Sleep Characteristics and Cardiovascular Disease Risk Among Thai Women

Purpose and Background: Sleep disturbances (i.e. poor sleep quality, low sleep efficiency, and Obstructive Sleep Apnea (OSA)) are common during the menopausal transition and menopause. These disturbances are risk factors for Cardiovascular Disease (CVD), obesity, hypertension, and diabetes, with poor long-term outcomes. However, the association of sleep disturbances and CVD risk among Thai women, living in the US, have not been fully explored. Thus, this study examined the association between sleep characteristics and CVD risk in Thai women in Illinois. Theoretical/Conceptual Framework: Grandner’s (2010) Social-ecological Model of Sleep, based on Bronfenbrenner’s (1977) Social-ecological Theory was used as a theoretical framework for this study. The model presents the downstream negative effects of sleep on CVD risk and the upstream determinants to sleep and CVD risk. Methods: Using a cross-sectional descriptive design, 120 Thai women were recruited. The participants completed the Pittsburgh Sleep Quality Index (PSQI), Berlin questionnaire, and Menopause Rating Scale. The CVD risk was calculated using the BMI-based Framingham Risk Score (FRS). Descriptive, bivariate, robust regression with Structural Equation Model (SEM) analysis were performed using STATA 15.1. Results: The average CVD risk score was 6.56 % (SD=5.74) and 20 (17%) participants were classified as having high risk of CVD. The mean subjective sleep quality measured by PSQI was 4.18 (SD=3.03). The majority of participants were good sleepers (n=97, 80.83%). The mean sleep efficiency was 95.36 percent (SD=5.96). A small portion of the participants had a high risk of OSA (n=17, 14.17%). Only the increased risk of OSA was significantly associated with higher CVD risk (B=4.601, p<0.001). Conclusions: The findings of this study indicated that an increased risk of OSA can increase the risk of developing CVD. Sleep disturbances, especially OSA, may be modifiable risk factors to prevent CVD. Future studies may consider developing interventions to improve sleep and treat sleep disturbances to prevent CVD. Additionally, future studies may investigate the role of other sleep-related factors which may be correlated with CVD risk in other populations.