1. A novel non-invasive method for predicting bone mineral density and fracture risk using demographic and anthropometric measures
- Author
-
Justin Aflatooni, Steven Martin, Adib Edilbi, Pranav Gadangi, William Singer, Robert Loving, Shreya Domakonda, Nandini Solanki, Patrick C. McCulloch, and Bradley Lambert
- Subjects
Bone ,Bone density ,Fracture ,Fracture risk ,Assessment ,Osteoporosis ,Medicine (General) ,R5-920 - Abstract
Fractures are costly to treat and can significantly increase morbidity. Although dual-energy x-ray absorptiometry (DEXA) is used to screen at risk people with low bone mineral density (BMD), not all areas have access to one. We sought to create a readily accessible, inexpensive, high-throughput prediction tool for BMD that may identify people at risk of fracture for further evaluation. Anthropometric and demographic data were collected from 492 volunteers (♂275, ♀217; [44 ± 20] years; Body Mass Index (BMI) = [27.6 ± 6.0] kg/m2) in addition to total body bone mineral content (BMC, kg) and BMD measurements of the spine, pelvis, arms, legs and total body. Multiple-linear-regression with step-wise removal was used to develop a two-step prediction model for BMC followed by BMC. Model selection was determined by the highest adjusted R2, lowest error of estimate, and lowest level of variance inflation (α = 0.05). Height (HTcm), age (years), sexm=1, f=0, %body fat (%fat), fat free mass (FFMkg), fat mass (FMkg), leg length (LLcm), shoulder width (SHWDTHcm), trunk length (TRNKLcm), and pelvis width (PWDTHcm) were observed to be significant predictors in the following two-step model (p
- Published
- 2023
- Full Text
- View/download PDF