Background Chronic pain conditions as well as Restless Legs Syndrome (RLS) are known to be associated with subjectively and objectively disturbed sleep. RLS has been recently described as highly prevalent in multisite pain and the role of sleep as a modifying factor in this RLS phenotype is unknown. This study aimed to investigate if perceived sleep deficit and other sleep related parameters predict RLS in subjects with multisite pain. Current knowledge/study rationale We have recently demonstrated a strong association between Restless Legs Syndrome (RLS) and number of pain locations. In the current analysis we hypothesized that impaired sleep predicts RLS in subjects with multisite pain. Method Questionnaire-based data from 2727 randomly selected women aged 18–64 years were used to analyze RLS symptoms, self-reported sleep quality, and the degree of daytime sleepiness (Epworth Sleepiness Scale (ESS)) in relation to type, degree and localization of body pain. Potential confounders including anthropometrics, pain localization, co-morbidities, and medication were adjusted for in the Generalized Linear Models (GLM). Results Perceived sleep deficit ≥90 min (OR 2.4 (1.5–3.8), p < 0.001) and frequent nocturnal awakenings (OR 2.3 (1.4–3.6), p < 0.001) were the strongest sleep related predictors for RLS in subjects with multisite pain. Additional factors include prolonged sleep latency (≥30 min, OR 1.8 (1.1–2.8), p = 0.01) and daytime symptoms like elevated daytime sleepiness (ESS score ≥9, OR 1.8 (1.2–2.7), p = 0.005). Accordingly, RLS diagnosis was associated with impaired sleep quality (TST (Total Sleep Time) −8.2 min, sleep latency +8.0 min, and number of awakenings from sleep +0.4, p < 0.01). ESS score increased with RLS diagnosis (+0.74, p < 0.01) and number of pain locations (0.5, 1.7, and 1.8 for 1, 3, and 5 pain areas, p < 0.001). In addition, confounders like pain severity, the history of psychiatric disease, and current smoking were associated with impaired sleep quality in this group of females. Conclusions Perceived sleep deficit and sleep fragmentation are the strongest sleep related predictors of RLS in multisite pain. Potential implication of our results are that clinical management programmes of RLS in subjects with multisite pain need to consider both sleep quality and sleep quantity for individually tailored treatment regimes. Study impact RLS, pain, and sleep disorders are highly interrelated. Our study strongly suggests that clinical management of RLS in patients with multisite pain needs to consider sleep quality as an independent risk factor. [ABSTRACT FROM AUTHOR]