Organizational Risks Factors and Work-Related Musculoskeletal Disorders among Youth Welders in Informal Metalworking Setting

Organizational Risks Factors and Work-Related Musculoskeletal Disorders among Youth Welders in Informal Metalworking Setting | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Organizational Risks Factors and Work-Related Musculoskeletal Disorders among Youth Welders in Informal Metalworking Setting Mathew Kiplagat, Atupele Mulaga, Kondwani Chidziwisano, Save Kumwenda This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8183954/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Welding, within the metalworking industry is physically demanding job, commonly found in the informal sectors where there is limited occupational health and safety services. Young workers in these setups face greater risk of WMSDs because they are highly exposed to occupational risks factors. This study assessed organisational risk factors specifically; use of personal protective equipment (PPEs), safety training attendance and rest break and their influence on WMSD prevalence among youth welders aged 18–35years in Eldoret Town. Methods A cross-sectional descriptive study was conducted where 220 welders were sampled using a stratified and simple random sampling techniques in informal ‘Jua Kali’ workshops. Data were collected using a structured questionnaire with a Nordic Musculoskeletal Questionnaire (NMQ). Descriptive statistics, chi-square tests and binary logistic regression analyses at 95% confidence interval and significance level (p < 0.05) were performed with help of IBM SPSS. Results Of the 193 (87.7%) participants, 85% reported that they had experienced at least one WMSD within past one year. The lower back (83.9), upper back (80.8), hands/wrists (78.8) and knees (78.2) were mostly affected. Use of PPEs (p < 0.001, χ 2 = 41.242) and rest breaks (p < 0.001, χ 2 = 22.077) showed a significant association with overall WMSD prevalence and significantly reduced pain in different parts. Frequent use of PPE lowered MSD pain in the shoulders (OR = 0.240: 95% CI 0.056, 1.020), and hands/wrists (OR = 0.813: 95% CI 0.151, 4.373), while consistent use of PPEs significantly lowered pain in the elbows (OR = 0.103: 95% CI 0.013, 0.826). Rest breaks lowered the risk of pain in the neck (OR = 0.307:95% CI 0.147, 0.642), shoulders (OR = 0.410: 95% CI 0.207, 0.810), upper back (OR = 0.445: 95% CI 0.147, 0.642), and lower back (OR = 0.138: 95% CI 0.050, 0.382). Conclusion The current study exposed high prevalence of WMSD in youth welders and highlights the protective value of both the use of PPE and formal safety training and rest breaks. It recommends comprehensive and compulsory safety training programs, provision of appropriate and subsidised PPEs, structured rest breaks and a strengthened regulatory framework. Work-related musculoskeletal disorders Youth welders Informal sector Welding Occupational health and safety Figures Figure 1 Figure 2 Figure 3 Highlights • 85% WMSD overall prevalence reported among youth welders • The most affected areas are the lower back, upper back, hands/wrists and knees • Use of PPEs and rest breaks are the key organisational risk factors • Mandatory safety training, subsidised PPEs and rest breaks, and increased enforcement are suggested to reduce occurrence of WMSD 1. Introduction Like other metalwork tasks, welding involves physically demanding tasks, which requires the repetitive use of hand tools, manual lifting, and repeated handling of heavy metallic materials during the working [ 1 – 3 ]. Most of these working activities are done under poor postures and in confined areas. Despite the constraints, welding is key in infrastructure development as it supports major sectors in the economy including the automotive, construction and manufacturing industries [ 4 ]. In addition, it provides employment opportunities to many individuals especially the youths who lack formal employment [ 5 ]. In developing countries, most welding enterprises are carried out in the informal sectors, where regulatory policies are weak [ 6 ], formal registration is lacking, and where limited oversight on occupational health and safety (OHS) practices exist. Several studies in low-and-middle income countries (LMC), have reported that informal welders in this sector have insufficient organisational measures including inadequate access and use of personal protective equipment (PPEs), lack of job rotations, and rest time [ 7 – 10 ]. This scenario can be explained by the resource limitation and the poor institutional enforcement typical in the informal or small-scale industries [ 2 ]. In Africa, more than 80% of informal welding enterprises are not controlled by regulations and are poorly organised [ 5 ]. Studies conducted in Zimbabwe [ 11 ], Tanzania [ 12 ], South Africa [ 5 ] and Kenya [ 13 ] have all revealed that these workshops operate in impoverished environments, lack modernised equipment, and largely depend on manual labour with minimal to no occupational health services, thus rendering the welders disproportionately vulnerable to work-related injuries and other related illnesses. Work-related musculoskeletal disorders (WMSDs) in particular present a major occupational health problem among persons who deal with physically demanding work like welding and are more often associated with body ache and work-related fatigue. These conditions impair the muscles, nerves, tendons, joints, and spinal discs, causing pain, reduced mobility, job absenteeism, lower productivity, and long-term disability in extreme situations [ 14 – 16 ]. The body regions mostly impacted include the lower back, shoulders, wrists, neck, and knees, often due to the repetitiveness of the work, awkward postures and aggressive actions involved [ 11 ]. There is however no consolidated global data on prevalence of WMSDs in informal sector welders; but as per the country-level studies, the burden has always been high particularly in the LMC. For instance, studies conducted on informal welders in Bangladesh [ 17 ], Nigeria [ 18 ], and Ethiopia [ 19 ] found annual prevalence rates of 85%, 86.4% and 54% respectively with the lower back, shoulder, knee and wrist/hands being the commonly affected body parts. This demonstrates that WMSDs continues to be a major and prevalent occupational health issue in the informal welding industries. Organisational risk factors associated with WMSDs, such as task design, safety practices, and rest–work schedules, particularly in informal welding firms, remains limited. This issue is critical in Sub-Saharan Africa where informal sectors are the pillars of most economies, and having the majority (over 80%) of the workforce as youths [ 5 ]. These workers mostly do not have adequate PPEs, never undergo proper safety training, and have no timetabled rest breaks in such informal workplaces [ 20 ]. Moreover, these organisational weaknesses that have been identified to contribute to WMSDs but are scarcely studied. In Kenya, where a large proportion of the youthful population is concentrated in informal metalwork sector [ 21 ], these organisational gaps are even more pronounced, with limited regulation, weak enforcement of occupational health policies, and scarce empirical evidence on how such conditions contribute to the burden of WMSDs. Thus, this study attempts to fill this gap by analysing the organisational aspect of occupational health risks among informal sector welders in Kenya. 2. Materials and Methods 2.1 Study area This research was done in Eldoret City, Uasin Gishu County, Kenya (Fig. 1) which is approximately 310 km northwest of Nairobi. Eldoret is in the equator at an altitude of 2,100-2,300m with a tropical highland climate, having average rainfall of 1500 mm/year [22] Chelule et al, 2024). Eldoret has a population of 475,716 according to the Kenya National Bureau of statistics (2019) [23] and has officially been declared the fifth city in Kenya in 2024, due to its population increase and economic values in the region. The city is largely known for maize and wheat production, dairy production and agro-processing industries including textiles and flour milling [24]. Similarly, there is plenty of informal sector activities such as metalworking (welding and fabrication), carpentry, tailoring, and minor trade exist [25]. The dominance of informal metalworking industries in Eldoret renders it as an example to study the occupational health risk of urban informal economies in most Sub-Saharan Africa countries. 2.2 Study Design, Population, Sample size and Sampling This study adopted descriptive-explanatory (analytical cross-sectional) design, which provide the description of the occupational health outcomes and analysis of the relationships between the risk factors and the health conditions. Male and female welders who work in the metalworking businesses of the Jua Kali (informal sector) were part of the study population, a group that is very densely distributed throughout the industrial and residential estates of Eldoret. The Ministry of Labour (North Rift Chapter) estimated that there are 400 youth welders in the city. According to national statistics, the largest segment of the youth labor force in Kenya work in the informal sector where about 63% of workers in Kenya are under the age of 35 years [26]. This population trend highlights the need of research on young informal workers, who are subject to occupational risks and who have poor reach to social benefits, education, standards and regulations. Young welders represent an ideal study group to evaluate the occupational health risks since they are prone to musculoskeletal disorders, inadequately use protective strategies, and also experience extended durations of exposure to the dangerous work tasks on daily basis [25]. The sample size was determined by using Yamane’s formula [27] for finite populations [24]: Where: n = Sample size N = Total population of youth welders in Eldoret Town (estimated at 400 based on The Ministry of Labour, North Rift Chapter, estimates that there are 400 youth welders in the region.) e = Desired level of precision (0.05 for 95% confidence level) Applying the formula: Considering the non-response error, an additional 10% was added, final sample size became 220 participants. The study employed stratified sampling method where town was categorized into distinct zones, such as Langas, Kimumu, and Huruma, which are wards within Eldoret town in Uasin-Gishu County and known for having high concentration of welders. All informal welding workshops were listed from a walk through over these zones. The population of welders in each of the zones was determined, and a simple random sampling was employed to get proportionate sample participants. The local administration helped in process of locating the informal workshops and participants for this study. 2.3 Inclusion and Exclusion Criteria The participants in the study were welders aged 18 to 35 years, had at least one year of welding experience, and working in an informal (“Jua Kali ” ) setting in study area. Youth welders who had history of musculoskeletal injuries outside the workplace were excluded from the study. 2.4 Research Instrument, Reliability and Validity 2.4.1 Research Instrument Nordic Musculoskeletal Questionnaire (NMQ) for assessing the 12-month prevalence and distribution of MSDs pain or discomfort in nine major body regions [28] was modified and supplemented with a closed-ended structured questionnaire consisting of two additional sections: sociodemographic characteristics and organizational/work-related factors. The sociodemographic section captured information on participants’ gender, age, educational level, welding experience, employment status, working hours and workspace adequacy. The organizational factors gathered information on availability and duration of work breaks, use of personal protective equipment (PPE), occupational health and safety training, and presence of workplace safety policies. Research instrument attached as Supplementary File 1. 2.4.2 Reliability and Validity The study used the test-retest reliability, where the research instrument was given to a group of participants two times at a semi-monthly interval between administrations. This enabled the researcher to ascertain the ability of the instrument to generate consistent responses. Content validity was performed where experts including occupational health experts were consulted to review if the instrument is valid and reasonable in measuring the variables. The main areas which were assessed included whether the content of the tools were adequate in their measurement of the risk factors and musculoskeletal disorders. In addition, a pilot study was also used examine the face validity and 20 participants (10% of the primary sample) from a similar setting in the neighbouring towns of Nakuru were involved. 2.5 Data Collection Procedure The questionnaire was self-administered and the respondents were allowed 30 to 45 minutes to interact with the instrument. The drop-and-pick strategy was used where the questionnaires were distributed among the participants in their workplaces and were collected afterwards to avoid disturbance of the working processes. The study objectives, procedures and confidentiality assurances were explained to the respondents both verbally and in writing before they were given a chance to participate. Informed consent was obtained through writing with the individuals who consented to take part in it. It was all voluntary and people who refused were excused with respect. In order to minimize the chances of non-response bias, any non-responder was instantly replaced. 2.6 Data Analysis Sociodemographic characteristics and the prevalence of WMSDs were summarised using descriptive statistics which included frequencies and percentages. Bivariate analysis using Chi-square tests were performed to determine the unadjusted associations between specific organisational factors with the presence of WMSDs and binary logistic regression analysis assessed the independent influence of the risk factors. The results were interpreted at a significance level of 0.05 and 95% Confidence Interval (CI). 3. Results 3.1 Questionnaire Response Rate For this study, a total of 220 youth welders were selected to take part in the study. Thus, a total of 220 questionnaires were issued to the selected participants. The duly filled and returned questionnaires were 193, which represent a response rate of 87.7%. The overall response rate was suitable for data analysis and reporting. 3.2 Socio-Demographic Characteristics of the Respondents Table 1 summarises the sociodemographic characteristics of the youth welders in Eldoret Town. The majority (97.9%) of the welders were male, nearly half (42%) were aged 29 to 35 years and most of them (80.4%) had secondary education or below. Employment status indicated that only 9.3% only business owners and the majority were employed without formal contracts. Nearly three quarter (71%) had less than 5 years of welding experience. Working hours varied with welders working less than 6 hrs per day being 20.7%, and those working more than 8 hrs per day being 48.6%. Table 1 Socio-demographic characteristics of the youth welders in Eldoret Town Socio-demographic variable n (%) Gender Male 189 (97.9) Female 4 (2.1) Age (years) 18–23 58 (30.1) 24–28 54 (28.0) 29–35 81 (42.0) Education Primary education 75 (38.9) Secondary education 80 (41.5) Technical-Vocational training 38 (19.7) Employment Status Business owner 18 (9.3) Fully employed 58 (30.1) Partially employed 78 (40.4) Casual/Temporary 39 (20.2) Experience (Years) Less than 2 39 (20.2) 3 to 5 98 (50.8) More than 6 56 (29.0) Working Hours Less than 6 40 (20.7) 6 to 8 65 (33.7) 8 to 12 62 (32.1) More than 12 20 (13.5) 3.3 Prevalence of WMSD among Youth Welders in Eldoret Town Figure 2 indicated that Frequency of WMSDs among young welders in Eldoret Town was very high with majority of respondents stating that they had at least one WMSD in the last 12 months. The most impacted parts of the body were lower back (83.9%), upper back (80.8%), hands/wrists (78.8%), and knees (78.2%). 3.4 Organizational Risk Factors Influencing WMSD among Youth Welders in Eldoret Town 3.4.1 Organizational Risk Factors Figure 3 shows the occurrences (in percent) of the organisational risk factors among welders in the study area. 49.7% of welders occasionally used PPEs, the majority (59.1%) had previously never attended safety training, and over half (53.9%) did not taking rest breaks during working hours. 3.4.2 Relationship between Organizational Factors and WMSDs Table 3 presents results of bivariate analysis between organisational factors and overall WMSDs prevalence among welders in the study area. The highest MSD prevalence (96.9%) was reported among welders who occasionally use PPEs, and lowest (25%) reported among those who always use PPEs. In addition, the use of PPEs was significantly (p-Value < 0.001, χ 2 = 41.242) associated with overall WMSD prevalence. The prevalence remained high regardless of whether welders previously attended safety training or not. However, no significant association was found between attendance of training and overall WMSD prevalence. For rest breaks, welders who did not take rest breaks had a higher prevalence of WMSD (96.2%) compared to those who were taking rest breaks during working hours (71.9%). There was also a significant association (p-value < 0.001, χ 2 = 22.077) found between rest breaks and overall WMSD prevalence. Table 3 Relationship between Organizational Risk Factors and Overall WMSD Prevalence Risk factor Overall WMSD Prevalence Chi-Sq (χ²) p -Value Use of PPEs n (%) Never 11 (84.6) 41.242 < 0.001 Rarely 25 (86.2) Occasionally 93 (96.9) Frequently 33 (70.2) Always 2 (25) Attended Training Yes 95 (83.3) 0.587 0.443 No 69 (87.3) Rest Breaks (Excluding lunch breaks) Yes 64 (71.9) 22.077 < 0.001 No 100 (96.2) Table 4 shows the association between organisational risk factors and MSDs in different body parts over the last 12 months. Among welders that never used PPEs, the MSD prevalence remained high in all body parts, except the thighs (76.9% − 92.3%). A similar trend was observed among those who occasionally used PPEs (76.0% − 93.8%). Welders who always used PPEs had the lowest prevalence at any of the body parts ( ≤ 50%). Statistical analysis further demonstrated that there was a significant association between the use of PPE and MSDs in the neck (p < 0.001, χ 2 = 19.032), shoulders (p < 0.001, χ 2 = 22,523), upper back (p < 0.001, χ 2 = 18.992), elbows (p = 0.002, χ 2 = 17.517), hands/ wrists (p = 0.009, χ 2 = 1.061) and lower back (p < 0.001, χ 2 = 24.925). A little variation was observed in training attendance and WMSD prevalence. The WMSD prevalence among welders without previous training ranged 72.8% to 84.2% and 74.7% to 83.5% among those who had attended training in the neck, upper back, elbows, hands/wrists, lower back, knees and feet, respectively. There was also no significant relationships between attending training and the prevalence of MSD in any of the body parts. In terms of rest breaks, welders who took rest breaks during working hours reported a high prevalence of WMSD in the upper back, hands/wrist, knees and feet (71.9% to 78.8%), while those not taking breaks had high prevalence of WMSD in all the body parts except in the thighs (75.0% to 94.2%). Further, Rest breaks were significantly associated with MSDs in the neck (p = 0.002, χ 2 = 9.735), shoulders (p = 0.022, χ 2 = 5.250), upper back (p = 0.029, χ 2 = 4.744), hands/wrists (p = 0.001, χ 2 = 0.974) and lower back (p < 0.001, χ 2 = 17.722). Table 4 Relationship between Organizational Risk factors and MSD in Different Body Parts MSD prevalence (%) in the different body parts in the past 12 months Variable Neck Shoulders Upper-Back Elbow Hand/Wrists Lower Back Thighs Knees Feet Use of PPEs Never 76.9 76.9 92.3 76.9 84.6 76.9 61.5 84.6 92.3 Rarely 62.1 55.2 89.7 75.9 75.9 86.2 41.4 69.0 69.0 Occasionally 87.5 82.3 87.9 84.4 76.0 93.8 53.1 83.3 83.3 Frequently 55.3 55.3 63.8 66.0 80.9 72.3 44.7 72.3 74.5 Always 50.0 46.8 50.0 25.0 50.0 37.5 25.0 50.0 50.0 χ² 19.032 22.523 18.992 17.517 1.061 24.925 4.335 6.794 8.579 p -Value < 0.001 < 0.001 < 0.001 0.002 0.009 < 0.001 0.363 0.147 0.073 Attended Training Yes 72.8 69.3 80.7 72.8 81.6 84.2 46.5 78.1 80.7 No 77.2 65.8 81.0 79.7 74.7 83.5 51.9 74.7 74.7 χ² 0.479 0.258 0.003 1.220 1.326 0.015 0.546 0.299 0.993 p -Value 0.489 0.611 0.957 0.269 0.249 0.901 0.460 0.584 0.319 Rest Breaks Yes 64.0 59.6 74.2 69.7 78.8 71.9 50.6 71.9 76.4 No 83.7 75.0 86.5 80.8 78.7 94.2 47.1 80.8 79.8 χ² 9.735 5.250 4.744 3.211 0.974 17.722 0.228 2.105 0.326 p -Value 0.002 0.022 0.029 0.073 0.001 < 0.001 0.633 0.147 0.568 Table 5 shows the binary logistic regression analysis between organisational risk factors and the prevalence in WMSD in different body parts. Frequent use of PPEs showed a negative significant association with pain in shoulders (OR = 0.240, 95% CI 0.056–1.020), and hands/wrists (OR = 0.813, 95% CI 0.151–4.373) while the use of PPEs consistently or always was as well negatively associated with pain in the elbows (OR = 0.103, 95% CI 0.013–0.826). Negative significant association was also found between adoption of rest breaks and pain in the neck (OR = 0.307, 95% CI 0.147–0.642), shoulders (OR = 0.410, 95% CI 0.207–0.810), upper back (OR = 0.445, 95% CI 0.147–0.642) and lower back (OR = 0.138, 95% CI 0.050–0.382). Table 5 attached as Additional file 1. 4. Discussion The current study showed that the prevalence of WMSD among the youth welders population was high (85%), which may be explained by the physically intense nature of welding activities. More specifically, continuous static postures (prolonged trunk, neck, and shoulder flexions or out-of-position welds), sustained repetitive hand movements (cutting, hammering), and the manual handling of heavy metal items, and other pieces of equipment that impose intense cumulative loads on musculoskeletal system especially on the spine, upper limbs, and knees [ 3 , 29 , 30 ]. Additional impacts emanates from the tool related vibrations (due to the use of grinders), and less accessibility to modern lifting tools. The occurrence of high rates of WMSDs among youth welders who work in the informal welders sector concurs with other studies for instance, similar patterns were observed in Kenya’s cohorts in age neutral studies in Nakuru [ 13 ] and Nairobi [ 31 ], as well as in Nigeria [ 32 ] and Bangladesh [ 17 ] where prevalence of over 70% were reported. In the present study, prevalence of WMSD varied in different body parts. The prevalence of WMSD was highest in lower back, upper back, hands/wrists and knees (> 70%) and lowest in shoulders, thighs and feet (< 70%). During the informal welding, many tasks are performed in confined areas, which encourage long-term trunk flexion/twisting. Firstly, the load on the static spine is rapidly accumulated due to short or lack rest periods, often repetitive and not diverse, hence difficult to alternate [ 33 ]. Secondly, welders hold welding torches and hand tools (grinders, drills, hammers) repeatedly and with force, causing vibrations, and increasing the risk of pain particularly in the wrist /hand and forearm [ 1 ]. Thirdly, welding operations are most frequently performed by kneeling/squatting, which increases welders contact forces and load stress, hence resulting to knee pain [ 3 ]. By contrast, the percentage of shoulder pain in this study was low, due to limited work bench activities. Further, the younger and physically fit youth welders were more capable of sustaining the standing hours or other strains, which may be the reason for lesser ankles/feet complaints. The results of the present study are consistent with the earlier literature. For instance, according to Chatterjee and Sahu, in India, lower back and neck were found to be the most affected, and attributed to the repetitive bending, heavy lifting, and sitting with maladaptive postures [ 34 ]. Similarly, among informal Zimbabwean welders, 78% of them reported lower-back pain, 66% reported right-shoulder pain, and more than 60% complained of wrist pain, among the others [ 11 ]. On the other hand, Cameroonian metal workers reported pains in the upper back at 65% and lower back at 62.5% [ 35 ]. The current study also concurs with a another study Portuguese welders who reported higher WMSDs in the lower back, upper back, and wrists/hands thus demonstrating a specificity in the spinal areas and upper-limb [ 36 ]. Lastly, in an occupational analysis of German welders, MSD prevalence in the lower back was reported at 71%, neck pain at 61% and shoulder pain at 55% within the past 12 months, and again it confirmed that the spine and distal upper limb were more vulnerable during welding [ 16 ]. The results of occurrences of organizational risk factors showed that PPEs were used occasionally by 49.7% of welders, 59.1% never attended safety training and rest breaks were infrequent (53.9%) among the welders. The main factors behind the non-use or irregular use of PPEs among informal workers include non-awareness of the occupational hazards, economic barrier to purchase PPEs and the uncomfortable feeling in wearing of these safety equipment [ 37 , 38 ]. Studies conducted in Kenya and Nigeria indicated that despite the fair knowledge of the welding related hazards and importance of use of PPEs, the adoption of these safety measures is still minimal [ 39 , 40 ]. In Nepal, Maharja et al. [ 41 ] found that less than 40% of Nepalese welders wore PPEs and some substituted welding goggles with ordinary sunglasses which greatly increases the risk of injury. Additionally, in the informal welding settings, the high cost and accessibility of acquiring PPEs, compels the welders to share, or even discard the worn out PPEs. On the other hand, the occupational health and safety gaps within the informal sectors such as limited access to structured trainings (or occasionally), not taking breaks as well as weak enforcement deprive a many workers of proper orientation and essential knowledge for promoting safety at workplace. Rest breaks for instance, are limited in many informal organizations due to large workload that forces workers to work for longer hours and the absence of scheduled job rotations [ 42 ]. This study results are consistent with findings from other studies spanning across local and international regions which looked at these organizational factors. For instance, a research in Embakasi and Kamukunji (Nairobi) reported occasional pattern of PPE use which was associated with high levels exposures to physical hazards and insufficient trainings within small and medium welding businesses [ 43 ]. In a survey study involving 327 informal welders in Uganda, it was established that the level of occupational injury was high and it was directly linked to the lack of safety measures in the form of poor training and inappropriate use of personal protective equipment [ 44 ]. Their findings is supported by other empirical studies which were carried out in other parts of the world such as Austria and Australia and indicated that the occurrence of WMSDs in manual repetitive tasks is greatly alleviated due to the provision of rest breaks [ 42 , 45 ]. In the current study, the highest WMSD prevalence was reported by welders who occasionally used PPE (96.9%), never attended training (87.3%) and workers who never took a break (96.2%). The study results further indicated that MSD prevalence in welders that had never used or infrequently used PPEs was always high in most body parts: neck, upper/low back, elbows, hands/wrists, knees and feet, whereas the prevalence was lower (around 50% or less) among those who always used PPEs. This is mainly because regular wearing of PPE gears such as anti-vibration hand tools, gloves, knee pads, and welding helmets lowers the stress and glare of contact, and protects the body from vibrations and other injuries during welding. Prior studies have found that exposures of vibration in the upper limbs and spinal muscles has been found to be associated with musculoskeletal pains and other related disorders [ 46 , 47 ]. On the other hand, safety trainings has been mentioned to equip workers with knowledge of safety standards and promote adherence of preventive measures ultimately preventing injuries or illness including MSDs [ 48 , 12 ]. Conversely, lack of training increases the level of MSDs since welders are unaware of the dangers, unable to operate the equipment properly and cannot organize the workplace in a way that minimizes strain. Improper handling of the tools for instance decreases grip force, leading to vibration and torque at the wrist/shoulder. The high WMSD prevalence observed among those lacking training in this study is consistent with a study by Adhikari et al. [ 8 ] among construction workers in Nepal that found that workers who had not received any formal training had a higher prevalence MSD pain especially in the lower back (80.3%). Another study conducted in India found similar findings where untrained workers registered higher MSD risks in neck and upper back body regions [ 49 ]. In addition, rest breaks limits exposures to repetitive manual activities, reduces fatigue and enhances tissue repair and recovery [ 42 ]. A comparative literature from other regions reported high WMSD prevalence rates in different body parts including neck and shoulders among workers who did not take adequate work rest schedules [ 50 , 51 ]. Among informal-sector welders in Zimbabwe, work-rest breaks were significantly associated with reduction in MSD pain in the shoulders, lower back and fore-arms [ 11 ]. The logistic regression analysis further reinforced these interpretations. Frequent or consistent PPE use was associated with lower odds of MSD pain in the elbows and hand/wrists while rest breaks were associated with substantially lower odds of pain in the neck, shoulder, lower and upper backs. These findings compares well with a study covering a group of informal welders in Nigeria where use of PPEs was associated with reduced incidences of musculoskeletal injuries [ 52 ]. Ghimire et al. [ 30 ] and Sehsah et al. [ 53 ], further revealed that PPE use substantially lowered musculoskeletal disorders and other accidents in the physically demanding workplaces. Welders especially the youths, tend to neglect taking breaks as they prioritize working continuously and completing their daily tasks over taking breaks. This study however showed a strong protective effect of breaks, as high as 86.2% decrease in probability of developing WMSD. Chakrabarty et al. [ 54 ] in their study among embroidery workers in West Bengal, India also noted that rest breaks were important protective factors of MSD pain in body parts such as the neck, shoulders, lower back and wrists. The study indicated that taking frequent break times within working hours decreases the severity of musculoskeletal discomforts. 5. Conclusion The current study focused on the organisational risk factors of work-related musculoskeletal disorders (WMSDs) among the youth welders working under informal metal-working environments in Eldoret City. It was found that the prevalence of WMSDs was high, especially of the lower back, upper back, hands and wrists, and knees. Such high rates could be explained by the physically intensive welding work which is conducted in poor conditions in the areas of the study and the little use of safety equipment like personal protective equipment (PPEs) as well as the lack of frequent rest periods. The results indicate that the frequency of PPE use and rest breaks are associated with a significant decrease in the risk of MSD occurrence, emphasizing the protective value of these practices in decreasing the burden of WMSDs in informal workplaces. In line with this, this study suggests the usage of a multi-level plans to enhance occupational safety and health in the informal metal-working industry. The suggested measures include the administration of thorough and compulsory safety training to all informal welders, preferably during job entry; the regular application of proper PPEs and the introduction of regular rest periods that are short and frequent; and development of strong regulatory frameworks that are capable of enforcing compliance in the informal sector. Co-ordination of such activities at the organisational and regulatory levels can streamline the well-being of young welders and can reduce the effects of WMSDs in the informal sectors. Declarations Ethics Approval and Consent to participate. This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Mount Kenya University (Ethics ID: 3455). The National Commission for Science, Technology and Innovation (NACOSTI) gave a research permit (Ref No.796401) and informed consent was obtained from all the participants before data collection. Clinical Trial Number Not Applicable Consent for Publication. Not applicable Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing Interest The authors declare that they have no competing interests Funding The author did not receive any funding for research. Authors’ Contributions MKwas the main person responsible in conceptualising and writing the manuscript,AM guided in analyses and interpretation ofthe quantitativedata,KCprovided advice on the suitable research design, data collection tools, and analysis methodsand finally, SK helped in the review and refinement of the document. All the authors approved the manuscript for submission. Acknowledgements We acknowledge Department of Public and Environmental Health Sciences, Malawi University of Business and Applied Sciences [MUBAS] for their invaluable guidance and support. The authors express appreciation to the welders and owners of welding workshops who voluntarily participated in this study. References Murugan SS, Sathiya P. Analysis of welding hazards from an occupational safety perspective. Vietnam J Sci Technol Eng. 2024;66(3):63–74. Afata TN, Usmael Z, Werku M, Bute T, Ibrahim M, Hinsermu D. Risk detection and assessment in small-scale metalworking industries of southwest Ethiopia. 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Dong Y, Wang W, Zheng J, Chen S, Qiao J, Wang X. Whole body vibration exercise for chronic musculoskeletal pain: a systematic review and meta-analysis of randomized controlled trials. Arch Phys Med Rehabil. 2019;100(11):2167–78. Bamidele, E. F., Okebalama, V. C., Sodeinde, J. K., Ogunkoya, J. O., Oshinaike, A.,Adefala, N. O., … Nwankpa, C. C. (2023). The Prevalence of Musculoskeletal Symptoms among Welders and Non-Welders in Ikenne, Ogun State, Nigeria: A Comparative Cross-Sectional Study. West African Journal of Medicine, 40(9), 943–949. Joseph N, Venkatesh V, Akash SK, Hegde S, Moras E, Shenoy NP. Occupational hazards – pattern, awareness and preventive measures among welders from an unorganized sector in India. J Clin Diagn Res. 2017;11(5):LC23–8. Jain R, Meena ML, Dangayach GS, Bhardwaj AK. Association of risk factors with musculoskeletal disorders in manual-working farmers. Arch Environ Occup Health. 2018;73(1):19. Dev M, Bhardwaj A, Singh S. Analysis of work-related musculoskeletal disorders and ergonomic posture assessment of welders in unorganised sector. Int J Hum Factors Ergon. 2018;5(3):240. Agu AP, Umeokonkwo CD, Adeke AS, Nnabu CR, Ossai EN, Azuogu BN. Awareness of occupational hazards, use of personal protective equipment and workplace risk assessment among welders in Mechanic Village, Abakaliki, South-East Nigeria. Niger Med J. 2022;62(3):113–21. Sehsah R, El-Gilany AH, Ibrahim AM. Personal protective equipment (PPE) use and its relation to accidents among construction workers. Med Lav. 2020;111(4):285. Chakrabarty S, Sarkar K, Dev S, Das T, Mitra K, Sahu S, et al. Impact of rest breaks on musculoskeletal discomfort of Chikan embroiderers of West Bengal, India: a follow-up field study. J Occup Health. 2016;58(4):365–72. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":60222,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical map of the study area. Source: Author’s compilation based on data from Kenya National Bureau of Statistics (KNBS, 2019) county shapefiles.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8183954/v1/a2ce246ce533626dd1d1412c.jpg"},{"id":99187817,"identity":"3c20f51f-13e5-4e26-93d7-0da3727bab16","added_by":"auto","created_at":"2025-12-30 00:12:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":166495,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of WMSDs in different body parts among youth welders in Eldoret Town.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8183954/v1/327afdbfcc159db6212b493c.jpg"},{"id":99187821,"identity":"1ac14488-7748-484c-8453-2c9d731687fc","added_by":"auto","created_at":"2025-12-30 00:12:13","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":178599,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of organizational risk factors among the youth welders in Eldoret Town\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8183954/v1/0a1b7bdff0d71311a8fa7cb7.jpg"},{"id":99323455,"identity":"75a98c24-18df-4a31-8272-445dfe84270e","added_by":"auto","created_at":"2025-12-31 16:45:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1594798,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8183954/v1/10dc920b-ea2b-4771-a8cb-b735ac91f913.pdf"},{"id":99187815,"identity":"74b2c4cf-7188-45f2-94f0-56825b1daf8b","added_by":"auto","created_at":"2025-12-30 00:12:12","extension":"csv","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2446,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.csv","url":"https://assets-eu.researchsquare.com/files/rs-8183954/v1/5280863c16c56d3c81480f60.csv"},{"id":99187830,"identity":"51e3dd6a-6e28-41ae-935b-512475378583","added_by":"auto","created_at":"2025-12-30 00:12:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":265376,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1..docx","url":"https://assets-eu.researchsquare.com/files/rs-8183954/v1/c23a9e2c16b85981fc6fd99a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Organizational Risks Factors and Work-Related Musculoskeletal Disorders among Youth Welders in Informal Metalworking Setting","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; 85% WMSD overall prevalence reported among youth welders\u003c/p\u003e\u003cp\u003e\u0026bull; The most affected areas are the lower back, upper back, hands/wrists and knees\u003c/p\u003e\u003cp\u003e\u0026bull; Use of PPEs and rest breaks are the key organisational risk factors\u003c/p\u003e\u003cp\u003e\u0026bull; Mandatory safety training, subsidised PPEs and rest breaks, and increased enforcement are suggested to reduce occurrence of WMSD\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eLike other metalwork tasks, welding involves physically demanding tasks, which requires the repetitive use of hand tools, manual lifting, and repeated handling of heavy metallic materials during the working [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Most of these working activities are done under poor postures and in confined areas. Despite the constraints, welding is key in infrastructure development as it supports major sectors in the economy including the automotive, construction and manufacturing industries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In addition, it provides employment opportunities to many individuals especially the youths who lack formal employment [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In developing countries, most welding enterprises are carried out in the informal sectors, where regulatory policies are weak [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], formal registration is lacking, and where limited oversight on occupational health and safety (OHS) practices exist. Several studies in low-and-middle income countries (LMC), have reported that informal welders in this sector have insufficient organisational measures including inadequate access and use of personal protective equipment (PPEs), lack of job rotations, and rest time [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This scenario can be explained by the resource limitation and the poor institutional enforcement typical in the informal or small-scale industries [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Africa, more than 80% of informal welding enterprises are not controlled by regulations and are poorly organised [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Studies conducted in Zimbabwe [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], Tanzania [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], South Africa [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and Kenya [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] have all revealed that these workshops operate in impoverished environments, lack modernised equipment, and largely depend on manual labour with minimal to no occupational health services, thus rendering the welders disproportionately vulnerable to work-related injuries and other related illnesses.\u003c/p\u003e \u003cp\u003eWork-related musculoskeletal disorders (WMSDs) in particular present a major occupational health problem among persons who deal with physically demanding work like welding and are more often associated with body ache and work-related fatigue. These conditions impair the muscles, nerves, tendons, joints, and spinal discs, causing pain, reduced mobility, job absenteeism, lower productivity, and long-term disability in extreme situations [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The body regions mostly impacted include the lower back, shoulders, wrists, neck, and knees, often due to the repetitiveness of the work, awkward postures and aggressive actions involved [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. There is however no consolidated global data on prevalence of WMSDs in informal sector welders; but as per the country-level studies, the burden has always been high particularly in the LMC. For instance, studies conducted on informal welders in Bangladesh [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Nigeria [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and Ethiopia [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] found annual prevalence rates of 85%, 86.4% and 54% respectively with the lower back, shoulder, knee and wrist/hands being the commonly affected body parts. This demonstrates that WMSDs continues to be a major and prevalent occupational health issue in the informal welding industries.\u003c/p\u003e \u003cp\u003eOrganisational risk factors associated with WMSDs, such as task design, safety practices, and rest\u0026ndash;work schedules, particularly in informal welding firms, remains limited. This issue is critical in Sub-Saharan Africa where informal sectors are the pillars of most economies, and having the majority (over 80%) of the workforce as youths [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These workers mostly do not have adequate PPEs, never undergo proper safety training, and have no timetabled rest breaks in such informal workplaces [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Moreover, these organisational weaknesses that have been identified to contribute to WMSDs but are scarcely studied. In Kenya, where a large proportion of the youthful population is concentrated in informal metalwork sector [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], these organisational gaps are even more pronounced, with limited regulation, weak enforcement of occupational health policies, and scarce empirical evidence on how such conditions contribute to the burden of WMSDs. Thus, this study attempts to fill this gap by analysing the organisational aspect of occupational health risks among informal sector welders in Kenya.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003e2.1 Study area\u003c/h2\u003e\n \u003cp\u003eThis research was done in Eldoret City, Uasin Gishu County, Kenya (Fig.\u0026nbsp;1) which is approximately 310 km northwest of Nairobi. Eldoret is in the equator at an altitude of 2,100-2,300m with a tropical highland climate, having average rainfall of 1500 mm/year [22] Chelule et al, 2024). Eldoret has a population of 475,716 according to the Kenya National Bureau of statistics (2019) [23] and has officially been declared the fifth city in Kenya in 2024, due to its population increase and economic values in the region. The city is largely known for maize and wheat production, dairy production and agro-processing industries including textiles and flour milling [24]. Similarly, there is plenty of informal sector activities such as metalworking (welding and fabrication), carpentry, tailoring, and minor trade exist [25]. The dominance of informal metalworking industries in Eldoret renders it as an example to study the occupational health risk of urban informal economies in most Sub-Saharan Africa countries.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\"\u003e\n \u003ch2\u003e2.2 Study Design, Population, Sample size and Sampling\u003c/h2\u003e\n \u003cp\u003eThis study adopted descriptive-explanatory (analytical cross-sectional) design, which provide the description of the occupational health outcomes and analysis of the relationships between the risk factors and the health conditions. Male and female welders who work in the metalworking businesses of the Jua Kali (informal sector) were part of the study population, a group that is very densely distributed throughout the industrial and residential estates of Eldoret. The Ministry of Labour (North Rift Chapter) estimated that there are 400 youth welders in the city. According to national statistics, the largest segment of the youth labor force in Kenya work in the informal sector where about 63% of workers in Kenya are under the age of 35 years [26]. This population trend highlights the need of research on young informal workers, who are subject to occupational risks and who have poor reach to social benefits, education, standards and regulations. Young welders represent an ideal study group to evaluate the occupational health risks since they are prone to musculoskeletal disorders, inadequately use protective strategies, and also experience extended durations of exposure to the dangerous work tasks on daily basis [25].\u003c/p\u003e\n \u003cp\u003eThe sample size was determined by using Yamane\u0026rsquo;s formula [27] for finite populations [24]:\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img1766519105.png\"\u003e\u003c/p\u003e\n \u003cp\u003eWhere: n\u0026thinsp;=\u0026thinsp;Sample size N\u0026thinsp;=\u0026thinsp;Total population of youth welders in Eldoret Town (estimated at 400 based on The Ministry of Labour, North Rift Chapter, estimates that there are 400 youth welders in the region.) e\u0026thinsp;=\u0026thinsp;Desired level of precision (0.05 for 95% confidence level)\u003c/p\u003e\n \u003cp\u003eApplying the formula:\u0026nbsp;\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img1766519127.png\"\u003e\u003c/p\u003e\n \u003cp\u003eConsidering the non-response error, an additional 10% was added, final sample size became 220 participants.\u003c/p\u003e\n \u003cp\u003eThe study employed stratified sampling method where town was categorized into distinct zones, such as Langas, Kimumu, and Huruma, which are wards within Eldoret town in Uasin-Gishu County and known for having high concentration of welders. All informal welding workshops were listed from a walk through over these zones. The population of welders in each of the zones was determined, and a simple random sampling was employed to get proportionate sample participants. The local administration helped in process of locating the informal workshops and participants for this study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003e2.3 Inclusion and Exclusion Criteria\u003c/h2\u003e\n \u003cp\u003eThe participants in the study were welders aged 18 to 35 years, had at least one year of welding experience, and working in an informal (\u0026ldquo;Jua Kali\u003cem\u003e\u0026rdquo;\u003c/em\u003e) setting in study area. Youth welders who had history of musculoskeletal injuries outside the workplace were excluded from the study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003e2.4 Research Instrument, Reliability and Validity\u003c/h2\u003e\n \u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003e2.4.1 Research Instrument\u003c/h2\u003e\n \u003cp\u003eNordic Musculoskeletal Questionnaire (NMQ) for assessing the 12-month prevalence and distribution of MSDs pain or discomfort in nine major body regions [28] was modified and supplemented with a closed-ended structured questionnaire consisting of two additional sections: sociodemographic characteristics and organizational/work-related factors. The sociodemographic section captured information on participants\u0026rsquo; gender, age, educational level, welding experience, employment status, working hours and workspace adequacy. The organizational factors gathered information on availability and duration of work breaks, use of personal protective equipment (PPE), occupational health and safety training, and presence of workplace safety policies.\u003c/p\u003e\n \u003cp\u003eResearch instrument attached as Supplementary File 1.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e2.4.2 Reliability and Validity\u003c/h2\u003e\n \u003cp\u003eThe study used the test-retest reliability, where the research instrument was given to a group of participants two times at a semi-monthly interval between administrations. This enabled the researcher to ascertain the ability of the instrument to generate consistent responses. Content validity was performed where experts including occupational health experts were consulted to review if the instrument is valid and reasonable in measuring the variables. The main areas which were assessed included whether the content of the tools were adequate in their measurement of the risk factors and musculoskeletal disorders. In addition, a pilot study was also used examine the face validity and 20 participants (10% of the primary sample) from a similar setting in the neighbouring towns of Nakuru were involved.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e2.5 Data Collection Procedure\u003c/h2\u003e\n \u003cp\u003eThe questionnaire was self-administered and the respondents were allowed 30 to 45 minutes to interact with the instrument. The drop-and-pick strategy was used where the questionnaires were distributed among the participants in their workplaces and were collected afterwards to avoid disturbance of the working processes.\u003c/p\u003e\n \u003cp\u003eThe study objectives, procedures and confidentiality assurances were explained to the respondents both verbally and in writing before they were given a chance to participate. Informed consent was obtained through writing with the individuals who consented to take part in it. It was all voluntary and people who refused were excused with respect. In order to minimize the chances of non-response bias, any non-responder was instantly replaced.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e2.6 Data Analysis\u003c/h2\u003e\n \u003cp\u003eSociodemographic characteristics and the prevalence of WMSDs were summarised using descriptive statistics which included frequencies and percentages. Bivariate analysis using Chi-square tests were performed to determine the unadjusted associations between specific organisational factors with the presence of WMSDs and binary logistic regression analysis assessed the independent influence of the risk factors. The results were interpreted at a significance level of 0.05 and 95% Confidence Interval (CI).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Questionnaire Response Rate\u003c/h2\u003e \u003cp\u003eFor this study, a total of 220 youth welders were selected to take part in the study. Thus, a total of 220 questionnaires were issued to the selected participants. The duly filled and returned questionnaires were 193, which represent a response rate of 87.7%. The overall response rate was suitable for data analysis and reporting.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Socio-Demographic Characteristics of the Respondents\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarises the sociodemographic characteristics of the youth welders in Eldoret Town. The majority (97.9%) of the welders were male, nearly half (42%) were aged 29 to 35 years and most of them (80.4%) had secondary education or below. Employment status indicated that only 9.3% only business owners and the majority were employed without formal contracts. Nearly three quarter (71%) had less than 5 years of welding experience. Working hours varied with welders working less than 6 hrs per day being 20.7%, and those working more than 8 hrs per day being 48.6%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the youth welders in Eldoret Town\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocio-demographic variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e189 (97.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (30.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u0026ndash;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54 (28.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81 (42.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75 (38.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80 (41.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnical-Vocational training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38 (19.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness owner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFully employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (30.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartially employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78 (40.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCasual/Temporary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (20.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExperience (Years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (20.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 to 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98 (50.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56 (29.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking Hours\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40 (20.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 to 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65 (33.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8 to 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62 (32.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (13.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Prevalence of WMSD among Youth Welders in Eldoret Town\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e indicated that Frequency of WMSDs among young welders in Eldoret Town was very high with majority of respondents stating that they had at least one WMSD in the last 12 months. The most impacted parts of the body were lower back (83.9%), upper back (80.8%), hands/wrists (78.8%), and knees (78.2%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Organizational Risk Factors Influencing WMSD among Youth Welders in Eldoret Town\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1 Organizational Risk Factors\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the occurrences (in percent) of the organisational risk factors among welders in the study area. 49.7% of welders occasionally used PPEs, the majority (59.1%) had previously never attended safety training, and over half (53.9%) did not taking rest breaks during working hours.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2 Relationship between Organizational Factors and WMSDs\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents results of bivariate analysis between organisational factors and overall WMSDs prevalence among welders in the study area. The highest MSD prevalence (96.9%) was reported among welders who occasionally use PPEs, and lowest (25%) reported among those who always use PPEs. In addition, the use of PPEs was significantly (p-Value\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;41.242) associated with overall WMSD prevalence. The prevalence remained high regardless of whether welders previously attended safety training or not. However, no significant association was found between attendance of training and overall WMSD prevalence. For rest breaks, welders who did not take rest breaks had a higher prevalence of WMSD (96.2%) compared to those who were taking rest breaks during working hours (71.9%). There was also a significant association (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;22.077) found between rest breaks and overall WMSD prevalence.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between Organizational Risk Factors and Overall WMSD Prevalence\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall WMSD Prevalence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChi-Sq (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of PPEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (86.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttended Training\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (87.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRest Breaks\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(Excluding lunch breaks)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (71.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (96.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the association between organisational risk factors and MSDs in different body parts over the last 12 months. Among welders that never used PPEs, the MSD prevalence remained high in all body parts, except the thighs (76.9% \u0026minus;\u0026thinsp;92.3%). A similar trend was observed among those who occasionally used PPEs (76.0% \u0026minus;\u0026thinsp;93.8%). Welders who always used PPEs had the lowest prevalence at any of the body parts (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;50%). Statistical analysis further demonstrated that there was a significant association between the use of PPE and MSDs in the neck (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;19.032), shoulders (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;22,523), upper back (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;18.992), elbows (p\u0026thinsp;=\u0026thinsp;0.002, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;17.517), hands/ wrists (p\u0026thinsp;=\u0026thinsp;0.009, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;1.061) and lower back (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;24.925).\u003c/p\u003e \u003cp\u003eA little variation was observed in training attendance and WMSD prevalence. The WMSD prevalence among welders without previous training ranged 72.8% to 84.2% and 74.7% to 83.5% among those who had attended training in the neck, upper back, elbows, hands/wrists, lower back, knees and feet, respectively. There was also no significant relationships between attending training and the prevalence of MSD in any of the body parts.\u003c/p\u003e \u003cp\u003eIn terms of rest breaks, welders who took rest breaks during working hours reported a high prevalence of WMSD in the upper back, hands/wrist, knees and feet (71.9% to 78.8%), while those not taking breaks had high prevalence of WMSD in all the body parts except in the thighs (75.0% to 94.2%). Further, Rest breaks were significantly associated with MSDs in the neck (p\u0026thinsp;=\u0026thinsp;0.002, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.735), shoulders (p\u0026thinsp;=\u0026thinsp;0.022, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;5.250), upper back (p\u0026thinsp;=\u0026thinsp;0.029, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;4.744), hands/wrists (p\u0026thinsp;=\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.974) and lower back (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;17.722).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between Organizational Risk factors and MSD in Different Body Parts\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e \u003cp\u003eMSD prevalence (%) in the different body parts in the past 12 months\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNeck\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eShoulders\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eUpper-Back\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eElbow\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eHand/Wrists\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eLower Back\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eThighs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eKnees\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eFeet\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUse of PPEs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e69.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e69.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e72.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e74.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eχ\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.579\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttended Training\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e46.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e78.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e74.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e74.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eχ\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.319\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRest Breaks\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e76.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e79.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eχ\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;5 shows the binary logistic regression analysis between organisational risk factors and the prevalence in WMSD in different body parts. Frequent use of PPEs showed a negative significant association with pain in shoulders (OR\u0026thinsp;=\u0026thinsp;0.240, 95% CI 0.056\u0026ndash;1.020), and hands/wrists (OR\u0026thinsp;=\u0026thinsp;0.813, 95% CI 0.151\u0026ndash;4.373) while the use of PPEs consistently or always was as well negatively associated with pain in the elbows (OR\u0026thinsp;=\u0026thinsp;0.103, 95% CI 0.013\u0026ndash;0.826). Negative significant association was also found between adoption of rest breaks and pain in the neck (OR\u0026thinsp;=\u0026thinsp;0.307, 95% CI 0.147\u0026ndash;0.642), shoulders (OR\u0026thinsp;=\u0026thinsp;0.410, 95% CI 0.207\u0026ndash;0.810), upper back (OR\u0026thinsp;=\u0026thinsp;0.445, 95% CI 0.147\u0026ndash;0.642) and lower back (OR\u0026thinsp;=\u0026thinsp;0.138, 95% CI 0.050\u0026ndash;0.382).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;5 attached as Additional file 1.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe current study showed that the prevalence of WMSD among the youth welders population was high (85%), which may be explained by the physically intense nature of welding activities. More specifically, continuous static postures (prolonged trunk, neck, and shoulder flexions or out-of-position welds), sustained repetitive hand movements (cutting, hammering), and the manual handling of heavy metal items, and other pieces of equipment that impose intense cumulative loads on musculoskeletal system especially on the spine, upper limbs, and knees [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Additional impacts emanates from the tool related vibrations (due to the use of grinders), and less accessibility to modern lifting tools. The occurrence of high rates of WMSDs among youth welders who work in the informal welders sector concurs with other studies for instance, similar patterns were observed in Kenya\u0026rsquo;s cohorts in age neutral studies in Nakuru [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and Nairobi [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], as well as in Nigeria [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and Bangladesh [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] where prevalence of over 70% were reported.\u003c/p\u003e \u003cp\u003eIn the present study, prevalence of WMSD varied in different body parts. The prevalence of WMSD was highest in lower back, upper back, hands/wrists and knees (\u0026gt;\u0026thinsp;70%) and lowest in shoulders, thighs and feet (\u0026lt;\u0026thinsp;70%). During the informal welding, many tasks are performed in confined areas, which encourage long-term trunk flexion/twisting. Firstly, the load on the static spine is rapidly accumulated due to short or lack rest periods, often repetitive and not diverse, hence difficult to alternate [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Secondly, welders hold welding torches and hand tools (grinders, drills, hammers) repeatedly and with force, causing vibrations, and increasing the risk of pain particularly in the wrist /hand and forearm [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Thirdly, welding operations are most frequently performed by kneeling/squatting, which increases welders contact forces and load stress, hence resulting to knee pain [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. By contrast, the percentage of shoulder pain in this study was low, due to limited work bench activities. Further, the younger and physically fit youth welders were more capable of sustaining the standing hours or other strains, which may be the reason for lesser ankles/feet complaints. The results of the present study are consistent with the earlier literature. For instance, according to Chatterjee and Sahu, in India, lower back and neck were found to be the most affected, and attributed to the repetitive bending, heavy lifting, and sitting with maladaptive postures [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Similarly, among informal Zimbabwean welders, 78% of them reported lower-back pain, 66% reported right-shoulder pain, and more than 60% complained of wrist pain, among the others [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. On the other hand, Cameroonian metal workers reported pains in the upper back at 65% and lower back at 62.5% [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The current study also concurs with a another study Portuguese welders who reported higher WMSDs in the lower back, upper back, and wrists/hands thus demonstrating a specificity in the spinal areas and upper-limb [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Lastly, in an occupational analysis of German welders, MSD prevalence in the lower back was reported at 71%, neck pain at 61% and shoulder pain at 55% within the past 12 months, and again it confirmed that the spine and distal upper limb were more vulnerable during welding [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe results of occurrences of organizational risk factors showed that PPEs were used occasionally by 49.7% of welders, 59.1% never attended safety training and rest breaks were infrequent (53.9%) among the welders. The main factors behind the non-use or irregular use of PPEs among informal workers include non-awareness of the occupational hazards, economic barrier to purchase PPEs and the uncomfortable feeling in wearing of these safety equipment [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Studies conducted in Kenya and Nigeria indicated that despite the fair knowledge of the welding related hazards and importance of use of PPEs, the adoption of these safety measures is still minimal [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In Nepal, Maharja et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] found that less than 40% of Nepalese welders wore PPEs and some substituted welding goggles with ordinary sunglasses which greatly increases the risk of injury. Additionally, in the informal welding settings, the high cost and accessibility of acquiring PPEs, compels the welders to share, or even discard the worn out PPEs. On the other hand, the occupational health and safety gaps within the informal sectors such as limited access to structured trainings (or occasionally), not taking breaks as well as weak enforcement deprive a many workers of proper orientation and essential knowledge for promoting safety at workplace. Rest breaks for instance, are limited in many informal organizations due to large workload that forces workers to work for longer hours and the absence of scheduled job rotations [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. This study results are consistent with findings from other studies spanning across local and international regions which looked at these organizational factors. For instance, a research in Embakasi and Kamukunji (Nairobi) reported occasional pattern of PPE use which was associated with high levels exposures to physical hazards and insufficient trainings within small and medium welding businesses [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In a survey study involving 327 informal welders in Uganda, it was established that the level of occupational injury was high and it was directly linked to the lack of safety measures in the form of poor training and inappropriate use of personal protective equipment [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Their findings is supported by other empirical studies which were carried out in other parts of the world such as Austria and Australia and indicated that the occurrence of WMSDs in manual repetitive tasks is greatly alleviated due to the provision of rest breaks [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the current study, the highest WMSD prevalence was reported by welders who occasionally used PPE (96.9%), never attended training (87.3%) and workers who never took a break (96.2%). The study results further indicated that MSD prevalence in welders that had never used or infrequently used PPEs was always high in most body parts: neck, upper/low back, elbows, hands/wrists, knees and feet, whereas the prevalence was lower (around 50% or less) among those who always used PPEs. This is mainly because regular wearing of PPE gears such as anti-vibration hand tools, gloves, knee pads, and welding helmets lowers the stress and glare of contact, and protects the body from vibrations and other injuries during welding. Prior studies have found that exposures of vibration in the upper limbs and spinal muscles has been found to be associated with musculoskeletal pains and other related disorders [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. On the other hand, safety trainings has been mentioned to equip workers with knowledge of safety standards and promote adherence of preventive measures ultimately preventing injuries or illness including MSDs [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Conversely, lack of training increases the level of MSDs since welders are unaware of the dangers, unable to operate the equipment properly and cannot organize the workplace in a way that minimizes strain. Improper handling of the tools for instance decreases grip force, leading to vibration and torque at the wrist/shoulder. The high WMSD prevalence observed among those lacking training in this study is consistent with a study by Adhikari et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] among construction workers in Nepal that found that workers who had not received any formal training had a higher prevalence MSD pain especially in the lower back (80.3%). Another study conducted in India found similar findings where untrained workers registered higher MSD risks in neck and upper back body regions [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In addition, rest breaks limits exposures to repetitive manual activities, reduces fatigue and enhances tissue repair and recovery [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. A comparative literature from other regions reported high WMSD prevalence rates in different body parts including neck and shoulders among workers who did not take adequate work rest schedules [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Among informal-sector welders in Zimbabwe, work-rest breaks were significantly associated with reduction in MSD pain in the shoulders, lower back and fore-arms [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe logistic regression analysis further reinforced these interpretations. Frequent or consistent PPE use was associated with lower odds of MSD pain in the elbows and hand/wrists while rest breaks were associated with substantially lower odds of pain in the neck, shoulder, lower and upper backs. These findings compares well with a study covering a group of informal welders in Nigeria where use of PPEs was associated with reduced incidences of musculoskeletal injuries [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Ghimire et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and Sehsah et al. [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], further revealed that PPE use substantially lowered musculoskeletal disorders and other accidents in the physically demanding workplaces. Welders especially the youths, tend to neglect taking breaks as they prioritize working continuously and completing their daily tasks over taking breaks. This study however showed a strong protective effect of breaks, as high as 86.2% decrease in probability of developing WMSD. Chakrabarty et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] in their study among embroidery workers in West Bengal, India also noted that rest breaks were important protective factors of MSD pain in body parts such as the neck, shoulders, lower back and wrists. The study indicated that taking frequent break times within working hours decreases the severity of musculoskeletal discomforts.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe current study focused on the organisational risk factors of work-related musculoskeletal disorders (WMSDs) among the youth welders working under informal metal-working environments in Eldoret City. It was found that the prevalence of WMSDs was high, especially of the lower back, upper back, hands and wrists, and knees. Such high rates could be explained by the physically intensive welding work which is conducted in poor conditions in the areas of the study and the little use of safety equipment like personal protective equipment (PPEs) as well as the lack of frequent rest periods. The results indicate that the frequency of PPE use and rest breaks are associated with a significant decrease in the risk of MSD occurrence, emphasizing the protective value of these practices in decreasing the burden of WMSDs in informal workplaces. In line with this, this study suggests the usage of a multi-level plans to enhance occupational safety and health in the informal metal-working industry. The suggested measures include the administration of thorough and compulsory safety training to all informal welders, preferably during job entry; the regular application of proper PPEs and the introduction of regular rest periods that are short and frequent; and development of strong regulatory frameworks that are capable of enforcing compliance in the informal sector. Co-ordination of such activities at the organisational and regulatory levels can streamline the well-being of young welders and can reduce the effects of WMSDs in the informal sectors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to participate.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Mount Kenya University (Ethics ID: 3455). The National Commission for Science, Technology and Innovation (NACOSTI) gave a research permit (Ref No.796401) and informed consent was obtained from all the participants before data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author did not receive any funding for research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMKwas the main person responsible in conceptualising and writing the manuscript,AM guided in analyses and interpretation ofthe quantitativedata,KCprovided advice on the suitable research design, data collection tools, and analysis methodsand finally, SK helped in the review and refinement of the document. All the authors approved the manuscript for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge Department of Public and Environmental Health Sciences, Malawi University of Business and Applied Sciences [MUBAS] for their invaluable guidance and support. The authors express appreciation to the welders and owners of welding workshops who voluntarily participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMurugan SS, Sathiya P. Analysis of welding hazards from an occupational safety perspective. Vietnam J Sci Technol Eng. 2024;66(3):63\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfata TN, Usmael Z, Werku M, Bute T, Ibrahim M, Hinsermu D. Risk detection and assessment in small-scale metalworking industries of southwest Ethiopia. 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Impact of rest breaks on musculoskeletal discomfort of Chikan embroiderers of West Bengal, India: a follow-up field study. J Occup Health. 2016;58(4):365\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Work-related musculoskeletal disorders, Youth welders, Informal sector, Welding, Occupational health and safety","lastPublishedDoi":"10.21203/rs.3.rs-8183954/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8183954/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWelding, within the metalworking industry is physically demanding job, commonly found in the informal sectors where there is limited occupational health and safety services. Young workers in these setups face greater risk of WMSDs because they are highly exposed to occupational risks factors. This study assessed organisational risk factors specifically; use of personal protective equipment (PPEs), safety training attendance and rest break and their influence on WMSD prevalence among youth welders aged 18\u0026ndash;35years in Eldoret Town.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional descriptive study was conducted where 220 welders were sampled using a stratified and simple random sampling techniques in informal \u0026lsquo;Jua Kali\u0026rsquo; workshops. Data were collected using a structured questionnaire with a Nordic Musculoskeletal Questionnaire (NMQ). Descriptive statistics, chi-square tests and binary logistic regression analyses at 95% confidence interval and significance level (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were performed with help of IBM SPSS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 193 (87.7%) participants, 85% reported that they had experienced at least one WMSD within past one year. The lower back (83.9), upper back (80.8), hands/wrists (78.8) and knees (78.2) were mostly affected. Use of PPEs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;41.242) and rest breaks (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;22.077) showed a significant association with overall WMSD prevalence and significantly reduced pain in different parts. Frequent use of PPE lowered MSD pain in the shoulders (OR\u0026thinsp;=\u0026thinsp;0.240: 95% CI 0.056, 1.020), and hands/wrists (OR\u0026thinsp;=\u0026thinsp;0.813: 95% CI 0.151, 4.373), while consistent use of PPEs significantly lowered pain in the elbows (OR\u0026thinsp;=\u0026thinsp;0.103: 95% CI 0.013, 0.826). Rest breaks lowered the risk of pain in the neck (OR\u0026thinsp;=\u0026thinsp;0.307:95% CI 0.147, 0.642), shoulders (OR\u0026thinsp;=\u0026thinsp;0.410: 95% CI 0.207, 0.810), upper back (OR\u0026thinsp;=\u0026thinsp;0.445: 95% CI 0.147, 0.642), and lower back (OR\u0026thinsp;=\u0026thinsp;0.138: 95% CI 0.050, 0.382).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe current study exposed high prevalence of WMSD in youth welders and highlights the protective value of both the use of PPE and formal safety training and rest breaks. It recommends comprehensive and compulsory safety training programs, provision of appropriate and subsidised PPEs, structured rest breaks and a strengthened regulatory framework.\u003c/p\u003e","manuscriptTitle":"Organizational Risks Factors and Work-Related Musculoskeletal Disorders among Youth Welders in Informal Metalworking Setting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-30 00:12:08","doi":"10.21203/rs.3.rs-8183954/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-06T10:49:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-18T16:27:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T11:06:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25803757288590838155125033143012185822","date":"2026-02-13T14:50:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12229599053067668432551940131331805848","date":"2026-02-11T15:19:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167127935073766122786841147228395012315","date":"2026-01-28T14:10:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77085407344947991728458879037748737169","date":"2026-01-23T14:17:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-18T08:45:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-18T08:44:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-10T04:51:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-09T05:13:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-12-09T05:07:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a797815e-de2a-42c3-a7c5-42b07c7e7b91","owner":[],"postedDate":"December 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-30T00:12:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-30 00:12:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8183954","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8183954","identity":"rs-8183954","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}