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Biopsychosocial, neuroinflammatory, and behavioural correlates of temporomandibular disorders among Yemeni adults: A multicenter analytical study using structural equation modelling and machine learning

Year: 2026

Type: article

Abstract: Background: Temporomandibular disorders (TMDs) are complex conditions influenced by biopsychosocial factors. In fragile regions like Yemen, chronic contextual adversity may significantly amplify these disorders. This study aimed to investigate the biopsychosocial, neuroinflammatory, and behavioural correlates and predictive profiles of TMD. Methods: This multicenter analytical cross-sectional study included 1, 000 Yemeni adults (500 TMD patients and 500 matched controls). Data were collected using the Yemeni Living Conditions Index (YLCI), Generalised Anxiety Disorder-7 (GAD-7), and DC/TMD screening tools. Biological assessments included serum cortisol, inflammatory cytokines (IL-6, TNF-α, CRP), and oxidative stress markers (MDA, TAC, Omega-3). Data were analysed using Structural Equation Modelling (SEM) and Machine Learning (Random Forest and XGBoost). Results: Severe TMD was significantly associated with elevated anxiety and adverse living conditions (p < 0.001). Patients with severe TMD exhibited significantly higher levels of cortisol, IL-6, TNF-α, CRP, and MDA, alongside lower TAC and Omega-3 levels compared to controls (p < 0.001). Structural equation modelling demonstrated significant direct structural associations between contextual living adversity, anxiety severity, and TMD symptom burden (β = 0.222, p < 0.001). Machine learning models successfully predicted high-risk TMD profiles with high accuracy (XGBoost: 97.0%), where SHAP analysis identified anxiety, YLCI, and IL-6 as the most critical predictors. Clinical validation showed high diagnostic performance for symptom-based screening (AUC = 0.941). Conclusion: These findings support the implementation of multidisciplinary, context-sensitive diagnostic and management strategies integrating psychosocial assessment, biological risk profiling, and psychosocial support to improve TMD screening and patient care in resource-limited and conflict-affected settings.

Source: International Journal of Applied Dental Sciences

DOI: 10.22271/oral.2026.v12.i8c.2512

Authors: Muharrm Othman, Abdulghani Al-Dhahabi, Taghreed AL-kibsi, Wael Al-Sharjabi, Wael M Al Omari

Institutions: Sana'a University, Jordan University of Science and Technology

Language: English

Topic: Temporomandibular Joint Disorders

Subfield: Oral Surgery

Field: Dentistry

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W7204123262