To identify sex-specific patterns based on determinants related to sleep quality, using a representative sample of the Spanish adult population.

Cross-sectional, age-stratified and sex-stratified study.

Community-based assessments in two Spanish provinces (Salamanca and Ávila).

Adults aged 25–65 years (n=500), equally distributed by sex and five age strata, selected from the regional health-card database.

Objective sleep metrics from wrist actigraphy (time in bed, total sleep time (TST), sleep efficiency, wake after sleep onset, number/duration of awakenings, fragmentation/movement indices) and self-reported sleep quality (Pittsburgh Sleep Quality Index).

Standardised baseline assessments collected sociodemographic, clinical, mental-health and lifestyle variables using validated instruments. Actigraphy (ActiGraph GT3X+) recorded triaxial acceleration at 30 Hz over 5 days; data were aggregated in 60 s epochs (ActiLife). Sleep/wake was classified with Cole-Kripke and nocturnal episodes identified with Tudor-Locke before deriving sleep indices. Two-step cluster analysis was applied separately by sex.

Three clusters were identified for each sex, with age and educational level being the most influential factors. In men, the 65-year-old cluster with university education and lower anxious–depressive load showed the highest sleep efficiency (91.8±3.8%) and the lowest TST (351.7±74.8 min). In contrast, the 35-year-old cluster with middle or high school presented the lowest efficiency (88.3±10.0%) and higher TST (368.1±83.8 min). In women, the 55-year-old cluster with middle or high school and low emotional load showed the highest efficiency (93.6±2.8%), despite a reduced TST (352.0±79.7 min), while the 35-year-old cluster, with middle or high school and high levels of anxiety and depression, showed the worst efficiency metrics (89.5±3.9%) and a higher TST (394.8±67.3 min).

Sleep quality in Spanish adults is heterogeneous across sex-specific clusters shaped by age, education and mental-health burden. Cluster-based characterisation may support tailored public-health interventions.

NCT05324267.