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Relationships between cardiometabolic disorders and obstructive sleep apnea: Implications for cardiovascular disease risk.

Xiaolong ZhaoXinyi LiHuajun XuYingjun QianFang FangHongliang YiJian GuanShan Kai Yin
Published in: Journal of clinical hypertension (Greenwich, Conn.) (2019)
Previous studies have reported the effects of obstructive sleep apnea (OSA) and cardiometabolic disorders on cardiovascular disease (CVD), but associations between cardiometabolic biomarkers and two cardinal features of OSA (chronic intermittent hypoxia and sleep fragmentation) and their interactions on CVD in OSA populations remain unclear. A total of 1727 subjects were included in this observational study. Data on overnight polysomnography parameters, biochemical biomarkers, and anthropometric measurements were collected. Metabolic syndrome (MS), including blood pressure, waist circumference (WC), fasting glucose, triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C), was diagnosed based on modified criteria of the Adult Treatment Panel III. WC, mean arterial pressure, TG and low-density lipoprotein cholesterol (LDL-C) were independently associated with apnea-hypopnea index (AHI) after adjustment for confounding factors (β = 0.578, P = 0.000; β = 0.157, P = 0.001; β = 1.003, P = 0.019; and β = 4.067, P = 0.0005, respectively). Furthermore, the interaction analysis revealed joint effects between hypertension, obesity, hyperglycemia, and LDL-C dyslipidemia and AHI on CVD. The relative excess risks of CVD due to the interactions with OSA were 2.06, 1.02, 0.48, and 1.42, respectively (all P < 0.05). In contrast, we found no independent effect of the microarousal index (MAI) on CVD. However, LDL-C level and some MS components (WC, TG) were associated with MAI. Our findings indicate that hypoxemia and cardiometabolic disorders in OSA may potentiate their unfavorable effects on CVD. Sleep fragmentation may indirectly predispose patients with OSA to an increased risk of CVD. Thus, cardiometabolic disorders and OSA synergistically influence cardiometabolic risk patterns.
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