The association between sleeping time and metabolic syndrome features, among older adults living in Mediterranean region: the MEDIS Study

Background: Metabolic syndrome (MetS) as a combination of features has been known to significantly increase cardiovascular disease risk, while MetS presence is linked to lifestyle parameters, including physical activity and dietary habits; recently, the potential impact of sleeping habits has also become an issue under consideration. The aim of this study was to investigate the role of sleep quantity in several MetS components. Methods: Design: a cross-sectional observational study. Setting: 26 Mediterranean islands (MEDIS) and the rural Mani region (Peloponnesus) of Greece. Participants: during 2005-2017, 3130 older (aged 65-100 years) Mediterranean residents were voluntarily enrolled. Measurements: dietary habits (including MedDietScore assessment), physical activity status, sociodemographic characteristics, lifestyle parameters (sleeping and smoking habits), and clinical profile aspects, including MetS components [i.e., waist circumference, systolic and diastolic blood pressure, fasting glucose, triglycerides, and low-density lipoprotein (LDL) and high-density lipoprotein cholesterol (HDL-C)], were derived through standard procedures. Results: The number of daily hours of sleep was independently associated with greater waist circumference [b coefficient/hr = 0.91, 95% confidence interval (CI): 0.34-1.49], higher LDL-cholesterol levels (b/hr = 3.84, 95% CI: 0.63-7.05), and lower diastolic blood pressure levels (b/hr = -0.98, 95% CI: -1.57 to -0.39) after adjusting for participants' age, gender, body mass index, daily walking time, level of adherence to Mediterranean diet, and smoking status. No association was revealed between hours of sleep per day and fasting glucose, triglycerides, HDL-C, and systolic blood pressure. Conclusions: Increased hours of sleep is an indicator of metabolic disorders among elderly individuals, and further research is needed to identify the paths through which sleep quantity is linked to MetS features in different age groups.