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1. Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation

Author

Bockel-Rickermann, Christopher, Vanderschueren, Toon, Verdonck, Tim, and Verbeke, Wouter

Subjects
Computer Science - Machine Learning, 62D20
Abstract

Estimating conditional average dose responses (CADR) is an important but challenging problem. Estimators must correctly model the potentially complex relationships between covariates, interventions, doses, and outcomes. In recent years, the machine learning community has shown great interest in developing tailored CADR estimators that target specific challenges. Their performance is typically evaluated against other methods on (semi-) synthetic benchmark datasets. Our paper analyses this practice and shows that using popular benchmark datasets without further analysis is insufficient to judge model performance. Established benchmarks entail multiple challenges, whose impacts must be disentangled. Therefore, we propose a novel decomposition scheme that allows the evaluation of the impact of five distinct components contributing to CADR estimator performance. We apply this scheme to eight popular CADR estimators on four widely-used benchmark datasets, running nearly 1,500 individual experiments. Our results reveal that most established benchmarks are challenging for reasons different from their creators' claims. Notably, confounding, the key challenge tackled by most estimators, is not an issue in any of the considered datasets. We discuss the major implications of our findings and present directions for future research., Comment: 25 pages, 9 figures

Published
2024

4. Network Analytics for Anti-Money Laundering -- A Systematic Literature Review and Experimental Evaluation

Author

Deprez, Bruno, Vanderschueren, Toon, Baesens, Bart, Verdonck, Tim, and Verbeke, Wouter

Subjects
Computer Science - Social and Information Networks, Computer Science - Machine Learning
Abstract

Money laundering presents a pervasive challenge, burdening society by financing illegal activities. To more effectively combat and detect money laundering, the use of network information is increasingly being explored, exploiting that money laundering necessarily involves interconnected parties. This has lead to a surge in literature on network analytics (NA) for anti-money laundering (AML). The literature, however, is fragmented and a comprehensive overview of existing work is missing. This results in limited understanding of the methods that may be applied and their comparative detection power. Therefore, this paper presents an extensive and systematic review of the literature. We identify and analyse 97 papers in the Web of Science and Scopus databases, resulting in a taxonomy of approaches following the fraud analytics framework of Bockel-Rickermann et al.. Moreover, this paper presents a comprehensive experimental framework to evaluate and compare the performance of prominent NA methods in a uniform setup. The framework is applied on the publicly available Elliptic data set and implements manual feature engineering, random walk-based methods, and deep learning GNNs. We conclude from the results that network analytics increases the predictive power of the AML model with graph neural networks giving the best results. An open source implementation of the experimental framework is provided to facilitate researchers and practitioners to extend upon these results and experiment on proprietary data. As such, we aim to promote a standardised approach towards the analysis and evaluation of network analytics for AML.

Published
2024

5. Metalearners for Ranking Treatment Effects

Author

Vanderschueren, Toon, Verbeke, Wouter, Moraes, Felipe, and Proença, Hugo Manuel

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Efficiently allocating treatments with a budget constraint constitutes an important challenge across various domains. In marketing, for example, the use of promotions to target potential customers and boost conversions is limited by the available budget. While much research focuses on estimating causal effects, there is relatively limited work on learning to allocate treatments while considering the operational context. Existing methods for uplift modeling or causal inference primarily estimate treatment effects, without considering how this relates to a profit maximizing allocation policy that respects budget constraints. The potential downside of using these methods is that the resulting predictive model is not aligned with the operational context. Therefore, prediction errors are propagated to the optimization of the budget allocation problem, subsequently leading to a suboptimal allocation policy. We propose an alternative approach based on learning to rank. Our proposed methodology directly learns an allocation policy by prioritizing instances in terms of their incremental profit. We propose an efficient sampling procedure for the optimization of the ranking model to scale our methodology to large-scale data sets. Theoretically, we show how learning to rank can maximize the area under a policy's incremental profit curve. Empirically, we validate our methodology and show its effectiveness in practice through a series of experiments on both synthetic and real-world data.

Published
2024

7. Using representation balancing to learn conditional-average dose responses from clustered data

Author

Bockel-Rickermann, Christopher, Vanderschueren, Toon, Berrevoets, Jeroen, Verdonck, Tim, and Verbeke, Wouter

Subjects
Computer Science - Machine Learning, Statistics - Methodology, 62D20
Abstract

Estimating a unit's responses to interventions with an associated dose, the "conditional average dose response" (CADR), is relevant in a variety of domains, from healthcare to business, economics, and beyond. Such a response typically needs to be estimated from observational data, which introduces several challenges. That is why the machine learning (ML) community has proposed several tailored CADR estimators. Yet, the proposal of most of these methods requires strong assumptions on the distribution of data and the assignment of interventions, which go beyond the standard assumptions in causal inference. Whereas previous works have so far focused on smooth shifts in covariate distributions across doses, in this work, we will study estimating CADR from clustered data and where different doses are assigned to different segments of a population. On a novel benchmarking dataset, we show the impacts of clustered data on model performance and propose an estimator, CBRNet, that learns cluster-agnostic and hence dose-agnostic covariate representations through representation balancing for unbiased CADR inference. We run extensive experiments to illustrate the workings of our method and compare it with the state of the art in ML for CADR estimation., Comment: 21 pages, 7 figures, v2: updated methodology and experiments

Published
2023

8. Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time

Author

Vanderschueren, Toon, Curth, Alicia, Verbeke, Wouter, and van der Schaar, Mihaela

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

Machine learning (ML) holds great potential for accurately forecasting treatment outcomes over time, which could ultimately enable the adoption of more individualized treatment strategies in many practical applications. However, a significant challenge that has been largely overlooked by the ML literature on this topic is the presence of informative sampling in observational data. When instances are observed irregularly over time, sampling times are typically not random, but rather informative -- depending on the instance's characteristics, past outcomes, and administered treatments. In this work, we formalize informative sampling as a covariate shift problem and show that it can prohibit accurate estimation of treatment outcomes if not properly accounted for. To overcome this challenge, we present a general framework for learning treatment outcomes in the presence of informative sampling using inverse intensity-weighting, and propose a novel method, TESAR-CDE, that instantiates this framework using Neural CDEs. Using a simulation environment based on a clinical use case, we demonstrate the effectiveness of our approach in learning under informative sampling., Comment: To appear in the Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023

Published
2023

9. Factors Associated With Circulating Sex Hormones in Men : Individual Participant Data Meta-analyses.

Author

Bhasin, Shalender, Biggs, Mary, Cawthon, Peggy, Couper, David, Dobs, Adrian, Flicker, Leon, Handelsman, David, Hankey, Graeme, Hannemann, Anke, Haring, Robin, Hsu, Benjumin, Karlsson, Magnus, Martin, Sean, Matsumoto, Alvin, Mellström, Dan, Ohlsson, Claes, ONeill, Terence, Orwoll, Eric, Quartagno, Matteo, Shores, Molly, Steveling, Antje, Tivesten, Åsa, Travison, Thomas, Vanderschueren, Dirk, Wittert, Gary, Wu, Frederick, Yeap, Bu, Marriott, Ross, Murray, Kevin, Adams, Robert, Antonio, Leen, Ballantyne, Christie, and Bauer, Douglas

Subjects
Humans, Male, Adolescent, Young Adult, Adult, Middle Aged, Aged, Sex Hormone-Binding Globulin, Cross-Sectional Studies, Prospective Studies, Gonadal Steroid Hormones, Testosterone, Luteinizing Hormone
Abstract

BACKGROUND: Various factors modulate circulating testosterone in men, affecting interpretation of testosterone measurements. PURPOSE: To clarify factors associated with variations in sex hormone concentrations. DATA SOURCES: Systematic literature searches (to July 2019). STUDY SELECTION: Prospective cohort studies of community-dwelling men with total testosterone measured using mass spectrometry. DATA EXTRACTION: Individual participant data (IPD) (9 studies; n = 21 074) and aggregate data (2 studies; n = 4075). Sociodemographic, lifestyle, and health factors and concentrations of total testosterone, sex hormone-binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone, and estradiol were extracted. DATA SYNTHESIS: Two-stage random-effects IPD meta-analyses found a nonlinear association of testosterone with age, with negligible change among men aged 17 to 70 years (change per SD increase about the midpoint, -0.27 nmol/L [-7.8 ng/dL] [CI, -0.71 to 0.18 nmol/L {-20.5 to 5.2 ng/dL}]) and decreasing testosterone levels with age for men older than 70 years (-1.55 nmol/L [-44.7 ng/dL] [CI, -2.05 to -1.06 nmol/L {-59.1 to -30.6 ng/dL}]). Testosterone was inversely associated with body mass index (BMI) (change per SD increase, -2.42 nmol/L [-69.7 ng/dL] [CI, -2.70 to -2.13 nmol/L {-77.8 to -61.4 ng/dL}]). Testosterone concentrations were lower for men who were married (mean difference, -0.57 nmol/L [-16.4 ng/dL] [CI, -0.89 to -0.26 nmol/L {-25.6 to -7.5 ng/dL}]); undertook at most 75 minutes of vigorous physical activity per week (-0.51 nmol/L [-14.7 ng/dL] [CI, -0.90 to -0.13 nmol/L {-25.9 to -3.7 ng/dL}]); were former smokers (-0.34 nmol/L [-9.8 ng/dL] [CI, -0.55 to -0.12 nmol/L {-15.9 to -3.5 ng/dL}]); or had hypertension (-0.53 nmol/L [-15.3 ng/dL] [CI, -0.82 to -0.24 nmol/L {-23.6 to -6.9 ng/dL}]), cardiovascular disease (-0.35 nmol/L [-10.1 ng/dL] [CI, -0.55 to -0.15 nmol/L {-15.9 to -4.3 ng/dL}]), cancer (-1.39 nmol/L [-40.1 ng/dL] [CI, -1.79 to -0.99 nmol/L {-51.6 to -28.5 ng/dL}]), or diabetes (-1.43 nmol/L [-41.2 ng/dL] [CI, -1.65 to -1.22 nmol/L {-47.6 to -35.2 ng/dL}]). Sex hormone-binding globulin was directly associated with age and inversely associated with BMI. Luteinizing hormone was directly associated with age in men older than 70 years. LIMITATION: Cross-sectional analysis, heterogeneity between studies and in timing of blood sampling, and imputation for missing data. CONCLUSION: Multiple factors are associated with variation in male testosterone, SHBG, and LH concentrations. Reduced testosterone and increased LH concentrations may indicate impaired testicular function after age 70 years. Interpretation of individual testosterone measurements should account particularly for age older than 70 years, obesity, diabetes, and cancer. PRIMARY FUNDING SOURCE: Medical Research Future Fund, Government of Western Australia, and Lawley Pharmaceuticals. (PROSPERO: CRD42019139668).

Published
2023

10. Are Straight-Through gradients and Soft-Thresholding all you need for Sparse Training?

Author

Vanderschueren, Antoine and De Vleeschouwer, Christophe

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Turning the weights to zero when training a neural network helps in reducing the computational complexity at inference. To progressively increase the sparsity ratio in the network without causing sharp weight discontinuities during training, our work combines soft-thresholding and straight-through gradient estimation to update the raw, i.e. non-thresholded, version of zeroed weights. Our method, named ST-3 for straight-through/soft-thresholding/sparse-training, obtains SoA results, both in terms of accuracy/sparsity and accuracy/FLOPS trade-offs, when progressively increasing the sparsity ratio in a single training cycle. In particular, despite its simplicity, ST-3 favorably compares to the most recent methods, adopting differentiable formulations or bio-inspired neuroregeneration principles. This suggests that the key ingredients for effective sparsification primarily lie in the ability to give the weights the freedom to evolve smoothly across the zero state while progressively increasing the sparsity ratio. Source code and weights available at https://github.com/vanderschuea/stthree

Published
2022

12. Prescriptive maintenance with causal machine learning

Author

Vanderschueren, Toon, Boute, Robert, Verdonck, Tim, Baesens, Bart, and Verbeke, Wouter

Subjects
Economics - General Economics, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Machine maintenance is a challenging operational problem, where the goal is to plan sufficient preventive maintenance to avoid machine failures and overhauls. Maintenance is often imperfect in reality and does not make the asset as good as new. Although a variety of imperfect maintenance policies have been proposed in the literature, these rely on strong assumptions regarding the effect of maintenance on the machine's condition, assuming the effect is (1) deterministic or governed by a known probability distribution, and (2) machine-independent. This work proposes to relax both assumptions by learning the effect of maintenance conditional on a machine's characteristics from observational data on similar machines using existing methodologies for causal inference. By predicting the maintenance effect, we can estimate the number of overhauls and failures for different levels of maintenance and, consequently, optimize the preventive maintenance frequency to minimize the total estimated cost. We validate our proposed approach using real-life data on more than 4,000 maintenance contracts from an industrial partner. Empirical results show that our novel, causal approach accurately predicts the maintenance effect and results in individualized maintenance schedules that are more accurate and cost-effective than supervised or non-individualized approaches.

Published
2022

14. A new perspective on classification: optimally allocating limited resources to uncertain tasks

Author

Vanderschueren, Toon, Baesens, Bart, Verdonck, Tim, and Verbeke, Wouter

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

A central problem in business concerns the optimal allocation of limited resources to a set of available tasks, where the payoff of these tasks is inherently uncertain. In credit card fraud detection, for instance, a bank can only assign a small subset of transactions to their fraud investigations team. Typically, such problems are solved using a classification framework, where the focus is on predicting task outcomes given a set of characteristics. Resources are then allocated to the tasks that are predicted to be the most likely to succeed. However, we argue that using classification to address task uncertainty is inherently suboptimal as it does not take into account the available capacity. Therefore, we first frame the problem as a type of assignment problem. Then, we present a novel solution using learning to rank by directly optimizing the assignment's expected profit given limited, stochastic capacity. This is achieved by optimizing a specific instance of the net discounted cumulative gain, a commonly used class of metrics in learning to rank. Empirically, we demonstrate that our new method achieves higher expected profit and expected precision compared to a classification approach for a wide variety of application areas and data sets. This illustrates the benefit of an integrated approach and of explicitly considering the available resources when learning a predictive model.

Published
2022

18. How semantic and geometric information mutually reinforce each other in ToF object localization

Author

Vanderschueren, Antoine, Joos, Victor, and De Vleeschouwer, Christophe

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We propose a novel approach to localize a 3D object from the intensity and depth information images provided by a Time-of-Flight (ToF) sensor. Our method uses two CNNs. The first one uses raw depth and intensity images as input, to segment the floor pixels, from which the extrinsic parameters of the camera are estimated. The second CNN is in charge of segmenting the object-of-interest. As a main innovation, it exploits the calibration estimated from the prediction of the first CNN to represent the geometric depth information in a coordinate system that is attached to the ground, and is thus independent of the camera elevation. In practice, both the height of pixels with respect to the ground, and the orientation of normals to the point cloud are provided as input to the second CNN. Given the segmentation predicted by the second CNN, the object is localized based on point cloud alignment with a reference model. Our experiments demonstrate that our proposed two-step approach improves segmentation and localization accuracy by a significant margin compared to a conventional CNN architecture, ignoring calibration and height maps, but also compared to PointNet++.

Published
2020

20. Vitamin D metabolites and the gut microbiome in older men

Author

Thomas, RL, Jiang, L, Adams, JS, Xu, ZZ, Shen, J, Janssen, S, Ackermann, G, Vanderschueren, D, Pauwels, S, Knight, R, Orwoll, ES, and Kado, DM

Abstract

The vitamin D receptor is highly expressed in the gastrointestinal tract where it transacts gene expression. With current limited understanding of the interactions between the gut microbiome and vitamin D, we conduct a cross-sectional analysis of 567 older men quantifying serum vitamin D metabolites using LC-MSMS and defining stool sub-Operational Taxonomic Units from16S ribosomal RNA gene sequencing data. Faith’s Phylogenetic Diversity and non-redundant covariate analyses reveal that the serum 1,25(OH)2D level explains 5% of variance in α-diversity. In β-diversity analyses using unweighted UniFrac, 1,25(OH)2D is the strongest factor assessed, explaining 2% of variance. Random forest analyses identify 12 taxa, 11 in the phylum Firmicutes, eight of which are positively associated with either 1,25(OH)2D and/or the hormone-to-prohormone [1,25(OH)2D/25(OH)D] “activation ratio.” Men with higher levels of 1,25(OH)2D and higher activation ratios, but not 25(OH)D itself, are more likely to possess butyrate producing bacteria that are associated with better gut microbial health.

Published
2020

23. Sarcopenia in patients receiving TIPS is independently associated with increased risk of complications and mortality.

Author

Vanderschueren, Emma, Meersseman, Philippe, Wilmer, Alexander, Vandecaveye, Vincent, Dubois, Evelyne, Van Eldere, Anne, Clerick, Jan, Peluso, Jo P., Claus, Eveline, Bonne, Lawrence, Verslype, Chris, Maleux, Geert, and Laleman, Wim

Abstract

Sarcopenia is an acknowledged risk factor for individuals with chronic liver disease, however, the influence on outcomes in patients receiving transjugular intrahepatic portosystemic shunt (TIPS) remains underexplored. This study aimed to investigate the association between sarcopenia and incidence of complications and mortality post-TIPS. A retrospective analysis was performed on 175 patients who underwent TIPS between 2011–2021 at a Belgian tertiary care center. Transverse psoas muscle thickness (TPMT) was measured at baseline, with a subset of 85 patients having a second TPMT after 1–2 years for assessment of evolution. Over a median follow-up of 453 days (IQR 76–1179), sarcopenic patients exhibited a higher prevalence of complications (74.1% vs. 57.9%, p = 0.04) and one-year mortality (53.4% vs. 22.3%, p < 0.001) post-TIPS. Notably, 58.8% of patients showed an increase >10% from baseline TPMT/length post-TIPS, with the greatest improvement observed in severely sarcopenic patients (4.00 ± 4.55 mm/m vs. -0.82 ± 2.68 mm/m, p < 0.001) and in those patients free from TIPS-related complications (3.18 ± 4.09 mm/m vs. 1.31 ± 3.21 mm/m, p = 0.022). Sarcopenia increases the risk of complications and mortality post-TIPS. Importantly, sarcopenia improves in patients receiving TIPS, particularly in those with severe sarcopenia at baseline and free of TIPS-related complications. [ABSTRACT FROM AUTHOR]

Published
2025
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25. Spleen stiffness measurement by vibration-controlled transient elastography at 100 Hz for non-invasive predicted diagnosis of clinically significant portal hypertension in patients with compensated advanced chronic liver disease: a modelling study

Author

Jachs, Mathias, Odriozola, Aitor, Turon, Fanny, Moga, Lucile, Téllez, Luis, Fischer, Petra, Saltini, Dario, Kwanten, Wilhelmus J, Grasso, Maria, Llop, Elba, Mendoza, Yuly P, Armandi, Angelo, Thalhammer, Julia, Pardo, Carlos, Colecchia, Antonio, Ravaioli, Federico, Maasoumy, Benjamin, Laleman, Wim, Presa, José, Schattenberg, Jörn M, Berzigotti, Annalisa, Calleja, José L, Calvaruso, Vincenza, Francque, Sven, Schepis, Filippo, Procopet, Bogdan, Albillos, Agustín, Rautou, Pierre-Emmanuel, García-Pagán, Juan C, Puente, Ángela, Fortea, José I, Reiberger, Thomas, Mandorfer, Mattias, Kuner, Charlotte, Stättermayer, Albert Friedrich, Trauner, Michael, Hernández-Gea, Virginia, Payancé, Audrey, Roux, Olivier, Issoufaly, Tazime, Valainathan, Shantha, de Broucker, Chloé, Torres, María, Stefanescu, Horia, Platon, Monica, Fodor, Andreea, Nicoara-Farcau, Oana, Bianchini, Marcello, Guasconi, Tomas, Vanwolleghem, Thomas, Schoenmakers, Lotte, Vonghia, Luisa, Labenz, Christian, Dajti, Elton, Colecchia, Luigi, Vanderschueren, Emma, Sandmann, Lisa, and Greenfield, Helena

Abstract

In patients with compensated advanced chronic liver disease (cACLD), risk of clinically significant portal hypertension (CSPH) can be estimated by applying non-invasive tests such as liver stiffness measurement (LSM), platelet count, and, in some cases, BMI. We aimed to assess the diagnostic utility of spleen stiffness measurement (SSM) at 100 Hz as a standalone non-invasive test for CSPH and to evaluate its incremental value compared with the ANTICIPATE±NASH model in patients with cACLD.

Published
2024
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28. Associations of total and free 25OHD and 1,25(OH)2D with serum markers of inflammation in older men

Author

Srikanth, P, Chun, RF, Hewison, M, Adams, JS, Bouillon, R, Vanderschueren, D, Lane, N, Cawthon, PM, Dam, T, Barrett-Connor, E, Daniels, LB, Shikany, JM, Stefanick, ML, Cauley, JA, Orwoll, ES, Nielson, CM, and for the Osteoporotic Fractures in Men (MrOS) Study Research Group

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Inflammatory and immune system, Aged, Aged, 80 and over, Biomarkers, Humans, Inflammation, Interleukin-6, Male, Receptors, Tumor Necrosis Factor, Vitamin D, Elderly, Free 1, 25(OH)(2)D, Free 25OHD, Men, Total 1, 25(OH)(2)D, Total 25OHD, Osteoporotic Fractures in Men (MrOS) Study Research Group, Free 1, 25(OH)2D, Total 1, 25(OH)2D, Biomedical Engineering, Clinical Sciences, Public Health and Health Services, Endocrinology & Metabolism, Clinical sciences, Epidemiology
Abstract

UnlabelledVitamin D is hypothesized to suppress inflammation. We tested total and free vitamin D metabolites and their association with inflammatory markers. Interleukin-6 levels were lower with higher 25-hydroxyvitamin D. 1,25-dihydroxyvitamin D and free 25OHD associations mirrored those of 25OHD. However, associations for the two metabolites diverged for tumor necrosis factor alpha (TNF-α) soluble receptors.IntroductionVitamin D is hypothesized to suppress inflammation, and circulating 25-hydroxyvitamin D (25OHD) and inflammatory markers are inversely correlated. However, total serum 25OHD may not be the best indicator of biologically active vitamin D.MethodsWe tested serum total 25OHD, total 1,25(OH)2D, vitamin D binding protein (DBP), and estimated free 25OHD and free 1,25(OH)2D associations with inflammatory markers serum interleukin-6 (IL-6), TNF-α and their soluble receptors, interleukin-10 (IL-10), and C-reactive protein (CRP) as continuous outcomes and the presence of ≥2 inflammatory markers in the highest quartile as a dichotomous outcome, in a random subcohort of 679 men in the Osteoporotic Fractures in Men (MrOS) study.ResultsIL-6 was lower in men with higher 25OHD (-0.23 μg/mL per standard deviation (SD) increase in 25OHD, 95 % confidence intervals (CI) -0.07 to -0.38 μg/mL) and with higher 1,25(OH)2D (-0.20 μg/mL, 95 % CI -0.0004 to -0.39 μg/mL); free D associations were slightly stronger. 25OHD and DBP, but not 1,25(OH)2D, were independently associated with IL-6. TNF-α soluble receptors were inversely associated with 1,25(OH)2D but positively associated with 25OHD, and each had independent effects. The strongest association with ≥2 inflammatory markers in the highest quartile was for free 1,25(OH)2D (odds ratios (OR) 0.70, 95 % CI 0.54 to 0.89 per SD increase in free 1,25(OH)2D).ConclusionsAssociations of 1,25(OH)2D and free 25OHD with IL-6 mirrored those of 25OHD, suggesting that 1,25(OH)2D and free D do not improve upon 25OHD in population-based IL-6 studies. However, associations for the two metabolites diverged for TNF-α soluble receptor, warranting examination of both metabolites in studies of TNF-α and its antagonists.

Published
2016

29. Associations of 25‐Hydroxyvitamin D and 1,25‐Dihydroxyvitamin D With Bone Mineral Density, Bone Mineral Density Change, and Incident Nonvertebral Fracture

Author

Swanson, Christine M, Srikanth, Priya, Lee, Christine G, Cummings, Steven R, Jans, Ivo, Cauley, Jane A, Bouillon, Roger, Vanderschueren, Dirk, Orwoll, Eric S, Nielson, Carrie M, and Group, for the Osteoporotic Fractures in Men MrOS Study Research

Subjects
Physical Injury - Accidents and Adverse Effects, Aging, Prevention, Nutrition, Osteoporosis, Musculoskeletal, Aged, Aged, 80 and over, Bone Density, Follow-Up Studies, Hip Fractures, Humans, Incidence, Male, Radiography, Risk Factors, Vitamin D, Osteoporotic Fractures in Men MrOS Study Research Group, 1, 25-DIHYDROXYVITAMIN D, 25-HYDROXYVITAMIN D, BONE MINERAL DENSITY, CALCITRIOL, FRACTURE, Biological Sciences, Engineering, Medical and Health Sciences, Anatomy & Morphology
Abstract

Relationships between 1,25-dihydroxyvitamin D (1,25(OH)2 D) and skeletal outcomes are uncertain. We examined the associations of 1,25(OH)2 D with bone mineral density (BMD), BMD change, and incident non-vertebral fractures in a cohort of older men and compared them with those of 25-hydroxyvitamin D (25OHD). The study population included 1000 men (aged 74.6 ± 6.2 years) in the Osteoporotic Fractures in Men (MrOS) study, of which 537 men had longitudinal dual-energy X-ray absorptiometry (DXA) data (4.5 years of follow-up). A case-cohort design and Cox proportional hazards models were used to test the association between vitamin D metabolite levels and incident nonvertebral and hip fractures. Linear regression models were used to estimate the association between vitamin D measures and baseline BMD and BMD change. Interactions between 25OHD and 1,25(OH)2 D were tested for each outcome. Over an average follow-up of 5.1 years, 432 men experienced incident nonvertebral fractures, including 81 hip fractures. Higher 25OHD was associated with higher baseline BMD, slower BMD loss, and lower hip fracture risk. Conversely, men with higher 1,25(OH)2 D had lower baseline BMD. 1,25(OH)2 D was not associated with BMD loss or nonvertebral fracture. Compared with higher levels of calcitriol, the risk of hip fracture was higher in men with the lowest 1,25(OH)2 D levels (8.70 to 51.60 pg/mL) after adjustment for baseline hip BMD (hazard ratio [HR] = 1.99, 95% confidence interval [CI] 1.19-3.33). Adjustment of 1,25(OH)2 D data for 25OHD (and vice versa) had little effect on the associations observed but did attenuate the hip fracture association of both vitamin D metabolites. In older men, higher 1,25(OH)2 D was associated with lower baseline BMD but was not related to the rate of bone loss or nonvertebral fracture risk. However, with BMD adjustment, a protective association for hip fracture was found with higher 1,25(OH)2 D. The associations of 25OHD with skeletal outcomes were generally stronger than those for 1,25(OH)2 D. These results do not support the hypothesis that measures of 1,25(OH)2 D improve the ability to predict adverse skeletal outcomes when 25OHD measures are available. © 2015 American Society for Bone and Mineral Research.

Published
2015

30. The androgen receptor depends on ligand-binding domain dimerization for transcriptional activation

Author

El Kharraz, Sarah, Dubois, Vanessa, van Royen, Martin E, Houtsmuller, Adriaan B, Pavlova, Ekatarina, Atanassova, Nina, Nguyen, Tien, Voet, Arnout, Eerlings, Roy, Handle, Florian, Prekovic, Stefan, Smeets, Elien, Moris, Lisa, Devlies, Wout, Ohlsson, Claes, Poutanen, Matti, Verstrepen, Kevin J, Carmeliet, Geert, Launonen, Kaisa-Mari, Helminen, Laura, Palvimo, Jorma J, Libert, Claude, Vanderschueren, Dirk, Helsen, Christine, and Claessens, Frank

Published
2021
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32. Genetic determinants of heel bone properties: genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium.

Author

Moayyeri, Alireza, Hsu, Yi-Hsiang, Karasik, David, Estrada, Karol, Xiao, Su-Mei, Nielson, Carrie, Srikanth, Priya, Giroux, Sylvie, Wilson, Scott G, Zheng, Hou-Feng, Smith, Albert V, Pye, Stephen R, Leo, Paul J, Teumer, Alexander, Hwang, Joo-Yeon, Ohlsson, Claes, McGuigan, Fiona, Minster, Ryan L, Hayward, Caroline, Olmos, José M, Lyytikäinen, Leo-Pekka, Lewis, Joshua R, Swart, Karin MA, Masi, Laura, Oldmeadow, Chris, Holliday, Elizabeth G, Cheng, Sulin, van Schoor, Natasja M, Harvey, Nicholas C, Kruk, Marcin, del Greco M, Fabiola, Igl, Wilmar, Trummer, Olivia, Grigoriou, Efi, Luben, Robert, Liu, Ching-Ti, Zhou, Yanhua, Oei, Ling, Medina-Gomez, Carolina, Zmuda, Joseph, Tranah, Greg, Brown, Suzanne J, Williams, Frances M, Soranzo, Nicole, Jakobsdottir, Johanna, Siggeirsdottir, Kristin, Holliday, Kate L, Hannemann, Anke, Go, Min Jin, Garcia, Melissa, Polasek, Ozren, Laaksonen, Marika, Zhu, Kun, Enneman, Anke W, McEvoy, Mark, Peel, Roseanne, Sham, Pak Chung, Jaworski, Maciej, Johansson, Åsa, Hicks, Andrew A, Pludowski, Pawel, Scott, Rodney, Dhonukshe-Rutten, Rosalie AM, van der Velde, Nathalie, Kähönen, Mika, Viikari, Jorma S, Sievänen, Harri, Raitakari, Olli T, González-Macías, Jesús, Hernández, Jose L, Mellström, Dan, Ljunggren, Osten, Cho, Yoon Shin, Völker, Uwe, Nauck, Matthias, Homuth, Georg, Völzke, Henry, Haring, Robin, Brown, Matthew A, McCloskey, Eugene, Nicholson, Geoffrey C, Eastell, Richard, Eisman, John A, Jones, Graeme, Reid, Ian R, Dennison, Elaine M, Wark, John, Boonen, Steven, Vanderschueren, Dirk, Wu, Frederick CW, Aspelund, Thor, Richards, J Brent, Bauer, Doug, Hofman, Albert, Khaw, Kay-Tee, Dedoussis, George, Obermayer-Pietsch, Barbara, Gyllensten, Ulf, Pramstaller, Peter P, and Lorenc, Roman S

Subjects
Calcaneus, Humans, Osteoporosis, Genetic Predisposition to Disease, Ultrasonography, Cohort Studies, Bone Density, Polymorphism, Single Nucleotide, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Fractures, Bone, Genome-Wide Association Study, Young Adult, Human Genome, Genetics, Aging, 2.1 Biological and endogenous factors, Aetiology, Musculoskeletal, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n = 14 260), velocity of sound (VOS; n = 15 514) and BMD (n = 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n = 11 452) and new genotyping in 15 cohorts (de novo n = 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 × 10(-8)) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 × 10(-14)). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 × 10(-6) also had the expected direction of association with any fracture (P < 0.05), including three SNPs with P < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, this GWA study reveals the effect of several genes common to central DXA-derived BMD and heel ultrasound/DXA measures and points to a new genetic locus with potential implications for better understanding of osteoporosis pathophysiology.

Published
2014

34. Time to onset of antifracture efficacy and year‐by‐year persistence of effect of zoledronic acid in women with osteoporosis

Author

Boonen, Steven, Eastell, Richard, Su, Guoqin, Mesenbrink, Peter, Cosman, Felicia, Cauley, Jane A, Reid, Ian R, Claessens, Frank, Vanderschueren, Dirk, Lyles, Kenneth W, and Black, Dennis M

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Osteoporosis, Aging, Clinical Trials and Supportive Activities, Clinical Research, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Aged, Aged, 80 and over, Algorithms, Bone Density, Bone Density Conservation Agents, Diphosphonates, Double-Blind Method, Female, Humans, Imidazoles, Osteoporosis, Postmenopausal, Osteoporotic Fractures, Placebos, Proportional Hazards Models, Risk, Time Factors, Zoledronic Acid, FRACTURES, POSTMENOPAUSAL OSTEOPOROSIS, REACTION TIME, ZOLEDRONIC ACID, BONE MINERAL DENSITY, Biological Sciences, Engineering, Medical and Health Sciences, Anatomy & Morphology, Biological sciences, Biomedical and clinical sciences
Abstract

Oral bisphosphonates reduce fracture risk in osteoporotic patients but are often associated with poor compliance, which may impair their antifracture effects. This post hoc analysis assessed the time to onset and persistence of the antifracture effect of zoledronic acid, a once-yearly bisphosphonate infusion, in women with osteoporosis. Data from 9355 women who were randomized in two placebo-controlled pivotal trials were included. Endpoints included reduction in the rate of any clinical fracture at 6, 12, 18, 24, and 36 months in the zoledronic acid group compared with placebo, and the year-by-year incidence of all clinical fractures over 3 years. Cox proportional hazards regression was used to determine the timing of onset of antifracture efficacy. A generalized estimating equation model was used to assess fracture reduction for the 3 consecutive years of treatment, thereby evaluating persistence of effect. Safety results from women in the two studies were collated. Zoledronic acid reduced the risk of all clinical fractures at 12 months (hazard ratio [HR] = 0.75, 95% confidence interval [CI] 0.61-0.92, p = 0.0050) with significant reductions maintained at all subsequent time points. Year-by-year analysis showed that zoledronic acid reduced the risk for all clinical fractures compared with the placebo group in each of the 3 years (year 1: odds ratio [OR] = 0.74, 95% CI 0.60-0.91, p = 0.0044; year 2: OR = 0.53, 95% CI 0.42-0.66, p < 0.0001; year 3: OR = 0.61, 95% CI 0.48-0.77, p < 0.0001). This antifracture effect was persistent over 3 years, with the reductions in years 2 and 3 slightly larger than in year 1 (p = 0.097). This analysis shows that zoledronic acid offered significant protection from clinical fractures as early as 12 months. When administered annually, its beneficial effects persisted for at least 3 years.

Published
2012

35. General and abdominal adiposity and hypertension in eight world regions: a pooled analysis of 837 population-based studies with 7·5 million participants

Author

Zhou, Bin, Bennett, James E, Wickham, Aidan P, Singleton, Rosie K, Mishra, Anu, Carrillo-Larco, Rodrigo M, Ikeda, Nayu, Jain, Lakshya, Barradas-Pires, Ana, Heap, Rachel A, Lhoste, Victor PF, Sheffer, Kate E, Phelps, Nowell H, Rayner, Archie W, Gregg, Edward W, Woodward, Mark, Stevens, Gretchen A, Iurilli, Maria LC, Danaei, Goodarz, Di Cesare, Mariachiara, Aguilar-Salinas, Carlos A, Ahmad, Noor Ani, Bovet, Pascal, Chen, Zhengming, Damasceno, Albertino, Filippi, Sarah L, Janszky, Imre, Kengne, Andre P, Khang, Young-Ho, Khunti, Kamlesh, Laxmaiah, Avula, Lim, Lee-Ling, Lissner, Lauren, Margozzini, Paula, Mbanya, Jean Claude N, McGarvey, Stephen T, Shaw, Jonathan E, Söderberg, Stefan, Soto-Mota, Luis Adrián, Wang, Junyang, Zaccardi, Francesco, Abarca-Gómez, Leandra, Abbasi-Kangevari, Mohsen, Abdrakhmanova, Shynar, Abdul Ghaffar, Suhaila, Abdul Rahim, Hanan F, Abdurrahmonova, Zulfiya, Abu-Rmeileh, Niveen M, Acosta-Cazares, Benjamin, Adam, Ishag, Adamczyk, Marzena, Aekplakorn, Wichai, Agdeppa, Imelda A, Aghazadeh-Attari, Javad, Agyemang, Charles, Ahmad, Mohamad Hasnan, Ahmadi, Ali, Ahmadi, Naser, Ahmadi, Nastaran, Ahmed, Soheir H, Ahrens, Wolfgang, Aitmurzaeva, Gulmira, Ajlouni, Kamel, Al-Hazzaa, Hazzaa M, Al-Hinai, Halima, Al-Lawati, Jawad A, Al-Raddadi, Rajaa, Al Asfoor, Deena, Al Hourani, Huda M, Alarouj, Monira, AlBuhairan, Fadia, AlDhukair, Shahla, Ali, Mohamed M, Alieva, Anna V, Alkandari, Abdullah, Alkhatib, Buthaina M, Aly, Eman, Amarapurkar, Deepak N, Amiano Etxezarreta, Pilar, Amougou, Norbert, Andersen, Lars Bo, Anderssen, Sigmund A, Androutsos, Odysseas, Anjana, Ranjit Mohan, Ansari-Moghaddam, Alireza, Anufrieva, Elena, Aounallah-Skhiri, Hajer, Aris, Tahir, Arku, Raphael E, Arlappa, Nimmathota, Aryal, Krishna K, Assah, Felix K, Assembekov, Batyrbek, Assunção, Maria Cecília F, Auvinen, Juha, Avdičová, Mária, Azad, Kishwar, Azevedo, Ana, Azimi-Nezhad, Mohsen, Azizi, Fereidoun, Bacopoulou, Flora, Bahijri, Suhad, Bajramovic, Izet, Balakrishna, Nagalla, Bamoshmoosh, Mohamed, Banach, Maciej, Bandosz, Piotr, Banegas, José R, Baran, Rafał, Barbagallo, Carlo M, Barbosa Filho, Valter, Barceló, Alberto, Baretić, Maja, Barnoya, Joaquin, Barrera, Lena, Barros, Aluisio JD, Barros, Mauro Virgílio Gomes, Basit, Abdul, Bastos, Joao Luiz, Batieha, Anwar M, Batista, Aline P, Batista, Rosangela L, Battakova, Zhamilya, Baur, Louise A, Bayauli, Pascal M, Bel-Serrat, Silvia, Belavendra, Antonisamy, Ben Romdhane, Habiba, Benedek, Theodora, Benedics, Judith, Benet, Mikhail, Benitez Rolandi, Gilda Estela, Benzeval, Michaela, Bere, Elling, Berger, Nicolas, Bergh, Ingunn Holden, Berkinbayev, Salim, Bernabe-Ortiz, Antonio, Bettiol, Heloísa, Beybey, Augustin F, Bezerra, Jorge, Bhagyalaxmi, Aroor, Bhargava, Santosh K, Bika Lele, Elysée Claude, Bikbov, Mukharram M, Bista, Bihungum, Bjelica, Dusko J, Bjerregaard, Peter, Bjertness, Espen, Bjertness, Marius B, Björkelund, Cecilia, Bloch, Katia V, Blokstra, Anneke, Bo, Simona, Bobak, Martin, Boddy, Lynne M, Boehm, Bernhard O, Boggia, Jose G, Bogova, Elena, Bonaccio, Marialaura, Bonilla-Vargas, Alice, Borghs, Herman, Botomba, Steve, Bourne, Rupert, Boymatova, Khadichamo, Braeckman, Lutgart, Braithwaite, Tasanee, Brajkovich, Imperia, Branca, Francesco, Brenner, Hermann, Brewster, Lizzy M, Briceño, Yajaira, Brinduse, Lacramioara, Bringolf-Isler, Bettina, Brito, Miguel, Brug, Johannes, Bugge, Anna, Buntinx, Frank, Buoncristiano, Marta, Burns, Con, Cabrera de León, Antonio, Caixeta, Roberta B, Cama, Tilema, Can, Günay, Cândido, Ana Paula C, Cañete, Felicia, Capanzana, Mario V, Čapková, Naděžda, Capuano, Eduardo, Capuano, Rocco, Capuano, Vincenzo, Cardoso, Viviane C, Carlsson, Axel C, Casanueva, Felipe F, Casas, Maribel, Censi, Laura, Cervantes‐Loaiza, Marvin, Chamnan, Parinya, Chamukuttan, Snehalatha, Chan, Queenie, Chaturvedi, Nish, Chen, Fangfang, Chen, Huashuai, Chen, Long-Sheng, Cheng, Yiling J, Cheraghian, Bahman, Chetrit, Angela, Chikova-Iscener, Ekaterina, Chinapaw, Mai JM, Chinnock, Anne, Chiolero, Arnaud, Chirita-Emandi, Adela, Chirlaque, María-Dolores, Chong, Chean Lin, Christofaro, Diego G, Chudek, Jerzy, Cifkova, Renata, Cirillo, Massimo, Claessens, Frank, Clare, Philip, Cohen, Emmanuel, Confortin, Susana C, Coppinger, Tara C, Cortés, Lilia Yadira, Cosmin, Cojocaru R, Costanzo, Simona, Cowan, Melanie J, Cowell, Chris, Crampin, Amelia C, Cross, Amanda J, Crujeiras, Ana B, Cruz, Juan J, Cucu, Alexandra M, Cureau, Felipe V, Cuschieri, Sarah, D'Arrigo, Graziella, d'Orsi, Eleonora, da Silva-Ferreira, Haroldo, Dahm, Christina C, Dallongeville, Jean, Dankner, Rachel, Davletov, Kairat, de Assis Guedes de Vasconcelos, Francisco, de Assis, Maria Alice Altenburg, De Bacquer, Dirk, De Bacquer, Jaco, de Bont, Jeroen, De Curtis, Amalia, de Fragas Hinnig, Patrícia, de Gaetano, Giovanni, De Henauw, Stefaan, De Miguel-Etayo, Pilar, de Oliveira, Paula Duarte, de Paiva, Karina Mary, De Ridder, Karin, de Valois Correia Júnior, Marco Aurélio, Deepa, Mohan, DeGennaro, Vincent Jr, Demarest, Stefaan, Dennison, Elaine, Deschamps, Valérie, Dhimal, Meghnath, Díez Ripollés, María Pilar, Dika, Zivka, Djalalinia, Shirin, Dominguez, Liria, Donati, Maria Benedetta, Donfrancesco, Chiara, Dong, Guanghui, Donoso, Silvana P, Dorobantu, Maria, Dörr, Marcus, Dragano, Nico, Drygas, Wojciech, Du, Shufa, Duante, Charmaine A, Duboz, Priscilla, Duda, Rosemary B, Duleva, Vesselka L, Dushpanova, Anar, Dyussupova, Azhar, Dziankowska-Zaborszczyk, Elzbieta, Ebrahimi, Narges, Echeverría, Guadalupe, Eddie, Ricky, Eftekhar, Ebrahim, Efthymiou, Vasiliki, Egbagbe, Eruke E, Eghtesad, Sareh, Ekelund, Ulf, El-Khateeb, Mohammad, El Ati, Jalila, Elosua, Roberto, Enang, Ofem, Erasmus, Rajiv T, Erem, Cihangir, Ergor, Gul, Eriksen, Louise, Eriksson, Johan G, Escobedo-de la Peña, Jorge, Esmaeili, Ali, Evans, Roger G, Fakhradiyev, Ildar, Fakhretdinova, Albina A, Fall, Caroline H, Faramarzi, Elnaz, Farjam, Mojtaba, Farzadfar, Farshad, Farzi, Yosef, Fattahi, Mohammad Reza, Fawwad, Asher, Felix-Redondo, Francisco J, Ferguson, Trevor S, Fernandes, Romulo A, Fernández-Bergés, Daniel, Fernando, Desha R, Ferrante, Daniel, Ferrari, Gerson, Ferrari, Marika, Ferreccio, Catterina, Ferrer, Eldridge, Figueiró, Thamara Hubler, Fijalkowska, Anna, Fink, Günther, Fisberg, Mauro, Forsner, Maria, Fottrell, Edward F, Fouad, Heba M, Francis, Damian K, Frontera, Guillermo, Fuchs, Flavio D, Fuchs, Sandra C, Furdela, Viktoriya, Furusawa, Takuro, Gabriela, Stefan Adela, Gaciong, Zbigniew, Galán Cuesta, Manuel, Galbarczyk, Andrzej, Galcheva, Sonya V, Galfo, Myriam, Garcia-de-la-Hera, Manoli, Garcia, Pablo, Garnett, Sarah P, Gasull, Magda, Gazzinelli, Andrea, Gehring, Ulrike, Gerdts, Eva, Ghaderi, Ebrahim, Ghamari, Seyyed-Hadi, Ghanbari, Ali, Ghasemi, Erfan, Gheorghe-Fronea, Oana-Florentina, Ghimire, Anup, Gialluisi, Alessandro, Giampaoli, Simona, Gianfagna, Francesco, Gironella, Glen, Giwercman, Aleksander, Gkiouras, Konstantinos, Glushkova, Natalya, Godara, Ramesh, Godos, Justyna, Goldberg, Marcel, Gómez, Georgina, Gómez Gómez, Jesús Humberto, Gomez, Luis F, Gómez, Santiago F, Gomula, Aleksandra, Gonçalves Cordeiro da Silva, Bruna, Gonçalves, Helen, Gonçalves, Mauer, González-Alvarez, Ana D, Gonzalez-Chica, David A, González-Gil, Esther M, Gonzalez-Gross, Marcela, González-Rivas, Juan P, Gonzalez, Angel R, Gottrand, Frederic, Grafnetter, Dušan, Grajda, Aneta, Grammatikopoulou, Maria G, Grodzicki, Tomasz, Grøholt, Else Karin, Grøntved, Anders, Guajardo, Viviana, Guallar-Castillón, Pilar, Guerchet, Maëlenn, Guerrero, Ramiro, Guimaraes, Andre L, Gujral, Unjali P, Gulliford, Martin C, Gunter, Marc J, Gupta, Rajeev, Gureje, Oye, Gurinović, Mirjana A, Gurzkowska, Beata, Gutierrez, Laura, Gwee, Xinyi, Haghshenas, Rosa, Hakimi, Hamid, Halkjær, Jytte, Hambleton, Ian R, Hamzeh, Behrooz, Hanekom, Willem A, Hange, Dominique, Hanif, Abu AM, Hantunen, Sari, Hao, Jie, Hardman, Carla Menêses, Hardy, Louise, Hari Kumar, Rachakulla, Harooni, Javad, Hashemi-Shahri, Seyed Mohammad, Hassapidou, Maria, Hata, Jun, Haugsgjerd, Teresa, Heinen, Mirjam, Hendriks, Marleen Elisabeth, Henrique, Rafael dos Santos, Henriques, Ana, Hernandez Cadena, Leticia, Herrala, Sauli, Herrera-Cuenca, Marianella, Herrera, Victor M, Herter-Aeberli, Isabelle, Herzig, Karl-Heinz, Heshmat, Ramin, Hill, Allan G, Ho, Sai Yin, Holdsworth, Michelle, Homayounfar, Reza, Homs, Clara, Hoogendijk, Emiel O, Horimoto, Andrea RVR, Hormiga, Claudia M, Horta, Bernardo L, Houti, Leila, Howitt, Christina, Htay, Thein Thein, Htet, Aung Soe, Htike, Maung Maung Than, Huerta, José María, Huhtaniemi, Ilpo Tapani, Huiart, Laetitia, Huidumac Petrescu, Constanta, Huisman, Martijn, Husseini, Abdullatif, Huybrechts, Inge, Hwalla, Nahla, Iacoviello, Licia, Iakupova, Ellina M, Iannone, Anna G, Igland, Jannicke, Ijoma, Chinwuba, Iotova, Violeta, Irazola, Vilma E, Ishida, Takafumi, Isiguzo, Godsent C, Islam, Muhammad, Islam, Sheikh Mohammed Shariful, Islek, Duygu, Ittermann, Till, Ivanova-Pandourska, Ivaila Y, Iwasaki, Masanori, Jääskeläinen, Tuija, Jackson, Rod T, Jaddou, Hashem Y, Jadoul, Michel, Jafar, Tazeen, Jan, Nataša, Janus, Edward, Jarani, Juel, Jarnig, Gerald, Jarvelin, Marjo-Riitta, Jasienska, Grazyna, Jelaković, Ana, Jelaković, Bojan, Jha, Anjani Kumar, Jimenez, Ramon O, Jöckel, Karl-Heinz, Joffres, Michel, Jokelainen, Jari J, Jonas, Jost B, Joshi, Pradeep, Joshi, Rohina, Josipović, Josipa, Joukar, Farahnaz, Jóźwiak, Jacek J, Juolevi, Anne, Juresa, Vesna, Jureša, Vesna, Kaaks, Rudolf, Kaducu, Felix O, Kadvan, Agnes L, Kafatos, Anthony, Kajantie, Eero O, Kakutia, Natia, Kállayová, Daniela, Kalmatayeva, Zhanna, Kalter-Leibovici, Ofra, Kannan, Srinivasan, Kapantais, Efthymios, Karaglani, Eva, Karakosta, Argyro, Karki, Khem B, Kassi Anicet, Adoubi, Katibeh, Marzieh, Katulanda, Prasad, Katzmarzyk, Peter T, Kauhanen, Jussi, Kazakbaeva, Gyulli M, Kaze, François F, Ke, Calvin, Keinänen-Kiukaanniemi, Sirkka, Kelishadi, Roya, Kelleher, Cecily, Kemper, Han CG, Keramati, Maryam, Kersting, Mathilde, Khader, Yousef Saleh, Khaledifar, Arsalan, Khalili, Davood, Kheiri, Bahareh, Kheradmand, Motahareh, Khosravi, Alireza, Kiechl-Kohlendorfer, Ursula, Kiechl, Sophia J, Kiechl, Stefan, Kim, Hyeon Chang, Klakk, Heidi, Klanarong, Suntara, Klanova, Jana, Klimek, Magdalena, Knoflach, Michael, Kobel, Susanne, Koirala, Bhawesh, Kolle, Elin, Kolsteren, Patrick, König, Jürgen, Korpelainen, Raija, Korrovits, Paul, Korzycka, Magdalena, Kos, Jelena, Koskinen, Seppo, Koussoh Simone, Malik, Kovács, Éva, Kovalskys, Irina, Kowlessur, Sudhir, Koziel, Slawomir, Kratenova, Jana, Kratzer, Wolfgang, Kriemler, Susi, Kristensen, Peter Lund, Krizan, Helena, Kroker-Lobos, Maria F, Krokstad, Steinar, Kruger, Herculina S, Kruger, Ruan, Kryst, Łukasz, Kubinova, Ruzena, Kujala, Urho M, Kujundzic, Enisa, Kulaga, Zbigniew, Kulimbet, Mukhtar, Kumari, Meena, Kunešová, Marie, Kurjata, Pawel, Kyobutungi, Catherine, La, Quang Ngoc, Labadarios, Demetre, Lachat, Carl, Lai, Daphne, Laid, Youcef, Lall, Lachmie, Landaeta Jimenez, Maritza, Landais, Edwige, Lankila, Tiina, Lanska, Vera, Lappas, Georg, Larijani, Bagher, Lateva, Mina P, Latt, Tint Swe, Laurenzi, Martino, Lazo-Porras, Maria, Le Coroller, Gwenaëlle, Le Nguyen Bao, Khanh, Lehtimäki, Terho, Lemogoum, Daniel, Leong, Elvynna, Leszczak, Justyna, Leung, Gabriel M, Li, Yanping, Liivak, Merike, Lim, Charlie, Lim, Wei-Yen, Lima-Costa, M Fernanda, Lin, Hsien-Ho, Lind, Lars, Litwin, Mieczyslaw, Liu, Liping, Liu, Xiaotian, Longo Abril, Guadalupe, Lopes, Oscar, Lopez-Garcia, Esther, López-Gil, José Francisco, Lopez, Tania, Lozano, José Eugenio, Lukrafka, Janice L, Luksiene, Dalia, Lundqvist, Annamari, Lunet, Nuno, Lunogelo, Charles, Lustigová, Michala, M'Buyamba-Kabangu, Jean-René, Machado-Coelho, George LL, Machado-Rodrigues, Aristides M, Macia, Enguerran, Madar, Ahmed A, Maestre, Gladys E, Maggi, Stefania, Magliano, Dianna J, Magnacca, Sara, Magriplis, Emmanuella, Mahasampath, Gowri, Maire, Bernard, Makdisse, Marcia, Malekpour, Mohammad-Reza, Malekzadeh, Fatemeh, Malekzadeh, 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Abstract

Adiposity can be measured using BMI (which is based on weight and height) as well as indices of abdominal adiposity. We examined the association between BMI and waist-to-height ratio (WHtR) within and across populations of different world regions and quantified how well these two metrics discriminate between people with and without hypertension.

Published
2024
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37. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Author

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Abstract

Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories.

Published
2024
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39. Evaluation of cognitive subdomains, 25-hydroxyvitamin D, and 1,25-dihydroxyvitamin D in the European Male Ageing Study

Author

Overman, Margot J., Pendleton, Neil, O’Neill, Terence W., Bartfai, Gyorgy, Casanueva, Felipe F., Finn, Joseph D., Forti, Gianni, Rastrelli, Giulia, Giwercman, Aleksander, Han, Thang S., Huhtaniemi, Ilpo T., Kula, Krzysztof, Lean, Michael E. J., Punab, Margus, Lee, David M., Correa, Elon S., Ahern, Tomas, Verschueren, Sabine M. P., Antonio, Leen, Gielen, Evelien, Rutter, Martin K., Vanderschueren, Dirk, Wu, Frederick C. W., Tournoy, Jos, and The EMAS Study Group

Published
2017
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41. Changes in prevalence of obesity and high waist circumference over four years across European regions: the European male ageing study (EMAS)

Author

Han, Thang S., Correa, Elon, Lean, Michael E. J., Lee, David M., O’Neill, Terrence W., Bartfai, György, Forti, Gianni, Giwercman, Aleksander, Kula, Krzysztof, Pendleton, Neil, Punab, Margus, Rutter, Martin K., Vanderschueren, Dirk, Huhtaniemi, Ilpo T., Wu, Frederick C. W., Casanueva, Felipe F., and and the EMAS Study Group

Published
2017
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42. Lower bone turnover and relative bone deficits in men with metabolic syndrome: a matter of insulin sensitivity? The European Male Ageing Study

Author

Laurent, M. R., Cook, M. J., Gielen, E., Ward, K. A., Antonio, L., Adams, J. E., Decallonne, B., Bartfai, G., Casanueva, F. F., Forti, G., Giwercman, A., Huhtaniemi, I. T., Kula, K., Lean, M. E. J., Lee, D. M., Pendleton, N., Punab, M., Claessens, F., Wu, F. C. W., Vanderschueren, D., Pye, S. R., O’Neill, T. W., and EMAS Group

Published
2016
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