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magent RFM Calculator (Woolcott 2018)
x402
magent RFM Calculator (Woolcott 2018) is a paid API for AI agents from api.magentlab.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-13).
Calculates Relative Fat Mass (RFM) from height, waist circumference, and sex using the Woolcott 2018 published formula
Price / call$0.005
Success—
StatusUnknown
How this service works
Relative fat mass (RFM) from height, waist, and sex (Woolcott 2018). Height and waist in meters in the paper; magent accepts height_cm or height_in and waist_cm. Deterministic published arithmetic with citation. Not a medical device, not a body-fat diagnosis, and not later obesity cutoffs. magent does not measure the patient.
Output
Returns a numeric Relative Fat Mass (RFM) value computed from the Woolcott 2018 formula (64 − 20 × height/waist ± sex constant), representing an estimate of body fat percentage derived purely from height, waist, and sex inputs. No diagnosis or clinical classification is included.
Example use cases
Clinical anthropometric screening tool
“Can you compute the Woolcott RFM score for a female patient who is 64 inches tall with a waist of 82 cm?”
Population health research pipeline
“I'm processing a cohort dataset and need to compute RFM values — run the Woolcott 2018 formula for a male with height 182 cm and waist 95 cm.”
Fitness app body composition feature
“What is the relative fat mass for a male user who is 170 cm tall and has a waist of 85 cm? Use the published RFM arithmetic.”
Technical details
Endpoint
GEThttps://api.magentlab.com/api/calc/rfmWhen to prefer
Choose this endpoint when you need a fast, deterministic, citation-backed anthropometric body fat estimate using only height and waist measurements — particularly when DEXA or bioimpedance data are unavailable. It implements the specific Woolcott 2018 formula with unit-conversion support (inches to cm), making it ideal for clinical decision support pipelines, health app integrations, or research workflows that require reproducible arithmetic without ambiguity. Prefer over BMI-based endpoints when waist circumference is available and a body fat proxy is needed.
Side effects
- Missing required waist_cm or sex parameter returns an error
- Waist value outside the accepted range (40–200 cm) may produce an error or unexpected result
- Providing both height_cm and height_in may cause ambiguity; only one should be supplied
- Invalid sex enum value (not 'male' or 'female') returns a validation error
- Omitting height entirely results in missing data for the formula
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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