Taeho Kim
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This study examines the relationship between heart rate variability (HRV) and glucose metabolism (glucose clearance capacity) in healthy men and women. While HRV was significantly associated with fasting blood glucose, no clear correlation emerged between the glucose area under the curve (AUC) from a 2-hour oral glucose tolerance test (OGTT) and HRV in the overall group--only in the male subgroup did certain HRV indicators correlate with AUC. The study also addresses sex differences, menstrual cycle effects, and measurement method limitations while proposing directions for future research.

1. Research Background and Objectives

As the prevalence of Type 2 diabetes continues to rise in modern society, research into new methods for early detection of subtle metabolic abnormalities is thriving. The autonomic nervous system (ANS) coordinates multiple physiological functions to maintain homeostasis, and heart rate variability (HRV) is a non-invasive indicator that can assess its function.

"Recently, HRV has been utilized in various fields beyond cardiovascular disease prognosis, including exercise performance and recovery status assessment."

Additionally, the 2-hour oral glucose tolerance test (OGTT) is widely used for evaluating glucose metabolic function. This test quantifies glucose processing capacity by tracking blood glucose changes over a set period after glucose intake.

However, research on how autonomic nervous system activity (particularly HRV) relates to glucose regulation capacity, and how this relationship differs by sex, has been limited, which this study aimed to clarify.

2. Research Methods

2.1 Participant Recruitment and Selection Criteria

  • 10 healthy men and 8 healthy women around age 24 participated, with final data analysis including 15 participants (8 men, 7 women) after accounting for recording errors.
  • Exclusion criteria: pregnancy, history of cardiopulmonary or metabolic disease, BMI outside 18.5-24.9 kg/m-squared, medications affecting metabolism, etc.
  • Health status was confirmed via a self-report health history questionnaire.

2.2 Experimental Design

  1. Participants were instructed to fast for at least 12 hours and abstain from exercise and alcohol for 24 hours before the lab visit.

  2. The following tests were conducted between 7 AM and noon on the visit day:

    • Height and weight measurement, body composition assessment via bioelectrical impedance analysis (BIA)
    • HRV measurement: 10 minutes using Finapres NOVA, with the last 5 minutes analyzed using Kubios software

      "HRV analysis utilized indicators including RMSSD, SDNN, LF, and HF."

    • Urine test: Hydration status check (USG)
    • Baseline fasting capillary blood glucose measurement (fingertip blood draw)
    • 75g glucose beverage (TrutolTM) consumed within 1 minute for OGTT
    • Glucose curve measurement: Blood glucose drawn at 30 minutes, 1 hour, and 2 hours post-consumption

  3. HRV measurement details

    • First 5 minutes discarded as adaptation period; only the last 5 minutes analyzed
    • Kubios 'low artifact correction' filter (0.35s sensitivity), detrending, lambda, and interpolation rate settings specified

  4. Menstrual cycle (women) and hydration status questionnaire

    • Women recorded their most recent menstrual start date for cycle-phase representativeness (not incorporated into analysis)

2.3 Statistical Analysis

  • Normality testing (Shapiro-Wilk)
  • Pearson correlation analysis (between fasting blood glucose, OGTT AUC, and HRV indicators)
  • Additional analysis by sex-stratified groups
  • Independent samples t-tests to examine key indicator differences between sexes

3. Key Results

  • Final analysis: 8 men, 7 women (15 total)
  • Mean participant fasting time: overall 13.1+/-1.8 hours; men 12.6+/-2.1, women 13.7+/-1.2 hours
  • Baseline fasting blood glucose: 89.9+/-8.2 mg/dL (normal range)

3.1 Key Correlations Between HRV and Blood Glucose

Overall Group

  • Strong positive correlations between HRV indicators (RMSSD, SDNN, LF, HF) and fasting blood glucose (FBG) (p<0.05)
  • However, no correlation between OGTT AUC and HRV indicators in the overall group
  • "Significant correlations between fasting blood glucose and multiple HRV indicators were confirmed."

Sex-Stratified Analysis

  • Men:
    • Significant positive correlations between AUC and RMSSD, SDNN, LF
    • HF also approached statistical significance (r=.690, p=.058)
  • Women:
    • No significant correlations between AUC and HRV indicators, or fasting blood glucose

Between-Sex Differences

  • Independent samples t-test results: No statistically significant sex differences in AUC, fasting blood glucose, or HRV indicators
  • "No notable differences in resting HRV, OGTT results, or fasting blood glucose were observed between men and women."

3.2 Key Indicator Charts and Graphs

  • Blood glucose changes over OGTT time points Capillary blood glucose over time

    * Blood glucose was significantly elevated at 30 minutes, 1 hour, and 2 hours compared to baseline (fasting) (p<0.05, p<0.001)

  • Sex-stratified AUC-HRV correlations (OGTT) Male AUC vs HRV Female AUC vs HRV

4. Interpretation and Discussion

  • The positive correlation between fasting blood glucose and HRV aligns with existing theory that parasympathetic activity (RMSSD, HF in HRV) plays an important role in insulin secretion activation and blood glucose reduction.

    "Our findings, showing positive correlations between FBG and HRV indicators (RMSSD, HF), support the metabolic influence of parasympathetic activity."

  • Meanwhile, the relationship between glucose AUC (from OGTT) and HRV was observed only in men and was not significant in women.

  • This may be because women's autonomic nervous system activity patterns (sympathetic/parasympathetic regulation) vary with menstrual cycle phase.

    "Female participants were at various phases of their menstrual cycle (mean 19.9+/-11.5 days), and hormonal variability may have diluted the relationship between HRV and metabolic response."

  • When interpreting results that contradict prior research (Rothberg et al. found negative correlations in diabetic groups, while this study found positive correlations in healthy subjects), factors such as measurement posture (supine vs. seated), disease status, and age may play a role.

5. Limitations and Suggestions for Future Research

  • Insufficient sample size: Limits statistical test reliability.

    "This study has the limitation of a small sample size. Replication in larger samples is needed in future research."

  • Female participants' menstrual cycles were not matched or controlled (hormonal changes may have affected results)
  • Single time-point HRV-OGTT simultaneous measurement is insufficient: Longer-term data (e.g., weekly HRV averages) needed
  • Glucose was measured via fingertip (capillary) method: Greater standard error and variability compared to venous blood glucose measurement
  • Fasting time limitations: Reliance on participant compliance (only averages reported, some variance possible)
  • Blood insulin and other metabolic markers not measured
  • OGTT conducted only up to 2 hours; complete blood glucose recovery not confirmed

6. Conclusions

"Heart rate variability did not predict OGTT-based glucose processing capacity in the overall group, but in men, certain HRV indicators showed significant positive correlations with glucose AUC. These results suggest sex-specific associations between autonomic nervous system activity and glucose metabolism. Future research should control for menstrual cycle phase in women, and an integrated approach to HRV and metabolic function assessment is anticipated."

7. References and Data

  • Study data are available in the BioStudies repository (https://doi.org/10.6019/S-BSST1348).
  • The original text provides detailed explanations of all terms and analysis methods used, exact analytical procedures (statistical processing, filter usage, etc.), and descriptions of each HRV and OGTT measurement item.

Closing Thoughts

This study represents a step toward understanding HRV and metabolic health, suggesting that resting HRV activity and glucose metabolic capacity in healthy young adults may differ by sex. These are meaningful results of interest not only to health, exercise, and metabolic disease researchers but also to practitioners in the field. Follow-up research with expanded sample sizes and diversified measurement indicators is expected to continue.

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