19th of October 2025
Continuous Glucose Monitoring and the Science of Longevity
Understanding its promise, limitations, and the physician-led difference
CGM has moved beyond diabetes care. Used thoughtfully, it becomes a dynamic biomarker of metabolic resilience—used superficially, it’s just noise.
Why track glucose if you’re not diabetic?
Healthy adults typically maintain glucose in a narrow range most of the day.
Even within “normal”, post-meal spikes, day-to-day variability and overnight stability differ meaningfully between people.
Repeated sharp excursions and late-evening drift are increasingly linked with oxidative stress, vascular ageing and metabolic inflexibility.
Short, focused CGM cycles (10–14 days) can show:
how everyday meals affect post-prandial area under the curve (AUC)
whether late eating reduces overnight recovery
how stress or sleep debt destabilise glucose
Reference points from healthy cohorts:
Mean glucose ≈ 5.0 mmol/L | Variability (CV) < 14–15 % | Time-in-range > 94 %
These are not rigid targets, but useful context for understanding your own data.
Consumer CGM apps: usefulness and drawbacks
The popularity of ZOE and Lingo has brought CGM into the wellness space.
Both have benefits—and predictable limitations.
ZOE — awareness through nutrition science
Combines a 14-day CGM with gut-microbiome and lipid testing to create personalised food scores.
Excellent for awareness, but interpretation is app-led; spikes can reflect timing, stress, or hormonal changes as much as food itself.
Lingo (Abbott)
Focuses on real-time feedback with a simplified daily “Lingo Count”.
Good for habits and accessibility, but still a consumer tool—data depth and clinical context are limited.
Bottom line:
Apps like these are valuable for awareness, but true optimisation requires medical interpretation and context.
Goal | ZOE | Lingo | Physician-led CGM |
|---|---|---|---|
Focus | Nutrition awareness | Real-time habit feedback | Clinical interpretation & optimisation |
Strength | Microbiome + food scoring | Simple daily nudges | AUC/CV analysis, circadian mapping |
Limitation | App-led, less context | Consumer framing | Requires consultation, purposeful use |
Best for | Food education | Habit formation | Precision longevity goals |
When CGM adds the most value
Analysing AUC after real meals (not only test foods)
Comparing early vs late eating and overnight recovery
Relating changes to stress, caffeine, exercise, alcohol
Integrating data with genomics, sleep and HRV
It’s least helpful when used indefinitely without a goal, or when people chase a single “perfect” number.
How I use CGM differently
Clinical interpretation first: AUC, variability and circadian patterns benchmarked against healthy non-diabetic reference data.
Context always matters: Findings are integrated with genomics (if available), sleep, HRV, training load and the broader health picture.
Actionable and sustainable: Simple, elegant adjustments that stabilise glucose without unnecessary restriction.
Who I recommend CGM to
Performance-minded professionals or athletes seeking steadier energy and metabolic flexibility
Those stuck despite disciplined habits (plateaus, cravings, fatigue)
Clients on structured longevity programmes (fasting, peptide or NAD⁺ protocols) where timing and safety depend on metabolic insight