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.