Osteoporosis Prediction with body compositions in postmenopa
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The prevalence of osteoporosis is rising steadily as the aging population increases. Bone mineral density (BMD) assessment is a golden standard to establish the diagnosis of osteoporosis. A more convenient approach for screening is suggested.

The body composition [including fat-free mass (FFM), fat mass (FM), and basal metabolic rate (BMR)] and BMD of 363 postmenopausal women over the age of 50 were assessed in this research. The Shapiro-Wilk test and Pearson's correlation analysis were used to measure normal distributions and correlation coefficients among variables, respectively. To evaluate the optimal cutoff values for body composition variables for osteoporosis prediction, a receiver operating characteristic (ROC) curve was plotted and the area under the ROC curves (AUC) was calculated.

--The correlation coefficient of FFM, FM, FM ratio, and BMR with femur neck T-score was 0.373, 0.266, 0.165, and 0.369, respectively, while with spine T-score was 0.350, 0.251, 0.166, and 0.352, respectively.

--FFM, FM, and BMR showed an optimal cutoff value of 37.9kg, 18.6kg, and 1187.5kcal, respectively, for detecting osteoporosis.

The current study developed a model to predict osteoporosis in postmenopausal women, and the optimal FFM, FM, and BMR cutoff values in the Asian population were determined. BMR seemed to be a better indicator than the others. In postmenopausal women, the BMR may be a priority for exercise intervention in order to retain or improve BMD.

Source: https://josr-online.biomedcentral.com/articles/10.1186/s13018-021-02351-3