Investigating the associations between weekend catch-up sleep and insulin resistance: NHANES cross-sectional study

BACKGROUND: Insulin resistance (IR) is a precursor to metabolic syndrome. Weekend catch-up sleep (WCS) is practiced to compensate for insufficient weekday sleep, but its impact on IR remains unclear. This study investigated associations between WCS and severe IR risk. METHODS: Data from 1,903 adults participating in the National Health and Nutrition Examination Survey 2017-2020 were analyzed. IR was assessed using the Homeostatic Model Assessment for IR (HOMA-IR) and Metabolic Score for IR (METS-IR), with severe IR defined as the highest quartile. WCS was calculated by subtracting weekday sleep duration from weekend sleep duration and was categorized into five groups. Weighted logistic regression and restricted cubic spline analyses were performed to examine associations between WCS patterns and severe IR risk. Percentages reported were weighted to account for sampling design and population distribution. RESULTS: (59.2%, n = 1,082). Slightly more than half of the participants were female (51.3%, n = 990). A U-shaped relationship between WCS duration and severe IR risk was observed, with the lowest risk at approximately 0.7-1.0 h of WCS. Short WCS durations (0 < WCS ≤ 1 h) were associated with a significantly reduced risk of severe IR as defined by HOMA-IR (OR = 0.63, 95% CI: 0.41-0.97, P = 0.037) compared to stable sleep pattern (WCS = 0). Long WCS durations (WCS ≥ 2 h) were associated with an increased risk of severe IR as defined by METS-IR (OR = 1.88, 95% CI: 1.13-3.14, P = 0.018). Sensitivity analyses showed that the reduction in severe IR risk associated with short WCS durations was more significant in individuals with weekday sleep durations of seven hours or less. CONCLUSIONS: WCS duration exhibits a U-shaped association with severe IR risk, with approximately 0.7-1.0 h of WCS linked to the lowest risk. Both insufficient and excessive WCS are associated with increased severe IR risk, emphasizing the importance of optimal sleep patterns for metabolic health.