Prevalence and severity of carpal tunnel syndrome symptoms among Iranian butchers and their association with occupational risk factors: Implications for ergonomic interventions

Abstract

BACKGROUND:

Carpal tunnel syndrome (CTS) is a common disorder among occupations where upper extremities are actively involved in. Many occupational and non-occupational risk factors may contribute to this disorder. Knowledge regarding occupational risk factors can guide us to implement interventional programs.

OBJECTIVE:

The aim of the present study was to assess the prevalence and severity of CTS symptoms among butchers and their association with several occupational and non-occupational risk factors.

METHODS:

In this study, 152 butchers in Hamadan, Iran, were examined. The Boston Carpal Tunnel Syndrome Questionnaire (BCTQ) was used to investigate the severity of CTS symptoms among the individuals. Several risk factors such as body mass index (BMI), wrist ratio, active working hours per day, working experience, and the ergonomic quality of hand tools used by butchers were also investigated. Statistical tests such as the crude and robust regression were used to analyze the data.

RESULTS:

The prevalence of moderate and mild symptoms of CTS were 7% and 54%, respectively. Moreover, 39% of the butchers were free of CTS symptoms. Crude regression analyses showed that the severity of CTS symptoms had a significant relationship with age, work experience, active working hours per day, working hours per week, and ergonomic quality of the hand tools (p value <0.05). There was no significant relationship between the severity of CTS symptoms and wrist ratio and BMI. Results of the robust regression analysis showed a significant relationship between the severity of CTS symptoms with experience, active working hours, and quality of the hand tools.

CONCLUSION:

Occupational risk factors such as working experience, active working hours per day, and the ergonomic quality of hand tools are significant risk factors of CTS symptoms among butchers. Slippery handle is the main non-ergonomic feature of knives and cleavers used by butchers. There was no association between BMI and wrist ratio with CTS symptoms.

Keywords

Carpal tunnel syndrome upper extremity meat products ergonomics occupational risk factors butchers

1 Introduction

Work-related musculoskeletal disorders (WMSDs) are one of the most commonly occurring occupational diseases in the world. These disorders are associated with many undesired social and economic consequences for the affected employees and their families [1, 2]. WMSDs can involve various parts of the body, including muscles, bones, ligaments, tendons, veins and nerves. The prevalence of these disorders varies in different parts of the body. However, the likelihood of these injuries is higher in the upper limbs, which is mainly because of their frequent usage in performing job-related activities [3]. One of the most susceptible parts of the upper limbs is the wrist region, particularly the median nerve passing through a space under the wrist formed by connective tissues (transversal ligament of the wrist or flexor of the retinaculum) and wrist bones [3, 4].

Carpal tunnel syndrome (CTS) is one of the most commonly diagnosed neuropathies and the most common peripheral mono neuropathy caused by median nerve injury in the wrists [4]. Despite the high prevalence of the disease, there is still no consensus on its risk factors. Different studies have identified various risk factors in this regard. Van Rijn et al. [4], in a literature review study in 2009, found that meat and fish processing jobs, work in chainsaws and electronic assembly work had the highest risk of CTS. The study found that vibration, long working hours, force and repetitive movements are the main risk factors of CTS. These findings were confirmed by Newington et al. [5]. In a meta-analysis study, Barcenilla et al. [6] investigated studies from 1980 to 2009 and found that vibration, force and repetitive movements are main occupation are risk factors of CTS. In the study carried out by You et al. [7], it became clear that the change in wrist postures (extension and flexion) doubles the risk of CTS. In contrast, Kapellusch et al. [8] did not find any evidence suggesting hand/wrist posture as an independent risk factor for CTS. In 2018, Pramchoo et al. [9] conducted a study among rubber tappers and found that age, too low and too high BMI, gender (women are more vulnerable than men), underlying diseases (such as diabetes and hypertension), and work at a height below the knee can increase the risk of CTS. In a prospective multicenter study conducted by Harris-Adamson et al. [10] among workers from various industries in the United States, it was found that the maximum exerted force, the frequency of repetitions, and the percentage of working time during which force is actively exerted can increase the risk of CTS. In this study, no significant relationship was found between CTS risk and the frequency of hand movements, the percentage of time applied by the hand and the posture of the wrist. In the study conducted by El-Helaly et al. [11] among laboratory technicians, it was found that there was a significant relationship between the incidence of CTS and sex (women are more vulnerable than men), manual pressure, pipetting, repetitive tasks, and use of non-adjustable chairs or tables. It was also reported that the increase of work experience is associated with a higher risk of getting CTS. Wrist ratio (wrist depth/wrist width) is another controversial risk factor of CTS. However, recent studies have reported that a high wrist ratio or square shaped wrist increases the risk of CTS [12, 13].

Considering the above-mentioned issues, it can be inferred that, on one hand, the risk of CTS is high among occupations in which hand tools are continuously used [14] and, on the other hand, previous studies have rarely taken into account the ergonomic quality of hand tools used by employees and their effects on CTS. Therefore, the aim of the present study was to assess the effect of this factor as well as other occupational risk factors on the severity of CTS symptoms among butchers, an occupation for which hand tools are consistently used.

2 Materials and methods

2.1 Job description

In general, the main tasks of a butcher is to convert large pieces of meat received from slaughterhouses into smaller pieces and then directly sell them to the end consumers. In this occupation, most activities are carried out with the wrist and fingers of the dominant hand, and hand tools such as knives and cleavers (as demonstrated in Fig. 1) are consistently used. In general, the main workload is on the wrist and it is therefore postulated that the risk of CTS would be high. Some previous studies have stated that CTS is a concern among butchers [15].

Fig. 1

Various types of knives and cleavers used by butchers.

2.2 Participants

In this study, 152 butchers in Hamadan, Iran, were examined. All participants were selected in coordination with the Hamadan butchers’ union. Initially speaking with the butchers, they were informed about the objectives of the study, and if they agreed, they were given a form entitled “Conscious Consent Form” to sign. This study was approved by the Ethics Committee of Hamadan University of Medical Sciences (Ethic Code: IR.UMSHA.REC.1397.212). It should be noted that butchers with diabetes and hyperthyroidism were not included in the study. The reason for this was that there are credible evidences suggesting that such diseases are risk factors for CTS [16, 17]. It can also be said that musculoskeletal disorders are due to their accumulated nature in the long term, which is why people with an experience of less than one year were also not included in the study.

2.3 Assessment of the severity of carpal tunnel syndrome symptoms

The Boston Carpal Tunnel Syndrome Questionnaire (BCTQ) was used to investigate the severity of CTS symptoms among the individuals. Developed by Levine et al. [18] in 1993, BCTQ is recognized as a reliable tool for measuring the severity of CTS symptoms. The questionnaire consists of two parts. The first part is called “symptom severity scale”, containing 11 items regarding pain, numbness, weakness, and tingling in the wrists and fingers during work and at night during normal life activities. The second part is called “functional status scale”, containing eight items regarding difficulties in performing normal daily activities such as writing, bathing, dressing, holding, gripping and so on. Each item receives a score ranging from 1 to 5, a higher score is indicative of more severe CTS symptoms.

Studies conducted on the reliability and validity of this questionnaire have reported that there is an acceptable association between the results of BCTQ and those of electrodiagnostic tests in which conductivity of the median nerve is evaluated and is regarded as the gold standard for measuring the severity of CTS [19 –21]. This tool has been translated into Persian by Forouzanfar et al. in 2015 [22], and its validity and reliability have been approved. In the present study, we used this Persian version of the BCTQ.

2.4 Assessment of the ergonomic quality of hand tools

The ergonomic quality of hand tools is dependent on many factors. The handles of the hand tools must be designed in such a way to create a proper grip, thereby increasing task performance and reducing discomfort [23]. The handle diameter should be in an optimum range and handle length should be higher than palm breadth in order to produce the maximum grip strength. The optimum diameter of handles differs based on the various types of torques used and work orientation [24]. However, the best diameter is that in which a quite good grip is possible. In general, hand tools used for power applications should be 30 to 50 mm in diameter and have a handle length of more than 100 mm [25 –28]. Going away from the optimum range of handle diameter would force the muscle to implement more effort to produce the required force which predisposes the muscle and associated tissues to WMSDs [29]. Furthermore, the handle should be free of any sharp edges to prevent problems associated with contact stress. The handle should not be slippery and a good friction coefficient should be provided between the hand and the handle [27]. The weight of the hand tool, material of the handle, and cross-sectional shape of the handle are other factors which determine the ergonomic quality of hand tools [30]. Therefore, for assessing ergonomic quality of hand tools, many issues should be taken into account. In 2004, Dababneh et al. [31] developed a method for assessing the ergonomic quality of hand tools by considering all these issues.

In the present study, the method developed by Dababneh et al. [31] was used for assessing the ergonomic quality of hand tools. The method is a checklist containing 16 yes/no items investigating various aspects of a non-power hand tool, including characteristics of the grip surface, physical dimensions of the handle, weight of the tool, and its applicability for both left- and right-handed persons. According to this checklist, each tool receives a score ranging from 0 to 100, and higher values are indicative of a better ergonomic quality of the tool.

The checklist has been translated into Persian and used for assessing the quality of hand tools among the Iranian population in several studies. Motamedzade et al. [32] used it to assess the ergonomic quality of carpet weaving hand tools and Hashemi Nejad et al. [33] used it to develop a comprehensive risk assessment method for ergonomic assessment of furniture manufacturing workshops.

2.5 Demographic and anthropometric variables

Demographic information was collected using a checklist. The checklist was designed to gather information such as age, disease history, experience, and BMI of butchers.

Considering the aim of the study, the required anthropometric dimensions such as palm width, grip diameter, wrist diameter, and wrist ratio were measured. All the measurements were carried out by a trained and experienced ergonomist using a digital caliper (Model: CD-8CS, Mitutoyo, Japan). For assuring the intra-observer reliability of the measurements, the anthropometric dimensions of the first 15 participants were measured twice with a one-week interval between measurements.

2.6 Active working time in a day

During a work shift, butchers do not constantly use their hand tools. In some cases, they are very busy and may use their tools for eight hours or more. These butcher shops are located in regions where high-income people are resided. In contrast, in the regions where low-income citizens normally live, the amount of consumed meat is normally low and butchers are less busy. Therefore, the length of the work shift cannot be indicative of exposure time. Active working time means the time during which the hand tool is actively used. Active working time is nearly constant over time for a butcher. This variable was determined by interviewing the butchers.

2.7 Statistical analyses

In this study, the crude linear regression test was used to examine the association between the severity of CTS symptoms and various potential risk factors. As data were not normally distributed, the robust regression test was used to adjust the effects of confounder variables such as BMI, age, and wrist ratio. Worth mentioning, classical linear regression methods are based on the assumption of normal distribution of data. In the cases that this assumption is not satisfied, the b-coefficients provided by the classical methods are poor and unreliable. To deal with such a situation, the use of robust regression is recommended [34]. All tests were performed using STATA software package (ver.11) at 0.05 level of significance.

3 Results

3.1 Demographic characteristics

The mean age of participants in the study was 42.38 years (ranging from 20 to 73) and their mean work experience was 21.12 years old (ranging from 19.08 to 23.15). The average of active working hours per day of the participants were 5.3 hours (ranging from 4.93 to 5.68). This means that the butchers worked, on average, 5.3 hours per day with their knives or cleavers. The mean BMI of individuals was 26.34 (ranging from 25.60 to 27.08). Moreover, the wrist ratio of the subjects ranged from 0.45 to 0.9, with the mean and standard deviation of 0.63 and 0.08, respectively. The mean palm width of subjects was 96.60 mm (±7.36), ranging from 83 mm to 136 mm and the mean grip diameter was 36.46 mm (±4.94), ranging from 26 mm to 55 mm.

Table 1 summarizes the demographic data of the participants. Based on the results, it was found that the majority of butchers were aged between 35 and 55 years (94 cases, 61.84%). It was also found that the majority of subjects had work experience for over 15 years (95 cases, 62.5%). In most cases, the wrist ratio was less than 0.6 (65 cases, 42.8%). Half of the subjects (77 cases, 50.63%) were overweight and 22 cases (14.5%) were obese.

Table 1
Average score of the Boston Carpal Tunnel Syndrome Questionnaire in different groups of the study

Variable Category N (%) CTS symptoms

Mean (Std. dv)

Age ≤25 8 (5.26) 26.40 (7.47)

25–35 33 (21.71) 26.43 (7.71)

35–55 94 (61.84) 26.48 (7.71)

≥55 17 (11.18) 26.51 (7.47)

total 152 (100) 26.43 (7.71)

Work experience (years) ≤5 19 (12.5) 26.48 (7.71)

5 –10 18 (11.84) 26.43 (7.71)

10–15 20 (13.15) 26.5 (7.67)

≥15 95 (62.5) 26.55 (7.67)

total 152 (100) 26.43 (7.71)

Active working hours per day (h) ≤2 14 (9.21) 26.43 (7.71)

2–5 86 (56.57) 26.53 (7.71)

≥5 52 (34.21) 26.55 (7.67)

total 152 (100) 26.43 (7.71)

Wrist ratio ≤0.6 65 (42.76) 26.43 (7.71)

0.6–0.7 52 (34.21) 26.53 (7.65)

≥0.7 35 (23.02) 26.54 (7.41)

total 152 (100) 26.43 (7.71)

BMI ≤18.5 4 (2.63) 26.74 (7.45)

18.5–23 20 (13.15) 26.47 (7.65)

23–25 30 (19.73) 26.48 (7.71)

25–30 77 (50.63) 26.43 (7.71)

≥30 22 (14.47) 26.48 (7.59)

total 152 (100) 26.43 (7.71)

Variable	Category	N (%)	CTS symptoms
Age	≤25	8 (5.26)	26.40 (7.47)
	25–35	33 (21.71)	26.43 (7.71)
	35–55	94 (61.84)	26.48 (7.71)
	≥55	17 (11.18)	26.51 (7.47)
total	152 (100)	26.43 (7.71)
Work experience (years)	≤5	19 (12.5)	26.48 (7.71)
	5 –10	18 (11.84)	26.43 (7.71)
	10–15	20 (13.15)	26.5 (7.67)
	≥15	95 (62.5)	26.55 (7.67)
	total	152 (100)	26.43 (7.71)
Active working hours per day (h)	≤2	14 (9.21)	26.43 (7.71)
	2–5	86 (56.57)	26.53 (7.71)
	≥5	52 (34.21)	26.55 (7.67)
	total	152 (100)	26.43 (7.71)
Wrist ratio	≤0.6	65 (42.76)	26.43 (7.71)
	0.6–0.7	52 (34.21)	26.53 (7.65)
	≥0.7	35 (23.02)	26.54 (7.41)
	total	152 (100)	26.43 (7.71)
BMI	≤18.5	4 (2.63)	26.74 (7.45)
	18.5–23	20 (13.15)	26.47 (7.65)
	23–25	30 (19.73)	26.48 (7.71)
	25–30	77 (50.63)	26.43 (7.71)
	≥30	22 (14.47)	26.48 (7.59)
	total	152 (100)	26.43 (7.71)

3.2 Prevalence of CTS symptoms

As shown in Fig. 2, 54% of the butchers (82 cases) suffered from mild symptoms of CTS, while 7% of them (11 cases) showed moderate CTS symptoms. Moreover, 39% of them (59 cases) were free of any CTS symptom. None of the subjects in the study had severe or very severe CTS symptoms. It should be noted that the final scoring and classification was done according to the instruction of the BCTQ.

Fig. 2

The severity of the subjects’ CTS symptoms based on the score of the Boston Carpal Tunnel Syndrome Questionnaire.

3.3 Ergonomic quality of hand tools

The scores associated with the ergonomic quality of hand tools are depicted in Fig. 3. As can be seen, all hand tools used by butchers have a score higher than 50, suggesting that all of them meet the basic principles of ergonomics. Furthermore, nearly half of the hand tools had a score ranging from 80 to 90, which is a good and acceptable ergonomic quality. In 2.6% of cases, the ergonomic quality of hand tools had a score higher than 90, which is very desirable. Being slippery was the most prevalent non-ergonomic feature of hand tools investigated in the present study.

Fig. 3

The scores associated with the ergonomic quality of the hand tools.

3.4 Crude regression analysis

Table 2 shows the relationship between the severity of CTS symptoms and the personal and occupational parameters based on the crude regression analyses. Accordingly, the severity of CTS symptoms had a significant relationship with age, work experience, active working hours per day, working hours per week, and ergonomic quality of the hand tool (p value <0.05). There was no significant relationship between the severity of CTS symptoms and wrist ratio and BMI.

Table 2
The relationship between the severity of CTS symptoms and individual and occupational parameters based on the crude test

Variable Coefficient Std. err t p value CI (95% interval)

Age (years) 0.1673 0.0596 2.81 0.006 0.0496 0.2851

Work experience (years) 0.1558 0.0488 3.19 0.002 0.0592 0.2524

Active working hours per day (h) 0.7682 0.2743 2.80 0.006 0.2261 1.3103

Active working hours per week (h) 0.1173 0.0352 3.33 0.001 0.0476 0.1870

Wrist ratio 5.8775 7.7140 0.76 0.447 –9.3646 21.1197

Ergonomic quality score of the hand tools –0.3315 0.0532 –6.22 <0.001 –0.4367 –0.2262

BMI –0.0264 0.1396 –0.19 0.850 –0.3023 0.2494

Variable	Coefficient	Std. err	t	p value	CI (95% interval)
Age (years)	0.1673	0.0596	2.81	0.006	0.0496	0.2851
Work experience (years)	0.1558	0.0488	3.19	0.002	0.0592	0.2524
Active working hours per day (h)	0.7682	0.2743	2.80	0.006	0.2261	1.3103
Active working hours per week (h)	0.1173	0.0352	3.33	0.001	0.0476	0.1870
Wrist ratio	5.8775	7.7140	0.76	0.447	–9.3646	21.1197
Ergonomic quality score of the hand tools	–0.3315	0.0532	–6.22	<0.001	–0.4367	–0.2262
BMI	–0.0264	0.1396	–0.19	0.850	–0.3023	0.2494

3.5 Robust regression analysis

Table 3 shows the results of the robust regression analysis. Variables with no significant relationship in the crude regression analyses were excluded. There was a high correlation between age and experience (correlation coefficient was higher than 0.95), therefore age was also excluded. For the same reason, “active working hours per week” was excluded and “active working hours per day” remained in the robust regression model. The result of this test demonstrated that the relationships of the severity of CTS symptoms with experience, “active working hours per day” and ergonomic quality of the hand tool were significant (p value <0.05).

Table 3
The results of robust regression analysis

Variable Coefficient Std. err t p value CI (95% interval)

Work experience (years) 1.1230 0.4966 2.26 0.025 0.1417 2.1044

Active working hours per day (h) 0.6317 0.2262 2.79 0.006 0.1846 1.0788

Ergonomic quality of the tool –0.2927 0.0529 –5.53 <0.001 –0.3973 –0.1880

Variable	Coefficient	Std. err	t	p value		CI (95% interval)
Work experience (years)	1.1230	0.4966	2.26	0.025	0.1417	2.1044
Active working hours per day (h)	0.6317	0.2262	2.79	0.006	0.1846	1.0788
Ergonomic quality of the tool	–0.2927	0.0529	–5.53	<0.001	–0.3973	–0.1880

4 Discussion

The results of this study showed that 54% of the butchers in Hamadan had mild symptoms of CTS and 7% had moderate CTS symptoms. Therefore, 61% of butchers suffered from CTS symptoms which was higher than that reported in the study by Flack et al. [15], in which the prevalence was reported to be 47%.

The results of crude regression analyses demonstrated that age, experience, active working hours per day, and ergonomic quality of hand tools were the factors with significant associations with the severity of CTS symptoms. In contrast, no significant association was found between wrist ratio and BMI with the severity of CTS symptoms.

The non-significant association between CTS symptoms and the wrist ratio found in the present study is in contradiction with previous studies reporting that people with a square-shaped wrists (wrist ratio higher than 0.69) are more prone to CTS [12, 13]. This can be due to the fact that most participants investigated in the present study had a wrist ratio lower than 0.7, which is far from a square shape. In the other words, most participants in this study had a relatively low wrist ratio which is not a risk factor for CTS.

Previous studies have reported that people with higher BMI are more prone to CTS [35], which may be due to the deposition of fat in the carpal tunnel and thereby causes higher hydrostatic pressure on the median nerve [36]. However, other studies have not found such a significant relationship [37]. The findings of the later studies are in line with those of the present study as we did not find a significant association between BMI and severity of CTS symptoms.

Moreover, the robust regression analysis showed that experience, active working hours per day, and ergonomic quality of hand tools had significant associations with the severity of CTS symptoms. Therefore, these factors should be taken into account in order to prevent CTS among butchers. Experience and active working hours per day are well-known risk factors of CTS [10, 38], because the increase of these factors would result in the rise of exposure time and the number of repetitive actions during a work shift. The relationship between exposure time and the risk of CTS was also demonstrated in a study carried out by Bonfiglioli et al. [39], in which it was revealed that the risk of CTS was higher among full-time operators than part-time counterparts. Moreover, the results are in line with those of El-Helaly et al. [11], in which a significant association was found between work duration and the occurrence of CTS.

In the present study, after adjusting the effects of various factors such as age, experience, and active working hours per day, a significant and negative association was found between ergonomic quality of hand tools and the severity of CTS symptoms. In the other words, as hand tools became more ergonomic, the severity of CTS symptoms decreased. Various factors such as feelings regarding hand comfort and pain during performing a task, required effort, and performance (the time required for completing a task) are reliant on the ergonomic quality of hand tools [25 , 41]. The ergonomic quality of hand tools itself is dependent on many factors. The handle shape, handle diameter, handle surface, and work orientation are all factors to be considered in handle design [23 –28]. The knives and cleavers investigated in the present study were ergonomic in many ways, but they have several deficiencies. For instance, it was observed that the CTS symptoms are more severe among butchers who used knives with slippery handles. Because they tend to slip out of the hand, hand tools with slippery handles are difficult to grasp and require a higher level of grip forces [42, 43]. Higher grip forces can damage the palm skin and other relevant tissues such as nerves and muscles. There are several ways through which this problem can be avoided. Bisht and Khan [44] designed a new handle, a so called anatomical handle, for woodworking chisels in which the shape of the handle was designed based on the hand and finger shapes. The researchers explained that this new handle provides a greater contact area between the hand and handle, making the control of the hand tool easier. Such a handle can be also designed for knives and cleavers used by butchers. However, it should be mentioned that such handles are full of sharp edges for unfitted hands and can result in unpleasant grasping. Moreover, various types of slip-resistance covers have been developed which can be used in this regard, for example, the one developed by Decker and Hummel [45].

The present study has some limitations. This study was conducted among a limited number of butchers which can affect the generalizability of the findings. The method used for assessing the ergonomic quality of knives and cleavers is not specifically designed for this purpose. It is therefore recommended that such a method is developed in future studies.

5 Conclusion

Occupational risk factors such as working experience, active working hours per day, and ergonomic quality of hand tools are significant risk factors of CTS symptoms among butchers. A slippery handle is the main non-ergonomic feature of knives and cleavers used by butchers. There was no association between BMI and wrist ratio with CTS symptoms.

Conflict of interest

None to report.

Footnotes

Acknowledgments

The authors would like to thank Hamadan University of Medical Sciences for the financial support (grant number: 9704051873).

References

Punnett

, Wegman

. Work-related musculoskeletal disorders: The epidemiologic evidence and the debate, J Electromyogr Kinesiol. 2004;14(1):13–23.

Morse

, Dillon

, Warren

, Levenstein

, Warren

. The economic and social consequences of work-related musculoskeletal disorders: The Connecticut Upper-extremity Surveillance Project (CUSP), Int J Occup Environ Health. 1998;4(4):209–16.

Health and Safety Executive (HSE), Work-related Musculoskeletal Disorders (WRMSDs) Statistics in Great Britain. UK: HSE, 2017.

van Rijn

, Huisstede

, Koes

, Burdorf

. Associations between work-related factors and the carpal tunnel syndrome— a systematic review, Scand J Work Env Heal. 2009;35(1):19–36.

Newington

, Harris

, Walker-Bone

. Carpal tunnel syndrome and work, Best Pract Res Clin Rheumatol [Internet]. 2015;29(3):440–53 Available from: https://dx-doi-org.web.bisu.edu.cn/10.1016/j.berh.2015.04.026.

Barcenilla

, March

, Chen

, Sambrook

. Carpal tunnel syndrome and its relationship to occupation: A meta-analysis, Rheumatology. 2012;51(2):250–61.

You

, Smith

, Rempel

. Meta-analysis: Association between wrist posture and carpal tunnel syndrome among workers, Saf Health Work [Internet]. 2014;5(1):27–31. Available from: https://dx-doi-org.web.bisu.edu.cn/10.1016/j.shaw.2014.01.003

Dale

, Harris-Adamson

, Rempel

, Gerr

, Hegmann

, Silverstein

, et al. Working Populations: Pooled Analysis of Six Prospective Studies Populations: Pooled Analysis of Six Prospective Studies, Scand J Work Env Heal. 2013;39(5):495–505.

Pramchoo

, Geater

, Tangtrakulwanich

. Physical ergonomic risk factors of carpal tunnel syndrome among rubber tappers, Arch Environ Occup Heal [Internet]. 2018;0(0):1–9. Available from: https://doi.org/10.1080/19338244.2018.1507991

10.

Harris-Adamson

, Eisen

, Kapellusch

, Garg

, Hegmann

, Thiese

, et al. Biomechanical risk factors for carpal tunnel syndrome: A pooled study of 2474 workers, Occup Environ Med. 2015;72(1):33–41.

11.

El-Helaly

, Balkhy

, Vallenius

. Carpal Tunnel Syndrome among Laboratory Technicians in Relation to Personal and Ergonomic Factors at Work. J Occup Health. 2017;1-26.

12.

Ozcakir

, Sigirli

, Avsaroglu

. High wrist ratio is a risk factor for carpal tunnel syndrome, Clin Anat. 2018;31(5):698–701.

13.

Thiese

, Merryweather

, Koric

, Ott

, Wood

, Kapellusch

, et al. Association between wrist ratio and carpal tunnel syndrome: Effect modification by body mass index, Muscle and Nerve. 2017;56(6):1047–53.

14.

Harih

, Dolšak

. Tool-handle design based on a digital human hand model, Int J Ind Ergon. 2013;43(4):288–95.

15.

Falck

, Aarnio

. Left-sided carpal tunnel syndrome in butchers, Scand J Work Environ Heal. 1983;9(3):291–7.

16.

Padua

, Coraci

, Erra

, Pazzaglia

, Paolasso

, Loreti

, et al. Carpal tunnel syndrome: clinical features, diagnosis, and management, Lancet Neurol [Internet]. 2016;15(12):1273–84. Available from: https://dx-doi-org.web.bisu.edu.cn/10.1016/S1474-4422(16)30231-9

17.

Pourmemari

, Shiri

. Diabetes as a risk factor for carpal tunnel syndrome: A systematic review and meta-analysis, Diabet Med. 2016;33(1):10–6.

18.

Levine

, Simmons

, Koris

, Daltroy

, Hohl

, Fossel

, et al. A self-administered questionnaire for the assessment of severity of symptoms and functional status in carpal tunnel syndrome, J Bone Jt Surg. 1993;75(11):1585–92.

19.

Mondelli

, Reale

, Sicurelli

, Padua

, Senese

. Relationship between the self-administered Boston questionnaire and electrophysiological findings in follow-up of surgically-treated carpal tunnel syndrome, J Hand Surg Am. 2000;25(2):128–34.

20.

Lue

, Lu

, Lin

, Liu

. Validation of the Chinese version of the boston carpal tunnel questionnaire, J Occup Rehabil. 2014;24(1):139–45.

21.

Rezazadeh

, Bakhtiary

, Samaei

, Moghimi

. Validity and reliability of the Persian Boston questionnaire in Iranian patients with carpal tunnel syndrome, Koomesh. 2014;15(2):138–45.

22.

Foroozanfar

, Ebrahimi

, Khanjani

. Validity and Reliability of the Persian Boston Questionnaire in Diabetic Patients with Carpal Tunnel Syndrome, J Neyshabur Univ Med Sci. 2014;2(5):50–6.

23.

Harih

, Dolšak

. Comparison of subjective comfort ratings between anatomically shaped and cylindrical handles, Appl Ergon. 2014;45(4):943–54.

24.

Dianat

, Rahimi

, Nedaei

, Asghari Jafarabadi

, Oskouei

. Effects of tool handle dimension and workpiece orientation and size on wrist ulnar/radial torque strength, usability and discomfort in a wrench task, Appl Ergon. 2017;59:422–30.

25.

Kong

, Lowe

. Optimal cylindrical handle diameter for grip force tasks, Int J Ind Ergon. 2005;35(6):495–507.

26.

Kong

, Lowe

. Evaluation of handle diameters and orientations in a maximum torque task, Int J Ind Ergon. 2005;35(12):1073–84.

27.

Pheasant

, Haslegrave

. Bodyspace: Anthropometry, ergonomics and the design of work. Boca Raton: CRC Press; 2018.

28.

https://www.ccohs.ca/oshanswers/ergonomics/handtools/tooldesign.html

29.

Simoneau

, St-Vincent

, Chicoine

. Work-Related Musculoskeletal Disorders (WMSDs)-A Better Understanding for More Effective Prevention. Assoc Parit por la santé la sécurité du Trav Inst recherché Robert-Sauvé en santé en sécurité du Trav du Quebéc. 2003;

30.

Jain

, Sain

, Meena

, Dangayach

, Bhardwaj

. Non-powered hand tool improvement research for prevention of work-related problems: a review, Int J Occup Saf Ergon. 2018;24(3):347–57.

31.

Dababneh

, Lowe

, Krieg

, Kong

, Waters

. A checklist for the ergonomic evaluation of nonpowered hand tools, J Occup Environ Hyg. 2004;1(12).

32.

Motamedzade

, Choobineh

, Mououdi

, Arghami

. Ergonomic design of carpet weaving hand tools, Int J Ind Ergon. 2007;37(7):581–7.

33.

Nejad

, Choobineh

, Rahimifard

, Haidari

, Reza Tabatabaei

. Musculoskeletal risk assessment in small furniture manufacturing workshops, Int J Occup Saf Ergon. 2013;19(2):275–84.

34.

Varin

, Panagiotakos

. A review of robust regression in biomedical science research. Arch Med Sci. 2019;1-3.

35.

Shiri

, Pourmemari

, Falah-Hassani

, Viikari-Juntura

. The effect of excess body mass on the risk of carpal tunnel syndrome: A meta-analysis of 58 studies, Obes Rev. 2015;16(12):1094–104.

36.

Werner

, Albers

, Franzblau

, Armstrong

. The relationship between body mass index and the diagnosis of carpal tunnel syndrome, Muscle Nerve. 1994;17(6):632–6.

37.

Kouyoumdjian

, Zanetta

DMT

, Morita

MPA

. Evaluation of age, body mass index, and wrist index as risk factors for carpal tunnel syndrome severity, Muscle and Nerve. 2002;25(1):93–7.

38.

Kozak

, Schedlbauer

, Wirth

, Euler

, Westermann

, Nienhaus

. Association between work-related biomechanical risk factors and the occurrence of carpal tunnel syndrome: An overview of systematic reviews and a meta-analysis of current research, BMC Musculoskelet Disord. 2015;16(1).

39.

Bonfiglioli

, Mattioli

, Fiorentini

, Graziosi

, Curti

, Violante

. Relationship between repetitive work and the prevalence of carpal tunnel syndrome in part-time and full-time female supermarket cashiers: A quasi-experimental study, Int Arch Occup Environ Health. 2007;80(3):248–53.

40.

Dianat

, Nedaei

, Mostashar Nezami

. The effects of tool handle shape on hand performance, usability and discomfort using masons’ trowels, Int J Ind Ergon [Internet]. 2015;45:13–20. Available from: https://dx-doi-org.web.bisu.edu.cn/10.1016/j.ergon.2014.10.006

41.

Hokari

, Pramudita

, Ito

, Noda

, Tanabe

. The relationships of gripping comfort to contact pressure and hand posture during gripping, Int J Ind Ergon. 2019;70(October 2018):84–91. Available from: https://doi.org/10.1016/j.ergon.2019.01.010

42.

Buchholz

, Frederick

, Armstrong

. An investigation of human palmar skin friction and the effects of materials, pinch force and moisture, Ergonomics. 1988;31(3):317–25.

43.

Armstrong

. Mechanical considerations of skin in work, Am J Ind Med. 1985;8(4-5):463–72.

44.

Bisht

, Khan

. A novel anatomical woodworking chisel handle, Appl Ergon [Internet]. 2019;76(November 2018):38–47. Available from: https://doi.org/10.1016/j.apergo.2018.11.010

45.

Decker

, Hummel

. Slip resistant, cushioning cover for handles. U.S. Patent 4,941,232; 1990.