Table 1: Prevalence of Job Strain among View Screen Workers according to the Karasek model

Decision latitude
Psychological Demand	High n (%)	Low n (%)	Total
High	110 (48.9)	115 (51.1)	225
Low	13 (41.9)	18 (58.1)	31
Total	123 (48.0)	133 (52.0)	256

Table 2: Prevalence of Iso Strain among View Screen Workers according to the Karasek model

Job strain of Karasek
Social support	Yes	No	Total
Low	33 (56.9%)	25 (43.1%)	58
High	82 (41.4%)	116 (58.6%)	198
Total	115 (44.9%)	141 (55.1%)	256

Table 3: Distribution of View Screen Workers according to the location of MSDs

MSDs
		Yes n(%)	No n(%)
Neck		179 (69.9)	77 (30.1)
Back	Down	198 (77.3)	58 (22.7)
	Top	180 (70.3)	76 (29.7)
Shoulder	Right	118 (46.1)	138 (53.9)
	Left	89 (34.8)	167 (65.2)
Elbow	Right	53 (20.7)	203 (79.3)
	Left	43 (16.8)	213 (83.2)
Wrist	Right	117 (45.7)	139 (54.3)
	Left	67 (26.2)	189 (73.8)

Factors associated with the occurrence of MSDs

The main risk factors associated with MSDs among the workers surveyed during the study were: The use of a keyboard in poor condition (p=0.028), the use of corrective glasses (p=0.048) the female sex (p=0.039), and the subjective symptoms of stress: anxiety (p=0.031), cardiovascular disorders (p=0.001), gastrointestinal ulcer type disorders (p=0.008), anxiety (p=0.018), “Job strain” assessed based on decisional latitude and psychological demand (Tables 4 and 5).

Discussion

Though this is first study which estimated interleukin levels among those handling toxic gas like phosgene, there are some limitations in the study. The study involves a smaller sample size which was further reduced on categorization. This might have resulted in non-significant difference in mean levels according to study variables. Though the area monitoring of the workplace revealed that the phosgene exposure was within the international permissible level still the personal monitoring of toxic gas level would have given more appropriate dose response relationship. The most represented age group was that of participants aged 30-39 (61.3%). The mean age of the participants was 37 ± 7.1 years. This is a relatively young population. This is justified by the fact that the Beninese population is characterized by its youth. Indeed, according to the age pyramid of Benin, people aged 14- 64 years represent 54.3% [14]. Several studies have also found similar results. This is the case with that carried out by Odebiyi et al. among telephone workers in Nigeria [9], by Nawal et al. among computer users in the workplace in Morocco [15], and that carried out by Basu et al. with display screen users in India [16]. The majority of our study population is male (60.5%). This observation is the same in the work carried out by M Maduagwu et al. in Nigeria, Nawal et al. in Morocco and those of Basu et al. in India on bank workers, where males made up 76.55%, 55.08%, and 54.4% of the study population, respectively [15-17]. On the other hand, studies carried out in Ethiopia and Brazil respectively by Dagne et al. Rocha et al. still in the banking sector find a predominance of women in their study population [8,18]. The prevalence of MSDs in our study is very high and was 93.1%. This prevalence was similar to that found by Seknadji et al. in Morocco and Basu et al. in India in their study on MSDs among computer users where the prevalence of MSDs was also high, respectively 93% and 90.78% [15,16]. But it was higher than that found by Odebiyi et al. in Nigeria (65.2%) and by Abledu et al. in Ghana (83.5%) [9,19]. This difference could be explained by the fact that those two studies were carried out only with bank workers, unlike ours which covered in addition to bank workers, workers from other sectors such as insurance, banking and telecommunication. MSDs involving the spine (neck, upper back, lower back) were the most frequent and the lumbar spine was the region most affected. The prevalence of MSDs of the neck, upper and lower back was 69.9%, 70.3% and 77.3%, respectively. These results were similar to those found by Abledu et al. in Ghana where the spine was also the most affected region with an MSD prevalence of the neck, upper and lower back of 47.4%, 61.7%, and 64.8% [19]. They were also similar to the results of Dagne et al. in Ethiopia, among bank workers where the lumbar spine was the most affected region with a prevalence of 54.3% [18]. The same observation was made in Kuwait in the work of Alkrouf et al. in the banking sector (51.1%) [20]. As for the upper limbs, they were disproportionately affected with a predominance of damage to the right side. In the right shoulder, elbow, and wrist, the prevalence of MSDs was 46.1%, 20.7% and 45.7%, respectively. In contrast to the left side where the prevalence of MSDs was lower, was respectively 34.8%, 16.8% and 26.2%.

This predominance of damage on the right side is explained by the fact that almost all of the study population was of right laterality (94.5%). Also, the shoulder was the most affected area regardless of the side. Some studies were in the same direction, such as those by Dagne et al. in Ethiopia, Abledu et al. in Ghana, Maduagwu et al. in Nigeria and Rocha et al. in Brazil among bank workers, where the shoulder was also the most affected upper limb region with a respective prevalence of 40.9%, 37.4%, 46% and 43%[8,17,19]. In our study, female workers were at greater risk of developing upper back MSDs. The same observation has been made by several other authors. This is the case with Lompo et al. in Ouagadougou, Abledu et al. in Ghana [19,21]. This association between the female sex and MSDs could be justified by the fact that women are most often assigned to perform repetitive tasks at high speed [22]. In addition, it cannot be overlooked that in addition to their professional responsibilities, women generally take care of household chores, thus straining their musculoskeletal structures more frequently. Also, using a keyboard in poor condition was a risk factor for neck MSD. Gerr et al. in the United States found similar results in their study on the association between keyboard use and MSDs [23]. Indeed, the use of a keyboard in bad condition (keys too hard or too sensitive) causes typing errors during the text entry, which leads the worker to make a pronounced tilt of the head and the trunk to better visualize his keyboard. This inclination is associated with a significant flexion of the neck and therefore a shortening of the eye screen distance. The use of corrective lenses was also identified as a risk factor for neck MSD (p=0.048). Similar results were found by Pawalia et al. in India [24]. This association between the use of corrective lenses and the occurrence of MSDs could be explained by the incorrect adjustment of the viewing screen depending on the type of corrective lenses used. This forces the user to maintain prolonged extension or flexion of the neck (depending on the type of corrective lenses) while using their screen. The muscle fatigue that follows favours the occurrence of MSDs of the neck [24]. Finally, stress at work was a risk factor for MSDs. Stress is commonly described in the literature as a risk factor for MSDs, and the results of our study support this [25]. Symptoms of stress such as cardiovascular disorders (p<0.001), gastrointestinal disorders (p=0.008), anxiety (p=0.031) and anxiety (p=0.035) were all identified as risk factors of TMS in our study. The same is true in other studies carried out on MSDs such as that of Griffiths et al. in Australia and Dagne et al. in Ethiopia [18,26]. This association between stress and MSDs is explained by the fact that certain stressful working conditions are associated with increased muscle tension, thus facilitating the onset of MSDs [27].

Conclusion

The prevalence of MSDs among workers on display screens in Benin in 2020 was high (93%), with a predominance for low back pain.

For the female, the use of corrective glasses, the use of a bad keyboard condition and stress were all risk factors for MSDs.

The implementation of adequate measures taking into account compliance with ergonomic standards, and stress management in the workplace could help reduce the occurrence of those MSDs.

Acknowledgement

We thank all the study participants and the staff.

Competiting Interests

The authors declare no competing interests.

Funding

Any.

References

1. Lasfargues G. Periarticular overuse pathology of the upper limbs: Musculoskeletal disorders in the workplace 2003.
2. Aptel M, Aublet-Cuvelier A, Cnockaert JC. Work-related musculoskeletal disorders of the upper limb. Joint Bone Spine 2002; 69(6): 546-55.
3. Jensen C, Finsen L, Sogaard K. Musculoskeletal symptoms and duration of computer and mouse use. Int. J. Ind. Ergon 2002; 30(4): 265-75.
4. Luttman A, Jager M, Griefahn B. Prevention of musculoskeletal disorders in the workplace 2004.
5. Clarke TC, Nahin RL, Barnes PM, Stussman BJ. Use of complementary health approaches for musculoskeletal pain disorders among adults: United States. Natl Health Stat Report 2016; 98: 1-12.
6. Arcand R. Health surveillance in the workplace in Quebec. Bull Epidemiol Hebd 2006; 40: 317-19.
7. Driscoll RJ, Tubbs RL, Habes DJ. Health Hazard Evaluation Report 97-0137-3026 New York City Police Department Police Communications Section New York 2007; 1-41.
8. Rocha LE, Glina DMR, Marinho MDF, Nakasato D. Risk factors for musculoskeletal symptoms among call center operators of a bank in Sao Paulo, Brazil. Ind Health 2005; 43(4): 637-646.
9. Odebiyi DO, Akanle OT, Akinbo SR. Prevalence and impact of work-related musculoskeletal disorders on job performance of call center operators in Nigeria. Int J Occup Environ Med 2016; 7(2): 98-106.
10. Zomalheto X, Ayelo P, Lawin H. Musculoskeletal disorders related to computer screen work in the workplace in Benin. Int. J. Med. Sci 2015; 17: 114-17.
11. Bevan S. Economic impact of musculoskeletal disorders (MSDs) on work in Europe. Best Pract Res Clin Rheumatol 2015; 29(3): 356-73.
12. Aptel M, Lafaurie S, Tronchet L, Atain-Kouadio JJ. OREGE: A simple tool for the assessment of biomechanical risk factors for MSDs in the upper limb 2000.
13. Niedhammer I, Chastang JF, Gendrey L, David S,Degioanni S. Psychometric properties of the french version of the karasek job content questionnaire: A study of the scales of decision latitude, psychological demands, social support, and physical demands in the gazel cohort. Int Arch Occup Environ Health 2002; 75: 129-144.
14. Benin-Age pyramid 2018.
15. Seknaji N, Rachidi W, Hassoune S. Prevalence of neck pain and upper limb pain among computer users in the workplace in Casablanca (Morocco). Pan Afr Med J. 2013; 14: 1-8.
16. Basu R, Dasgupta A, Ghosal G. Musculo-Skeletal disorders among video display terminal users: A cross-sectional study in a software company, kolkata. J of Clinl and Digstic Rsrch 2014; 8: JC01-JC04.
17. M Maduagwu S. Prevalence and patterns of work-related musculoskeletal disorders among bankers in Maiduguri, Northeast Nigeria. Occup Med Health Aff 2014; 2(3): 1-6.
18. Dagne D, Abebe SM, Getachew A. Work-related musculoskeletal disorders and associated factors among bank workers in Addis Ababa, Ethiopia: A cross-sectional study. Environ Health Prev Med 2020 ; 25(33): 2-8.
19. Abledu J, Abledu G. Multiple logistic regression analysis of predictors of Musculoskeletal Disorders and disability among bank workers in Kumasi, Ghana. J Ergonomics 2012; 2(4):1-4.
20. Akrouf QAS, Crawford JO, Al-Shatti AS, Kamel MI . Musculoskeletal disorders among bank office workers in Kuwait. East Mediterr Health J 2010; 16: 94-100.
21. Lompo MS, Congo M, Owona JM, Tiendrebogo J, Ouedraogo AF, et al. Factors associated with Tendinopathies of the hand among bank employees in Ouagadougou. Jr of Med and Phar2019; 9: 1001-08.
22. Wolf JM, Cannada L, Heest AVE, O Connor MI, Ladd Al. Male and female differences in musculoskeletal disease. J Am Acad Orthop Surg 2015; 23: 339-47.
23. Gerr F, Marcus M, Monteilh C. Epidemiology of musculoskeletal disorders among computer users: Lesson learned from the role of posture and keyboard use. J Electromyogr Kinesiol 2004; 14: 25-31.
24. Pawalia A, Joshi S, Yadav V. Can your eye glasses lead to future neck pain and disability? Relation of eyeglasses with neck muscle endurance and posture. Int J of Comnty Mdce Public Hlth 2019; 6: 2402-07.
25. Musculoskeletal Disorders and the workplace: Low back and Upper Extremities 2001.
26. Griffiths KL, Mackey MG, Adamson BJ. The impact of a computerized work environment on professional Occupational groups and behavioural and physiological risk factors for musculoskeletal symptoms: A Literature Review. J Occup Rehabil 2007; 17: 743-65.
27. Malchaire JBM. Occupational heat stress assessment by the predicted heat strain model. Ind Health 2006; 44: 380-387.

Copyright: © 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution NonCommercial ShareAlike 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/). This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.