Association of body mass index and sarcopenia with osteoporosis: a predictive nomogram model for risk assessment.

OBJECTIVE

Body mass index (BMI) and sarcopenia are linked to osteoporosis, but the extent to which BMI influences osteoporosis through sarcopenia remains unclear. This study aims to assess the associations between BMI, sarcopenia, and osteoporosis, and to explore the predictive value of their combined biochemical markers for osteoporosis.

METHODS

We retrospectively collected clinical data from 813 inpatients in the endocrinology department to explore the relationships between serum markers and skeletal muscle mass or BMI, and to evaluate the predictive value of BMI and sarcopenia for osteoporosis. Mediation analysis was employed to examine the associations among BMI, sarcopenia, and osteoporosis. Participants were randomly divided into training (n = 407) and testing (n = 406) sets (5:5). Independent risk factors were identified using least absolute shrinkage and selection operator and logistic regression, leading to the development of a nomogram model. Model evaluation was conducted through receiver operating characteristic curves, confusion matrices, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).

RESULTS

BMI and skeletal muscle mass were negatively correlated with serum 25-hydroxyvitamin D and calcium levels. The "BMI < 28 and Non-Sarcopenia" emerged as a protective factor against osteoporosis. Sarcopenia significantly mediated the association between BMI and osteoporosis (46.88%). Gender, age, high-density lipoprotein, alkaline phosphatase, BMI, and sarcopenia emerged as independent predictors of osteoporosis. The area under the curve (AUC) for the training and testing sets was 0.859 and 0.866, respectively, with calibration curves indicating good consistency. DCA and CIC demonstrated clinical net benefits at risk thresholds of 0.02-0.82 and 0.02-0.67. Sankey diagrams and partial AUCs (1.00-0.75 sensitivity and specificity) illustrate the significant negative predictive value of BMI and sarcopenia.

CONCLUSION

Lower BMI and non-sarcopenia are negatively associated with the risk of osteoporosis. In addition, the nomogram demonstrates good predictive value, with a greater negative predictive value of the BMI and sarcopenia.