Assessment Of Hip Fracture Risk Research Articles

Adjusting Hip Fracture Probability in Men and Women Using Hip Axis Length: the Manitoba Bone Density Database

Most studies report that longer hip axis length (HAL) is associated with increased hip fracture risk in women, but comparable data in men are sparse. Using a registry of all dual-energy X-ray absorptiometry (DXA) results for Manitoba, Canada, we identified 4738 men and 50,420 women aged 40 yr and older with baseline hip DXA results, HAL measurements, and Fracture Risk Assessment Tool (FRAX) hip fracture probability computed with femoral neck bone mineral density (BMD). Population-based health service records were assessed for a subsequent hospitalization with a primary diagnosis of hip fracture. During mean 6.2 yr of follow-up, 70 men and 1020 women developed incident hip fractures. Mean HAL was significantly greater in those with vs without incident hip fractures (men 123.0 ± 7.6 vs 121.3 ± 7.4 mm, p = 0.050; women 106.9 ± 6.2 vs 104.6 ± 6.2 mm, p < 0.001). When adjusted for age and femoral neck BMD, each millimeter increase in HAL increased hip fracture risk by 3.6% in men (p = 0.022) and 4.6% in women (p < 0.001); this association was unaffected by sex (p value for interaction = 0.477). When adjusted for log-transformed FRAX hip fracture probability, each millimeter increase in HAL increased hip fracture risk by 3.4% in men (p = 0.031) and 4.8% in women (p < 0.001); this association was again unaffected by sex (p interaction = 0.409). A bilinear adjustment applicable to both men and women was developed: relative increase in hip fracture probability 4.7% for every millimeter that HAL is above the sex-specific average, relative decrease in hip fracture probability 3.8% for every millimeter that HAL is below the sex-specific average. We concluded that greater DXA-derived HAL is associated with increased incident hip fracture risk in both men and women, and this risk is independent of BMD and FRAX probability.

A two-level subject-specific biomechanical model for improving prediction of hip fracture risk

BackgroundSideways fall-induced hip fracture is a major worldwide health problem among the elderly population. However, all existing biomechanical models for predicting hip fracture mainly consider the femur related parameters. Their accuracy is limited as hip fracture is significantly affected by loading conditions as well. The objective of this study was to develop a biomechanical model for improving assessment of hip fracture risk by subject-specific prediction of fall-induced loading conditions. MethodAll information required to construct the models was extracted from the subject's whole-body and hip medical image in order to make the models subject-specific. Fall-induced hip fracture risk for eighty clinical cases was calculated under two sets of loading conditions: subject-specific determined by the proposed model, and non-subject-specific obtained from empirical functions. The predicted hip fracture risk indices were then compared with clinical observations. FindingsIt was found that the subject-specific prediction of fall-induced loading conditions significantly improves the hip fracture risk assessment. Consistent to the clinical observations, the fracture risk predicted by the proposed model suggested that obesity is a protective factor for hip fracture and underweight subjects are more likely to experience a hip fracture. InterpretationsThis study shows that hip fracture risk is affected by a number of factors, including body weight, body height, impact force, body mass index, hip soft tissue thickness, and bone quality. The proposed model provides a comprehensive, fast, accurate, and non-expensive method for prediction of hip fracture risk which should lead to more effective prevention of hip fractures.

Study of DXA-derived lateral–medial cortical bone thickness in assessing hip fracture risk

The currently available clinical tools have limited accuracy in predicting hip fracture risk in individuals. We investigated the possibility of using normalized cortical bone thickness (NCBT) estimated from the patient's hip DXA (dual energy X-ray absorptiometry) as an alternative predictor of hip fracture risk. Hip fracture risk index (HFRI) derived from subject-specific DXA-based finite element model was used as a guideline in constructing the mathematical expression of NCBT. We hypothesized that if NCBT has stronger correlations with HFRI than the single risk factors such as areal BMD (aBMD), then NCBT can be a better predictor. The hypothesis was studied using 210 clinical cases, including 60 hip fracture cases, obtained from the Manitoba Bone Mineral Density Database. The results showed that, in general HFRI has much stronger correlations with NCBT than any of the single risk factors; the strongest correlation was observed at the superior side of the narrowest femoral neck with r2=0.81 (p<0.001), which is much higher than the correlation with femoral aBMD, r2=0.50 (p<0.001). The capability of aBMD, NCBT, and HFRI in discriminating the hip fracture cases from the non-fracture ones, expressed as the area under the curve with 95% confidence interval, AUC (95% CI), is respectively 0.627 (0.593–0.657), 0.714 (0.644–0.784) and 0.839 (0.787–0.892). The short-term repeatability of aBMD, NCBT, and HFRI, measured by the coefficient of variation (CV, %), was found to be in the range of (0.64–1.22), (1.93–3.41), (3.10–4.16), respectively. We thus concluded that NCBT is potentially a better predictor of hip fracture risk.

Assessment of Hip Fracture Risk Using Cross-Section Strain Energy Determined by QCT-Based Finite Element Modeling

Accurate assessment of hip fracture risk is very important to prevent hip fracture and to monitor the effect of a treatment. A subject-specific QCT-based finite element model was constructed to assess hip fracture risk at the critical locations of femur during the single-leg stance and the sideways fall. The aim of this study was to improve the prediction of hip fracture risk by introducing a novel failure criterion to more accurately describe bone failure mechanism. Hip fracture risk index was defined using cross-section strain energy, which is able to integrate information of stresses, strains, and material properties affecting bone failure. It was found that the femoral neck and the intertrochanteric region have higher fracture risk than other parts of the femur, probably owing to the larger content of cancellous bone in these regions. The study results also suggested that women are more prone to hip fracture than men. The findings in this study have a good agreement with those clinical observations reported in the literature. The proposed hip fracture risk index based on strain energy has the potential of more accurate assessment of hip fracture risk. However, experimental validation should be conducted before its clinical applications.

AB0824 Improved Prediction of Hip Fracture Using the Health Assessment Questionnaire and FRAX in Japanese Patients with Rheumatoid Arhritis: A Prospective Observational Study

BackgroundThe World Health Organization Fracture Risk Assessment Tool (FRAX®) algorithm can be used to estimate 10-year probabilities of hip and major osteoporotic fractures. This tool has not yet been validated...

Fall-related risk factors and heel quantitative ultrasound in the assessment of hip fracture risk: a 10-year follow-up of a nationally representative adult population sample

Maximal walking speed and quantitative ultrasound index (QUI) were significant and independent predictors of hip fracture among subjects aged ≥ 55 years. A model including readily available variables along with simple fall-related factors may be clinically useful in the assessment of hip fracture risk even without a QUI measurement. This study assessed fall-related risk factors along with heel bone quantitative ultrasound (QUS) measurements for the prediction of hip fracture during a mean follow-up of 9.8 years in a nationally representative population sample. The study population consisted of 2,300 subjects (1,331 women and 969 men) aged 55 years or over, who had participated in a comprehensive health survey in 2000-2001. Information on the subjects’ health and fall-related risk factors was obtained with interviews, questionnaires and tests carried out by specially trained professionals. QUS measurements were made by means of the Hologic Sahara device. First emerging cases of hip fracture were identified from the National Hospital Discharge Register. During the follow-up, 96 subjects sustained a hip fracture. Slow maximal walking speed, low quantitative ultrasound index (QUI), high age, tallness, short waist circumference, Parkinson's disease and the number of central nervous system active medication were significant and independent predictors of hip fracture. The model including all of these risk factors explained 68 % of the variation in hip fracture risk. Excluding QUI from this model reduced the percentage to 66%. Maximal walking speed and QUI were significant and independent predictors of hip fracture. A model including readily available variables such as age, gender, height and waist circumference along with simple fall-related factors may be of clinical use in the assessment of hip fracture risk even without a QUS measurement.

One-leg standing time and hip-fracture prediction

A hip fracture results in a lower quality of life and a cost of £30,000. In this study, one-leg standing time (OLST) had a negative linear relationship to the risk of a hip fracture. OLST could be a useful tool to assess the need for fracture-preventive interventions. A hip fracture immobilizes, restricts autonomy, shortens life expectancy, and results in a cost of £30,000 in the UK health care system. However, effective preventive treatments can be offered to high-risk individuals. Impaired postural balance is an important risk factor for hip fractures, and the aim of this study was to evaluate whether OLST can predict hip fractures in elderly women. FRAX is the most established fracture risk assessment tool worldwide and a secondary aim was to relate the predictive ability of OLST to that of FRAX in this population. Three hundred fifty-one women aged between 69 and 79 years were timed standing on one leg up to 30 s with eyes open and assessed with FRAX. Fracture data was obtained from registers. The main outcome, a hip fracture, occurred in 40 of the 351 participants (11.4%). The age-adjusted risk of a hip fracture was 5% lower with 1 s longer OLST (Hazard ratio 0.95, 95% CI 0.927-0.978). The relation between OLST and hip fracture risk was linear. Harrell's c was 0.60 for FRAX and 0.68 for OLST adjusted for age. With 1 s longer OLST, the risk of a hip fracture decreased significantly by 5%. This risk reduction was not explained by differences in the classic fracture risk factors included in FRAX. OLST had a predictive ability similar to FRAX. OLST is an easily performed balance test which may prove to be valuable in the assessment of hip fracture risk.

Recent Methods for Assessing Osteoporosis and Fracture Risk

In the management and treatment of osteoporosis, the target is to assess fracture risk and the end-point is to prevent fractures. Traditionally, measurement of bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA) has been the standard method for diagnosing osteoporosis, in addition to assessing fracture risk and therapeutic effects. Quantitative computed tomography (QCT) can quantify volumetric BMD, and cancellous bone can be measured independently of surrounding cortical bone and aortic calcification. Hip structure analysis (HSA) is a method using the DXA scan image and provides useful data for assessing hip fracture risk. Recently, new tools to assess osteoporosis and fracture risk have been developed. One of the recent advances has been the development of the FRAX (Fracture Risk Assessment Tool), which is helpful in conveying fracture risk to patients and providing treatment guidance to clinicians. Another advance is the finite element (FE) method based on data from computed tomography (CT), which is useful for assessing bone strength, fracture risk, and therapeutic effects on osteoporosis. In selecting the most appropriate drug for osteoporosis treatment, assessment by bone metabolic markers is an important factor. In this review, recent patents for assessing osteoporosis and fracture risk are discussed.

Prediction of impact force in sideways fall by image-based subject-specific dynamics model

The impact force applied to the greater trochanter during sideways fall is a critical factor for determining whether or not a hip fracture would occur. However, the impact force is subject-dependent as it is related to the subject’s anthropometric parameters and the kinematic variables in fall. It cannot be accurately predicted by the currently available dynamics models. We developed and validated a method for constructing subject-specific dynamics models to more accurately predict the impact force. The anthropometric parameters required in the model were obtained from the subject’s whole body DXA (dual energy X-ray absorptiometry) image. The subject-specific dynamics models were then validated by protected fall tests using young volunteers. The effects of anthropometric parameters on the impact force were investigated using 90 clinical DXA images obtained from a local osteoporosis clinic center. The impact forces predicted by subject-specific dynamics models had much better agreement with the experimental data, compared with those predicted by the existing empirical functions. The parametric study results indicated that although body weight and height are the dominant parameters affecting the impact force, other parameters such as the hip vertical velocity before impact also have considerable effects. This finding suggests that the existing empirical functions that only consider body weight and height may not be able to accurately predict the impact force. As whole body DXA images are readily available in osteoporosis clinic centers, the proposed method may have potential applications in the clinic to improve the assessment of fall-induced hip fracture risk.

Experimental Validation of Subject-Specific Dynamics Model for Predicting Impact Force in Sideways Fall

Sideways fall has been identified as the most critical situation for the elderly to develop hip fractures. The impact force onto the greater trochanter is the key factor for predicting fracture risk. For the elderly, the impact force can only be determined by dynamics simulations, and the dynamics model must be first validated by experiments before it can be applied in clinic. In this study, subject-specific whole-body dynamics models constructed from dual energy X-ray absorptiometry (DXA) images of the subjects were validated by controlled and protected fall tests using young volunteers. The validation results suggested that subject-specific dynamics model is much more accurate in predicting impact force induced in sideways fall than conventional non-subject-specific dynamics model. Therefore, subject-specific dynamics model can be applied in clinic to improve the accuracy of assessing hip fracture risk.

Hip fracture risk assessment: artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

BackgroundOsteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared.MethodsThe study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests.ResultsIn univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively).ConclusionsThe risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.

Precision study of DXA‐based patient‐specific finite element modeling for assessing hip fracture risk

Finite element (FE) modeling based on a patient's hip dual energy X-ray absorptiometry (DXA) image is a promising tool for more accurately assessing hip fracture risk, as it is able to comprehensively consider effects from all the mechanical parameters affecting hip fracture. However, a number of factors influence the precision (also known as repeatability or reproducibility) of a DXA-based FE procedure, for example, subject positioning in DXA scanning. As a procedure is required to have adequately high precision in clinical application, we investigated the effects of the involved factors on the precision of a DXA-based patient-specific FE procedure developed by the authors, to provide insight into how the precision of the procedure can be improved so that it can meet the clinical standards. Fracture risk indices corresponding to initial and repeat DXA scans acquired in 30 typical clinical subjects were computed and compared to assess short term repeatability of the procedure. It was found that inconsistent positioning followed by manual segmentation of the projected femur contour induced significant variability in the predicted fracture risk indices. This research suggests that, to apply the DXA-based FE procedure in clinical assessment, it will be necessary to pay more strict attention to subject positioning in DXA scanning.

Quantitative ultrasound measurements and vitamin D status in the assessment of hip fracture risk in a nationally representative population sample

Adjusted for age, gender, height and weight, calcaneal quantitative ultrasound (QUS) and serum 25-hydroxyvitamin D (S-25(OH)D) proved to be significant predictors of hip fracture among subjects aged ≥50 years. Even if their contribution to the predictive power was modest, they may be useful in the assessment of hip fracture risk in the elderly. This study assessed calcaneal QUS measurements, S-25(OH)D and several other factors for the prediction of hip fracture risk in a nationally representative population sample. The study population consisted of 3,305 subjects (1,872 women), aged 50 years or over, who had participated in a comprehensive health survey. QUS measurements were made by means of the Hologic Sahara device. S-25(OH)D was measured by radioimmunoassay. Emerging cases of hip fracture were identified from the National Hospital Discharge Register. During a mean follow-up of 8.4 years, 95 subjects sustained a hip fracture. After adjusting for age, gender, height, weight and each other, a 1 standard deviation increment in the quantitative ultrasound index (QUI) (21.7) and in S-25(OH)D (17.5 nmol/L) reduced the risk of hip fracture by 40 % (hazard ratio [HR] = 0.60, 95 % confidence interval [CI] = 0.42-0.86) and by 31 % (HR = 0.69, 95 % CI = 0.55-0.87), respectively. The predictive power of a model including age, gender, height and weight was improved by about 8 % after the addition of QUI and S-25(OH)D. Among subjects aged 75 years or over, the corresponding improvement was about 130 %. QUI and S-25(OH)D were significant and independent predictors of hip fracture. However, their ability to increase the predictive power of a statistical model including readily available simple variables such as age, gender, height and weight was rather modest. Still, our findings suggest that QUI and S-25(OH)D may be of clinical use in the assessment of hip fracture risk particularly in the elderly.

Predicting the Biomechanical Strength of Proximal Femur Specimens through High Dimensional Geometric Features and Support Vector Regression.

Estimating local trabecular bone quality for purposes of femoral bone strength prediction is important for improving the clinical assessment of osteoporotic hip fracture risk. In this study, we explore the ability of geometric features derived from the Scaling Index Method (SIM) in predicting the biomechanical strength of proximal femur specimens as visualized on multi-detector computed tomography (MDCT) images. MDCT scans were acquired for 50 proximal femur specimens harvested from human cadavers. An automated volume of interest (VOI)-fitting algorithm was used to define a consistent volume in the femoral head of each specimen. In these VOIs, the non-linear micro-structure of the trabecular bone was characterized by statistical moments of its BMD distribution and by local scaling properties derived from SIM. Linear multi-regression analysis and support vector regression with a linear kernel (SVRlin) were used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the FL values determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each image feature on independent test set. The best prediction result was obtained from the SIM feature set with SVRlin, which had the lowest prediction error (RMSE = 0.842 ± 0.209) and which was significantly lower than the conventionally used mean BMD (RMSE = 1.103 ± 0.262,, p<0.005). Our results indicate that the biomechanical strength prediction can be significantly improved in proximal femur specimens on MDCT images by using high-dimensional geometric features derived from SIM with support vector regression.

Relationships Between Femoral Strength Evaluated by Nonlinear Finite Element Analysis and BMD, Material Distribution and Geometric Morphology

Precise quantification of femur strength and accurate assessment of hip fracture risk would help physicians to identify individuals with high risk and encourage them to take preventive interventions. A major contributing factor of hip fracture is the reduction of hip strength, determined by the bone quality. Bone mineral density (BMD) alone cannot determine bone strength accurately. In this paper, subject-specific quantitative computer tomography (QCT) image-based finite element analyses were conducted to identify the quantitative relationships between femoral strength and BMD, material distribution and geometric morphology. Sixty-six subjects with QCT data of hip region were selected from the MrOS cohorts in Hong Kong. Subject-specific nonlinear finite element models were developed to predict strengths of proximal femurs. The models took non-linear elasto-plasticity and heterogeneity of bone tissues into consideration and derived bone strengths with proper bone failure criteria. From finite element analysis (FEA), relationships between femoral strength and BMD, material distribution, and geometric parameters were determined. Results showed that FEA-predicted femoral strength was highly correlated with BMD, material distribution, height, weight, diameters of femoral head (HD), and femoral neck (ND), as well as the moment arm for femoral neck bending-offset (OFF). Through principal components analysis, three independent principal components (PCs) were extracted. PC1 was the component of bone material quality. PC2 included height, weight, HD, and ND. PC3 mainly represented OFF. Multivariate linear regression showed that the PCs were strongly predictive of the FEA-predicted strength. This study provided quantitative information regarding the contributing factors of proximal femur strength and showed that such a biomechanical approach may have clinical potential in noninvasive assessment of hip fracture risk.

Investigation of differences between hip fracture types: A worthy strategy for improved risk assessment and fracture prevention

Edited by David Fyhrie could we improve this situation? For example, finite element techniques permitmodeling of different loading conditions and such analyseswould provide improved insight into fracture mechanics and guide the development of refined techniques, e.g. based on computed tomography. Hip fractures are the most problematic outcome of osteoporosis. In this perspective, we suggest that one potential reason for the current limits of hip fracture risk assessment may relate to the neglect of etiological and pathophysiological diversity of (a minimum of two) different types of hip fractures. We suggest that we can improve risk

Assessment of volumetric bone mineral density and geometry for hip with clinical CT device

It is one of the most important challenges for preventing hip fractures to establish an accurate non-invasive assessment of hip fracture risk. Quantitative computed tomography (QCT) is able to analyze not only volumetric bone mineral density (mg/cm3) of trabecular and cortical bone compartment separately, but also geometry and biomechanical parameters in bone such as cross-sectional area, cortical bone thickness, section modulus, buckling ratio etc. The analysis of geometry and biomechanical parameters at hip could provide better prediction of hip fracture risk, better understanding pathogenesis of hip fractures, and thus better selection of drug and/or lifestyle-based interventions.

Spine–hip discordance and fracture risk assessment: a physician-friendly FRAX enhancement

The FRAX® tool estimates a 10-year probability of fracture based upon multiple clinical risk factors and an optional bone mineral density (BMD) measurement obtained from the femoral neck. We describe a simple procedure for using lumbar spine BMD to enhance fracture risk assessment under the FRAX system. Discordance between lumbar spine (LS) and femoral neck (FN) T-scores is common and a source of clinical confusion since the LS measurement is not an input variable for the FRAX algorithm. The purpose of this study is to develop a procedure for adjusting FRAX probability based upon the T-score difference between the LS and FN (termed offset). The Manitoba BMD database was used to identify baseline LS and FN dual-energy X-ray absorptiometry examinations (33,850 women and 2,518 men age 50 and older) with FRAX estimates for a major osteoporotic fracture categorized as low (<10%), moderate (10-20%), and high (>20%). Fracture outcomes were assessed from population-based administrative data. An approach was developed and internally validated using a split-cohort design. The offset was found to significantly affect fracture risk [HR, 1.12 (95% CI, 1.06-1.18) per SD LS below FN] independent of the FRAX probability. The following rule was formulated: "Increase/decrease FRAX estimate for a major fracture by one tenth for each rounded T-score difference between LS and FN." In the validation subgroup, there was a significant improvement in the fracture prediction using FRAX with the proposed offset adjustment for major osteoporotic (P = 0.007) and vertebral fracture prediction (P < 0.001). For those at moderate risk under FRAX, 12.6% showed reclassification using the offset to a risk level that more accurately reflected their observed risk (25.2% reclassification for moderate risk discordant cases). A simple procedure that incorporates the offset between the LS and FN T-scores can enhance fracture risk prediction under the FRAX system.

Age-specific reference values of hip geometric indices from a representative sample of the Japanese female population: Japanese Population-based Osteoporosis (JPOS) Study

We analyzed 2,107 hip dual-energy X-ray absorptiometry (DXA) images from the Japanese Population-based Osteoporosis Study with the Hip Structure Analysis (HSA) program to obtain age-specific reference values of HSA indices for the Japanese female population. These references may help physicians accurately assess HSA results and aid researchers in making interracial comparisons of the indices. Hip geometry is expected to improve hip fracture risk assessment, which is usually assessed by bone mineral density (BMD) alone. We aimed to establish a reference database for Japanese women. We studied 2,107 Japanese women (15-79 years old) with no history of bone metabolism-related diseases from the Japanese Population-based Osteoporosis Study performed in 1996. Hip geometry was conducted on DXA images with the HSA program, which yielded data for cross-sectional area (CSA), subperiosteal diameter (PD), endocortical diameter (ED), mean cortical thickness (CT), section modulus (SM), and buckling ratio at the narrow neck (NN), intertrochanter (IT), and femoral shaft (FS) regions. Mean HSA indices were determined for each 5-year age group after adjustment for height and weight based on most recent Japanese population values. Age-related changes in HSA indices were evident for the 50-54 year group in the NN and IT regions and for the 55-59 year group in the FS region; these changes increased with age thereafter. Age-related changes in CSA and CT were almost identical to that of BMD. Japanese subjects exhibited BMD and CT values similar to those reported for US non-Hispanic white women, but had 16-23% smaller SM values. CSA and CT were highly correlated with conventional BMD, whereas ED, SM, and PD showed lower correlations. Age-specific reference values of HSA indices for the Japanese female population were obtained. This database will form the foundation for accurate HSA result evaluation.

Evaluation of Compressive Strength Index of the Femoral Neck in Caucasians and Chinese

Compressive strength index (CSI) of the femoral neck is a parameter that integrates the information of bone mineral density (BMD), femoral neck width (FNW), and body weight. CSI is considered to have the potential to improve the performance of assessment for hip fracture risk. However, studies on CSI have been rare. In particular, few studies have evaluated the performance of CSI, in comparison with BMD, FNW, and bending geometry, for assessment of hip fracture risk. We studied two large populations, including 1683 unrelated U.S. Caucasians and 2758 unrelated Chinese adults. For all the study subjects, CSI, femoral neck BMD (FN_BMD), FNW, and bending geometry (section modulus [Z]) of the samples were obtained from dual-energy X-ray absorptiometry scans. We investigated the age-related trends of these bone phenotypes and potential sex and ethnic differences. We further evaluated the performance of these four phenotypes for assessment of hip fracture risk by logistic regression models. Chinese had significantly lower FN_BMD, FNW, and Z, but higher CSI than sex-matched Caucasians. Logistic regression analysis showed that higher CSI was significantly associated with lower risk of hip fracture, and the significance remained after adjusting for covariates of age, sex, and height. Each standard deviation (SD) increment in CSI was associated with odds ratios of 0.765 (95% confidence interval, 0.634, 0.992) and 0.724 (95% confidence interval, 0.569, 0.921) for hip fracture risk in Caucasians and Chinese, respectively. The higher CSI in Chinese may partially help explain the lower incidence of hip fractures in this population compared to Caucasians. Further studies in larger cohorts and/or longitudinal observations are necessary to confirm our findings.