OBJECTIVES: Apnea hypopnea index (AHI) is used to study the association between obstructive sleep apnea (OSA) and hypertension, but the independent contributions of total sleep time (TST) and apnea/hypopnea event count to hypertension have not been previously investigated. We studied the relationship between polysomnographically assessed TST and hypertension in a sex-balanced community-dwelling cohort of hypertensive patients and normotensive controls (Skara Sleep Cohort). METHODS: Participants (n = 344, men 173, age 61.2 ± 6.5 years, BMI 28.6 ± 4.8 kg/m, mean ± SD) underwent ambulatory home polysomnography. Hypertension was defined according to contemporary Swedish national guidelines. A multivariate logistic regression model was used to predict hypertension status from TST and apnea/hypopnea count (total events/night) adjusting for sex, age and BMI. RESULTS: OSA was highly prevalent in this population (AHI 26 ± 4 events/h). Hypertensive patients had shorter TST than normotensive patients (353 ± 81 vs. 389 ± 65 min, P < 0.001), whereas total apnea/hypopnea count did not differ (167 ± 138 vs. 146 ± 148 events/night, P = 0.2). Multivariate logistic regression analysis revealed that short TST was associated with hypertension status [odds ratio 2.0; 95% confidence interval (95% CI) 1.2-3.3; P = 0.0015]. The significant association between apnea/hypopnea count and hypertension status was nonlinear (odds ratio 2.6; 95% CI 1.2-5.8; P = 0.04). The type of antihypertensive treatment was not found to significantly influence TST. CONCLUSION: Short sleep time assessed by polysomnography was associated with hypertension in this community-dwelling population. Short sleep and presence of sleep apnea appear to independently link to hypertension.
OBJECTIVES:Apnea hypopnea index (AHI) is used to study the association between obstructive sleep apnea (OSA) and hypertension, but the independent contributions of total sleep time (TST) and apnea/hypopnea event count to hypertension have not been previously investigated. We studied the relationship between polysomnographically assessed TST and hypertension in a sex-balanced community-dwelling cohort of hypertensivepatients and normotensive controls (Skara Sleep Cohort). METHODS:Participants (n = 344, men 173, age 61.2 ± 6.5 years, BMI 28.6 ± 4.8 kg/m, mean ± SD) underwent ambulatory home polysomnography. Hypertension was defined according to contemporary Swedish national guidelines. A multivariate logistic regression model was used to predict hypertension status from TST and apnea/hypopnea count (total events/night) adjusting for sex, age and BMI. RESULTS: OSA was highly prevalent in this population (AHI 26 ± 4 events/h). Hypertensivepatients had shorter TST than normotensive patients (353 ± 81 vs. 389 ± 65 min, P < 0.001), whereas total apnea/hypopnea count did not differ (167 ± 138 vs. 146 ± 148 events/night, P = 0.2). Multivariate logistic regression analysis revealed that short TST was associated with hypertension status [odds ratio 2.0; 95% confidence interval (95% CI) 1.2-3.3; P = 0.0015]. The significant association between apnea/hypopnea count and hypertension status was nonlinear (odds ratio 2.6; 95% CI 1.2-5.8; P = 0.04). The type of antihypertensive treatment was not found to significantly influence TST. CONCLUSION:Short sleep time assessed by polysomnography was associated with hypertension in this community-dwelling population. Short sleep and presence of sleep apnea appear to independently link to hypertension.
Authors: Nathaniel F Watson; M Safwan Badr; Gregory Belenky; Donald L Bliwise; Orfeu M Buxton; Daniel Buysse; David F Dinges; James Gangwisch; Michael A Grandner; Clete Kushida; Raman K Malhotra; Jennifer L Martin; Sanjay R Patel; Stuart F Quan; Esra Tasali Journal: J Clin Sleep Med Date: 2015-08-15 Impact factor: 4.062
Authors: Nathaniel F Watson; M Safwan Badr; Gregory Belenky; Donald L Bliwise; Orfeu M Buxton; Daniel Buysse; David F Dinges; James Gangwisch; Michael A Grandner; Clete Kushida; Raman K Malhotra; Jennifer L Martin; Sanjay R Patel; Stuart F Quan; Esra Tasali Journal: Sleep Date: 2015-08-01 Impact factor: 5.849
Authors: Karen A Matthews; Yuefang Chang; Howard M Kravitz; Joyce T Bromberger; Jane F Owens; Daniel J Buysse; Martica H Hall Journal: Sleep Med Date: 2013-11-20 Impact factor: 3.492