Liu Qingling, Pan Shengquan, Tang Ming, Yin Shiwu
Department of Gastroenterology and Endocrinology, Huining County People's Hospital, Huining County, Gansu Province, China.
Department of Interventional Vascular Medicine, Hefei Hospital Affiliated to Anhui Medical University, The Second People's Hospital of Hefei, Hefei City, Anhui Province, China.
Ther Adv Endocrinol Metab. 2025 Apr 28;16:20420188251332055. doi: 10.1177/20420188251332055. eCollection 2025.
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.
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 ( = 407) and testing ( = 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).
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.
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.
体重指数（BMI）和肌肉减少症与骨质疏松症相关，但BMI通过肌肉减少症影响骨质疏松症的程度尚不清楚。本研究旨在评估BMI、肌肉减少症和骨质疏松症之间的关联，并探讨其联合生化标志物对骨质疏松症的预测价值。
我们回顾性收集了内分泌科813例住院患者的临床资料，以探讨血清标志物与骨骼肌质量或BMI之间的关系，并评估BMI和肌肉减少症对骨质疏松症的预测价值。采用中介分析来检验BMI、肌肉减少症和骨质疏松症之间的关联。参与者被随机分为训练集（n = 407）和测试集（n = 406）（5:5）。使用最小绝对收缩和选择算子及逻辑回归确定独立危险因素，从而建立列线图模型。通过受试者工作特征曲线、混淆矩阵、校准曲线、决策曲线分析（DCA）和临床影响曲线（CIC）进行模型评估。
BMI和骨骼肌质量与血清25-羟维生素D和钙水平呈负相关。“BMI < 28且无肌肉减少症”是预防骨质疏松症的保护因素。肌肉减少症显著介导了BMI与骨质疏松症之间的关联（46.88%）。性别、年龄、高密度脂蛋白、碱性磷酸酶、BMI和肌肉减少症是骨质疏松症的独立预测因素。训练集和测试集的曲线下面积（AUC）分别为0.859和0.866，校准曲线显示一致性良好。DCA和CIC表明在风险阈值为0.02 - 0.82和0.02 - 0.67时具有临床净效益。桑基图和部分AUC（灵敏度和特异度为1.00 - 0.75）说明了BMI和肌肉减少症具有显著的阴性预测价值。
较低的BMI和无肌肉减少症与骨质疏松症风险呈负相关。此外，列线图显示出良好的预测价值，BMI和肌肉减少症具有更大的阴性预测价值。
