Assessment of the Impact of Alcohol Consumption Patterns on Heart Rate Variability by Machine Learning in Healthy Young Adults

Gheorghe Nicusor Pop,Ruxandra Christodorescu,Miruna Corbu,Simona Dragan,Dana Emilia Velimirovici,Olivia Bodea,Mihaela Valcovici,Raluca Sosdean

doi:10.3390/medicina57090956

Abstract

Background and Objectives: Autonomic nervous system (ANS) dysfunction is present in early stages of alcohol abuse and increases the likelihood of cardiovascular events. Given the nonlinear pattern of dynamic interaction between sympathetic nervous system (SNS) and para sympathetic nervous system (PNS) and the complex relationship with lifestyle factors, machine learning (ML) algorithms are best suited for analyzing alcohol impact over heart rate variability (HRV), because they allow the analysis of complex interactions between multiple variables. This study aimed to characterize autonomic nervous system dysfunction by analysis of HRV correlated with cardiovascular risk factors in young individuals by using machine learning. Materials and Methods: Total of 142 young adults (28.4 ± 4.34 years) agreed to participate in the study. Alcohol intake and drinking patterns were assessed by the AUDIT (Alcohol Use Disorders Identification Test) questionnaire and the YAI (Yearly Alcohol Intake) index. A short 5-min HRV evaluation was performed. Post-hoc analysis and machine learning algorithms were used to assess the impact of alcohol intake on HRV. Results: Binge drinkers presented slight modification in the frequency domain. Heavy drinkers had significantly lower time-domain values: standard deviation of RR intervals (SDNN) and root mean square of the successive differences (RMSSD), compared to casual and binge drinkers. High frequency (HF) values were significantly lower in heavy drinkers (p = 0.002). The higher low-to-high frequency ratio (LF/HF) that we found in heavy drinkers was interpreted as parasympathetic inhibition. Gradient boosting machine learner regression showed that age and alcohol consumption had the biggest scaled impact on the analyzed HRV parameters, followed by smoking, anxiety, depression, and body mass index. Gender and physical activity had the lowest impact on HRV. Conclusions: In healthy young adults, high alcohol intake has a negative impact on HRV in both time and frequency-domains. In parameters like HRV, where a multitude of risk factors can influence measurements, artificial intelligence algorithms seem to be a viable alternative for correct assessment.

Highlights

Excessive alcohol consumption represents a health problem worldwide, which is associated with increased morbidity and mortality [1]
In our study if we look at the LF and High frequency (HF) values expressed in ms2, we observe that between casual drinkers and heavy drinkers there is just a small difference regarding LF, while HF values are significantly lower in heavy drinkers
The results presented in this study show clearly that high alcohol intake is associated with parasympathetic inhibition, rather than sympathetic activation

Summary

Introduction

Excessive alcohol consumption represents a health problem worldwide, which is associated with increased morbidity and mortality [1]. These are explained, at least partially, by the increased cardiovascular (CV) risk [2] of alcohol-dependent individuals. The increased likelihood of alcohol abusers to suffer CV events is explained, by the close relationship between the autonomic nervous system (ANS) and the heart and vessels [5]. The ANS dysfunction is determined mostly by the inhibition of the parasympathetic nervous system (PNS) and/or the hyperactivity of the sympathetic nervous system (SNS) expressed by a sympathetic hyperarousal (tachycardia, diaphoresis, elevated blood pressure) [6].

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