Age, gender, ethnicity, and disability change the distribution of body measurements within a population. Designers must therefore use anthropometric data that represent the intended target population, not one supposedly universal dataset.
Anthropometric data include stature, seated height, shoulder breadth, reach, and hand dimensions. Measurements vary both between demographic groups and between individuals within each group.
| Factor | Effect on anthropometric data | Design implication |
|---|---|---|
| Age | Children’s dimensions increase during growth, while older adults may experience reduced stature, reach, mobility, or changes in posture. | Select data for the relevant age range rather than using measurements from working-age adults. |
| Gender | Population datasets may show differences in average stature, shoulder breadth, and hand size, although distributions overlap considerably. | Use a range of measurements; do not assume every person of one gender has similar dimensions. |
| Ethnicity | Average proportions may vary among populations because of genetic, environmental, nutritional, and socioeconomic influences. | Data from one geographical or ethnic population may not represent another target market accurately. |
| Disability | Disability may affect posture, reach, movement, limb dimensions, or space required for mobility aids. | Use accessibility data and direct user research because standard population tables may be insufficient. |
Designers apply percentiles to accommodate a chosen proportion of users. A low percentile is suitable for reachable controls because smaller users must reach them; a high percentile is suitable for clearances such as doorway height or legroom because larger users must fit. Adjustability can accommodate a wider range.
A common misconception is that designing for the “average person” serves most users. An average is a statistical value, but an individual who is average in every body dimension is unlikely to exist.
For an IB Design Technology A1.1 Ergonomics response, identify the factor, explain its effect on variation, and justify a design decision. Examiners expect application to the target user, appropriate percentile selection, and consideration of inclusive design.
