Undiagnosed mood disorders and sleep disturbances in primary care patients with chronic musculoskeletal pain.
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Author/sSalazar, Alejandro; Dueñas, María; Micó, Juan Antonio; Ojeda, Begoña; Agüera-Ortiz, Luis; Cervilla, Jaime; Failde, Inmaculada
DepartmentBioquímica y Biología Molecular, Microbiología, Medicina Preventiva, Salud Pública
SourcePain Medicine 2013;14:1416-1425.
Objective. The study aims to determine the prevalence of undiagnosed comorbid mood disorders in patients suffering chronic musculoskeletal pain in a primary care setting and to identify sleep disturbances and other associated factors in these patients, and to compare the use of health services by chronic musculoskeletal pain patients with and without comorbid mood disorders. Design. Cross-sectional study. Subjects. A total of 1,006 patients with chronic musculoskeletal pain from a representative sample of primary care centers were evaluated. Outcome Measures. Pain was measured using a visual analog scale and the Primary Care Evaluation of Mental Disorders questionnaire was used to measure mood disorders. Results. We observed a high prevalence of undiagnosed mood disorders in chronic musculoskeletal pain patients (74.7%, 95% confidence interval [CI] 71.9–77.4%), with greater comorbidity in women (adjusted odds ratio [OR] = 1.91, 95% CI 1.37–2.66%) and widow(er)s (adjusted OR = 1.87, 95% CI 1.19–2.91%). Both sleep disturbances (adjusted OR = 1.60, 95% CI 1.17–2.19%) and pain intensity (adjusted OR = 1.02, 95% CI 1.01–1.02%) displayed a direct relationship with mood disorders. Moreover, we found that chronic musculoskeletal pain patients with comorbid mood disorders availed of health care services more frequently than those without (P < 0.001). Conclusions. The prevalence of undiagnosed mood disorders in patients with chronic musculoskeletal pain is very high in primary care settings. Our findings suggest that greater attention should be paid to this condition in general practice and that sleep disorders should be evaluated in greater detail to achieve accurate diagnoses and select the most appropriate treatment.