematics of the simulated tasks for spinal loads prediction for different job categories by 3DSSPP software.
Statistical data analysis was performed by SPSS software version 22. Cross-sectional, description-analytical statistics were used to determine the sociological characteristics of responders, including mean, standard deviation (SD), median, and percentage. The study involved a chi-square test, a t-test, and a variance analysis to determine occupational differences. First, a chi-square test was conducted to relate individual hazard factors to MSDs. Then, odds ratios and their 95 % confidence intervals were computed using logistic regression models to assess and classify MSD-related variables. The presumptions of regression models and the models’ fit were checked and verified by the Hosmer-Lemeshow test. Statistical significance was established at the level of p < 0.05 for all tests.
Ethics
The study was endorsed by Ethical Committee Members of the Shahid Chamran University of Ahvaz to observe ethical principles. The names and details of the farm workers were avoided in the questionnaire and checklist. Participants were assured that their information would be confidential and would only be used for research purposes.
Results
Demographic data
The average age of manual harvesting, fertilizer transportation, and spraying workers was 26.9 years [SD = 5.1], 27.8 years [SD = 4.5], and 28.5 years [SD = 3.2], respectively. Most participants in all three jobs were in their twenties and thirties. The percentage of workers with low literacy levels was high. Among manual harvesting, fertilizer transportation, and spraying workers, the rates were 45.4%, 32.5%, and 13.5%, respectively. The majority of the manual harvesting workers, 64%, had a healthy BMI. Meanwhile, the percentage of people with a healthy BMI fell to 50% compared to manure transportation workers. At the lower levels of 30%, 50%, and 44%, respectively, the overweight group was identified. 6% of manual harvesting workers were in the underweight group. In the study, the heights’ mean was 173.4, 173.8, and 172.4, respectively.
Socio-demographic details of farm workers
Socio-demographic details of farm workers
More than half of the farm workers in Table 2 had over ten years of work experience, and the corresponding ranges were 54.5%, 67.5%, and 86.5% of these workers. Work experience among farm workers was 38%, 22.5%, and 11.5% for people with 6-10 years of industry experience. Approximately 65% of manual harvesting workers, roughly 70% of fertilizer transportation workers, and nearly 60% of spraying workers claimed they worked longer than eight hours per day. In addition, the majority of workers got about 6-8 hours of sleep, 56 %, 67.5 %, and 60%. It was found that there was a significant lack of sports activities at work, with the figures showing that 12%, 7.5%, and 21% of workers participated in sports activities.
Work-related details of farm workers
Work-related details of farm workers
The incidence of MSDs in the last 12 months is shown in Table 3. 94% of farm workers reported having low back pain in the previous year, with only 6% reporting no pain. While undertaking all three activities, the incidence of MSDs was the highest in the lower back. Additionally, the most significant number of work-related MSDs in manual harvesting workers occurred in the lower back, 91%, and the knee, 89%. The percentage of MSDs prevalence in fertilizer transportation workers was significantly higher in their lower back 97.5% and wrist/hand 95%. Similarly, MSDs among spraying workers were mainly linked to the lower back and the shoulder, with 94% and 92%.
Characteristics of musculoskeletal discomfort among farm workers (n = 158)
Characteristics of musculoskeletal discomfort among farm workers (n = 158)
Tables 4 and 5 indicate the factors associated with the causes of potential hazards and their role in different parts of the body (nine areas). It was determined that MSDs are prevalent in the back, wrist/hand, knee, shoulder, upper back, and hip/thigh. This study discovered that younger manual harvesting workers (20–29 years old), fertilizer transportation workers (30–39 years old), and spraying workers (30–39 years old) were more likely to have musculoskeletal disorders. During work hours and physical activity, manual harvesting workers in all age groups have an increased risk of hip/thigh problems. Additionally, a significant correlation was observed in fertilizer transportation workers’ necks, elbow, and knee (p < 0.05). Workers in the fertilizer transportation industry (BMI > 25) were significantly correlated with elbow pain (p < 0.05). More disorders were observed among manual harvesting workers during the 1–8 hour working time than during the 9–12 hour. Moreover, this study discovered a significant correlation between working hours and wrist/hand discomfort in manual harvesting workers (p < 0.05). In turn, among manual harvesting workers, sleeping hours were correlated with the elbow, wrist, and the upper back (p < 0.01). Conversely, neck, shoulder, elbow, and work experience connect with the task of fertilizer transportation workers (p < 0.01). Work experience correlated significantly with the neck, upper-back, and lower back among spraying workers (p < 0.01). The lower back and knee were remarkably affected by sports activity among manual harvesting workers (p < 0.01). Moreover, there is no correlation between working and sleeping hours with the MSDs of nine areas among spraying workers and fertilizer transportation workers.
Related risk factors to MSDs prevalence
Related risk factors to MSDs prevalence
Note: p-value were conducted using Chi-square.
Related risk factors to MSDs prevalence
Note: p-value were conducted using Chi-square.
Table 6 illustrates the relationship between risk factors and the extent of compression and shear forces on the L4-L5 and L5-S1 vertebrae. These findings indicated that nearly all factors resulted in increased pressure on the lumbar vertebrae. The age factor was significant among all farm workers except fertilizer transportation workers (L4-L5, L5-S1 compression forces). A similar relationship was observed between compression and shear forces and BMI for manual harvesting workers (p < 0.01). This study revealed that the higher the BMI rate, the more pressure on farm workers, and, as a consequence, workers endured more compression and shear forces. Nonetheless, there was no meaningful relationship between BMI and L4-L5, L5-S1 (compression forces) vertebrae among fertilizer transportation workers. Likewise, there was no significant relationship between working hours and compression/shear forces among manual harvesting and manure transportation workers. The working hours and compression/shear forces were significantly correlated for spraying workers (p < 0.01). The connection between sleeping hours and compression/shear forces was variable, and there was no relationship in any jobs. Work experience was linked to compression/shear forces (p < 0.01). Furthermore, all numbers indicated a significant relationship between work experience and the compression/shear forces among fertilizer transportation workers (except L4-L5/L5-S1/ compression force). Among spraying workers, sports activities significantly affected L4-L5 (shear force) (p < 0.05). Additionally, no correlation exists between sports activities and compression/shear forces among manual harvesting and fertilizer transportation workers.
Related risk factors to compression and shear forces
Related risk factors to compression and shear forces
Note: p-value were conducted using Chi-square.
In Table 7, logistic regression was applied to study the role of different groups. A preliminary analysis of Chi-square was conducted to identify hazard factors that related to MSDs. The results proved a substantial connection between age and all parts of the body except the hip/thigh among hand-operated harvesting workers. Conversely, BMI was positively correlated with hip/thigh MSDs, with 2.66 times more likely among manual harvesting workers. Moreover, work experience was significantly associated with shoulder disorders, occurring 3.47 times more frequently in manual harvesting workers. Working hours and sports activity were associated with increased odds of wrist/hand and neck MSDs among manual harvesting workers, who were 5.62 and 6.38 times as likely to incur such injuries. The study demonstrated that fertilizer transportation workers have high rates of work-related musculoskeletal disorders, and they account for a large percentage of the occupational group with musculoskeletal disorders. Age, BMI, and work experience have been linked to knee, neck, and knee disorders in fertilizer transportation workers, appearing 5.84, 3.41, and 4.18 times more frequently. On the other hand, only age was directly associated with elbow, spraying workers having a 5.42 times greater likelihood of suffering an elbow problem.
Regression analysis of relation of significant factors predicting MSDs among farm workers
Regression analysis of relation of significant factors predicting MSDs among farm workers
Prevalence of MSDs
Compelling evidence has found that the incidence of MSDs among agricultural workers was relatively high. Therefore, the purpose of this study was to find related risk factors and MSDs among farm workers in Amirkabir agro-industry company in Ahvaz, Iran, over 12-months. This study showed that 94% of agricultural workers had experienced lower back discomfort in the past 12 months, and only 6% had no pain. Kaewdok et al. reported that the prevalence of MSDs was almost in three parts of the body, with the highest occurrence of pain in the lower extremities, lower back, and shoulder [33]. A study from South Korea showed that MSDs in the lower back among Korean farmers were not equivalent to the findings of this study. It was found that the prevalence of WMSDs in each position was 33.3% [34]. Mcmillan et al. found that MSDs most frequently happened in the lower back among Canadian farmers [35]. A survey in Nepal illustrated that more than 70% of farmers had MSDs [36]. Dianat et al. reported a relatively high prevalence among Iranian farm workers, with lower back 75.1%, knee 62.1%, upper-back 61.55%, and neck 59.9%, this study found that lower back pain was more common than other body parts, and musculoskeletal discomfort among farm workers (neck, upper-back, and lower back) was approximately equivalent to the research findings [18]. Nevertheless, this survey indicated that the lower back prevalence was relatively more distinguished than reported in the United States of America, at 33.2%, followed by the neck/shoulder at 30.8%, and the elbow/wrist/hand at 21.6% [37]. Among manual harvesting workers, neck, upper-back, and lower back MSDs were noted in 74%, 62%, and 91%, respectively. In turn, among U.S. farm workers, 24.3% and 10.5% reported having lower back and neck pain in the previous three months, while 17.0% reported having joint pain in their hip/thigh/knee, 9.8% reported having joint pain in their shoulder, 9.5% reported having joint pain in their wrist/hand, 5.4% reported having joint pain in their elbow, 4.7% reported having joint pain in their ankle, and 4.7% reported having pain in their feet/toes [38]. The prevalence of MSDs among male and female farmers was 79.0% and 88.5%, respectively. According to the study, the lower back, shoulder, and knee among men were higher, whereas the shoulder, lower back, and wrist/hand were higher among women [39]. A substantial number of studies have shown an elevated MSD incidence among farmers. These statistics showed that 33.3% in Korea, 54% in the United States, 56% in Ireland, 68.1% in Kenya, and 69% in Nepal, while around 85.4% in Canada, 88.7% in China, and 92% in India [34, 51]. However, other studies report that the prevalence of neck pain is approximately 39.6% in Canada, nearly 18.5% in Thailand, and roughly 25% in Ireland [33, 41]. An Indian survey revealed higher MSDs in most body parts, and approximately 99% of the study participants suffered from them, especially in the lower back, shoulder, hands, and knee [45].
MSDs remarkable factors
Age
The current study results showed that elbow problems were 5.42 times more likely for workers between the ages of 30 and 39 (p = 0.02). Additionally, between ages 30 and 39, the risk of neck problems among fertilizer transportation workers is expected to increase by 5.84 times (p = 0.015). Although the occupations were different, the results by Dianat et al., who studied the musculoskeletal pain of Iranian farmers’, were in agreement with these findings [18]. A study was conducted in the U.S. on farm workers to examine the correlation between age and musculoskeletal discomfort. The results also illustrated that the relationship was significantly related to younger participants (shoulder pain, p = 0.04; back pain, p = 0.05) [46]. Still, despite this, Xiao et al. found that workers who reported lower back, knee, and hip/thigh pain were more likely to have musculoskeletal pain and were more likely to have MSDs as they got older [47].
Body mass index
According to findings, a person’s BMI was strongly linked to the areas of the body affected: the shoulder, wrist/hand, upper-back, and hip/thigh. For the odds ratio for hip/thigh, manual harvesting workers had a 2.66 times greater chance of having this measurement than non-manual workers. Specifically, BMI was positively associated with the MSDs of the lower extremity, in concordance with the findings of this study [48]. In addition, research done on other occupations, such as teachers, has also shown that the likelihood of having a musculoskeletal disorder increases as BMI increases [19]. Based on this study, the relationship between BMI and upper body parts (wrist/hand, upper-back) was also significant (p < 0.01). The results by Holmberg et al. are in line with the obesity epidemic affecting the knee 3.21 times [49]. This issue can lead to various musculoskeletal problems due to the additional weight placed on the body.
Sports activity
This study claims that most agricultural workers are not physically active because of their low wages. Manual harvesting workers had an association of 6.38 times with neck pain, as measured by logistic regression (p = 0.02). Conclusions drawn from this evidence suggest that the neck is heavily involved in sports activities, which mirrors conclusions drawn by Dianat et al. [18]. Additionally, sports activities had no significant association with the other two occupations, especially among spraying workers.
Working hours
A relationship was found between BMI, age, hours of sleep, and manual harvesting work hours. However, manual harvesting work hours were 5.62 times more potent in predicting wrist/hand MSDs (p = 0.032). Conversely, Holmberg et al. reported that the odds ratio for wrist/hands concerning working hours for Swedish farmers was 0.98 [49]. Due to the inadequate wages prevalent in developing countries, farm workers are frequently required to work additional hours. Manure transportation and spraying workers were not significantly affected by this risk factor.
Work experience
The results of Table 7 demonstrated that manual harvesting workers are 3.47 times more likely to suffer from shoulder pain than those who have no prior work experience (p = 0.016). In addition, among fertilizer transportation workers, there was an associated risk of pain in the knee 4.18 times (p = 0.015). The role of using sickles in manual harvesting jobs was to increase the connection between shoulder pain and previous work experience. Repetitive movements were likely to increase musculoskeletal disorders. They also perambulate several meters to transport harvested sugarcane during working hours. Additionally, the repeated stress of bending and lifting manure bags during work can have irreversible effects on the knee of fertilizer transportation workers.
Lower back pain
The shear, compression, and moment forces on agricultural workers were estimated using 3DSSPP software. According to the National Institute for Occupational Safety and Health, a compression force of less than 3400 N is not harmful., the risk of injury is relatively high (between 3400 and 6400 N), and the risk of injury is extremely high (above 6400 N) [50]. Table 8 has proved that all workers, especially fertilizer transportation workers, suffer from awkward posture and heavy loads. According to the present study, the maximum L5-S1 compression, shear, and moment forces among fertilizer transportation workers were 7113 N, 472 N, and 381 N-m at first posture. Compared to other workers, the spraying workers endured the lowest pressure, where the maximum L4-L5 compression, shear, and moment forces were 642, 177, and-14 N-m, respectively. It was also revealed that height, weight, and BMI affected lower back pain. The taller and fatter the worker, the more pressure on L4-L5 and L5-S1 between all three jobs. The maximum and minimum moment forces on the L4-L5 and L5-S1 among fertilizer transportation workers were-366 N-m, -381 N-m, -144 N-m, and-154 N-m, respectively. In the first posture, the maximum L5-S1 compression, shear, and moment forces were 2922 N, 459 N, and-166 N-m, respectively, between manual harvesting workers. Compared to the other jobs, the moment forces on L4-L5 and L5-S1 among spraying workers were negligible, and the most significant moment forces were-14 and-22 N-m, respectively. The 3DSSPP results also showed that compression, shear, and moment forces exceeded the NIOSH limit for various postures.
Predicted L4-L5 and L5-S1 compression (c), moment (m), and posterior-anterior shear (s) forces using 3DSSPP software
Predicted L4-L5 and L5-S1 compression (c), moment (m), and posterior-anterior shear (s) forces using 3DSSPP software
Note: data were calculated using 3DSSPP software.
A substantial number of agro-industry companies have successfully implemented ergonomics remedies in their facilities to address the risk of injuries due to MSDs in their workers. These plans consisted of modifying existing equipment, changing work practices, and implementing new devices to facilitate the production process. These changes have reduced physical requirements, eliminated unnecessary movements, injury rates, and associated costs of workplace problems. Successful ergonomics interventions may be implemented through various mediations or interventions, such as engineering/interfacing design, training, and selection. Based on the results of this study, back, knee, neck, shoulder, arms, and hand pain were the most frequent symptoms reported by agricultural workers. According to the studies conducted by the authors, the following items were introduced to company managers to reduce the effects of pain.
The results of the 3DSSPP software illustrated that awkward postures and weight in all three occupations led to increased pressure on the lumbar vertebrae. In all three jobs, the results were associated with weight. After interventions, compression, shear, and moment forces among fertilizer workers in the first posture on L4-L5 and L5-S1 reached 5157 N, 292 N, and-272 N-m and 5322 N, 387 N, and-272 N-m, respectively (Fig. 3). The results of the 3DSSPP software illustrated that these remedies were also suitable for sprayers and manual harvesters. Moreover, based on the results of this study, some interventions, including job rotation, design and manufacture of a medical belt based on anthropometric data in order to reduce pressure on the lumbar vertebrae, using a forklift in order to decrease the pressure on the manure transportation workers, and thermal control, which have a less detrimental effect on the environment and the health of consumers [51], were suggested to managers. These findings emphasize that farm workers need to be under surveillance continuously at their workstations where interventions and improvement in specific tasks are required.
Comparing mean total forces before and after interventions.
This study compared with international standards revealed a high prevalence of MSDs, particularly in the lower back, wrist/hand, shoulder, knee, and hip/thigh among farm workers, especially fertilizer transportation workers, which emphasizes the requirement for ergonomic interventions to improve working conditions. Associated risk factors such as age, BMI, sports activity, work experience, and working hours among farm workers were investigated. Since related risk factors propel a higher prevalence of MSDs, improving working conditions and reducing the incidence of MSDs are critical. To mitigate MSDs, more intervention strategies should be implemented among agricultural workers to increase ergonomic awareness through training programs. In most cases, ergonomics lessons and new methods should be taught to farm workers as much as possible. Physical work can be reduced by designing low-cost and ergonomic tools for carrying, harvesting, and spraying. Agricultural robots can be a great help for farmers. It is recommended to reduce working hours. It is also suggested to check medical conditions every month.
Limitations
There were several limitations in the current study that should be considered as a warning. The respondents filed the questionnaire casually due to a busy schedule and unwillingness, which led to information collection problems. Respondents’ biases and hesitations had a major impact on survey analysis. NMQ was used to find musculoskeletal pain. Consequently, some workers may have given unrealistic answers, which may result in biased data.
Furthermore, since all workers were men, the impact of risk factors on women was not investigated. On the other hand, flexion, extension, and rotation are three movements of the spine. These movements result in various forces acting on the lumbar spine, including compression, tensile, muscle, shear, and moment forces. Due to the limitations of 3DSSPP software, only compression, shear, and moment forces were considered by researchers.
Conflict of interest
The authors confirm that there is no conflict of interest to disclose.
Footnotes
Acknowledgments
The authors would like to thank Amir Kabir Agro-industry Company and Shahid Chamran University of Ahvaz for providing information and for their technical and content-related support during the study performance.