Effect of personal risk factors on the prevalence rate of musculoskeletal disorders among workers of an Iranian rubber factory

Abstract

BACKGROUND:

Musculoskeletal Disorders (MSDs) are among the most common occupational disorders in many countries and have an increasing trend.

OBJECTIVE:

The present study was conducted in order to determine the prevalence rate of MSDs in different body regions and the effect of personal factors on the prevalence rate of MSDs among rubber industry workers.

METHODS:

This analytical and cross-sectional study was performed on 206 workers of an Iranian rubber factory in 2014. The samples were randomly selected. Data were gathered by means of personal information form, the Nordic Musculoskeletal Questionnaire (NMQ) and the Rapid Entire Body Assessment (REBA). The results were analyzed using SPSS16; by descriptive and analytical statistics.

RESULTS:

The mean age and work history of subjects were 34.54±6.36 and 12.34±6.28 years, respectively. The highest prevalence rate of MSDs in the last twelve-months was related to the lower back region with a prevalence rate of 62.1%. Based on logistic regression, a significant correlation was found between MSDs and the final REBA score so that for a one-unit increase in score, the risk or complaint of neck and low back pain increased by 48.5% and 37.1%, respectively.

CONCLUSION:

Many rubber factory workers experience MSDs especially in the lower back region as a consequence of occupational risk factors. Therefore, detecting the occupational risk factors, work position standards and following ergonomic interventions are highly recommended.

Keywords

Ergonomics working posture Rapid Entire Body Assessment (REBA).

1 Introduction

Musculoskeletal disorders (MSDs) are described as a group of disorders affecting different regions of the musculoskeletal system such as the nerves, tendons and supportive structures such as inter vertebral discs [1]. These disorders can cause pain, injury, illness and reduction in the quality of life and work efficiency among the individuals [2, 3].

Now days, these disorders affect the lives of millions of people and have been known as the most common causes of pain and disability throughout the world [4, 5]. On one hand, MSDs are determined as a common health problem and the leading cause of occupational disability and, they are the major challenge in healthcare systems all around the world [6, 7]. MSDs result in loss of work time, increased healthcare costs, increased injuries and are also regarded as the leading cause of absence in the workplace [8, 9].

The economic burden of these disorders do not only affect the individuals, but organizations and communities as well [10]. According to reports, about a quarter of workers’ compensation claims in the United States is due to musculoskeletal injuries. If MSDs are caused by long-term exposure to risk factors, they can cause Cumulative Trauma Disorders (CTD). The main features of CTDs are their accumulation over time and the incidence of physical and mechanical stress [11, 12].

MSDs are caused by physical, psychological and social factors as well as demographic factors such as age, weight, stress and Body Mass Index(BMI) [13, 14]. Based on research findings, the increasing prevalence rate of these disorders in the workplace has a direct relation with ergonomic and physical factors [13]. Physical and ergonomic factors involved in the occurrence of MSDs, include high physical activity, improper body posture during work, lifting heavy objects, manual load handling, prolonged standing and sitting, repetitive and individual works, bending and stretching of body parts and long working shifts [15 –20].

The rubber manufacturing industry unlike the chemical industry has a non-continuous batch process. Also unlike the chemical industry which is often fully automatic, the rubber manufacturing industry has a low automation level, and this industry has a high number of workers. Rubber manufacturing industry includes processes such as; raw material handling, material weighing and mixing, preparing rubber compounds, extruding and calendaring, construction and preparation of rubber components, component assembly and building, vulcanization, testing, inspection, storage and dispatch [21]. Due to the working conditions in the rubber manufacturing industry, many risk factors described above are evident in this industry. Therefore, workers are exposed to many risk factors that cause MSDs [22, 23]. Previous reports on the prevalence rates of MSDs in the rubber manufacturing industry were from 73% to 77% [8, 22]. Despite the high risk of MSDS in the rubber industry, yet few studies have been done on the risk factors and their impact on MSDs. The present study aimed to determine the prevalence of MSDs in different body regions, assess the incidence risk of MSDs by the REBA assessment method and determine the effect of personal factors on the prevalence rate of MSDs among rubber industryworkers.

2 Methods

2.1 Setting and samples

This cross-sectional study was an analytical study performed on workers of one of Iran’s rubber factories in 2014. The research population included all production line workers (600 workers). Subjects were chosen by simple random sampling using a table of random numbers. Inclusion criteria consisted of having a work history for at least one year and exclusion criteria included having congenital MSDs or musculoskeletal injuries caused by accidents.

Based on previous reports on the prevalence rate of MSDs in the rubber manufacturing industries [8, 22], in order to determine the sample size, the prevalence rate was assumed to be 75%, with an acceptable error of 5% and α= 0.05. Then, a sample size of at least 194 people was calculated. Considering the possibility of losing samples, data were collected from 213 subjects. Later, due to lack of cooperation and incomplete answers, some questionnaires (only 7 cases) were excluded.

2.2 Study instruments

A) A Demographic and Organizational questionnaire including age, weight, height, work history and marital status was used. BMI 1 was calculated by dividing weight (kg) by height (m²), and was classified into four weight categories according to World Health Organization’s standards which were; low weight (<18. 5), normal weight (18.5–24.9), overweight (25–29.9) and obese (>30) [24].

B) The NMQ 2 : This questionnaire was designed by previous researchers in order to determine the prevalence rate of MSDs in multiple regions of the body. NMQ as a screening and surveillance tool is repeatable, sensitive and useful for assessing musculoskeletal disorders in a wide range of occupational groups. NMQ quantifies musculoskeletal pain and activity restriction in 9 body parts which are Neck, Shoulders, Elbows, Wrists/Hands, Upper Back, Lower Back, Hips/Thighs, Knees, and Ankles/Feet) [25, 26]. The validity and reliability of this questionnaire in various languages such as Persian has been confirmed [10 , 28].

C) REBA 3 : This method is one of the well-known assessment methods of body posture for occupations in which workers have a static, dynamic and or changing status or have obvious changes in body posture during working hours. In evaluating the body postures by this method, different regions of the body were divided into two groups: A (included the trunk, neck and legs) and B (included the upper arms, lower arms and wrist). Group A included a total of 60 possible posture combinations for the trunk, neck and legs. The combined score of body part postures in group A, according to the posture of each body part varies from 1 to 9. The Force score is added to the score of group A body parts in order to calculate score A. Group B had a total of 36 possible posture combinations for the upper arms, lower arms and wrists. The combined score of body postures in group B according to the posture of each body part varies from 1 to 9. The Hand Coupling’ score is added to the score of group B body parts in order to calculate score B. Scores A and B are combined and result in score C. Then, the activity score will be added to score C that results in the final REBA score. Based on the final score, the priority levels of corrective measures were specified. An acceptable reliability and validity for REBA has been reported in many studies. The inter-observer agreement was between 62 and 85% [29 –31]. REBA was developed to assess job posture in various activities. This method is very general and has acceptable sensitivity and provides the ability for rapid assessment of the entire body [32, 33]. Main goals of the REBA method is to design and develop a highly sensitive method for analyzing postures in various jobs and tasks, classifying the body into different coding regions based on motion plates, scoring the muscle’s activities for dynamic and static postures or unsustainable postures.

Among the rubber factory workers, every job is made up of a variety of tasks. Therefore, the first step of job evaluation was to break down each job into tasks. All tasks were recorded by a trained occupational health practitioner. The worst personal body postures or the working posture with the highest frequency were selected and pictures were taken of each task and were later interpreted according to the method guidelines [30]. The final scores were then computed by researcher consensus and the final risk level was identified.

2.3 Ethical considerations and data collection

The present study was approved by the ethics committee of Kerman University of Medical Sciences (Ethics Code: IR.KMU.REC.1395.337). In order to respect the rights, principles and ethical considerations, the study purpose and use of information was explained to the subjects and after informed consent, the workers answered the questionnaires and then their work stations were evaluated. They were also assured that the data was only used for research purposes, and their information was kept confidential. Participants had the right to withdraw from the study whenever they wanted. The questionnaires were distributed at the beginning of the workday by one researcher and after being filled out by the worker himself, they were collected on the same day or 24 hours later.

2.4 Data analysis

Data analysis was done using SPSS16 and descriptive statistics. In order to assess the relation between the existence of MSDs in different body regions and demographics, also organizational factors and work station ergonomic features, binary logistic backward regression was used. The odds ratios (OR) were calculated, and a 95% confidence interval (95% CI) was estimated. A multiple logistic regression model by backward stepwise method was used to assess the independent work-related risk factors.

3 Results

In this study, all of the workers were male (100%). The mean age and work history of the workers were 34.54±6.36 and 12.34±6.28 years respectively, 96.6% of them were married and 51.1% were in the age group of 26–40 years (Table 1).

Results of the Nordic questionnaire showed that the highest prevalence of MSDs in the last twelve-month period was related to the lower back region with a prevalence rate of 62.1%, and the lowest in this period was related to the hips/thighs regions (Table 2).

Table 1
Demographic and organizational characteristics among rubber industry workers, 2014

Variable Classification Frequency Mean±Standard

(percent) deviation

Age (year)

<25 11 (5.3) 34.54±6.36

26–40 112 (54.4)

>40 83 (40.3)

Work history(year)

<10 81 (39.5) 12.34±6.28

11–20 86 (41.5)

>21 39 (19)

BMI (kg/m²)

underweight 8 (3.8) 25.39±3.55

normal weight 97 (47.1)

overweight 85 (41.3)

obese 16 (7.8)

Work Shift

Rotational 38 (18.4)

Stable 168 (81.6)

Marital status

Married 199 (96.6)

Single 7 (3.4)

Education level

High school 180 (87.4)

post-high school education 26 (12.6)

Variable	Classification	Frequency	Mean±Standard
Age (year)
	<25	11 (5.3)	34.54±6.36
	26–40	112 (54.4)
	>40	83 (40.3)
Work history(year)
	<10	81 (39.5)	12.34±6.28
	11–20	86 (41.5)
	>21	39 (19)
BMI (kg/m²)
	underweight	8 (3.8)	25.39±3.55
	normal weight	97 (47.1)
	overweight	85 (41.3)
	obese	16 (7.8)
Work Shift
	Rotational	38 (18.4)
	Stable	168 (81.6)
Marital status
	Married	199 (96.6)
	Single	7 (3.4)
Education level
	High school	180 (87.4)
	post-high school education	26 (12.6)

Table 2

The frequency of MSDs in the past 12 months in different body regions among rubber industry workers, 2014

Different Body Regions	MSDs frequency(percent)
Neck	110 (53.4)
Shoulders	107 (51.9)
Elbows	74 (35.9)
Wrists/Hands	95 (46.1)
Upper Back	116 (56.3)
Lower Back	127 (62.1)
Hips/Thighs	73 (35.4)
Knees	105 (50.9)
Ankles/Feet	97 (47.1)

Based on REBA posture assessment results, most of the subjects (35.4%) were on the medium risk level and corrective measures are necessary at this level (Table 3).

In the present study, logistic regression was used to identify the predictive variables for MSDs in multiple regions of the body. Based on the results, a significant correlation (p < 0.05) was observed between pain in different regions of the body and the final REBA score. Therefore, for one-unit increase in the final REBA score, the risk or complaint of neck and low back pain increased by 48.5 and 37.1%, respectively (Table 4).

Table 3

The results of postural assessment by REBA method among rubber industry workers, 2014

Method	Action	REBA	Risk	Frequency	Action (including
	level	score	level	(percent)	further assessment)
REBA	0	1	Negligible	0	Not necessary
	1	2–3	Low	38 (18.4)	May be necessary
	2	4–7	Medium	73 (35.4)	Necessary
	3	8–10	High	49 (23.8)	Necessary soon
	4	11–15	Very high	46 (22.3)	Necessary NOW

Table 4

The factors affecting the occurrence of MSDs in different body regions among rubber industry workers, 2014

Body regions	Variable	Logistic regression model
		OR	CI 95%	P-Value
Neck
	REBA score (awkward posture)	1.485	1.323–2.667	<0.001
	Work history (year)	1.061	1.007–3.119	0.023
Shoulders
	REBA score (awkward posture)	1.151	1.052–2.260	0.002
	Work history (year)	1.069	1.012–2.213	0.049
	Age (year)	1.141	1.016–3.225	0.012
Elbows
	REBA score (awkward posture)	1.107	1.009–2.213	0.031
	Work history (year)	1.084	1.983–2.232	0.029
Wrists/Hands
	Age (year)	1.073	1.134–3.073	0.042
Upper Back
	REBA score (awkward posture)	1.140	1.044–3.251	.004
	BMI (kg/m²)	1.111	1.017–3.225	0.032
Lower Back
	REBA score (awkward posture)	1.371	1.221–2.535	0.021
	BMI (kg/m²)	1.267	1.126–4.426	0.014
	Work history (year)	1.082	1.004–3.129	0.043
Hips/Thighs
	REBA score (awkward posture)	1.101	1.007–2.205	0.035
	Work history (year)	1.088	1.036–2.141	0.004
Knees
	Work history (year)	1.321	1.009–2.175	0.022
Ankles/Feet
	REBA score (awkward posture)	1.046	1.064–1.167	0.048
	BMI (kg/m²)	1.228	1.103–1.366	0.009
	Work history (year)	1.136	1.076–1.199	<0.001

4 Discussion

Based on the results of this study, the highest prevalence rate of MSDs (62.1%) in the last twelve-month period was related to the lower back region (Table 2), which is consistent with the results of other studies in the rubber industry [22, 23]. It should be noted that, this rate of MSDs among workers, was more than its rate in the general population of Iran [22] and this could be a reason for more attention to MSDs in rubber industry workers.

The high prevalence rate of low back pain (LBP) can be attributed to poor working conditions in the rubber industry such as improper body posture during the work hours, manual load handling at short time intervals, repetitive low back turning and bending, pushing heavy objects and long-term work in standing, kneeling and squatting postures [15 , 23]. Each of these factors increases the risk of LBP among workers of this industry.

Results of the MSDs risk evaluation by the REBA method showed that most employees (35.4%) were at medium risk (necessary for corrective measures), and there was a significant relationship between the existence of MSDs in different body regions and the REBA score (Table 3). Interestingly, in another study in the rubber industry in Iran by using the OWAS evaluation method, there was a high percentage of risk that meant a need for immediate changes and corrective actions [22]. One reason for this difference may be related to the different assessment tool used.

Based on the results, a significant relation was observed between the occurrence of MSDs in different regions of the body and the score obtained by the REBA risk assessment method. This indicator was associated with pains in the neck, shoulder, elbow, upper and lower back, thighs/hips and feet/ankles regions and for one-unit increase in REBA final score, the odds ratio of MSDs in the neck, the upper back and lower back region, increased by 48%, 14% and 37.1% respectively (Table 4).

Our results represent the ability of REBA, to predict MSDs in various regions of the body among rubber industry workers (Table 4). As stated before, the REBA risk assessment method was designed to evaluate occupations with unpredictable body postures, static or dynamic and/or jobs in which significant changes occur in body postures [29, 34]. It should also be noted that the REBA evaluation method is a method with proper validity and reliability for evaluating the entire body postures (upper and lower limbs of the body), considering the affective factors such as load/force, load coupling status and type of activity (static/dynamic) [29, 34].

Based on statistical analysis, another important factor affecting the occurrence of MSDs in body regions is work history. Work history was related to the occurrence of MSDs in the neck, shoulders, elbows, lower back (lower region), hips/thighs, knees and ankles/feet regions and for each one unit (year) increase in work history, the risk of pain in the neck, shoulder and lower back regions increased by 6.1%, 6.9% and 8.2% respectively (Table 4).

According to studies, work history has been an effective factor on MSDs. Results of the present study are also in line with findings from other studies [22 , 36].

In this study, there was a significant relation between the existence of MSDs in some regions such as the shoulder and wrist with aging so that with increased age, the risk of wrist and shoulder pains increased as well (Table 4). This finding is similar to the findings of studies conducted by Choobineh et al. in Iran and Mekasawi et al. in Thailand [22, 23].

According to our findings, the prevalence rate of MSDs in the upper limbs of the body gradually and steadily increased from the age of 40 years to 50 years (Table 4). This observation can be caused by factors such as reduced body size, muscle strength and upper extremity access, due to aging [37, 38].

About half of the studied workers (49/1%) were overweight or obese in terms of body mass index (Table 1). According to a study conducted by Leboeuf et al., increase in body weight can be another important factor related to MSDs [39]. Based on our results, body mass index was reported to be related to MSDs. Also, a significant relation was observed between pain in the upper and lower regions of the back and the leg and ankle regions (Table 4).

Results of the present study are consistent with numerous studies performed in this context [13 , 40]. However, it is in conflict with the study conducted by Abedini et al. on 136 workers in the rubber industry. They found no significant relation between body mass index and MSDs [8]. These insignificant results may be because of the study’s small sample size.

The prevalence rate of MSDs in any industry such as rubber manufacturing, in addition to the main occupational factors, can be affected by environmental, personal, organizational as well as managing factors. This may be the reason for the different results seen in various articles. The NMQ questionnaire has some limitations. The experience of the person who is completing the questionnaire can affect the results. Also more serious musculoskeletal disorders or ones that have recently occurred may be recalled more than previous disorders or less severe ones. Meanwhile, the job environment and situation at the time of responding may affect the results. From an epidemiological viewpoint, this questionnaire should rather be used for cross-sectional studies. Other limitations of this study include the lack of reliable objective diagnostic tests for the diagnosis of MSDs and reliance on the statements of workers.

5 Conclusions

Low back pain is the most common type of MSD among rubber factory workers. Most employees in this industry were at medium risk level and this clearly shows the high susceptibility of these workers to MSDs. There was a significant relation between demographic variables (work history, age and body mass index) and MSDs. A significant relation was also observed between MSDs in multiple regions of the body and the REBA risk evaluation method, which confirms the capability of this method in predicting MSDs in different regions. It is recommended that corrective actions be put in place in high-risk workstations (higher than REBA, Level 2).

Conflict of interest

None to report.

Footnotes

Body Mass Index.

Nordic Musculoskeletal Questionnaire.

The Rapid Entire Body Assessment.

References

Osborne

, Blake

, McNamara

, Meredith

, Phelan

, Cunningham

. Musculoskeletal disorders among Irish farmers. Occup Med (Lond) 2010;60(8):598–603.

Bihari

, Kesavachandran

, Pangtey

, Srivastava

, Mathur

. Musculoskeletal pain and its associated risk factors in residents of National Capital Region. Indian Journal of Occupational and Environmental Medicine 2011;15(2):59–63.

Punchihewa

, Gyi

. Reducing work-related Musculoskeletal Disorders (MSDs) through design: Views of ergonomics and design practitioners. Work 2015;53(1):127–42.

Banerjee

, Jadhav

, Bhawalkar

. Limitations of activities in patients with musculoskeletal disorders. Annals of Medical and Health Sciences Research 2012;2(1):5–9.

Storheim

, Zwart

. Musculoskeletal disorders and the Global Burden of Disease study. Annals of the rheumatic diseases 2014;73(6):949–50.

Samaei

, Hasheminejad

, Zolala

. Evaluation of risk factors influencing low back pain in patient transfer tasks. International Journal of Occupational Hygiene 2015;7(2):76–82.

Kinge

, Knudsen

, Skirbekk

, Vollset

. Musculoskeletal disorders in Norway: Prevalence of chronicity and use of primary and specialist health care services. BMC Musculoskeletal Disorders 2015;16(1):1–9.

Abedini

, Choobineh

, Soltanzadeh

, Gholami

, Amiri

, Hashyani

. Ergonomic risk assessment of lifting activities: A case study in a rubber industry. Jundishapur Journal of Health Sciences 2013;5(1):9–15.

Yasobant

, Rajkumar

. Work-related musculoskeletal disorders among health care professionals: A cross-sectional assessment of risk factors in a tertiary hospital, India. Indian Journal of Occupational and Environmental Medicine 2014;18(2):75–81.

10.

Choobineh

, Lahmi

, Shahnavaz

, Khani Jazani

, Hosseini

. Musculoskeletal symptoms as related to ergonomic factors in Iranian hand-woven carpet industry and general guidelines for workstation design. International Journal of Occupational Safety and Ergonomics 2004;10(2):157–68.

11.

Roquelaure

. Workplace intervention and musculoskeletal disorders: The need to develop research on implementation strategy. Occupational and Environmental Medicine 2008;65(1):4–5.

12.

Gallagher

, editor . Impact of Loading and Rest Intervals on Muscle Inflammation. Proceedings of the Human Factors and Ergonomics Society 58th Annual Meeting: 2014:SAGE Publications.

13.

da Costa

, Vieira

. Risk factors for work-related musculoskeletal disorders: A systematic review of recent longitudinal studies. American Journal of Industrial Medicine 2010;53(3):285–323.

14.

Bugajska

, Żołnierczyk-Zreda

, Jędryka-Góral

, Gasik

, Hildt-Ciupińska

, Malińska

, et al. Psychological factors at work and musculoskeletal disorders: A oneyear prospective study. Rheumatology International 2013;33(12):75–83.

15.

Reid

, Bush

, Karwowski

, Durrani

. Occupational postural activity and lower extremity discomfort: A review. International Journal of Industrial Ergonomics 2010;40(3):247–56.

16.

Choobineh

, Sani

, Rohani

, Pour Gangi

, Neghab

. Perceived demands and musculoskeletal symptoms among employees of an Iranian petrochemical industry. International Journal of Industrial Ergonomics 2009;39(5):766–70.

17.

Scuffham

, Legg

, Firth

, Stevenson

. Prevalence and risk factors associated with musculoskeletal discomfort in New Zealand veterinarians. Applied Ergonomics 2010;41(3):444–53.

18.

Yeung

, Genaidy

, Deddens

, Alhemood

, Leung

. Prevalence of musculoskeletal symptoms in single and multiple body regions and effects of perceived risk of injury among manual handling workers. Spine 2002;27(19):2166–72.

19.

Tirgar

, Javanshir

, Talebian

, Amini

, Parhiz

. Musculoskeletal disorders among a group of Iranian general dental practitioners. Journal of Back and Musculoskeletal Rehabilitation 2014;28(4):755–9.

20.

Abaraogu

, Odebiyi

, Olawale

. Association between postures and work-related musculoskeletal discomforts (WRMD) among beverage bottling workers. Work 2016;54(1):1–7.

21.

IARC. Occupational exposures in the rubber-manufacturing industry:International Agency for Research on Cancer: 2012 [cited 2012]. Available from: https://www.ncbi.nlm.nih.gov/

22.

Choobineh

, Tabatabaei

, Mokhtarzadeh

, Salehi

. Musculoskeletal problems among workers of an Iranian rubber factory. Journal of Occupational Health 2007;49(5):418–23.

23.

Meksawi

, Tangtrakulwanich

, Chongsuvivatwong

. Musculoskeletal problems and ergonomic risk assessment in rubber tappers: A community-based study in southern Thailand. International Journal of Industrial Ergonomics 2012;42(1):129–35.

24.

Anuurad

, Shiwaku

, Nogi

, Kitajima

, Enkhmaa

, Shimono

, et al. The new BMI criteria for asians by the regional office for thewestern pacific region of WHO aresuitable for screening of overweight to prevent metabolic syndromein elder Japanese workers. Journal of Occupational Health 2003;45(6):335–43.

25.

Aghilinejad

, Azar

, Ghasemi

, Dehghan

, Mokamelkhah

. An ergonomic intervention to reduce musculoskeletal discomfort among semiconductor assembly workers. Work 2016;54(2):445–50.

26.

Crawford

. The Nordic musculoskeletal questionnaire. Occupational Medicine 2007;57(4):300.

27.

Kuorinka

, Jonsson

, Kilbom

, Vinterberg

, Biering-Sørensen

, Andersson

, et al. Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms. Applied Ergonomics 1987;18(3):233–7.

28.

Namnik

, Negahban

, Salehi

, Shafizadeh

, Tabib

. Validity and reliability of persian version of the specific nordic questionnaire in Iranian industrial workers. Work 2016;(Preprint):1–7.

29.

Hignett

, McAtamney

. Rapid entire body assessment (REBA). Applied Ergonomics 2000;31(2):201–5.

30.

Middlesworth

. A Step-by-Step Guide Rapid Entire Body Assessment[Internet]: Ergonomics Plus, 2015 oct, 17 [cited 2015 Dec, 13]. Available from: http://www.ergo-plus.com/wp-content/uploads/REBA-A-Step-by-Step-Guide.pdf

31.

Motamedzade

, Ashuri

, Golmohammadi

, Mahjub

. Comparison of ergonomic risk assessment outputs from rapid entire body assessment and quick exposure check in an engine oil company. Journal of Research in Health Sciences 2011;11(1):26–32.

32.

Maldonado-Macías

, Realyvásquez

, Hernández

, García-Alcaraz

. Ergonomic assessment for the task ofrepairing computers in a manufacturing company: A case study. Work 2015;52(2):393–405.

33.

Musavi

, Saremi

, Alibabaei

. The effect of assembly line redesign based on engineering techniques on productivity and ergonomics factors. Iran Occupational Health 2016;12(6):1–15.

34.

Moussavi-Najarkola

, Mirzaei

. Assessment of Musculoskeletal Loads of Electric Factory Workers by Rapid Entire Body Assessment. Health Scope 2012;1(2):71–9.

35.

Côté

, van der Velde

, Cassidy

, Carroll

, Hogg-Johnson

, Holm

, et al. The burden and determinants of neck pain in workers. European Spine Journal 2008;17(1):60–74.

36.

Burdorf

, Sorock

. Positive and negative evidence of risk factors for back disorders. Scandinavian Journal of Work, Environment & Health 1997;23(4):243–56.

37.

Kostova

, Koleva

. Back disorders (low back pain, cervicobrachial and lumbosacral radicular syndromes) and some related risk factors. Journal of the Neurological Sciences 2001;192(1):17–25.

38.

Carter

, Banister

. Musculoskeletal problems in VDT work: A review. Ergonomics 1994;37(10):1623–48.

39.

Leboeuf-Yde

. Body weight and low back pain: A systematic literature review of 56 journal articles reporting on 65 epidemiologic studies. Spine 2000;25(2):226–37.

40.

Wearing

, Hennig

, Byrne

, Steele

, Hills

. Musculoskeletal disorders associated with obesity: A biomechanical perspective. Obesity Reviews 2006;7(3):239–50.