Systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for osteoporosis or low bone density

Comparative accuracy of osteoporosis risk assessment tools in postmenopausal women: A systematic review and network meta-analysis

BACKGROUND

The Fracture Risk Assessment Tool (FRAX, threshold ≥9.3 %), Osteoporosis Risk Assessment Instrument (ORAI, ≥9), Osteoporosis Index of Risk (OSIRIS, <1), Osteoporosis Self-Assessment Tool (OST, <2), and Simple Calculated Osteoporosis Risk Estimation (SCORE, ≥6) have been endorsed by the US Preventive Services Task Force for evaluating the need for bone mineral density measurement by dual-energy X-ray absorptiometry in postmenopausal women.

OBJECTIVE

To systematically compare the sensitivity and specificity of the five osteoporosis risk assessment tools for detecting bone mineral density-defined osteoporosis.

METHODS

A systematic search was conducted across the Cochrane Library, Embase, PubMed and Web of Science databases up to January 29, 2024, to identify observational studies that evaluated comparative accuracy of these tools in postmenopausal women. The Quality Assessment of Diagnostic Accuracy Studies-2 and its comparative extension were utilized to evaluate the risk of bias and applicability. Pooled odds ratios (ORs) and 95 % confidence intervals (CIs) for relative sensitivity and specificity were calculated using a multivariate random-effects model, with tool rankings determined by Surface Under the Cumulative Ranking (SUCRA).

RESULTS

17 studies were included, involving 9669 postmenopausal women with bone mineral density-defined osteoporosis and 34,143 without the condition. The SCORE (OR = 12.11, 95 % CI [4.46-32.86]) exhibited significantly higher sensitivity than FRAX, followed by ORAI (OR = 7.01, 95 % CI [2.84-17.31]) and OST (OR = 6.90, 95 % CI [3.07-15.52]). Compared to OSIRIS, higher sensitivity was observed for SCORE (OR = 4.92, 95 % CI [2.41-10.05]), ORAI (OR = 2.85, 95 % CI [1.63-4.99]), and OST (OR = 2.80, 95 % CI [1.58-4.97]). However, specificity was lower for SCORE (OR = 0.16, 95 % CI [0.08-0.33]), ORAI (OR = 0.26, 95 % CI [0.13-0.51]), and OST (OR = 0.28, 95 % CI [0.15-0.53]) compared to FRAX. Similarly, SCORE (OR = 0.25, 95 % CI [0.15-0.41]), ORAI (OR = 0.40, 95 % CI [0.26-0.62]), and OST (OR = 0.44, 95 % CI [0.27-0.69]) showed significantly lower specificity than OSIRIS. Based on SUCRA values, SCORE (98.2 %) ranked as the most sensitive tool, followed by ORAI (64.2 %) and OST (62.6 %), whereas FRAX (96.7 %) was the most specific, followed by OSIRIS (78.3 %).

CONCLUSIONS

The risk assessment tools for identifying postmenopausal women with bone mineral density-defined osteoporosis, endorsed by the US Preventive Services Task Force, can be categorized into two groups. SCORE (≥6), ORAI (≥9), and OST (<2) offer higher sensitivity, identifying more osteoporosis patients, whereas FRAX (≥9.3 %) and OSIRIS (<1) provide higher specificity, identifying those without the condition more accurately.

REGISTRATION

PROSPERO (CRD42024507532).

Comparing machine learning models for osteoporosis prediction in Tibetan middle aged and elderly women

The aim of this study was to establish the optimal prediction model by comparing the prediction effect of 6 kinds of prediction models containing biochemical indexes on the risk of osteoporosis in middle-aged and elderly women in Tibet. This study adopted a multi-stage cluster random sampling cross-sectional survey method. From January 2022 to January 2024, we obtained biochemical and bone mineral density (BMD) data from high altitudes in Tibet. We built a predictive model of osteoporosis in three steps. First, we performed feature selection to identify factors associated with osteoporosis. Next, the eligible participants were randomly divided into a training set and a test set in a ratio of 8:2. Then, the prediction model of osteoporosis was established based on Random Forest, ANN, XGB, and SVM. Finally, we compared the performance of the prediction models using sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) to select the best prediction model. Correlation analysis was used to screen indicators with statistical differences from T-score. Finally, Age (P < 0.01), LDL-C (P < 0.05), UA (P < 0.01), AST (P < 0.05), CREA (P < 0.01), BMI (P < 0.01), ALT (P < 0.01) were associated with osteoporosis. In train set, the order of AUC from highest to lowest is Random Forest (1.000), XGB (0.887), SVM (0.868), regression (0.801), ANN (0.793) and OSTA (0.739). In test set, the order of AUC from highest to lowest is XGB (0.848), regression (0.801), Random Forest (0.772), SVM (0.755), OSTA (0.739), ANN (0.732). SVM and XGB algorithm models had better screening effect on osteoporosis than OSTA in middle-aged and elderly Tibetan residents in Tibet. Compared with Random Forest, ANN and SVM, the established XGB model had the best prediction ability and can be used to predict the risk of osteoporosis on biochemical indexes. The model needs to be further improved through large sample research.

Osteoporosis risk and its association with all-cause and cause-specific mortality among the elderly: a 16-year nationwide cohort study

BACKGROUND

Aged osteoporosis poses a significant threat to the well-being and longevity of older individuals, yet evidence regarding the relationship between osteoporosis risk and mortality among the elderly population in Asia remains unknown.

AIMS

Our study aimed to investigate associations between osteoporosis risk and all-cause mortality, as well as cause-specific mortality, among the Chinese elderly population.

METHODS

Pooled data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) conducted between 2002 and 2018 were utilized to analyze the associations between osteoporosis risk and all-cause, heart disease, cardiovascular disease (CVD), respiratory disease, and cancer mortality. Cox proportional hazards models were employed for this analysis. Osteoporosis risk was assessed using the Osteoporosis Self-Assessment Tool for Asians (OSTA). Restricted cubic spline (RCS) functions were applied to explore the nonlinear relationship between OSTA and mortality. The robustness of the Cox models was evaluated through internal verification, subgroup analyses, and sensitivity analyses.

RESULTS

A total of 12,711 elderly individuals aged ≥ 65 years were included for analysis at baseline. During a 16-year follow-up, 7,963 individuals in the cohort were identified as deceased. Compared to those with low osteoporosis risk, elderly individuals with high osteoporosis risk demonstrated a significantly elevated risk of all-cause, heart disease, CVD, respiratory disease and cancer mortality. The relationship between OSTA level and all-cause and cause-specific mortality exhibited a significant L-shaped pattern.

CONCLUSIONS

The risk of osteoporosis is independently associated with the prediction of mortality. The OSTA may serve as a suitable predictor for mortality related to osteoporosis among the Asian population.

Performance of the Osteoporosis Self-Assessment Tool for Asians (OSTA) Index for Osteoporosis Screening in Thai Men: A Cross-Sectional Study

Background Addressing the under-recognition of osteoporosis in men necessitates the use of suitable screening tools tailored to the male population. The Osteoporosis Self-Assessment Tool for Asians (OSTA) index is a reliable tool for evaluating the risk of osteoporosis. This cross-sectional study aims to assess the predictive performance of the OSTA index in Thai men. Additionally, the study compares the performance of the OSTA index with the Khon Kaen Osteoporosis Study (KKOS) score and an age cutoff value of ≥70 years. Methods Between November 2017 and October 2024, men aged 50 years or older who underwent dual-energy X-ray absorptiometry and did not receive any osteoporosis treatment were included. The performance of the individual OSTA index cutoff values in predicting osteoporosis was assessed. Results A total of 427 men were included in this study and classified into normal bone mineral density (BMD) (175 men, 41%), osteopenia (210 men, 49.2%), and osteoporosis (42 men, 9.8%). The mean age, weight, and body mass index were 76.4 years, 65.9 kg, and 24.1 kg/m², respectively. The OSTA index cutoff of -1 at any BMD site produced a Youden index of 0.187, with a sensitivity of 85.7% and a specificity of 33%. Meanwhile, the OSTA index cutoff of -4 at any BMD site resulted in a Youden index of 0.395, with a sensitivity of 59.5% and a specificity of 80%. The area under the receiver operating characteristic curve (AUC) of the KKOS score ≤-1 was 0.636. The AUC of the OSTA index ≤-1 was 0.594, which was significantly lower than the AUC of the KKOS score ≤-1 (P = 0.003). The AUC of age ≥70 years was 0.494, which was significantly lower than the AUC of the OSTA index ≤-1 (P < 0.001). Conclusion For osteoporosis screening in Thai men, the OSTA index cutoff value of -1 is more appropriate than a cutoff value of -4. However, the KKOS score cutoff value of ≤-1 serves as the most effective predictor for osteoporosis screening.

Osteoporosis in men-East and West: Can the twain meet? A perspective from Asia

Osteoporosis in men remains a significantly underrecognized condition, with notable differences in bone mineral density (BMD) and fracture risk between Asian and Western populations. Despite 30% of hip fractures globally occurring in men, they are less likely to be diagnosed or treated for osteoporosis, especially in resource-limited settings. Given these disparities, a deeper understanding of osteoporosis epidemiology and treatment efficacy in men is essential, particularly in Asian populations. This review synthesizes the latest evidence on the epidemiology, screening, and treatment of osteoporosis in men, with a focus on genetic, environmental, and epidemiological disparities between Eastern and Western populations. Additionally, the review examines existing controversies surrounding fracture risk screening in men and evaluates the efficacy and cost-effectiveness of pharmacological treatments such as bisphosphonates, denosumab, and anabolic agents. Asian men exhibit lower peak BMD compared to their Caucasian counterparts, leading to potential misdiagnoses when using Caucasian-based BMD reference ranges. Screening tools like the Fracture Risk Assessment Tool (FRAX)® show variability in performance across populations. Data on pharmacological treatment in men remain limited, although studies suggest comparable benefits to those observed in women. Larger studies, particularly in male and Asian populations, are urgently needed to refine diagnostic and therapeutic guidelines. Osteoporosis in men is underdiagnosed and undertreated globally, with pronounced disparities between populations. Current diagnostic tools and treatment protocols are not fully tailored to male and Asian populations. There is an urgent need for longitudinal studies focusing on male-specific osteoporosis management to reduce fracture risk and improve outcomes.

Associations between gut microbiota and osteoporosis or osteopenia in a cohort of Chinese Han youth

Osteoporosis (OP) is a common metabolic bone disease characterized by low bone mass and microstructural deterioration of bone. Changes in the composition and structure of gut microbiota (GM) are related to changes of bone mass and bone microstructure. However, the relationship between GM and bone mineral density (BMD) is complex, and data are especially scarce for Chinese Han youth. Therefore, 62 Chinese Han youth participants were recruited. Furthermore, according to the T-score evaluation criteria of the World Health Organization (WHO), we divided the BMD levels of participants into three groups: osteoporosis\BDL, osteopenia\BDM, normal bone density\BDH, and the associations between GM community and BMD groups were conducted. According to alpha and beta diversity analysis, significant differences were found in the microbial richness and composition between groups. The dominant phyla of GM in a cohort of Chinese Han youth were Bacteroidota (50.6%) and Firmicutes (41.6%). Anaerobic microorganisms, such as g_Faecalibacterium and g_Megamonas, account for the largest proportion in the gut, which were mainly Firmicutes phylum. The dominant genera and species in the three BMD groups were g_Prevotella, g_Bacteroides, g_Faecalibacterium, g_Megamonas, s_Prevotella copri, s_unclassified_g_Faecalibacterium, s_unclassified_g_Prevotella, s_unclassified_g_Bacteroides and s_Bacteroides plebeius. g_Faecalibacterium, g_Bacteroides and g_Ruminococcus differed between the BDH and BDL groups as well as between the BDH and BDM groups. LEfSe showed three genus communities and eight species communities were enriched in the three BMD groups, respectively. The associations between microbial relative abundance and T-score was not statistically significant by Spearman and regression analysis. In conclusion, the alpha diversity indexes in the BDH group were higher than in the BDL group, and several taxa were identified that may be the targets for diagnosis and therapy of OP.

Clinical Validation of a Deep Learning-Based Software for Lumbar Bone Mineral Density and T-Score Prediction from Chest X-ray Images

Screening for osteoporosis is crucial for early detection and prevention, yet it faces challenges due to the low accuracy of calcaneal quantitative ultrasound (QUS) and limited access to dual-energy X-ray absorptiometry (DXA) scans. Recent advances in AI offer a promising solution through opportunistic screening using existing medical images. This study aims to utilize deep learning techniques to develop a model that analyzes chest X-ray (CXR) images for osteoporosis screening. This study included the AI model development stage and the clinical validation stage. In the AI model development stage, the combined dataset of 5122 paired CXR images and DXA reports from the patients aged 20 to 98 years at a medical center was collected. The images were enhanced and filtered for hardware retention such as pedicle screws, bone cement, artificial intervertebral discs or severe deformity in target level of T12 and L1. The dataset was then separated into training, validating, and testing datasets for model training and performance validation. In the clinical validation stage, we collected 440 paired CXR images and DXA reports from both the TCVGH and Joy Clinic, including 304 pared data from TCVGH and 136 paired data from Joy Clinic. The pre-clinical test yielded an area under the curve (AUC) of 0.940, while the clinical validation showed an AUC of 0.946. Pearson's correlation coefficient was 0.88. The model demonstrated an overall accuracy, sensitivity, and specificity of 89.0%, 88.7%, and 89.4%, respectively. This study proposes an AI model for opportunistic osteoporosis screening through CXR, demonstrating good performance and suggesting its potential for broad adoption in preliminary screening among high-risk populations.

Insights and implications of sexual dimorphism in osteoporosis

Osteoporosis, a metabolic bone disease characterized by low bone mineral density and deterioration of bone microarchitecture, has led to a high risk of fatal osteoporotic fractures worldwide. Accumulating evidence has revealed that sexual dimorphism is a notable feature of osteoporosis, with sex-specific differences in epidemiology and pathogenesis. Specifically, females are more susceptible than males to osteoporosis, while males are more prone to disability or death from the disease. To date, sex chromosome abnormalities and steroid hormones have been proven to contribute greatly to sexual dimorphism in osteoporosis by regulating the functions of bone cells. Understanding the sex-specific differences in osteoporosis and its related complications is essential for improving treatment strategies tailored to women and men. This literature review focuses on the mechanisms underlying sexual dimorphism in osteoporosis, mainly in a population of aging patients, chronic glucocorticoid administration, and diabetes. Moreover, we highlight the implications of sexual dimorphism for developing therapeutics and preventive strategies and screening approaches tailored to women and men. Additionally, the challenges in translating bench research to bedside treatments and future directions to overcome these obstacles will be discussed.

Osteoporosis Prediction Using Machine-Learned Optical Bone Densitometry Data

Optical bone densitometry (OBD) has been developed for the early detection of osteoporosis. In recent years, machine learning (ML) techniques have been actively implemented for the areas of medical diagnosis and screening with the goal of improving diagnostic accuracy. The purpose of this study was to verify the feasibility of using the combination of OBD and ML techniques as a screening tool for osteoporosis. Dual energy X-ray absorptiometry (DXA) and OBD measurements were performed on 203 Thai subjects. From the OBD measurements and readily available demographic data, machine learning techniques were used to predict the T-score measured by the DXA. The T-score predicted using the Ridge regressor had a correlation of r = 0.512 with respect to the reference value. The predicted T-score also showed an AUC of 0.853 for discriminating individuals with osteoporosis. The results obtained suggest that the developed model is reliable enough to be used for screening for osteoporosis.

A novel primary osteoporosis screening tool (POST) for adults aged 50 years and over

PURPOSE

This study aimed to develop and validate a simple primary osteoporosis screening tool (POST) based on adults aged 50 years and older.

METHODS

This study included participants aged ≥50 from the National Health and Nutrition Examination Survey. Osteoporosis was defined according to bone mineral density values. The POST was developed based on methods from previous studies. Moreover, we plotted the receiver operating characteristic curves to calculate the area under the curve (AUC) and determine the optimal cut-off value according to the weighted Youden index. In addition, we compared the performances in identifying individuals with osteoporosis between the POST and the Osteoporosis Self-assessment Tool (OST). Finally, we also assessed the performance of the POST in the Chinese population.

RESULTS

Finally, a total of 6665 individuals were included in this study. The AUC values of the POST for identifying individuals with osteoporosis in the development cohort and the validation cohort were 0.81 (95% CI: 0.79-0.83) and 0.81 (95% CI: 0.77-0.84), respectively. Moreover, a POST-score ≥7 was determined as the threshold to identify individuals with osteoporosis, in which the sensitivity was greater than 90%. In addition, the POST showed significantly higher sensitivity than the OST. Finally, the POST showed an AUC of 0.75 (95% CI: 0.65-0.85) among 94 Chinese subjects aged ≥50 years old.

CONCLUSIONS

POST is a convenient and effective tool for osteoporosis screening among adults aged 50 years and over, which might provide new methodological support for future osteoporosis screening.

Screening for Osteoporosis Risk Among Community-Dwelling Older Adults: A Scoping Review

BACKGROUND AND PURPOSE

Due to potential health-related consequences of osteoporosis (OP), health care providers who do not order imaging, such as physical therapists, should be aware of OP screening tools that identify individuals who need medical and rehabilitation care. However, current knowledge and guidance on screening tools is limited. Therefore, we explored OP screening tools that are appropriate and feasible for physical therapy practice, and evaluated tools' effectiveness by examining their clinimetric properties.

METHODS

A systematic search of the following databases was performed: PubMed, PEDro, PsycINFO, CINAHL, and Web of Science. Articles were included if the study population was 50 years and older, had a diagnosis of OP, if the screening tool was within the scope of physical therapy practice, and was compared to either a known diagnosis of OP or bone densitometry scan results. Included articles underwent multiple reviews for inclusion and exclusion, with each review round having a different randomly selected pair of reviewers. Data were extracted from included articles for participant demographics, outcome measures, cut-off values, and clinimetric properties. Results were categorized with positive and negative likelihood ratios (+LR/-LR) based on the magnitude of change in the probability of having or not having OP.

RESULTS

+LRs ranged from 0.15 to 20.21, with the Fracture Risk Assessment Tool (FRAX) and Study of Osteoporotic Fractures (SOF) having a large shift in posttest probability. -LRs ranged from 0.03 to 1.00, with the FRAX, Male Osteoporosis Risk Estimation Scores, Osteoporosis Self-Assessment Tool (OST), and Simple Calculated Osteoporosis Risk Estimation having a large shift in posttest probability.

CONCLUSION

Tools with moderate-large shift for both +LR and -LR recommended for use are: (1) OST; (2) FRAX; and (3) SOF. The variability in cut-off scores and clinimetric properties based on gender, age, and race/ethnicities made it impossible to provide one specific recommendation for an OP screening tool. Future research should focus on OP risk prediction among males and racial and ethnic groups.

Klotho reduces the risk of osteoporosis in postmenopausal women: a cross-sectional study of the National Health and Nutrition Examination Survey (NHANES)

BACKGROUND

Osteoporosis (OP) is one of the diseases that endanger the health of the elderly population. Klotho protein is a hormone with anti-aging effects. A few studies have discussed the relationship between Klotho and OP. However, there is still a lack of research on larger populations. This study aims to evaluate the association between OP and Klotho in American postmenopausal women.

METHODS

This is a retrospective study. We searched the National Health and Nutrition Examination Survey (NHANES) database and collected data of 3 survey cycles, finally involving 871 postmenopausal women over 50 years old in the present study. All participants took dual-energy X-ray absorptiometry examination and serum Klotho testing at the time of investigation. After adjusting the possible confounding variables, a multivariate regression model was employed to estimate the relationship between OP and Klotho proteins. Besides, the P for trend and restricted cubic spline (RCS) were applied to examine the threshold effect and calculate the inflection point.

RESULTS

Factors influencing the occurrence of OP included age, ethnicity, body mass index and Klotho levels. Multivariate regression analysis indicated that the serum Klotho concentration was lower in OP patients than that in participants without OP (OR[log2Klotho] = 0.568, P = 0.027). The C-index of the prediction model built was 0.765, indicating good prediction performance. After adjusting the above-mentioned four variables, P values for trend showed significant differences between groups. RCSs revealed that when the Klotho concentration reached 824.09 pg/ml, the risk of OP decreased drastically.

CONCLUSION

Based on the analysis of the data collected from the NHANES database, we propose a correlation between Klotho and postmenopausal OP. A higher serum Klotho level is related to a lower incidence of OP. The findings of the present study can provide guidance for research on diagnosis and risk assessment of OP.

Development and Validation of a New Clinical Diagnostic Screening Model for Osteoporosis in Postmenopausal Women

BACKGROUND

Age and weight are not only strong predictive parameters for osteoporosis diagnosis but can also be easily acquired from patients. This study aimed to develop and validate a new diagnostic screening model for postmenopausal osteoporosis that uses only 2 parameters, viz., age and weight. The discriminative ability of the model was analyzed and compared with that of the osteoporosis self-assessment tool for Asians (OSTA) index.

METHODS

The age-weight diagnostic screening model was developed using a retrospective chart review of postmenopausal women aged ≥50 years who underwent dual energy X-ray absorptiometry at a tertiary hospital from November 2017 to April 2022. Logistic regression analysis was used to derive a diagnostic screening model for osteoporosis.

RESULTS

A total of 533 postmenopausal women were included in the study. According to the highest Youden index value, a probability cut-off value of 0.298 was used in the diagnosis screening model at any site, which yielded a sensitivity of 84.3% and a specificity of 53.8%. For increased sensitivity as a screening tool, a cut-off value of 0.254 was proposed to obtain a sensitivity of 90.2% and a specificity of 42.2%. The area under receiver operating characteristic curves from all screening models were significantly higher than those from the OSTA index model (p<0.05).

CONCLUSIONS

This study showed the feasibility of a postmenopausal osteoporosis diagnostic screening model that uses 2 strong predictors for osteoporosis diagnosis: age and weight. This age-weight diagnostic model is a simple, effective option in postmenopausal osteoporosis screening.

Ireland DXA-FRAX may differ significantly and substantially to Web-FRAX

Appropriate use of FRAX reduces the number of people requiring DXA scans, while contemporaneously determining those most at risk. We compared the results of FRAX with and without inclusion of BMD. It suggests clinicians to carefully consider the importance of BMD inclusion in fracture risk estimation or interpretation in individual patients.

PURPOSE

FRAX is a widely accepted tool to estimate the 10-year risk of hip and major osteoporotic fracture in adults. Prior calibration studies suggest this works similarly with or without the inclusion of bone mineral density (BMD). The purpose of the study is to compare within-subject differences between FRAX estimations derived using DXA and Web software with and without the inclusion of BMD.

METHOD

A convenience cohort was used for this cross-sectional study, consisting of 1254 men and women aged between 40 and 90 years who had a DXA scan and complete validated data available for analysis. FRAX 10-year estimations for hip and major osteoporotic fracture were calculated using DXA software (DXA-FRAX) and the Web tool (Web-FRAX), with and without BMD. Agreements between estimates within each individual subject were examined using Bland-Altman plots. We performed exploratory analyses of the characteristics of those with very discordant results.

RESULTS

Overall median DXA-FRAX and Web-FRAX 10-year hip and major osteoporotic fracture risk estimations which include BMD are very similar: 2.9% vs. 2.8% and 11.0% vs. 11% respectively. However, both are significantly lower than those obtained without BMD: 4.9% and 14% respectively, P < 0.001. Within-subject differences between hip fracture estimates with and without BMD were < 3% in 57% of cases, between 3 and 6% in 19% of cases, and > 6% in 24% of cases, while for major osteoporotic fractures such differences are < 10% in 82% of cases, between 10 and 20% in 15% of cases, and > 20% in 3% of cases.

CONCLUSIONS

Although there is excellent agreement between the Web-FRAX and DXA-FRAX tools when BMD is incorporated, sometimes there are very large differences for individuals between results obtained with and without BMD. Clinicians should carefully consider the importance of BMD inclusion in FRAX estimations when assessing individual patients.

Osteoporosis Screening Using Dental Panoramic Radiographs and Age at Menarche

Since early detection of osteoporosis is essential, the development of an efficient and cost-effective screening model would be incredibly beneficial. The aim of this study was to evaluate the diagnostic accuracy of MCW and MCI indices from dental panoramic radiographs in combination with a new variable, age at menarche, for the detection of osteoporosis. The study enrolled 150 Caucasian women (aged 45 to 86) who met the eligibility criteria, had DXA scans of the left hip and lumbar spine (L2 to L4), and were classified as osteoporotic, osteopenic, or normal based on T-score. Two observers evaluated MCW and MCI indexes on panoramic radiographs. There was a statistically significant correlation between the T-score and MCI and MCW. In addition, age at menarche had a statistically significant correlation with T-score (p = 0.006). In conclusion, in the current study, MCW proved to be more effective in detecting osteoporosis when combined with age at menarche. Individuals with MCW less than 3.0 mm and age at menarche later than 14 years old should be referred for DXA since they present high risk of osteoporosis.

Construction and validation of a risk prediction model for aromatase inhibitor-associated bone loss

Purpose

To establish a high-risk prediction model for aromatase inhibitor-associated bone loss (AIBL) in patients with hormone receptor-positive breast cancer.

Methods

The study included breast cancer patients who received aromatase inhibitor (AI) treatment. Univariate analysis was performed to identify risk factors associated with AIBL. The dataset was randomly divided into a training set (70%) and a test set (30%). The identified risk factors were used to construct a prediction model using the eXtreme gradient boosting (XGBoost) machine learning method. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression methods were used for comparison. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the model in the test dataset.

Results

A total of 113 subjects were included in the study. Duration of breast cancer, duration of aromatase inhibitor therapy, hip fracture index, major osteoporotic fracture index, prolactin (PRL), and osteocalcin (OC) were found to be independent risk factors for AIBL (p < 0.05). The XGBoost model had a higher AUC compared to the logistic model and LASSO model (0.761 vs. 0.716, 0.691).

Conclusion

The XGBoost model outperformed the logistic and LASSO models in predicting the occurrence of AIBL in patients with hormone receptor-positive breast cancer receiving aromatase inhibitors.

Measurement accuracy and reliability of self-reported versus measured weight and height among adults in Malaysia: Findings from a nationwide blood pressure screening programme

Most studies reporting prevalence of obesity use actual weight and height measurements. Self-reported weight and height have been used in epidemiological studies as they have been shown to be reliable, convenient, and inexpensive alternatives to actual measurements. However, the accuracy of self-reported weight and height might vary in different regions because of the difference in health awareness and social influences. This study aims to determine the accuracy and reliability of self-reported weight and height compared to actual measured weight and height among adults in Malaysia. This was a cross-sectional study conducted at the community level during blood pressure screening campaigns. Participants self-reported their weight and height in a questionnaire survey. Their weight and height were validated using measurements by researchers on the same setting. Body mass index (BMI) was defined as underweight (<18.5kg/m2), normal (18.5-22.9 kg/m2), overweight (23-27.4 kg/m2) and obesity (≥27.5 kg/m2). Bland-Altman analysis, intraclass correlation coefficients and weighted Kappa statistics were used to assess the degree of agreement between self-reported and measured weight and height. A total of 2781 participants were recruited in this study. The difference between the mean self-reported and measured weight and height were 0.4 kg and 0.4 cm respectively. Weighted Kappa statistics analysis showed that there was a substantial agreement between the BMI classifications derived from self-reported and actual measurement (ҡ = 0.920, p<0.001). There was no marked difference in the sensitivity and specificity of self-reported BMI among Malaysian adults by gender. We observed substantial agreement between self-reported and measured body weight and height within a sample of Malaysian adults. While self-reported body weight showed weaker agreement with actual measurements particularly for obese and overweight individuals, BMI values derived from self-reported weight and height were accurate for 88.53% of the participants. We thus conclude that self-reported height and weight measures may be useful for tracking and estimating population trends amongst Malaysian adults.

Risk of primary osteoporosis score (RPOPs): an algorithm model for primary osteoporosis risk assessment in grass-roots hospital

BACKGROUND

This study aimed to develop and validate a lasso regression algorithm model which was established by correlation factors of bone mineral density (BMD) and could be accurately predicted a high-risk population of primary osteoporosis (POP). It provides a rapid, economical and acceptable early screening method for osteoporosis in grass-roots hospitals.

METHODS

We collected 120 subjects from primary osteoporosis screening population in Zhejiang Quhua Hospital between May 2021 and November 2021 who were divided into three groups (normal, osteopenia and osteoporosis) according to the BMD T-score. The levels of three micro-RNAs in the plasma of these people were detected and assessed by qRT-PCR. At the same time, the levels of β-CTX and t-P1NP in serum of the three groups were determined. Based on the cluster random sampling method, 84 subjects (84/120, 70%) were selected as the training set and the rest were the test set. Lasso regression was used to screen characteristic variables and establish an algorithm model to evaluate the population at high risk of POP which was evaluated and tested in an independent test cohort. The feature variable screening process was used 10-fold cross validation to find the optimal lambda.

RESULTS

The osteoporosis risk score was established in the training set: Risk of primary osteoporosis score (RPOPs) = -0.1497785 + 2.52Age - 0.19miR21 + 0.35miR182 + 0.17β-CTx. The sensitivity, precision and accuracy of RPOPs in an independent test cohort were 79.17%, 82.61% and 75%, respectively. The AUC in the test set was 0.80. Some risk factors have a significant impact on the abnormal bone mass of the subjects. These risk factors were female (p = 0.00013), older than 55 (p < 2.2e-16) and BMI < 24 (p = 0.0091) who should pay more attention to their bone health.

CONCLUSION

In this study, we successfully constructed and validated an early screening model of osteoporosis that is able to recognize people at high risk for developing osteoporosis and remind them to take preventive measures. But it is necessary to conduct further external and prospective validation research in large sample size for RPOPs prediction models.

Decision Tree Modeling for Osteoporosis Screening in Postmenopausal Thai Women

Osteoporosis is still a serious public health issue in Thailand, particularly in postmenopausal women; meanwhile, new effective screening tools are required for rapid diagnosis. This study constructs and confirms an osteoporosis screening tool-based decision tree (DT) model. Four DT algorithms, namely, classification and regression tree; chi-squared automatic interaction detection (CHAID); quick, unbiased, efficient statistical tree; and C4.5, were implemented on 356 patients, of whom 266 were abnormal and 90 normal. The investigation revealed that the DT algorithms have insignificantly different performances regarding the accuracy, sensitivity, specificity, and area under the curve. Each algorithm possesses its characteristic performance. The optimal model is selected according to the performance of blind data testing and compared with traditional screening tools: Osteoporosis Self-Assessment for Asians and the Khon Kaen Osteoporosis Study. The Decision Tree for Postmenopausal Osteoporosis Screening (DTPOS) tool was developed from the best performance of CHAID’s algorithms. The age of 58 years and weight at a cutoff of 57.8 kg were the essential predictors of our tool. DTPOS provides a sensitivity of 92.3% and a positive predictive value of 82.8%, which might be used to rule in subjects at risk of osteopenia and osteoporosis in a community-based screening as it is simple to conduct.

Engagement in Primary Prevention Program among Rural Veterans With Osteoporosis Risk

A primary osteoporosis prevention program using a virtual bone health team (BHT) was implemented to comanage the care of rural veterans in the Mountain West region of the United States. The BHT identified, screened, and treated rural veterans at risk for osteoporosis using telephone and United States Postal Service communications. Eligibility was determined by regular use of Veterans Health Administration primary care, age 50 or older, and evidence of fracture risk. This study was conducted to identify demographic and clinical factors associated with the acceptance of osteoporosis screening and the initiation of medication where indicated. A cross-sectional cohort design (N = 6985) was utilized with a generalized estimating equation and logit link function to account for facility-level clustering. Fully saturated and reduced models were fitted using backward selection. Less than a quarter of eligible veterans enrolled in BHT's program and completed screening. Factors associated with a lower likelihood of clinic enrollment included being of older age, unmarried, greater distance from VHA services, having a copayment, prior fracture, or history of rheumatoid arthritis. A majority of veterans with treatment indication started medication therapy (N = 453). In this subpopulation, Fisher's exact test showed a significant association between osteoporosis treatment uptake and a history of two or more falls in the prior year, self-reported parental history of fracture, current smoking, and weight-bearing exercise. The BHT was designed to reduce barriers to screening; however, for this population cost and travel continue to limit engagement. The remarkable rate of medication initiation notwithstanding, low enrollment reduces the impact of this primary prevention program, and findings pertaining to fracture, smoking, and exercise imply that health beliefs are an important contributing factor. Efforts to identify and address barriers to osteoporosis screening and treatment, such as clinical factors, social determinants of health, and health beliefs, may pave the way for effective implementation of population bone health care delivery systems. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Interactions between central nervous system and peripheral metabolic organs

According to Descartes, minds and bodies are distinct kinds of "substance", and they cannot have causal interactions. However, in neuroscience, the two-way interaction between the brain and peripheral organs is an emerging field of research. Several lines of evidence highlight the importance of such interactions. For example, the peripheral metabolic systems are overwhelmingly regulated by the mind (brain), and anxiety and depression greatly affect the functioning of these systems. Also, psychological stress can cause a variety of physical symptoms, such as bone loss. Moreover, the gut microbiota appears to play a key role in neuropsychiatric and neurodegenerative diseases. Mechanistically, as the command center of the body, the brain can regulate our internal organs and glands through the autonomic nervous system and neuroendocrine system, although it is generally considered to be outside the realm of voluntary control. The autonomic nervous system itself can be further subdivided into the sympathetic and parasympathetic systems. The sympathetic division functions a bit like the accelerator pedal on a car, and the parasympathetic division functions as the brake. The high center of the autonomic nervous system and the neuroendocrine system is the hypothalamus, which contains several subnuclei that control several basic physiological functions, such as the digestion of food and regulation of body temperature. Also, numerous peripheral signals contribute to the regulation of brain functions. Gastrointestinal (GI) hormones, insulin, and leptin are transported into the brain, where they regulate innate behaviors such as feeding, and they are also involved in emotional and cognitive functions. The brain can recognize peripheral inflammatory cytokines and induce a transient syndrome called sick behavior (SB), characterized by fatigue, reduced physical and social activity, and cognitive impairment. In summary, knowledge of the biological basis of the interactions between the central nervous system and peripheral organs will promote the full understanding of how our body works and the rational treatment of disorders. Thus, we summarize current development in our understanding of five types of central-peripheral interactions, including neural control of adipose tissues, energy expenditure, bone metabolism, feeding involving the brain-gut axis and gut microbiota. These interactions are essential for maintaining vital bodily functions, which result in homeostasis, i.e., a natural balance in the body's systems.

Risk assessment tools for osteoporosis and fractures in 2022

Osteoporosis is one of the frequently encountered non-communicable diseases in the world today. Several hundred million people have osteoporosis, with many more at risk. The clinical feature is a fragility fracture (FF), which results in major reductions in the quality and quantity of life, coupled with a huge financial burden. In recognition of the growing importance, the World Health Organisation established a working group 30 years ago tasked with providing a comprehensive report to understand and assess the risk of osteoporosis in postmenopausal women. Dual-energy X-ray absorptiometry (DXA) is the most widely endorsed technology for assessing the risk of fracture or diagnosing osteoporosis before a fracture occurs, but others are available. In clinical practice, important distinctions are essential to optimise the use of risk assessments. Traditional tools lack specificity and were designed for populations to identify groups at higher risk using a 'one-size-fits-all' approach. Much has changed, though the purpose of risk assessment tools remains the same. In 2022, many tools are available to aid the identification of those most at risk, either likely to have osteoporosis or suffer the clinical consequence. Modern technology, enhanced imaging, proteomics, machine learning, artificial intelligence, and big data science will greatly advance a more personalised risk assessment into the future. Clinicians today need to understand not only which tool is most effective and efficient for use in their practice, but also which tool to use for which patient and for what purpose. A greater understanding of the process of risk assessment, deciding who should be screened, and how to assess fracture risk and prognosis in older men and women more comprehensively will greatly reduce the burden of osteoporosis for patients, society, and healthcare systems worldwide. In this paper, we review the current status of risk assessment, screening and best practice for osteoporosis, summarise areas of uncertainty, and make some suggestions for future developments, including a more personalised approach for individuals.

Is it time to consider population screening for fracture risk in postmenopausal women? A position paper from the International Osteoporosis Foundation Epidemiology/Quality of Life Working Group

The IOF Epidemiology and Quality of Life Working Group has reviewed the potential role of population screening for high hip fracture risk against well-established criteria. The report concludes that such an approach should strongly be considered in many health care systems to reduce the burden of hip fractures.

INTRODUCTION

The burden of long-term osteoporosis management falls on primary care in most healthcare systems. However, a wide and stable treatment gap exists in many such settings; most of which appears to be secondary to a lack of awareness of fracture risk. Screening is a public health measure for the purpose of identifying individuals who are likely to benefit from further investigations and/or treatment to reduce the risk of a disease or its complications. The purpose of this report was to review the evidence for a potential screening programme to identify postmenopausal women at increased risk of hip fracture.

METHODS

The approach took well-established criteria for the development of a screening program, adapted by the UK National Screening Committee, and sought the opinion of 20 members of the International Osteoporosis Foundation's Working Group on Epidemiology and Quality of Life as to whether each criterion was met (yes, partial or no). For each criterion, the evidence base was then reviewed and summarized.

RESULTS AND CONCLUSION

The report concludes that evidence supports the proposal that screening for high fracture risk in primary care should strongly be considered for incorporation into many health care systems to reduce the burden of fractures, particularly hip fractures. The key remaining hurdles to overcome are engagement with primary care healthcare professionals, and the implementation of systems that facilitate and maintain the screening program.

Utility of Osteoporosis Self-Assessment Tool as a Screening Tool for Osteoporosis in Irish Men and Women: Results of the DXA-HIP Project

Many algorithms have been developed and publicised over the past 2 decades for identifying those most likely to have osteoporosis or low BMD, or at increased risk of fragility fracture. The Osteoporosis Self-assessment Tool index (OSTi) is one of the oldest, simplest, and widely used for identifying men and women with low BMD or osteoporosis. OSTi has been validated in many cohorts worldwide but large studies with robust analyses evaluating this or other algorithms in adult populations residing in the Republic of Ireland are lacking, where waiting times for public DXA facilities are long. In this study we evaluated the validity of OSTi in men and women drawn from a sampling frame of more than 36,000 patients scanned at one of 3 centres in the West of Ireland. 18,670 men and women aged 40 years and older had a baseline scan of the lumbar spine femoral neck and total hip available for analysis. 15,964 (86%) were female, 5,343 (29%) had no major clinical risk factors other than age, while 5,093 (27%) had a prior fracture. Approximately 2/3 had a T-score ≤-1.0 at one or more skeletal sites and 1/3 had a T-score ≤-1.0 at all 3 skeletal sites, while 1 in 5 had a DXA T-score ≤-2.5 at one or more skeletal sites and 5% had a T-score ≤-2.5 at all 3 sites. OSTi generally performed well in our population with area under the curve (AUC) values ranging from 0.581 to 0.881 in men and 0.701 to 0.911 in women. The performance of OSTi appeared robust across multiple sub-group analyses. AUC values were greater for women, proximal femur sites, those without prior fractures and those not taking osteoporosis medication. Optimal OSTi cut-points were '2' for men and '0' for women in our study population. OSTi is a simple and effective tool to aid identification of Irish men and women with low BMD or osteoporosis. Use of OSTi could improve the effectiveness of DXA screening programmes for older adults in Ireland.

Validation and Optimization of Proximal Femurs Microstructure Analysis Using High Field and Ultra-High Field MRI

Trabecular bone could be assessed non-invasively using MRI. However, MRI does not yet provide resolutions lower than trabecular thickness and a comparative analysis between different MRI sequences at different field strengths and X-ray microtomography (μCT) is still missing. In this study, we compared bone microstructure parameters and bone mineral density (BMD) computed using various MRI approaches, i.e., turbo spin echo (TSE) and gradient recalled echo (GRE) images used at different magnetic fields, i.e., 7T and 3T. The corresponding parameters computed from μCT images and BMD derived from dual-energy X-ray absorptiometry (DXA) were used as the ground truth. The correlation between morphological parameters, BMD and fracture load assessed by mechanical compression tests was evaluated. Histomorphometric parameters showed a good agreement between 7T TSE and μCT, with 8% error for trabecular thickness with no significative statistical difference and a good intraclass correlation coefficient (ICC > 0.5) for all the extrapolated parameters. No correlation was found between DXA-BMD and all morphological parameters, except for trabecular interconnectivity (R2 > 0.69). Good correlation (p-value < 0.05) was found between failure load and trabecular interconnectivity (R2 > 0.79). These results suggest that MRI could be of interest for bone microstructure assessment. Moreover, the combination of morphological parameters and BMD could provide a more comprehensive view of bone quality.

[Menopause, menopause hormone therapy and osteoporosis. Postmenopausal women management: CNGOF and GEMVi clinical practice guidelines]

Postmenopausal osteoporosis is a frequent clinical condition, which affects nearly 1 in 3 women. Estrogen deficiency leads to rapid bone loss, which is maximal within the first years after the menopause transition and can be prevented by menopause hormone therapy (MHT). Assessment of the individual risk of osteoporosis is primarily based on the measurement of bone mineral density (BMD) at the spine and femur by DXA. Clinical risk factors (CRFs) for fractures taken either alone or in combination in the FRAX score were shown not to reliably predict fractures and/or osteoporosis (as defined by a T-score<-2.5) in early postmenopausal women. If DXA measurement is indicated in all women with CRFs for fractures, it can be proposed on a case-by-case basis, when knowledge of BMD is likely to condition the management of women at the beginning of menopause, particularly the benefit-risk balance of MHT. MHT prevents both bone loss and degradation of the bone microarchitecture in early menopause. It significantly reduces the risk of fracture at all bone sites by 20 to 40% regardless of basal level of risk with an estrogen-dependent dose-effect. Given the inter-individual variability in bone response, individual monitoring of the bone effect of MHT is warranted when prescribed for the prevention of osteoporosis. This monitoring is based on repeated measurement of lumbar and femoral BMD (on the same DXA measurement system) after 2years of MHT, the response criterion being no significant bone loss. Discontinuation of treatment is associated with a resumption of transient bone loss although there is a large variability in the rate of bone loss among women. Basically, there is a return to the level of fracture risk comparable to that of in untreated woman of the same age within 2 to 5years. Therefore, when MHT is prescribed for the prevention of osteoporosis in women with an increased risk at the beginning of menopause, measurement of BMD is recommended when MHT is stopped in order to consider further management of the risk of fracture whenever necessary (with possibly another anti-osteoporotic treatment).

Menopausal osteoporosis: screening, prevention and treatment

Screening for osteoporosis in women can be based on age and weight, using the Osteoporosis Screening Tool for Asians and assessment for other risk factors such as early menopause, Chinese ethnicity and other secondary factors. Based on the resulting risk profile, women can be triaged to dual-energy X-ray absorptiometry (DEXA) scanning for definite diagnosis of osteoporosis. Treatment should be considered in women with previous fragility fractures, DEXA-diagnosed osteoporosis and high risk of fracture. Exercise improves muscle function, can help prevent falls and has moderate effects on improvements in bone mass. Women should ensure adequate calcium intake and vitamin D. Menopausal hormone therapy (MHT) effectively prevents osteoporosis and fractures, and should be encouraged in those aged < 50 years. For women aged < 60 years, MHT or tibolone can be considered, especially if they have vasomotor or genitourinary symptoms. Risedronate or bisphosphonates may then be reserved for those aged over 60 years.

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

Background

The prevalence of osteoporosis is rising steadily as the aging population increases. Bone mineral density (BMD) assessment is a golden standard to establish the diagnosis of osteoporosis. However, the accessibility and radiation exposure limited its role in community screening. A more convenient approach for screening is suggested.

Methods

A total of 363 postmenopausal women over the age of 50 were included in this study and assessed with the body composition [including fat-free mass (FFM), fat mass (FM), and basal metabolic rate (BMR)] and BMD. Normal distributions and correlation coefficients among variables were calculated using the Shapiro-Wilk test and Pearson’s correlation analysis, respectively. A receiver operating characteristic (ROC) curve was plotted, and the area under ROC curves (AUC) was determined to obtain the optimal cutoff values of the body composition variables for osteoporosis prediction.

Results

The correlation coefficient of FFM, FM, FM ratio, and BMR with femur neck T-score was 0.373, 0.266, 0.165, and 0.369, respectively, while with spine T-score was 0.350, 0.251, 0.166, and 0.352, respectively (p < 0.01 for all). FFM, FM, and BMR showed an optimal cutoff value of 37.9 kg, 18.6 kg, and 1187.5 kcal, respectively, for detecting osteoporosis.

Conclusions

The present study provided a model to predict osteoporosis in postmenopausal women, and the optimal cutoff value of FFM, FM, and BMR could be calculated in the Asian population. Among these factors, BMR seemed a better predictor than others. The BMR could be a target for exercise intervention in postmenopausal women for maintaining or improving BMD.

Trial registration

ClinicalTrials.gov, NCT02936336. Retrospectively registered on13 October 2016.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-021-02351-3.

Survey of MRI Usefulness for the Clinical Assessment of Bone Microstructure

Bone microarchitecture has been shown to provide useful information regarding the evaluation of skeleton quality with an added value to areal bone mineral density, which can be used for the diagnosis of several bone diseases. Bone mineral density estimated from dual-energy X-ray absorptiometry (DXA) has shown to be a limited tool to identify patients' risk stratification and therapy delivery. Magnetic resonance imaging (MRI) has been proposed as another technique to assess bone quality and fracture risk by evaluating the bone structure and microarchitecture. To date, MRI is the only completely non-invasive and non-ionizing imaging modality that can assess both cortical and trabecular bone in vivo. In this review article, we reported a survey regarding the clinically relevant information MRI could provide for the assessment of the inner trabecular morphology of different bone segments. The last section will be devoted to the upcoming MRI applications (MR spectroscopy and chemical shift encoding MRI, solid state MRI and quantitative susceptibility mapping), which could provide additional biomarkers for the assessment of bone microarchitecture.

Delivering fracture prevention services to rural US veterans through telemedicine: a process evaluation

An informatics-driven population bone health clinic was implemented to identify, screen, and treat rural US Veterans at risk for osteoporosis. We report the results of our implementation process evaluation which demonstrated BHT to be a feasible telehealth model for delivering preventative osteoporosis services in this setting.

PURPOSE

An established and growing quality gap in osteoporosis evaluation and treatment of at-risk patients has yet to be met with corresponding clinical care models addressing osteoporosis primary prevention. The rural bone health tea m (BHT) was implemented to identify, screen, and treat rural Veterans lacking evidence of bone health care and we conducted a process evaluation to understand BHT implementation feasibility.

METHODS

For this evaluation, we defined the primary outcome as the number of Veterans evaluated with DXA and a secondary outcome as the number of Veterans who initiated prescription therapy to reduce fracture risk. Outcomes were measured over a 15-month period and analyzed descriptively. Qualitative data to understand successful implementation were collected concurrently by conducting interviews with clinical personnel interacting with BHT and BHT staff and observations of BHT implementation processes at three site visits using the Promoting Action on Research Implementation in Health Services (PARIHS) framework.

RESULTS

Of 4500 at-risk, rural Veterans offered osteoporosis screening, 1081 (24%) completed screening, and of these, 37% had normal bone density, 48% osteopenia, and 15% osteoporosis. Among Veterans with pharmacotherapy indications, 90% initiated therapy. Qualitative analyses identified barriers of rural geography, rural population characteristics, and the infrastructural resource requirement. Data infrastructure, evidence base for care delivery, stakeholder buy-in, formal and informal facilitator engagement, and focus on teamwork were identified as facilitators of implementation success.

CONCLUSION

The BHT is a feasible population telehealth model for delivering preventative osteoporosis care to rural Veterans.

Ex vivo vibro-acoustography characterization of osteoporosis in an experimental mice model

Background

Osteoporosis is a highly prevalent multifactorial osteometabolic disease, classically diagnosed, in vivo, by dual energy X-ray absorptiometry (DXA). This study evaluated osteoporosis, ex vivo, using vibro-acoustography (VA), an elastographic technique based on ultrasound radiation force.

Methods

Three groups of mice femurs were used: (I) control group (CG), (II) osteoporosis group (OG) and (III) treated osteoporosis group (TOG), in which the animals received pamidronate, an antiresorptive drug. Evaluation was performed in an acoustic tank, using two high frequency focused beams produced by a confocal ultrasonic transducer. A hydrophone registered the low frequency acoustic response (AR) of bone samples. We used micro-computed tomography (microCT) as the reference standard and evaluated the correlation between VA and microCT parameters.

Results

The spectral analyses of the ARs with estimated area under the curve (AUC) values (mean; st. dev.) were, respectively, 1.29e^-07 and 9.32e^-08 for the CG, 3.25e^-08 and 2.16e^-08 for the OG, and 1.50e^-07 and 8.37e^-08 for the TOG. VA differentiated the experimental groups (P<0.01) and the results were reproducible [interclass correlation coefficient (ICC): 0.43 (95% CI: 0.15-0.71)]. There was also a statistically significant association between VA and microCT connectivity (Conn.) (r=0.80; P<0.01) and connectivity density (Conn. D) (r=0.76; P<0.01).

Conclusions

These results encourage further studies aimed at evaluating the potential use of VA for the diagnosis of osteoporosis as a relatively low-cost and radiation-free alternative to DXA.

Comparison of OSTA, FRAX and BMI for Predicting Postmenopausal Osteoporosis in a Han Population in Beijing: A Cross Sectional Study

Purpose

To validate the efficacies of three screening tools including the Osteoporosis Self-Assessment Tool for Asians (OSTA), Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD), and body mass index (BMI) for predicting postmenopausal osteoporosis (OP) and to define the ideal thresholds for avoidance of dual-energy X-ray absorptiometry (DXA) scanning in a Han Chinese population in Beijing.

Patients and Methods

A total of 2055 community-dwelling Han Beijing postmenopausal females aged ≥45 years were enrolled in this study. All participants completed a questionnaire, and BMD was measured by DXA. OP was defined by a T-score at least -2.5 SD less than that of average young adults in different diagnostic criteria [lumbar spine, femoral neck, total hip, worst hip, WHO]. The abilities of the OSTA, FRAX, and BMI to predict OP were analyzed by receiver operating characteristic (ROC) curves. Sensitivity, specificity, and area under the ROC curves (AUC) were calculated. Ideal thresholds for identifying OP were proposed.

Results

The prevalence of OP ranged from 8.1% to 28.4% according to different diagnostic criteria. The AUC range for the OSTA (0.758-0.849) was similar to the FRAX (0.728-0.855), which revealed that both tools predicted OP reliably. The AUC range for BMI was 0.643-0.682, suggesting limited predictive value. According to WHO criteria, the AUC values for the FRAX for hip fracture risk (FRAX-HF) and for the OSTA were 0.796 and 0.798, with corresponding sensitivities of 74.79% and 69.64% and specificities of 70.45% and 75.07%, respectively. At defined thresholds, the FRAX-HF and OSTA allowed avoidance of DXA in 42.4-37.6% of participants, at a cost of missing only 7.2-8.6% of individuals with OP.

Conclusion

The OSTA and FRAX-HF may be reliable and effective tools for identifying postmenopausal OP in the Han Beijing population without BMD.

Development of a model for identification of individuals with high risk of osteoporosis

Many developing countries, including Vietnam, lack DXA resources for the diagnosis of osteoporosis, which poses difficulties in the treatment and prevention of osteoporosis at the individual level. We have developed and validated a prediction model for individualized assessment of osteoporosis based on age and body weight for men and women.

PURPOSE

To estimate the prevalence of osteoporosis and to develop and validate a prediction model for estimating the absolute risk of osteoporosis in the Vietnamese population.

METHODS

The study involved 1477 women and 669 men aged 50 years and older, who were recruited from the general population in Ho Chi Minh City (Vietnam). Bone mineral density (BMD) at the femoral neck, total hip, and lumbar spine was measured by DXA (Hologic Horizon). The diagnosis of osteoporosis was based on BMD T-score (T-score ≤ - 2.5) at the femoral neck or lumbar spine which was derived from a published reference range for the Vietnamese population. The logistic regression model was used to develop the prediction model for men and women separately. The bootstrap method was used to evaluate the model performance using 3 indices: the area under the receiver's operating characteristic curve (AUC), Brier score, and R-squared values.

RESULTS

The prevalence of osteoporosis at any site was 28.3% in women and 15.5% in men. The best predictors of osteoporosis risk were age and body weight. Using these indices, a cut-off of 0.195 for women yielded an AUC of 0.825, Brier score = 0.112, and it explained 33.8% of total variance in risk of osteoporosis between individuals. Similarly, in men, the internal validation with a cut-off of 0.09 yielded good accuracy, with AUC = 0.858, Brier score = 0.040, and R-squared = 30.3%.

CONCLUSION

We have developed and validated a prediction model for individualized assessment of osteoporosis. In settings without DXA, this model can serve as a useful screening tool to identify high-risk individuals for DXA scan.

The Belgian Bone Club 2020 guidelines for the management of osteoporosis in postmenopausal women

PURPOSE

To provide updated evidence-based guidelines for the management of osteoporosis in postmenopausal women in Belgium.

METHODS

The Belgian Bone Club (BBC) gathered a guideline developer group. Nine "Population, Intervention, Comparator, Outcome" (PICO) questions covering screening, diagnosis, non-pharmacological and pharmacological treatments, and monitoring were formulated. A systematic search of MEDLINE, the Cochrane Database of Systematic Reviews, and Scopus was performed to find network meta-analyses, meta-analyses, systematic reviews, guidelines, and recommendations from scientific societies published in the last 10 years. Manual searches were also performed. Summaries of evidence were provided, and recommendations were further validated by the BBC board members and other national scientific societies' experts.

RESULTS

Of the 3840 references in the search, 333 full texts were assessed for eligibility, and 129 met the inclusion criteria. Osteoporosis screening using clinical risk factors should be considered. Patients with a recent (<2 years) major osteoporotic fracture were considered at very high and imminent risk of future fracture. The combination of bone mineral density measured by dual-energy X-ray absorptiometry and 10-year fracture risk was used to categorize patients as low or high risk. Patient education, the combination of weight-bearing and resistance training, and optimal calcium intake and vitamin D status were recommended. Antiresorptive and anabolic osteoporosis treatment should be considered for patients at high and very high fracture risk, respectively. Follow-up should focus on compliance, and patient-tailored monitoring should be considered.

CONCLUSION

BBC guidelines and 25 guideline recommendations bridge the gap between research and clinical practice for the screening, diagnosis, and management of osteoporosis.

Use of age-dependent FRAX-based intervention thresholds for Singapore

Assessment and treatment pathways based on age-specific intervention thresholds in Singapore using FRAX paths can be used to identify patients at high risk of fracture and avoid unnecessary treatment in those at low risk.

PURPOSE

Intervention thresholds for the treatment of osteoporosis have been based historically on the measurement of bone mineral density. The development of FRAX® has permitted a more accurate assessment of fracture risk. The aim of the present study was to explore treatment paths and characteristics of women selected for treatment in Singapore based on FRAX.

METHODS

The approach to the setting of intervention and assessment thresholds used the methodology adopted by the National Osteoporosis Guideline Group for FRAX-based guidelines in the UK but based on the epidemiology of fracture and death in Singapore. The methodology was applied to women age 50 years or more drawn from the population-based Singapore Chinese Health Study (SCHS) cohort. Missing data for the calculation of FRAX was simulated using data from Chinese cohorts from Hong Kong.

RESULTS

Intervention thresholds expressed as a 10-year probability of a major osteoporotic fracture ranged from 2.9% at the age of 50 years increasing to 32% at the age of 90 years. A total of 1927 of 29,323 women (7%) had a prior fragility fracture and would be eligible for treatment for this reason. An additional 3019 women (10.3%) would be eligible for treatment on the basis of age-dependent thresholds. The mean BMD T-score of women so selected was -2.94.

CONCLUSION

Probability-based assessment of fracture risk using age-specific intervention thresholds was developed for Singapore to help guide decisions about treatment.

A brief history of FRAX

This paper reviews the research programme that went into the development of FRAX® and its impact in the 10 years since its release in 2008.

INTRODUCTION

Osteoporosis is defined on the measurement of bone mineral density though the clinical consequence is fracture. The sensitivity of bone mineral density measurements for fracture prediction is low, leading to the development of FRAX to better calculate the likelihood of fracture and target anti-osteoporosis treatments.

METHODS

The method used in this paper is literature review.

RESULTS

FRAX, developed over an 8-year period, was launched in 2008. Since the launch of FRAX, models have been made available for 64 countries and in 31 languages covering more than 80% of the world population.

CONCLUSION

FRAX provides an advance in fracture risk assessment and a reference technology platform for future improvements in performance characteristics.

Brain to bone: What is the contribution of the brain to skeletal homeostasis?

The brain, which governs most, if not all, physiological functions in the body, from the complexities of cognition, learning and memory, to the regulation of basal body temperature, heart rate and breathing, has long been known to affect skeletal health. In particular, the hypothalamus - located at the base of the brain in close proximity to the medial eminence, where the blood-brain-barrier is not as tight as in other regions of the brain but rather "leaky", due to fenestrated capillaries - is exposed to a variety of circulating body cues, such as nutrients (glucose, fatty acids, amino acids), and hormones (insulin, glucagon, leptin, adiponectin) [1-3].Information collected from the body via these peripheral cues is integrated by hypothalamic sensing neurons and glial cells [4-7], which express receptors for these nutrients and hormones, transforming these cues into physiological outputs. Interestingly, many of the same molecules, including leptin, adiponectin and insulin, regulate both energy and skeletal homeostasis. Moreover, they act on a common set of hypothalamic nuclei and their residing neurons, activating endocrine and neuronal systems, which ultimately fine-tune the body to new physiological states. This review will focus exclusively on the brain-to-bone pathway, highlighting the most important anatomical sites within the brain, which are known to affect bone, but not covering the input pathways and molecules informing the brain of the energy and bone metabolic status, covered elsewhere [8-10]. The discussion in each section will present side by side the metabolic and bone-related functions of hypothalamic nuclei, in an attempt to answer some of the long-standing questions of whether energy is affected by bone remodeling and homeostasis and vice versa.

Bacteria, Bones, and Stones: Managing Complications of Short Bowel Syndrome

Short bowel syndrome (SBS) occurs in patients who have had extensive resection. The primary physiologic consequence is malabsorption, resulting in fluid and electrolyte abnormalities and malnutrition. Nutrient digestion, absorption, and assimilation may also be diminished by disturbances in the production of bile acids and digestive enzymes. Small bowel dilation, dysmotility, loss of ileocecal valve, and anatomical changes combined with acid suppression and antimotility drugs increase the risk of small intestinal bacterial overgrowth, further contributing to malabsorption. Metabolic changes that occur in SBS due to loss of colonic regulation of gastric and small bowel function can also lead to depletion of calcium, magnesium, and vitamin D, resulting in demineralization of bone and the eventual development of bone disease. Persistent inflammation, steroid use, parenteral nutrition, chronic metabolic acidosis, and renal insufficiency may exacerbate the problem and contribute to the development of osteoporosis. Multiple factors increase the risk of nephrolithiasis in SBS. In the setting of fat malabsorption, increased free fatty acids are available to bind to calcium, resulting in an increased concentration of unbound oxalate, which is readily absorbed across the colonic mucosa where it travels to the kidney. In addition, there is an increase in colonic permeability to oxalate stemming from the effects of unabsorbed bile salts. The risk of nephrolithiasis is compounded by volume depletion, metabolic acidosis, and hypomagnesemia, resulting in a decrease in renal perfusion, urine output, pH, and citrate excretion. This review examines the causes and treatments of small intestinal bacterial overgrowth, bone demineralization, and nephrolithiasis in SBS.

Complex interventions can increase osteoporosis investigations and treatment: a systematic review and meta-analysis

Osteoporosis is affecting over 200 million people worldwide. Despite available guidelines, care for these patients remains sub-optimal. We developed an osteoporosis tool to address the multiple dimensions of chronic disease management. Findings from its evaluation showed a significant increase from baseline in osteoporosis investigations and treatment, so we are revising this tool to include multiple chronic conditions including an update of evidence about osteoporosis. Our objectives were to conduct a systematic review of osteoporosis interventions in adults at risk for osteoporosis. We searched bibliometric databases for randomized controlled trials (RCTs) in any language evaluating osteoporosis disease management interventions in adults at risk for osteoporosis. Reviewer pairs independently screened citations and full-text articles, extracted data, and assessed risk of bias. Analysis included random effects meta-analysis. Primary outcomes were osteoporosis investigations and treatment, and fragility fractures. Fifty-five RCTs and one companion report were included in the analysis representing 165,703 patients. Our findings from 55 RCTs and 18 sub-group meta-analyses showed that complex implementation interventions with multiple components consisting of at least education + feedback + follow-up significantly increased the initiation of osteoporosis medications, and interventions with at least education + follow-up significantly increased the initiation of osteoporosis investigations. No significant impact was found for any type of intervention to reduce fracture. Complex interventions that include at least education + follow-up or feedback have the most potential for increasing osteoporosis investigations and treatment. Patient education appears to be an important component in osteoporosis disease management.

Performance of risk assessment tools for predicting osteoporosis in south Indian rural elderly men

Osteoporosis in elderly men is an under-recognized problem. In the current study, we intend to look at the performance of two risk assessment tools [OSTA and MORES] for the diagnosis of osteoporosis. Osteoporosis was seen in 1/4th of elderly men at spine and 1/6th of them at femoral neck. Both risk assessment tools were found to have good sensitivity in predicting osteoporosis at spine and femoral neck with good area under curve (AUC).

PURPOSE

This study attempts to look at the performance of osteoporosis self-assessment tool for Asians (OSTA) and male osteoporosis risk estimation score (MORES) for predicting osteoporosis in south Indian rural elderly men.

METHODS

Five hundred and twelve men above 65 years of age from a south Indian rural community were recruited by cluster random sampling. All subjects underwent detailed clinical, anthropometric, and bone mineral density measurement at lumbar spine and femoral neck using dual-energy X-ray absorptiometry scan. A T score ≤ - 2.5 was diagnostic of osteoporosis. Scores for OSTA and MORES were calculated at various cut offs, and their sensitivities and specificities for predicting osteoporosis were derived.

RESULTS

The prevalence of osteoporosis was found to be 16% at femoral neck and 23% at spine. OSTA with a cut-off value of ≤2 predicted osteoporosis with a sensitivity and specificity at lumbar spine of 94 and 17% and at femoral neck of 99 and 18%. The area under ROC curve for OSTA index for spine was 0.716 and for femoral neck was 0.778. MORES with a cut-off value of ≥6 predicted osteoporosis at spine with a sensitivity of 98% and specificity of 15%, and at femoral neck, they were 98 and 13%, respectively. The area under ROC curve for MORES for spine was 0.855 and for femoral neck was 0.760.

CONCLUSION

OSTA and MORES were found to be useful screening tools for predicting osteoporosis in Indian elderly men. These tools are simple, easy to perform, and cost effective in the context of rural Indian setting.

A comparison of electronic and manual fracture risk assessment tools in screening elderly male US veterans at risk for osteoporosis

This study compares four screening tools in their ability to predict osteoporosis. We found that there was no significant difference between the tools. These results provide support for the use of automated screening tools which work in conjunction with the electronic medical record and help improve screening rates for osteoporosis.

INTRODUCTION

The purpose of this study is to compare the performance of four fracture risk assessment tools (FRATs) in identifying osteoporosis by bone mineral density (BMD) T-score: Veterans Affairs Fracture Absolute Risk Assessment Tool (VA-FARA), World Health Organization's Fracture Risk Assessment Tool (FRAX), electronic FRAX (e-FRAX), and Osteoporosis Self-Assessment Screening Tool (OST).

METHODS

We performed a cross-sectional analysis of all patients enrolled in the VA Salt Lake City bone health team (BHT) who had completed a DXA scan between February 1, 2012, and February 1, 2013. DXA scan results were obtained by chart abstraction. For calculation of FRAX, osteoporosis risk factors were obtained from a screening questionnaire completed prior to DXA. For VA-FARA and e-FRAX, risk factors were derived from the electronic medical record (EMR). Clinical risk scores were calculated and compared against the gold standard of DXA-based osteoporosis. Sensitivity, specificity, and predictive values were calculated. Receiver operator characteristic (ROC) curves were plotted, and areas under the curve (AUC) were compared.

RESULTS

A cohort of 463 patients met eligibility criteria (mean age 80.4 years). One hundred twelve patients (24%) had osteoporosis as defined by DXA T-score ≤-2.5. Sensitivity, specificity, and predictive values were calculated. ROC statistics were compared and did not reach statistical significance difference between FRATs in identifying DXA-based osteoporosis.

CONCLUSIONS

Our study suggests that all FRATs tested perform similarly in identifying osteoporosis among elderly, primarily Caucasian, male veterans. If these electronic screening methods perform similarly for fracture outcomes, they could replace manual FRAX and thus improve efficiency in identifying individuals who should be sent for DXA scan.

Screening for Osteoporosis in Older Men: Operating Characteristics of Proposed Strategies for Selecting Men for BMD Testing

BACKGROUND

The optimal approach for selecting men for bone mineral density (BMD) testing to screen for osteoporosis is uncertain.

OBJECTIVE

To compare strategies for selecting older men for screening BMD testing.

DESIGN

Prospective cohort study.

PARTICIPANTS

A total of 4043 community-dwelling men aged ≥70 years at four US sites.

MAIN MEASURES

BMD at the total hip, femoral neck, and lumbar spine using dual-energy x-ray absorptiometry (DXA). Sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, and area under the receiver operating curve (AUC) of the Osteoporosis Self-Assessment Tool (OST) and Fracture Risk Assessment Tool (FRAX) without BMD to discriminate between those with and without osteoporosis as defined by World Health Organization (WHO) diagnostic criteria, and between those recommended and not recommended for pharmacologic therapy based on the National Osteoporosis Foundation (NOF) guidelines.

KEY RESULTS

Among the cohort, 216 (5.3%) had a BMD T-score ≤ -2.5 at the femoral neck, total hip, or lumbar spine, and 1184 (29.2%) met criteria for consideration of pharmacologic therapy according to NOF guidelines. The OST had better discrimination (AUC 0.68) than the FRAX (AUC 0.62; p = 0.004) for identifying T-score-defined osteoporosis. Use of an OST threshold of <2 resulted in sensitivity of 0.83 and specificity of 0.36 for the identification of osteoporosis, compared to sensitivity of 0.59 and specificity of 0.59 for the use of FRAX with a cutoff of 9.3% 10-year risk of major osteoporotic fracture.

CONCLUSIONS

The OST performs modestly better than the more complex FRAX in selecting older men for BMD testing to screen for osteoporosis; the use of either tool substantially reduces the proportion of men referred for BMD testing compared to universal screening. Of 1000 men aged 70 and older in this community-based cohort, the use of an OST cutoff of <2 to select men for BMD testing would result in 654 men referred for BMD testing, of whom 44 would be identified as having osteoporosis, and nine with osteoporosis would be missed.

Comparison of fracture risk assessment tools in older men without prior hip or spine fracture: the MrOS study

Femoral neck bone mineral density (BMD), age plus femoral neck BMD T score, and three externally generated fracture risk tools had similar accuracy to identify older men who developed osteoporotic fractures. Risk tools with femoral neck BMD performed better than those without BMD. The externally developed risk tools were poorly calibrated.

INTRODUCTION

We compared the performance of fracture risk assessment tools in older men, accounting for competing risks including mortality.

METHODS

A comparative ROC curve analysis assessed the ability of the QFracture, FRAX® and Garvan fracture risk tools, and femoral neck bone mineral density (BMD) T score with or without age to identify incident fracture in community-dwelling men aged 65 years or older (N = 4994) without hip or clinical vertebral fracture or antifracture treatment at baseline.

RESULTS

Among risk tools calculated with BMD, the discriminative ability to identify men with incident hip fracture was similar for FRAX (AUC 0.77, 95% CI 0.73, 0.81), the Garvan tool (AUC 0.78, 95% CI 0.74, 0.82), age plus femoral neck BMD T score (AUC 0.79, 95% CI 0.75, 0.83), and femoral neck BMD T score alone (AUC 0.76, 95% CI 0.72, 0.81). Among risk tools calculated without BMD, the discriminative ability to identify hip fracture was similar for QFracture (AUC 0.69, 95% CI 0.66, 0.73), FRAX (AUC 0.70, 95% CI 0.66, 0.73), and the Garvan tool (AUC 0.71, 95% CI 0.67, 0.74). Correlated ROC curve analyses revealed better diagnostic accuracy for risk scores calculated with BMD compared with QFracture (P < 0.0001). Calibration was good for the internally generated BMD T score predictor with or without age and poor for the externally developed risk tools.

CONCLUSION

In untreated older men without fragility fractures at baseline, an age plus femoral neck BMD T score classifier identified men with incident hip fracture as accurately as more complicated fracture risk scores.

Chronic joint pain and handgrip strength correlates with osteoporosis in mid-life women: a Singaporean cohort

This study aimed to identify novel correlates which may relate to low bone mass at lumbar spine in mid-life Asian women. The possibility of developing a prediction model for osteoporosis (OP) was explored which resulted in a risk assessment tool that performed better than currently available tools.

INTRODUCTION

In order to identify novel correlates associated with low spinal bone mineral density (BMD) in mid-life women, we examined a large number of lifestyle and medical and performance measurements and developed a prediction model for triage to BMD scanning.

METHODS

Women (n = 512) aged 45-69 years (mean 57.0 ± 6.3) attending gynecology clinics for "well woman" visits were recruited for this cross-sectional study from 2014 to 2015. We assessed symptoms, medical history, anthropometry, and physical performance. Stepwise multinomial logistic regressions were performed to examine significant associated covariates for pre-specified outcomes (normal [T-score ≥ -1.0], low bone mass [T-score between -1 and -2.5], and OP [T-score ≤ -2.5] at the lumbar spine). A new screening model was developed, and its performance was compared with the OP Screening Tool for Asians (OSTA) and Fracture Risk Assessment Tool (FRAX®).

RESULTS

Spinal OP was found in 6.8%. Multivariate analysis indicated that chronic joint pain, the most common symptom reported by 37.5% of the women, was significantly associated with OP. Only age (Relative Risk Ratio [RRR] 1.63; 95%CI, 1.03-2.60), weight (RRR 0.14; 95% CI, 0.07-0.27), postmenopausal status (RRR 11.59, 95%CI, 1.15-116.73), chronic joint pain (RRR, 4.12; 95% CI, 1.53-11.07), and right handgrip strength (RRR 0.50; 95% CI, 0.31-0.80) were independently associated with spinal OP. Combining these five variables, our final model's area under curve (AUC) was significantly higher at 84% than both the OSTA [AUC; 79% (p value < 0.0231 'c' statistics)] and FRAX® [AUC 58% (p value < 0.0001 'c' statistic)].

CONCLUSION

A novel screening tool that combines age, weight, and menopausal status with chronic joint pain and right handgrip strength more reliably predicts spinal OP in mid-life Singaporean women.

Effectiveness of Osteoporosis Self-Assessment Tool for Asians in Screening for Osteoporosis in Healthy Males Over 40 Years Old in China

In this study, we evaluated the effectiveness of the Osteoporosis Self-assessment Tool for Asians (OSTA) in screening for osteoporosis in the elderly male population in the Chengdu area, China. The Lunar Prodigy Advance bone densitometer was used to measure the bone mineral density of 11,039 healthy males over the age of 40 years. Men with OSTA scores of >-1, -4 < OSTA ≤ -1, or ≤-4 were assigned to the low-risk, moderate-risk, or high-risk group, respectively. The T-scores measured with dual-energy X-ray absorptiometry at the different sites were compared across the groups. The bone mineral density of the lumbar spines L1-L4, the left femur, and other sites decreased gradually with age. With increasing age, the screening sensitivity of OSTA for osteoporosis in the lumbar spine and femur gradually increased, whereas its specificity decreased. The areas under the receiver operating characteristic curves for the OSTA index in different age groups and at different sites were 0.644-0.831. Therefore, the OSTA index demonstrated some value in screening for osteoporosis in men over the age of 50 years. Significant differences in its effectiveness were observed among different age groups.

Validity of Knee-Estimated Height to Assess Standing Height in Older Adults: A Secondary Longitudinal Analysis of the Mexican Health and Aging Study

OBJECTIVE

The main objective was to test the validity of height estimated by knee height in Mexican older adults, as a surrogate for standing height.

DESIGN

Cohort study.

SETTING

Data were drawn from the first and third waves of the Mexican Health and Aging Study.

PARTICIPANTS

Included participants were community-dwelling 50-year or older adults with measured height at baseline and in follow-up. Subjects with a lower limb fracture in the follow-up were excluded.

MEASUREMENTS

Main measurements were baseline standing height and 11-year follow-up and knee-estimated height in follow-up. Population specific equations were used to estimate standing height from knee height. Comparisons between baseline standing height and knee-derived height were done with simple correlations, limits of agreement (Bland-Altman plot) and Deming regressions.

RESULTS

A total of 136 50-year or older adults were followed-up for eleven years, with a mean age of 60. There was a positive correlation between knee-estimated height and baseline standing height of 0.895 (p<0.001) for men and of 0.845 (p<0.001) for women. Limits of agreement for men were from -6.95cm to 7.09cm and for women from -6.58cm to 8.44cm.

CONCLUSION

According to our results, knee-estimated height could be used interchangeably with standing height in Mexican older adults, and these results might apply also to other populations.