Fragility fracture is a serious clinical event, because it is associated with increased risk of mortality and reduced quality of life. The risk of fracture is determined by multiple risk factors, and their effects may be interactional. Over the past 10 years, a number of predictive models (e.g., FRAX, Garvan Fracture Risk Calculator, and Qfracture) have been developed for individualized assessment of fracture risk. These models use different risk profiles to estimate the probability of fracture over 5- and 10-year period. The ability of these models to discriminate between those individuals who will and will not have a fracture (i.e., area under the receiver operating characteristic curve [AUC]) is generally acceptable-to-good (AUC, 0.6 to 0.8), and is highly variable between populations. The calibration of existing models is poor, particularly in Asian populations. There is a strong need for the development and validation of new prediction models based on Asian data for Asian populations. We propose approaches to improve the accuracy of existing predictive models by incorporating new markers such as genetic factors, bone turnover markers, trabecular bone score, and time-variant factors. New and more refined models for individualized fracture risk assessment will help identify those most likely to sustain a fracture, those most likely to benefit from treatment, and encouraging them to modify their risk profile to decrease risk.
Asian Continental Ancestry Group ; Bone Remodeling ; Calibration ; Humans ; Mortality ; Osteoporosis ; Quality of Life ; Risk Assessment ; Risk Factors ; ROC Curve

Objectives: The association between body composition parameters and peak bone mineral density is not well documented. The aim of this study is to assess the relative contributions of lean mass and fat mass on peak bone mineral density (BMD). Methods: The study involved 416 women and 334 men aged between 20 and 30 years who were participants in the population-based Vietnam Osteoporosis Study. Whole body composition parameters (eg, fat mass and lean mass) and BMD at the lumbar spine and femoral neck were measured by dual-energy X-ray absorptiometry. The association between lean mass and fat mass and BMD was analyzed by the linear regression model using the Least Absolute Shrinkage and Selection Operator (LASSO). Results: Peak BMD in men was higher than women, and the difference was more pronounced at the femoral neck (average difference: 0.123 g/㎠; 95% confidence interval [CI] 0.105–0.141 g/㎠) than at the lumbar spine (average difference 0.019 g/㎠; 95% CI, 0.005–0.036 g/㎠). Results of LASSO regression indicated that lean mass was the only predictor of BMD for either men or women. Each kilogram increase in lean mass was associated with ∼0.01 g/㎠ increase in BMD. Lean mass alone explained 16% and 36% of variation in lumbar spine and femoral neck BMD, respectively. Conclusions Lean mass, not fat mass, is the main determinant of peak bone mineral density. This finding implies that good physical activity during adulthood can contribute to the maximization of peak bone mass during adulthood.

Objectives: The association between body composition parameters and peak bone mineral density is not well documented. The aim of this study is to assess the relative contributions of lean mass and fat mass on peak bone mineral density (BMD). Methods: The study involved 416 women and 334 men aged between 20 and 30 years who were participants in the population-based Vietnam Osteoporosis Study. Whole body composition parameters (eg, fat mass and lean mass) and BMD at the lumbar spine and femoral neck were measured by dual-energy X-ray absorptiometry. The association between lean mass and fat mass and BMD was analyzed by the linear regression model using the Least Absolute Shrinkage and Selection Operator (LASSO). Results: Peak BMD in men was higher than women, and the difference was more pronounced at the femoral neck (average difference: 0.123 g/㎠; 95% confidence interval [CI] 0.105–0.141 g/㎠) than at the lumbar spine (average difference 0.019 g/㎠; 95% CI, 0.005–0.036 g/㎠). Results of LASSO regression indicated that lean mass was the only predictor of BMD for either men or women. Each kilogram increase in lean mass was associated with ∼0.01 g/㎠ increase in BMD. Lean mass alone explained 16% and 36% of variation in lumbar spine and femoral neck BMD, respectively. Conclusions Lean mass, not fat mass, is the main determinant of peak bone mineral density. This finding implies that good physical activity during adulthood can contribute to the maximization of peak bone mass during adulthood.

Objectives: Vertebral fracture is both common and serious among adults, yet it often goes undiagnosed. This study aimed to develop a shape-based algorithm (SBA) for the automatic identification of vertebral fractures. Methods: The study included 144 participants (50 individuals with a fracture and 94 without a fracture) whose plain thoracolumbar spine X-rays were taken. Clinical diagnosis of vertebral fracture (grade 0 to 3) was made by rheumatologists using Genant’s semiquantitative method. The SBA algorithm was developed to determine the ratio of vertebral body height loss. Based on the ratio, SBA classifies a vertebra into 4 classes: 0 = normal, 1 = mild fracture, 2 = moderate fracture, 3 = severe fracture). The concordance between clinical diagnosis and SBAbased classification was assessed at both person and vertebra levels. Results: At the person level, the SBA achieved a sensitivity of 100% and specificity of 62% (95% CI, 51%–72%). At the vertebra level, the SBA achieved a sensitivity of 84% (95% CI, 72%–93%), and a specificity of 88% (95% CI, 85%–90%). On average, the SBA took 0.3 s to assess each X-ray. Conclusions The SBA developed here is a fast and efficient tool that can be used to systematically screen for asymptomatic vertebral fractures and reduce the workload of healthcare professionals.

OBJECTIVES: Osteoporosis and fracture impose a significant health care burden on the contemporary populations in developing countries. The Vietnam Osteoporosis Study (VOS) sought to assess the burden of osteoporosis and its comorbidities in men and women. METHODS: The study was designed as a population-based family investigation in which families were randomly recruited from Ho Chi Minh City, Vietnam. Individuals were assessed for bone health, including bone mineral density (BMD) and body composition and trabecular and cortical bone properties by pQCT (peripheral quantitative computed tomography). Fasting blood samples were obtained for the analysis of plasma glucose, glycosylated hemoglobin, and bone turnover markers. Genomic DNA extraction from whole blood samples for further genetic and genomic analyses. RESULTS: We have recruited more than 4157 individuals from 817 families. The average age of participants was 51, with approximately 45% of the individuals aged 50 years and older. Approximately 3% of participants were obese (body mass index ≥ 30 kg/m²), and 21% were overweight. Notably, 11% of participants aged 40 years and older were diabetic. Among those aged 50 years and older, approximately 14% of women and 5% of men had osteoporosis (i.e., femoral neck BMD T-scores ≤−2.5). There were modest correlations between volumetric BMD and areal BMD. CONCLUSIONS: VOS is a major bone research project in Vietnam aimed at comprehensively documenting the burden osteoporosis, its co-occurrence of chronic diseases, and their underlying etiologies. The Study will make important contributions to the literature of bone health worldwide.
Blood Glucose ; Body Composition ; Bone Density ; Bone Remodeling ; Chronic Disease ; Comorbidity ; Delivery of Health Care ; Developing Countries ; DNA ; Fasting ; Female ; Femur Neck ; Hemoglobin A, Glycosylated ; Humans ; Male ; Muscle Strength ; Osteoporosis* ; Overweight ; Sarcopenia ; Vietnam*

Bone research is a dynamic area of scientific investigation that usually encompasses multidisciplines. Virtually all basic cellular research, clinical research and epidemiologic research rely on statistical concepts and methodology for inference. This paper discusses common issues and suggested solutions concerning the application of statistical thinking in bone research, particularly in clinical and epidemiological investigations. The issues are sample size estimation, biases and confounders, analysis of longitudinal data, categorization of continuous data, selection of significant variables, over-fitting, P-values, false positive finding, confidence interval, and Bayesian inference. It is hoped that by adopting the suggested measures the scientific quality of bone research can improve.

Bone research is a dynamic area of scientific investigation that usually encompasses multidisciplines. Virtually all basic cellular research, clinical research and epidemiologic research rely on statistical concepts and methodology for inference. This paper discusses common issues and suggested solutions concerning the application of statistical thinking in bone research, particularly in clinical and epidemiological investigations. The issues are sample size estimation, biases and confounders, analysis of longitudinal data, categorization of continuous data, selection of significant variables, over-fitting, P-values, false positive finding, confidence interval, and Bayesian inference. It is hoped that by adopting the suggested measures the scientific quality of bone research can improve.

Background: Common variants in the fat mass and obesity-related transcript (FTO) gene are related to body mass index and obesity, suggesting its potential association with bone mineral density (BMD) and fracture risk. This study sought to define the association between FTO gene variants and the following phenotypes: (1) BMD; (2) bone loss; and (3) fracture risk. Methods: This analysis was based on the Dubbo Osteoporosis Epidemiology Study that included 1,277 postmenopausal women aged ≥60 years living in Dubbo, Australia. BMD at the femoral neck and lumbar spine was measured biennially by dual energy X-ray absorptiometry (GE Lunar). Fractures were radiologically ascertained. Six single nucleotide polymorphisms (SNPs; rs1421085, rs1558902, rs1121980, rs17817449, rs9939609, and rs9930506) of the FTO gene were genotyped using TaqMan assay. Results: Women homozygous for the minor allele (GG) of rs9930506 had a significantly higher risk of hip fracture (adjusted hazard ratio, 1.93; 95% confidence interval, 1.15–3.23) than those homozygous for the major allele (AA) after adjusting for potential confounding effects. Similar associations were also observed for the minor allele of rs1121980. However, there was no significant association between the FTO SNPs and BMD or the rate of bone loss. Conclusions Common variations in the FTO gene are associated with a hip fracture risk in women, and the association is not mediated through BMD or bone loss.

Objectives: Osteoporotic fracture is a significant public health burden associated with increased mortality risk and substantial healthcare costs. Accurate and early identification of high-risk individuals and mitigation of their risks is a core part of the treatment and prevention of fractures. Here we introduce a digital tool called 'BONEcheck' for personalized assessment of bone health. Methods: The development of BONEcheck primarily utilized data from the prospective population-based Dubbo Osteoporosis Epidemiology Study and the Danish Nationwide Registry. BONEcheck has 3 modules: input data, risk estimates, and risk context. Input variables include age, gender, prior fracture, fall incidence, bone mineral density (BMD), comorbidities, and genetic variants associated with BMD. Results: Based on the input variables, BONEcheck estimates the probability of any fragility fracture and hip fracture within 5 years, subsequent fracture risk, skeletal age, and time to reach osteoporosis. The probability of fracture is shown in both numeric and human icon array formats. The risk is also contextualized within the framework of treatment and management options on Australian guidelines, with consideration given to the potential fracture risk reduction and survival benefits. Skeletal age was estimated as the sum of chronological age and years of life lost due to a fracture or exposure to risk factors that elevate mortality risk. Conclusions BONEcheck is an innovative tool that empowers doctors and patients to engage in wellinformed discussions and make decisions based on the patient's risk profile. Public access to BONEcheck is available via https://bonecheck.org and in Apple Store (iOS) and Google Play (Android).

Objectives: Calcaneal quantitative ultrasound measurement (QUS) has been considered an alternative to dual-energy X-ray absorptiometry (DXA) based bone mineral density (BMD) for assessing bone health. This study sought to examine the utility of QUS as an osteoporosis screening tool by evaluating the correlation between QUS and DXA. Methods: The study was a part of the Vietnam Osteoporosis Study that involved 1270 women and 773 men aged 18 years and older. BMD at the femoral neck, total hip and lumbar spine was measured using DXA. Osteoporosis was diagnosed based on the femoral neck T-score using World Health Organization criteria. Broadband ultrasound attenuation (BUA) at the calcaneus was measured by QUS. The concordance between BUA and BMD was analyzed by the linear regression model. Results: In all individuals, BUA modestly correlated with femoral neck BMD (r = 0.35; P < 0.0001) and lumbar spine BMD (r = 0.34; P < 0.0001) in both men and women. In individuals aged 50 years and older, approximately 16% (n = 92/575) of women and 3.2% (n = 10/314) of men were diagnosed to have osteoporosis. Only 0.9% (n = 5/575) women and 1.0% (n = 3/314) men were classified as “Low BUA”. The kappa coefficient of concordance between BMD and BUA classification was 0.09 (95% CI, 0.04 to 0.15) for women and 0.12 (95% CI, 0.03 to 0.22) for men. Conclusions In this population-based study, QUS BUA modestly correlated with DXA BMD, suggesting that BUA is not a reliable method for screening of osteoporosis.