Abstract
BACKGROUND: With the global population ageing rapidly, the combined health burden of chronic pain and chronic diseases is increasingly evident. Despite this, significant gaps remain in understanding the interrelationship between these factors. OBJECTIVE: This study aimed to examine the associations between chronic pain and a range of chronic diseases in a nationally representative sample of US adults. STUDY DESIGN: A cross-sectional analysis was performed using data from the National Health and Nutrition Examination Survey (NHANES). METHODS: Data from four NHANES cycles (1999-2004, 2009-2010) were analyzed, including 7,135 adults aged 20 years and older. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between chronic pain and each chronic disease, adjusting for sociodemographic, lifestyle, medication use, and anthropometric factors. RESULTS: A significant comorbidity risk was identified between chronic pain and multiple chronic diseases, with the strongest associations observed for arthritis (OR = 3.07, 95% CI: 2.71-3.48), renal failure (OR = 1.85, 95% CI: 1.36-2.51), liver disease (OR = 1.77, 95% CI: 1.37-2.29), and congestive heart failure (OR = 1.72, 95% CI: 1.24-2.40). Additionally, smoking (OR = 1.83, 95% CI: 1.66-2.02), prescription medication use (OR = 2.33, 95% CI: 2.10-2.58), and widowhood (OR = 2.13, 95% CI: 1.72-2.65) were also significant risk factors for chronic pain. Subgroup analyses of chronic conditions comorbid with chronic pain further explored the influence of specific factors. CONCLUSION: Chronic pain, as a comorbid factor, should be integrated into the management of chronic diseases. Clinical practice should prioritize synergistic prevention strategies, such as smoking cessation interventions, to reduce both pain and comorbidity risks. To better understand the causal relationships between chronic pain and chronic diseases, future studies should focus on longitudinal designs and include objective pain measures, such as biomarkers.