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Background <p>Limited information exists on how modifiable health risks cluster among patients with back pain. The aim of this study was to identify latent classes defined by selected modifiable-risk indicators and to describe the clinical and demographic characteristics of these classes.</p> Methods <p>This cross-sectional observational survey included consecutive patients with back pain referred to a university-hospital outpatient clinic of Physical and Rehabilitation Medicine between April 2014 and February 2017. Latent class analysis was used to identify classes based on four dichotomous modifiable-risk indicators: current smoking, excessive alcohol consumption, obesity, and physical inactivity. Demographic characteristics, pain severity, and disability were used to describe the identified classes.</p> Results <p>The analysis included 1,379 patients; 881 (64%) were women and the mean age was 47.9 (15.0) years. A two-class solution was selected because it showed better AIC and BIC than the one-class model, while the three-class model did not converge. Entropy was modest (0.466), indicating limited individual-level classification certainty. The two classes were differentiated mainly by physical inactivity: the estimated probability of physical inactivity was 0.38 (95% CI 0.28 to 0.48) in Class 1 and 0.90 (95% CI 0.82 to 0.95) in Class 2. Smoking and excessive alcohol consumption showed smaller differences between classes, while obesity was more common in Class 2. Lower educational attainment and severe pain were associated with a higher probability of belonging to Class 2.</p> Conclusion <p>In this specialized rehabilitation-clinic sample, LCA identified two modifiable-risk pattern classes that differed mainly by physical inactivity. The findings are exploratory and cross-sectional; they should not be interpreted as evidence that physical inactivity causes worse back pain or disability. Further studies are needed to examine whether similar patterns are present in primary care and community settings and whether addressing physical inactivity improves outcomes.</p>

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Modifiable health-risk patterns among patients with back pain: a latent class analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月20日

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  • Mikhail Saltychev,
  • Konsta Koivunen,
  • Juhani Juhola

摘要

Background

Limited information exists on how modifiable health risks cluster among patients with back pain. The aim of this study was to identify latent classes defined by selected modifiable-risk indicators and to describe the clinical and demographic characteristics of these classes.

Methods

This cross-sectional observational survey included consecutive patients with back pain referred to a university-hospital outpatient clinic of Physical and Rehabilitation Medicine between April 2014 and February 2017. Latent class analysis was used to identify classes based on four dichotomous modifiable-risk indicators: current smoking, excessive alcohol consumption, obesity, and physical inactivity. Demographic characteristics, pain severity, and disability were used to describe the identified classes.

Results

The analysis included 1,379 patients; 881 (64%) were women and the mean age was 47.9 (15.0) years. A two-class solution was selected because it showed better AIC and BIC than the one-class model, while the three-class model did not converge. Entropy was modest (0.466), indicating limited individual-level classification certainty. The two classes were differentiated mainly by physical inactivity: the estimated probability of physical inactivity was 0.38 (95% CI 0.28 to 0.48) in Class 1 and 0.90 (95% CI 0.82 to 0.95) in Class 2. Smoking and excessive alcohol consumption showed smaller differences between classes, while obesity was more common in Class 2. Lower educational attainment and severe pain were associated with a higher probability of belonging to Class 2.

Conclusion

In this specialized rehabilitation-clinic sample, LCA identified two modifiable-risk pattern classes that differed mainly by physical inactivity. The findings are exploratory and cross-sectional; they should not be interpreted as evidence that physical inactivity causes worse back pain or disability. Further studies are needed to examine whether similar patterns are present in primary care and community settings and whether addressing physical inactivity improves outcomes.