Related Experiment Video
Updated: Jul 26, 2026
06:28
Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation
Published on: December 13, 2024
Prediction of Chronic Low Back Pain Risk Based on Dietary Trace Elements Using Multiple Machine Learning Models and
Lishen Zhou1, Jianyue Wang1, Canfeng Wang1
1Department of Orthopedic Surgery, Xiaoshan Hospital of Traditional Chinese Medicine.
Journal of Visualized Experiments : Jove
|June 15, 2026
Summary
Dietary trace elements like calcium and vitamin C may reduce chronic low back pain (LBP) risk. This study analyzed NHANES data, identifying key nutrients associated with lower LBP incidence, offering potential dietary strategies.
Area of Science:
- Nutrition Science
- Epidemiology
- Biostatistics
Background:
- The link between dietary trace elements and chronic low back pain (LBP) is not well understood.
- Understanding this relationship could inform preventative strategies for LBP.
Purpose of the Study:
- To investigate the association between dietary trace elements and the risk of chronic low back pain (LBP).
- To identify specific dietary components that may influence LBP risk using machine learning models.
Main Methods:
- Analysis of National Health and Nutrition Examination Survey (NHANES) data (2001-2004, 2009-2010).
- Application of multicollinearity assessment (Spearman's correlation, VIF) and Boruta algorithm for feature selection.
- Development and interpretation of six machine learning models (Random Forest, SHAP, LIME) to identify key dietary associations with LBP.
Main Results:
- Random Forest models showed the best predictive performance for LBP risk.
- Dietary components including moisture, theobromine, calcium, caffeine, sodium, and vitamin C were inversely associated with LBP risk.
- Model discrimination was moderate (AUC ≈ 0.60-0.72), indicating clinically relevant patterns.
Conclusions:
- Specific dietary factors are associated with a reduced risk of chronic low back pain (LBP).
- Findings suggest potentially modifiable dietary elements for LBP risk stratification and future research.
- Further investigation into these dietary patterns may support public health initiatives for LBP prevention.