Abstract TMP85: The Protective Roles of Sleep Duration and Physical Activity on Stroke Risk

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Abstract

Introduction: Health behavior profiles to reduce stroke risk are limited methodologically and hard to apply at the population level. Big data and machine learning was used to quantify dynamic omnidirectional interactions between physical activity, sleep, and stroke risk in the context of multiple socio-demographic, clinical, behavioral, and psychosocial factors.

Hypothesis: Average sleep duration and moderate-vigorous physical activity will reduce stroke risk.

Method: Analysis was based on the 2004-2013 National Health Interview Survey (N=288,888). We employed a machine-learning Bayesian Belief Network (BBN) to model the probabilistic relationships (independent and additive) of sleep duration and physical activity to stroke risk. Factors considered included demographic, behavioral, health/medical, and psychosocial as well as sleep duration (short, average, and long), and physical activity (leisurely walking/bicycling, slow swimming/dancing, and simple gardening activities).

Results: Of the sample, 48.1% were ≤45 years; 77.4% were White; 15.9%, Black/African American; and 45.1% reported less than $35K annually. Overall, the model had a precision index of 95.84%. Average sleepers (7-8hours) were 25% (2.3% to 3%) less likely to experience a stroke. Respectively, long sleepers (>8hours) were 146% (3% to 7.5%) and short sleepers (<7 hours) 22% (3%-3.74%) more likely to report a stroke. A model-based adaptive method evidenced that the combined effect of health status, hypertension, heart condition, income, and alcohol consumption increased the likelihood of stroke from 3% to 90%. Healthy sleep (7-8 hours) and vigorous leisurely activity (30-60 minutes) three to six times per week significantly decreased stroke risk. Using the observational inference technique, we developed idiosyncratic profiles of protective behaviors (i.e. minutes and frequency of moderate or vigorous exercise per week and short, average or long sleep) that reduced stroke risk.

Conclusion: Utilization of BBN analysis is important, as it provides a more dynamic risk stratification system. Healthy sleep and exercise routines reduced stroke risk, based on systematic iterations.

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