• Pain · Dec 2007

    Simple patterns behind complex spatial pain reporting? Assessing a classification of multisite pain reporting in the general population.

    • Carsten Oliver Schmidt and Sebastian E Baumeister.
    • Institute of Community Medicine, University of Greifswald, Walther Rathenau Str. 48, 17475 Greifswald, Germany. carsten.schmidt@uni-greifswald.de
    • Pain. 2007 Dec 15; 133 (1-3): 174-82.

    AbstractPain is a common symptom in the general population. While most subjects experience pain in more than one body site, most epidemiologic and clinical studies focus on single pain sites. Limited evidence on spatial pain pattern reporting is available to date. This study develops a taxonomy for complex spatial pain pattern reporting in the general population, and assesses associations to external criteria with emphasis on physical and social functioning. Analyses are based on the cross-sectional German National Health Survey. In total, 7124 subjects aged 18-79 completed a self-rating questionnaire. It comprised items on the 7-day prevalence of pain in 13 body sites. Physical and social functioning were assessed with the Short Form 36. Lifetime prevalences of migraine and degenerative and inflammatory joint diseases were measured using layman descriptions. Latent class cluster analysis was used to classify spatial pain patterns. Four-hundred and seventy-five spatial pain patterns were grouped into seven pain classes: no or one painful body site (46.9%), prevailing headache with limited upper body involvement (16.4%), musculoskeletal upper body pain either with (8.2%) or without headache (8.5%), musculoskeletal pain in the back and lower extremities (10.8%), widespread musculoskeletal pain (4.9%), and whole body pain (4.3%). The seven pain classes differed substantially with regard to sociodemographic characteristics, and showed meaningful associations to self-reported medical diseases. Spatial pain patterns predicted physical functioning better than social functioning. The results suggest that a meaningful classification of complex pain patterns may be based on a very simple measure of pain symptoms.

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