Association of respiratory symptoms and lung function with occupation in the multinational Burden of Obstructive Lung Disease (BOLD) study

Background Chronic obstructive pulmonary disease has been associated with exposures in the workplace. We aimed to assess the association of respiratory symptoms and lung function with occupation in the Burden of Obstructive Lung Disease study. Methods We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income. Results Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19–1.94), wheeze (OR 1.37, 95% CI 1.16–1.63) and dyspnoea (OR 1.83, 95% CI 1.53–2.20), but not lower FVC (β=0.02 L, 95% CI −0.02–0.06 L) or lower FEV1/FVC (β=0.04%, 95% CI −0.49–0.58%). Some findings differed by sex and gross national income. Conclusion At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.publishedVersio

Cohort Profile: Burden of Obstructive Lung Disease (BOLD) study

The Burden of Obstructive Lung Disease (BOLD) study was established to assess the prevalence of chronic airflow obstruction, a key characteristic of chronic obstructive pulmonary disease, and its risk factors in adults (≥40 years) from general populations across the world. The baseline study was conducted between 2003 and 2016, in 41 sites across Africa, Asia, Europe, North America, the Caribbean and Oceania, and collected high-quality pre- and post-bronchodilator spirometry from 28 828 participants. The follow-up study was conducted between 2019 and 2021, in 18 sites across Africa, Asia, Europe and the Caribbean. At baseline, there were in these sites 12 502 participants with high-quality spirometry. A total of 6452 were followed up, with 5936 completing the study core questionnaire. Of these, 4044 also provided high-quality pre- and post-bronchodilator spirometry. On both occasions, the core questionnaire covered information on respiratory symptoms, doctor diagnoses, health care use, medication use and ealth status, as well as potential risk factors. Information on occupation, environmental exposures and diet was also collected

Accelerating the CBFM-enhanced jacobi method

© 2017 IEEE. The Characteristic Basis Function Method (CBFM)-enhanced Jacobi method has been introduced as an improvement to the standard iterative Jacobi method for finite array analysis. This technique is a domain decomposition approach based on the Method of Moments (MoM) formulation. In some cases, e.g. array environments with a low degree of mutual coupling, the runtime benefit of the CBFM-enhanced Jacobi method is not as significant when compared to that of the Jacobi technique. The reason for this is that additional computational overhead is introduced during each iteration, i.e. setting up and solving the CBFM reduced matrix equation. In this work the adaptive cross approximation (ACA) algorithm is used to accelerate this step in the CBFM-enhanced Jacobi method

Introducing the Iterative Domain Green's Function Method for finite array analysis

© 2016 IEEE. The purpose of this work Is to Introduce the Iterative Domain Green's Function Method (DGFM) that may be used for the analysis of large, disjoint finite antenna arrays. The iterative DGFM presents an improvement over the conventional DGFM in terms of accuracy. The convergence rate of the technique will be illustrated at the hand of an example

A multiphysics analysis of dish reflector antennas for radio astronomy applications

© 2016 European Association of Antennas and Propagation. This work considers a combined structural-electromagnetic analysis of large dish reflector antennas typically used in radio astronomy. The effect of gravitational deformation on the radio telescope is quantified by a structural analysis conducted with a finite element solver. The deformed geometry is then analysed using a computational electromagnetic package from which the performance degradation can be assessed. This offers key insights into the operation of the radio telescope under the influence of external forces, such as gravity

Enhancing the Jacobi method with the CBFM for array antenna analysis

© 2017 IEEE. The analysis of sparse, disjoint finite antenna array structures is considered in this work. The Method-of-Moments (MoM) based CBFM-enhanced Jacobi technique is presented, and offers an improvement over the standard iterative Jacobi method in terms of convergence and accuracy. By applying the Characteristic Basis Function Method (CBFM) during each iteration the effect of mutual coupling between the array elements can be accounted for more accurately than in the standard Jacobi method. The convergence rate of the method is found to be better than that of the Jacobi technique

Comparison of the iterative jacobi method and the iterative Domain Green'S Function Method for finite array analysis

© 2016 European Association of Antennas and Propagation. The purpose of this work is to compare two iterative techniques that may be used for the analysis of large, disjoint finite antenna arrays, viz. the iterative Jacobi method and the iterative Domain Green's Function Method. These methods are conceptually similar, in that they offer alternative ways to improve non-local current distributions during the iterative process. The error convergence of each method will be studied at the hand of an example

The CBFM-Enhanced Jacobi Method for Efficient Finite Antenna Array Analysis

© 2017 IEEE. An enhancement to the iterative Jacobi technique with the characteristic basis function method is presented. The resulting method is intended for efficient method of moments (MoM)-based analysis of large, disjoint finite antenna arrays. The enhancement improves the convergence rate of the Jacobi method by better accounting for mutual coupling between array elements. This involves solving a small, global problem at each iterative step, using macrobasis functions that are iteratively generated. Results are presented, and it is found that the proposed method can recover fast convergence in cases where the Jacobi method diverges or converges slowly. The proposed method also converges significantly faster than a conventional, preconditioned, iterative solution of the MoM matrix equation

Comparison of the iterative jacobi method and the iterative Domain Green\u27S Function Method for finite array analysis

The purpose of this work is to compare two iterative techniques that may be used for the analysis of large, disjoint finite antenna arrays, viz. the iterative Jacobi method and the iterative Domain Green\u27s Function Method. These methods are conceptually similar, in that they offer alternative ways to improve non-local current distributions during the iterative process. The error convergence of each method will be studied at the hand of an example