| Metric | Value | Meaning | Copy |
|---|---|---|---|
| {{ row.label }} | {{ row.value }} | {{ row.note }} |
| Method | LBM (kg) | LBM (lb) | Lean (%) | Vs consensus | Why use it | Copy |
|---|---|---|---|---|---|---|
| {{ row.label }} | {{ formatMass(row.lbmKg) }} | {{ formatMass(row.lbmLb) }} | {{ formatPercent(row.leanPercent) }} | {{ formatSignedMass(row.deltaVsConsensusKg) }} kg | {{ row.note }} |
Lean body mass is the part of body weight that is not fat. It includes muscle, bone, organs, and body water, which is why it is often more useful than scale weight alone when you are trying to understand what a gain or loss might actually represent.
This calculator estimates lean mass from weight, height, sex, and a selected equation, then reports the result in kilograms and pounds together with implied fat mass and body-fat percentage. It is most helpful when you want a quick composition estimate, a way to compare several formulas on the same input, or a structured record for tracking changes over time.
The main output follows the chosen formula, but the package does not stop there. It also builds a comparison table across Boer, James, Hume, and Janmahasatian, adds an optional alternate row based on a body-fat method, and gives you both a bar chart for method spread and a composition chart for lean-versus-fat mass.
That comparison view matters because anthropometric equations do not behave identically. Two people with the same body weight can land on different lean-mass estimates once height, sex, age, or circumference measurements are taken into account, and the gap between formulas can be as informative as the headline number itself.
The tool is best treated as an estimation aid rather than as a measurement device. Hydration status, unusual muscularity, edema, pregnancy, pediatric use, and inconsistent tape measurements can all move the result away from what a direct method such as DXA, imaging, or a clinical assessment would show.
The basic workflow is simple. Enter weight and height, choose units, set sex, and pick the lean-body-mass formula you want as the primary result. The summary box then shows that selected estimate in kilograms and pounds, plus the fat mass and fat percentage implied by the difference between body weight and estimated lean mass.
The Formula Summary tab is the best first stop because it keeps all four built-in equations side by side. That table highlights the selected formula, but it also shows whether the other methods cluster tightly or diverge. Tight clustering usually means the estimate is reasonably stable for the given inputs, while a wide spread tells you to treat the result more cautiously.
The advanced panel adds a second path for context rather than a replacement for the main formulas. You can enter a known body-fat percentage directly, estimate body fat from BMI, age, and sex with the Deurenberg method, or use the US Navy circumference method with waist, neck, and, for female inputs, hip measurements.
Those alternate methods are most useful as a cross-check. If an entered or estimated body-fat percentage leads to a lean-mass value close to the chosen formula, confidence in the rough range improves. If the gap is large, the disagreement is telling you that assumptions and measurement technique matter more than the single headline number.
The script converts weight to kilograms and height to centimeters before applying the built-in lean-body-mass equations. The selected result is rounded to two decimal places, converted to pounds with the standard kilogram-to-pound constant, and then used to derive fat mass and body-fat percentage from total body weight.
| Method | Equation used by the package |
|---|---|
| Boer male | LBM = 0.407 × weight + 0.267 × height − 19.2 |
| Boer female | LBM = 0.252 × weight + 0.473 × height − 48.3 |
| James male | LBM = 1.1 × weight − 128 × weight² ÷ height² |
| James female | LBM = 1.07 × weight − 148 × weight² ÷ height² |
| Hume male | LBM = 0.3281 × weight + 0.33929 × height − 29.5336 |
| Hume female | LBM = 0.29569 × weight + 0.41813 × height − 43.2933 |
| Janmahasatian | LBM = 9270 × weight ÷ (6680 + 216 × BMI) |
In these equations, weight is in kilograms, height is in centimeters, and BMI is calculated as weight divided by height in meters squared. Once lean mass is known, the rest of the output is derived directly: fat mass equals body weight minus lean mass, and fat percentage equals fat mass divided by body weight.
The optional body-fat routes work differently. A known body-fat percentage converts directly to lean mass from body weight. The Deurenberg option estimates body fat from BMI, age, and sex, while the US Navy option converts circumference inputs to inches and then applies sex-specific logarithmic tape formulas. The resulting body-fat percentage is clamped to a 0 to 70 percent range before it is turned into an alternate lean-mass row.
Validation is intentionally simple. Weight and height must be greater than zero, and the Navy path only works when the circumference relationships are physically valid, such as waist being larger than neck for the male equation. If an alternate path cannot be computed cleanly, the package omits that extra row rather than inventing a value.
The first question to ask is whether the formulas broadly agree. If Boer, James, Hume, and Janmahasatian all land in a narrow band, the estimate is probably stable enough for personal trend tracking. If one method sits far away from the others, the gap is not an error by itself; it is a sign that body shape, equation assumptions, or population fit may matter more than usual.
The second question is whether you are comparing the right thing. Lean mass in kilograms is usually the clearest headline, but the implied fat percentage can be just as useful because it shows how much of total body weight is being assigned to fat by the chosen method. That is especially helpful when scale weight has changed only a little but training or diet might have changed body composition underneath it.
The alternate body-fat row should be read as a cross-check, not as the final answer. A direct body-fat entry reflects whatever measurement you trust. Deurenberg uses age and BMI, so it is quick but broad. The Navy method can be more personal because it uses tape measurements, but it is also sensitive to where and how consistently those measurements were taken.
This tool is strongest as a repeatable comparison aid. Use the same formula, units, and measurement habits each time if you want trend value. For clinical decisions, sports-performance assessment, or cases where hydration and body composition are unusual, a direct measurement method remains the more reliable reference.
For a male entry of 70 kg and 175 cm, the package computes the following comparison table before any alternate body-fat row is added. The small spread shows why formula selection matters even when the inputs look ordinary.
| Method | Lean mass | Fat mass | Body fat |
|---|---|---|---|
| Boer | 56.02 kg | 13.99 kg | 20.0% |
| James | 56.52 kg | 13.48 kg | 19.3% |
| Hume | 52.81 kg | 17.19 kg | 24.6% |
| Janmahasatian | 55.86 kg | 14.14 kg | 20.2% |
If the same person opens the advanced panel, chooses Deurenberg, and leaves age at 30, the alternate body-fat path gives a body-fat estimate of about 18.1 percent. Converted back into lean mass from the same 70 kg body weight, that produces an alternate row of about 57.31 kg, which sits near the upper end of the built-in equation range.
That kind of comparison is where the tool is most useful. You are not looking for a mathematically perfect winner. You are looking for a believable range and for a repeatable way to track whether the range shifts over time as your measurements change.
There is no single best answer for every body type. The default is Boer, which is a reasonable starting point for many adults, but the stronger habit is to pick one method and stay consistent if you want trend tracking. The comparison table is there so you can judge how sensitive the estimate is to the chosen equation.
No. It estimates lean mass from anthropometric inputs. That means the result includes more than muscle alone and should not be interpreted as a direct muscle-mass measurement.
Because it is built from a different path. A direct body-fat entry depends on the number you supply, Deurenberg depends on BMI and age, and Navy depends on circumference measurements. Different input assumptions naturally lead to different lean-mass estimates.
No. The donut chart shows lean versus fat mass for the currently selected formula only. The bar chart and summary table are the places to compare methods side by side.
No. The visible package logic performs the calculations in the browser and builds the tables, charts, and JSON output directly from the entered values.