Obstructive sleep apnoea as a risk factor for incident metabolic syndrome: a joined Episono and HypnoLaus prospective cohorts study

Abstract

@ERSpublications REM sleep-disordered breathing is highly prevalent and is associated with metabolic syndrome and diabetes ABSTRACT This study determined the prevalence of rapid eye movement (REM) related sleepdisordered breathing (REM-SDB) in the general population and investigated the associations of REM-SDB with hypertension, metabolic syndrome, diabetes and depression.Home polysomnography (PSG) recordings (n=2074) from the population-based HypnoLaus Sleep Cohort (48.3% men, 57±11 years old) were analysed. The apnoea-hypopnoea index was measured during REM and non-REM sleep (as REM-AHI and NREM-AHI, respectively). Regression models were used to explore the associations between REM-SDB and hypertension, diabetes, metabolic syndrome and depression in the entire cohort and in subgroups with NREM-AHI <10 events·h −1 and total AHI <10 events·h −1 .The prevalence of REM-AHI ⩾20 events·h −1 was 40.8% in the entire cohort. An association between increasing REM-AHI and metabolic syndrome was found in the entire cohort and in both the NREM-AHI and AHI subgroups ( p-trend=0.014, <0.0001 and 0.015, respectively). An association was also found between REM-AHI ⩾20 events·h −1 and diabetes in both the NREM-AHI <10 events·h −1 (odds ratio (OR) 3.12 (95% CI 1.35-7.20)) and AHI <10 events·h −1 (OR 2.92 (95% CI 1.12-7.63)) subgroups. Systolic and diastolic blood pressure were positively associated with REM-AHI ⩾20 events·h −1 .REM-SDB is highly prevalent in our middle-to-older age sample and is independently associated with metabolic syndrome and diabetes. These findings suggest that an increase in REM-AHI could be clinically relevant.This article has supplementary material available from Outcome variables Body weight and height were measured with participants standing without shoes in light indoor clothes. Body weight was measured in kilograms to the nearest 100 g using a Seca scale (Seca, Hamburg, Germany), which was calibrated regularly. Height was measured to the nearest 5 mm using a Seca height gauge. Body mass index (BMI) was calculated as weight (kg)/height (m 2 ).Waist was measured with a non-stretchable tape over the unclothed abdomen at the narrowest point between the lowest rib and the iliac crest, while hip was measured at the largest part of the hips. Two measures were made for waist and hip and the mean (expressed in centimetres) was used to assess the waist-to-hip ratio (WHR). Neck circumference was measured at the middle of the neck between the mid-cervical spine and the superior line of the cricothyroid membrane.

Feasibility of Single Channel Oximetry for Mass Screening of Obstructive Sleep Apnea

“…It is estimated that a large proportions of individuals with OSA are undiagnosed and untreated [3], [4], [5]. Several studies have shown that if untreated, OSA increases the risk of cardiovascular diseases [6], metabolic syndrome [7] and diabetes [8]. Undiagnosed and untreated OSA is associated with behavioral alteration [9], workplace productivity losses and increased motor vehicle accidents due to sleepiness on the road, leading to high clinical and economical costs [10].…”

The Case of Sleep Apnoea and Cardiovascular Events

“…Abdominal visceral fat and intramuscular ectopic fat deposits are pro-inflammatory, diabetogenic and atherogenic (A) 18 . Intramuscular fat deposits in the tongue cause the tongue to enlarge, encroach on the upper airway lumen and increase the risk of OSA (B) 22,23 attributed to OSA to be overestimated including in studies of incident diabetes 28 , hypertension 9 and metabolic syndrome 29 . Visceral fat is the main source of circulating biomarkers of inflammation.…”

Sleep Apnea and Sleep Habits: Relationships with Metabolic Syndrome

“…A recent cohort study evaluated the influence of OSAS on the incidence of metabolic syndrome in a multiethnic sample of 1853 people from two population-based samples (Episono in Brazil and HypnoLaus in Switzerland) [63]. Participants included in the analysis were mainly female (56%) and Caucasian (88%), with an average age of 51.9 (±13.1) years and a BMI of 24.9 (±3.7) kg/m 2 .…”