Free ToolLIVE
Muscle Mass Calculator.
Estimate whole-body skeletal muscle mass using two published anthropometric equations, shown side by side, compared against age- and sex-specific study reference ranges. For adults only — this is a screening estimate, not a diagnosis.
Processed locally
Two published equations
Study reference comparison
Enter measurements
Adults · client-side calculationAnthropometricsInputs used by the published equations
years
%
Used only for lean/fat-mass context; it does not change either muscle-mass equation.
cm
kg
cm
cm
Hip circumference is required by the no-race anthropometric equations used here.
Pure client-side calculation. No network request, localStorage, IndexedDB, or cookie storage is used by this tool.
Estimated resultSkeletal muscle mass & composition context
Skeletal muscle mass
—
kg estimated SMM (Al-Gindan et al. 2014)
Body composition context
Body-weight share—
Alternative estimate—
Lean body massNot provided
Estimated fat massNot provided
Age/sex study reference
Comparison uses age- and sex-specific skeletal-muscle percentage ranges reported from MRI reference data (Janssen et al. 2000). It is descriptive — a study reference comparison, not a diagnostic cutoff.
Below rangeStudy reference rangeAbove range
Interpretation: These are population-derived anthropometric estimates from two independent published equations. Neither should be used to diagnose sarcopenia or replace MRI, DXA, BIA, clinical examination, or professional assessment.
Reference Comparison
Descriptive study ranges, not diagnostic cutoffs.
The gauge compares estimated skeletal muscle as a percentage of body weight with age- and sex-specific ranges reported in MRI reference data from adults aged 18–88. The labels intentionally say below / within / above the study reference range.
Age- and sex-specific reference ranges
| Age | Female | Male |
|---|---|---|
| 18–29 | 28.4–39.8% | 37.9–46.7% |
| 30–39 | 25.0–36.2% | 34.1–44.1% |
| 40–49 | 24.2–34.2% | 33.1–41.1% |
| 50–59 | 24.7–33.5% | 31.7–38.5% |
| 60–69 | 22.7–31.9% | 29.9–37.7% |
| 70+ | 25.5–34.9% | 28.7–43.3% |
Equations used
Primary — Al-Gindan et al. 2014
Men: SM = 39.5 + 0.665×weight − 0.185×waist − 0.418×hip − 0.0805×age
Women: SM = 2.89 + 0.255×weight − 0.175×hip − 0.0384×age + 0.118×height
Women: SM = 2.89 + 0.255×weight − 0.175×hip − 0.0384×age + 0.118×height
Alternative — Heymsfield et al. 2020
Men: SM = 0.47×weight + 0.03×height + 0.012×age − 0.001×age² − 0.29×waist + 14.3
Women: SM = 0.25×weight + 0.09×height − 0.111×age + 0.0005×age² − 0.06×waist − 3.5
Women: SM = 0.25×weight + 0.09×height − 0.111×age + 0.0005×age² − 0.06×waist − 3.5
Research basis: primary estimate uses Al-Gindan et al., American Journal of Clinical Nutrition (2014), no-race practical anthropometric equations validated against whole-body MRI. Alternative estimate uses Heymsfield et al., Frontiers in Endocrinology (2020), a NHANES-derived model validated against DXA in 12,330 participants. The reference gauge uses age- and sex-specific skeletal-muscle percentage ranges from Janssen et al., Journal of Applied Physiology (2000), a whole-body MRI study of 468 adults aged 18–88. These are population reference data, not clinical diagnostic thresholds. The Heymsfield equations' race/ethnicity term is fixed at the midpoint between the two studied groups, since this tool doesn't collect race — noted here for transparency about how the "alternative estimate" figure was produced.
Carmedin · Pure client-side calculation · No network request, localStorage, IndexedDB, or cookie storage is used by this tool.
Beyond a screening number
We help healthcare organizations build the systems behind population health data.
From clinical data pipelines to reporting dashboards, tools like this are one small piece of a much larger health informatics picture. That's what we do.