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Updated: Jun 20, 2026
Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
Published on: January 29, 2018
Body composition-derived principal components partially explain sex and age effects on bone mineral density in type 2
Dihe Cheng1, Yan Chen1, Yan Cai1
1Department of Endocrinology, The Second Hospital of Jilin University, Changchun, Jilin, China.
Objective:
Patients with type 2 diabetes (T2DM) often exhibit high fracture risk. While body composition critically influences bone mineral density (BMD), the specific independent roles of its interrelated components (muscle vs. fat) remain poorly characterized in T2DM. This study aimed to disentangle these correlated phenotypes and quantify their distinct associations with BMD.
Methods:
In this cross-sectional study at the Second Hospital of Jilin University, 424 adults with T2DM were assessed. BMD was measured by dual-energy X-ray absorptiometry (DXA), and body composition by bioelectrical impedance analysis (BIA). PCA was applied to derive integrated phenotypes. Multivariable linear regression and mediation analysis assessed their associations with site-specific BMD and quantified the extent to which they statistically account for age/sex effects. A nomogram was developed and internally validated.
Results:
The cohort (mean age 58.09 years, 51.4% male, 16.0% osteoporosis prevalence) exhibited significant sex-related differences. PCA mainly identified a "muscle-metabolic" component (PC1) and a "fat-obesity" component (PC2). PC1 was consistently associated with higher BMD at all sites, while PC2 showed a positive association only with total hip BMD, and this association was observed specifically in middle-aged women. PC1 statistically accounted for 30.2-54.5% of the sex effect and 16.7-22.4% of the age effect on BMD. The nomogram (incorporating PC1, PC2, age, sex, and smoking status) demonstrated excellent discrimination (bootstrap-corrected C-index=0.854).
Conclusions:
Integrated body composition phenotypes are strongly associated with BMD and statistically explain key demographic effects in T2DM. The developed model provides a cross-sectional tool for identifying current osteoporosis status.
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