A CGM is a quarter-sized sensor that sits on the back of your arm and reads your blood sugar every minute for 14 days.
Every KINS guest wears one. Not because we think they're diabetic — because their annual physical can't see what's actually happening between meals.
My own TruDiagnostic results (May 2025, sample ID SL5U5EK) showed fasting glucose at the 87th percentile epigenetically, LDL at the 95th, triglycerides at the 89th. My metabolic system was aging at 34.3 — 4.3 years older than my chronological age of 30. A standard fasting glucose test at a clinic would have come back "normal." Fourteen days of continuous data would not.
That's the gap a CGM fills. It shows the texture that a single-point blood draw hides.
How it works
You can't feel it. You don't bleed. A tiny filament sits in the fluid between your skin cells, measures glucose there, and beams the number to your phone every minute. By the end of 14 days, you have ~20,000 data points.¹
Three things matter from a CGM trace, and none of them is the fasting number your doctor checks once a year.
Fasting glucose — your baseline first thing in the morning. Optimal is 70–85 mg/dL. Consistently above 100 is the first warning sign of metabolic dysfunction.²
Post-meal spike — how high glucose climbs after eating, and how fast it returns. A spike under 30 mg/dL above baseline that clears in 2 hours is healthy. A spike of 60+ that lingers is the pattern that drives insulin resistance over time.³
Glycemic variability — the jaggedness of your trace across the day. Sharp spikes and crashes — even if the average is normal — predict cardiovascular risk independently of average glucose.⁴
HbA1c, the number your doctor runs annually, is a 3-month average. It hides everything interesting. A CGM is the opposite.
What we actually see at KINS
The pattern is consistent enough that I can describe the typical high-performer CGM trace before we even apply the sensor.
Morning fasting glucose: 90–105 mg/dL. Not diabetic. Not flagged. But higher than the 70–85 range associated with optimal metabolic health. The reason: cortisol. These guests wake in sympathetic dominance. Their liver dumps glucose as part of the stress response, every morning, before they eat anything.
Post-breakfast spike: 50–80 mg/dL above baseline. The oatmeal-with-banana guest spikes to 170–180. The black-coffee-skip-breakfast guest stays flat until noon, then crashes. Neither pattern is good.
3pm crash. The trace drops from 130 to 65 after a carb-heavy lunch. Energy collapses. They reach for coffee or sugar. The cycle repeats.
Elevated overnight baseline. Instead of settling to 75–80 after dinner, the trace hovers at 95–110. Alcohol is usually the reason. A glass of wine at 8pm keeps glucose elevated until 2am and fragments sleep architecture at the same time.
Stress spikes with no food. A difficult call at 4pm pushes glucose up 20–30 mg/dL — no meal involved. The guest watches their own stress response on screen, in real time. That moment lands harder than any lecture.
This is the pattern of someone whose annual physical says "normal" and whose body is quietly building metabolic dysfunction. HbA1c won't catch it for another 5–10 years. The CGM shows it in 48 hours.
Why we pair it with epigenetics
A CGM is honest about glucose. It's silent about the biology underneath.
Two people with the exact same glucose curve can have wildly different insulin levels driving them. That's why we pair CGM data with a fasting insulin draw and HOMA-IR calculation on every KINS panel. The CGM shows the surface. The blood work shows the driver.
My own data told this story. CGM would have flagged the variability. But the epigenetic panel (TruDiagnostic, May 2025) went deeper — metabolic system aging 4.3 years ahead, VLDL cholesterol at the 96th percentile epigenetically, PUFA at the 99th. The CGM trace would have been the symptom. The methylation data was the mechanism.
At KINS, we never interpret a CGM trace in isolation. It's one layer in a stack: CGM + blood panel (60+ markers) + epigenetic age + DUTCH cortisol + HRV tracking. Each fills a gap the others can't see.
What 14 days teaches that a blood draw can't
Here's what a KINS guest actually learns from 14 days of continuous data:
Which "healthy" foods aren't, for them. Glycemic response is partly genetic, partly microbiome, partly muscle mass.⁵ Oatmeal spikes some people to 180 and barely moves others. The only way to know is to test. We have guests eat their normal diet for the first 7 days — no optimization, no "winning." Just data.
What sequence and timing do. Eating protein before carbs flattens the spike. A 10-minute walk after dinner cuts it in half. The same meal at 9pm vs 6pm produces a dramatically different curve. These aren't theoretical — the guest watches it happen on their phone.
Where stress hits metabolically. A bad night of sleep raises fasting glucose 10–20 mg/dL.⁶ Two glasses of wine destroys the overnight curve. A stressful meeting spikes glucose with no food at all. The CGM makes the invisible visible — and for a data-driven person, seeing their own stress response charted minute by minute changes behavior in ways that advice never does.
Days 8–14, we run experiments. Protein first. Walk after dinner. Same meal, different time. No alcohol for 3 days and watch the overnight trace flatten. By the end, the guest has a personalized playbook — not a generic diet, but specific rules for their specific biology.
What it costs and whether it's worth it
A single Abbott Libre 3 sensor: $80–$100 without a prescription. Programs like Levels or Nutrisense bundle two sensors plus coaching for $200–$400.
Ready to experience data-driven longevity?
Book a Discovery Call →For most people, 14 days once is enough. Maybe twice — once now, once after a real intervention. The patterns are learned. The behavior changes stick.
At KINS, the CGM is included in the protocol. We source sensors locally and pair them with clinical interpretation rather than app-based coaching.
What it doesn't tell you
It doesn't measure insulin. This is the biggest gap. A normal-looking glucose curve can mask hyperinsulinemia — the body compensating by pumping more insulin. We always pair CGM with fasting insulin.
It doesn't predict diabetes risk alone. Genetics, body composition, family history, and inflammation all matter. CGM is one input.
It will lie to you on day one. New sensors take 24 hours to calibrate. We tell guests to ignore everything from the first day.
It will make you neurotic if you wear one too long. Most people get the insight in two weeks. After a month, the data turns into anxiety. The protocol is: wear it, learn the patterns, take it off, live with the knowledge.
FAQ
Does it hurt to apply?
A small click. No real pain. The filament is thinner than a hair.
Can I shower and surf with it?
Yes. Waterproof to about 3 feet for 30 minutes. KINS guests wear them in the pool and ocean.
Will insurance cover it?
In the US, only with a diabetes diagnosis. Non-diabetic use is out-of-pocket. Same in most countries.
How is this different from just getting my blood sugar checked?
A fasting glucose test is one data point — a snapshot. A CGM is 20,000 data points over 14 days. It's the difference between a photograph and a time-lapse. The photograph says "you're fine." The time-lapse shows the 3pm crash, the overnight elevation, the stress spike that has nothing to do with food.
Up next:
- How to test cortisol — and why every high performer should
- The math of reversing biological age
- The 14-Day Deep Reset →
References
- Bailey TS, et al. (2015). The performance and usability of a factory-calibrated flash glucose monitoring system. Diabetes Technol Ther, 17(11), 787-794. PubMed
- American Diabetes Association (2024). Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes. Diabetes Care, 47(Suppl 1), S20-S42. PubMed
- Hall H, et al. (2018). Glucotypes reveal new patterns of glucose dysregulation. PLOS Biology, 16(7), e2005143. PubMed
- Monnier L, et al. (2006). Activation of oxidative stress by acute glucose fluctuations compared with sustained chronic hyperglycemia in patients with type 2 diabetes. JAMA, 295(14), 1681-1687. PubMed
- Zeevi D, et al. (2015). Personalized nutrition by prediction of glycemic responses. Cell, 163(5), 1079-1094. PubMed
- Spiegel K, et al. (1999). Impact of sleep debt on metabolic and endocrine function. Lancet, 354(9188), 1435-1439. PubMed
This is educational content, not medical advice. If you have diabetes, prediabetes, or a family history of either, work with a doctor before starting a CGM.