Determining the predictive equation for height from ulnar length in the Vietnamese population.

Background And Objectives: Height is an essential measurement in clinical medicine. It allows the calculation of body mass index, ideal body weight, basic energy requirements and tidal volumes. In many patient groups, such as the critically ill, height cannot be measured easily and surrogate anthropometric measures are used. Regression equations estimating height are specific to ethnicity. We aimed to develop the regression equation for Vietnamese men and women to predict height from ulna length and so improve prescription of life-saving treatment in the intensive care units.

Methods And Study Design: A cross-sectional survey of patients and relatives at the National Hospital for Tropical Diseases was undertaken. Ulna length, standing height and weight were measured. The first two thirds of participants' data, stratified by sex and age, were allocated to a model training group, the subsequent participants entered the validation group. Linear regression equations were calculated for the model group by sex, then applied to the validation group and assessed for precision. Other international equations were also compared.

Results: 498 males and 496 females were recruited. There was good correlation between ulna length and height in those aged 21-64, r=0.66, p<0.001 in males and females. The regression equations were: male: height = 85.61 + (3.16 x ulna length), female: height = 85.80 + (2.97 x ulna length). Equations from other populations were less accurate.

Conclusions: The regression equations calculated for men and women aged 21-64 showed good correlation and can be used to predict height in those where direct measurement is impossible.