Body Fat (Skinfold) Calculator
The formula
What the body fat (skinfold) tells you
Tape-meat body composition for body fat (skinfold): the US Navy circumference method — the field standard gyms and physicals actually use — with fat and lean mass in kilograms.
Calculation: US Navy: BF% = 86.010·log₁₀(waist−neck) − 70.041·log₁₀(height) + 36.76 (men); +1.08·…−84.52 women. Enter your inputs and every substitution is shown below the result.
Reading the result
Track the trend monthly under the same conditions; ±2 points of tape error is normal.
Limitations and best practice
Hydration and recent meals shift centimetres — measure fasted, morning, same spot.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
How accurate is tape-meat body fat?
Which formula is best for me?
Source & methodology
US Navy Body Composition Program method.
Body Fat (Skinfold) explained: formula, worked example and honest limits
Health numbers only mean something against a reference — this page gives you both the number and the band it sits in. Body Fat (Skinfold) is the kind of number people argue about from memory. This page ends that argument with arithmetic you can watch happen: enter your figures, get Body fat in real time, and see every substitution printed below.
What makes Body Fat (Skinfold) worth calculating is not precision but position: it tells you which side of a threshold you are on, and by how much. A rough figure that settles the direction beats an elaborate one that never commits.
Health figures in Health & Medical describe populations, not individuals — Body Fat (Skinfold) places you on a distribution built from bodies like yours, and the 26.1% answer is a starting point for a conversation, not a diagnosis. That framing is the difference between using a health metric and being misled by one.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here body fat = 26.1%, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Waist / hip circumference first, at ≈28.7 % of the headline for a ten-percent error either way in that input. Read the sections in order and you will be able to reproduce every figure by hand.
Inside the Body Fat (Skinfold) calculation: formula and every input
One formula, published in full: US Navy: BF% = 86.010·log₁₀(waist−neck) − 70.041·log₁₀(height) + 36.76 (men); +1.08·…−84.52 women. Anything you can read, you can reproduce in a spreadsheet, and that reproducibility is the whole point of printing it rather than hiding it behind a button.
Weight (kg) (example value 61) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. Use the same conditions each time (same scale, same time of day) so that changes in the output reflect real change.
Height (cm) (example value 169) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Small measurement errors grow here: a length that is squared or cubed in the model magnifies a one-percent slip into a three-percent answer.
Neck / waist circumference (cm) (example value 40) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
Waist / hip circumference (cm) (example value 89) is a measured number in the unit named by the label; the formula does not convert for you. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Sex (example value Male) is a branching choice rather than a figure you measure; the per-option effects are computed below. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
What each “Sex” choice actually does: Male → 26.1% · Female → 2.0% — each value above is the model’s own output for that option, so the choice can be made on evidence rather than on what a category feels like it means.
Body Fat (Skinfold) with real numbers, step by step
The tool prints its own working; this is the same arithmetic on the example values, reproduced so you can follow it by hand. Starting figures: Weight (kg), Height (cm), Neck / waist circumference (cm), Waist / hip circumference (cm). The computed body fat comes out at 26.1%, which the interpretation band labels “Above the healthy band — the trend matters more than today’s point”.
- Circumference difference waist−neck = 49.0 cm
- Navy formula (log₁₀ terms) → 26.1 %
- Fat mass = 61.0 × 26.1 % = 15.9 kg
Fat mass — 15.9 kg. If your inputs change, this is usually the first companion figure to move.
Lean mass — 45.1 kg. If your inputs change, this is usually the first companion figure to move.
BMI — 21.4. This is the number experienced users quote when the headline alone would mislead.
Keep this worked example open while you enter your own figures: matching the shape of the substitution is the fastest way to spot a unit or convention mistake.
The Body Fat (Skinfold) corridor: your result across a realistic band
The honest version of any estimate is a corridor, and this one is cheap to produce: Body Fat (Skinfold) was recomputed at 5 points along the dominant input, with every other field left untouched.
| Waist / hip circumference setting | Body fat |
|---|---|
| 80 % of the example value | 9.2% |
| 90 % of the example value | 18.6% |
| example inputs | 26.1% |
| 110 % of the example value | 32.3% |
| 120 % of the example value | 37.7% |
The corridor runs from 9.2% to 37.7% across that band — which is the range worth planning inside rather than the single 26.1% point estimate. Reproduce it in the form above by editing Waist / hip circumference alone; the substitution steps will follow your figures exactly.
The levers behind Body Fat (Skinfold), ranked by effect
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the body fat recomputed, so the ranking below is measured rather than asserted. For Body Fat (Skinfold) the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Waist / hip circumference: ten percent up gives 32.3%, ten percent down gives 18.6% — ≈28.7 % of the body fat either way
- Height +10 % → Body Fat (Skinfold) = 23.2% · −10 % → 29.3% (the body fat shifts ≈12.3 %)
- Neck / waist circumference: ten percent up gives 22.9%, ten percent down gives 29.0% — ≈12.2 % of the body fat either way
Waist / hip circumference is the dominant lever here: ten percent either way moves the result by about 28.7 %, from 18.6% to 32.3%. That is where a careless figure does the most damage, so check it against a source, and treat Height as the second priority (≈12.3 % per ten percent). The rest of the inputs earn only a rounding-error of attention, and that asymmetry is the practical payoff of measuring rather than asserting.
What a Body Fat (Skinfold) of 26.1% means in practice
The value above only becomes useful the moment you know what it is being measured against. On the example inputs the band reads “Above the healthy band — the trend matters more than today’s point”; your own figures place you on a different rung of the same ladder. Before treating the band as fact, note its width: ten percent either way on Waist / hip circumference already spans 18.6% to 32.3%. The practical reading rules: read the band as a starting hypothesis, then test it: change the two dominant inputs by ten percent and see whether the verdict survives. Verdicts that survive stress are the ones worth acting on.
Where Body Fat (Skinfold) sits next to similar measures: this tool answers “how much is the Body Fat (Skinfold)”, while the related calculators answer “what do I do about it”. Reading the result alone tends to over-weight a single snapshot; pairing it with the companion tools above turns the number into a decision.
How people get Body Fat (Skinfold) wrong
Hydration and recent meals shift centimetres — measure fasted, morning, same spot. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Comparing a Body Fat (Skinfold) computed here with a figure from another source that uses different conventions. Same name, different denominator — the disagreement is usually in the definitions, not the data.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Waist / hip circumference first, everything else second.
A final trap is presentation: reporting Body Fat (Skinfold) to more decimal places than the inputs support. The tool prints what the arithmetic gives; you should quote only what your least precise field justifies.
Before you trust your Body Fat (Skinfold): a short checklist
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Check Waist / hip circumference before anything else: it is the measured dominant input, ≈28.7 % of Body Fat (Skinfold) per ten percent.
- State, in one sentence, which convention each rate, unit or period in the form is using.
- Verify each input against its original source document, not memory.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
A routine for decision-grade Body Fat (Skinfold)
Using a calculator well sounds trivial, but the difference between a decision-grade figure and a throwaway one lives entirely in the routine. The routine for Body Fat (Skinfold) takes a minute to learn and applies to every input above.
Step 1 — collect, then type. Everything this tool asks for is listed above (weight (kg), height (cm), neck / waist circumference (cm), waist / hip circumference (cm), sex). Pull each figure from something you can point at — paperwork, a dashboard, a label — before touching a field. Guesswork at the input stage cannot be repaired at the interpretation stage. Suspiciously tidy answers deserve the same scrutiny as untidy ones.
Step 2 — compute the version you would not be embarrassed by. If a stranger audited your inputs, which set would you hand over? Enter that set, read the result, and treat everything else as upside. Repeating a calculation with the same numbers proves only that the arithmetic is reliable — which is worth knowing.
Step 3 — play with the inputs on purpose. Ten percent up, ten percent down, one field at a time. Within a few minutes you will know this calculation better than most people who quote its results. A result worth acting on survives having its two shakiest inputs halved.
Step 4 — run the scenario trio. Expected, pessimistic, optimistic. The gap between pessimistic and expected is the number to plan against; the optimistic result is useful only as a ceiling. The inputs are the part of the work that nobody else can do for you.
Step 5 — save the story with the figure. A number without its inputs and its date is unusable within a quarter. Record 26.1%, the assumptions behind it, and today’s date; your future self will be auditing a stranger’s arithmetic. Numbers are cheap to produce and expensive to retract; the extra minute is the cheapest insurance available.
From calculation to decision: where Body Fat (Skinfold) earns its keep
Most Body Measurements disagreements are arithmetic disagreements in disguise. When Body fat of 26.1% sits on the table with its working shown, the conversation stops being about who sounds more confident and starts being about which input is wrong. Most surprises in numbers are surprises about inputs, not about formulas.
The audience for this page is people checking a personal health figure before acting on it. In professional Body Measurements practice the pattern is always the same — screen with Body Fat (Skinfold), then invest slow analysis only in whatever survives the screen. Write the assumptions in the same file as the result, and future arguments take minutes instead of meetings.
Nothing here is stored or transmitted, so the habit of checking is free: open the page, re-enter current figures, compare with the number you saved last time. Repeating a calculation with the same numbers proves only that the arithmetic is reliable — which is worth knowing.
People also ask about Body Fat (Skinfold)
What affects Body Fat (Skinfold) the most?
Body Fat (Skinfold) is driven above all by Waist / hip circumference. Perturbing only that field by ten percent either way produced 32.3% against the 26.1% baseline — a ≈28.7 % response, while Height manages ≈12.3 %.
Which matters more: height or waist / hip circumference?
By the numbers, Waist / hip circumference: a ten-percent change in it moves the result ≈28.7 %, versus ≈12.3 % for Height. Spend your measuring effort in that order — precision on the weaker lever buys almost nothing.
How much does the “Sex” choice change the answer?
The spread is not cosmetic: this choice alone takes Body Fat (Skinfold) from 2.0% to 26.1% with every other input frozen, which is more influence than most of the numeric fields on this page can claim.
What is a typical Body Fat (Skinfold)?
With the example inputs on this page the result is 26.1%, labelled “Above the healthy band — the trend matters more than today’s point”. “Typical” varies with situation, which is why every result here ships with its verdict band and its sensitivity list: they turn one figure into a range you can locate yourself inside.
How do I calculate Body Fat (Skinfold) by hand?
US Navy: BF% = 86.010·log₁₀(waist−neck) − 70.041·log₁₀(height) + 36.76 (men); +1.08·…−84.52 women is the entire method. Work the inputs in that order — Circumference difference waist−neck = 49.0 cm — and you will reach 26.1% on the default figures, the same number this tool prints.
What happens to Body Fat (Skinfold) if waist / hip circumference changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the body fat goes across 18.6% to 32.3%, a swing of roughly 28.7 % around the 26.1% baseline. That ratio is the practical definition of how much this input matters.
Is the Body Fat (Skinfold) result of 26.1% good or bad?
Neither, on its own — the label “Above the healthy band — the trend matters more than today’s point” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Waist / hip circumference alone moves it by ≈28.7 %.
Does Body Fat (Skinfold) change with age?
Yes — reference bands shift deliberately across the lifespan, which is why this tool prints an interpretation rather than a bare number. Re-read the bands each time inputs like Weight (kg) change materially.
How accurate is Body Fat (Skinfold) for me personally?
The formula encodes averages; body-composition and measurement error typically shifts results by a few percent in either direction. Use ranges and trends, and treat any single 26.1% as approximate.
How accurate is tape-meat body fat?
±3 points versus DEXA in lean subjects, better in groups; the trend is reliable even when the level is soft.
Which formula is best for me?
Consistency beats formula choice — the same method, same conditions, every time.
Is my data private on this page?
Yes — computation happens locally in your browser, with no account, no tracking of your inputs and nothing sent to a server. The printed formula is the whole story of what happens to your figures.
Key terms on this page
- Fat mass
- 15.9 kg on the example inputs — a companion figure printed beside the headline of Body Fat (Skinfold) so that no result is read in isolation.
- Lean mass
- 45.1 kg in the default Body Fat (Skinfold) calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- BMI
- 21.4 on the example inputs — a companion figure printed beside the headline of Body Fat (Skinfold) so that no result is read in isolation.
- Body fat
- The primary output of this tool: 26.1% for the default inputs, computed exactly from US Navy: BF% = 86.010·log₁₀(waist−neck) − 70.041·log₁₀(height) + 36.76 (men); +1.08·…−84.52 women.
- Worked example
- The calculation written out in full so that nothing on this page has to be taken on trust.
- Verdict band
- A named zone on the range of plausible results; the example inputs land in “Above the healthy band — the trend matters more than today’s point”, and your inputs may not.
- Sensitivity (±10 %)
- How far the Body Fat (Skinfold) moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Where the Body Fat (Skinfold) model comes from
The model is published arithmetic implemented exactly as written: US Navy: BF% = 86.010·log₁₀(waist−neck) − 70.041·log₁₀(height) + 36.76 (men); +1.08·…−84.52 women. Source of record: US Navy Body Composition Program method. Any other implementation of this model should return the same figure for the same inputs. If one does not, the difference is in its assumptions — which this page prints and that one probably does not.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. The promise to the reader is narrow and testable: same inputs, same output, no silent rounding, and no figure presented without the formula that produced it.
Turning this Body Fat (Skinfold) into a decision
Re-measure on a second occasion before changing behaviour; single readings carry natural day-to-day variation.
Whoever you are (people checking a personal health figure before acting on it), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Health & Medical, a dated figure is a trend, and an undated one is a rumour.