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

Area of Science:

• Psychophysiology
• Biomarker Discovery
• Stress and Mental Health Research

Background:

• Existing literature on Allostatic Load (AL) and Neurovisceral Integration (NVI) models informs the study of stress regulation.
• Heart Rate Variability (HRV) is a common metric, but emerging nonlinear metrics like Heart Rate Fragmentation (HRF) offer new insights.

Purpose of the Study:

• To explore the efficacy of Heart Rate Fragmentation (HRF) as a potential Allostatic Load (AL) biomarker.
• To distinguish psychosocial stress reactivity conditions and predict subclinical mental health symptomology in healthy adults.
• To investigate HRF's utility in understanding stress regulation and adaptation within the framework of AL and NVI models.

Main Methods:

• One hundred fifty-six undergraduate students participated, monitored for cardiovascular activity using a chest band.
• Participants completed psychosocial surveys to identify probable mental health symptoms (pMH).
• Cardiovascular activity was measured during a resting baseline, acute stressor task, and paced breathing recovery (RRR paradigm) to capture HRF.

Main Results:

• HRF significantly differentiated between the resting, stress, and recovery conditions (p < 0.001).
• Healthy individuals showed significantly greater HRF reactivity between conditions compared to the pMH group, indicating a blunted response in the pMH sample.
• While no significant differences were found within individual conditions, HRF reactivity patterns differed between healthy and pMH groups.

Conclusions:

• HRF is established as a promising biomarker associated with mental health and contributes to AL and NVI models.
• HRF may identify early signs of dysregulation in individuals considered 'healthy'.
• HRF offers advantages over traditional HRV biomarkers in non-clinical studies, addressing limitations in detecting subtle stress-related changes.