Background & Aims

Disparities in chronic pain are driven, in part, by systems of social stratification that distribute resources, prestige, as well as exposures unequally across groups.1 Socioeconomic position (SEP) is a multidimensional construct that captures an individual’s material and social resources  and social rank.2,3 Lower SEP is associated with increased risk for developing chronic pain conditions.4,5 Despite strong theoretical grounding1,2 and broad empirical support for socioeconomic gradients in pain,6,7 there remains little consensus on how best to operationalize SEP for the purposes of describing chronic pain inequalities or for explaining the mechanisms through which these inequalities are produced and maintained.1 This study determined which aspects of SEP are most relevant to identifying individuals currently suffering from chronic pain by addressing methodological limitations of prior work while accommodating data analytic challenges handling large numbers of SEP indicators.

Methods

The National Health Interview Survey (NHIS) is an annual cross-sectional survey of US households. This study focused on the 2019 adult interviews, which included both chronic pain and mental health assessments. Participants (n=31,840) provided data for the high-impact chronic pain outcome.

 

SEP predictors included education, family income, employment, housing, and food security features, as well as the impact of SEP on health care utilization. Additional predictors assessed demographic, mental health, physical health, and geographic domains.

 

Machine learning algorithms (i.e., Gradient Boosted Decision Tree [GBDT], Random Forest, feed-forward Deep Neural Network) assessed the accuracy of SEP and other features in predicting chronic pain status. Models were trained to evaluate accuracy and predictiveness. Shapley Additive Explanation (SHAP) values were employed to evaluate the importance of features.

Results

There were 2,977 adults (9.4%) who reported high-impact chronic pain. Of the machine learning algorithms evaluated, GBDT achieved the highest overall accuracy (93%) and discriminatory power (area under the curve [AUC]=0.88).

General self-rated health status was the most important predictive feature for high-impact chronic pain. Other physical health measures, including being told by a doctor they had arthritis and prescription opioid use in the past 12 months, were also among the most important predictive features.

Four SEP variables were among the 10 most relevant predictive features: working in the past week, ratio of family income to poverty threshold, family income, and highest level of education completed by any adult in the home.

Conclusions

SEP features (i.e., income, education) were among the most important predictors of high-impact chronic pain – more so even than well-established chronic pain risk factors such as smoking status and body mass index. Another SEP feature – working in the past week – was the third most important predictive feature for high-impact chronic pain.

 

Consistent with prior research, general self-rated health status, depressive symptoms, and prescription opioid use were among the most important predictors of chronic pain. The present study adds to this literature by showing that distinct SEP dimensions, including material resources (e.g., ratio of family income to poverty threshold) and social rank (i.e., household educational attainment), were among the top 10 chronic pain predictors. Although cross-sectional, findings suggest that policies addressing poverty and financial relief could benefit individuals suffering from high-impact chronic pain.

References

  1. Galobardes, B., Lynch, J., & Smith, G. D. Measuring socioeconomic position in health research. British Medical Bulletin. 2007;81(1): 21.
  2. Khalatbari-Soltani S, Blyth FM. Socioeconomic position and pain: a topical review. Pain 2022;163(10):1855-1861.
  3. Krieger N, Williams DR, Moss NE. Measuring social class in US public health research: concepts, methodologies, and guidelines. Annual Review of Public Health. 1997;18(1):341-378.
  4. Karran EL, Grant AR, Moseley GL. Low back pain and the social determinants of health: a systematic review and narrative synthesis. Pain 2020;161(11):2476-2493.
  5. Zajacova A, Rogers RG, Grodsky E, Grol-Prokopczyk H. The relationship between education and pain among adults aged 30–49 in the United States. The journal of pain 2020;21(11-12):1270-1280.
  6. Janevic MR, McLaughlin SJ, Heapy AA, Thacker C, Piette JD. Racial and socioeconomic disparities in disabling chronic pain: findings from the health and retirement study. The Journal of Pain 2017;18(12):1459-1467.
  7. Poleshuck EL, Green CR. Socioeconomic disadvantage and pain. Pain 2008;136(3):235-238.
  8. Gaskin DJ, Richard P. The economic costs of pain in the United States. J Pain 2012;13:715–24.
  9. Williams AC de C, Fisher E, Hearn L, Eccleston C. Psychological therapies for the management of chronic pain (excluding headache) in adults. Cochrane Database of Systematic Reviews 2020, Issue 8. Art. No.: CD007407.

Presenting Author

Matthew C. Morris

Poster Authors

Matthew Morris

PhD

Vanderbilt University Medical Center

Lead Author

Hamidreza Moradi

PhD

University of North Carolina Agricultural and Technical State University

Lead Author

Maryam Aslani

MS

University of North Texas

Lead Author

Sicong Sun

PhD

UCLA

Lead Author

Cynthia Karlson

PhD

University of Mississippi Medical Center

Lead Author

Emily Bartley

University Of Florida

Lead Author

Stephen P. Bruehl

PhD

Vanderbilt University Medical Center

Lead Author

Kristin Archer

PT PhD

University of Iowa

Lead Author

Patrick Bergin

MD

University of Mississippi Medical Center

Lead Author

Kerry Kinney

Vanderbilt University

Lead Author

Ashley Watts

PhD

Vanderbilt University

Lead Author

Felicitas Huber

PhD

Washington University in St. Louis

Lead Author

Gaarmel Funches

PhD

University of Mississippi Medical Center

Lead Author

Subodh Nag

PhD

Vanderbilt University Medical Center

Lead Author

Burel Goodin

Washington University in St. Louis

Lead Author

Topics

  • Racial/Ethnic/Economic Differences/Disparities