Work-related musculoskeletal disorders in agriculture: Ergonomics risk assessment and its prevention among Indian farmers

2.1 Research design and setting

A random sampling of four hundred and seventy-two farmers from Chowtara, Banna, Gopinagar, and Ichhapur of the Hooghly district near Tarakeswar, West Bengal, was conducted in this study. For this cross-sectional study, West Bengal, India, was chosen to avoid bias. Due to unwillingness to share data and other factors, 37 farmers declined to participate, and 23 were excluded due to random sampling. The four hundred and seventy-two farmers are divided into two groups: 235 work on their farms, while 237 are paid, farmers (who work as a paid labors). Out of 472 farmers in this study, 213 are rice farmers, 206 are potato farmers, and 56 are groundnut farmers.This study included only farmers with at least two years of farming practice. In addition, farmers with a history of occupational injuries were excluded from the study. A questionnaire was used to gather this information, which included years of experience and previous occupational injury history. Performed the interview among farmers during recess (without obstructing their work) and after the participants had completed their day’s work. The Indian Council of Medical Research Guidelines Institutional Human Ethical Clearance Committee approved (Approval number 01/2019, dated 12.03.2019) the study before it was conducted.

2.2 Nordic modified questionnaire (NMQ) study

For analyzing the different types of discomfort (pain, numbness, tingling, swelling, etc.) in the other parts of the body, the Nordic questionnaire [25] was used among the study participants. Before the survey was conducted, the farmers gave individual explanations of the procedure. While farming was in recess, interviews were conducted confidentially. A variety of objective questions are included in this questionnaire, written in the local language (Bengali). Farmers were asked about their details, socioeconomic conditions, types of activities they perform, and the types of pain they feel in various parts of their bodies. The first part of the process involves identifying the symptoms of discomfort (pain) in different body parts of the body and pain experienced for the past 24 hours, 7 days, and the past 12 months.

The NMQ includes questions pertaining to musculoskeletal problems during the past 24 hours, past 7 days, and past 12 months in nine anatomical areas of the body (neck, shoulders, upper back, elbows, wrists/hands, lower back, hips/thighs, knees, and ankles/feet). Regarding discomfort or pain in these areas, only a “yes” or “no” response was needed by the farmers to assess the pain or discomfort.

2.3 Assessment of repetitive tasks (ART) tool

ART is a tool designed to assess repetitive upper-limb tasks. This study examines common risk factors associated with repetitive work contributing to upper limb disorders. Upper Limb Disorders (ULDs) can be diagnosed by assessing common risk factors related to repetitive work [26]. Generally, used this tool to determine how often work processes were repeated. ART identifies the common risk factors in repetitive work related to upper limb development disorders and assesses tasks that require repetitive movement of upper body parts (arms and hands).

The assessment of ART tool is split into four stages: Stage A: Frequency and repetition of movements; Stage B: Force; Stage C: Awkward postures; Stage D: Additional factors.

Moreover, in Stage A, there is mainly two divisions, A1 = Arm movements (Observe the movement of the arm and select the category that is most appropriate) and A2 = Repetitions (This refers to movement of the arm and hand, but not the fingers). Stage B: Force (This mainly determine the level of force exerted with the hand and the amount of time that the force is exerted).

2.4 Examination of working posture

This study investigated several agricultural activities, including weeding, spading, ridging, carrying, sowing, sprinkling water, harvesting, threshing, and winnowing. The farmers performed all these activities in a constrained working posture. The postural analysis was performed using the Rapid Entire Body Assessment (REBA) method [27] to analyze different working postures in other activities in rice farming, potato farming, and groundnut farming in all the experimental farmers. First, the analysis of different working postures of the diverse group of farmers with the REBA method was carried out with digital photography (Sony Handycam 360X, Japan). Later on, stick diagrams were drawn from frozen frame video records and eventually subjected to analysis. All the farmer working postures were analyzed based on the most frequent ones.

In the REBA, the neck, trunk, and leg are scored (score A), the arm, forearm, and wrist are scored (score B), as well as the final score (grand score). Scores A and B were also calculated based on force, grip type, and muscle activity. As a result, a final score was calculated based on the proportion of musculoskeletal risks to each individual. Five action levels were created to represent the risk level: action level 0 (REBA score of 1), which indicates negligible risks; action level 1 (REBA score of 2–3), which indicates low risks; action level 2 (REBA score of 4–7), which indicates a medium level of risk, action level 3 (REBA score of 8–10), which indicates a high level of risk, and action level 4 (REBA score of 11–15), which indicates a very high level of risk.

REBA method has the advantage of evaluating different body parts at once: the upper limbs (arms, forearms, and wrists), the lower extremities, and the trunk. This method helps identify workers’ forced postures and develop improvement measures if necessary [28]. The REBA method has some advantages and limitations. i) It has a good cost-effectiveness ratio. ii) Easy to implement. While pen and paper are sufficient for data collection, computer applications can speed up/facilitate the process. iii) after assessing each body part, individual scores are used to identify the most conflicting ergonomic aspects [29]. The limitations of this method are as follows: i) cannot analyze sequences or sets of postures. ii) The researchers will determine how to evaluate the different constrained working postures. It may or may not be possible to examine some positions adopted. In addition, it only measures the intensity of the effort. The exposure duration and postures frequency throughout the working day are not considered [28].

2.5 Borg’s CR 10 scale

A Borg scale CR10 was used to measure the farmers’ perceived discomfort across different body parts, including their shoulders, hands, wrists, elbows, and lower extremities, including their low backs, hips, thighs, legs, and feet. The Borg CR10 scale [30] has been used in different studies to measure perceived discomfort subjectively. According to the Borg CR10 scale, 0 represents no discomfort, 5 represents intense discomfort, and 10 represents extreme discomfort. Many studies have confirmed the validity and reliability of the scale [31, 32].

2.6 Data analysis

The study involves a total of 472 farmers. The data were analyzed with Primer of Biostatistics (5.0.msi, MSI version = 1.20.1827.0; McGraw-Hill). The data were summarized using descriptive statistics (frequency and percentage). Multiple logistic regression models were used to assess the prevalence of MSDs in various body parts, their odds ratios (ORs), and 95% confidence intervals (CIs). P-values less than 0.05 were considered statistically significant for all statistical tests.

3.1 Sociodemographic variables and work-related details

According to Table 1, 45.1% of rice farmers, 43.6% of potato farmers, and 11.3% of groundnut farmers participated in the study. According to Table 1, 52.8 % of farmers are male, while 47.2 % are female. MSDs are prevalent in 69% of female farmers, while only 66.3% of male farmers. According to Table 1, people aged 40–49 (87.9%) are more likely to suffer from most MSDs than others. Most farmers (48.9%) work 8 hours a day, 27.3% work 9 hours a day, and 23.8% work 7 hours a day. Table 1 shows that 89.4% of farmers work with repetitive hand movements, while 8.5% report occasionally performing repetitive hand movements. According to the study, 92.6% of the farmers reported working awkwardly while farming, whereas only 4.9% reported sometimes adopting a constrained working posture. As a result of working with a constrained working posture and repetitive tasks, MSDs are more prevalent among different groups of farmers.

Table 2 provides a comparative analysis of the three groups based on the results of farmers. As a result of the study, rice farmers are most affected (80.3%) by MSDs, whereas potato and groundnut farmers have prevalence rates of 64.6% and 28.3%, respectively. In addition to BMI, education, household income, previous work experience, and MSDs, there was a significant difference between the three groups of farmers at p < 0.05.

The results of the univariate logistic regression analyses are shown in Table 3. According to the results of the logistic regression analyses, more females than males reported pain in their neck (OR = 0.51, 95% CI: 0.350–0.743, p < 0.001), shoulders (OR = 0.65, 95% CI: 0.405–1.066, p = 0.122), lower back (OR 0.181, 95% CI: 0.069–0.477), knees (OR 0.352, 95% CI: 0.280–0.598). Disruption of normal activities due to such symptoms and the severity of complaints are also presented in Table 3. The reported symptoms were mostly significant different between males and females. However, more females than males reported disruption of normal activities due to neck, shoulder, elbows, upper back, low back, and knees (p < 0.05) symptoms.

Table 4 states that there are two types of farmers in this study. Group A farmers work on their agricultural land, and Group B farmers generally work as daily wage labor. The study also found that both groups of farmers are affected among these two groups, especially in the low back, 98.7% and 87.3%, followed by 89.7% and 77.2%, respectively, shoulder 89.4% and 72.6%, respectively. The result of the study also shows that farmers works in his/her farm reported more discomfort feeling (pain) than farmers works as daily wage labour in their neck (OR = 7.293, 95% CI: 4.782 –11.123, p < 0.001), shoulders (OR = 3.174, 95% CI: 1.919–5.251, p < 0.001), lower back (OR = 11.208, 95% CI: 3.371–37.268), knees (OR = 2.455, 95% CI: 1.468–4.105).

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Fig. 1

Comparative analysis of percentage of discomfort feeling (Pain) in different body parts among different group of farmers.

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Fig. 2

Comparative study of feelings of discomfort (pain) at different times among the different groups of farmers.

Table 5 shows the ART tool’s analysis of repetitive tasks. According to the results, pain in different body parts, specifically A1, A2, and B, was represented as Arm movements, repletion, and force, respectively, and showed the highest values due to high repetitive movements of the respective body parts and in some cases due to constrained static postures. ART analysis revealed a high exposure level in rice and potato farmers, requiring urgent investigation. The exposure level of groundnut farmers is medium and requires further research.

Farmers are exposed to different ergonomic hazards due to various agricultural activities. Among all groups of farmers, repetitive extension and flexion of the elbow for more than one hour/day (64.4%) is the highest risk factor (64.4%), followed by squatting or kneeling for more than one hour/day (63.3%), moving wrists and fingers for more than four hours per day (54.9%), and working with hands above shoulder height for more than one hour/day (44.5%) (Table 6).

Table 7 presents psychosocial factors related to WMSDs among all farmer groups. Again, psychosocial factors like long working hours (90%) dominate the study results. Furthermore, monotony at work (87.5%), working despite severe pain because of fear of losing a job (83.0%), being required to finish a specific number of items/days (71.4%), and being pressured to finish the job on time (67.2%) are also critical psychosocial factors.

In REBA, the upper limbs (arm, forearm, wrist), trunk, neck, and lower extremities can be assessed together. Additionally, it distinguishes between different types of grips and muscle activities. There are five levels of risk, ranging from negligible to very high. By applying the REBA method, postural disorders of the whole body can be identified in relation to muscular action, external loads applied to the body, and grip type. Additionally, these methods are widely applied in several working contexts, primarily in agriculture [10]. As a result of the difficulty in evaluating the biomechanical overload risk in primary sector activities, REBA have been adopted a few times in the agricultural sector. Due to the wide variability of tasks the operators must perform, REBA has been adopted a few times in the agricultural sector [33].

The REBA method is used to assess the different body postures involved in different agricultural activities in rice, potato and groundnut farming. REBA method is applied to identify postural disorders of the whole body, in relation to the muscular action, to the external loads applied to the body and to the type of grip. A score is assigned to each of the following body regions: neck, shoulders, wrists, forearms, elbows, trunk, back, legs, and knees.

The analysis of posture by REBA method is outlined in Table 8. The result of the study shows that weeding, digging or spading, sowing, sprinkling water for better germination of the seeds, harvesting, and uprooting are considered as a very high risk of injury and required immediate action to be changed. Whereas, the other agricultural activities like: carrying crops, threshing, winnowing are the agricultural activities are considered as a high risk of injury and required action needs to take very soon. The ridging activity in potato and groundnut farming are medium risk level. According REBA method ridging activity requires further investigation requires and take necessary action.

In Fig. 3, some of the agricultural activities of rice farming (spading, sowing seeds, harvesting, and carrying crops), groundnut farming (sowing, weeding, and harvesting) and potato farming (spading activities) has been shown, where the farmers are working in a constrained working postures with a bending, twisting, stooping, and squatting position.

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Fig. 3

Different agricultural activities.

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Fig. 4

According to Borg’s CR 10 scale for the assessment of severity of musculoskeletal symptoms reported by farmers.

A higher percentage of female farmers rated their pain severity at CR10 than male farmers, according to Borg’s scale (figure 3). There may be a reason these female farmers have to do more work at home than male farmers. Furthermore, the study shows that the low back region of the body is most affected. On a scale of 1 to 10, female farmers rated 9.1, and male farmers rated 7.9, indicating severe pain. In addition to knees, female farmers rated 8.1 while male farmers rated 7.2, showing extreme pain.

4.1 Prevalence of MSDs

The study found that musculoskeletal disorders were prevalent among the study population (67.6%). Based on the study results, farmers diagnosed with musculoskeletal symptoms most often in the low back (OR = 0.181; 95% CI = 0.069–0.477), then knees (OR = 0.352; 95% CI = 0.280–0.598), shoulder (OR = 0.657; 95% CI = 0.405–1.066), neck (OR = 0.510; 95% CI = 0.350–0.743), ankle or foot (OR = 0.815; 95% CI = 0.556–1.196), and upper back region (OR = 0.681; 95% CI = 0.463–1.002). Other researchers have also found similar findings [34–38]. Farmers have been found to have a higher prevalence of lower back, shoulder, neck, and upper back pain and knee pain due to ergonomic risk factors. Das and Gangopadhyay [10] and Gangopadhyay et al. [14] concluded that potato farmers in India have a higher prevalence of musculoskeletal symptoms in the low back region due to constrained working posture for an extended period. According to Keawduangdee et al., the majority of low back pain (LBP) among Thai rice farmers is high (83.14%) [9]. According to the study, LBP is also significantly associated with male and female rice farmers. In addition, there was a high prevalence of knee pain among farmers. As a result of the study, knee pain was the second most prevalent pain after low back pain. These findings indicate that farmers perform several agricultural activities in a squatting posture for long periods. Farmers may suffer from knee pain because of this. A similar result was found by Dianat et al. [34] and Das et al. [38]. They also reported that knee pain plagued farmers.

4.2 Factors affecting MSDs

This study analyzes risk factors such as age, gender, BMI, duration of work, repetition of work, constrained working posture, and manual material handling (MMH), which affect MSDs among farmers.

4.3 Limitations

The present study had some limitations that should take into account. First, this study used self-reported questionnaires to collect data, which may have resulted in bias. A second limitation of the study is that it was cross-sectional, so causal draw causal conclusions from it. A direct measurement technique (such as electrogoniometry or inclinometry) may be necessary to confirm the findings of the present study based on the REBA technique. Muscle fatigue was not assessed through the EMG study in this study. Furthermore, the hand grip strength of the farmers is not assessed in this study. Lastly, this study does not provide injury data, which is considered a major limitation.

4.4 Recommendations for future research

Future research needs identified are as follows: i. Studies should be undertaken that look at modifications of agricultural hand tools such that the forward bending posture and different awkward postures can be modified to reduce musculoskeletal pain. ii. Future research regarding accident and injury analysis is required to assure the health and safety among the Indian farmers.

4.5 Prevention and ergonomics intervention

According to the present study, prevention is essential in the agricultural field to reduce MSDs among different farmer groups.

Using modified and properly designed hand tools may prevent farmers’ injuries and musculoskeletal disorders. Handling tools are more accessible and safer with grips. Tool grips should be shaped correctly and have adequate friction.