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This paper focuses on the consumer credit market in Italy and the related risk of over-indebtedness. Using panel data from the Survey on Household Income and Wealth, we investigate the role of households financial fragility on the use and increase in consumer debt over time, evaluating, in particular, whether there exists a statistically significant relationship between the growth in the use of consumer credit and the increase in the proportion of indebted households that are in a negative financial situation.

This paper proposes a broad measure of the country-level intensity of the main monitoring activities that are likely to affect financial reporting quality. The overall indicator (FRC) is a composite indicator combining three components, which measure the intensity of three different financial reporting controls (FRCs) exercised through corporate governance, audit, and enforcement. The indicator design adds to country measures used in accounting research in several ways. First, it employs recent process-oriented data to capture the intensity of controls in a regulatory context that is characterized by increasing harmonization. Process data can be updated periodically, and thus is also suitable for longitudinal analyses. Additionally, the development of the FRC indicator applies standard techniques for constructing composite indicators without a priori assumptions and weights. The paper presents the values of the FRC indicator in 17 European countries, revealing a diversified mix of FRC intensity across Europe. Our analysis shows that the three domain-specific indicators, which can also be used separately, measure different aspects of the intensity of financial reporting controls rather than an overall country attribute. Consistency analyses also show that the FRC indicator is not capturing a latent construct of financial reporting quality present in other metrics, thus providing support for its innovative use in cross-country accounting research.

In the original publication of the article the following text and tables were published incorrectly. The correct text and tables have been provided with this Correction.

Unconventional formulation and baking conditions were exploited for obtaining omega-3 polyunsaturated fatty acids enriched biscuits. A monoglyceride-flaxseed oil–water gel was used to obtain biscuits which had physical and chemical properties analogous to those of a control sample prepared with palm oil. To reduce fat oxidation and acrylamide and furan formation, the dough was baked at different temperature, time and pressure (i.e. varying from 101.33 to 0.15 kPa) conditions according to a central composite design. Baking at high temperature and reduced pressure allowed to obtain biscuits with acceptable water content and colour, while minimizing omega-3 fatty acids oxidation and acrylamide and furan formation. The biscuits best responding to these characteristics were obtained by applying the combination 174 °C-3.99 kPa-45 min. The low pressure generated inside the oven likely exerted a stripping effect towards acrylamide and furan as well as oxygen thus preventing toxicants to accumulate and lipid oxidation to occur. This study highlighted that the use of monoglyceride-flaxseed oil–water gel combined with baking under reduced pressure is potentially applicable at the industrial level to obtain nutritionally enhanced biscuits, while simultaneously preventing the occurrence of degradation reactions and toxic molecules formation. Due to the worldwide diffusion of cereal-based foods, including sweet biscuits, this formulation and process strategy could have a great economic impact.

In this paper the focus is on environmental statistics, with the aim of estimating the concentration surface and related uncertainty of an air pollutant. We used air quality data recorded by a network of monitoring stations within a Bayesian framework to overcome difficulties in accounting for prediction uncertainty and to integrate information provided by deterministic models based on emissions meteorology and chemico-physical characteristics of the atmosphere. Several authors have proposed such integration, but all the proposed approaches rely on representativeness and completeness of existing air pollution monitoring networks. We considered the situation in which the spatial process of interest and the sampling locations are not independent. This is known in the literature as the preferential sampling problem, which if ignored in the analysis, can bias geostatistical inferences. We developed a Bayesian geostatistical model to account for preferential sampling with the main interest in statistical integration and uncertainty. We used PM10 data arising from the air quality network of the Environmental Protection Agency of Lombardy Region (Italy) and numerical outputs from the deterministic model. We specified an inhomogeneous Poisson process for the sampling locations intensities and a shared spatial random component model for the dependence between the spatial location of monitors and the pollution surface. We found greater predicted standard deviation differences in areas not properly covered by the air quality network. In conclusion, in this context inferences on prediction uncertainty may be misleading when geostatistical modelling does not take into account preferential sampling.

The relation between disease risk and a point source of pollution is usually investigated using distance from the source as a proxy of exposure. The analysis may be based on case-control data or on aggregated data. The definition of the function relating risk of disease and distance is critical, both in a classical and in a Bayesian framework, because the likelihood is usually very flat, even with large amounts of data. In this paper we investigate how the specification of the function relating risk of disease with distance from the source and of the prior distributions on the parameters of the function affects the results when case-control data and Bayesian methods are used. We consider different popular parametric models for the risk distance function in a Bayesian approach, comparing estimates with those derived by maximum likelihood. As an example we have analyzed the relationship between a putative source of environmental pollution (an asbestos cement plant) and the occurrence of pleural malignant mesothelioma in the area of Casale Monferrato (Italy) in 1987-1993. Risk of pleural malignant mesothelioma turns out to be strongly related to distance from the asbestos cement plant. However, as the models appeared to be sensitive to modeling choices, we suggest that any analysis of disease risk around a putative source should be integrated with a careful sensitivity analysis and possibly with prior knowledge. The choice of prior distribution is extremely important and should be based on epidemiological considerations.

Conservation tillage (CT) is widely considered to be a practice aimed at preserving several ecosystem functions. In the literature, however, there seems to be no clear pattern with regard to its benefits on species diversity and species composition. In Northern Italy, we compared species composition and diversity of both vascular plants and Carabids under two contrasting tillage systems, i.e., CT and conventional tillage, respectively. We hypothesized a significant positive impact of CT on both species diversity and composition. We also considered the potential influence of crop type. The tillage systems were studied under open field conditions with three types of annual crops (i.e., maize, soybean, and winter cereals), using a split-plot design on pairs of adjacent fields. Linear mixed models were applied to test tillage system, crop, and interaction effects on diversity indices. Plant and Carabids communities were analyzed by multivariate methods (CCA). On the whole, 136 plant and 51 carabid taxa were recorded. The two tillage systems studied did not differ in floristic or carabid diversity. Species composition, by contrast, proved to be characteristic for each combination of tillage system and crop type. In particular, CT fields were characterized by nutrient demanding weeds and the associated Carabids. The differences were especially pronounced in fields with winter cereals. The same was true for the flora and Carabids along the field boundaries. For studying the effects of CT practices on the sustainability of agro-ecosystems, therefore, the focus should be on species composition rather than on diversity measures.

The 75-Gram Glucose Load in Pregnancy Relation between glucose levels and anthropometric characteristics of infants born to women with normal glucose metabolism Giorgio Mello , MD 1 , Elena Parretti , MD 1 , Riccardo Cioni , MD, MSC 1 , Roberto Lucchetti , MD 1 , Lucia Carignani , MD 1 , Elisabetta Martini , MD 1 , Federico Mecacci , MD 1 , Corrado Lagazio , PHD 2 and Monica Pratesi , PHD 3 1 Department of Gynecology, Perinatology and Human Reproduction, University of Florence, Florence, Italy 2 Department of Statistic Sciences, University of Udine, Udine, Italy 3 Department of Mathematics, Statistics, Informatics and Applications, University of Bergamo, Bergamo, Italy Abstract OBJECTIVE —To investigate, in pregnant women without gestational diabetes mellitus (GDM), the relation among obstetric/demographic characteristics; fasting, 1-h, and 2-h plasma glucose values resulting from a 75-g glucose load; and the risk of abnormal neonatal anthropometric features and then to verify the presence of a threshold glucose value for a 75-g glucose load above which there is an increased risk for abnormal neonatal anthropometric characteristics. RESEARCH DESIGN AND METHODS —The study group consisted of 829 Caucasian pregnant women with singleton pregnancy who had no history of pregestational diabetes or GDM, who were tested for GDM with a 75-g, 2-h glucose load, used as a glucose challenge test, in two periods of pregnancy (early, 16–20 weeks; late, 26–30 weeks), and who did not meet the criteria for a GDM diagnosis. In the newborns, the following abnormal anthropometric characteristics were considered as outcome measures: cranial/thoracic circumference (CC/TC) ratio ≤10th percentile for gestational age (GA), ponderal index (birth weight/length 3 × 100) ≥90th percentile for GA, and macrosomia (birth weight ≥90th percentile for GA), on the basis of growth standard development for our population. For the first part of the objective, logistic regression models were used to identify 75-g glucose load values as well as obstetric and demographic variables as markers for abnormal neonatal anthropometric characteristics. For the second part, the receiver operating characteristic (ROC) curve was performed for the 75-g glucose load values to determine the plasma glucose threshold value that yielded the highest combined sensitivity and specificity for the prediction of abnormal neonatal anthropometric characteristics. RESULTS —In both early and late periods, maternal age >35 years was a predictor of neonatal CC/TC ratio ≤10th percentile and macrosomia, with fasting 75-g glucose load values being independent predictors of neonatal CC/TC ratio ≤10th percentile. In both periods, 1-h values gave a strong association with all abnormal neonatal anthropometric characteristics chosen as outcome measures, with maternal age >35 years being an independent predictor for macrosomia. The 2-h, 75-g glucose load values were significantly associated in both periods with neonatal CC/TC ratio ≤10th percentile and ponderal index ≥90th percentile, whereas maternal age >35 years was an independent predictor of both neonatal CC/TC ratio ≤10th percentile and macrosomia. In the ROC curves for the prediction of neonatal CC/TC ratio ≤10th percentile for GA in both early and late periods of pregnancy, inflection points were identified for a 1-h, 75-g glucose load threshold value of 150 mg/dl in the early period and 160 mg/dl in the late period. CONCLUSIONS —This study documented a significant association, seen even in the early period of pregnancy, between 1-h, 75-g glucose load values and abnormal neonatal anthropometric features, and provided evidence of a threshold relation between 75-g glucose load results and clinical outcome. Our results would therefore suggest the possibility of using a 75-g, 1-h oral glucose load as a single test for the diagnosis of GDM, adopting a threshold value of 150 mg/dl at 16–20 weeks and 160 mg/dl at 26–30 weeks. CC/TC ratio, cranial/thoracic circumference GA, gestational age GCT, glucose challenge test GDM, gestational diabetes GTT, glucose tolerance test OR, odds ratio ROC, receiver operating characteristic Footnotes Address correspondence and reprint requests to Dr. Giorgio Mello, Via Masaccio, 92, 50100 Florence, Italy. E-mail: mellog{at}unifi.it . Received for publication 29 May 2002 and accepted in revised form 2 January 2003. A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. DIABETES CARE

We study how different prior assumptions on the spatially structured heterogeneity term of the convolution hierarchical Bayesian model for spatial disease data could affect the results of an ecological analysis when response and exposure exhibit a strong spatial pattern. We show that in this case the estimate of the regression parameter could be strongly biased, both by analyzing the association between lung cancer mortality and education level on a real dataset and by a simulation experiment. The analysis is based on a hierarchical Bayesian model with a time dependent covariate in which we allow for a latency period between exposure and mortality, with time and space random terms and misaligned exposure-disease data.

Model-based geostatistics and Bayesian approaches are useful in the context of veterinary epidemiology when point data have been collected by appropriate study design. We take advantage of an example of Epidemiological Surveillance on urban settings where a two-stage sampling design with first stage transects is applied to study the risk of dog parasite infection in the city of Naples, 2004-2005. We specified Bayesian Gaussian spatial exponential models and Bayesian kriging were performed to predict the continuous risk surface of parasite infection on the study region. We compared the results with those obtained by the application of hierarchical Bayesian models on areal data (proportion of positive specimens by transect). The models results were consistent with each other and the Bayesian geostatistical approach proved to be more accurate in identifying areas at risk of zoonotic parasitic diseases. In general, larger risk areas were identified at the city border where wild dogs mixed with domestic dogs and human or urban barriers were less present.