Work-related diseases and risk factors associated with work-related musculoskeletal disorders among unionized metal industry workers: a cross-sectional study

Objectives. This study aimed to determine the prevalence of work-related diseases (WRDs) and work-related musculoskeletal disorders (WR-MSDs), as well as investigate WR-MSD-associated risk factors, among metal industry workers in Turkey. Methods. The cross-sectional study was conducted with 1374 members of the Birleşik Metal İş Union from 121 companies. Data were collected using a self-administered 30-item questionnaire. Results. The survey response rate was 81.4% (1374/1686). Almost one out of every six workers (14.8%) stated that they had been diagnosed with a WRD, 3.6% reported that they had been diagnosed with an occupational disease and 38.6% of them indicated that they had suffered an occupational accident (OA) at least once. The prevalence of WR-MSDs was 10.7%, of work-related lung diseases was 1.8% and of occupational hearing loss was 0.6%. Quitting smoking, smoking, OA, heavy lifting, time pressure and working in the automotive industry were all associated with WR-MSDs. Conclusions. Interventions aimed at reducing musculoskeletal disorders (MSDs) should focus on smoking cessation, training workers in proper techniques and equipment for lifting and pushing/pulling heavy loads, preventing OAs and injuries, and reducing the time pressure in the workplace in the metal industry.


Introduction
The metal industry is a large industry that includes metal production and processing.Primary metal production includes smelting and refining ferrous and non-ferrous metals from ores, raw iron or scrap [1].Turkey has the highest number of enterprises manufacturing basic metals among countries in the Organization for Economic Co-operation and Development (OECD); 5641 (25.6%) of 21,997 establishments producing basic metals are in Turkey [2].According to data from the Turkish Ministry of Labor and Social Security from July 2021, a total of 1,789,038 workers were employed in the metal industry in Turkey [3].The proportion of employees in the metal industry in 2020 in Turkey was 8.4% of all industries and 32.3% of the manufacturing industry [4,5].
Basic metalworking techniques in the metal industry include ore and scrap smelting and refinement, casting, hot or cold forging, welding, metal cutting, sintering and turning.In addition to these processes, techniques such as grinding, polishing, sanding, surface treatment and coating are used until the final product is obtained [6].Many operations in the metal industry involve risk factors such as exposure to various chemicals (heavy metals, gasses, vapors, dust and fumes) and physical factors (noise, vibration, heat and cold stress, radiation and electricity) as well as ergonomics.
During production procedures, accidents and injuries caused by any of the exposures already mentioned may occur.In addition, manual lifting, inappropriate posture, stationary position, direct pressure, vibration, repetitive movements, extreme temperatures, noise and work stress are ergonomic risk factors that may cause musculoskeletal problems [3,7].
At the same time, there are various risk factors for work-related musculoskeletal disorders (WR-MSDs), such as workers' different working departments and tasks, duration of employment, weekly working hours, etc. [7].Risk factors include personal factors such as age, body mass index (BMI), smoking and alcohol consumption [8,9].
Health risks are generally higher in the metal industry than in other manufacturing industries [1].This is due to the innately hazardous nature of this industry, which needs to be adequately addressed to ensure worker protection and production safety.In Turkey and the rest of the world, studies on safety and health in this industry have focused on specific aspects just as hazards/risks of industry or prevalence of musculoskeletal symptoms and disorders [6][7][8][9], not the whole.
The primary aim of this study is to identify and assess workrelated health issues, with a specific focus on musculoskeletal disorders (MSDs), prevalent within the metal industry.Moreover, the study aims to investigate distinct work-related risk factors and individual variables, as well as their collective impact on the occurrence of WR-MSDs.Determination of the prevalence of WR-MSDs and possible associated risk factors may contribute to the planning of interventions for the prevention of MSDs in the metals industry.

Population and sampling
The study population comprises MIWs, who are members of the BMIS, from a total of 121 companies.The sample size was calculated as 1686 participants using the following formula in OpenEpi Version 3: where the total number of members of the BMIS was accepted as N = 22,095, the prevalence of WR-MSD possibility existence as P = 5%, the confidence interval (CI) as 95% and the confidence limit (d) as 1%.The sample size was weighted by the total number of employees in 121 companies, and a random computergenerated sample selection was made from the BMIS members list.The number of companies in the sample subdivided by industry is shown in Figure 1.The research was conducted with 1374 workers who agreed to participate in the study among the workers selected for the sample.The study has no inclusion criteria other than being a member of the BMIS and agreeing to participate.

Data collection method
The data were collected using self-administered questionnaires.The 'occupational health risks and health conditions questionnaire for metal industry workers' was created by the researchers through a detailed literature review and consisted of a 30-item questionnaire with five different sections: demographics; lifestyle and medical background; working experience and conditions; workplace risks and exposures; and occupational diseases (ODs), work-related diseases (WRDs) and occupational accidents (OAs).The questionnaires were sent to the workers selected for the sample in a sealed, opaque envelope to be given to them by workplace representatives.After the worker filled in the questionnaire, the same workplace representative received the completed questionnaire in the same closed envelope.

Definitions and classification of data
Self-reported BMI, based on self-reported height and weight, was calculated as weight in kilograms divided by height in meters squared.The definition of BMI categories was made according to the World Health Organization (WHO) criteria [10]: underweight was defined as BMI < 18.5, normal weight as BMI = 18.5-24.9,overweight as BMI = 25.0-29.9,obesity class 1 as BMI = 30.0-34.9, obesity class 2 as BMI = 35.0-39.9 and obesity class 3 as BMI ≥ 40.0.
Smoking status was assessed as: current smoker, workers who currently smoke; non-smoker, workers who have never smoked; and former smoker, workers who smoked before but have not smoked for at least the last 6 months.
The existence of chronic disease was described as a prior physician diagnosis of chronic diseases; the existence of a WRD was described as a prior physician diagnosis of WRD; and OD was described as an official OD diagnosis in authorized diagnostic centers.

Statistical analysis
Data are expressed as the mean ± standard deviation for continuous variables and as frequencies and percentages for qualitative variables.The Shapiro-Wilk test was used to test normality.Student's t test or the Mann-Whitney U test was used to compare numerical variables.Categorical data were compared using the χ 2 test.This study accepted WR-MSD diagnosis information, which MIWs reported, as the outcome variable.Multiple logistic regression analysis was performed to identify independent variables significantly affecting the WR-MSD.Statistically significant univariate analysis results were included in the regression model.Although 'annoying/threatening behaviors' was a significant factor in univariate analyses, it was not included in the logistic regression model because it showed a high correlation with 'time pressure/excessive workload'.All predictor variables were entered into the full model until the best-fitting model (age, BMI, smoking habit, total duration of work life, working hours in a week, heavy lifting, time pressure and OA) was found.Results are reported as the hazard ratio (HR) with 95% CI.Statistical significance was set as p < 0.05.All statistical analyses were performed using SPSS Statistics for Windows version 25.0.

Results
The survey response rate was 81.4% (1374/1686).The mean age of the participants was 36.5 ± 7.4 years, and 92.4% were male.MIWs with a middle school or lower education constituted 26.1% of participants, those with a high school or vocational high school education comprised 56.1% of the sample and those with an associate or higher degree constituted 16.2%.The percentage of those who had a vocational education degree by completing either vocational high school or associate degree education was 51.2%.Most MIWs were married.Table 1 presents the sociodemographic characteristics of MIWs.
The mean duration of employment in the last workplace was 8.9 ± 6.6 years and the mean total duration of employment was 17.1 ± 7.8 years.The rate of overtime was 36.8% in the study group.The most common industries that MIWs worked in were those of fabricated metal products (22.5%), automotive (14.8%), manufacturers   nearly half (48.3%) were overweight and 14.0% were class 1 obese.The combined prevalence of overweight status and obesity in male MIWs was 67.3%, and the combined prevalence for women was 39.3%.It was determined that three out of four participants perceived their health status as good or very good, at 52.7 and 22.2% of MIWs, respectively.While 22.9% of the workers defined their health status as fair, the rate of those who said their health was bad was 1.3% and the rate of those who stated it was very bad was 0.1%.
Almost one out of every three workers (30.6%) stated that they had a chronic disease, 14.8% of them declared that they had been diagnosed with a work-related disease by a physician, 3.6% reported that they had been diagnosed with an OD and 38.6% of them indicated that they had an OA at least once.Factors related to the health status of MIWs are presented in Table 3.
The body system affected the most was the musculoskeletal system (MSS), reported in 72.9% of MIWs.Other work-related adverse effects and their prevalence in study responses were lung disease (11.4%), occupational hearing loss (3.8%), workrelated skin disease (2.9%) and chronic venous insufficiency (1.9%).The prevalence of WR-MSDs among MIWs was 10.7%, of work-related lung diseases was 1.8% and of occupational hearing loss was 0.6%.
Lumbar disease (6.0%), cervical disc disorders (2.8%) and muscle and joint pain (3.0%) were the most frequent WR-MSDs.The distribution of WRDs according to the reported organ/tissue and system complaint is presented in Table 4, and the diversity of WRD-MSDs among workers is shown in Figure 2.
The first three health complaints faced by workers in the last 6 months related to the MSS were pain in the neck or upper extremity (67.6%), upper back or lower back pain (LBP) (64.5%) and lower extremity pain (50.4%).The other complaints are presented in Table 6.The health complaints that the workers thought were related to their work are presented in  Note: n = number of individuals.
Table 7.The same complaints occurred in the first three ranks with higher rates: pain in the neck or upper extremity (78.6%), upper back or LBP (74.6%) and lower extremity pain (61.3%), respectively.
A comparison between workers with WR-MSDs and other workers based on group characteristics is presented in Table 8.Smoking habits, perceived health status, diagnosis of OD, previous OA, total duration of employment, weekly working hours, welder jobs, industry (automotive) and risk factors in the workplace (inappropriate posture and movements, vibration, temperature, increased time pressure/working overload and heavy lifting) were statistically different between the groups (p < 0.05).MIWs who have any WR-MSD were more likely to have smoked before (13.8% vs. 9.0%) or to be current smokers (58.5% vs. 50.2%),less likely to describe their health status as 'very good' (7.9% vs. 24.2%)or 'good' (45.4% vs. 54.0%),more likely to have an OD (18.7% vs. 1.9%) or an OA (57.9% vs. 36.8%),more likely to have a long length of employment (20.0 vs. 16.0) and short weekly working hours (45.0 vs. 47.5),more likely to be working as a welder (10.4% vs. 4.8%) or in

Discussion
We focused on MIWs who were members of the BMIS to determine the prevalence of WRDs, work-related risk factors (job and department of workers, perceived risk factors in the workplace, duration of employment and weekly working hours) and individual factors connected with WR-MSDs in the metal industry.In the sample in the present study, sex, age, marital status, having a child and education status in the industry were distributed similarly to those reported in the Member Identity Survey 2017of the BMIS [11].Remarkably, more than half of the union members have a high level of education, including vocational education; their total employment duration was longer; and their ages tended to be older.This finding, related to age, may reflect the increased age at the time of first employment due to the longer education/higher education period since the importance of being experienced and well-trained in the metal industry is emphasized [11].

Health status indicators
Our study shows that while male MIWs had similar smoking habits to male workers in other industries (52%), the prevalence of smoking in female MIWs was higher than that of females in other industries (22%) [10].On the other hand, both male and female MIWs had a higher smoking prevalence than in Turkey overall (41.8% of men, 17.5% of women) and the world [12,13].The smoking rates in MIWs are noticeably higher.
Although the prevalence of overweight status among MIWs was greater than in the adult population (35.0%) in Turkey, obesity was lower (21.1%).The combined prevalence of overweight and obesity in male MIWs is also similar to the combined prevalence in the adult population of men (67.0%) in Turkey.In contrast, the total prevalence of overweight and obesity in women is less than the total prevalence of both in the adult population of women in Turkey (55.2%) [14,15].These findings indicate that overweight/obesity problems affect male more than female MIWs.
The present study determined that one of every two workers with chronic diseases reported them as work-related.Unfortunately, only one-quarter of MIWs with WRDs were officially diagnosed with an OD, and more than one-third of all cases reported injury due to a work-related accident.Occupational injuries and accidents can be easily determined based on the direct relationship between workplace conditions, accidents and injuries.If work-related risk factors are well-defined, physicians can easily diagnose work-related diseases; however, since this is frequently not the case for ODs, the relationship between work and disease must be proven [15].Therefore, the detected occupational injuries and accidents in the workplace are expected to be higher than the reported OD rates, and our study findings showed similar trends.

Workplace exposures and health issues
Most MIWs declared exposure to hazardous noise levels within the workplace, and some reported hearing problems; however, very few MIWs were diagnosed with occupational hearing loss in this study.In a current systematic review, the pooled prevalence of occupational noise exposure was found to be similarly high, at 60%, in the Eastern Mediterranean [16].
Although in previous studies [17,18] workers were reported to be younger than our study population, noise-induced hearing loss was found to be lower in our study because of study limitations.Our study relied on self-reported previous diagnoses; MIWs were not screened using a pure tone audiometry test.MIWs with hearing loss who do not recognize their symptoms and those with hearing problems who did not report their injury to the health institution could not be detected.At least half of the MIWs in our study complained of dusty work environments, gas/vapor and smoke, chemicals and heavy metal exposure.Some respiratory symptoms or diseases could be related to workplace exposure, as mentioned previously [19].In our study sample, the number of MIW patients with respiratory symptoms or lung diseases was eight times higher than that of MIW patients with confirmed work-related lung diseases.The gap between MIWs with respiratory symptoms or diseases and those who have a diagnosed with work-related lung disease may be associated with either a high prevalence of smoking among MIWs or the fact that lung diseases were not detected because ODs/WRDs may also be categorized as non-work-related, in case occupational risk factors were not explored in the working history [20].
Similar to our study, numerous reports [1,3,7] have noted that heavy lifting, inappropriate posture, time pressure or excessive workload, extreme temperatures and vibration are other frequent workplace exposures in the metal industry.
Several research papers [21][22][23][24][25] have found that these workplace risk factors are related to MSDs among MIWs and workers in other industries [8,26].Consistent with our findings is back pain, followed by muscular pain in the upper and lower limbs, which is the most commonly reported health problem in a study from Italy [9,27].Of all industry workers in the European Union (EU) with a work-related health problem, 60% identify MSDs as their most serious issue [21].Other studies showed a similarly high prevalence of MSDs among MIWs in India and a high prevalence of LBP despite younger ages and a short duration of employment in steel industry workers in Iran [28][29][30].

Risk factors for work-related musculoskeletal disorders
As presented in this study, MSDs are the most commonly recognized OD in France, Italy and Spain, according to the national data for EU countries [21].The results showed that smoking, previous OAs, heavy lifting, time pressure/excessive workload and the automotive industry were associated with WR-MSDs.Each risk factor increased the odds by approximately two-fold.

Smoking
In this study, former and current smokers were found to have an increased risk of WR-MSDs.A meta-analysis demonstrated that current and former smokers had an increased risk of lumbar radicular pain.In contrast, another recent metaanalysis pointed out that current smoking was associated with increased chronic musculoskeletal pain risk [31,32].Previous studies have investigated the biological effects of smoking and reported that the combination of smoking and hard physical workload increased vertebral inflammation [33] and decreased oxygenated hemoglobin in the muscles during incremental exercise [34].Smokers show increased oxidative stress and skeletal muscle dysfunction via an increase in inflammatory markers (sTNFR1) and thiobarbituric acid, and a decrease in the total antioxidant capacity of plasma and catalase activity [35].A cross-sectional study reported that smokers had a lower amount of type I and IIa muscle fibers than non-smokers, indicating that smokers' skeletal muscles have oxidative fiber atrophy [36].
In contrast, there was no significant relationship between overweight status or obesity and WR-MSDs in this study.While there were no significant associations between the single explanatory variables, physical workload, in combination with either heavy smoking or overweight status, was strongly associated with disc degeneration in a previous study [32].

Occupational accidents
Previous OAs are also risk factors for MSDs.Awkward working positions and forceful exertion may cause musculoskeletal injuries resulting in work-related disorders and diseases.A study suggested that injury and ergonomic risk factors resulting in LBP were responsible for the greatest overall burden [25].Accident rates in the workplace may include acute episodes of musculoskeletal pain, contraction or other problems, such as those occurring after lifting heavy loads; dislocations, sprains, strains and bone fractures are examples [21].In the current study, work-related accidents are hypothesized to account for a sizeable proportion of acute episodes of musculoskeletal problems.

Heavy lifting
In our study, a systematic review proved that heavy lifting was among the most common biomechanical risk factors for WR-MSDs [22].Analyses of 432 job evaluations showed that high-risk levels of heavy lifting resulted in high rates of WR-MSDs in companies [23].According to a meta-analysis, lifting heavy objects -varying with the frequency, duration and intensity of lifting -plays a role in LBP symptomatology and severity [37].A current study showed that lifting weights was related to higher muscular workload in the lower back and neck/shoulder muscle groups [38].

Time pressure or excessive workload
Similar to our study, studies showed that working under time pressure or with deadlines increased the risk of upper extremity MSDs [39]; the odds were approximately twice higher in the case of deadline presence in a longitudinal study.

Automotive industry
Although our study did not focus on upper extremity MSDs, previous studies suggest a high prevalence of upper extremity MSD and its association with biomechanical workload among automobile manufacturing workers [40,41].
A previous review that focused on the aging of industrial workers suggested that the reported side effects among industrial workers were minimal due to older workers compensating for the decline in physical and cognitive work capacity via their knowledge and experience.In the present study, the fact that age was not a risk factor for WR-MSDs may be explained by workers having a high level of vocational education and adequate work experience.

Strengths and limitations
This study is based on a large representative sample, which adequately reflects the population characteristics of unionized MIWs.In this study, work-related, officially diagnosed MSDs as reported by workers were assessed, in addition to unofficial work complaints.However, the present study has some limitations.First, because of its cross-sectional design, the data were collected simultaneously.Longitudinal studies may yield more reliable conclusions and causative relationships regarding risk factors and WR-MSDs.Second, our study did not include workplace or medical measurements or examination results; diagnostic information and workplace exposures were also reported by the participants.Additionally, the data on complaints are self-reported and refer to the last 6 months; thus, recall bias may be a factor.

Conclusion
This study sheds light on WRDs, and specifically the prevalence and risk factors of WR-MSDs among MIWs in Turkey.The prevalence of WRDs and WR-MSDs among MIWs underscores the need for targeted interventions to improve the health and well-being of this workforce.Smoking, previous OAs, heavy lifting, time pressure and excessive workload, and working in the automotive industry were all linked to a higher likelihood of WR-MSDs.
Well-planned and multidimensional workplace prevention programs that target smoking cessation may reduce the risk of MSD and other favorable health effects.Although the study did not establish obesity as a cause of WR-MSDs, the high prevalence of overweight status and obesity in men underscores the need for workplace intervention programs to reduce overweight/obesity.Smoking cessation and overweight/obesity reduction interventions should be part of the metal industry's workplace health and safety policy and a central interest for unions.
The correlation between OAs and WR-MSDs highlights the importance of workplace safety measures and accident prevention strategies.Moreover, addressing the ergonomic risks associated with heavy lifting and promoting proper techniques and equipment usage could alleviate the burden of MSDs.In addition, creating a workplace environment that allows workers to decrease workload and implementing procedures that can increase the control on their tasks can help mitigate WR-MSDs.
Further studies are needed to longitudinally assess the effectiveness of the recommended interventions and to explore additional factors that may contribute to WR-MSDs among MIWs.
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Figure 1 .
Figure 1.Number of companies in the sample listed by industry.

Figure 2 .
Figure 2. Coexistence of work-related musculoskeletal disorders.Note: numbers are counts of workers with work-related musculoskeletal disorders.
This cross-sectional study was conducted among Birleşik Metal İş (BMIS) members, an organized trade union in Turkey's metal industry.The BMIS is the third-largest metal industry union in Turkey.With22,095 members, the BMIS represents 1.78% of all metal industry workers (MIWs) in Turkey and 10.9% of those unionized in the metal industry.This study was approved by the Ethical Committee of Istanbul Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital (YAEK/(2022/183)/2022.01.06).

Table 1 .
Sociodemographic characteristics of metal industry workers.

Table 2 .
Characteristics of metal industry workers in terms of their working life.

Table 3 .
Health status indicators among metal industry workers.

Table 2 .
One-half of the MIWs (50.7%; male 52.1% vs. female 38.5%) were current smokers, 9.5% of them had quit smoking and 38.9% had never smoked before.While more than half of MIWs (53.7%) had never consumed alcohol, 8.0% said they drank at least once a week.Only 32.9% of MIWs had normal weight,

Table 4 .
Distribution of work-related diseases according to the organ/tissue and system among metal industry workers.

Table 5 .
Occupational exposures in the workplace.

Table 6 .
Distribution of complaints among metal industry workers in the last 6 months.
Note: n = number of individuals.

Table 8 .
Comparison of some characteristics between workers with work-related musculoskeletal disorders and other workers.

Table 9 .
Multiple logistic regression analysis (adjusted by age and BMI) of risk factors for work-related musculoskeletal disorders.