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Este estudo objetivou analisar o sofrimento emocional de idosos com diabetes mellitus tipo 2 da Estratégia Saúde da Família de Ribeirão Preto, São Paulo. Trata-se de um estudo descritivo do tipo inquérito domiciliar de base populacional, de delineamento transversal. Empregou-se a versão brasileira do questionário Problems Areas in Diabetes para verificar o grau de sofrimento emocional. Participaram 338 pessoas com idade igual ou superior a 60 anos, 66,3% eram mulheres, 51,5% encontravam-se na faixa etária de 60 a 69 anos, possuíam baixa renda e escolaridade. O escore médio de sofrimento emocional foi de 20,2 (DP=16,6) e variou de 0 a 74. Na subdimensão relacionada aos problemas emocionais verificou-se que 35,2% dos idosos se preocupavam com o futuro e com a possibilidade de sérias complicações. Acerca do tratamento, 20,4% relataram problemas nas metas claras e concretas no cuidado da doença. Além disso, 25,1% dos idosos referiram a existência de sentimentos de privação a respeito da comida e refeições. Na subdimensão sobre o apoio social, 6,8% se sentem sozinhos com o diabetes. O alto grau de sofrimento emocional mostrou-se associado a: autopercepção de saúde, idade do diagnóstico, número de doenças associadas ao DM2, uso de insulina isolado ou associado aos antidiabéticos orais, autoeficácia e disfunções renais (p

Aim: To analyse the emotional distress in elderly people with type 2 diabetes mellitus who attend primary healthcare centres in the city of Ribeirão Preto, state of São Paulo, Brazil. Methods: This is a cross-sectional, descriptive, populational, home-survey study. The Brazilian version of the questionnaire called Problems Areas in Diabetes was used to assess the level of emotional distress. Results: A total of 338 low-income people older than 60 years old participated in the study, in which 66.3% were women and 51.5% were aged between 60 and 69 years, all with low schooling level. The mean score of emotional distress was 20.2 ranging from 0 to 74. The high level of emotional distress was found to be associated with self-perception of health, age of diagnosis, number of diseases associated with diabetes, use of insulin associated or not with oral anti-diabetic drugs, self-efficacy, and renal dysfunctions (p < 0.05). The main problem reported by the participants was their concern with the future and likelihood of severe complications (35.2%). Conclusion: This study was able to assess some aspects of emotional distress amongst diabetic elderly people. The evidence from this research enables the strategic planning of actions at the geriatric population attending the primary healthcare centres to ensure quality of life during ageing.

Objective The objective of this study was to compare the efficacy of renal perfusion with Custodiol (Dr Franz-Kohler Chemie GmbH, Bensheim, Germany) versus enriched Ringer's solution for renal protection in patients undergoing open thoracoabdominal aortic aneurysm (TAAA) repair. Methods Ninety consecutive patients scheduled for elective open TAAA repair were enrolled between 2015 and 2017 in a single-center, phase IV, prospective, parallel, randomized, double-blind trial (the CUstodiol versus RInger: whaT Is the Best Agent [CURITIBA] trial), and randomized to renal arteries perfusion with 4°C Custodiol (Dr Franz-Kohler Chemie GmbH, Bensheim, Germany; n = 45) or 4°C lactated Ringer's solution (n = 45). The incidence of acute kidney injury (AKI) in patients undergoing TAAA open surgery using Custodiol renal perfusion versus an enriched Ringer's solution was the primary end point. Results Ninety patients completed the study (45 patients in each group). The incidence of postoperative AKI was significantly lower in the Custodiol group (48.9% vs 75.6%; P = .02). In the multivariable model, only the use of Custodiol solution resulted as protective from the occurrence of any AKI (odds ratio, 0.230; 95% confidence interval, 0.086-0.614; P = .003), whereas TAAA type II extent was associated with the development of severe AKI (odds ratio, 4.277; 95% confidence interval, 1.239-14.762; P = .02). At 1-year follow-up, serum creatinine was not significantly different from the preoperative values in both groups. Conclusions The use of Custodiol during open TAAA repair was safe and resulted in significantly lower rates of postoperative AKI compared with Ringer's solution. These findings support safety and efficacy of Custodiol in this specific setting, which is currently off-label.

Background Spontaneous intracranial hypotension (SIH) is a rare condition resulting from cerebrospinal fluid (CSF) volume depletion, nearly always from spontaneous CSF leaks. CSF pressure in SIH is usually normal; low CSF pressure is found in a substantial minority of patients. SIH is uncommonly described in pregnancy. Case series Five women with SIH during pregnancy have been conservatively treated adopting bed rest and overhydration. After prolonged conservative treatment, only 1 patient showed complete symptoms resolution. A rare SIH complication as cerebral venous thrombosis has been reported in 1 case. All 4 remaining patients had lumbar epidural blood patch (EBP) with symptoms disappearance. Conclusions EBP might be proposed to SIH patients also during pregnancy and after a brief period (~10 days) of ineffective conservative treatment, because it could allow faster symptoms improvement and complete recovery. Furthermore, EBP would avoid prolonged bed rest with the risk of SIH severe complications.

Small area statistics on economic inequality are becoming important for better planning public regional policies. We focus on the estimation of entropy inequality measures in Italian provinces by using data taken from the EU-SILC sample survey for Italy. In EUSILC survey the number of units sampled at provincial level is generally too small to obtain reliable estimates, and the use of small area estimation models is advisable. We consider small area models specified at area level that include the “direct” survey weighted estimators. In these models “direct” estimators are usually assumed to be unbiased and normally distributed. Nevertheless, in the case of inequality measures, design based estimators are known to be biased for small sample sizes. To solve this problem, we search for a correction that can produce approximately unbiased direct estimators. Moreover, due to the range of values that these estimators can assume and to the possible asymmetry of their distribution, the normality assumption could be inadequate in small area estimation models. In this regard we propose a small area model based on more flexible distributions as alternative to the normal one.

In the recent years the theme of sustainability has become so important that it has involved all economic sectors, including that of clothing, in which the phase concerning the dyeing of the garments deserves particular attention due to the substances used that are often harmful both in environmental and in social terms. This study analyses, by using the Social Life Cycle Assessment methodology, the life cycle of a made-in-Italy cashmere sweater, which is subject to natural dyeing. The aim of the study is to highlight the positive impacts (handprints) that arise along all the production phases (product design, yarn making, weaving, dyeing and finishing, sewing, labelling and packaging). For all the four stakeholder categories under analysis (Workers, Consumers, Value chain Actors, Society), several questionnaires were submitted that investigated the issues related to the category (e.g., for Workers: working hours, fair salary, etc.). Furthermore, the Subcategory Assessment Method was used to provide a quantitative character to the obtained results by illustrating the social behaviour of all the organisations that are involved in the life cycle. The emerged positive impacts include: a greater protection of consumers health and safety thanks to the reduction of chemical substances and to a particular labelling system that guarantees that sweaters are naturally dyed; greater responsibility of the local community towards sustainability issues; the setting up of new green production technologies.

Materials and methods From 1992 to 2015 we observed 326 patients (169 females and 157 males; age range 15-84; mean, 47 years) with OH from SIH according to the ICHD 2004 criteria. One hundred and sixteen performed a conservative treatment, while 210 underwent lumbar EBP with 15-50 ml (mean 28 ml) autologous blood. In 203 cases blood was mixed with contrast medium (1 ml of gadolinium [12 pts] and 5 ml of iopamidol [191 pts]), because about 30’ after EBP they underwent a spinal MRI or CT to document the blood spread into the epidural space. All patients were kept in a 30° Trendelenburg position for an hour before the procedure, during and for 24 h (52 pts) or 16 h (158 pts) after the procedure. Fifty-two patients were premedicated with acetazolamide (500 mg). The follow-up ranged from 6 months to 8 years.

Many parameters that describe poverty, social exclusion and inequality can take values in the (0,1) interval. This class includes headcount ratios such as the at-risk-of-poverty or material deprivation rates, the median poverty gap and the Gini inequality index, just to cite a few. Social scientists and policy planners often need estimates of this type of parameters for small subpopulations for which only small or no samples are available. In this work, we discuss area level models for the estimation of these parameters. Given their nature, Beta regression models are suitable, as the Beta distribution is very flexible over the (0,1) range and it allows for asymmetric sampling distributions. We adopt a Bayesian approach with approximate inference for relevant posterior distributions relying on MCMC algorithms. We focus on specific problems that we think are particularly relevant for small area applied researchers and discuss them with an application to real data. The problems we consider are: i) the estimation of the at-risk-of-poverty rate; ii) the joint estimation of the material deprivation and severe material deprivation rates (i.e. two rates based on increasing thresholds); iii) the joint estimation of two correlated parameters, namely the at-risk-of-poverty rate and the Gini inequality index. The data set that we analyze is a subset of the Italian sample of the EUSILC survey, and the small areas we target are Italian health districts, whose administrations play an important role in the implementation of many social and health expenditure programs related to the contrast of poverty and social exclusion. When estimating the at-risk-of-poverty rate we face the problem of areas with no poor in the sample that leads us to consider zero-mixture Beta regressions, a class of models that will be extended to the multivariate setting. In fact, the joint estimation of parameters in the (0,1) range requires multivariate extensions of the Beta regressions: for material deprivation and severe deprivation rates, based on increasing thresholds, we discuss a multivariate logistic-normal model for the expected values of the Beta distributions, while for the joint estimation of the at-risk-of-poverty rate and the Gini inequality index, we model the correlation between direct estimators using copula functions.

Objective (1) To determine the frequency of CT mimics of subarachnoid hemorrhage (SAH) in a large cohort of subjects with spontaneous intracranial hypotension (SIH). (2) To emphasize the distinctive radiologic features of SIH. Patients and methods CT scans of 95 subjects with SIH were retrieved and reviewed to search for findings of pseudo-SAH (CT mimics of SAH in the absence of blood). Results Pseudo-SAH radiologic findings (increased attenuation in the basilar cisterns, sylvian fissures, or along the tentorium) were detected on CT scans of 10 of the 95 SIH subjects. However, on MRI scans, these subjects exhibited the typical SIH abnormalities (diffuse pachymeningeal enhancement and brain sagging with obliteration of basilar cisterns). Conclusions In the emergency room, SIH should be considered in the differential diagnosis between SAH and pseudo-SAH. Although SIH and SAH can share some radiologic features, SIH has distinctive MRI and CT findings. Their recognition should obviate the need for more invasive procedures (e.g., cerebral angiography) to definitely rule out SAH and an aneurismal source of bleeding.

In this paper we propose a new small area estimation methodology aimed at the estimation of Value Added, Labor Cost and related competitiveness indicators for subsets of the population of Italian small and medium sized manufacturing firms classified according to geographical region, industrial sector and firms size. This disaggregation is needed in regional comparisons in order to avoid the confounding effect of sectorial and firm size composition of a region's manufacturing industry. We use data on the Small and Medium Enterprises sample survey conducted by the Italian National Statistical Institute (year 2009) that provided us this information in the framework of the BLUE-ETS project. The estimates obtained with our method are more reliable than those that would have been obtained using standard survey weighted estimators, and offer therefore the basis for more sound economic analysis. The small area methods that we propose are model based and take into account the peculiarities of business such as the skewness of target variables' distributions. For this reason the model we propose is based on the log-normal distribution. We consider a multivariate model in which two different variables (Value Added and Labor Cost) and jointly modeled in order to exploit their correlation. We adopt a Bayesian approach to inference. The problem of prior specification is considered and two alternative solutions compared. Since we produce estimates for several variables and hundreds of subset of the target population results are difficult to summarize. A general conclusion may be that, for Italy, the North-South divide in productivity levels is more apparent in capital and knowledge intensive sectors, especially when industrial districts are present. The productivity gap tends to grow for larger firms, but there exists several exception to this rule. Many industries traditionally associated to the Italian productive system (furniture, clothing, textile) are characterized by low labor productivity levels: in these cases the productivity gap between Northern and Southern regions is less pronounced or absent. As the paper is mostly about the methodology needed to obtain the estimates, it is relevant not only for those interested in Italian economy. The same ideas may be applied to data from other countries. The relevance of the mentioned indicators is highlighted by the increasing divergences in economic competitiveness among regions within the different EU member states observed in these last years.

The aim of this work is to propose a methodology for estimating domains’ poverty rates. SAE model often rely on the normality of the area parameters, but this assumption may be inappropriate for rates. As different rates are obtained by using different, increasing thresholds, we propose a multivariate hierarchical Normal-Logistic-Normal (NLN) model that constraints the estimates to monotonically increase with the thresholds. Moreover, considering that also the assumption of normality of the direct estimators is not satisfying (the distribution of poverty rates is left truncated at 0 and possibly skewed) we introduce, in the univariate context, a Beta sampling models that leads to a Beta-Logistic small area model (BL). Results obtained show both the NLN and the BL models perform considerably better then more ‘usual’ models based on Normality. A Hierarchical Bayesian approach to estimation, where posterior distributions are approximated by means of MCMC computation methods, is adopted.

In recent years, the measure of regional disparities on household poverty and social exclusion has received increasing attention by policy makers and this has produced a growing demand of sub-national statistical information on income parameters. Many studies have shown a strong connection between poverty and some characteristics of the household such as its composition, highlighting the concentration of the greatest economic difficulties in particular household typologies. For this reason, the aim of the work is to provide estimates of some poverty indicators for domains defined by cross-classifying the population by household typology (9 categories) and administrative region (20 categories), on the basis of data collected for Italy by the “European Union – Statistics on Income and Living Conditions” survey (EU-SILC). The need of estimating simultaneously more than one parameter is due to the multidimensionality of the studied phenomenon. In particular, we focus on three poverty rates based on three different thresholds, so to distinguish between poor people (PR, standard poverty threshold defined as the 60% of median of personal equivalent income), very poor people (PR80, threshold defined as the 80% of the standard poverty threshold) and people who are at risk of becoming poor (PR120, threshold defined as the 120% of the standard poverty threshold). The considered source, EU-SILC, is a sample survey on households’ income and social conditions, coordinated by Eurostat (Eurostat, 2005), designed to provide reliable estimates of main parameters of interest for areas within countries that do not correspond to our target domains. The number of units sampled from those domains are too scarce, in many cases, to obtain reliable estimates of the parameters of interest, therefore some small area estimation strategies have to be considered.

Bayesian estimators of small area parameters may be very effective in improving the precision of “direct”, design-based estimates. By the way, the may be poor estimators of the actual Empirical Distribution Function of the ensemble of small area parameters. In this paper we review different adjusted estimators that correct or mitigate this problem in the context of Hierarchical Bayesian modelling, considering also extensions to the case of multivariate models that are widely used in Small Area estimation. In particular we consider constrained and linear constrained Hierarchical Bayes estimators, along with an estimation method recently by Zhang. The posterior Mean Square Errors are proposed as measures of uncertainty. Different methods are compared by means of a simulation exercise in which many situations occurring in small area estimation applied problems are artificially re-created. The main goals of the simulation is to assess the ability of various estimators to properly estimate the actual Empirical Distribution Function of area parameters and secondly to assess the frequentist properties of posterior MSEs. The method of Zhang emerges as best in both the univariate and the multivariate setting, although the picture in the latter case is less clear.

Since the mid-1990s, under the wave of New Public Management reforms around the globe, Italian local governments (LGs) have received growing pressure from the legislature to implement performance measurement systems. With reference to municipalities, data show that there has been a growing diffusion of management control systems (MCSs) and therefore some sort of performance measurement. In 1998, less than one-tenth of about 8,100 Italian municipalities indicated that they had a MCS in place. This number increased during the following four years to about 36% for municipalities with a population less than 60,000 inhabitants, and 77% for larger municipalities (source: Italian Court of Audit, 2003). Other evidence depicts similar trends: an increase in benchmarking projects during the latter half of the 1990s and 2001 (Lucianelli and Tanese, 2002), and a growing attention on cost accounting which led to half of Italian municipalities with some sort of measurement of costs in 2003 (Orelli and Visani, 2004). The general framework of the Italian Local Governments Accounting Standards (Commission for Local Governments' Finance and Accounting - Ministry of the Interior, 2004) emphasize that the annual budget approved by each municipality's council should present the true and fair view of the next year. In other words, municipalities should plan the year after attempting to determine the best feasible picture of it in terms - above all - of revenues and expenses. Toward this end the legislature (Decree no. 267/00, articles no. 162, 196, and 197) suggests the use of performance measures, especially those connected to a MCS. Therefore an important question is whether the growth of performance measurement had a positive impact on Italian municipalities' ability to estimate revenues and expenditures more accurately in their annual budgets. To answer this question we use a quantitative approach based on an analysis of annual budgets and annual reports of Italian municipalities covering financial years 1999-2002.

This paper investigates the post-entry effect on productivity experienced by firms that start to exporting. The effect of entering into international markets is disentangled by the self-selection component and its empirical distribution is evaluated. Results show that the impact on productivity of moving from the status of non-exporter to the status of exporter is different at different sections of the productivity distribution.

Linear Mixed Models used in small area estimation usually rely on normality for the estimation of the variance components and the Mean Square Error of predictions. Nevertheless, normality is often inadequate when the target variable is income. For this reason, in this paper we consider Linear Mixed Models for the log-transformed income (which require back-transformation for prediction of means and totals on the variable’s original scale) and a Generalized Linear Mixed Model based on the Gamma distribution. Various prediction methods are compared by means of a simulation study based on the ECHP data. Standard predictors obtained from Linear Mixed Model for the untrasformed income are shown to be preferable to the considered alternatives, confirming their robustness with respect to the failure of the normality assumption.

The aim of this work is to evaluate the propensity of firms located in the industrial districts to demand skilled and/or unskilled workers. Based on information collected by the Excelsior survey, the number of hiring, by skill levels, has been estimated for the local labour market areas (llma) of the Emilia-Romagna and Tuscany regions. The evaluation of the reliability of estimates obtained at this territorial detail has addressed our analysis towards the firms having more than 100 employees. The districts has been compared with the remaining llma at first by productive sector, then also by the industrial district specialization. To summarize the multifaceted results arising from this comparison, a Poisson regression model has been estimated. One of the obtained results shows that firms operating in mechanical industrial districts show a higher propensity to hire managers and high-skilled workers.

The positive skewness of study variables is a peculiarity a of business survey data. It is due to the presence of a majority of small firms, beside a minority of big ones. For this reason, thenormality assumption, typical of small area models, can fail. We aim at the estimation of value added for subsets of the population of Italian small and medium sized manufacturing firms classified according to geographical region, industrial sector and firms size. This disaggregation is needed to compare regions meaningfully, avoiding the confounding effect of different sectorial and firm size composition of a regional manufacturing industries. We use data on the Small and Medium Enterprises sample survey conducted yearly by the Italian National Statistical Institute. The target variable we consider, value added, is positivelyskewed and so is the sampling distribution of total estimators in small samples. We assume log-normality of direct estimators of total value added and we specify linear mixed models onthe log scale. We adopt a Bayesian approach to inference, with relevant posterior distributions approximated by MCMC methods. The models we consider are characterized by the presence of several random effects to account for variation between areas not accounted for by the covariates. The considered effects include sectorial, regional and a time effect describing year to year variation. Some of these random effects are not exchangeable: e.g. time effects will have a dependence structure such as the random walk we consider in our application. As a consequence the priors for various variance components should be specified carefully as they can keep an influence on some aspect of inference based on posterior distributions even in presence of good auxiliary information.

The relationship between firm’s internationalization and productivity, widely analyzed in the literature, predicts the presence of a productivity premium for internationally involved firms with respect to the domestic ones. This finding is alternatively supported either by comparing the means of productivities over the two groups controlled for the relevant covariates or by the analysis of the stochastic dominance of the unconditional productivity distributions. In the present paper we unify the two approaches by estimating the entire distribution of the internationalization premium adjusted from the effects of different composition of groups. The statistical tool we adopt is based on the quantile regression decomposition approach. The main result we obtain shows that: i) by controlling for effects of firms heterogeneity the productivity premium is substantially reduced; ii) the adjusted productivity premium is significant only for less productive firms.