health.bmi Unreviewed

def bmi(weight_kg: float, height_cm: float) -> Bmi

BmiCategory = Literal["underweight", "healthy-weight", "overweight", "obesity-class-1", "obesity-class-2", "obesity-class-3"]

@dataclass(frozen=True)
class Bmi:
    """The index and the category read from it."""

    #: kg/m², rounded half away from zero to 1 decimal place
    value: float
    #: read from the rounded value, as the published bands are
    category: BmiCategory

from fune.health.bmi import bmi  # health.bmi@^1

import math

from .health_bmi_types import Bmi, BmiCategory
from .math_round_float import round_float  ← from math.round-float ^1.0.0 · built alongside by fune


def _check_range(name: str, value: float, low: float, high: float, unit: str) -> None:
    ok = not isinstance(value, bool) and isinstance(value, (int, float)) and math.isfinite(value)
    if not ok or value < low or value > high:
        raise ValueError("%s must be a number from %s to %s %s, received %r" % (name, low, high, unit, value))


def bmi(weight_kg: float, height_cm: float) -> Bmi:
    """Body mass index for an adult: weight over height squared, to one
    decimal place, and the band it falls in. The bands are published to one
    decimal place (18.5-24.9, 25-29.9, ...), so the category is read from the
    rounded index: 24.97 is reported as 25.0 and is overweight, not healthy."""
    _check_range("weightKg", weight_kg, 10, 650, "kg")
    # Height in metres (1.75) is the commonest unit slip; 50 cm is the floor.
    _check_range("heightCm", height_cm, 50, 272, "cm")
    metres = float(height_cm) / 100
    value = round_float(float(weight_kg) / (metres * metres), 1)
    category: BmiCategory
    if value < 18.5:
        category = "underweight"
    elif value <= 24.9:
        category = "healthy-weight"
    elif value <= 29.9:
        category = "overweight"
    elif value <= 34.9:
        category = "obesity-class-1"
    elif value <= 39.9:
        category = "obesity-class-2"
    else:
        category = "obesity-class-3"
    return Bmi(value=value, category=category)

Install

fune build

With that line in your source, in a Python project (language python in fune.project), fune build resolves it and its 1 dependency, pins them in fune.lock, downloads only the Python package of each, and builds the code above into your project’s .fune/build, one readable file per capability with a header linking back here. Or pin a range in fune.project and build in one step:

fune add health.bmi

The manifest, vectors and README with only the Python implementation. Install it without the registry with fune add ./health.bmi-1.0.1-python.fune, or fetch it from a terminal with fune pull health.bmi@1.0.1:python.

The whole function, every language, is one file too: health.bmi-1.0.1.fune, 14,901 bytes, sha256 2288b649366d888521b2232654f5e07174beeac4280a8d070cc3bdb001bcb593. It installs into a project of any language.

# fune: before health.bmi

# fune: after health.bmi

# fune: replace math.round-float in health.bmi

# fune: step health.bmi after <n|label>

More from the author

## Categories

| category | BMI (kg/m²) | |-------------------|--------------| | `underweight` | below 18.5 | | `healthy-weight` | 18.5 to 24.9 | | `overweight` | 25 to 29.9 | | `obesity-class-1` | 30 to 34.9 | | `obesity-class-2` | 35 to 39.9 | | `obesity-class-3` | 40 or more |

The bands are published to one decimal place, so the category is read from the rounded index. 99.9 kg at 200 cm is 24.975, reported as 25.0, and is overweight; a classifier that compares the raw 24.975 with `< 25` says healthy weight, which disagrees with the number it prints.

## What it deliberately does not do

- **Lower thresholds for some ethnic backgrounds.** NICE recommends lower thresholds (overweight 23 to 27.4, obesity 27.5 or more) for people with a South Asian, Chinese, other Asian, Middle Eastern, Black African or African-Caribbean family background. This function returns the general bands only; apply the lower thresholds to `value` where they are relevant. - **Interpretation.** BMI does not measure body fat or central adiposity; NICE asks for clinical judgement, particularly in the healthy-weight band, and a measure of central adiposity alongside it.

## Inputs

Weight is 10 to 650 kg and height 50 to 272 cm. Anything outside is refused, not clamped: in practice it is a unit slip, such as height in metres (1.75) or weight in pounds. The ranges are wide enough to include every recorded adult. The arithmetic is plain division and multiplication, which is correctly rounded in every language, and the rounding is `math.round-float`, so the three implementations return the same double (`floats exact`).

## Sources

- NICE guideline NG246, *Overweight and obesity management*, recommendations 1.9.10 (the bands above, adults) and 1.9.11 (lower thresholds for some ethnic backgrounds): https://www.nice.org.uk/guidance/ng246/chapter/Identifying-and-assessing-overweight-obesity-and-central-adiposity - The cut-offs are those of the World Health Organization's adult classification (WHO, *Obesity: preventing and managing the global epidemic*, Technical Report Series 894, 2000). `underweight` (below 18.5) is WHO's; NICE's list starts at healthy weight, 18.5. (The WHO report itself was not retrieved when this was written; every cut-off here was checked against NICE NG246.)

## Before you rely on this

**Not professional advice.** This capability calculates health figures from published rules. It is a software component for developers, not medical advice. Rules change and every rate here has an effective date. Check that the dates cover your case. Verify results against the official sources listed above, and have a clinician review how you use it, before anyone relies on the output. Provided "as is" under its licence, without warranty.

**Not a medical device.** It is not intended to diagnose, treat or support clinical decisions about any individual. Anyone building it into clinical software is responsible for that software's regulatory status, and must validate it under their own clinical governance.

**Unreviewed.** This capability's implementations agree in every language and pass its published test vectors, which were worked out from the official sources cited. But no qualified clinician has yet checked those vectors, or confirmed that the capability covers the cases it claims. Treat it as a draft. Do not use it for real people, money or decisions without your own expert review. Once a qualified reviewer signs off, this notice is replaced with their name, qualification and the date. Each new version needs fresh sign-off.

1.0.1 marks it unreviewed. The code and the tests are unchanged.

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