The interindividual variation in femoral neck width is associated with the acquisition of predictable sets of morphological and tissue-quality traits and differential bone loss patterns.

A better understanding of femoral neck structure and age-related bone loss will benefit research aimed at reducing fracture risk. We used the natural variation in robustness (bone width relative to length) to analyze how adaptive processes covary traits in association with robustness, and whether the variation in robustness affects age-related bone loss patterns. Femoral necks from 49 female cadavers (29-93 years of age) were evaluated for morphological and tissue-level traits using radiography, peripheral quantitative computed tomography, micro-computed tomography, and ash-content analysis. Femoral neck robustness was normally distributed and varied widely with a coefficient of variation of 14.9%. Age-adjusted partial regression analysis revealed significant negative correlations (p < 0.05) between robustness and relative cortical area, cortical tissue-mineral density (Ct.TMD), and trabecular bone mineral density (Ma.BMD). Path analysis confirmed these results showing that a one standard deviation (SD) increase in robustness was associated with a 0.70 SD decrease in RCA, 0.47 SD decrease in Ct.TMD, and 0.43 SD decrease in Ma.BMD. Significantly different bone loss patterns were observed when comparing the most slender and most robust tertiles. Robust femora showed significant negative correlations with age for cortical area (R(2) = 0.29, p < 0.03), Ma.BMD (R(2) = 0.34, p < 0.01), and Ct.TMD (R(2) = 0.4, p < 0.003). However, slender femora did not show these age-related changes (R(2) < 0.09, p > 0.2). The results indicated that slender femora were constructed with a different set of traits compared to robust femora, and that the natural variation in robustness was a determinant of age-related bone loss patterns. Clinical diagnoses and treatments may benefit from a better understanding of these robustness-specific structural and aging patterns.