Age-Specific Associations between Cardiac Vagal Activity and Functional Somatic Symptoms: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Functional somatic symptoms (FSS) are symptoms not explained by underlying organic pathology. It has frequently been suggested that dysfunction of the autonomic nervous system (ANS) contributes to the development of FSS. We hypothesized that decreased cardiac vagal activity is cross-sectionally and prospectively associated with the number of FSS in the general population. METHODS: This study was performed in a population-based cohort of 774 adults (45.1% male, mean age +/- SD 53.5 +/- 10.7 years). Participants completed the somatization section of the Composite International Diagnostic Interview surveying the presence of 43 FSS. ANS function was assessed by spectral analysis of heart rate variability in the high-frequency band (HRV-HF), reflecting cardiac vagal activity. Follow-up measurements of HRV-HF and FSS were performed approximately 2 years later. RESULTS: Linear regression analyses, with adjustments for gender, age, body mass index, anxiety, depression, smoking, alcohol use, and frequency of exercise, revealed an interaction of cardiac vagal activity with age: HRV-HF was negatively associated with FSS in adults <or=52 years of age (beta = -0.12, t = -2.37, p = 0.018), but positively with FSS in adults aged >52 years (beta = 0.13, t = 2.51, p = 0.012). Longitudinal analysis demonstrated a similar pattern. CONCLUSIONS: Decreased cardiac vagal activity is associated with a higher number of FSS in adults aged <or=52 years in the general population. The unexpected association between increased cardiac vagal activity and FSS in adults aged >52 years needs further exploration. The role of age should be acknowledged in future studies on ANS function in the etiology of FSS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".