Predicting osteoporosis with body compositions in postmenopausal women: a non-invasive method

Abstract Background The prevalence of osteoporosis is rising steadily as the aging population increases. Bone mineral density (BMD) assessment a golden standard to establish diagnosis osteoporosis. However, accessibility and radiation exposure limited its role in community screening. A more convenient approach for screening suggested. Methods total 363 postmenopausal women over age 50 were included this study assessed with body composition [including fat-free mass (FFM), fat (FM), basal metabolic rate (BMR)] BMD. Normal distributions correlation coefficients among variables calculated using Shapiro-Wilk test Pearson’s analysis, respectively. receiver operating characteristic (ROC) curve was plotted, area under ROC curves (AUC) determined obtain optimal cutoff values prediction. Results coefficient FFM, FM, FM ratio, BMR femur neck T -score 0.373, 0.266, 0.165, 0.369, respectively, while spine 0.350, 0.251, 0.166, 0.352, respectively ( p < 0.01 all). showed an value 37.9 kg, 18.6 1187.5 kcal, detecting Conclusions present provided model predict women, could be Asian population. Among these factors, seemed better predictor than others. target exercise intervention maintaining or improving Trial registration ClinicalTrials.gov , NCT02936336 . Retrospectively registered on13 October 2016.