Due to the gradual improvement in living standards, the latest statistics from the World Health Organization (WHO) indicate that more than 650 million people are obese1, Clearly, obesity has become a significant global health crisis and is a major determinant among numerous risk factors for chronic non-communicable diseases. It can significantly increase the relative risk of developing diabetes, metabolic syndrome, and cardiovascular diseases2.

Osteoporosis is a metabolic bone disease affecting the entire body that leads to a decrease in bone density and mass due to various causes, along with damage to the bone microstructure, thereby increasing the risk of fractures3. Osteopenia and osteoporosis impact over 44 million persons in the United States who are 50 years of age or older. The main risk factors for osteopenia or osteoporosis include genetics, smoking, alcohol consumption, and rheumatoid arthritis4. A study by Shilpa N. Bhupathiraju et al. revealed that an increase in abdominal fat is associated with a higher likelihood of decreased bone mass or osteoporosis5. Yao-Hsien Tseng et al. found a positive correlation between waist circumference in males and decreased bone mineral density (BMD)6. Moreover, a cross-sectional study suggested that when waist circumference exceeds 95cm, there is a decrease in BMD levels, indicating that abdominal obesity can serve as a risk predictor for bone health7. These studies collectively demonstrate a strong association between abdominal obesity and the development of osteopenia, thus highlighting it as another risk factor for the disease. However, there is currently a lack of risk assessment methods for osteopenia in the abdominal obesity population. Therefore, it is crucial to develop relevant osteopenia prediction tools for individuals with abdominal obesity. Such tools can identify high-risk individuals for osteopenia at an early stage and implement targeted preventive measures to ultimately prevent fragility fractures.

Clinical prediction models play a vital role in estimating the risk of existing diseases or predicting future outcomes for individuals. Nomograms, which visually represent these models, are highly practical tools8. This study utilized the National Health and Nutrition Examination Survey (NHANES) database to select clinical data and investigate the risk factors associated with decreased osteopenia in individuals with abdominal obesity. The primary objective of this study was to construct and validate a nomogram that can evaluate the risk of developing osteopenia, thereby providing timely clinical decision-making support for healthcare professionals.