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Modeling chronic pain interconnections using Bayesian networks: insights from the Qatar Biobank study
Aisha Ahmad M A Al-Khinji1,2, Dhafer Malouche2,3
1College of Medicine, Qatar University, Doha, Qatar.
Frontiers in Pain Research (Lausanne, Switzerland)
|June 11, 2025
Summary
This study reveals how chronic pain locations interconnect and vary by age and gender. Understanding these links can help create personalized pain management strategies.
Area of Science:
- Epidemiology
- Biostatistics
- Public Health
Background:
- Chronic pain is a complex condition with multifactorial origins.
- Understanding the interdependencies between different pain locations and demographic factors is crucial for developing effective clinical strategies.
- Previous research has often examined pain locations in isolation, limiting a holistic understanding of chronic pain networks.
Purpose of the Study:
- To investigate the interdependencies among various chronic pain locations.
- To explore the relationships between chronic pain patterns, age, and gender.
- To provide a framework for personalized chronic pain management.
Main Methods:
- A Bayesian network approach was utilized.
- Data from 2,400 adult participants (18+ years) from the Qatar Biobank (QBB) were analyzed.
- Participants were stratified into young (18-35), middle-aged (36-60), and senior (61+) age groups, with equal gender distribution.
Main Results:
- The study identified significant direct and indirect associations between pain locations and demographic factors.
- Younger females exhibited a higher prevalence of headaches/migraines compared to younger males.
- Strong correlations were observed between hand and hip pain, as well as hand and neck/shoulder pain. Back pain emerged as a key predictor of generalized pain, especially when co-occurring with hand pain.
- Knee pain prevalence was significantly influenced by age, back pain, and foot pain, particularly in older individuals.
Conclusions:
- Bayesian network parameters reveal probabilistic interdependencies among pain locations, suggesting targeted interventions can mitigate broader chronic pain networks.
- Demographic predispositions significantly influence downstream pain patterns, highlighting the need for personalized chronic pain management.
- The findings offer an actionable framework for clinicians to develop individualized treatment strategies for chronic pain.
