Relationship Age Calculator
The formula
What the relationship age tells you
Tape-meat body composition for relationship age: 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.
Relationship Age explained: formula, worked example and honest limits
You are counting something that matters — this tool counts it exactly, including the edge cases calendars hide. Searchers land on a Relationship Age page for three reasons — to plan, to compare options, and to check that somebody else’s arithmetic is honest. This tool serves all three, and everything after the calculator explains the model instead of hiding it.
What makes Relationship Age 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.
There is a habit that separates people who get useful answers from Dates & Time numbers: they decide what question the figure answers before they compute it. Relationship Age answers “Body fat?” — and nothing else, which is precisely why the result is trustworthy.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here body fat = 27.3%, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Waist / hip circumference first, at ≈24.9 % 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.
The Relationship Age formula, explained
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 135) is a measured number in the unit named by the label; the formula does not convert for you. Weigh rather than estimate where you can — this field usually enters the formula multiplicatively.
Height (cm) (example value 179) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. 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 35) is a plain measured quantity — the unit shown in the label is the unit the formula expects. 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 88) is a plain measured quantity — the unit shown in the label is the unit the formula expects. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Sex (example value Male) is a categorical input — the option you choose decides which numbers the formula uses. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
What each “Sex” choice actually does: Male → 27.3% · Female → 2.0% These figures are computed from this engine, not estimated — switch the dropdown above and you will land on exactly these numbers.
Relationship Age on the example inputs: the complete substitution
Abstract formulas are hard to trust, so here is the complete substitution using the default inputs, written the way an examiner would want it. Starting figures: Weight (kg), Height (cm), Neck / waist circumference (cm), Waist / hip circumference (cm). The computed body fat comes out at 27.3%, which the interpretation band labels “Above the healthy band — the trend matters more than today’s point”.
- Circumference difference waist−neck = 53.0 cm
- Navy formula (log₁₀ terms) → 27.3 %
- Fat mass = 135.0 × 27.3 % = 36.8 kg
Fat mass — 36.8 kg. Read next to the headline, this is the figure that shows the shape of the trade-off.
Lean mass — 98.2 kg. Read next to the headline, this is the figure that shows the shape of the trade-off.
BMI — 42.1. If your inputs change, this is usually the first companion figure to move.
Overwrite any input above and every line of this example updates with it — the substitution is live, not a screenshot of somebody else’s numbers.
The Relationship Age corridor: your result across a realistic band
The honest version of any estimate is a corridor, and this one is cheap to produce: Relationship Age 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 | 12.2% |
| 90 % of the example value | 20.5% |
| example inputs | 27.3% |
| 110 % of the example value | 33.0% |
| 120 % of the example value | 38.0% |
Across 5 settings of Waist / hip circumference, the result spans 12.2% to 38.0%. A decision that only works at one row of this table is a decision waiting for an input to move. Reproduce it in the form above by editing Waist / hip circumference alone; the substitution steps will follow your figures exactly.
Where Relationship Age is fragile — and where it is not
Nobody should have to guess which input matters. The engine was re-run once per field below — ten percent up, ten percent down, everything else frozen — and the results ranked by how far they moved the body fat. For Relationship Age the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Nudge Waist / hip circumference by ±10 % and Relationship Age lands between 20.5% and 33.0% (sensitivity ≈24.9 %)
- Height: ten percent up gives 24.4%, ten percent down gives 30.5% — ≈11.8 % of the body fat either way
- Nudge Neck / waist circumference by ±10 % and Relationship Age lands between 24.7% and 29.7% (sensitivity ≈9.4 %)
Waist / hip circumference is the dominant lever here: ten percent either way moves the result by about 24.9 %, from 20.5% to 33.0%. Measure that input from a document rather than from memory, and treat Height as the second priority (≈11.8 % 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.
Reading the result: bands, zones and thresholds
The value above only becomes useful the moment you know what it is being measured against. The default case lands in the “Above the healthy band — the trend matters more than today’s point” band, and bands are deliberately wide because real situations overlap. The sensitivity list shows how far a modest input error moves you along that ladder: for Waist / hip circumference, ±10 % covers 20.5% to 33.0%. The practical reading rules: compare against your own history before comparing against other people; treat band boundaries as zones, not walls — one point on the wrong side of a threshold rarely changes a real outcome; and when a companion output contradicts the headline, believe the pair.
Where Relationship Age sits next to similar measures: this tool answers “how much is the Relationship Age”, 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.
Why Relationship Age results go wrong — and how to prevent it
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.
Stopping at the first plausible answer. If the result surprises you, the productive question is which input would have to be wrong for the surprise to disappear — then go check that input.
One mistake is specific to this engine: assuming every input matters equally. The computation above shows Waist / hip circumference dominating — a careful figure there beats false precision everywhere else.
A final trap is presentation: reporting Relationship Age 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.
A quick check for any Relationship Age figure
- Compare the output against one published benchmark or a colleague’s independent estimate.
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- Re-verify Waist / hip circumference against a source document — ten percent of error there moves the headline by ≈24.9 %.
- Note the date and the inputs beside the number so the figure can be audited later.
- Confirm the example values are plausible for your own situation before replacing them.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
Step by step: getting a trustworthy Relationship Age out of this tool
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — gather before you type. Relationship Age depends on weight (kg), height (cm), neck / waist circumference (cm), waist / hip circumference (cm), sex. Collect them from a source document — a statement, a report, an invoice, a log — rather than from memory, because recalled inputs are the single largest cause of wrong results. A calculation you cannot explain to somebody else is a calculation you cannot defend.
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. Write the figure down before moving on; memory flatters whichever number you saw last.
Step 3 — change one input at a time. Nudge a single field by ten percent, watch the headline and its companions move, then undo it. Two or three fields will dominate — the sensitivity table above already ranks them for this engine. Repeating a calculation with the same numbers proves only that the arithmetic is reliable — which is worth knowing.
Step 4 — compute a corridor, not a point. Three runs — worst, likely, best — turn Relationship Age from a snapshot into a range. Plan against the pessimistic end and treat the optimistic end as the upside story. Numbers are cheap to produce and expensive to retract; the extra minute is the cheapest insurance available.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 27.3% output. Six months from now the context is what turns this figure into a trend. Note the assumption you are least sure about; that is where the real risk lives.
From calculation to decision: where Relationship Age earns its keep
In Dates & Time the figure computed here is usually the first one somebody asks to see. Having it — with the formula behind it — changes your position in the conversation from participant to reference. Write the figure down before moving on; memory flatters whichever number you saw last.
The audience for this page is people planning around a point or span in time. In professional Dates & Time practice the pattern is always the same — screen with Relationship Age, then invest slow analysis only in whatever survives the screen. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
There is a personal-administration use people overlook: periodic self-checking. Relationship Age quietly drifts as life changes — rates move, bodies change, costs compound — and re-running it a few times a year catches drift while correction is still cheap. The input you reach for first is usually the one you measured longest ago.
People also ask about Relationship Age
What affects Relationship Age the most?
The short answer: Waist / hip circumference. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the body fat recalculated — Waist / hip circumference moved it furthest, by roughly 24.9 % (20.5% to 33.0%).
Which matters more: height or waist / hip circumference?
Waist / hip circumference, by a factor of about 2.1. Concretely: ten percent on Waist / hip circumference is worth ≈24.9 % of Relationship Age, the same nudge on Height only ≈11.8 %. That ranking is re-computed for each page from that page’s own defaults.
How much does the “Sex” choice change the answer?
Across every option this tool offers, the body fat ranges from 2.0% (Female) to 27.3% (Male) with all other inputs held at their example values. The per-option table is printed in the inputs section — this is a decision that genuinely moves the number, not a cosmetic dropdown.
What is a typical Relationship Age?
With the example inputs on this page the result is 27.3%, 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 Relationship Age by hand?
Three steps: write the formula (US Navy: BF% = 86.010·log₁₀(waist−neck) − 70.041·log₁₀(height) + 36.76 (men); +1.08·…−84.52 women), insert your values, and simplify. The worked example section shows exactly that chain for the default inputs; replicating it once on paper teaches you more about Relationship Age than any number of calculator runs.
What happens to Relationship Age if waist / hip circumference changes by 10 %?
Try it in the form above and the printed substitution will follow you; the pre-computed answer for the defaults is 20.5% to 33.0% across the ten-percent probe, i.e. ≈24.9 % sensitivity on the body fat.
Is the Relationship Age result of 27.3% 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 ≈24.9 %.
Can Relationship Age be negative or empty?
Yes, and that is informative rather than broken: a negative Relationship Age usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
What affects Relationship Age the most?
Sensitivity depends on where you start, but the inputs Weight (kg) and Height (cm) typically move Relationship Age further than the rest because they enter the formula multiplicatively. If you can only measure two things well, measure those and hold the others at conservative defaults.
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.
Does this Relationship Age tool store my numbers?
No. The entire calculation runs in your browser session; nothing entered above is transmitted or saved, which is the correct behaviour for sensitive Miscellaneous & Fun figures and the reason you can re-run this page as often as you like.
Key terms on this page
- Fat mass
- 36.8 kg in the default Relationship Age calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Lean mass
- 98.2 kg for the Relationship Age worked case; it sits next to the main result because it carries context the headline leaves out.
- BMI
- 42.1 for the Relationship Age worked case; it sits next to the main result because it carries context the headline leaves out.
- Body fat
- The primary output of this tool: 27.3% 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
- The interpretation attached to a result (“Above the healthy band — the trend matters more than today’s point” on these inputs), which turns a bare number into a position on a scale.
- Sensitivity (±10 %)
- How far the Relationship Age moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Methodology, sources and limits
There is no black box on this page — the engine evaluates 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.
This page is an estimation aid, not professional advice. The design rule is simple: two people entering identical figures must get identical answers. What that buys you is reproducibility — two people, two browsers, the same arithmetic, and a printed trail from inputs to result that either of them can audit.
What to do with your Relationship Age next
Re-run whenever a start date moves — time calculations compound small shifts into large misses.
This page was written for people planning around a point or span in time, and the promise is that nothing above required trust. Bookmark the tool, re-run it whenever an input moves by more than a few percent, and keep the date with the number.