Diabetes: One Diagnosis, Two Perspectives

We often refer to “diabetes” as if it were a single fact. In reality, it is the same physiological reality expressed through two different cognitive systems. Understanding this distinction is the starting point for moving beyond confusion toward a rational, actionable approach.

1. Medical Diagnosis Perspective: Your Health Traffic Light

Medicine uses objective criteria — fasting glucose, OGTT, HbA1c, random glucose + symptoms, and temporal confirmation — to establish a diagnosis when thresholds are consistently exceeded.

Core value: Medicine’s role is not to explain “why this happened,” but to clearly state “what must be done now to remain safe.” It is an essential tool for risk control and clinical decision-making.

2. Body State Perspective: Your Physiological Roadmap

The body does not suddenly “become diabetic” on a single day. Metabolism, endocrine function, inflammation, and nutrient ratios are in continuous, long-term dynamic change — like an evolving curve.

Key insight:
“Diabetes” is ultimately a road-segment label. It tells you where you are and what rules to follow on this stretch — but it cannot tell you how you arrived here, whether your current trajectory is worsening or stabilizing, or whether improvement is possible ahead.

3. Engineering Description of Body State: Five-Dimensional Steady-State Space

In the life steady-state engineering framework, body state is represented as a five-dimensional coordinate:

(Na/K, Cu/Se, Cu/Zn, Fe/Mn, Ca/Mg)

This is a continuous, measurable, direction-trackable steady-state space.

A medical diagnosis (e.g., diabetes) is not a fixed point in this space, but the projection of prolonged deviation in certain regions onto clinical indicators such as blood glucose.

4. Reference Steady-State Ranges (Green Zone)

Note: These ranges are for engineering trend analysis and modeling only. They do not constitute medical diagnostic criteria.

5. Empirical Example: Fe/Mn Ratio and Diabetes (Open-Source Analysis)

Using public NHANES data and HbA1c ≥ 6.5% as a diagnostic proxy, we observed:

• Higher Fe/Mn ratios correlate with higher diabetes diagnosis rates
• The relationship is continuous and approximately exponential

🔗 Open-source project
(Engineering correlation demonstration only. No causal claims. Not for diagnosis or treatment.)

6. Engineering Practice: Four-Step Method

Goal: Gradually shift deviated ratios (e.g., elevated Fe/Mn) back toward reference ranges.

1. Measure — Use HTMA; focus on ratio trends, not single absolute values
2. Assess — Is Fe/Mn chronically > 15? Is the trend worsening?
3. Act (example directions only):
   • Avoid additional iron load (high-dose supplements, excessive red meat)
   • Support manganese and cofactors through food sources (whole grains, nuts, etc.)
   All changes must not replace medication or contradict medical advice.
4. Repeat — Re-test every 90 days; monitor directional movement toward reference ranges

7. Critical Boundaries (Must Read)

• This content does not alter the medical definition of diabetes
• It does not replace diagnosis or treatment
• It does not promise cure
• HTMA is used solely as an auxiliary tool for long-term steady-state trend observation

The most important sentence:
Diagnosis is a signpost that must be taken seriously — but it is never the destination.
Read the signpost to avoid wrong turns; read the road to go farther.