Predictors of Opioid Use in Individuals with Pain

The opioid epidemic remains a major global health crisis. To better understand who is most vulnerable to opioid prescribing, misuse, and opioid-related disorders, we analyzed data from the UK Biobank (n=195,808) and the All of Us Research Program (n=48,390). Opioids were more frequently prescribed to individuals with widespread pain and comorbid clinical conditions. We applied machine learning to evaluate both pain-related and non-pain risk factors separately, and the two models predicted opioid use with good accuracy in both cohorts (AUC 0.70–0.78). Longitudinal analyses showed that psychosocial and functional factors contributed as strongly as pain measurements, predicted opioid initiation nearly nine years later, and were elevated in individuals with opioid misuse and opioid-related disorders. These findings demonstrate that psychiatric, psychosocial, and functional vulnerabilities are sufficient to predict opioid use, and that integrating psychosocial risk profiling into routine pain care could support safer prescribing and mitigate opioid-related harms.