Heart Rate Fragmentation: A Novel Analytic Approach to Detect Allostatic Load Among Healthy Adults

Building on prior psychophysiological stress regulation and adaptation literature (e.g., Allostatic load (AL) and Neurovisceral Integration (NVI) models), the current study explores the emerging nonlinear heart rate variability (HRV) metric-heart rate fragmentation (HRF)-and it's efficacy as a potential AL biomarker to distinguish psychosocial stress reactivity conditions and predicting subclinical mental health symptomology in healthy adults. One hundred and fifty-six (n = 156) undergraduate student participants were fitted with a chest band to monitor cardiovascular activity and completed online demographic and psychosocial surveys. Participants were grouped as healthy or displaying probable mental health symptoms (pMH; n = 94, 60.25% of sample) based on scoring above associated inventory thresholds for depression, anxiety, and posttraumatic stress disorder. Subsequently, cardiovascular activity was measured to capture HRF under the established "RRR" experimental stress paradigm: a resting baseline, reactivity to an acute stressor task, and a paced breathing recovery. Results support the global study aim in which HRF significantly differentiated between each RRR condition (p < 0.001). While healthy and pMH individuals did not significantly differ within individual conditions, exploratory analyses revealed that healthy individuals displayed significantly greater HRF reactivity between conditions (p's < 0.001) in comparison to the pMH sample, which displayed a more blunted pattern. Overall, this study establishes associations between HRF and mental health, serving as a promising biomarker that contributes towards the AL and NVI models of stress regulation and adaptation. HRF may also identify early signs of adverse dysregulation in samples otherwise considered "healthy", while addressing the limitations of frequently used HRV biomarkers in non-clinical studies.