Non-HDL cholesterol costs nothing extra — it is arithmetic on numbers already on your panel. ApoB costs more and has to be requested by name. The honest question is not which one is "real," but how much the free version actually gives up.
| ApoB | non-HDL cholesterol | |
|---|---|---|
| What it measures | A direct count of atherogenic particles — one ApoB molecule per LDL, VLDL, IDL or Lp(a) particle | Total cholesterol minus HDL cholesterol — the cholesterol carried by every atherogenic particle combined |
| Extra test required | Yes — must be requested specifically | No — calculated from total cholesterol and HDL, both on every standard panel |
| Fasting required | No | No |
| Affected by high triglycerides | No | No — this is exactly the failure mode non-HDL was built to avoid; calculated LDL-C is unreliable here, non-HDL is not |
| Guideline status (ESC/EAS, 2019) | Class IIa — "should be considered," preferred over non-HDL-C specifically in high triglycerides, diabetes, obesity or very low LDL-C | A reasonable alternative to ApoB where ApoB is unavailable or not reimbursed |
| Scored on this calculator | Yes — atherogenic dial | Yes — atherogenic dial, as the free proxy |
ApoB counts atherogenic particles directly: every LDL, VLDL, IDL and Lp(a) particle carries exactly one apolipoprotein B molecule, so measuring ApoB measures the particle count itself. Non-HDL cholesterol gets at the same underlying biology a different way — it is simply total cholesterol minus HDL cholesterol, which leaves behind the cholesterol carried by every atherogenic particle combined, not LDL alone.
That subtraction requires no additional blood draw and no new assay. Where LDL-C on a standard panel is usually estimated with the Friedewald equation — which becomes unreliable once triglycerides climb — non-HDL sidesteps that calculation problem entirely, because it never needs to estimate LDL-C in the first place.
Non-HDL is widely considered the best available ApoB proxy that a standard lipid panel already provides at no extra cost. It does not require fasting, it survives high triglycerides without distortion, and it is particularly informative in people with metabolic syndrome, where LDL-C alone can look reassuring while total atherogenic particle burden is actually high.
The 2019 ESC/EAS dyslipidaemia guidelines reflect exactly this layered reality: ApoB gets a Class IIa recommendation and is specifically preferred over non-HDL-C in people with high triglycerides, diabetes, obesity or very low LDL-C — precisely the groups where particle count and cholesterol mass are most likely to genuinely diverge. Outside those groups, non-HDL carries most of the same signal for free.
Non-HDL cholesterol's own evidence base is substantial. The Multinational Cardiovascular Risk Consortium (Brunner et al., The Lancet, 2019), pooling data across cohorts, found non-HDL cholesterol of 220 mg/dL or above carried nearly double the cardiovascular disease risk of levels under 145 mg/dL, after adjusting for age, sex and standard risk factors. Ference et al.'s Mendelian randomization analysis (JACC, 2016) found each 1 mmol/L of genetically lower LDL cholesterol — the dominant component of non-HDL for most people — maintained from birth cut coronary heart disease risk by roughly 55%, about double the reduction achieved from the same drop started later in life with a statin.
ApoB's distinguishing evidence runs through discordance specifically: INTERHEART (Yusuf et al., Lancet, 2004), the largest case-control study ever run on heart attack risk across 52 countries, found the ApoB/ApoA1 ratio was the single strongest lipid predictor of myocardial infarction, outperforming every cholesterol-based ratio tested, including non-HDL-based ones.
Non-HDL closes most, but not all, of the gap between LDL-C and ApoB. Because it already includes VLDL and its remnants, it captures more of the "more particles, same or less cholesterol mass" pattern that insulin resistance produces than LDL-C does — but it is still a cholesterol-mass measurement, not a particle count, so some discordance with ApoB remains possible, particularly at the more severe end of insulin resistance and very high triglycerides.
If ApoB is unavailable or not reimbursed, non-HDL is a genuinely strong, free substitute calculated from numbers you likely already have — ask your lab or your own report for total cholesterol and HDL if non-HDL is not printed directly. Where ApoB is available and affordable, particularly if you have high triglycerides, diabetes, obesity or a family history of early heart disease despite "normal" cholesterol, it remains the more direct and better-discriminating measurement of the two.
It is the best free proxy available from a standard lipid panel and captures most of what ApoB would show. The two part ways most clearly in people with high triglycerides, diabetes, obesity or very low LDL-C — the exact groups the 2019 ESC/EAS guidelines flag as where ApoB specifically outperforms it.
They are not fully redundant. Non-HDL is scored because it is free and nearly universal; ApoB is scored because, where available, it is the more direct and better-validated measurement. Scoring both reflects what is actually available to most people rather than assuming everyone has access to ApoB.
Yes. Subtract your HDL cholesterol from your total cholesterol — both numbers are on essentially every standard lipid panel, even if non-HDL is not printed as its own line.
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It is the best free proxy available from a standard lipid panel and captures most of what ApoB would show. The two part ways most clearly in people with high triglycerides, diabetes, obesity or very low LDL-C — the exact groups the 2019 ESC/EAS guidelines flag as where ApoB specifically outperforms it.
They are not fully redundant. Non-HDL is scored because it is free and nearly universal; ApoB is scored because, where available, it is the more direct and better-validated measurement. Scoring both reflects what is actually available to most people rather than assuming everyone has access to ApoB.
Yes. Subtract your HDL cholesterol from your total cholesterol — both numbers are on essentially every standard lipid panel, even if non-HDL is not printed as its own line.
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.