The positive association of lignan and flavonoid intakes with bone mineral density (BMD) in men from Southern China

OBJECTIVE(S): There have been promising data showing that phytoestrogens may prevent bone loss in postmenopausal women. However there has been little data on the skeletal effect of specific phytoestrogens among young men and premenopausal women. The purpose of this study was to examine the relationship between phytoestrogens intake (isoflavones, coumestrol, flavonoids and lignans) and BMD at femoral neck and spine in a cohort of Southern Chinese young men and wompostprin

Association of handgrip strength with chronic diseases and multimorbidity - A cross-sectional study

The prevalence of chronic diseases has risen along with increased longevity. Co-occurrence of two or more chronic diseases in an individual (multimorbidity) is prevalent and poses a huge burden to individuals and the society. However, determinants of multimorbidity are largely unknown. Handgrip strength is a general indicator of muscle strength and linked with premature mortality. However, its role in multimorbidity has never been evaluated. To investigate the relationships between handgrip strength and multiple chronic diseases and multimorbidity, and to assess the usefulness of age and handgrip as a marker of chronic diseases and multimorbidity in a community dwelling sample of men and women, we analyzed a cross-sectional cohort with 1,145 subjects (748 men and 397 women) aged 50 years and older living in Hong Kong. Low handgrip strength was significantly associated with increased odds of having five and three chronic diseases in men and women, respectively, after controlling for age, body mass index, history of smoking, educational level, marital level and comorbidity. Multivariable-adjusted handgrip strength was significantly decreased with the number of chronic diseases in men (trend, P = 0.001), but the trend in women was marginal (trend, P = 0.06). Conversely, multivariable-adjusted age was significantly increased with the number of chronic diseases in women (trend, P = 0.033), but not in men (trend, P = 0.118). In conclusion, handgrip strength is associated with multiple chronic diseases and multimorbidity in men and women after adjustment of confounding factors. It shows a linear trend of association with the number of chronic diseases in men, but not in women. Since handgrip strength is a biomarker of multiple physiological systems, its augmentation may be a feasible strategy to improve general health and decrease likelihood of having multiple chronic diseases and hence, premature mortality. © 2012 The Author(s).published_or_final_versionSpringer Open Choice, 25 May 201

Low handgrip strength is a predictor of osteoporotic fractures: Cross-sectional and prospective evidence from the Hong Kong Osteoporosis Study

Handgrip strength (HGS) is a potentially useful objective parameter to predict fracture since it is an indicator of general muscle strength and is associated with fragility and propensity to fall. Our objective was to examine the association of HGS with fracture, to evaluate the accuracy of HGS in predicting incident fracture, and to identify subjects at risk of fracture. We analyzed a cross-sectional cohort with 2,793 subjects (1,217 men and 1,576 women aged 50-101 years) and a subset of 1,702 subjects which were followed for a total of 4,855 person-years. The primary outcome measures were prevalent fractures and incident major fragility fractures. Each standard deviation (SD) reduction in HGS was associated with a 1.24-fold increased odds for major clinical fractures even after adjustment for other clinical factors. A similar result was obtained in the prospective cohort with each SD reduction in HGS being associated with a 1.57-fold increased hazard ratio of fracture even after adjustment for clinical factors. A combination of HGS and femoral neck bone mineral density (FN BMD) T-score values (combined T-score), together with other clinical factors, had a better predictive power of incident fractures than FN BMD or HGS T-score alone with clinical factors. In addition, combined T-score has better sensitivity and specificity in predicting incidence fractures than FN BMD alone. This study is the first study to compare the predictive ability of HGS and BMD. We showed that HGS is an independent risk factor for major clinical fractures. Compared with using FN BMD T-score of -2.5 alone, HGS alone has a comparable predictive power to BMD, and the combined T-score may be useful to identify extra subjects at risk of clinical fractures with improved specificity. © The Author(s) 2011.published_or_final_versionSpringer Open Choice, 21 Feb 201

Replication study of genetic loci influencing age at menopause in Southern Chinese women

Session - Ovarian AgeingThis journal issue contain Abstracts: 10th EMAS Congress 2015INTRODUCTION: Age at menopause is a highly heritable trait. Previous genome-wide meta-analysis in European and Northern Chinese identified 26 loci underlying age at menopause. OBJECTIVES: To validate these 26 genetic loci in Southern Chinese women. AIMS: To study genetic factors which may influence age at menopause in Southern Chinese. METHODS: This study was performed on 653 women who participated in the Hong Kong Osteoporosis Study, whose age at menopause was available. These women consented to have blood taken and archived for genotyping. DNA was extracted from the buffy coat, and genotyping was performed using Sequenom iPLEX. Age at menopause ...postprin

A woman with raised alkaline phosphatase and forearm deformity

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Optimal vitamin D status and its relationship with bone and mineral metabolism in Hong Kong Chinese

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Development and validation of sex-specific hip fracture prediction models using electronic health records: a retrospective, population-based cohort study

Background: Hip fracture is associated with immobility, morbidity, mortality, and high medical cost. Due to limited availability of dual-energy X-ray absorptiometry (DXA), hip fracture prediction models without using bone mineral density (BMD) data are essential. We aimed to develop and validate 10-year sex-specific hip fracture prediction models using electronic health records (EHR) without BMD. Methods: In this retrospective, population-based cohort study, anonymized medical records were retrieved from the Clinical Data Analysis and Reporting System for public healthcare service users in Hong Kong aged ≥60 years as of 31 December 2005. A total of 161,051 individuals (91,926 female; 69,125 male) with complete follow-up from 1 January 2006 till the study end date on 31 December 2015 were included in the derivation cohort. The sex-stratified derivation cohort was randomly divided into 80% training and 20% internal testing datasets. An independent validation cohort comprised 3046 community-dwelling participants aged ≥60 years as of 31 December 2005 from the Hong Kong Osteoporosis Study, a prospective cohort which recruited participants between 1995 and 2010. With 395 potential predictors (age, diagnosis, and drug prescription records from EHR), 10-year sex-specific hip fracture prediction models were developed using stepwise selection by logistic regression (LR) and four machine learning (ML) algorithms (gradient boosting machine, random forest, eXtreme gradient boosting, and single-layer neural networks) in the training cohort. Model performance was evaluated in both internal and independent validation cohorts. Findings: In female, the LR model had the highest AUC (0.815; 95% Confidence Interval [CI]: 0.805–0.825) and adequate calibration in internal validation. Reclassification metrics showed the LR model had better discrimination and classification performance than the ML algorithms. Similar performance was attained by the LR model in independent validation, with high AUC (0.841; 95% CI: 0.807–0.87) comparable to other ML algorithms. In internal validation for male, LR model had high AUC (0.818; 95% CI: 0.801–0.834) and it outperformed all ML models as indicated by reclassification metrics, with adequate calibration. In independent validation, the LR model had high AUC (0.898; 95% CI: 0.857–0.939) comparable to ML algorithms. Reclassification metrics demonstrated that LR model had the best discrimination performance. Interpretation: Even without using BMD data, the 10-year hip fracture prediction models developed by conventional LR had better discrimination performance than the models developed by ML algorithms. Upon further validation in independent cohorts, the LR models could be integrated into the routine clinical workflow, aiding the identification of people at high risk for DXA scan. Funding: Health and Medical Research Fund, Health Bureau, Hong Kong SAR Government (reference: 17181381)

Ethnic difference of clinical vertebral fracture risk

Vertebral fractures are the most common osteoporotic fractures. Data on the vertebral fracture risk in Asia remain sparse. This study observed that Hong Kong Chinese and Japanese populations have a less dramatic increase in hip fracture rates associated with age than Caucasians, but the vertebral fracture rates were higher, resulting in a high vertebral-to-hip fracture ratio. As a result, estimation of the absolute fracture risk for Asians may need to be readjusted for the higher clinical vertebral fracture rate. Introduction: Vertebral fractures are the most common osteoporotic fractures. Data on the vertebral fracture risk in Asia remain sparse. The aim of this study was to report the incidence of clinical vertebral fractures among the Chinese and to compare the vertebral-to-hip fracture risk to other ethnic groups. Methods: Four thousand, three hundred eighty-six community-dwelling Southern Chinese subjects (2,302 women and 1,810 men) aged 50 or above were recruited in the Hong Kong Osteoporosis Study since 1995. Baseline demographic characteristics and medical history were obtained. Subjects were followed annually for fracture outcomes with a structured questionnaire and verified by the computerized patient information system of the Hospital Authority of the Hong Kong Government. Only non-traumatic incident hip fractures and clinical vertebral fractures that received medical attention were included in the analysis. The incidence rates of clinical vertebral fractures and hip fractures were determined and compared to the published data of Swedish Caucasian and Japanese populations. Results: The mean age at baseline was 62 ± 8.2 years for women and 68 ± 10.3 years for men. The average duration of follow-up was 4.0 ± 2.8 (range, 1 to 14) years for a total of 14,733 person-years for the whole cohort. The incidence rate for vertebral fracture was 194/100,000 person-years in men and 508/100,000 person-years in women, respectively. For subjects above the age of 65, the clinical vertebral fracture and hip fracture rates were 299/100,000 and 332/100,000 person-years, respectively, in men, and 594/100,000 and 379/100,000 person-years, respectively, in women. Hong Kong Chinese and Japanese populations have a less dramatic increase in hip fracture rates associated with age than Caucasians. At the age of 65 or above, the hip fracture rates for Asian (Hong Kong Chinese and Japanese) men and women were less than half of that in Caucasians, but the vertebral fracture rate was higher in Asians, resulting in a high vertebral-to-hip fracture ratio. Conclusions: The incidences of vertebral and hip fractures, as well as the vertebral-to-hip fracture ratios vary in Asians and Caucasians. Estimation of the absolute fracture risk for Asians may need to be readjusted for the higher clinical vertebral fracture rate. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research