Obesity continues to be a major health risk for Danish seafarers and fishermen

Background. In addition to the well-known medical consequences of overweight, severe obesity may also constitute a safety problem on board a ship in case of an emergency. The purpose of this study was to determine the current extent of the problem of overweight among Danish seafarers and fishermen and to follow-up the situation since a previous survey. The aim was to identify the main target groups and determine the need for continuous intervention. Material and methods. Data on height and weight were obtained from the mandatory health examinations of seafarers and fishermen. A total of 2,101 seafarers were included in the study. Body Mass Index (BMI) was calculated for each individual seafarer. Data from two other surveys were used as reference. Results. A total of 1,379 (66%) of all tested subjects were overweight. Among the male officers and ratings, the relative risk of being overweight was 1.33 (1.25–1.38) and 1.30 (1.22–1.38), respectively. The relative risk for fishermen was 1.45 (1.25–1.66) and for maritime students and trainees 1.44 (1.25–1.66). The female seafarers had a relative risk of being overweight of 1.42 (1.23–1.65). There were a statistical significantly increased number of overweight merchant seafarers since 2001/2002. Discussion. The study shows that Danish merchant seafarers have a major and significantly increasing overweight problem. Among fishermen, overweight was even more frequent. Overweight constitutes a threat not only to their health, but also to their career at sea. The larger than expected incidence of overweight among new employees in the industry provides particular cause for concern. The causes of the problem are complex and interventions need to be broad. (Int Marit Health 2011; 62, 2: 98–103

Obesity continues to be a major health risk for Danish seafarers and fishermen

Background. In addition to the well-known medical consequences of overweight, severe obesity may also constitute a safety problem on board a ship in case of an emergency. The purpose of this study was to determine the current extent of the problem of overweight among Danish seafarers and fishermen and to follow-up the situation since a previous survey. The aim was to identify the main target groups and determine the need for continuous intervention. Material and methods. Data on height and weight were obtained from the mandatory health examinations of seafarers and fishermen. A total of 2,101 seafarers were included in the study. Body Mass Index (BMI) was calculated for each individual seafarer. Data from two other surveys were used as reference. Results. A total of 1,379 (66%) of all tested subjects were overweight. Among the male officers and ratings, the relative risk of being overweight was 1.33 (1.25–1.38) and 1.30 (1.22–1.38), respectively. The relative risk for fishermen was 1.45 (1.25–1.66) and for maritime students and trainees 1.44 (1.25–1.66). The female seafarers had a relative risk of being overweight of 1.42 (1.23–1.65). There were a statistical significantly increased number of overweight merchant seafarers since 2001/2002. Discussion. The study shows that Danish merchant seafarers have a major and significantly increasing overweight problem. Among fishermen, overweight was even more frequent. Overweight constitutes a threat not only to their health, but also to their career at sea. The larger than expected incidence of overweight among new employees in the industry provides particular cause for concern. The causes of the problem are complex and interventions need to be broad. (Int Marit Health 2011; 62, 2: 98–103

Use of GIS and Exposure Modeling as Tools in a Study of Cancer Incidence in a Population Exposed to Airborne Dioxin

In environmental health research there is a recognized need to develop improved epidemiologic and statistical methods for rapid assessment of relationships between environment and health. Exposure assessment is identified as a major challenge needing attention. In this study an exposure simulation model was used to delimit almost exactly in space and time an urban population exposed to airborne dioxin. A geographic information system (GIS) was used as the electronic environment in which to link the exposure model with the demographic, migration, and cancer data of the exposed population. This information is available in Denmark on an individual basis. Standardized incidence ratios (SIRs) for both men and women in 10-year age bands were calculated for three different exposure areas. Migration patterns were outlined. SIRs showed no excess of cancer incidences during the time span chosen (13 years; 1986–1998) in the whole exposed area or in the medium or higher polluted areas. The exposure model appeared very useful in selection of the appropriate exposure areas. The integration of the model in a GIS together with individual data on addresses, sex, age, migration, and information from routine health statistics (Danish Cancer Registry) proved its usefulness in demarking the exposed population and identifying the cancers related to that population. Less than one-third of the study population lived at the same address after 13 years of observation, and only half were still residing in the area, indicating migration of people as a major misclassification

Improved model identification for non-linear systems using a random subsampling and multifold modelling (RSMM) approach

In non-linear system identification, the available observed data are conventionally partitioned into two parts: the training data that are used for model identification and the test data that are used for model performance testing. This sort of 'hold-out' or 'split-sample' data partitioning method is convenient and the associated model identification procedure is in general easy to implement. The resultant model obtained from such a once-partitioned single training dataset, however, may occasionally lack robustness and generalisation to represent future unseen data, because the performance of the identified model may be highly dependent on how the data partition is made. To overcome the drawback of the hold-out data partitioning method, this study presents a new random subsampling and multifold modelling (RSMM) approach to produce less biased or preferably unbiased models. The basic idea and the associated procedure are as follows. First, generate K training datasets (and also K validation datasets), using a K-fold random subsampling method. Secondly, detect significant model terms and identify a common model structure that fits all the K datasets using a new proposed common model selection approach, called the multiple orthogonal search algorithm. Finally, estimate and refine the model parameters for the identified common-structured model using a multifold parameter estimation method. The proposed method can produce robust models with better generalisation performance

Functional variation in the arginine vasopressin 2 receptor as a modifier of human plasma von Willebrand factor levels\ud

Objectives: Stimulation of arginine vasopressin 2 receptor (V2R) with arginine vasopressin (AVP) results in a rise in von Willebrand factor (VWF) and factor VIII plasma levels. We hypothesized that gain-of-function variations in the V2R gene (AVPR2) would lead to higher plasma levels of VWF and FVIII. Methods and Results: We genotyped the control populations of two population-based studies for four AVPR2 variations: a-245c, G12E, L309L, and S331S. Rare alleles of a-245c, G12E, and S331S, which were in linkage disequilibrium, were associated with higher VWF propeptide, VWF and FVIII levels. The functionality of the G12E variant was studied in stably transfected MDCKII cells, expressing constructs of either 12G-V2R or 12E-V2R. Both V2R variants were fully glycosylated and expressed on the basolateral membrane. The binding affinity of V2R for AVP was increased three-fold in 12E-V2R–green fluorescent protein (GFP) cells, which is in accordance with increased levels of VWF propeptide associated with the 12E variant. The dissociation constant (KD) was 4.5 nm [95% confidence interval (CI) 3.6–5.4] for 12E-V2R–GFP and 16.5 nm (95% CI 10.1–22.9) for 12G-V2R–GFP. AVP-induced cAMP generation was enhanced in 12E-V2R–GFP cells. Conclusions: The 12E-V2R variant has increased binding affinity for AVP, resulting in increased signal transduction, and is associated with increased levels of VWF propeptide, VWF, and FVII

Model confidence sets and forecast combination: an application to age-specific mortality

Background: Model averaging combines forecasts obtained from a range of models, and it often produces more accurate forecasts than a forecast from a single model. Objective: The crucial part of forecast accuracy improvement in using the model averaging lies in the determination of optimal weights from a finite sample. If the weights are selected sub-optimally, this can affect the accuracy of the model-averaged forecasts. Instead of choosing the optimal weights, we consider trimming a set of models before equally averaging forecasts from the selected superior models. Motivated by Hansen et al. (2011), we apply and evaluate the model confidence set procedure when combining mortality forecasts. Data & Methods: The proposed model averaging procedure is motivated by Samuels and Sekkel (2017) based on the concept of model confidence sets as proposed by Hansen et al. (2011) that incorporates the statistical significance of the forecasting performance. As the model confidence level increases, the set of superior models generally decreases. The proposed model averaging procedure is demonstrated via national and sub-national Japanese mortality for retirement ages between 60 and 100+. Results: Illustrated by national and sub-national Japanese mortality for ages between 60 and 100+, the proposed model-average procedure gives the smallest interval forecast errors, especially for males. Conclusion: We find that robust out-of-sample point and interval forecasts may be obtained from the trimming method. By robust, we mean robustness against model misspecification

Adaptive cluster expansion for the inverse Ising problem: convergence, algorithm and tests

We present a procedure to solve the inverse Ising problem, that is to find the interactions between a set of binary variables from the measure of their equilibrium correlations. The method consists in constructing and selecting specific clusters of variables, based on their contributions to the cross-entropy of the Ising model. Small contributions are discarded to avoid overfitting and to make the computation tractable. The properties of the cluster expansion and its performances on synthetic data are studied. To make the implementation easier we give the pseudo-code of the algorithm.Comment: Paper submitted to Journal of Statistical Physic

Associated charged Higgs and W boson production in the MSSM at the CERN Large Hadron Collider

We investigate the viability of observing charged Higgs bosons (H^+/-) produced in association with W bosons at the CERN Large Hadron Collider, using the leptonic decay H^+ -> tau^+ nu_tau and hadronic W-decay, within different scenarios of the Minimal Supersymmetric Standard Model (MSSM) with both real and complex parameters. Performing a parton level study we show how the irreducible Standard Model background from W+2 jets can be controlled by applying appropriate cuts and find that the size of a possible signal depends on the cuts needed to suppress QCD backgrounds and misidentifications. In the standard maximal mixing scenario of the MSSM we find a viable signal for large tan(beta) and intermediate H^+/- masses (~m_t) when using optimistic cuts whereas for more pessimistic ones we only find a viable signal for very large tan(beta) (>~50). We have also investigated a special class of MSSM scenarios with large mass-splittings among the heavy Higgs bosons where the cross-section can be resonantly enhanced by factors up to one hundred, with a strong dependence on the CP-violating phases. Even so we find that the signal after cuts remains small except for small masses (~< m_t) with optimistic cuts. Finally, in all the scenarios we have investigated we have only found small CP-asymmetries.Comment: 28 pages, 12 figures, version to appear in Euro. Phys. J.

Density functional method for nonequilibrium electron transport

We describe an ab initio method for calculating the electronic structure, electronic transport, and forces acting on the atoms, for atomic scale systems connected to semi-infinite electrodes and with an applied voltage bias. Our method is based on the density functional theory (DFT) as implemented in the well tested Siesta approach (which uses non-local norm-conserving pseudopotentials to describe the effect of the core electrons, and linear combination of finite-range numerical atomic orbitals to describe the valence states). We fully deal with the atomistic structure of the whole system, treating both the contact and the electrodes on the same footing. The effect of the finite bias (including selfconsistency and the solution of the electrostatic problem) is taken into account using nonequilibrium Green's functions. We relate the nonequilibrium Green's function expressions to the more transparent scheme involving the scattering states. As an illustration, the method is applied to three systems where we are able to compare our results to earlier ab initio DFT calculations or experiments, and we point out differences between this method and existing schemes. The systems considered are: (1) single atom carbon wires connected to aluminum electrodes with extended or finite cross section, (2) single atom gold wires, and finally (3) large carbon nanotube systems with point defects.Comment: 18 pages, 23 figure