Hongshun Liu from the Department of Orthopedics, Zhengzhou Orthopedic Hospital, Henan, China, and colleagues conducted the investigation, analyzing a large cohort of Chinese adults to evaluate the association between TyG-BMI—a surrogate marker reflecting both insulin resistance and adiposity—and incident osteoporosis. The research aimed to clarify whether this easily accessible index could help identify individuals at high risk for the disease.
The study included 23,930 participants, categorized into four TyG-BMI quartiles (Q1–Q4). Researchers tracked osteoporosis incidence over a median follow-up of four years, comparing baseline characteristics, biochemical profiles, and medication use across groups. Cox proportional hazards models were used to estimate hazard ratios (HRs) for osteoporosis, adjusting for potential confounders. Additional stratified analyses examined how age, sex, smoking status, renal function, and medication use influenced the associations.
The study revealed the following notable findings:
- Osteoporosis cases increased sharply from the lowest to the highest TyG-BMI quartile, with 71 cases in Q1 and 855 cases in Q4.
- Participants in Q4 were younger, with a mean age of 56.2 years compared to 63.0 years in Q1.
- Those in Q4 had higher BMI (29.7 vs. 20.8 kg/m²), elevated fasting glucose (9.15 vs. 7.02 mmol/L), and higher triglyceride levels (2.95 vs. 1.06 mmol/L).
- Individuals in the highest TyG-BMI quartile had a 3.67-fold increased risk of developing osteoporosis compared to the lowest quartile.
- Stratified analyses showed particularly high risk among participants under 65 years (HR: 14.6).
- Males had an elevated osteoporosis risk (HR: 12.4).
- Smokers exhibited a higher risk (HR: 15.2).
- Participants with preserved renal function also showed increased risk (HR: 12.2).
The researchers acknowledged several limitations, including potential misclassification of osteoporosis based on DXA T-scores and ICD-10 coding, residual confounding from unmeasured lifestyle factors, and variations in testing practices across health systems. Sensitivity analyses, including restriction to DXA-confirmed events and adjustment for additional variables such as HDL-C and eGFR, confirmed the robustness of the observed associations.
The study concludes that TyG-BMI is a robust and accessible marker for identifying individuals at heightened risk of osteoporosis. Its integration into clinical practice could enable early intervention strategies, particularly for younger men, smokers, and those with preserved kidney function. The authors advocate for future research to validate TyG-BMI thresholds in diverse populations and explore targeted interventions for those with insulin resistance, aiming to reduce osteoporosis incidence and its associated complications.
Reference:
Liu, H., Tan, H., & Pan, Y. (2025). Association of triglyceride glucose body mass index with osteoporosis risks in a large Chinese adult cohort. Frontiers in Endocrinology, 16, 1680775. https://doi.org/10.3389/fendo.2025.1680775
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