1058 Modeling Self-reported Sleep Duration And Hypertension Using Deep Learning Network: Analysis Of The National Health And Nutrition Examination Survey Data. (27th May 2020)

• Record Type: Journal Article
• Authors: Williams, S; Seixas, A; Avirappattu, G; Robbins, R; Lough, L; Rogers, A; Beaugris, L; Bernard, M; Jean-Louis, G
• Is Part Of: Sleep. Volume 43(2020)Supplement 1
• Page Start: A402
• Page End: A402
• Publication Date: 2020-05-27
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsaa056.1054
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Epidemiologic data show strong associations between self-reported sleep duration and hypertension (HTN). Modeling these associations is suboptimal when utilizing traditional logistic regressions. In this study, we modeled the associations of sleep duration and HTN using Deep Learning Network. Methods: Data were extracted from participants (n=38, 540) in the National Health and Nutrition Examination Survey (2006-2016), a nationally representative study of the US civilian non-institutionalized population. Self-reported demographic, medical history and sleep duration were determined from household interview questions. HTN was determined as SBP ≥ 130 mmHg and DBP ≥ 80 mmHg. We used a deep neural network architecture with three hidden layers with two input features and one binary output to model associations of sleep duration with HTN. The input features are the hours of sleep (limited to between 4 and 10 hours) and its square; and the output variable HTN. Probability predictions were generated 100 times from resampled (with replacement) data and averaged. Results: Participants ranged from 18 to 85 years old; 51% Female, 41% white, 22% black, 26% Hispanic, 46% married, and 25% < high school. The model showed that sleeping 7 hours habitually was associated with the least observed HTN probabilities (P=0.023%). HTN probabilities increased as sleep duration decreased (6hrs=0.05%; 5hrs=0.110%; 4hrs=0.16%); HTN probabilities for long sleepers were: (8hrs=0.027; 9hrs=0.024; 10hrs=0.022). Whites showed sleeping 7hrs or 9hrs was associated with lowest HTN probabilities (0.008 vs. 0.005); blacks showed the lowest HTN probabilities associated with sleeping 8hrs (0.07), and Hispanics showed the lowest HTN probabilities sleeping 7hrs (0.04). Conclusion: We found that sleeping 7 hours habitually confers the least amount of risk for HTN. Probability of HTN varies as a function of individual's sex and race/ethnicity. Likewise, the finding that blacks experience the lowest HTN probability when they sleep habitually 8 hours is of great public health importance. Support: This study was supported by funding from the NIH: R01MD007716, R01HL142066, R01AG056531, T32HL129953, K01HL135452, and K07AG052685.