OBJECTIVE: To investigate the influence of height on the relationships between the intra-abdominal fat and anthropometric measures. SUBJECTS: Twenty healthy female volunteers aged 20–51 y from Aberdeen, and 71 men and 34 women aged 19–85 y from Nijmegen, The Netherlands. OUTCOME MEASURES: Intra-abdominal fat volumes by magnetic resonance imaging (MRI) in Aberdeen and cross-sectional areas at L4-L5 level by computerised tomography (CT) in Nijmegen, height, body mass index (BMI), waist circumference, waist sagittal and transverse diameters, waist to hip ratio, and skinfolds. RESULTS: In the MRI study the women with BMI 20–33 kg/m2, waist circumference 62–97 cm, height 148–172 cm, and intra-abdominal fat volume 0.07–2.66 kg, waist circumference gave the highest correlation of simple indices with intra-abdominal fat volume, explaining 77.8% of variance. Single cross-sectional MRI cuts predicted volume with r=0.94–0.99. Height in various levels of index power was not related to waist circumference, waist diameters, BMI, or skinfolds and did not improve prediction of intra-abdominal fat volume or of cross-sectional intra-abdominal fat area at any level. The CT study of men and women with BMI 18–32 kg/m2 and 19–38 kg/m2, waist circumference 71–112 cm and 74–125 cm, height 158–197 cm and 151–182 cm, and intra-abdominal fat area 13–274 cm2 and 19–221 cm2 respectively, height also had little influence on the relationships of intra-abdominal fat area with waist circumference or with any other indices of adiposity in linear or quadratic models. Compared to younger subjects, intra-abdominal fat area was higher in older subjects for a given waist circumference. CONCLUSIONS: Height does not importantly influence the differences in measures of adiposity or intra-abdominal fat volume in women, or intra-abdominal fat area in both sexes. Age does influence the prediction of intra-abdominal fat from waist circumference, but waist circumference alone has a predictable simple relationship with intra-abdominal fat volume or area, which is likely to relate to the prediction of health risk for health promotion.