Team-based working and employee well being:a cross-cultural comparison of United Kingdom and Hong Kong health services

This study examined the impact of team-based working, team structure, and job design on employee well-being (in term of job satisfaction and work stress) in staff working in healthcare organizations in Hong Kong. Cross-cultural differences in the impact of job design, team structure, and employee well-being outcomes between United Kingdom and Hong Kong were also investigated. A group of 197 staff from two Hong Kong hospitals were compared to a sample of 270 UK staff working in National Health Service organizations in the UK. Results showed that team structure and job design were significantly associated with greater employee satisfaction and lower stress for Hong Kong healthcare staff. Culture was also found to moderate the impact of team structure and job design on employee well-being. The findings suggest that although team structure and job design contribute to employee well-being, they have differential impacts across cultures. This provides insights to policy planning on building team-based organizations in the healthcare sector involving multinational collaboration.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Covariance functions for body weight from birth to maturity in Nellore cows

The objective of this study was to estimate (co)variance functions using random regression models on Legendre polynomials for the analysis of repeated measures of BW from birth to adult age. A total of 82,064 records from 8,145 females were analyzed. Different models were compared. The models included additive direct and maternal effects, and animal and maternal permanent environmental effects as random terms. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of animal age (cubic regression) were considered as random co-variables. Eight models with polynomials of third to sixth order were used to describe additive direct and maternal effects, and animal and maternal permanent environmental effects. Residual effects were modeled using 1 (i.e., assuming homogeneity of variances across all ages) or 5 age classes. The model with 5 classes was the best to describe the trajectory of residuals along the growth curve. The model including fourth- and sixth-order polynomials for additive direct and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects were the best. Estimates of (co) variance obtained with the multi-trait and random regression models were similar. Direct heritability estimates obtained with the random regression models followed a trend similar to that obtained with the multi-trait model. The largest estimates of maternal heritability were those of BW taken close to 240 d of age. In general, estimates of correlation between BW from birth to 8 yr of age decreased with increasing distance between ages.

Mecanismos de inflamação brônquica resultantes da exposição a factores ambientais

RESUMO Tratando-se a asma de uma doença respiratória, desde há várias décadas que tem sido abordada a hipótese de que factores ambientais, nomeadamente os relacionados com a qualidade do ar inalado, possam contribuir para o seu agravamento. Para além dos aeroalergenos, outros factores ambientais como a poluição atmosférica estarão associados às doenças respiratórias. O ar respirado contém uma variedade de poluentes atmosféricos, provenientes quer de fontes naturais quer de origem antropogénica, nomeadamente de actividades industriais, domésticas ou das emissões de veículos. Estes poluentes, tradicionalmente considerados como um problema de foro ambiental, têm sido cada vez mais encarados como um problema de saúde pública. Também a qualidade do ar interior, tem sido associada a queixas respiratórias, não só em termos ocupacionais mas também em exposições domésticas. Dentro dos principais poluentes, encontramos a matéria particulada (como as PM10), o O3, NO2, e os compostos orgânicos voláteis (COVs). Se é verdade que os três primeiros têm como principais fontes de exposição a combustão fóssil associada aos veículos automóveis, já os COVs (como o benzeno, tolueno, xileno, etilbenzeno e formaldeído) são poluentes mais característicos do ar interior. Os mecanismos fisiopatológicos subjacentes à agressão dos poluentes do ar não se encontram convenientemente esclarecidos. Pensa-se que após a sua inalação, induzam um grau crescente de stress oxidativo que será responsável pelo desenvolvimento da inflamação das vias aéreas. A progressão do stress oxidativo e da inflamação, associarse- ão posteriormente a lesão local (pulmonar) e sistémica. Neste trabalho pretendeu-se avaliar os efeitos da exposição individual a diversos poluentes, do ar exterior e interior, sobre as vias aéreas, recorrendo a parâmetros funcionais, inflamatórios e do estudo do stress oxidativo. Neste sentido, desenvolveu-se um estudo de painel na cidade de Viseu, em que foram acompanhadas durante 18 meses, 51 crianças com história de sibilância, identificadas pelo questionário do estudo ISAAC. As crianças foram avaliadas em quatro Visitas (quatro medidas repetidas), através de diversos exames, que incluíram execução de espirometria com broncodilatação, medição ambulatória do PEF, medição de FENO e estudo do pH no condensado brônquico do ar exalado. O estudo dos 8-isoprostanos no condensado brônquico foi efectuado somente em duas Visitas, e o do doseamento de malonaldeído urinário somente na última Visita. Para além da avaliação do grau de infestação de ácaros do pó do colchão, para cada criança foi calculado o valor de exposição individual a PM10, O3, NO2, benzeno, tolueno, xileno, etilbenzeno e formaldeído, através de uma complexa metodologia que envolveu técnicas de modelação associadas a medições directas do ar interior (na casa e escola da criança) e do ar exterior. Para a análise de dados foram utilizadas equações de estimação generalizadas com uma matriz de correlação de trabalho uniforme, com excepção do estudo das associações entre poluentes, 8-isoprostanos e malonaldeído. Verificou-se na análise multivariável a existência de uma associação entre o agravamento dos parâmetros espirométricos e a exposição aumentada a PM10, NO2, benzeno, tolueno e etilbenzeno. Foram também encontradas associações entre diminuição do pH do EBC e exposição crescente a PM10, NO2, benzeno e etilbenzeno e associações entre valores aumentados de FENO e exposição a etilbenzeno e tolueno. O benzeno, o tolueno e o etilbenzeno foram associados com maior recurso a broncodilatador nos 6 meses anteriores à Visita e o tolueno com deslocações ao serviço de urgência. Os resultados dos modelos de regressão que incluíram o efeito do poluente ajustado para o grau de infestação de ácaros do pó foram, de uma forma geral, idênticos ao da análise multivariável anterior, com excepção das associações para com o FENO. Nos modelos de exposição com dois poluentes, com o FEV1 como variável resposta, somente o benzeno persistiu com significado estatístico. No modelo com dois poluentes tendo o pH do EBC como variável resposta, somente persistiram as PM10. Os 8-isoprostanos correlacionaram-se com alguns COVs, designadamente etilbenzeno, xileno, tolueno e benzeno. Os valores de malonaldeído urinário não se correlacionaram com os valores de poluentes. Verificou-se no entanto que de uma forma geral, e em particular mais uma vez para os COVs, as crianças mais expostas a poluentes, apresentaram valores superiores de malonaldeído na urina. Verificou-se que os poluentes do ar em geral, e os COVs em particular, se associaram com uma deterioração das vias aéreas. A exposição crescente a poluentes associou-se não só com obstrução brônquica, mas também com FENO aumentado e maior acidez das vias aéreas. A exposição crescente a COVs correlacionou-se com um maior stress oxidativo das vias aéreas (medido pelos 8-isoprostanos). As crianças com exposição superior a COVs apresentaram maiores valores de malonaldeído urinário. Este trabalho sugere uma associação entre exposição a poluentes, inflamação das vias aéreas e stress oxidativo. Vem reforçar o interesse dos poluentes do ar, nomeadamente os associados a ambientes interiores, frequentemente esquecidos e que poderão ser explicativos do agravamento duma criança com sibilância.-----------ABSTRACT: Asthma is a chronic respiratory disease that could be influenced by environmental factors, as allergens and air pollutants. The air breathed contains a diversity of air pollutants, both from natural or anthropogenic sources. Atmospheric pollution, traditionally considered an environmental problem, is nowadays looked as an important public health problem. Indoor air pollutants are also related with respiratory diseases, not only in terms of occupational exposures but also in domestic activities. Particulate matter (such as PM10), O3, NO2 and volatile organic compounds (VOCs) are the main air pollutants. The main source for PM10, O3, NO2 exposure is traffic exhaust while for VOCs (such as benzene, toluene, xylene, ethylbenzene and phormaldehyde) the main sources for exposure are located in indoor environments. The pathophysiologic mechanisms underlying the aggression of air pollutants are not properly understood. It is thought that after inhalation, air pollutants could induce oxidative stress, which would be responsible for airways inflammation. The progression of oxidative stress and airways inflammation, would contribute for the local and systemic effects of the air pollutants. The present study aimed to evaluate the effects of individual exposure to various pollutants over the airways, through lung function tests, inflammatory and oxidative stress biomarkers. In this sense, we developed a panel study in the city of Viseu, that included 51 children with a history of wheezing. Those children that were identified by the ISAAC questionnaire, were followed for 18 months. Children were assessed four times (four repeated measures) through the following tests: spirometry with bronchodilation test, PEF study, FENO evaluation and exhaled breath condensate pH measurement. 8-isoprostane in the exhaled breath condensate were also measured but only in two visits. Urinary malonaldehyde measurement was performed only in the last visit. Besides the assessment of the house dust mite infestation, we calculated for each child the value of individual exposure to a wide range of pollutants: PM10, O3, NO2, benzene, toluene, xylene, ethyl benzene and formaldehyde. This strategy used a complex methodology that included air pollution modelling techniques and direct measurements indoors (homes and schools) and outdoors. Generalized estimating equations with an exchangeable working correlation matrix were used for the analysis of the data. Exceptions were for the study of associations between air pollutants, malonaldehyde and 8-isoprostanes. In the multivariate analysis we found an association between worsening of spirometric outcomes and increased exposure to PM10, NO2, benzene, toluene and ethylbenzene. In the multivariate analysis we found also negative associations between EBC pH and exposure to PM10, NO2, benzene, ethylbenzene and positive associations between FENO and exposure to ethylbenzene and toluene. Benzene, toluene and ethylbenzene were associated with increased use of bronchodilator in the 6 months prior to the visit and toluene with emergency department visits. Results of the regression models that included also the effect of the pollutant adjusted for the degree of infestation to house dust mites, were identical to the previous models. Exceptions were for FENO associations. In the two-pollutant models, with the FEV1 as dependent variable, only benzene persisted with statistical significance. In the two pollutant model with pH of EBC as dependent variable, only PM10 persisted. 8-isoprostanes were well correlated with some VOCs, namely with ethylbenzene, xylene, toluene and benzene. Urinary malonaldehyde did not present any correlation with air pollutants exposure. However, those children more exposed to air pollutants (namely to VOCs), presented higher values of malonaldehyde. It was found that air pollutants in general, and namely VOCs, were associated with deterioration of the airways. The increased exposure to air pollutants was associated not only with airways obstruction, but also with increased FENO and higher acidity of the airways. The increased exposure to VOCs was correlated with increased airways oxidative stress (measured by 8-isoprostane). Children with higher levels of exposure to VOCs had higher values of urinary malonaldehyde. This study suggests a relation between air pollution, airways inflammation and oxidative stress. It suggests also that attention should be dedicated to air quality as air pollutants could cause airways deterioration.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Class of correlated random networks with hidden variables

We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.

Outcome of smoking cessation counselling of HIV-positive persons by HIV care physicians.

OBJECTIVES: Smoking is the most prevalent modifiable risk factor for cardiovascular diseases among HIV-positive persons. We assessed the effect on smoking cessation of training HIV care physicians in counselling. METHODS: The Swiss HIV Cohort Study (SHCS) is a multicentre prospective observational database. Our single-centre intervention at the Zurich centre included a half day of standardized training for physicians in counselling and in the pharmacotherapy of smokers, and a physicians' checklist for semi-annual documentation of their counselling. Smoking status was then compared between participants at the Zurich centre and other institutions. We used marginal logistic regression models with exchangeable correlation structure and robust standard errors to estimate the odds of smoking cessation and relapse. RESULTS: Between April 2000 and December 2010, 11 056 SHCS participants had 121 238 semi-annual visits and 64 118 person-years of follow-up. The prevalence of smoking decreased from 60 to 43%. During the intervention at the Zurich centre from November 2007 to December 2009, 1689 participants in this centre had 6068 cohort visits. These participants were more likely to stop smoking [odds ratio (OR) 1.23; 95% confidence interval (CI) 1.07-1.42; P=0.004] and had fewer relapses (OR 0.75; 95% CI 0.61-0.92; P=0.007) than participants at other SHCS institutions. The effect of the intervention was stronger than the calendar time effect (OR 1.19 vs. 1.04 per year, respectively). Middle-aged participants, injecting drug users, and participants with psychiatric problems or with higher alcohol consumption were less likely to stop smoking, whereas persons with a prior cardiovascular event were more likely to stop smoking. CONCLUSIONS: An institution-wide training programme for HIV care physicians in smoking cessation counselling led to increased smoking cessation and fewer relapses.

Low adiponectin is associated with increased ambulatory pulse pressure and activation of the renin-angiotensin system in subjects of African descent

Purpose: Adiponectin, arterial stiffness, as well components of the renin-angiotensin system are associated with cardiovascular risk. This study was aimed to investigate whether plasma adiponectin was directly linked with pulse pressure (PP), as a marker for arterial stiffness, and the renin-angiotensin system (RAS). Methods and materials: A family-based study in subjects of African descent enriched with hypertensive patients was carried out in the Seychelles. Fasting plasma adiponectin was determined by ELISA, plasma renin activity according to the antibody-trapping principle and plasma aldosterone by radioimmunoassay. Daytime ambulatory blood pressure (BP) was measured using Diasys Integra devices. PP was calculated as the difference between systolic and diastolic BP. The association of adiponectin with PP, plasma renin activity and plasma aldosterone were analyzed using generalized estimating equations with a gaussian family link and an exchangeable correlation structure to account for familial aggregation. Results: Data from 335 subjects from 73 families (152 men, 183 women) were available. Men and women had mean (SD) age of 45.4 ± 11.1 and 47.3 ± 12.4 years, BMI of 26.3 ± 4.4 and 27.8 ± 5.1 kg/m2, daytime systolic/diastolic BP of 132.6 ± 15.4 / 86.1 ± 10.9 and 130 ± 17.6 / 83.4 ± 11.1 mmHg, and daytime PP of 46.5 ± 9.9 and 46.7 ± 10.7 mmHg, respectively. Plasma adiponectin was 4.4± 3.04 ng/ml in men and 7.39 ± 5.44 ng/ml in women (P <0.001). After adjustment for age, sex and BMI, log-transformed adiponectin was negatively associated with daytime PP (-0.009 ± 0.003, P = 0.004), plasma renin activity (-0.248 ± 0.080, P = 0.002) and plasma aldosterone (-0.004 ± 0.002, P = 0.014). Conclusion: Low adiponectin is associated with increased ambulatory PP and RAS activation in subjects of African descent. Our data are consistent with the observation that angiotensin II receptor blockers increase adiponectin in humans.

Étude des maxima de champs gaussiens corrélés.

Ce mémoire porte sur l’étude des maxima de champs gaussiens. Plus précisément, l’étude portera sur la convergence en loi, la convergence du premier ordre et la convergence du deuxième ordre du maximum d’une collection de variables aléatoires gaussiennes. Les modèles de champs gaussiens présentés sont le modèle i.i.d., le modèle hiérarchique et le champ libre gaussien. Ces champs gaussiens diffèrent par le degré de corrélation entre les variables aléatoires. Le résultat principal de ce mémoire sera que la convergence en probabilité du premier ordre du maximum est la même pour les trois modèles. Quelques résultats de simulations seront présentés afin de corroborer les résultats théoriques obtenus.

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.

Quantifying uncertainty in critical loads: (B) acidity mass balance critical loads on a sensitive site

This paper reports an uncertainty analysis of critical loads for acid deposition for a site in southern England, using the Steady State Mass Balance Model. The uncertainty bounds, distribution type and correlation structure for each of the 18 input parameters was considered explicitly, and overall uncertainty estimated by Monte Carlo methods. Estimates of deposition uncertainty were made from measured data and an atmospheric dispersion model, and hence the uncertainty in exceedance could also be calculated. The uncertainties of the calculated critical loads were generally much lower than those of the input parameters due to a "compensation of errors" mechanism - coefficients of variation ranged from 13% for CLmaxN to 37% for CL(A). With 1990 deposition, the probability that the critical load was exceeded was > 0.99; to reduce this probability to 0.50, a 63% reduction in deposition is required; to 0.05, an 82% reduction. With 1997 deposition, which was lower than that in 1990, exceedance probabilities declined and uncertainties in exceedance narrowed as deposition uncertainty had less effect. The parameters contributing most to the uncertainty in critical loads were weathering rates, base cation uptake rates, and choice of critical chemical value, indicating possible research priorities. However, the different critical load parameters were to some extent sensitive to different input parameters. The application of such probabilistic results to environmental regulation is discussed.

The interannual variability of energy transports within and over the Atlantic Ocean in a coupled climate model

To gain a new perspective on the interaction of the Atlantic Ocean and the atmosphere, the relationship between the atmospheric and oceanic meridional energy transports is studied in a version of HadCM3, the U.K. Hadley Centre's coupled climate model. The correlation structure of the energy transports in the atmosphere and Atlantic Ocean as a function of latitude, and the cross correlation between the two systems are analyzed. The processes that give rise to the correlations are then elucidated using regression analyses. In northern midlatitudes, the interannual variability of the Atlantic Ocean energy transport is dominated by Ekman processes. Anticorrelated zonal winds in the subtropics and midlatitudes, particularly associated with the North Atlantic Oscillation (NAO), drive anticorrelated meridional Ekman transports. Variability in the atmospheric energy transport is associated with changes in the stationary waves, but is only weakly related to the NAO. Nevertheless, atmospheric driving of the oceanic Ekman transports is responsible for a bipolar pattern in the correlation between the atmosphere and Atlantic Ocean energy transports. In the Tropics, the interannual variability of the Atlantic Ocean energy transport is dominated by an adjustment of the tropical ocean to coastal upwelling induced along the Venezuelan coast by a strengthening of the easterly trade winds. Variability in the atmospheric energy transport is associated with a cross-equatorial meridional overturning circulation that is only weakly associated with variability in the trade winds along the Venezuelan coast. In consequence, there is only very limited correlation between the atmosphere and Atlantic Ocean energy transports in the Tropics of HadCM3

O_3-N_2O correlations from the Atmospheric Chemistry Experiment: revisiting a diagnostic of transport and chemistry in the stratosphere

Our knowledge of stratospheric O3-N2O correlations is extended, and their potential for model-measurement comparison assessed, using data from the Atmospheric Chemistry Experiment (ACE) satellite and the Canadian Middle Atmosphere Model (CMAM). ACE provides the first comprehensive data set for the investigation of interhemispheric, interseasonal, and height-resolved differences of the O_3-N_2O correlation structure. By subsampling the CMAM data, the representativeness of the ACE data is evaluated. In the middle stratosphere, where the correlations are not compact and therefore mainly reflect the data sampling, joint probability density functions provide a detailed picture of key aspects of transport and mixing, but also trace polar ozone loss. CMAM captures these important features, but exhibits a displacement of the tropical pipe into the Southern Hemisphere (SH). Below about 21 km, the ACE data generally confirm the compactness of the correlations, although chemical ozone loss tends to destroy the compactness during late winter/spring, especially in the SH. This allows a quantitative comparison of the correlation slopes in the lower and lowermost stratosphere (LMS), which exhibit distinct seasonal cycles that reveal the different balances between diabatic descent and horizontal mixing in these two regions in the Northern Hemisphere (NH), reconciling differences found in aircraft measurements, and the strong role of chemical ozone loss in the SH. The seasonal cycles are qualitatively well reproduced by CMAM, although their amplitude is too weak in the NH LMS. The correlation slopes allow a "chemical" definition of the LMS, which is found to vary substantially in vertical extent with season.

Data assimilation with correlated observation errors: experiments with a 1-D shallow water model

Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information. As operational centres move towards higher-resolution forecasting, there is a requirement to retain data providing detail on appropriate scales. Thus an alternative approach to dealing with observation error correlations is needed. In this article, we consider several approaches to approximating observation error correlation matrices: diagonal approximations, eigendecomposition approximations and Markov matrices. These approximations are applied in incremental variational assimilation experiments with a 1-D shallow water model using synthetic observations. Our experiments quantify analysis accuracy in comparison with a reference or ‘truth’ trajectory, as well as with analyses using the ‘true’ observation error covariance matrix. We show that it is often better to include an approximate correlation structure in the observation error covariance matrix than to incorrectly assume error independence. Furthermore, by choosing a suitable matrix approximation, it is feasible and computationally cheap to include error correlation structure in a variational data assimilation algorithm.