The Prevalence of Fibromyalgia in the General Population and At-Risk Subpopulations: A Systematic Review and Meta-Analysis.

Abstract

Estimates of fibromyalgia prevalence vary widely worldwide due to differences in diagnostic criteria, study methodology, and population characteristics. Accurate estimates are essential to inform population-level surveillance, guide resource allocation, and highlight disparities in disease recognition and access to care. The objective of this systematic review and meta-analysis was to determine the global prevalence of fibromyalgia in the general population, and secondarily to identify factors moderating prevalence variation and to assess prevalence in defined at-risk subpopulations. Pooled prevalence estimates with 95% confidence intervals (CIs) were calculated using the inverse variance heterogeneity model with Freeman-Tukey transformation. Subgroup analyses were performed by sex, diagnostic criteria, country, and other study characteristics, and meta-regression assessed moderators including publication year and Human Development Index (HDI). Of 21,645 records identified, 1,728 underwent full-text review and 882 studies were included in the final analysis. Across 38 countries and 30,070,032 individuals (188 studies), the pooled fibromyalgia prevalence in the general population was 1.40% (95% CI, 0.49-2.47), with substantial heterogeneity (I2 = 100%) and very low certainty of evidence. Among at-risk subpopulations (9,771,123 participants; 768 studies), prevalence was markedly higher in autoimmune and inflammatory conditions, such as chronic urticaria (37.1%), interstitial cystitis (30.8%), systemic sclerosis (20.6%), celiac disease (20.5%), and inflammatory bowel disease (19.9%), and elevated in chronic pain, rheumatologic, and post-infection cohorts. Meta-regression identified publication year (β = 0.008, P < .001) and HDI (β = 0.725, P = .002) as significant moderators of prevalence. In conclusion, fibromyalgia affects 1% to 2% of the global population, with substantially higher rates in at-risk subpopulations. Temporal and socioeconomic trends emphasize diagnostic inconsistency and global disparities in care.