Predictors of fibromyalgia: a population-based twin cohort study

BACKGROUND: Fibromyalgia (FM) is a pain syndrome, the mechanisms and predictors of which are still unclear. We have earlier validated a set of FM-symptom questions for detecting possible FM in an epidemiological survey and thereby identified a cluster with “possible FM”. This study explores prospectively predictors for membership of that FM-symptom cluster. METHODS: A population-based sample of 8343 subjects of the older Finnish Twin Cohort replied to health questionnaires in 1975, 1981, and 1990. Their answers to the set of FM-symptom questions in 1990 classified them in three latent classes (LC): LC1 with no or few symptoms, LC2 with some symptoms, and LC3 with many FM symptoms. We analysed putative predictors for these symptom classes using baseline (1975 and 1981) data on regional pain, headache, migraine, sleeping, body mass index (BMI), physical activity, smoking, and zygosity, adjusted for age, gender, and education. Those with a high likelihood of having fibromyalgia at baseline were excluded from the analysis. In the final multivariate regression model, regional pain, sleeping problems, and overweight were all predictors for membership in the class with many FM symptoms. RESULTS: The strongest non-genetic predictor was frequent headache (OR 8.6, CI 95 % 3.8–19.2), followed by persistent back pain (OR 4.7, CI 95 % 3.3–6.7) and persistent neck pain (OR 3.3, CI 95 % 1.8–6.0). CONCLUSIONS: Regional pain, frequent headache, and persistent back or neck pain, sleeping problems, and overweight are predictors for having a cluster of symptoms consistent with fibromyalgia. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12891-016-0873-6) contains supplementary material, which is available to authorized users.