DEXA and body composition
Separates fat, lean mass, visceral fat, and bone density. Useful as a trend; noisier than the decimal places suggest.
The value of DEXA over the bathroom scale is that it distinguishes fat from lean mass, flags visceral fat specifically, and reports bone density along the way.
It reports to a precision it does not have. Hydration and timing move the numbers, so scan under similar conditions and compare across scans rather than agonizing over a single result.
Sources and context
- website — What DEXA measures and how to read it.
Vitamin D status
Test, correct if low, retest. It is cheap and one of the few supplements where deficiency is common and measurable.
Patrick and Attia treat this as a status question rather than a supplement question. Deficiency is common enough — particularly at higher latitudes and through winter — that guessing is a poor strategy.
The retest is the step people skip. Taking vitamin D without ever rechecking means you still do not know where you are.
Sources and context
- website — Vitamin D status and testing overview.
- website — Attia and Patrick on supplementation decisions.
Untreated apnea is common, frequently undiagnosed, and carries real cardiovascular consequences. Walker’s overview treats it as a medical question, and home sleep tests have made getting an answer much easier than it used to be.
Nothing on the rest of this site substitutes for that. Mouth tape in particular is not a treatment for apnea, and taping over it is worse than doing nothing.
Sources and context
The Perform overview separates gas-exchange lab testing from field tests and watch estimates. Only the first actually measures anything; the others infer it, with error bars people tend to ignore.
Estimates are still useful if you keep the method identical and read the trend. The much-quoted mortality associations come from observational cohorts — fit people differ in many ways, so treat the size of the effect with some caution even though the direction is consistent.
Sources and context
- website — Lab, field, and wearable VO2 max estimates compared.
- study — Observational cohort linking cardiorespiratory fitness to mortality.
Attia’s argument: each atherogenic particle carries one ApoB, so measuring ApoB counts the particles. Two people with identical LDL cholesterol can carry very different particle numbers, and the particle number tracks risk more closely.
It is inexpensive and not usually on a standard panel, so you generally have to ask. The outcome data is observational, and what to do about a given number is a conversation with a doctor, not a number to self-treat.
Sources and context
- website — Why particle count can beat cholesterol concentration.
- study — Cohort analysis comparing lipid measures against cardiovascular risk.
Lp(a) and inherited risk context
Largely genetic, barely changed by lifestyle, and worth measuring exactly once. Most people never have.
Lp(a) is set mostly by genetics and does not move much with diet or exercise, which is why the EAS consensus recommends measuring it once in a lifetime. A high value does not change day to day, but it changes how aggressively everything else should be managed.
Drugs targeting it specifically are still in trials. For now the value is context — particularly if heart disease shows up early in your family and nobody has explained why.
Sources and context
- website — Lp(a) as an inherited cardiovascular risk factor.
- website — 2022 consensus statement on measuring Lp(a).
Blood pressure as a risk lever
One of the highest-leverage numbers in medicine, and one of the easiest to measure badly.
SPRINT was stopped early because tighter blood-pressure control showed a clear benefit in the population studied. Few interventions have that kind of evidence behind them.
Technique dominates home readings: feet flat, back supported, arm at heart height, no talking, several minutes seated first, cuff on bare skin and correctly sized. A cuff that is too small reads high. Take several readings across days before concluding anything.
Sources and context
- website — SPRINT trial on intensive blood-pressure control.
CGM as a learning tool, not a diagnosis
Interesting for seeing how you personally respond to meals. Not a diagnostic, and one spike means nothing.
The review of CGM use in people without diabetes finds the evidence for wellness use is thin, while allowing that seeing your own response to particular meals can be genuinely instructive.
Glucose is supposed to rise after eating. Normal ranges in healthy people are wider than the apps imply, and reading a post-meal rise as damage is the standard way to end up anxious about food for no reason.
Sources and context
- study — Review of continuous glucose monitoring in people without diabetes.
Measured versus calculated biomarkers
Some numbers on your lab panel were never measured - they were computed from other numbers. LDL is usually one of them.
Galpin’s point catches people out: standard LDL cholesterol is typically calculated from other values via an equation, not measured directly. The equation is less reliable at high triglycerides or very low LDL.
Before comparing results across labs, check the method, units, and reference range. Two panels using different methods are not directly comparable, and that difference gets mistaken for a real change all the time.
Sources and context
- x — Commonly reported panel values are often calculated, not measured.
Fitness does not rule out cardiovascular risk
Being extremely fit does not mean your arteries are clear. Performance is not a screening test.
Galpin’s example is a very fit coach who turned out to have significant coronary disease. It is one anecdote, and its value is as a corrective to a belief plenty of fit people hold without examining it.
Family history, ApoB, Lp(a), and blood pressure all carry information your training numbers do not.
Sources and context
- x — A highly fit coach with significant coronary disease.
Cardiovascular metrics need context
Resting heart rate, HRV, heart-rate recovery, VO2 max, blood pressure - related, not interchangeable, none self-explanatory.
Attia groups these together while making the point that they are not substitutes for each other. A good HRV does not tell you about your blood pressure.
HRV is the one most often over-read. It varies hugely between people, so your own trend is the only meaningful comparison — and illness, alcohol, and a late meal all move it enough to swamp whatever you were trying to observe.
Sources and context
- x — These metrics measure different things and need sound measurement.