Introduction
Heart rate variability (HRV) is an important marker of heart health with low values reflecting (sub) clinical target organ damage of heart 1-4. Given that many studies have reported substantial individual differences for HRV, the overall aim of this study was to estimate to what extent demographic, lifestyle and psychosocial factors explain individual differences in HRV in the general population.
Methods
We conducted a cross-sectional study using the baseline data from the Lifelines cohort study, a large prospective study of more than 167,000 individuals. We calculated the Root Mean Square of Successive Differences (RMSSD) between adjacent inter-beat intervals as an index of cardiac parasympathetic nervous system activity using ECG measurements of 10 seconds. RMSSD was corrected to take into account for its dependency on mean heart rate level, and RMSSD was transformed to a natural logarithm (ln) to achieve approximate normality. To assess the relationship of determinant factors with RMSSD, multiple linear regression models were performed. Adjusted R2 was calculated to estimate the total variance explained by determinant variables.
Results
A total of 149,205 individuals were included in the analysis. From this total study population, 58.7% of participants were female, and over one third were in age group 40-50 years. Men and women differed markedly in HRV value where mean lnRMSSD was significantly higher in women (p<0.001). The results showed age and sex alone explained almost one fifth of the individual differences in lnRMSSD values (R2=0.18). Controlling the effect of potential confounders like medication use and disease status increased the variance explained by 1.7%. Adding lifestyle and psychosocial factors into the base model improved the estimate. Nevertheless, the change was small. Our finding also revealed that taking into account the effect of heart rate on HRV resulted in a larger explained variance. Almost five percent increase in R2 was observed when lnRMSSD was corrected for its dependency on heart rate (R2=0.23). Adding lifestyle and psychosocial factors to demographic variables hardly increase (~1%) the variance estimation.
Discussion
In this study age and sex were the most important determinants to explain the individual difference of HRV in which one quarter of the variation was attributed to demographic factors.Further research needs to consider unmeasured variables like genetic information to estimate individual differences in HRV better. In addition, longitudinal studies might be helpful to observe within person change trajectories