To assess the relationship of total fat mass (TFM) and total lean mass (TLM) with bone mineral density (BMD) and bone mineral content (BMC), we studied 770 postmenopausal white women after total body measurements by dual-energy X-ray absorptiometry. Height-independent bone mineral density (HIBMD) was also tested. The effects of TFM and TLM on the dependent variables HIBMD, BMD, and BMC were assessed by the univariate general linear model (UGLM). Age, age at menopause, height, and bone area were entered in the models as controlling variables when appropriate. In the total population, TLM and TFM were associated with BMD, BMC, and HIBMD (P < 0.001). Taking the T-score cut-off as -2.5, women without (463) and with (307) osteoporosis were then tested separately. In nonosteoporotic women, TLM was significantly associated with BMD, BMC, and HIBMD (P < 0.001), while TFM was not. In osteoporotic women, both TLM and TFM were associated with BMD to the same extent (P < 0.05), but not with HIBMD. Women without osteoporosis were then tested according to whether their TFM/TLM fraction was less than or greater than 1. In those with TFM/TLM less than 1, both TLM (P < 0.001) and TFM (P < 0.01), tested separately, were associated with BMD and BMC, but not with HIBMD. When TLM and TFM were tested at the same time and assessed by the same UGLM, only TLM (P < 0.001) still affected these three bone parameters. In women with TFM/TLM greater than 1, testing the body components both separately and at the same time and using the UGLM showed that TFM affected both BMC and BMD (P < 0.05), while TLM did not. In conclusion, our data indicate that both TFM and TLM affect bone density, with different physiological/pathological conditions modulating this relationship.

We used femoral neck structural parameters (FNSPs), calculated from bone mineral density (BMD) measurements of the femoral neck by dual X-ray absorptiometry, to discriminate osteoporotic fractures of the proximal femur in post-menopausal women. We compared 1646 women without fracture and 429 women with hip fractures, including 273 with femoral neck (FN) and 156 with trochanter (TR) fractures. The association between the studied parameters and the fractures was modelled using multiple logistic regression, and included age, height and weight. Fracture-predicted probability (FPP) was also calculated for each predictor tested. Receiver operating characteristic (ROC) curve areas with their standard errors (SEs) were calculated for the fracture status, having the calculated FPP as a test variable. The areas were compared by the Hanley-McNeil test. Hip fracture had lower BMD, cross-sectional area (CSA), section modulus (SM) and cortical thickness (CT), and higher buckling ratio (BR), than controls. To the same extent as FN BMD, BR best predicted the risk for each fracture, showing ROC curve areas of 0.809 (SE 0.011) for hip fracture, 0.789 (SE 0.014) for FN fracture, and 0.848 (SE 0.016) for TR fracture. The association of BR with fracture risk did not differ from that of FN BMD, which has a ROC curve area of 0.801 (SE 0.011) for hip fracture, 0.778 (SE 0.014) for FN fracture, and 0.852 (SE 0.016) for TR fracture. Both FN BMD and BR predicted TR fracture significantly better than they did FN fracture. FNSPs, although interesting in understanding the biomechanics of bone fragility, do not appear to add diagnostic value to the simple measurement of BMD.

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