Hypothesis

Combining continuous glucose monitoring (CGM)-guided timed walking with real‑time heart‑rate variability (HRV) biofeedback will produce a greater reduction in systolic blood pressure than either intervention alone in non‑diabetic adults.

Mechanistic Reasoning

CGM‑guided walking reduces postprandial glucose spikes, lowering oxidative stress and improving endothelial nitric oxide synthase (eNOS) activity [https://pmc.ncbi.nlm.nih.gov/articles/PMC12612783/]. HRV biofeedback increases parasympathetic (vagal) tone, which attenuates sympathetic‑mediated vasoconstriction and enhances shear‑stress‑induced vasodilation [https://nursing.jmir.org/2023/1/e50991/]. The combined effect synergistically augments flow‑mediated dilation (FMD) and reduces arterial stiffness, leading to a measurable drop in systolic BP.

Testable Prediction

In a randomized crossover n‑of‑1 trial, participants will experience a mean systolic BP reduction of ≥5 mmHg after 4 weeks of combined CGM‑guided walking + HRV biofeedback, whereas each single component will yield <2 mmHg change.

Experimental Design

• Recruit 30 non‑diabetic adults aged 30‑60 with baseline systolic BP 120‑139 mmHg.
• Each participant completes three 4‑week periods in random order: (1) CGM‑guided timed walking (post‑meal walks when glucose >120 mg/dL), (2) HRV biofeedback (daily 10‑min paced breathing guided by HRV feedback), (3) Combined intervention (both).
• Washout of 2 weeks between periods.
• Primary outcome: change in office systolic BP measured blindly.
• Secondary outcomes: 24‑hr ambulatory BP, FMD, fasting lipids, CGM metrics (glucose variability, time in range).

Falsifiability

If the combined intervention does not produce a statistically significant greater systolic BP reduction than the single interventions (p > 0.05), the hypothesis is falsified.

Potential Confounds & Mitigation

• Seasonal BP variation: counterbalance order and include season as covariate.
• Medication changes: exclude participants on antihypertensives and monitor for new prescriptions.
• Adherence: use CGM and HRV app logs to verify compliance; exclude periods with <80 % adherence.

Implications

Demonstrating a synergistic BP effect would justify integrating CGM and HRV feedback into preventive cardiology programs, shifting self‑tracking from passive data collection to active hypothesis‑driven physiology modulation.

References

• Self‑tracking trends: [https://yougov.com/en-us/articles/49119-americans-health-tracking-habits-2024]
• Self‑experimentation validity: [https://nursing.jmir.org/2023/1/e50991/]
• CGM insights in non‑diabetics: [https://pmc.ncbi.nlm.nih.gov/articles/PMC12612783/]