Independent risk factors of carpal tunnel syndrome: Assessment of body mass index,hand,wrist and finger anthropometric measurements

Abstract

BACKGROUND:

The most prevalent neuropathy in the upper extremity is carpal tunnel syndrome (CTS). A variety of related risk factors such as biomechanical exposures, body mass index (BMI), sex and hand shape are reported to be related to CTS.

OBJECTIVE:

We aimed to identify the role of BMI, hand, wrist and finger anthropometric dimensions in the development of CTS, and to compare these measured variables between control and CTS participants.

METHODS:

A cross-sectional, case control study (n = 240, CTS = 120, controls = 120) with participants recruited from a convenience sample diagnosed with CTS and referred for anthropometric measurements. The control participants were matched by age and sex. The body height, weight, hand width, hand length, wrist depth, wrist width, wrist circumference, and finger length were measured. Hand, wrist and finger indices, hand to height ratio, and BMI were calculated. Mean values of all dimensions were compared between cases and controls, and the role of independent risk factors were determined by logistic regression analysis.

RESULTS:

The mean BMI, age, weight, sex and height were not significant between the two groups. Among the measured dimensions and calculated indices the significantly different variables between two groups were the wrist width, wrist depth, wrist circumference, hand index, hand to height index, and wrist index. Regression analysis showed that the wrist index (β=-1.7, p = 0.0001), wrist depth (β=0.25, p = 0.0001) and wrist width (β=0.21, p = 0.0001) were the strongest factors in CTS development in the sample.

CONCLUSION:

Wrist parameters have a strong role in predicting the development of CTS, while BMI was not confirmed as an independent risk factor.

Keywords

Hand shape wrist index carpal tunnel syndrome BMI anthropometry

1 Introduction

Carpal tunnel syndrome (CTS) is the most common neuropathy in the upper limb [1]. The median nerve compression at the level of the carpal tunnel commonly results in symptoms of pain and paresthesia in the hand, with symptoms worsening at night [2]. The prevalence and incidence of CTS in the general population are reported at 1–6% [3 –6] and 3.3–3.5 per 1000 person-years, respectively [4], and is more common in working populations (8%) [3 , 7]. The direct and indirect costs of CTS was 110 million and 130 million US dollars respectively in 2007 [8] and increased to more than 2 billion US dollars for 500,000 CTS release surgeries in the United States alone in 2016 [9].

The etiology of CTS is multifactorial and associated with a number of individual characteristics in the adult population. These factors can be occupational [6], physical or medical [10, 11]. Specific factors play a major role in the development of CTS [4, 12] and include: repetitive stress, repetitive bending or twisting of the hand and wrist at work, exposure of the hand to vibration [4 , 13–15], sex [2], age, race, pregnancy [14, 16], disease conditions such as diabetes [2, 17], hypothyroidism [14], and osteoarthritis [17]. Moreover, there are studies that have investigated the association with anthropometric characteristics such as body weight, height, and body mass index (BMI) as potential factors in CTS development. However, there has been limited simultaneous consideration of the association between specific hand and wrist anthropometric dimensions or indices and CTS in these studies [18, 19]. Some of the previous investigation limitations have included; small sample size (n < 67) [19 –21]; lack of adequate matched-controls from the perspective of BMI, age and gender [13, 22]; no control group; insufficient measures of dimensions or indices [19, 23]; and, inadequately reported statistical analysis [13, 22]. In-depth knowledge of CTS risk factors is essential in order to screen for, and prevent the condition. Current research suggests that people with CTS have anatomical differences in the hand/s affected by CTS [24].

There is a clear need for studies to investigate potential anthropometric risk contributors due to the high prevalence of CTS, lack of comprehensive information about related risk factors for CTS, and the lack of consideration of hand dimensions and indices in the examination of people with CTS [25], particularly in studies of adequate sample size [26]. With an improved knowledge of the prominent CTS related risk factors, including those that are anthropometric related, the strategies and treatment programs adopted can be selected more precisely from an evidence-based perspective. For this study, the aim was to identify the influence of various hand anthropometric measures and indices in the development of CTS; and the comparison between CTS and controls in a case-matched cohort.

2 Methods and materials

2.1 Study design and participants

In this cross-sectional case-matched control study, a sample of convenience (n = 240, aged 25-60 years; female = 75.8%, 91 in each group) were recruited with 120 participants in each group of CTS and matched controls. In the CTS group, a total of 90 participants had CTS unilaterally, with 30 participants having bilateral CTS, in which both hands were examined and matched with the control group (right-CTS=86, 57.3%; left-CTS=64).

The study protocol was approved by the ethics committee of the University of Social Welfare and Rehabililitation Sciences. The CTS participants were recruited from outpatients referred to the Tehran Red Crescent Rehabilitation Clinic, and the control participants from volunteers recruited through the relatives of the CTS participants and staff from the University of Social Welfare and Rehabililitation Sciences. The study was conducted from April to November 2018 in Tehran. All CTS participants had their diagnosis confirmed through a clinical examination and completion of an electrophysiological confirmation (electromyography-EMG and nerve conduction velocity-NCV) [27] by an orthopaedic physician. Participants were then referred for anthropometric measurement to a physiotherapist with extensive experience in this field. Participants were excluded if they had any history of hand surgery, cervical radiculopathy, current pregnancy, diabetes mellitus, or were taking any medications including oral contraception [26]. Recruited participants who formed the control group were evaluated by a physician to exclude the presence of CTS or cervical radiculopathy, and then were matched by age and sex with participants from the CTS group.

Informed consent was obtained from all participants. The study was approved by the Ethical Committee of the University of Social Welfare and Rehabilitation Sciences, Tehran, Iran (IR.USWR.REC.1396.384).

Information on participants’ symptoms, age, weight, height and associated diseases was recorded. All anthropometric measurements were performed by the physiotherapist within the rehabilitation clinic between 9 : 00 AM and 12 : 00 AM in an attempt to ameliorate the influence of daily diurnal changes, such as oedema, which is common in this population. To ensure an appropriate matched selection between the two groups, the symptomatic CTS hands were examined first, and the control participant’s matched hands were then subsequently measured.

2.2 Anthropometric measurements

In the CTS group, the anthropometric measures of the affected hand and wrist, as referred by the orthopaedic physician, were used for statistical evaluation. Measurements of the hand and wrist were taken from the palmar side with the fingers extended and abducted on a hard, flat surface [13, 26]. All measurements were performed three times using a standard engineering calliper with the mean of the three recordings used for further analysis. Height and weight were measured by one of the research team, with BMI calculated as weight/height² (kg/m²) [26, 28].

2.2.1 Hand

Palm length: the distance between the midpoint of the distal wrist crease and the midpoint of the proximal crease of the third finger [13]. Hand length: the distance between the distal flexor crease of the wrist and the tip of the extended third finger [13]. Hand width: the maximum distance of the volar surface between the second and fifth metacarpal heads [13]. Hand index: the hand length/hand width [29 –31]. Hand length to height index: the hand length/body height [29].

2.2.2 Wrist

Wrist depth and width: the antero-posterior depth and medio-lateral width at the distal flexor wrist crease, respectively [13]. Wrist circumference: the measured circumference just distal to the prominences of the radius and ulna bones [31 –33]. Wrist index: the wrist depth/wrist width [30, 31].

2.2.3 Fingers

Third finger length: the distance between the proximal flexor crease to the tip of the of the third digit [13, 29]. Finger index: as calculated from: (third finger length×100)/(hand length) [13, 29].

3 Data analysis

Descriptive statistics for continuous variables are presented as the mean±SD. Normal distribution of the data and equality of variance in standard deviation were assessed. The comparison between the two groups was performed with the independent t-test with no assumptions violated. The correlation between variables was measured by the Pearson correlation (r), and multiple regression analysis was used to evaluate anthropometric risk factors for CTS participants. The diagnosis of CTS was considered as the dependent variable and the anthropometric dimensions as the independent variables when findings and data were entered into the model. Age and sex were used as a group-matching factor and consequently not used in the model. Statistical analysis was performed using SPSS 13.0 and all statistically significant levels were set at p = 0.05. A power of analysis calculation indicated that the minimum sample size required was n = 118 to determine a minimum a statistical difference between the CTS and control groups at the given p = 0.05 level using the formula $= \frac{z^{2} p (1 - P)}{d^{2}}$ where the constant for 95% is z = 1.96, p = 0.5, and d = 0.09.

4 Results

This study enrolled 240 participants (CTS = 120, controls = 120) with no statistically significant difference between groups for demographic data on age, weight, height and BMI (see Table 1).

Table 1
Descriptive data and comparison of CTS and control participants

Variable Group N Mean SD p-value

Height (cm) Healthy 120 164.1 6.5 0.52

CTS 120 161.8 5.8

Weight (kg) Healthy 120 70.1 12.2 0.24

CTS 120 71.3 12.7

Age (years) Healthy 120 43.8 9.4 0.38

CTS 120 44.2 9.5

BMI (kg/m²) Healthy 120 26.0 4.2 0.08

CTS 120 26.6 4.5

Variable	Group	N	Mean	SD	p-value
Height (cm)	Healthy	120	164.1	6.5	0.52
	CTS	120	161.8	5.8
Weight (kg)	Healthy	120	70.1	12.2	0.24
	CTS	120	71.3	12.7
Age (years)	Healthy	120	43.8	9.4	0.38
	CTS	120	44.2	9.5
BMI (kg/m²)	Healthy	120	26.0	4.2	0.08
	CTS	120	26.6	4.5

BMI=Body Mass Index, Independent t-Test was used.

A variety of anthropometric dimensions and indices were measured and comparisons were made between the two groups (see Table 2). Wrist dimensions included width, depth and circumference and each had statistically significant differences between the CTS and the control participants (see Table 2). Palm length, hand width, hand length and finger length were found to have no significant difference. Hand, hand to height, and wrist indices were significantly different between groups; while the finger index was not significantly different (see Table 2).

Table 2

The comparison of anthropometric data in CTS (n = 120) and control participants (n = 120)

	Group	Mean	Std.	p-value
Deviation
Palm length	Control	9.96	0.67	0.81
	CTS	9.80	0.50
Hand width	Control	7.90	0.49	0.09
	CTS	8.12	0.48
Hand length	Control	17.41	1.03	0.72
	CTS	17.03	1.02
Wrist depth	Control	3.66	0.40	<0.001^**
	CTS	4.15	0.31
Wrist width	Control	5.21	0.48	<0.001^**
	CTS	5.75	0.70
Wrist	Control	16.11	1.84	0.01^*
circumference
	CTS	16.58	0.91
Finger length	Control	7.45	0.47	0.35
	CTS	7.37	0.34
Hand index	Control	2.20	0.09	<0.001^**
	CTS	2.04	.081
Wrist index	Control	0.70	0.04	<0.001^**
	CTS	0.73	0.03
Finger index	Control	42.82	1.45	0.09
	CTS	42.09	0.77
Hand to height ratio	Control	10.48	0.40	<0.001^**
	CTS	10.88	0.42

^*p<0.05; ^**p<0.01, Independent t-Test was used.

A correlation analysis was performed between anthropometric dimensions, indexes and BMI using the data from all 240 hands. The BMI correlated with wrist depth (r = 0.57, p < 0.001), wrist width (r = 0.61, p < 0.001), wrist circumference (r = 0.54, p < 0.001), finger length (r = 0.52, p < 0.001), hand length (r = 0.57, p < 0.001) and palm length (r = 0.55, p < 0.001).

A multiple regression analysis was carried out to investigate whether anthropometric dimensions and indices could significantly predict CTS development (see Table 3). These results indicated the model explained 95.6% of variance; and that the model was a significant predictor of CTS development, F (7,253)=13834.28, p < 0.001. The model demonstrated that the risk factors for CTS are palm length, hand length, wrist depth, wrist circumference, wrist width and finger index. Among the measured parameters the wrist index (β=-1.7, p = 0.0001), wrist depth (β=0.25, p = 0.0001) and wrist width (β=0.21, p = 0.0001) were respectively the strongest factors in the development of CTS.

Table 3

Risk factors for CTS in the logistic regression analysis for all patients

Dependent variable	Independent variable	R	β	p-value
CTS development	Palm length	0.94	–0.04	0.0001^**
	Hand length	0.01	0.001^**
	Wrist depth	0.25	0.001^**
	Wrist width	–0.21	0.0001^**
	Wrist circumference	0.01	0.0001^**
	Wrist index	1.70	0.0001^**
	Finger index	0.01	0.0001^**

CTS: Carpal Tunel Syndrome. ^*p<0.05; ^*p<0.01. Logistics regression analysis was used.

5 Discussion

A variety of demographic and anthropometric factors have previously been reported to be variably associated with CTS development including age, BMI, sex, wrist and also hand dimensions [26, 34]. This study aimed to determine the role of various anthropometric measures of the hand, wrist and finger dimensions in the development of CTS, and also to compare these measured variables between CTS and control participants in a matched cohort. Among the calculated anthropometric dimensions, the wrist depth, wrist width, wrist circumference, wrist index, hand index, and hand length/height ratio were significantly different between healthy and CTS participants. However, regression analysis showed only wrist index, wrist depth and wrist width as the determinant dimensions in the prediction of CTS development.

One of the key findings of this study was that wrist parameters are major determinants in CTS development [35, 36]. Among these, the wrist index was the strongest determinant, which is consistent with the results of previous studies. Wrist index is the ratio of wrist depth/wrist width which is usually a value < 1.0 and referred to by different authors as “wrist squareness” [37], “squarer” [26] or “square-shaped” [24]. Kamolz et al. [18], Moghtaderi et al. [31], Farmer et al. [30], Kouyoumdjian et al. [38], Trybus et al. [24] and Lim et al. [19] showed that the wrist index, or squareness, in CTS participants was very close to the values obtained in this study. In our study, the wrist index (wrist depth/wrist width) in CTS participants (0.73) were higher than the control participants (0.70). The reported wrist index for control participants was 0.69, 0.68, 0.69, 0.68, 0.69, 0.69 by Kamolz et al. [18], Moghtaderi et al. [31], Farmer et al. [30], Kouyoumdjian et al. [38], Lim et al. [19], and Plave et al. [39], respectively.

It appears that with an increasing wrist index, the wrist shape becomes squarer and higher sensory latencies are reported [18 , 39]. Therefore, in participants with this square-shaped wrist, completing a task requires greater wrist flexion and extension during range of motion, which consequently could cause greater pressure in the carpal tunnel [18 , 26]. This discrepancy of the wrist index between CTS and control participants has been suggested as being explained by the presence of oedema, tenosynovial hypertrophy, and transient changes in the adjacent soft tissue [18 , 40]. There is still no consensus on whether this is a pre-existing physiological anomaly that predisposes individuals to CTS, or whether it is a transient change that develops as a consequence.

Clinically, the wrist index measure can be readily determined and intervention strategies assessed as effective or not in eliminating or reducing the potential for CTS to occur. These interventions include: therapies such as carpal bone mobilisation [41, 42], myofascial mobilisation [43], mobilising the transverse carpal space through self-stretching [44], or the use of a traction device [45], which subsequently affect oedema or hypertrophy. Traditionally, research into carpal tunnel manual therapies has not included anthropometric measurements [46] but clinical practice guidelines [34] have summarised the significant role that measurements have in predicting disposing factors and severity of CTS. Preventative ergonomics should be investigated specific to the square wrist due to the anatomical difference in torque, available active range of motion, and grip loading. To our knowledge no research has been published in regard to ergonomics and the wrist index.

Farmer et al. [30] found no significant difference between the wrist indices of the symptomatic and contralateral wrists of CTS participants with unilateral symptoms, which is in contrast to our findings. In their study, they also reported that participants with bilateral CTS, in which their hands were operated, did not present with a lower wrist index. The authors suggested that any relationship between the wrist index and CTS may be related to the differences in BMI between the two groups. Our findings challenge this finding. We controlled for potential variability in the BMI in the two groups of this study and no significant difference was found. Consequently, BMI cannot be a source of difference which supports the findings of Boz et al, who found that the relationship between CTS and wrist index is independent of BMI [13].

Hand index or hand shape (hand length/hand width), usually a value in the order of 2.0 is another parameter which was considered in previous research with some studies reporting a significant difference in hand index between the CTS and control participants [18, 20]. Previous studies have also shown that the hand length is shorter and the palm width is larger in a CTS group than control participants [20]. Our results confirmed this with a significant difference (p < 0.001) in the hand index found between control participants at 2.20, compared to the lower value of those with CTS at 2.04. These findings are further supported in CTS studies where the control participants versus CTS has been shown to be lower with respective values of 2.23 and 2.03 by Chroni et al. [20] and 2.20 and 2.0 by Kamolz et al. [18]. Sharifi-Mollayousefi et al. [47] and Boz et al. [13] used an alternative hand index measurement methodology (hand width (mm)/hand length (mm)×100, which usually provides a value in the order of 40-45, but the CTS was lower than the control) and respectively demonstrated a higher index in the CTS group (44.9, 44.84) than in the control participants (42.87, 42.30). The suggested mechanism for the effect of a lower hand index on the development of CTS can be the increased exerted force by a hand with higher length for a given repetitive hand motion. There is only one older study with some recognised methodological limitation such as low sample size (18 case, 18 control) and no electrophysiological confirmation of CTS, where the results were in contrast to the current study [48].

We also found that finger index can be an independent risk determinant for CTS, which is in accordance with the findings of Boz et al. [13] and Chroni et al. [20]. Boz et al. found a significant difference between finger index in control participants and CTS female participants [13], but showed no relationship between the finger index and CTS severity. Another study by Sgarifi et al. [47], failed to show the role of the digit index as a risk determinant. We are unaware of any previous studies that have investigated the finger index relationship with CTS. Consequently, future research will be required for greater clarification.

Lastly, we also found a significant difference in hand length/height ratio between the two groups but logistic regression analysis did not confirm it as a risk factor for CTS, suggesting that the ratio of hand to body height is not related to the development of CTS. Furthermore, this result supports similar findings by Boz et al. [13], and Sharifi et al. [47]. We are not aware of any other published studies that considered this relationship of hand length/height ratio and the presence of CTS. Consequently, from both our results and that of previous research findings it is indicative that the presence of a square-shape wrist and hand, as quantified by shorter lengths (palm, finger, hand length) and larger widths (palm, wrist, fingers width), are risk factors for CTS. This square-shape may compound a predisposition for a greater requirement for a fulcrum and torque increase due to the shorter lever arm mechanical deficiency when compared to the more stretched hand [49, 50]. A recommendation from this study would be that individuals with this square-shape wrist and hand would potentially require altered fulcrum lever length for work settings (such as the use of pliers) in the presence of increased torque load.

A major strength is that this is the first study in an Iranian population on this aspect of the links between anthropometrics and CTS. Additional strengths are that the study has matched the participants based on the age, sex, height and weight to control the BMI as a cofounding parameter. We have employed an adequate sample size in both the CTS and control participants to find the optimal contributed indices and dimensions related to CTS development. There are some limitations in this study such as categorised participants based on the severity of involvement and evaluating the relation between severity of CTS and hand/wrist parameters, and that differences in indices by sex were not determined. Furthermore, the total sample size was skewed toward female participants, which may limit the generalisability of the results. Future research must consider a higher proportion of male participants, and other dimensions and indices to thoroughly determine the full series of CTS risks related to the hand and wrist. This may include parameters such as grip strength and further investigation into hand shape. A longitudinal study may be required to determine whether the wrist index or “squareness” is a risk factor for or a consequence of CTS.

6 Conclusion

The aim of our study was to compare the hand anthropometric measures and indices in CTS and healthy control participants, and to investigate their role in the presence of CTS. Our results suggest that the wrist index, sometimes referred to as “squareness”, is more strongly associated with CTS than the hand index or hand shape. We also found hand length, hand palm, and finger index are independent risk factors for CTS. Controlling for BMI in both groups did not demonstrate it as an independent risk factor. The overall findings from our study indicate that wrist parameters are among the most critical and useful parameters in the research of CTS prevalence; and anthropometric measurements, which can be rapidly and accurately determined within the clinical practice setting, can highlight an individual’s potential risk for CTS, or in the presence of CTS it can explain the causal presence of CTS. Consequently, integrating this assessment knowledge with manual interventions may provide an evidence base to therapeutic and preventative opportunities. Longitudinal studies investigating these indices in asymptomatic participants or people with mild-moderate CTS may clarify these different relationships, the ability of interventions to mitigate CTS severity, or whether the anthropometric change is a consequence.

Funding

This study was financially supported by the Rofideh Rehabilitation Hospital, University of Social Welfare and Rehabilitation Sciences, Iran, Tehran (Grant no. 1896).

Conflict of interest

All authors declare that they have no conflicts of interest.

Footnotes

Acknowledgment

The authors appreciate the financial and technical support from Rofideh Rehabilitation Hospital Clinical Research Development Center. Also, the authors are grateful to the volunteers for their participation.

References

Evanoff

, Dale

, Deych

, Ryan

, Franzblau

. Risk factors for incident carpal tunnel syndrome: results of a prospective cohort study of newly-hired workers. Work. 2012;41:4450–2.

Pourmemari

, Heliövaara

, Viikari-Juntura

, Shiri

. Carpal tunnel release: Lifetime prevalence, annual incidence, and risk factors. Muscle & nerve. 2018;58(4):497–502.

Alhusain

, Almohrij

, Althukeir

, Alshater

, Alghamdi

, Masuadi

, et al. Prevalence of carpal tunnel syndrome symptoms among dentists working in Riyadh. Annals of Saudi Medicine. 2019;39(2):104–11.

Hulkkonen

, Shiri

, Auvinen

, Miettunen

, Karppinen

, Ryhanen

. Risk factors of hospitalization for carpal tunnel syndrome among the general working population. Scandinavian Journal of Work, Environment & Health. 2020;46(1):43–9.

Mokhtarinia

, Zareiyan

, Gabel

. Cross-cultural adaptation, validity, and reliability of the persian version of the upper limb functional index. Hand Therapy. 2021;26(2):43–52.

Ghasemi

, Gholamizadeh

, Rahmani

, Doosti-Irani

. Prevalence and severity of carpal tunnel syndrome symptoms among Iranian butchers and their association with occupational risk factors: Implications for ergonomic interventions. Work. 2020;66:817–25.

Gabrielli

, Lesiak

, Fowler

, The Direct and Indirect Costs to Society of Carpal Tunnel Release. Hand (New York, NY), 2020;15(2):Np1–np5.

Bhattacharya

. Costs of occupational musculoskeletal disorders (MSDs) in the United States. International Journal of Industrial Ergonomics. 2014;44(3):448–54.

Milone

, Karim

, Klifto

, Capo

. Analysis of Expected Costs of Carpal Tunnel Syndrome TreatmentStrategies. Hand (New York, NY).. 2019;14(3):317–23.

10.

Palmer

, Harris

, Coggon

. Carpal tunnel syndrome and its relation to occupation: a systematic literature review. Occupational Medicine. 2007;57(1):57–66.

11.

Tseng

, Liao

, Kuo

, Sung

, Hsieh

, Tsai

. Medical and non-medical correlates of carpal tunnel syndrome in a Taiwan cohort of one million. European Journal of Neurology. 2012;19(1):91–7.

12.

Nathan

, Meadows

, Istvan

. Predictors of carpal tunnel syndrome: an 11-year study of industrial workers. The Journal of Hand Surgery. 2002;27(4):644–51.

13.

Boz

, Ozmenoglu

, Altunayoglu

, Velioglu

, Alioglu

. Individual risk factors for carpal tunnel syndrome: an evaluation of body mass index, wrist index and hand anthropometric measurements. Clinical Neurology and Neurosurgery. 2004;106(4):294–9.

14.

Shiri

, Miranda

, Heliövaara

, Viikari-Juntura

. Physical work load factors and carpal tunnel syndrome: a population-based study. Occupational and Environmental Medicine. 2009;66(6):368–73.

15.

Hulkkonen

, Shiri

, Auvinen

, Miettunen

, Karppinen

, Ryhänen

. Risk factors of hospitalization for carpal tunnel syndrome among the general working population. Scandinavian Journal of Work, Environment & Health 2019.

16.

Guan

, Lao

, Gu

, Zhao

, Rui

, Gao

. Case-control study on individual risk factors of carpal tunnel syndrome. Experimental and Therapeutic Medicine. 2018;15(3):2761–6.

17.

Van Rijn

, Huisstede

, Koes

, Burdorf

. Associations between work-related factors and the carpal tunnel syndrome—a systematic review. Scandinavian Journal of Work, Environment & Health. 2009:19-36.

18.

Kamolz

L-P

, Beck

, Haslik

, Högler

, Rab

, Schrögendorfer

, et al. Carpal tunnel syndrome: a question of hand and wrist configurations? Journal of Hand Surgery 2004;29(4):321–4.

19.

Lim

, Tan

, Ahmad

. The role of wrist anthropometric measurement in idiopathic carpal tunnel syndrome. Journal of Hand Surgery (European Volume). 2008;33(5):645–7.

20.

Chroni

, Paschalis

, Arvaniti

, Zotou

, Nikolakopoulou

, Papapetropoulos

. Carpal tunnel syndrome and hand configuration. Muscle & Nerve. 2001;24(12):1607–11.

21.

Chiotis

, Dimisianos

, Rigopoulou

, Chrysanthopoulou

, Chroni

. Role of anthropometric characteristics in idiopathic carpal tunnel syndrome. Archives of Physical Medicine and Rehabilitation. 2013;94(4):737–44.

22.

Arslan

, Bülbül

Öcek

, Şener

, Zorlu

. Effect of hand volume and other anthropometricmeasurements on carpal tunnel syndrome. Neurological Sciences. 2017;38(4):605–10.

23.

Zyluk

, Dabal

, Szlosser

. Association of anthropometric factors and predisposition to carpal tunnel syndrome. Chirurgia narzadow ruchu i ortopedia polska. 2011;76(4):193–6.

24.

Trybus

, Stepańczak

, Koziej

, Gniadek

, Kołodziej

, Hołda

. Hand anthropometry in patients withcarpal tunnel syndrome: a case-control study with a matched control group of healthy volunteers. FoliaMorphologica. 2019;78(1):182–90.

25.

Cazares-Manríquez

, Wilson

, Vardasca

, García-Alcaraz

, Olguín-Tiznado

, López-Barreras

, et al. A Review of Carpal Tunnel Syndrome and Its Association with Age, Body Mass Index, Cardiovascular Risk Factors, Hand Dominance, and Sex. Applied Sciences. 2020;10(10):3488.

26.

Imam

, Hasan

, ELnemr

, El-Sayed

. Body, wrist, and hand anthropometric measurements as risk factors for carpal tunnel syndrome. Egyptian Rheumatology and Rehabilitation. 2019;46(1):35.

27.

Maghsoudipour

, Hosseini

, Coh

, Garib

. Evaluation of occupational and non-occupational risk factors associated with carpal tunnel syndrome in dentists. Work. 2021;69:181–6.

28.

WHO.World Health Organization. Obesity: Preventing and Managing the Global Epidemic: Report of the WHO Consultation of Obesity. World Health Organization Geneva; 1997.

29.

Kulaksiz

, Gözil

. The effect of hand preference on hand anthropometric measurements in healthy individuals. Annals of Anatomy-Anatomischer Anzeiger. 2002;184(3):257–65.

30.

Farmer

, Davis

. Carpal tunnel syndrome: a case–control study evaluating its relationship with body mass index and hand and wrist measurements. Journal of Hand Surgery (European Volume). 2008;33(4):445–8.

31.

Moghtaderi

, Izadi

, Sharafadinzadeh

. An evaluation of gender, body mass index, wrist circumference and wrist ratio as independent risk factors for carpal tunnel syndrome. Acta Neurologica Scandinavica. 2005;112(6):375–9.

32.

Organization WH.Waist circumference and waist-hip ratio: report of aWHO expert consultation, Geneva, 8-11 December 2008. 2011.

33.

Jahangiri Noudeh

, Hadaegh

, Vatankhah

, Momenan

, Saadat

, Khalili

, et al. Wrist Circumference as a Novel Predictor of Diabetes and Prediabetes: Results of Cross-Sectional and 8. 8-Year Follow-up Studies. The Journal of Clinical Endocrinology & Metabolism. 2013;98(2):777–84.

34.

Erickson

, Lawrence

, Jansen

CWS

, Coker

, Amadio

, Cleary

,et al. Hand pain and sensory deficits: carpal tunnel syndrome: clinical practice guidelines linked to the international classification of functioning, disability and health from the academy of hand and upper extremity physical therapy and the academy of orthopaedic physical therapy of the american physical therapy association. Journal of Orthopaedic & Sports Physical Therapy.CPG1-CPG. 2019;49(5):85.

35.

Radecki

. A gender specific wrist ratio and the likelihood of a median nerve abnormality at the carpal tunnel. American Journal of Physical Medicine & Rehabilitation. 1994;73(3):157–62.

36.

Gordon

, Johnson

, Gatens

, Ashton

. Wrist ratio correlation with carpal tunnel syndrome in industry. American Journal of Physical Medicine & Rehabilitation. 1988;67(6):270–2.

37.

Shiri

. A square-shaped wrist as a predictor of carpal tunnel syndrome: A meta-analysis. Muscle & Nerve. 2015;52(5):709–13.

38.

Kouyoumdjian

, Zanetta

, Morita

. Evaluation of age, body mass index, and wrist index as risk factors for carpal tunnel syndrome severity. Muscle & Nerve: Official Journal of the American Association of Electrodiagnostic Medicine. 2002;25(1):93–7.

39.

Palve

, Palve

. Study of wrist ratio and wrist-to-palm index radio in individuals suffering from carpaltunnel syndrome. Ann Indian Acad Neurol.. 2019;22(2):159–63.

40.

Pickering

, Stevens

, Davis

. Work practices and histopathological changes in the tenosynovium in carpal tunnel syndrome in men. Journal of Hand Surgery. 2004;29(4):325–8.

41.

Bueno-Gracia

, Ruiz-de-Escudero-Zapico

, Malo-Urries

, Shacklock

, Estebanez-de-Miguel

, Fanlo-Mazas

, et al. Dimensional changes of the carpal tunnel and the median nerve during manual mobilization of the carpal bones. Musculoskeletal Science and Practice. 2018;36:12–6.

42.

Dinarvand

, Abdollahi

, Raeissadat

, Bandpei

MAM

, Babaee

, Talimkhani

. The effect of scaphoid and hamate mobilization on treatment of patients with carpal tunnel syndrome. Anesthesiology and Pain Medicine. 2017;7(5).

43.

Burke

, Buchberger

, Carey-Loghmani

, Dougherty

, Greco

, Dishman

. A pilot study comparing two manual therapy interventions for carpal tunnel syndrome. Journal of Manipulative and Physiological Therapeutics. 2007;30(1):50–61.

44.

Shem

, Wong

, Dirlikov

. Effective self-stretching of carpal ligament for the treatment of carpal tunnel syndrome: A double-blinded randomized controlled study. Journal of Hand Therapy. 2020.

45.

Porrata

, Porrata

, Sosner

. New carpal ligament traction device for the treatment of carpal tunnel syndrome unresponsive to conservative therapy. Journal of Hand Therapy. 2007;20(1):20–8.

46.

Page

, O’Connor

, Pitt

, Massy-Westropp

. Exercise and mobilisation interventions for carpal tunnel syndrome. Cochrane Database of Systematic Reviews. 2012:(6).

47.

Sharifi-Mollayousefi

, Yazdchi-Marandi

, Ayramlou

, Heidari

, Salavati

, Zarrintan

. Assessment of body mass index and hand anthropometric measurements as independent risk factors for carpal tunnel syndrome. Folia Morphologica. 2008;67(1):36–42.

48.

Armstrong

, Chaffin

. Carpal tunnel syndrome and selected personal attributes. Journal of Occupational Medicine: Official Publication of the Industrial Medical Association. 1979;21(7):481–6.

49.

Werner

, Armstrong

. Carpal tunnel syndrome: ergonomic risk factors and intracarpal. Physical Medicine and Rehabilitation Clinics of North America. 1997;8(3):555–69.

50.

Crawford

, Wanibe

, Nayak

. The interaction between lid diameter, height and shape on wrist torque exertion in younger and older adults. Ergonomics. 2002;45(13):922–33.