BackgroundStanding Sewing Machine Operators (SSMOs) are engaged in highly repetitive operations, and work while standing during their entire working hours. This leads to discomforts and Musculoskeletal Disorders (MSDs). However, there is a dearth of research in SSMOs’ working conditions.Objective: Aim of the study is to evaluate the prevalence of MSDs and related ergonomic risk factors among SSMOs in the Sri Lankan textile industry.Methods: The sample included 552 female sewing machine operators. Data were collected through self-reported questionnaires which included demographic, job-related factors and Cornell Musculoskeletal Discomfort Questionnaire [CMDQ], along with the application of validated ergonomic tools (Rapid Entire Body Assessment [REBA] and Strain Index [SI]) to assess the ergonomic risks amongst them. The inter-rater reliability test ensured the reliability among observers. An individual regression model was developed for each body parts to assess the associated risk factors.Results: The highest occurrence of musculoskeletal symptoms were in knee, foot, thigh, lower leg and lower back of SSMOs. REBA grand score (4–11) indicated that workers’ postures were at medium, high and very high risk levels necessitating evaluation to change. Moreover, SI indicated medium and high risk of upper extremity disorders. Finally, regression models revealed associated risk factors with musculoskeletal symptoms among various body parts including age, Body Mass Index (BMI), marital status, SSMO experience, job satisfaction, job stress, daily walking distance to the boarding place/factory, interest in job rotation and satisfaction with the design of sewing machine.Conclusion: The findings highlighted that the prevalence of discomfort and MSDs in the lower limbs were higher than in the upper limbs among SSMOs. The findings revealed the working conditions of SSMO and emphasised the need for ergonomic interventions to minimise the MSDs among them. Relevance to industryThe findings highlighted ergonomic risks among SSMOs and associated risk factors which will help managers and researchers better understand the working conditions of SSMOs. The identified risk factors could be considered during the implementation of standing sewing operation layouts and during the selection and allocation of new employees.
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