Exploring the Multifactorial Predictors of Pain in Chronic Musculoskeletal Pain: A Regression-Based Study

Angel González-de-la-Flor, María Bravo-Aguilar, Jaime Almazán-Polo, Guillermo García-Pérez-de-Sevilla, Pedro Martínez-Lozano, Carlos Romero-Morales Department of Physiotherapy, Faculty of Medicine, Health and Sport, European University of Madrid, Villaviciosa de Odón, Madrid, SpainCorrespondence: Angel González-de-la-Flor, Department of Physiotherapy, Faculty of Medicine Health and Sport, Universidad Europea de Madrid, Calle Tajo s/N, 28670, Villaviciosa de Odón, Madrid, Spain, Email [email protected]: This study aimed to assess differences in pain neurophysiology knowledge between individuals with chronic musculoskeletal pain (CMP) and those without CMP, and to explore associations between pain knowledge, pain intensity, and demographic and lifestyle factors.Methods: A cross-sectional study was conducted with 171 participants, including 120 with CMP and 51 without CMP. Sociodemographic, pain-related, and lifestyle data were collected. Pain knowledge was assessed using the Revised Neurophysiology of Pain Questionnaire (R-NPQ). Statistical analyses included t-tests, chi-squared tests, Pearson’s correlation, and stepwise regression models to identify predictors of pain intensity and CMP presence.Results: Significant differences were found between participants with and without CMP in BMI (p< 0.001), physical activity (p=0.023), education level (p=0.002), and alcohol consumption (p=0.017). Participants with CMP scored lower on the R-NPQ (mean 4.40 ± 2.1) than those without CMP (mean 6.31 ± 2.03; p< 0.001). Pain intensity was negatively associated with R-NPQ scores (r=− 0.315; p< 0.001), physical activity (r=− 0.199; p=0.030), and education level (rho=0.236; p=0.010). Stepwise regression analysis revealed that R-NPQ scores (20.7%), BMI (6.7%), education level (3.9%), and physical activity (2.6%) collectively explained 33.9% of the variance in pain intensity (adjusted R²=0.339). Binary logistic regression identified BMI, R-NPQ scores, and education level as significant predictors of CMP presence, with higher BMI and lower R-NPQ scores increasing the odds of CMP, while higher education levels and physical activity were predictive factors.Conclusion: Individuals with CMP exhibited lower knowledge of pain neurophysiology, higher BMI, reduced physical activity levels, and lower educational attainment, all of which were associated with increased pain intensity and a greater likelihood of CMP presence.Keywords: chronic pain, pain perception, educational status, musculoskeletal pain, body mass index

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SHILAP Revista de lepidopterología
Published
2025-04-01
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Musculoskeletal pain and rehabilitation
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article

Exploring the Multifactorial Predictors of Pain in Chronic Musculoskeletal Pain: A Regression-Based Study

SHILAP Revista de lepidopterología
Musculoskeletal pain and rehabilitation
article

Exploring the Multifactorial Predictors of Pain in Chronic Musculoskeletal Pain: A Regression-Based Study

article en

Abstract

Angel González-de-la-Flor, María Bravo-Aguilar, Jaime Almazán-Polo, Guillermo García-Pérez-de-Sevilla, Pedro Martínez-Lozano, Carlos Romero-Morales Department of Physiotherapy, Faculty of Medicine, Health and Sport, European University of Madrid, Villaviciosa de Odón, Madrid, SpainCorrespondence: Angel González-de-la-Flor, Department of Physiotherapy, Faculty of Medicine Health and Sport, Universidad Europea de Madrid, Calle Tajo s/N, 28670, Villaviciosa de Odón, Madrid, Spain, Email [email protected]: This study aimed to assess differences in pain neurophysiology knowledge between individuals with chronic musculoskeletal pain (CMP) and those without CMP, and to explore associations between pain knowledge, pain intensity, and demographic and lifestyle factors.Methods: A cross-sectional study was conducted with 171 participants, including 120 with CMP and 51 without CMP. Sociodemographic, pain-related, and lifestyle data were collected. Pain knowledge was assessed using the Revised Neurophysiology of Pain Questionnaire (R-NPQ). Statistical analyses included t-tests, chi-squared tests, Pearson’s correlation, and stepwise regression models to identify predictors of pain intensity and CMP presence.Results: Significant differences were found between participants with and without CMP in BMI (p< 0.001), physical activity (p=0.023), education level (p=0.002), and alcohol consumption (p=0.017). Participants with CMP scored lower on the R-NPQ (mean 4.40 ± 2.1) than those without CMP (mean 6.31 ± 2.03; p< 0.001). Pain intensity was negatively associated with R-NPQ scores (r=− 0.315; p< 0.001), physical activity (r=− 0.199; p=0.030), and education level (rho=0.236; p=0.010). Stepwise regression analysis revealed that R-NPQ scores (20.7%), BMI (6.7%), education level (3.9%), and physical activity (2.6%) collectively explained 33.9% of the variance in pain intensity (adjusted R²=0.339). Binary logistic regression identified BMI, R-NPQ scores, and education level as significant predictors of CMP presence, with higher BMI and lower R-NPQ scores increasing the odds of CMP, while higher education levels and physical activity were predictive factors.Conclusion: Individuals with CMP exhibited lower knowledge of pain neurophysiology, higher BMI, reduced physical activity levels, and lower educational attainment, all of which were associated with increased pain intensity and a greater likelihood of CMP presence.Keywords: chronic pain, pain perception, educational status, musculoskeletal pain, body mass index

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Exploring the Multifactorial Predictors of Pain in Chronic Musculoskeletal Pain: A Regression-Based Study · SHILAP Revista de lepidopterología (2025) | TGRS Research Map | TGRS