Elsevier

Bone

Volume 42, Issue 4, April 2008, Pages 798-805
Bone

Pelvic body composition measurements by quantitative computed tomography: Association with recent hip fracture

https://doi.org/10.1016/j.bone.2007.12.002Get rights and content

Abstract

Introduction

Loss of subcutaneous fat, decreased muscle cross-sectional area (CSA) and increased muscle adiposity are related to declining physical function and disability in the elderly, but there is little information about the relationship of these tissue changes to hip fracture. Thus we have compared body composition measures in women with hip fractures to age-matched controls, using quantitative computed tomography (QCT) imaging of the hip to characterize total adiposity, muscle CSA and muscle attenuation coefficient, a measure of adiposity.

Materials and methods

45 Chinese women (mean age 74.71 ± 5.94) with hip fractures were compared to 66 healthy control subjects (mean age 70.70 ± 4.66). Hip QCT scans were analyzed to compute total adipose CSA as well as CSA and attenuation values of muscle groups in the CT scan field of view, including hip extensors, abductors, adductors and flexors. The total femur areal BMD (aBMD) was estimated from the QCT images. Logistic regression was employed to compare body composition measures between fracture subjects and controls after adjustment for age, height, BMI and aBMD. Receiver–operator curve (ROC) analyses determined whether combinations of aBMD and body composition had higher area under curve (AUC) than aBMD alone.

Results and conclusions

Fracture subjects had lower fat CSA (p < 0.0001) than controls but had higher muscle adiposity as indicated by lower attenuation in the adductor, abductor and flexor groups (0.00001 < p < 0.02). Fracture subjects also had lower extensor and adductor CSA values (p < 0.0001). After age and BMI adjustment, the total fat CSA, the extensor and adductor CSA values, and the adductor attenuation values remained significantly lower in the fracture subjects (0.001 < p < 0.05). In ROC analyses, models combining aBMD with soft tissue measures had higher AUC than models containing only BMD (0.001 < p < 0.05). Combining body composition with skeletal measures may improve fracture prediction compared to bone measures alone.

Introduction

Measures of proximal femoral bone mineral density (BMD) and structure from quantitative computed tomography (QCT) images are correlated in vitro to hip strength [4], [5], [6], [25] and are associated in cross-sectional studies with hip fracture [3]. In addition to the skeletal anatomy, the images also depict the muscle and adipose tissue surrounding the proximal femur. These images provide information about the total pelvic adipose and lean content as well information on the cross-sectional areas and Hounsfield Unit (HU) values (a measure of tissue X-ray attenuation) of the functional muscle groups in the field of view. CT measurements of the cross-sectional area (CSA) and mean Hounsfield Unit (HU) of the abdomen and mid thigh muscle bundle are well established measurements in epidemiologic studies of physical function in the elderly [13], [35], [36]. The CSA is a measure of overall muscle size and is strongly correlated to muscle strength and fall-related measures of physical function [14]. The HU value is a measure of the inter- and intra-cellular adipose content of the muscles [14], [27], with decreasing HU proportional to increasing fattiness [13]. In the thigh, the CSA and HU are independently correlated to knee extensor strength, and low mean HU is associated with reduced current physical function, lower strength, and with onset of disability [35], [36], [37].

We recently reported a cross-sectional analysis of the associations of QCT-derived measures of proximal femoral skeletal structure measures with hip fracture [3]. In this cohort, Cheng et al.showed that elderly Chinese women with hip fractures, imaged within 48 h of their fracture, differed from age-matched controls in multiple indices of proximal femoral bone density and geometry, even after adjustment for age and body size. In this study, we hypothesized that performance-related elements of body composition obtained from QCT scans of the hip, in particular the HU and CSA of the muscles surrounding the proximal femur, would be associated with hip fracture. We also hypothesized that combining these soft tissue indices with BMD would result in better discrimination between fractured subjects and controls than BMD measurements alone.

Section snippets

Study subjects

Forty-five women with fractures of the hip (34 cervical, 11 trochanteric), aged 65 or older were recruited from the emergency room, Department of Traumatology and Orthopedic Surgery, Beijing Ji Shui Tan hospital. In order to minimize changes in BMD and body composition factors due to the fracture, only those subjects whose fractures had occurred within the last 48 h were accepted into the study. Potential hip fracture subjects were referred to the ER CT scanning service and to the study by

Descriptive statistics

Controls were not significantly different from fracture subjects in height but on average were 4 year s younger than subjects (p < 0.001) and 5% higher in BMI (p < 0.05). Descriptive statistics for each group are summarized in Table 2. BMD differed strongly between subjects with hip fractures and controls. Even after adjustment for age, height and BMI, subjects with fractures had 24% lower aBMD than controls in the total femur region (p < 0.0001,see Table 3).

Contribution of body fat measures

As shown in Table 3, subjects with hip

Discussion

Areal bone mineral density (aBMD) measured by DXA operates clinically as a surrogate measure for bone strength and is operatescommonly employed to select patients for preventive drug therapies [7], [34]. However, a growing number of studies have pointed out the limitations associated with using aBMD in isolation as an estimator of hip fracture risk, showing that considerable numbers of fractures occur in subjects who have higher aBMD than would normally be associated with osteoporosis [32], [38]

Acknowledgments

This patient study was funded by a grant from Eli Lilly. Development of the analytic technique was funded by NASA grant NNJ04HF78G.

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