Homeโ€บCalculatorsโ€บHealthโ€บHeight Percentile Calculator

Height Percentile Calculator

Health

See how your height compares to the general adult population by sex. Get an instant height percentile rank using global adult height reference averages.

130220

Height Percentile

70.3
z-score
0.53
Reference Average Height
171

This calculator computes your Height Percentile, z-score, Reference Average Height from the values you enter.

Inputs
SexHeight
Outputs
Height Percentilez-scoreReference Average Height

What is a Height Percentile?

The Height Percentile Calculator shows how a given height compares to the general adult population by sex, using global average height reference data. Enter your height and sex, and the calculator returns a percentile rank showing what portion of the reference population you're taller than.

This pairs with the Weight Percentile Calculator for a fuller picture of how body measurements compare to population averages, and with the BMI Calculator for a combined height-and-weight health metric.


How to use this Height Percentile calculator

  1. Select your sex โ€” Male or Female.
  2. Enter your height in centimetres.
  3. Read the Height Percentile result instantly.
  4. Check the Reference Average Height shown to see the baseline used for comparison.
  5. Try different height values to see how the percentile shifts across the range.

Formula & Methodology

The calculator uses a global adult average height reference by sex:

z-score = (Height โˆ’ Reference average) รท Reference standard deviation

Percentile = ฮฆ(z-score) ร— 100, where ฮฆ is the cumulative standard normal distribution.

Worked example โ€” a woman who is 168 cm tall:

Reference average (women) = 159 cm, SD = 7.0 cm

z-score = (168 โˆ’ 159) รท 7.0 = 1.29

Percentile โ‰ˆ ฮฆ(1.29) ร— 100 = 90th percentile

This means a height of 168 cm is taller than approximately 90% of the reference adult female population.

Frequently Asked Questions

Height percentile shows what percentage of the population of the same sex is shorter than a given height. A percentile of 70 means the height is taller than roughly 70% of that reference population.
The calculator compares the entered height to a global adult average height reference for the selected sex, computes a z-score based on the reference standard deviation, and converts that z-score into a percentile using the normal distribution.
This calculator uses approximate global adult averages of 171 cm for men and 159 cm for women; actual national averages vary meaningfully by country, so results here are a general global reference rather than a country-specific comparison.
Average height differs across populations due to a combination of genetics, nutrition, healthcare access, and other socioeconomic factors that vary by region and have shifted over generations.
No โ€” a height that ranks in the 80th percentile against a global reference might rank quite differently against a specific national population, since some countries have taller or shorter average heights than the global figure used here.
A z-score shows how many standard deviations a height is from the reference average; a z-score of 0 means exactly average, while +1 or -1 means one standard deviation above or below average respectively.
Height is strongly influenced by genetics โ€” often estimated to account for the majority of height variation between individuals โ€” though nutrition and overall health during childhood growth years also play a meaningful role.
No โ€” this calculator uses adult population reference data; for children and teens, height should be compared against age- and sex-specific pediatric growth charts instead, since a child's expected height changes constantly with age.
This calculator ranks height against the adult population, while the [Weight Percentile Calculator](/weight-percentile-calculator/) does the same comparison for body weight โ€” both use the same normal distribution approach with different reference data.
This calculator currently uses a single global reference average by sex rather than country-specific data, so results should be treated as a general worldwide comparison rather than a precise national ranking.
Also known as
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