The relationship of anthropometric measures to radiological features of the breast in premenopausal women

• Published in: British journal of cancer Vol. 78; no. 9; pp. 1233 - 1238
• Main Authors: BOYD, N. F, LOCKWOOD, G. A, BYNG, J. W, LITTLE, L. E, YAFFE, M. J, TRITCHLER, D. L
• Format: Journal Article
• Language: English
• Published: Basingstoke Nature Publishing Group 01-11-1998; Nature Publishing Group|1
• Subjects: Adult; Anthropometry; Biological and medical sciences; Body Constitution - physiology; Breast - anatomy & histology; Breast Neoplasms - etiology; Female; Genital system. Mammary gland; Humans; Investigative techniques, diagnostic techniques (general aspects); Mammography; Medical sciences; Middle Aged; Premenopause - physiology; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Regression Analysis; Risk Factors; Human; Carcinoma; Adipose tissue; Radiodiagnosis; Premenopause; Anthropometry; Body weight; Mammography; Malignant tumor; Density; Mammary gland diseases; Connective tissue; Risk factor; Adult; Female; Mammary gland
• ISSN: 0007-0920; 1532-1827
• DOI: 10.1038/bjc.1998.660

We studied 273 premenopausal women recruited from mammography units who had different degrees of density of the breast parenchyma on mammography, in whom we measured height, weight and skinfold thicknesses. Mammograms were digitized to high spatial resolution by a scanning densitometer and images analysed to measure the area of dense tissue and the total area of the breast. Per cent density and the area of non-dense tissue were calculated from these measurements. We found that the mammographic measures had different associations with body size. Weight and the Quetelet index of obesity were strongly and positively associated with the area of non-dense tissue and with the total area of the breast, but less strongly and negatively correlated with the area of dense tissue. We also found a strong inverse relationship between the areas of radiologically dense and non-dense breast tissue. Statistical models containing anthropometric variables explained up to 8% of the variance in dense area, but explained up to 49% of the variance in non-dense area and 43% of variance in total area. These results suggest that aetiological studies in breast cancer that use mammographic density should consider dense and non-dense tissues separately. In addition to per cent density, methods should be examined that combine information from these two tissues.