Chronic neck pain in young adults: perspectives on anatomic differences

Abstract

BACKGROUND CONTEXT: Neck pain (NP) is a common musculoskeletal disorder, but little is known about the associated risk factors. PURPOSE: We compared anatomic differences in the neck and trunk area of young adult patients with chronic NP and control subjects without NP to identify risk factors and predictors. STUDY DESIGN: This is an age-, sex-, and body mass index-matched retrospective case-control study of a consecutive sample. PATIENT SAMPLE: Patients with axial NP for longer than 6 months (23 males and 25 females) and pain-free volunteers (23 males and 25 females) were included. OUTCOME MEASURES: Outcome measures were linear and angular dimensions of the cervicothoracic junction. METHODS: Midsagittal magnetic resonance imaging scans of the cervicothoracic spine were obtained. Four linear and four angular parameters were identified and measured. These parameters included depth of the T1-manubrium arch (T1AD), depth of the thoracic cage (TXD), tangential height of T1 (T1H1), relative height of T1 (T1H2), T1 slope (T1S), thoracic inlet inclination (TiI), T1-manubrium arch inclination (T1AI), and the angular difference between TiI and T1AI (TiI-T1AI). The measurements were taken by two neurosurgeons. RESULTS: Depth of the T1-manubrium arch and TiI were identified as predictors for NP in the binary logistic regression analysis. Each millimeter increase in T1AD lessened the probability of NP with an adjusted odds ratio (OR) of 0.823 (95% confidence interval [CI], 0.701-0.966) in females and 0.809 (95% CI, 0.681-0.959) in males. Each degree increase in TiI was associated with the probability of NP with an adjusted OR of 1.247 (95% CI, 1.060-1.466) in males. CONCLUSIONS: Measurement of cervicothoracic junctional structures is a reliable and feasible method of estimating potential predictor of chronic NP in young adults. Forward inclination of the thoracic inlet in males and a shallow thoracic cage in females were identified as important predictors. (C) 2014 Elsevier Inc. All rights reserved.