Influence of nicotine dependence and tabacco consumption intensity in heart rate variability

• Grant number: 13/21430-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: January 01, 2014
• End date: December 31, 2014
• Field of knowledge: Health Sciences - Physiotherapy and Occupational Therapy
• Principal Investigator: Ercy Mara Cipulo Ramos
• Grantee: Ana Paula Soares dos Santos
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil

Abstract

Smoking is considered a public health problem and is the main cause of avoidable death in the world. It is known that nicotine promotes changes in the autonomic nervous system and reduces heart rate variability (HRV), which predisposes to increased morbidity and mortality in smokers due to cardiovascular events. However, there are still few studies that evaluated the HRV impairment at different intensities of tobacco consumption, and there are no studies about the influence of nicotine dependence degree in this damage. Aim: To evaluate the influence of the nicotine dependence degree and tobacco consumption intensity in cardiac autonomic modulation measured by HRV indices. Methods: Smokers with normal lung function confirmed by spirometry will be divided according to the nicotine dependence degree and the tobacco consumption intensity. The HRV indices will be evaluated in the resting condition by heart rate monitor (Polar S810i) in linear methods by the time domain (TD) and frequency domain (FD) and the Poincaré plot. Statistical analysis: The data normality will be tested by the Shapiro-Wilk test and results will be described as mean ± standard deviation, except for non parametric data, which will be described as median (interquartile range 25-75). For analysis between two groups will be used the unpaired t test or Mann-Whitney test depending of the data normality, and the analysis into three groups will be used to One- way ANOVA test followed by Tukey or Kruskal-Wallis test followed by Dunn, also depending of the data normality. Differences will be considered significant at P < 0.05.