An investigation of cardiac indices in normal sleepers and those with insomnia disorder

Cardiovascular disease (CVD) is the world’s leading cause of death. Insomnia, a prevalent disorder among Canadian adults, has been identified in some studies as an independent risk factor for CVD. Heart rate variability (HRV), often used as a proxy for autonomic activity in the body, has been demonstrated to be impaired in individuals with insomnia. Scientists have suggested that results implicate exaggerated sympathetic activation in people with insomnia, which can lead to impaired cardiac reactivity and poorer heart health. Much of the research in this field has been with poorly classified clinical groups and potentially confounding comorbid disorders, making the results difficult to interpret. Findings of the present study extend our understanding of the relationship between insomnia and CVD by addressing the weaknesses of prior research and by utilizing contemporary statistical methods. A well-classified clinical group meeting Research Diagnostic Criteria for Insomnia Disorder (ID; N = 26) was compared to normal sleepers (NS; N = 23) on two well-validated indices of cardiovascular health and autonomic activity, cardiac output (CO) and pre-ejection period (PEP). Values of these indices were derived from an acoustic challenge paradigm that allowed the heart to adapt to the environment via autonomic influence. A multi-level modeling (MLM) approach was used to evaluate both the within-person and between-person differences in autonomic activation and cardiac functioning using a group of predictors that are known to be associated with insomnia and/or CVD. Results of the level two MLM analyses revealed that sleep variables are not significantly predictive of cardiac reactivity indices. A post-hoc linear regression analysis using the same predictor variables to predict HRV revealed that insomnia was significantly predictive of HRV. These conflicting results raise important questions about research methodology, validity of chosen indices, and statistical techniques.