Trends in socioeconomic inequalities in mortality in small areas of 33 Spanish cities

Background: In Spain, several ecological studies have analyzed trends in socioeconomic inequalities in mortality from all causes in urban areas over time. However, the results of these studies are quite heterogeneous finding, in general, that inequalities decreased, or remained stable. Therefore, the objectives of this study are: (1) to identify trends in geographical inequalities in all-cause mortality in the census tracts of 33 Spanish cities between the two periods 1996–1998 and 2005–2007; (2) to analyse trends in the relationship between these geographical inequalities and socioeconomic deprivation; and (3) to obtain an overall measure which summarises the relationship found in each one of the cities and to analyse its variation over time.Methods: Ecological study of trends with 2 cross-sectional cuts, corresponding to two periods of analysis: 1996–1998 and 2005–2007. Units of analysis were census tracts of the 33 Spanish cities. A deprivation index calculated for each census tracts in all cities was included as a covariate. A Bayesian hierarchical model was used to estimate smoothed Standardized Mortality Ratios (sSMR) by each census tract and period. The geographical distribution of these sSMR was represented using maps of septiles. In addition, two different Bayesian hierarchical models were used to measure the association between all-cause mortality and the deprivation index in each city and period, and by sex: (1) including the association as a fixed effect for each city; (2) including the association as random effects. In both models the data spatial structure can be controlled within each city. The association in each city was measured using relative risks (RR) and their 95 % credible intervals (95 % CI).Results: For most cities and in both sexes, mortality rates decline over time. For women, the mortality and deprivation patterns are similar in the first period, while in the second they are different for most cities. For men, RRs remain stable over time in 29 cities, in 3 diminish and in 1 increase. For women, in 30 cities, a non-significant change over time in RR is observed. However, in 4 cities RR diminishes. In overall terms, inequalities decrease (with a probability of 0.9) in both men (RR¿=¿1.13, 95 % CI¿=¿1.12–1.15 in the 1st period; RR¿=¿1.11, 95 % CI¿=¿1.09–1.13 in the 2nd period) and women (RR¿=¿1.07, 95 % CI¿=¿1.05–1.08 in the 1st period; RR¿=¿1.04, 95 % CI¿=¿1.02–1.06 in the 2nd period).Conclusions: In the future, it is important to conduct further trend studies, allowing to monitoring trends in socioeconomic inequalities in mortality and to identify (among other things) temporal factors that may influence these inequalities

Modelling the covariance structure in marginal multivariate count models: Hunting in Bioko Island.

The main goal of this article is to present a flexible statistical modelling framework to deal with multivariate count data along with longitudinal and repeated measures structures. The covariance structure for each response variable is defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. In order to specify the joint covariance matrix for the multivariate response vector, the generalized Kronecker product is employed. We take into account the count nature of the data by means of the power dispersion function associated with the Poisson–Tweedie distribution. Furthermore, the score information criterion is extended for selecting the components of the matrix linear predictor. We analyse a data set consisting of prey animals (the main hunted species, the blue duiker Philantomba monticola and other taxa) shot or snared for bushmeat by 52 commercial hunters over a 33-month period in Pico Basilé, Bioko Island, Equatorial Guinea. By taking into account the severely unbalanced repeated measures and longitudinal structures induced by the hunters and a set of potential covariates (which in turn affect the mean and covariance structures), our method can be used to indicate whether there was statistical evidence of a decline in blue duikers and other species hunted during the study period. Determining whether observed drops in the number of animals hunted are indeed true is crucial to assess whether species depletion effects are taking place in exploited areas anywhere in the world. We suggest that our method can be used to more accurately understand the trajectories of animals hunted for commercial or subsistence purposes and establish clear policies to ensure sustainable hunting practices

Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing

This article explores how to incorporate a spatial dependence effect into the standard multilevel modeling (MLM). The proposed method is particularly well suited to the analysis of geographically clustered survey data where individuals are nested in geographical areas. Drawing on multivariate conditional autoregressive models, we develop a spatial random slope MLM approach to account for the within-group dependence among individuals in the same area and the spatial dependence between areas simultaneously. Our approach improves on recent methodological advances in the integrated spatial and MLM literature, offering greater flexibility in terms of model specification by allowing regression coefficients to be spatially varied. Bayesian Markov chain Monte Carlo (MCMC) algorithms are derived to implement the proposed model. Using two-level travel satisfaction data in Beijing, we apply the proposed approach as well as the standard nonspatial random slope MLM to investigate subjective travel satisfaction of residents and its determinants. Model comparison results show strong evidence that the proposed method produces a significant improvement against a nonspatial random slope MLM. A fairly large spatial correlation parameter suggests strong spatial dependence in district-level random effects. Moreover, spatial patterns of district-level random effects of locational variables have been identified, with high and low values clustering together

Are smartphone applications (App) useful to improve hearing?

The objective of the study is to assess whether a smartphone application (App) designed to improve hearing can improve audiological performance in patients with normal hearing and with varying grades of hearing loss (HL). This is a multicentre prospective analytical study. We performed a battery of audiological tests consisting of pure tone audiometry (PTA) and a word recognition test (WRT) in quiet and in noise at different signal-to-noise ratio (SNR) using or not a smartphone App. Intra-subject results under both conditions were compared to determine the App\u2019s effect on hearing. A survey was also carried out to obtain data on subjective hearing experience with the App. We recruited 55 HL patients and 13 normalhearing controls between June to December 2017. The results show that use of the App in HL patients improved WRT scores by a mean of 30.3% in quiet, 24.3% in noise + 10 dB SNR, and 20.8% in + 5 dB SNR. App use was identified as a factor that increased word recognition (odds ratio = 1.812, p < 0.05) and 61% of subjects rated sound quality when using the App as good or excellent. The use of a smartphone hearing App improved scores in both PTA and WRT in most cases. Patients with binaural hearing impairment < 60% obtained the best results. Subjective user satisfaction was good in both conditions

Letter to the editor regarding &ldquo;Rotavirus infection beyond the gut&rdquo;

Alejandro Orrico-S&aacute;nchez,1 M&oacute;nica L&oacute;pez-Lacort,1 Cintia Mu&ntilde;oz-Quiles,1 Miguel Angel Martinez-Beneito,2 Javier D&iacute;ez-Domingo1&nbsp;1Vaccine Research, Fundaci&oacute;n para el Fomento de la Investigaci&oacute;n Sanitaria y Biom&eacute;dica de la Comunitat Valenciana, FISABIO-Public Health, Valencia, Spain; 2Health Inequalities, Fundaci&oacute;n para el Fomento de la Investigaci&oacute;n Sanitaria y Biom&eacute;dica de la Comunitat Valenciana, FISABIO-Public Health, Valencia, Spain&nbsp;Gomez-Rial et al, in their review paper &ldquo;Rotavirus infection beyond the gut&rdquo;,1&nbsp;concluded that there is some degree of protection of the RV vaccination against&nbsp;seizure hospitalizations. A detailed analysis of the potential biases of the literature&nbsp;could lead to a less optimistic position for the vaccine. For example, the protection&nbsp;found in the USA and Australia could be partly due to the uncontrolled influenza&nbsp;vaccine (where the coverage in children under 5 years in EEUU reached 66&ndash;75%2).&nbsp;Other studies have small sample sizes, or used poorly adjusted analyses.Beyond their different degrees of appraisal of the papers depending on the direction&nbsp;of the results, there is a lack of discussion of the publication bias, as this bias disrupts&nbsp;the literature promoting positive findings and hiding negative results.&nbsp;View the original paper by&nbsp;Gomez-Rial and colleagues

Do socioeconomic inequalities in mortality vary between different Spanish cities? a pooled cross-sectional analysis

Background: The relationship between deprivation and mortality in urban settings is well established. This relationship has been found for several causes of death in Spanish cities in independent analyses (the MEDEA project). However, no joint analysis which pools the strength of this relationship across several cities has ever been undertaken. Such an analysis would determine, if appropriate, a joint relationship by linking the associations found. Methods: A pooled cross-sectional analysis of the data from the MEDEA project has been carried out for each of the causes of death studied. Specifically, a meta-analysis has been carried out to pool the relative risks in eleven Spanish cities. Different deprivation-mortality relationships across the cities are considered in the analysis (fixed and random effects models). The size of the cities is also considered as a possible factor explaining differences between cities. Results: Twenty studies have been carried out for different combinations of sex and causes of death. For nine of them (men: prostate cancer, diabetes, mental illnesses, Alzheimer’s disease, cerebrovascular disease; women: diabetes, mental illnesses, respiratory diseases, cirrhosis) no differences were found between cities in the effect of deprivation on mortality; in four cases (men: respiratory diseases, all causes of mortality; women: breast cancer, Alzheimer’s disease) differences not associated with the size of the city have been determined; in two cases (men: cirrhosis; women: lung cancer) differences strictly linked to the size of the city have been determined, and in five cases (men: lung cancer, ischaemic heart disease; women: ischaemic heart disease, cerebrovascular diseases, all causes of mortality) both kinds of differences have been found. Except for lung cancer in women, every significant relationship between deprivation and mortality goes in the same direction: deprivation increases mortality. Variability in the relative risks across cities was found for general mortality for both sexes. Conclusions: This study provides a general overview of the relationship between deprivation and mortality for a sample of large Spanish cities combined. This joint study allows the exploration of and, if appropriate, the quantification of the variability in that relationship for the set of cities considered.This article was partially funded by Ministerio de Economia y Competitividad via the research grant MTM2010-19528 (jointly financed with European Regional Development Fund), the FIS-FEDER projects: PI042013, PI040041, PI040170, PI040069, PI042602, PI040388, PI040489, PI042098, PI041260, PI040399, PI08/1488, PI08/0330 and by the CIBER Epidemiología y Salud Publica (CIBERESP), Spain