Musculoskeletal Disorders among Agricultural Workers in Rural Communities of Loja, Ecuador

1. Introduction

This study was conducted in Ecuador, a country located in the northwestern region of South America. According to data collected by the National Institute of Statistics and Census (INEC), it has a population of approximately 18,249,223 people [1]. In this country, agriculture plays a significant role in the country’s economy, representing around 8% of the Gross Domestic Product (GDP) and providing substantial employment opportunities, particularly in rural communities such as those found in Loja [2]. This city situated in the southern part of the Andean region, has a total population of 485,421 inhabitants, according to the 2022 Population and Housing Census by the INEC [3]. Many of these residents are dedicated to agricultural work, primarily cultivating corn, coffee, rice, and cassava, among other crops [4,5]. The main work activities include planting, harvesting, irrigation, crop maintenance, weeding, and product transportation [6].

According to the WHO, approximately 1.71 billion people suffer from MSDs, making it the most common occupational disease worldwide [7,8]. Similarly, the International Labour Organization (ILO) states that among occupational illnesses, ergonomic-related disorders are the most prevalent [9]. Studies conducted among workers have reported a prevalence of musculoskeletal symptoms of up to 88.9%, indicating that these conditions are highly common, especially among farmers [10]. Research conducted in Thailand revealed that this group of workers exhibited a higher prevalence of MSDs (67.8%; 95% CI: 66.3–69.3) compared to other occupational populations [11].

The development of MSDs in farmers is closely related to the type of work and physical exposure involved. Farmers often perform repetitive activities over prolonged periods, adopting forced and awkward postures [12,13]. These factors cause physical fatigue and pain in several body regions, including the neck, shoulders, elbows, wrists/hands, lower back, trunk, legs/ankles, and feet [14]. For instance, a study assessing MSD prevalence among pistachio harvesters using the NMQ reported that many workers experienced at least one type of MSD, with 63.7% in the shoulders, 63% in the lower back, and 52.1% in the wrists/hands [15].

Agricultural workers are thus exposed to multiple work-related physical risks, one of which is the occurrence of MSDs [16]. Moreover, the onset of these disorders has been related to sociodemographic factors such as gender, age, and body composition [17]. A study found that the prevalence of knee-related MSDs reached 54.04% among male workers over 60 years old, some of whom were overweight, which influenced this result [18]. These findings support that MSDs are associated with sociodemographic characteristics, as prevalence tends to increase with age due to prolonged occupational exposure and age-related degenerative changes [19].

Given the occupational conditions and sociodemographic characteristics of farmers, it is essential to examine the prevalence of MSDs in this population and their relationship with these factors. MSDs can become a critical occupational health problem among farmers due to repetitive movements, heavy lifting, intense manual labor, and forced working postures [20], compounded by the influence of personal and occupational aspects such as job position and working hours [21,22]. As there is a lack of sufficient scientific evidence regarding this issue in the Ecuadorian agricultural workers, the present study aims to determine the prevalence of MSDs and their relationship with sociodemographic and occupational factors among farmers in rural communities of Loja, Ecuador.

2. Materials and Methods

2.1. Study Design

A quantitative, descriptive, and field-based investigation was conducted using a cross-sectional design to determine the relationship between sociodemographic or occupational factors and the presence of MSDs in agricultural communities in Loja. This research was developed as part of the project titled Relationship between Musculoskeletal Disorders and Occupational Activity in the Communities of Loja [5], from which the study data were collected.

2.2. Sample Size

The study sample consisted of 103 farmers from the communities of Changaimina, Cruz de Yazapa, Lucero, Naranjillo, Tablón, Bellamaría, and Cariamanga in the province of Loja. A non-probabilistic, intentional sampling method was chosen to select participants who met the specific characteristics of the research.

Inclusion criteria comprised adult individuals aged 30 to 60 years residing in the agricultural communities of Loja and working as farmers. Exclusion criteria included the presence of any physical or mental disability and a medical history of severe injuries or congenital pathology, or its equivalent.

2.3. Data Collection Process

Data collection was carried out in person with the study participants through field visits to their homes, where they were invited to participate. Each participant was individually evaluated using the study instrument NMQ. Once the data was collected, it was securely stored in the office of the principal investigator.

2.4. Data Analysis

Data were analyzed using IBM SPSS Statistics software. Descriptive statistics, including frequency, percentage, mean, and standard deviation, were used to describe the participants and the prevalence of MSDs. The 95% confidence intervals were calculated for the most affected body regions. To determine the factors associated with MSDs, multivariate logistic regression analyses were performed, including gender, age, BMI, weekly working hours, and family income as risk factors. Adjusted odds ratios (aOR) with 95% confidence intervals were obtained, and p < 0.05 was considered statistically significant [23].

2.5. Instrument

The NMQ was used for data collection. This instrument aims to detect initial symptoms of MSDs in workers exposed to physical demands [24]. Previous studies assessing its reliability and validity have reported a Cronbach’s alpha of 0.863, indicating good reliability and high validity [25].

This instrument contains 27 multiple-choice questions divided into two sections: a general part and the specific part [26,27]. The general section asks about musculoskeletal symptoms experienced within the last 12 months or 7 days across 9 body parts (neck, shoulders, elbows, wrists/hands, upper back, lower back, hips/thighs, knees, and ankles/feet). The specific section asks about symptoms in 3 body parts (neck, shoulders, and lower back) within the last 12 months or 7 days and whether these discomforts interfered with their daily or occupational activities [27].

2.6. Ethical Considerations

The research adhered to the ethical principles protecting the rights, privacy, and confidentiality of the participants. The principle of voluntary participation and the right to withdraw from studying at any time were established. The study received approval from the Research Ethics Committee for Human Beings (CEISH) of the Pontifical Catholic University of Ecuador (PUCE) under code CEISH-461-2023.

2.7. Use of Artificial Intelligence Tools:

The authors used artificial intelligence (AI) tools (ChatGPT, OpenAI) to support the translation of the manuscript and to improve grammatical clarity.

3. Results

3.1. Sociodemographic and Occupational Characteristics

A total of 103 farmers participated in the present study. Table 1 shows that the sample had a similar distribution by gender, with 51 men (49.5%) and 52 women (50.5%), demonstrating a balanced representation of male and female agricultural workers in these communities. The mean age was 46 years (σ = 9.767), indicating that the majority of workers are middle-aged adults.

Nutritional status was assessed using the Body Mass Index (BMI), categorized according to the WHO criteria: underweight (< 18.5 kg/m²), normal weight (18.5-24.9 kg/m²), overweight (25-29.9 kg/m²), and obesity (≥ 30 kg/m²). Table 1 indicates that most workers had normal weight (n = 66, 64.1%). Additionally, 17 participants (16.6%) were classified as underweight, while a smaller proportion fell into the overweight. No participants were classified as obese, and BMI data were missing for 3 participants.

Regarding occupational conditions, several key variables were analyzed to establish a relationship with the onset of musculoskeletal symptoms. Concerning the job position, Table 2 indicates that the majority of participants performed tasks while standing (n = 82, 79.6%), while a smaller number worked seated (n = 6, 5.8%), bent over (n = 13, 11.7%), and only a few involved lifting weights (n = 3, 2.9%), reflecting the high physical demands of their labor. Furthermore, most participants reported a weekly working time of over 40 hours (n = 43, 41.7%). In terms of household income, the majority earned 0–100 USD per month (n = 43, 41.7%), which may limit access to healthcare and negatively impact worker health.

3.2. Prevalence of Musculoskeletal Disorders

Table 3 shows the results obtained through the NMQ. More than half of the participants reported musculoskeletal symptoms in at least one body region in the last 12 months, with the highest prevalence in the lower back (78.6%; 95% CI 69.8–85.5), neck (58.3%; 48.6-67.3), and knees (64.1%; 54.5-72.7). In contrast, the least affected regions were the left wrist/hand (n = 34, 33.0%) and left elbow (n = 28, 27.2%).

3.3. Factors Associated with Musculoskeletal Disorder Prevalence

Logistic regression models adjusted for gender, age, BMI, weekly working hours, and family income. Table 4 revealed that having a high BMI was significantly associated with lower back pain (aOR = 15.01; 95% CI 1.06-212.24; p = 0.045), and a marginally significant association was observed between neck pain and having a BMI in the overweight category (aOR = 6.33; 95% CI 0.99-40.46; p = 0.05). No statistically significant associations were observed between musculoskeletal disorders and the other variables like gender, age, weekly working hours, or family income in any of the three body regions most affected.

4. Discussion

In line with the ILO, MSDs are among the most relevant problems in occupational health, as most of these disorders are work-related [28]. These disorders cause impairments in an individual’s movement function and may arise from excessive mechanical strain on biological structures. Furthermore, evidence suggests that organizational psychosocial factors also contribute to MSD development, making them one of the leading causes of productivity loss and economic burden worldwide [29].

Regarding agricultural work in rural and urban areas of Loja Province, agricultural activities are predominantly carried out by men, consistent with findings from a study conducted in the canton of Catamayo [2], where 93% of farming households were headed by males. In the present study, males and females were equally represented, indicating no significant gender imbalance in agricultural participation.

Agricultural workers often engage in long working hours that exceed 40 hours per week, increasing the risk of musculoskeletal injury. In contrast, a study conducted in Tulcán, Ecuador, reported that 49.5% of workers worked 32 hours per week, while 29.5% reached 40 hours [30]. In contrast, in the present research, only 5.8% of participants reported working between 21 and 30 hours per week.

Furthermore, studies on coffee harvesters found that most workers remain standing for extended periods during their work activities. Other research indicates that farmers tend to adopt prolonged sitting postures, increasing the risk of knee and joint disorders. In planting tasks, workers often kneel on one or both knees for extended periods [30,31,32]. Although this study did not directly assess working postures, these previous findings help contextualize the high prevalence of musculoskeletal pain observed among participants that are commonly affected by awkward postures in agricultural labor.

Similar studies that applied the NMQ among agricultural populations have consistently found that lower back pain is the most prevalent MSD, followed by knee and neck pain [5,31,33]. This investigation reflected similar results, as the prevalence of lower back pain accounted for 78.6% of the sample, followed by the knee region at 64.1%. These outcomes may be attributed to factors such as sustained and awkward postures, whole-body vibrations, work frequency, and task difficulty, in addition to demographic and lifestyle variables such as age, height, BMI, smoking, and psychosocial stressors [34].

Cervical pain ranked third in prevalence (58.3%), affecting more than half of the participants. Other studies have reported lower neck pain prevalence rates (7.4% and 47.2%), which may be explained by differences in workplace settings and daily working hours, ranging between 9 and 12 hours per day [35,36]. In the current study, a marginal association was observed between neck pain and having a BMI in the overweight category. This finding may indicate that even moderate increases in body mass can influence cervical loading and muscular strain during our static agricultural tasks.

Among female tobacco farmers, a study revealed that cervical pain was more prevalent with a ratio of 1.7 compared to a population under 40 years old. This may be related to the length of time spent in labor activity at an intense or accelerated pace and exposure to other environmental factors [36]. The present study also found a high prevalence of cervical pain, although the association with gender was not statistically significant.

In contrast, the multivariate analysis revealed a statistically significant association between lower back pain and having a high BMI. This supports previous research linking overweight and obesity to lumbar disorders due to increased mechanical stress on the spinal structures and degenerative musculoskeletal changes [5,37,38]. These findings underscore the importance of controlling body weight among agricultural workers [39,40].

It is relevant to note that the main limitation of this study is its cross-sectional design, which does not allow for temporal follow-up of sociodemographic and occupational factors related to MSD occurrence. Future research should consider longitudinal or cohort designs. Likewise, the sample size may limit the generalization of the results to other agricultural contexts in Ecuador. Nonetheless, these limitations do not diminish the relevance of the findings, as the analysis identified significant associations that constitute a substantial contribution to understanding the problem and guiding future interventions within this population.

The study findings offer important practical implications for occupational health, ergonomics, and physiotherapy within agricultural communities. The high prevalence of lumbar, cervical, and knee pain highlights the urgent need to implement preventive strategies tailored to the agricultural work context. Furthermore, the results emphasize the importance of addressing the specific needs of female agricultural workers to develop interventions that consider their unique occupational conditions. For future research, it is suggested to develop studies with larger samples to allow for greater representativeness of the farmers, in addition to combining the use of self-reported questionnaires with clinical, biomechanical, and field evaluations to enrich the understanding of the different factors involved in MSDs.

5. Conclusions

In conclusion, the findings of this study revealed a high prevalence of MSDs in farmers, mainly affecting the lower back, neck, and knees. Also, the results of this study indicate a high prevalence of MSDs in farmers, mainly in the lower back, neck, and knees, with statistically significant associations observed between lumbar pain and having a high BMI, and a marginally significant association was observed between neck pain and having a BMI in the overweight category. These findings underscore the importance of implementing preventive measures through ergonomic strategies and health education, aiming to improve the quality of life of agricultural workers and reduce the incidence of musculoskeletal disorders. It is recommended that future research be conducted on a broader population to allow for a more detailed exploration of related risk factors, thereby strengthening scientific evidence on occupational health in rural contexts.