Age and Body Anthropometry as Predicting Factors for Carpal Tunnel Syndrome among Egyptian Obese Women

Moushira Zaki; Maha Ali; Walaa Yousef; Wafaa Ezzat; Walaa Basha

doi:10.3889/oamjms.2020.3317

Authors

Moushira Zaki Department of Biological Anthropology, National Research Centre, Cairo, Egypt
Maha Ali Department of Internal Medicine, National Research Centre, Giza, Egypt
Walaa Yousef Department of Biological Anthropology, National Research Centre, Cairo, Egypt
Wafaa Ezzat Department of Internal Medicine, National Research Centre, Giza, Egypt
Walaa Basha Department of Biological Anthropology, National Research Centre, Cairo, Egypt

DOI:

https://doi.org/10.3889/oamjms.2020.3317

Keywords:

CTS, Obese Women, age, Risk Factors

Abstract

BACKGROUND: Carpal tunnel syndrome (CTS) is the most prevalent entrapment neuropathy in the upper limb. The most consistent risk factors are female gender, age, and obesity. The results of previous studies are conflicting, and moreover, data from studies regarding obesity and nerve conduction velocity are not available for our Egyptian population.

AIM: This study was designed to investigate the contribution of age and body anthropometry as predictor factors to the CTS and to identify patients at high risk for CTS among Egyptian obese women.

METHODS: The study included 120 obese women grouped according to the clinical and electrodiagnostic (EDX) findings into two groups: 60 with CTS and 60 without CTS (non-CTS). EDX study was used in the diagnosis of median nerve entrapment at the level of the wrist, according to the American Association of Neuromuscular and EDX Medicine. Body weight and height were measured and then body mass index (BMI) was calculated. Waist-to-hip ratio (WHR) was determined from the measured waist circumference (WC) and hip circumference (HC). Mid upper arm circumference (MUAC) was measured as well. The receiver operating characteristic (ROC) curve was used to assess the power of age and body anthropometry as predictor factors for CTS.

RESULTS: CTS obese cases showed significantly lower values of both median motor nerve conduction velocity (MMNCV) and median sensory nerve conduction velocity compared to those without CTS. Significantly higher median sensory latency and median motor latency have been found in CTS cases compared to non-CTS group. Significant differences in the mean age have been found between the two groups and a tendency for higher body anthropometry measures in the CTS cases relative to those without CTS. Moreover, there were negative correlations between MMNCV and obesity indices. Age showed the highest area under the ROC curve, followed by BMI, WHR WC, HC, and MUAC.

CONCLUSION: Age and obesity indices are important risk factors that can be used as predictors to CTS in obese women. Age is a more powerful diagnostic tool relative to the anthropometric measurements. Women of age above 40 years and suffering from a high degree of obesity are at risk of developing CTS.

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References

Werner RA, Andary M. Carpal tunnel syndrome: Pathophysiology and clinical neurophysiology. Clin Neurophysiol. 2002;113(9):1373-81. https://doi.org/10.1016/ s1388-2457(02)00169-4 ` PMid:12169318

Kouyoumdjian JA, Zanetta DM, Morita MP. Evaluation of age, body mass index, and wrist index as risk factors for carpal tunnel syndrome severity. Muscle Nerve. 2002;25(1):93-7. https://doi. org/10.1002/mus.10007 PMid:11754190

Becker J, Nora DB, Gomes I, Stringari FF, Seitensus R, Panosso JS, et al. An evaluation of gender, obesity, age and diabetes mellitus as risk factors for carpal tunnel syndrome. Clin Neurophysiol. 2002;113(9):1429-34. https://doi.org/10.1016/ s1388-2457(02)00201-8 PMid:12169324

Hendriks SH, van Dijk PR, Groenier KH, Houpt P, Bilo HJ, Kleefstra N. Type 2 diabetes seems not to be a risk factor for the carpal tunnel syndrome: A case control study. BMC Musculoskelet Disord. 2014;15:346. https://doi.org/10.1186/1471-2474-15-346 PMid:25315096

Barcenilla A, March LM, Chen JS, Sambrook PN. Carpal tunnel syndrome and its relationship to occupation: A meta-analysis. Rheumatology. 2012;51(2):250-61. https://doi.org/10.1093/ rheumatology/ker108 PMid:21586523

Kozak A, Schedlbauer G, Wirth T, Euler U, Westermann C, Nienhaus A. 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;16:231. https://doi. org/10.1186/s12891-015-0685-0 PMid:26323649

Phalen GS. The carpal-tunnel syndrome. Seventeen years’ experience in diagnosis and treatment of six hundred fifty-four hands. J Bone Joint Surg Am. 1966;48(2):211-28. https://doi. org/10.2106/00004623-196648020-00001 PMid:5934271

Wang L. Electrodiagnosis of carpal tunnel syndrome. Phys Med Rehabil Clin N Am. 2013;24(1):67-77. PMid:23177031

Basiri K, Katirji B. Practical approach to electrodiagnosis of the carpal tunnel syndrome: A review. Adv Biomed Res. 2015;4:50. https://doi.org/10.4103/2277-9175.151552 PMid:25802819

Atroshi I, Gummesson C, Johnsson R, Ornstein E, Ranstam J, Rosén I. Prevalence of carpal tunnel syndrome in a general population. JAMA. 1999;282(2):153-8. https://doi.org/10.1001/ jama.282.2.153 PMid:10411196

Aroori S, Spence RA. Carpal tunnel syndrome. Ulster Med J. 2008;77(1):6-17. PMid:18269111

Graham B. The value added by electrodiagnostic testing in the diagnosis of carpal tunnel syndrome. J Bone Joint Surg Am. 2008;90(12):2587-93. https://doi.org/10.2106/jbjs.g.01362 PMid:19047703

Ibrahim I, Khan WS, Goddard N, Smitham P. Carpal tunnel syndrome: A review of the recent literature. Open Orthop J. 2012;6:69-76. https://doi.org/10.2174/1874325001206010069 PMid:22470412

Nordstrom DL, Vierkant RA, DeStefano F, Layde PM. Risk factors for carpal tunnel syndrome in a general population. Occup Environ Med. 1997;54(10):734-40. https://doi. org/10.1136/oem.54.10.734 PMid:9404321

Tunç A, Güngen BD. Carpal tunnel syndrome: Investigating the sensitivity of initial-diagnosis with electro-diagnostic tests in 600 cases and associated risk factors especially manual milking. J Back Musculoskelet Rehabil. 2017;30(2):333-8. https://doi.org/10.3233/bmr-160547 PMid:27858695

Chiotis K, Dimisianos N, Rigopoulou A, Chrysanthopoulou A, Chroni E. Role of anthropometric characteristics in idiopathic carpal tunnel syndrome. Arch Phys Med Rehabil. 2013;94(4):737-44. https://doi.org/10.1016/j.apmr.2012.11.017 PMid:23178273

Mondelli M, Aretini A, Ginanneschi F, Greco G, Mattioli S. Waist circumference and waist-to-hip ratio in carpal tunnel syndrome : A case-control study. J Neurol Sci. 2014;338(1-2):207-13. https://doi.org/10.1016/j.jns.2014.01.012 PMid:24468538

Solomon DH, Katz JN, Bohn R, Mogun H, Avorn J. Nonoccupational risk factors for carpal tunnel syndrome. J Gen Intern Med. 1999;14(5):310-4. https://doi. org/10.1046/j.1525-1497.1999.00340.x PMid:10337041

Majumdar S, Chaudhuri A, Ghar M, Rahaman WB, Hai A. Effect of obesity on nerve conduction study in an urban population of a developing country. Saudi J Sports Med. 2017;17:162-7. https:// doi.org/10.4103/sjsm.sjsm_8_17934