Work

Role of Body Fat and Metabolic Rate in Site-Specific Fracture Risk: A 20-Year Taiwanese Cohort Study

Year: 2025

Type: article

Abstract: BACKGROUND Osteoporotic fractures are a significant public health problem, yet traditional risk assessment methods have limitations. This retrospective study used the integrated Healthcare information (iHi) Data Platform of China Medical University Hospital (CMUH) (2000-2020) to evaluate associations between body mass index (BMI), bone mineral density (BMD), body fat percentage (BFP), basal metabolic rate (BMR), and site-specific fracture risk in 9583 Taiwanese individuals. MATERIAL AND METHODS We extracted DXA-measured BMD, BMI, BFP, and BMR data from CMUH's iHi Platform. Fracture events were identified using ICD-9/10 codes and verified through radiology reports. Cox proportional hazards regression models estimated fracture risk, adjusting for demographic and clinical factors. Mediation analysis quantified the contributions of BFP and BMR to the BMI-fracture relationship. RESULTS During median follow-up of 8.7 years, 1672 fractures (17.4%) occurred. Individuals with normal BMD showed an 82% lower fracture risk compared to those with osteoporosis (adjusted hazard ratio [aHR]=0.18, 95% CI: 0.15-0.22, p<0.001). Normal BFP significantly reduced fracture risk by 77% versus low BFP (aHR=0.23, 95% CI: 0.07-0.72, p=0.012). Higher BMR was consistently protective, with aHR=0.54 (95% CI: 0.36-0.82, p=0.004) for BMR ≥1500 versus BMR<1000. While underweight increased fracture risk (aHR=1.75, 95% CI: 1.29-2.36, p<0.001), obesity conferred no significant protection (aHR=1.04, 95% CI: 0.89-1.21, p=0.58). CONCLUSIONS This study demonstrates that fracture risk assessment should incorporate BFP and BMR alongside BMD and BMI. The "BMI paradox" was explained through mediation analysis, revealing BFP and BMR as critical intermediaries accounting for 50% and 32% of the BMI-fracture relationship, respectively. These findings support developing ethnicity-specific fracture risk models integrating body composition metrics for more precise risk stratification.

Source: Medical Science Monitor

DOI: 10.12659/msm.947660