Different association patterns of emotion regulation and heart rate variability in older and younger adults

Abstract

Several mental health conditions seen in older people are associated with impaired emotion regulation. Heart rate variability (HRV) may be an index of emotion regulation capacity, but it is unclear whether and how aging influences this association. Early neurodegenerative processes, such as Alzheimer's disease-related reduction of locus coeruleus (LC) integrity, may play a role, as LC modulates both HRV and self-regulatory networks. We pre-registered a cross-sectional study to investigate the relationship between measures of emotion regulation, HRV and LC structural MRI integrity in a lifespan sample of cognitively normal healthy adults (n = 678, aged 18-88 years, 51% female), recruited between 2010 and 2012 as part of the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) cohort. We hypothesized that age-related differences in the HRV-emotion regulation relationship could be attributed to reduced LC integrity in older versus younger adults. Exploratory analyses incorporated alternative and novel measures of emotionality and LC rostro-caudal functional connectivity gradients from more recent Cam-CAN studies. In contrast to younger adults, we found an inverse relationship between resting HRV and measures of emotion regulation performance in older adults. There was no evidence that LC integrity influenced this relationship. A more 'old-like' LC rostro-caudal functional connectivity gradient, but not LC signal intensity, was related to lower HRV and worse reappraisal outcomes. We identify complexity in the association between HRV and emotion regulation with age and gaps in understanding of the relationship between different measures of LC integrity. Future studies should explore compensatory mechanisms underlying age-related differences in autonomic and emotion regulation.

Keywords: aging; autonomic; emotion regulation; heart rate variability; locus coeruleus.

Graphical Abstract

Figure 1

Proposed relationships between HRV, emotion regulation and LC integrity. Prior studies have mainly reported negative (−) or positive (+) associations between the variables, as well as age-related differences (increase ↑ or decrease ↓). These include a potential bidirectional, positive relationship between emotion regulation and HRV and a negative association between LC MRI signal intensity and HRV.^, With older age, studies have reported improvement in emotion regulation and decline in LC integrity and HRV.^, Unreported or unclear (?) associations (blue arrows) relate to conflicting findings between younger and older adults. We pre-registered the representation of emotion regulation and HRV via latent factors (circles) and LC signal intensity values via observed variables (square). HRV, heart rate variability; LC, locus coeruleus; MRI, magnetic resonance imaging.

Figure 2

Correlational multigroup SEM for emotion regulation capacity and resting HRV. A multigroup SEM showed a negative covariance between HR-adjusted resting HRV obtained using ECG data (logHRV) and Negative Reappraisal (Neg_reappraisal) that was driven by older adults, which survived adjustment for age. The primary +/− secondary variables loading onto the ‘neural’ emotion regulation latent factor (emoreg) have not been shown for clarity. The constant is represented by a triangle, latent factors are represented by circles and observed variables are represented by squares/rectangles. Only significant standardized covariances (double-headed arrows) and regressions (single-headed arrows), formally assessed using the LRT, are reported and shown in blue. Number of observations used: n = 364 (11 missing patterns) younger adults, n = 314 (10 missing patterns) older adults. Younger (left side; ♢1) and older (right side; ♢2) adult submodels are shown. The multigroup structural equation model for HRV reactivity using PPG data showed no significant covariances between the PPG HRV latent change score (dhrv1) and emotion regulation capacity, and multigroup analysis was not subsequently conducted for this model as it did not achieve metric invariance. Further information on covariance/regression estimates and model fit indices are reported in Supplementary Table 7. ECG, electrocardiogram; HR, heart rate; HRV, heart rate variability; PPG, photoplethysmography; SEM, structural equation model.