0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Join our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessIntroduction: Both sleep apnea and diabetes are strong cardiovascular disease (CVD) risk factors with substantial healthcare burden. It is hypothesized that intermittent hypoxemia and sleep fragmentation resulting from sleep apnea may contribute to diabetes through inflammation, insulin resistance and glucose intolerance. Conversely, pre-existing diabetes may promote sleep apnea development through increased abnormalities in autonomic nervous system activity and ventilatory control due to peripheral neuropathy, or through effects on inflammatory pathways. However, no population-based study has simultaneously evaluated the potential bidirectional association between these two highly prevalent disorders. Methods: We followed 161,824 participants from the Nurses' Health Study (NHS; 2002-2012), NHSII (1995-2013), and the Health Professional Follow-up Study (1996-2012) who were free of diabetes, CVD and cancer at baseline. Cox proportional hazards model was used to estimate hazard ratios (HR) for developing diabetes according to sleep apnea status. In parallel, we used similar approaches to estimate risk of developing sleep apnea according to diabetes status among 167,277 participants free of sleep apnea, CVD and cancer at baseline. In all 3 cohorts, diagnoses of diabetes or sleep apnea were identified by validated self-reports. Results: Similar results were observed across 3 cohorts. In the pooled analysis, 9,370 incident diabetes cases were identified during follow-up. After adjusting for age, sex, menopausal status in women, smoking, alcohol drinking, diet quality, physical activity, sleep duration, regular physical exams, and hypertension, the HR (95% CI) for diabetes was 2.28 (2.07, 2.51) comparing those with versus without sleep apnea. The association was attenuated but remained statistically significant after accounting for waist circumference (WC) and BMI (HR: 1.57; 95% CI: 1.42, 1.73). By contrast, we documented 9,409 incident sleep apnea cases during follow-up. Compared with those without diabetes, the multivariable HR (95% CI) for sleep apnea prior to adjustment for BMI and WC was 1.44 (1.25, 1.67) in individuals with diabetes. Although there was no overall association after the adjustment (HR: 1.04; 95% CI: 0.95, 1.14), an increased risk was observed among those with diabetes who used insulin compared with those without diabetes (HR: 1.38; 95% CI: 1.11, 1.72). Conclusions: Sleep apnea is independently associated with an increased risk of diabetes, whereas insulin-dependent diabetes is associated with a higher risk of sleep apnea. Clinical awareness of this bidirectional association may improve prevention and treatment of both diseases and reduce their adverse impact on CVD. Future research aimed at elucidating the mechanisms that underlie each association may identify novel intervention targets.
Tianyi Huang, Brian M. Lin, Meir J. Stampfer, Shelley S. Tworoger, Susan Redline, Frank B Hu (2018). Abstract P086: A Population-based Study of the Bidirectional Association Between Sleep Apnea and Diabetes in Three Prospective US Cohorts. , 137(suppl_1), DOI: https://doi.org/10.1161/circ.137.suppl_1.p086.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2018
Authors
6
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1161/circ.137.suppl_1.p086
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free AccessYes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration