They appear on the same blood panel, get interpreted against the same disease, and still measure two genuinely different things — one a moment, the other a trailing average.
| HbA1c | fasting glucose | |
|---|---|---|
| What it measures | A three-month average, via glucose permanently bound to haemoglobin over a red cell's roughly 120-day lifespan | Blood glucose at a single moment, after an 8–12 hour fast |
| Fasting required? | No | Yes — a genuine 8–12 hour fast |
| Reacts to a single bad night or meal | No — averages it away over months | Yes — moves with yesterday's sleep and dinner |
| Time to reflect a real change | 8–12 weeks (red cell lifespan) | Days to weeks |
| Diagnostic thresholds | Normal <5.7%, prediabetes 5.7–6.4%, diabetes ≥6.5% | Normal <100 mg/dL, prediabetes 100–125, diabetes ≥126 |
| Can be distorted by something other than glucose | Yes — anaemia, blood loss, haemoglobin variants, kidney disease | Yes — acute illness, poor sleep, a too-long fast, delayed sample processing |
Fasting glucose is the concentration of glucose in your blood at one specific moment, taken after 8–12 hours without food. It is cheap, fast and on almost every basic panel — and it is also just one data point from a system that moves throughout the day with meals, stress, sleep and exercise.
HbA1c sidesteps that volatility by measuring something indirect but stable: the proportion of haemoglobin that has become permanently glycated — chemically bound to glucose — inside red blood cells. Because red cells live around three months, HbA1c is a running average of glucose exposure over roughly the last 8–12 weeks, smoothing out the day-to-day noise a single fasting draw cannot avoid.
Because one is a point-in-time reading and the other is a long average, the two can genuinely tell different stories about the same person. Someone with excellent fasting discipline but large after-meal glucose spikes can show a reassuring fasting glucose while HbA1c quietly reflects the accumulated exposure from those spikes. The reverse pattern also happens: a stressful week, poor sleep, or a hard training session the night before a blood draw can push fasting glucose up temporarily without moving a three-month average at all.
Each measure also has its own, unrelated failure modes. Fasting glucose is distorted by anything that breaks the fasting protocol or triggers a counter-regulatory stress response. HbA1c is distorted by anything that changes red cell lifespan — anaemia, recent blood loss, certain haemoglobin variants such as sickle cell trait, and chronic kidney disease can all make it read artificially high or low regardless of actual glucose control.
The most informative pattern is not either number in isolation — it is what happens when they disagree. A normal HbA1c alongside a raised fasting glucose, or a normal fasting glucose alongside a raised HbA1c, is each a meaningful signal in its own right, not a result to average away. And a normal result on both, paired with a raised fasting insulin, is arguably the pattern worth the most attention: it usually means the system is still compensating, and compensation is exactly the kind of drift neither glucose measure is built to catch early — fasting insulin tends to move first.
In practice this is why both sit on the same metabolic dial here rather than being treated as redundant: fasting glucose is the fast, cheap floor test, and HbA1c is the slower audit that confirms whether a pattern is a one-off or three months of real exposure.
Both diagnostic thresholds were set to detect disease, not to mark where risk is lowest. For HbA1c, the EPIC-Norfolk cohort of over 10,000 adults (Khaw et al., Annals of Internal Medicine, 2004) found 72% of deaths over the following years occurred in people with HbA1c between 5% and 6.9% — comfortably inside the non-diabetic range — with each 1% rise in HbA1c raising all-cause mortality risk by roughly a quarter. For fasting glucose, a 22-year follow-up of nearly 2,000 healthy Norwegian men (Bjørnholt et al., Diabetes Care, 1999) found that fasting glucose in the upper part of the non-diabetic range independently predicted cardiovascular death, after accounting for cholesterol, blood pressure and fitness. Both curves bend upward well before the diagnostic line, which is the whole reason this dashboard scores them against tighter, longevity-optimised ranges rather than the disease-detection cut-points alone.
Yes. They can disagree, and each has failure modes the other does not share. A normal HbA1c with a raised fasting glucose, or the reverse, is a real pattern worth noticing rather than a result to ignore because the other number looked fine.
Fasting glucose. It reflects days to weeks, so it is the faster-moving marker to check progress against a recent change. HbA1c averages roughly three months, so retesting it sooner than about 8–12 weeks after a change mostly measures noise rather than real improvement.
Yes, if something changes red blood cell lifespan — anaemia, recent blood loss, certain haemoglobin variants, or chronic kidney disease can all distort HbA1c independent of actual glucose control. Where any of those apply, fasting glucose, fasting insulin, or continuous glucose monitoring are more reliable, and worth discussing with a clinician.
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Yes. They can disagree, and each has failure modes the other does not share. A normal HbA1c with a raised fasting glucose, or the reverse, is a real pattern worth noticing rather than a result to ignore because the other number looked fine.
Fasting glucose. It reflects days to weeks, so it is the faster-moving marker to check progress against a recent change. HbA1c averages roughly three months, so retesting it sooner than about 8–12 weeks after a change mostly measures noise rather than real improvement.
Yes, if something changes red blood cell lifespan — anaemia, recent blood loss, certain haemoglobin variants, or chronic kidney disease can all distort HbA1c independent of actual glucose control. Where any of those apply, fasting glucose, fasting insulin, or continuous glucose monitoring are more reliable, and worth discussing with a clinician.
Chronological age counts birthdays. Biological age estimates how old your body appears to be functioning, based on measurable biomarkers. Two people born the same year can differ by a decade or more in vascular stiffness, insulin signalling or cardiorespiratory fitness. Biological age makes that gap explicit — and unlike your birthday, it can move in either direction.
Each biomarker you enter is scored against longevity-optimised reference ranges and grouped into one of eight dials. Every dial produces its own biological age, and those are combined using fixed weights into a single composite, then expressed as a Longevity Score from 0 to 100. The weighting reflects how strongly each system predicts healthspan: structural and vascular carry the most, hormonal the least.
No. The short form contains a subset of scoring inputs plus context-only fields, and you can leave any of them blank. It is not a recommendation to obtain tests. Missing values are excluded from the calculation — never treated as zero or as 'normal'. A dial with no scored data is dropped entirely and the remaining weights renormalise.
Some inputs can be measured without bloodwork. Blood pressure needs a home cuff and waist-to-height needs a tape measure. Wearable estimates vary; the floor-based sitting-rising test carries a fall risk and should only be attempted if safe.
Both terms describe what this tool does, and which one fits depends on what you are asking. "Anti-aging" is the term most people search, and loosely means anything aimed at slowing or reversing age-related decline — this tool fits that description if you score your dials and act on what you find. "Healthspan calculator" is the more precise term: healthspan is the number of years lived without serious chronic disease or disability, and that cannot be measured directly, so this tool scores eight systems that each function as an early-warning proxy for it. Either way, the method is the same: real biomarkers, published thresholds, no vanity-metric framing.
Several popular tools ask only about habits — exercise days, sleep hours, smoking, diet quality — and return a single precise-looking age. We looked at the research behind that approach and chose not to build it. Published studies do show real, individually-measured links between specific habits and epigenetic age acceleration, but those effect sizes come from different study populations, different DNA-methylation clocks and different measurement units. Adding them together into one number is not something the underlying research actually supports — it produces a precise-looking result built on an imprecise method. Our dials use direct physiological measurements instead: a real blood pressure reading, a real VO₂ max, a real ApoB value. Several dials score from home-measurable data alone with no quiz-guessing involved — see what you can measure without a blood test, above.
Standard reference ranges describe what is common in a general population, which now includes a great deal of metabolic dysfunction. They are tuned to flag disease, not to identify what is optimal for a long healthspan. A fasting insulin of 20 µIU/mL sits inside most labs' normal range and is strongly associated with insulin resistance. This tool uses longevity-optimised thresholds instead, so a flag here means room for optimisation — not a diagnosis.