DOI 10.1097/pr9.0000000000001480
Prevalence and competing risk of psychiatric comorbidities in chronic low back pain by age group.
Аннотация
INTRODUCTION
Nonspecific chronic low back pain (cLBP) frequently accompanies psychiatric comorbidities, including anxiety, depression, insomnia, and substance use disorders (SUDs), which worsen patient outcomes. However, research characterizing the prevalence and temporal risk of these comorbidities using large-scale, age-stratified data remains limited.
Objectives
This study evaluated the prevalence of anxiety, depression, insomnia, and SUDs after cLBP diagnosis and the population's vulnerability to these conditions.
METHODS
We performed a retrospective cohort study using the TriNetX network, analyzing deidentified electronic health records from over 150 million patients. Individuals with cLBP from 2014 to 2023 were categorized into age groups (0-25, 26-49, and 50+ years) based on neurodevelopmental milestones and cLBP epidemiology. Annual point prevalence of anxiety, depression, insomnia, and SUDs was calculated for each group. Competing risk analysis determined the 10-year cumulative incidence of each outcome after cLBP diagnosis.
RESULTS
Among 1,045,921 individuals with cLBP, all psychiatric comorbidities rose in prevalence across age groups from 2014 to 2023. By 2023, anxiety prevalence reached 30.8% (0-25), 39.0% (26-49), and 33.0% (50+); depression prevalence was 20.9%, 28.7%, and 27.1%, respectively. Insomnia prevalence increased from 6.9% (0-25) to 13.6% (26-49) and 20.1% (50+). SUD substantially increased from 0 to 25 (7.73%) to 26 to 49 (27.7%) and 50+ (23.2%) groups. For all groups, females showed higher anxiety, depression, and insomnia rates, whereas SUDs were more common in males. Ten-year competing risk cumulative incidence showed that anxiety had the highest risk across all groups: 30.5% (0-25), 27.3% (26-49), 20.5% (50+).
CONCLUSION
Individuals with cLBP face a rising and substantial burden of psychiatric comorbidities, with age- and sex-specific increasing patterns. Screening and interventions should be tailored by age to improve outcomes for this high-risk population.
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