Dataset Information

Troubled Hearts: Association Between Heart Rate Variability and Depressive Symptoms in Healthy Children.

ABSTRACT: Heart rate variability (HRV) captures the change in timing of consecutive heart beats and is reduced in individuals with depression and anxiety. The present study investigated whether typically-developing children without clinically recognized signs of depression or anxiety showed a relationship between HRV and depressive or anxiety symptoms. Children aged 9-14 years (N = 104) provided three minutes of cardiac signal during eyes closed rest and eyes open rest. The association between high frequency HRV, low frequency HRV, root mean square of the successive differences (RMSSD), and pNN20 versus depressive symptoms (NIH Toolbox and Child Behavior Checklist) was investigated. Results partially confirm our hypothesis, with pNN20 positively correlated with the self-reported depression measure of loneliness while controlling for age, sex, social status, and physical activity. The association was stronger in male participants. However, there is no consensus in the literature about which HRV measures are associated with depressive symptoms in healthy children. Additional studies are needed which reliably account for variables that influence HRV to establish whether certain HRV measures can be used as an early marker for depression risk in children.

SUBMITTER: Gleichmann DC

PROVIDER: S-EPMC8045383 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Troubled Hearts: Association Between Heart Rate Variability and Depressive Symptoms in Healthy Children.

Gleichmann Dathan C DC Solis Isabel I Janowich Jacqueline R JR Wang Yu-Ping YP Calhoun Vince D VD Wilson Tony W TW Stephen Julia M JM

Applied psychophysiology and biofeedback 20200925 4

Heart rate variability (HRV) captures the change in timing of consecutive heart beats and is reduced in individuals with depression and anxiety. The present study investigated whether typically-developing children without clinically recognized signs of depression or anxiety showed a relationship between HRV and depressive or anxiety symptoms. Children aged 9-14 years (N = 104) provided three minutes of cardiac signal during eyes closed rest and eyes open rest. The association between high freque ...[more]

PMID: 32978742

Similar Datasets

Project description:Importance:Depressive symptoms are associated with lower heart rate variability (HRV), an index of autonomic dysregulation, but the direction of the association remains unclear. Objective:To investigate the temporal association between depression and HRV. Design, Settings, and Participants:A longitudinal, cross-lagged twin difference study, with baseline assessments from March 2002 to March 2006 (visit 1) and a 7-year follow-up (visit 2) at an academic research center with participants recruited from a national twin registry. Twins (n = 166) from the Vietnam Era Twin Registry, who served in the US military during the Vietnam War, and were discordant for depression at baseline were recruited. Main Outcomes and Measures:At both visits, depressive symptoms were measured using the Beck Depression Inventory-II (BDI-II), and HRV was measured through 24-hour electrocardiogram monitoring. To assess the direction of the association, within-pair differences in multivariable mixed-effects regression models were examined, and standardized β coefficients for both pathways were calculated. The associations were evaluated separately in monozygotic and dizygotic twins. Results:In the final analytic sample (N = 146), all participants were men, 138 (95%) were white, and the mean (SD) age was 54 (3) years at baseline. Results showed consistent associations between visit 1 HRV and visit 2 BDI score across all HRV domains and models (β coefficients ranging from -0.14 to -0.29), which were not explained by antidepressants or other participant characteristics. The magnitude of the association was similar in the opposite pathway linking visit 1 BDI score to visit 2 HRV, with β coefficients ranging from 0.05 to -0.30, but it was largely explained by antidepressant use. In stratified analysis by zygosity, significant associations were observed in monozygotic and dizygotic twins for the path linking visit 1 HRV to visit 2 BDI score, although the associations were slightly stronger in dizygotic twins. Conclusions and Relevance:The association between depression and autonomic dysregulation, indexed by HRV, is bidirectional, with stronger evidence suggesting that autonomic function affects depression risk rather than vice versa. The opposite causal pathway from depression to lower HRV is mostly driven by antidepressant use. These findings highlight an important role of autonomic nervous system in the risk of depression and contribute new understanding of the mechanisms underlying the comorbidity of depression and cardiovascular disease.

Project description:BackgroundStress is a significant risk factor for psychiatric disorders such as major depressive disorder (MDD) and panic disorder (PD). This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the autonomic nervous system, which can be evaluated via heart rate variability (HRV). While machine learning has enabled automated stress detection via HRV in healthy individuals, its application in psychiatric patients remains underexplored. This study evaluated the feasibility of using machine-learning algorithms to detect stress automatically in MDD and PD patients, as well as healthy controls (HCs), based on HRV features.MethodsThe study included 147 participants (MDD: 41, PD: 47, HC: 59) who visited the laboratory up to five times over 12 weeks. HRV data were collected during stress and relaxation tasks, with 20 HRV features extracted. Random forest and multilayer perceptron classifiers were applied to distinguish between the stress and relaxation tasks. Feature importance was analyzed using SHapley Additive exPlanations, and differences in HRV between the tasks (ΔHRV) were compared across groups. The impact of personalized longitudinal scaling on classification accuracy was also assessed.ResultsRandom forest classification accuracies were 0.67 for MDD, 0.69 for PD, and 0.73 for HCs, indicating higher accuracy in the HC group. Longitudinal scaling improved accuracies to 0.94 for MDD, 0.90 for PD, and 0.96 for HCs, suggesting its potential in monitoring patients' conditions using HRV. The HC group demonstrated greater ΔHRV fluctuation in a larger number of and more significant features than the patient groups, potentially contributing to higher accuracy. Multilayer perceptron models provided consistent results with random forest, confirming the robustness of the findings.ConclusionThis study demonstrated that differentiating between stress and relaxation was more challenging in the PD and MDD groups than in the HC group, underscoring the potential of HRV metrics as stress biomarkers. Psychiatric patients exhibited altered autonomic responses, which may influence their stress reactivity. This indicates the need for a tailored approach to stress monitoring in these patient groups. Additionally, we emphasized the significance of longitudinal scaling in enhancing classification accuracy, which can be utilized to develop personalized monitoring technologies for psychiatric patients.

Dataset Information

Troubled Hearts: Association Between Heart Rate Variability and Depressive Symptoms in Healthy Children.

Publications

Troubled Hearts: Association Between Heart Rate Variability and Depressive Symptoms in Healthy Children.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets