Adjusting for Weight

Because anthropometry data are so expensive to collect, surveys are conducted only rarely among civilian populations, and are restricted in the number of different dimensions that are measured. It is also difficult to include a representative number of extreme sizes in anthropometry measurement surveys, because these individuals are less likely to volunteer.

The data in PeopleSize are scaled by both stature and weight, to create a single large dataset covering the main consumer populations, brought up to date as necessary from the time of the original surveys.

To cater for the steady increase in body weight in Western populations since the 70's, an adjustment factor has been calculated thus:

For each dimension, the correlation with stature and with weight was calculated, then squared to express the amount of variability associated with them. The squared correlations were then converted to decimal fractions of 1, in their respective proportions. Weight is more variable than any of the body dimensions, so a further factor was applied to improve the accuracy of the estimate - the ratio of the Coefficient of Variation of the dimension with that of weight in the original survey. The two factors were multiplied, so that if the CV of the dimension is half that of weight, the correlation-based factor was halved.

Some dimensions did not have known correlations, and occasional anomalies were seen where dimensions have low correlations with both stature and weight. In this situation the ratio between two low correlations may not be meaningful. Accordingly, the coefficients were inspected by a human biologist, to fill in missing coefficients and to adjust spuriously high coefficients.

see also:

The distribution of fatty dimensions

Principles of estimation

Estimation methods