Abstract
BACKGROUND: This study aimed to assess the relationship between specific nighttime-daytime sleep patterns and prevalence of different chronic diseases in an elderly population. METHODS: We conducted a community-based cross-sectional study in 4150 elderly Chinese, with an average age of 74 years. Sleep-related variables (nighttime sleep duration, daytime napping and duration) and chronic disease status, including diabetes, cardiovascular diseases (CVD), dyslipidemia cancer and arthritis were collected for the study. Multivariable logistic regression models were used to analyze the relationship between nighttime-daytime sleep patterns and prevalence of chronic diseases. RESULTS: Overall prevalence of any of chronic diseases was 83.8%. Nighttime-daytime sleep patterns were defined according to nighttime sleep duration and habitual nappers/non-nappers. Taking the nighttime-daytime sleep pattern "short nighttime sleep with daytime napping" as reference, those with "long nighttime sleep without daytime napping" had higher prevalence of diabetes [OR and 95% CI, 1.35 (1.01-1.80)] and lower prevalence of arthritis [OR and 95% CI, 0.46 (0.33-0.63)]. And those with "long nighttime sleep with daytime napping" had higher prevalence of diabetes [OR and 95% CI, 1.36 (1.05-1.78)] while lower prevalence of cancer [OR and 95% CI, 0.48 (0.26-0.85)] and arthritis [OR and 95% CI, 0.67 (0.51-0.86)]. Further, in habitual nappers, subjects were classified according to duration of nighttime sleep and daytime naps. Compared to "short nighttime sleep with long daytime napping", individuals with "long nighttime sleep with short daytime napping" had significantly positive association with diabetes prevalence [OR and 95% CI, 1.73 (1.15-2.68)] while border-significantly and significantly negative association with cancer [OR and 95% CI, 0.49 (0.23-1.07)] and arthritis [OR and 95% CI, 0.64 (0.44-0.94)], respectively. CONCLUSIONS: Elderly individuals with chronic diseases had different nighttime-daytime sleep patterns, and understanding these relationships may help to guide the management of chronic diseases.