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Adult BMI screening — sensitivity table

Estimate adult body mass index from entered height and weight; screening only. Build a multi-point table showing how weight changes the main result.

Five planning modes, one calculator topic

These modes share an underlying model, not five unrelated formulas. This advanced mode is excluded from search indexing. Visit the main adult bmi calculator for the topic overview.

Planning mode: Build a multi-point table showing how weight changes the main result. Adjust the inputs to fit your situation. Related tools share an underlying model, with distinct calculation, reverse-solve, comparison and sensitivity functions.

Your numbers

lb
lb
points
ft
in
lb

Sensitivity analysis

5 comparison points

Weight ranges from 90 lb to 270 lb.

Weight: 90 lb
13.3
Weight: 135 lb
19.9
Weight: 180 lb
26.6
Weight: 225 lb
33.2
Weight: 270 lb
39.9
Baseline — Entered weight
180 lb
Baseline — Entered height
69 in
Baseline — BMI
26.6
Baseline — CDC adult screening range
18.5 to 24.9 is the usual reference range

Assumptions to check

  • BMI is a screening measure, not a diagnosis or individualized health assessment.

How this is calculated

Evaluate the model at evenly spaced input values, rounded to the allowed input step. BMI = pounds × 703 ÷ inches².
  1. 1Keep all other model inputs constant.
  2. 2Each row reports the same headline measure, not a separate forecast.

Assumptions and limits

  • CDC adult BMI screening categories do not diagnose health; BMI is not a measure of individual body composition.
  • BMI is a screening measure, not a diagnosis or individualized health assessment.

Practical guide

Understanding adult bmi screening — sensitivity table

Everyday editorial team · GEOINNOVATION CO., LTD · Published · Updated

What this calculation is for

Adult body mass index is a screening measure relating weight to height. It can provide a consistent way to discuss population-level weight categories, but it does not measure body fat directly or diagnose an individual’s health.

How the method works

BMI equals weight in kilograms divided by height in meters squared. The equivalent US customary formula uses pounds and inches with the standard conversion factor. Select matching units and enter the total height correctly rather than treating feet as decimal inches.

A worked example

A person who is 5 feet 10 inches tall is 70 inches tall, not 5.10 feet. A mistaken height has a large effect because height is squared in the denominator.

Assumptions and real-world differences

Adult categories are not the appropriate interpretation for children, adolescents or every pregnancy context. Muscle mass, age, body composition, disability and clinical history affect interpretation. Do not use the result to prescribe weight loss or disregard symptoms.

Reading the weight sensitivity table

The tool evaluates the same model across a range of weight values while holding other assumptions constant. Choose a realistic low value, high value and number of points. Each row reports the same headline measure; the table is a set of conditional calculations, not a probability distribution or a forecast. Input-step rounding can make nearby rows equal.

Reproduce this tool’s example

These fixed example inputs are independent of edits you make above. Enter them in this tool to reproduce the result, then replace them with your own assumptions.

Minimum weight
90 lb
Maximum weight
270 lb
Number of comparison points
5 points
Height — feet
5 ft
Height — additional inches
9 in
Comparison weight
170 lb

Sensitivity analysis: 5 comparison points

Weight ranges from 90 lb to 270 lb.

  • Weight: 90 lb: 13.3
  • Weight: 135 lb: 19.9
  • Weight: 180 lb: 26.6

Frequently asked questions

Does a BMI category prove that I am unhealthy?
No. It is one screening measure; a clinician can interpret it alongside other information.
Can children use the adult categories?
Children and teens need age- and sex-specific assessment rather than the adult thresholds.
Does the most favorable row show the most likely outcome?
No. The table assigns no likelihood to any row. It shows how the result responds to the chosen assumption, and you remain responsible for selecting a plausible range.

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