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BACKGROUND: Malnutrition is common among hospitalized children with chronic diseases and increases hospital care needs. The aim of this study is to estimate the clinical consequences of nutrition therapy (NT) after discharge. METHODS: A retrospective analysis of all pediatric inpatients with diagnosis of malnutrition hospitalized at our center from January 2017 to February 2018 was conducted. Malnutrition was assessed according to body mass index (BMI) z-score, routinely recorded in patient's files. The treatment group consists of all patients referred to nutrition assessment and treated by the clinical nutrition team; all the other patients not receiving NT are selected as the control group. The effect of NT on rehospitalization rates, length of stay (LOS), and emergency room (ER) visits was estimated for the total cohort and in a propensity score (PS) matched sample. RESULTS: 277 malnourished pediatric inpatients were enrolled and analyzed. NT was prescribed in 111 patients (40%). Rehospitalization rate was lower in the treated group (rate ratio [RR] = 0.797; 95% CI, 0.630-1.009); particularly, nonelective hospital admissions are considerably lower (RR = 0.556; 95% CI, 0.325-0.952). The strength of this association increased in the PS-matched sample. There is no clear evidence of NT's effect on ER visits (RR = 0.892; 95% CI, 0.580-1.373) or LOS per episode (Δ = 1.46 days; 95% CI, -3.39 to 6.31). CONCLUSIONS: Detecting and treating malnutrition seems to promptly improve the patients' clinical course after discharge, reducing the number of subsequent hospitalizations, particularly nonelective ones, probably caused by unresolved, ongoing malnutrition.

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Nineteen samples of Arabica and 14 of Robusta coming from various plantation were analysed by dynamic headspace capillary gas chromatography-mass spectrometry to characterize the volatile fraction of green and roasted samples and the relationships of the same species with geographical origin. As concerns green beans, Arabica species appear characterized by high content of n-hexanol, furfural and amylformate, while Robusta species by greater content of ethylpyrazine, dimethylsulfone and 2-heptanone. Four variables, 4-methyl-2,3-dihydrofuran, n-hexanol, limonene and nonanal, appear involved in the characterization of the geographical origin of the analysed samples. The volatile fraction of the roasted Arabica samples, appear characterized by high content of pyridine, diacetyl, propylformate, acetone and 2,3-pentanedione, while Robusta samples by high content of methylbutyrate, 2,3-dimethylpyrazine and 3-hexanone. Considering geographical origin of the analysed samples, four compounds appear involved, in particular 2-butanone, methylbutyrate, methanol and ethylformate. Very accurate (error rate lower than 5%) rules to classify samples as Arabica or Robusta according to their compounds profile were developed.

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BACKGROUND: the first confirmed cases of COVID-19 in WHO European Region was reported at the end of January 2020 and, from that moment, the epidemic has been speeding up and rapidly spreading across Europe. The health, social, and economic consequences of the pandemic are difficult to evaluate, since there are many scientific uncertainties and unknowns. OBJECTIVES: the main focus of this paper is on statistical methods for profiling municipalities by excess mortality, directly or indirectly caused by COVID-19. METHODS: the use of excess mortality for all causes has been advocated as a measure of impact less vulnerable to biases. In this paper, observed mortality for all causes at municipality level in Italy in the period January-April 2020 was compared to the mortality observed in the corresponding period in the previous 5 years (2015-2019). Mortality data were made available by the Ministry of Internal Affairs Italian National Resident Population Demographic Archive and the Italian National Institute of Statistics (Istat). For each municipality, the posterior predictive distribution under a hierarchical null model was obtained. From the posterior predictive distribution, we obtained excess death counts, attributable community rates and q-values. Full Bayesian models implemented via MCMC simulations were used. RESULTS: absolute number of excess deaths highlights the burden paid by major cities to the pandemic. The Attributable Community Rate provides a detailed picture of the spread of the pandemic among the municipalities of Lombardy, Piedmont, and Emilia-Romagna Regions. Using Q-values, it is clearly recognizable evidence of an excess of mortality from late February to April 2020 in a very geographically scattered number of municipalities. A trade-off between false discoveries and false non-discoveries shows the different values of public health actions. CONCLUSIONS: despite the variety of approaches to calculate excess mortality, this study provides an original methodological approach to profile municipalities with excess deaths accounting for spatial and temporal uncertainty.

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The effect of expiry date communication on acceptability and wasting risk of fresh-cut lettuce was investigated. Fresh-cut lettuce was packed in plastic pouches reporting or not the expiry date on the label and stored at recommended (8 °C) or abuse temperature (12 °C) for increasing time up to 21 days. Lettuce was assessed during storage for colour, total viable count, consumer rejection and wasting risk. Independently on storage temperature, the presence of the expiry date caused an increase of wasting risk. When lettuce was stored at 8 °C, about 4% packages were estimated to be wasted within the expiry date (7 days). Even a lower amount of waste was estimated when expiry date was not reported. Within 7 days of storage at 12 °C, 12% of the packages without expiry date was estimated to be wasted. This percentage increased to 27% when the expiry date was printed on the lettuce label. Results emphasise the dramatic effect of the presence of the expiry date on the consumer decision to waste food.

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The miRNA expression profiles of bone marrow resident cells from children with neuroblastoma were compared to that of healthy children. No significant difference was found between localized and metastatic neuroblastoma, or between children with neuroblastoma and healthy children. By considering the fold change we identified six miRNAs over-expressed by more than 150 fold in neuroblastoma. Validation confirmed miR-221 over-expression in BM resident cells from children with neuroblastoma, regardless of localized or metastatic disease. MiR-221 over-expression was unlikely derived from neuroblastoma primary tumors or from bone marrow-infiltrating metastatic cells, since neuroblastoma cells expressed lower or similar amount of miR-221 than BM cells, respectively. To get insight on the genes potentially regulated by miR-221 we merged the list of miR-221 potential targets with the genes under-expressed by BM resident cells from children with neuroblastoma, as compared with healthy children. In silico analysis demonstrated that none of the miR-221 target genes belonged to heme biosynthetic processes found altered in children with neuroblastoma, whereas two genes associated with mitochondria. However, the encoded proteins were not under-expressed in children with neuroblastoma, making unlikely that altered erythrocyte maturation in children with neuroblastoma was mediated by miR-221. In conclusion, miRNA expression profiles of BM resident cells from children with localized and metastatic neuroblastoma were similar to that of BM resident cells from healthy children. Moreover, miRNAs expressed by neuroblastoma primary tumors or by BM-infiltrating NB cells do not appear to be involved in mediating the functional defect of erythrocyte maturation recently observed in children with neuroblastoma.

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Neuroblastoma (NB) is a pediatric tumor presenting at diagnosis either as localized or metastatic disease, which mainly involves the bone marrow (BM). The physical occupancy of BM space by metastatic NB cells has been held responsible for impairment of BM function. Here, we investigated whether localized or metastatic NB may alter hematopoietic lineages' maturation and release of mature cells in the periphery, through gene expression profiling, analysis of BM smears, cell blood count and flow cytometry analysis. Gene ontology and disease-associated analysis of the genes significantly under-expressed in BM resident cells from children with localized and metastatic NB, as compared to healthy children, indicated anemia, blood group antigens, and heme and porphyrin biosynthesis as major functional annotation clusters. Accordingly, in children with NB there was a selective impairment of erythrocyte maturation at the ortho-chromic stage that resulted in reduced erythrocyte count in the periphery, regardless of the presence of metastatic cells in the BM. By considering all NB patients, low erythrocyte count at diagnosis associated with worse survival. Moreover, in the subset of metastatic patients, low erythrocyte count, hemoglobin and hematocrit and high red cell distribution width at follow-up also associated with worse outcome. These observations provide an alternative model to the tenet that infiltrating cells inhibit BM functions due to physical occupancy of space and may open a new area of research in NB to understand the mechanism(s) responsible for such selective impairment.

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BACKGROUND: The objective was to evaluate whether an ultrasonic reflectance technique has predictive capacity for breadmaking performance of doughs made under a wide range of formulation conditions. Two flours of contrasting dough strength augmented with different levels of ingredients (inulin, oil, emulsifier or salt) were used to produce different bread doughs with a wide range of properties. Breadmaking performance was evaluated by conventional large-strain rheological tests on the dough and by assessment of loaf quality. The ultrasound tests were performed with a broadband reflectance technique in the frequency range of 0.3-6 MHz. RESULTS: Principal component analysis showed that ultrasonic attenuation and phase velocity at frequencies between 0.3 and 3 MHz are good predictors for rheological and bread scoring characteristics. CONCLUSIONS: Ultrasonic parameters had predictive capacity for breadmaking performance for a wide range of dough formulations. Lower frequency attenuation coefficients correlated well with conventional quality indices of both the dough and the bread. © 2016 Society of Chemical Industry.

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Preferential sampling refers to any situation in which the spatial process and the sampling locations are not stochastically independent. In this paper, we present two examples of geostatistical analysis in which the usual assumption of stochastic independence between the point process and the measurement process is violated. To account for preferential sampling, we specify a flexible and general Bayesian geostatistical model that includes a shared spatial random component. We apply the proposed model to two different case studies that allow us to highlight three different modeling and inferential aspects of geostatistical modeling under preferential sampling: (1) continuous or finite spatial sampling frame; (2) underlying causal model and relevant covariates; and (3) inferential goals related to mean prediction surface or prediction uncertainty.

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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.

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BACKGROUND: The volatile fraction of virgin olive oil is characterised by low molecular weight compounds that vaporise at room temperature. In order to obtain an aroma profile similar to natural olfactory perception, the composition of the volatile compounds was determined by applying dynamic headspace gas chromatography, performed at room temperature, with a cryogenic trap directly connected to a gas chromatograph-mass spectrometer system. Samples were also evaluated according to European Union and International Olive Council official methods for sensory evaluation. In this paper, the composition of the volatile fraction of 25 extra virgin olive oils from different regions of Italy was analysed and some preliminary considerations on relationships between chemical composition of volatile fraction and sensory characteristics are reported. RESULTS: Forty-two compounds were identified by means of the particular analytical technique used. All the analysed samples, classified as extra virgin by the panel test, never present peaks whose magnitude is important enough in defected oils. The study was focused on the evaluation of volatile compounds responsible for the positive impact on olive odour properties ('green-fruity' and 'sweet') and olfactory perception. CONCLUSION: Chemometric evaluation of data, obtained through headspace analysis and the panel test evaluation, showed a correlation between chemical compounds and sensory properties. On the basis of the results, the positive attributes of virgin olive oil are divided into two separated groups: sweet types or green types. Sixteen volatile compounds with known positive impact on odour properties were extracted and identified. In particular, eight compounds seem correlated with sweet properties whereas the green sensation appears to be correlated with eight other different substances. The content of the compounds at six carbon atoms proves to be very important in defining positive attributes of extra virgin olive oils and sensory evaluation.

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To get insights on the metastatic process of human neuroblastoma (NB), the miRNA expression profile of bone marrow (BM)-infiltrating cells has been determined and compared to that of primary tumors.Twenty-two BM-infiltrating cells, 22 primary tumors, and 4 paired samples from patients with metastatic NB aged > 12 months were analyzed for the expression of 670 miRNAs by stem-loop RT-qPCR. The miRNAs whose expression was significantly different were subjected to selection criteria, and 20 selected miRNAs were tested in 10 additional BM-infiltrating cells and primary tumors. Among the miRNAs confirmed to be differentially expressed, miR-659-3p was further analyzed. Transfection of miR-659-3p mimic and inhibitor demonstrated the specific suppression and over-expression, respectively, of the miR-659-3p target gene CNOT1, a regulator of transcription of genes containing AU-rich element (ARE) sequence. Among the ARE-containing genes, miR-659-3p mimic and inhibitor specifically modified the expression of AKT3, BCL2, CYR61 and THSB2, belonging to the focal adhesion pathway. Most importantly, in BM-infiltrating cells CNOT1 expression was significantly higher, and that of AKT3, BCL2, THSB2 and CYR61 was significantly lower than in primary tumors. Thus, our study suggests a role of the focal adhesion pathway, regulated by miR-659-3p through CNOT1, in the human NB metastatic process.

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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.

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Model-based geostatistics and Bayesian approaches are appropriate in the context of Veterinary Epidemiology when point data have been collected by valid study designs. The aim is to predict a continuous infection risk surface. Little work has been done on the use of predictive infection probabilities at farm unit level. In this paper we show how to use predictive infection probability and related uncertainty from a Bayesian kriging model to draw a informative samples from the 8794 geo-referenced sheep farms of the Campania region (southern Italy). Parasitological data come from a first cross-sectional survey carried out to study the spatial distribution of selected helminths in sheep farms. A grid sampling was performed to select the farms for coprological examinations. Faecal samples were collected for 121 sheep farms and the presence of 21 different helminths were investigated using the FLOTAC technique. The 21 responses are very different in terms of geographical distribution and prevalence of infection. The observed prevalence range is from 0.83% to 96.69%. The distributions of the posterior predictive probabilities for all the 21 parasites are very heterogeneous. We show how the results of the Bayesian kriging model can be used to plan a second wave survey. Several alternatives can be chosen depending on the purposes of the second survey: weight by posterior predictive probabilities, their uncertainty or combining both information. The proposed Bayesian kriging model is simple, and the proposed samping strategy represents a useful tool to address targeted infection control treatments and surbveillance campaigns. It is easily extendable to other fields of research.

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S. Daniele hams were collected at different stages during dry-curing and submitted to magnetic resonance imaging (MRI) according to the acquisition Spin-Echo sequences T1 and T2. The intensity of the MR signals in the images of the Semimembranosus, Semitendinosus, Rectus femoris and Biceps femoris muscles of the hams was computed and expressed in grey levels. Muscles were also submitted to traditional analyses, including aw, soluble solids, sodium chloride, total and water soluble nitrogen. T1 and T2 MR signals well described the evolution of the phenomena occurring in the different muscles during dry-curing. MR signal acquired in T2 mode well correlated with traditional indicators in Semitendinosus, Rectus femoris and Biceps femoris muscles. Predictive models estimating the value of aw, moisture, salt content and proteolysis extent on the basis of the MR signal intensity were proposed.

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UNLABELLED: Fruit salads stored for different lengths of time as well as their images were used to estimate sensory shelf life by survival analysis. Shelf life estimates obtained using fruit salad images were longer than those achieved by analyzing the real product. This was attributed to the fact that images are 2-dimensional representations of real food, probably not comprehensive of all the visual information needed by the panelists to produce an acceptability/unacceptability judgment. Images were also subjected to image analysis and the analysis of the overall visual quality by a trained panel. These indices proved to be highly correlated to consumer rejection of the fruit salad and could be exploited for routine shelf life assessment of analogous products. To this regard, a failure criterion of 25% consumer rejection could be equivalent to a score 3 in a 5-point overall visual quality scale. PRACTICAL APPLICATION: Food images can be used to assess product shelf life. In the case of fruit salads, the overall visual quality assessed by a trained panel on product images and the percentage of brown pixels in digital images can be exploited to estimate shelf life corresponding to a selected consumer rejection.

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We propose a Bayesian approach to multiple testing in disease mapping. This study was motivated by a real example regarding the mortality rate for lung cancer, males, in the Tuscan region (Italy). The data are relative to the period 1995-1999 for 287 municipalities. We develop a tri-level hierarchical Bayesian model to estimate for each area the posterior classification probability that is the posterior probability that the municipality belongs to the set of non-divergent areas. We show also the connections of our model with the false discovery rate approach. Posterior classification probabilities are used to explore areas at divergent risk from the reference while controlling for multiple testing. We consider both the Poisson-Gamma and the Besag, York and Mollié model to account for extra Poisson variability in our Bayesian formulation. Posterior inference on classification probabilities is highly dependent on the choice of the prior. We perform a sensitivity analysis and suggest how to rely on subject-specific information to derive informative a priori distributions. Hierarchical Bayesian models provide a sensible way to model classification probabilities in the context of disease mapping.

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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.

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In 2002, serious criticism was raised about the use of standard statistical software (Splus, SAS, Stata) to fit Generalized Additive Models (GAM) to epidemiological time series data. This criticism concerns convergence problems of the backfitting algorithm and inappropriate use of a linear approximation in estimating standard errors of estimates for parametric terms, such as the effect of air pollution. Here we analysed the association between PM10 and Mortality/Hospital Admissions in the Italian Meta-analysis of Short-term effects of Air pollutants (MISA) using two alternative approaches that are not affected by the same drawbacks: GAM with penalized regression spline fitted by the direct method in R (GAM-R) software and Generalized Linear Models with natural cubic spline (GLM+NS). A sensitivity analysis is also provided varying number of degrees of freedom for the seasonality spline and modality of adjustment for confounding effect of temperature. Published theoretical results and a simulation study are provided in order to explain discrepancies between GLM+NS and GAM-R estimates. We conclude that in general the fully parametric GLM+NS approach retains better statistical properties than GAM-R that could bring to biased air pollution effect estimates unless a certain degree of under-smoothing for seasonality spline is settled.

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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.

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The work described in the present report has been requested by the Secretary of Hygiene, Health and Social Welfare of the Sardinia Region (Italy). It has been carried out by the Regional Epidemiological Observatory within the domain of ESA (Epidemiology Development and Environment) and with the support of the European Union. Eighteen areas (for a total of 73 municipalities) were identified a priori as "potentially polluted", accounting for a population of 917,977 in 2001 census (56% of the total population of Sardinia). The areas have been named after the most important town, as listed below (in brackets rounded 2001 population), major activities in industrial areas are briefly described. INDUSTRIAL AREAS: Portoscuso (59,000). Processing of aluminium and other metals. Foundry. Power plants. Dismissed mines (mainly coal mining, lead, zinc). Plants for storing and treating special wastes. Italian Law 349/1986 classified this area as "at high risk of environmental crisis" and classified some plants as being "at high technological risk" (Norma Seveso Decree 334/1999). The area is part of the Sulcis National Restoration site. San Gavino (24,000). Industrial and commercial activities. Lead and zinc foundry. Dairy factories. Food industry. Sarroch (52,000). Petrochemical and refinery industry. Power plants. Mining. Incinerator. Plants for storing and treating special wastes. Gas and mineral oil deposits. Ottana (15,000). Chemical industry. Production of plastics and synthetic fibres. Denim production. Porto Torres (168,000). Chemical industry: production of basic chemicals (benzene, toluene, ethylene, propylene and others), polyethylene, elastomers and vinyl chloride. Textile industry. First and second category landfills. Some plants have been classified "at high technological risk" (Norma Seveso Decree 334/1999). The area is a National Restoration site. The town of Sassari is included. Tortolì (23,000). Construction of steel structures for offshore facilities of the oil and gas industry. Paper industry. Tempio Pausania (21,000). Cork production. Stone quarries. Macomer (17,000). Textile industry (velvet). First and second category landfills. Incinerator. MINING AREAS: Arbus (30,000). Extraction of zinc, lead and silver. Iglesias (39,000). Extraction of zinc, lead and silver. MILITARY SITES: Teulada (16,000). La Maddalena (11,000). Naval army shipyards. Salto di Quirra (31,000). Mining area. URBAN AREAS: Cagliari (299,000). Petrochemical plants, port, airport. Nuoro (37,000). Olbia (47,000). Port and airport. Oristano (31,000). Sassari (121,000). RESULTS: THE COMPARISON SARDINIA-ITALY: In 1997-2001, the age-standardized mortality rate (x1,000 person-years) among males was higher than in Italy (84.4 vs 80.8) while the reverse occurred in females (50.9 vs 52.0). Ill defined causes of death were 1.4% in males and 2.5% in females (vs corresponding estimates of 1.1% and 1.4% in Italy). Compared to Italian national data, regional age-standardized estimates were higher in Sardinia for infectious diseases (23% in males and 12% in females), respiratory diseases (22% and 14%: pneumoconiosis was more than 6 times more frequent in Sardinia than in Italy), diseases of the digestive system (26% and 9%: for liver cirrhosis, the excess was 33% in males and 9% in females; corresponding figures for liver cancer were 13% and 16%), breast cancer in females (5%). On the other hand, regional mortality rates were lower than the national rates for cardiovascular diseases (-1.3% and -7.4% in males and females respectively), all cancers considered as a whole (-9% and -7%) and lung cancer (-5% and -32%). Regional and national death rates for non Hodgkin lymphoma in both sexes and for leukaemia in females were almost identical, whereas the latter rate in males was slightly higher in Sardinia than in Italy (9.4 vs 8.4 x100,000 person-years). Particularly in men, the differences in mortality rates from all causes and from cardiovascular, respiratory diseases and lung cancer among the four traditional Provinces (Cagliari, Nuoro, Oristano and Sassari) were greater than the difference between Sardinia and Italy. Remarkably enough, also death rates from lymphohaemopoietic tumours were more heterogeneous within Sardinia. RESULTS IN THE INVESTIGATED AREAS: Rates of hospital discharges in Sardinia showed a high variability, which is partly attributable to differences in the availability of both hospital beds and alternative forms of care. This heterogeneity must be taken into account in the interpretation of rates of hospital discharge. These were relatively high in some areas (Cagliari, Iglesias, Portoscuso, Tortolì) and low in others (Olbia, Porto Torres, Sassari). All the reported observed/expected ratios were based on material deprivation adjusted figures. All the estimated statistics were reported with 90% Confidence Interval. INDUSTRIAL AREAS: In 1997-2001, deaths from respiratory diseases were significantly in excess in males in Portoscuso (obs/exp 205/124.77) and in San Gavino (69/46.77). Deaths from pneumoconiosis were recorded sporadically, with the exception of Portoscuso, where the excess was impressive (obs/exp 112/30.46). SMRs for lung cancer in males ranged between 0.62 in Ottana and 1.22 in San Gavino, with statistically significant departure from expected values in Portoscuso and Sarroch (both with SMR significantly in excess in males: 1.24). In Porto Torres mortality from all causes was in significant excess in both sexes (SMRs 1.04 in males and 1.09 in females), for respiratory diseases (1.08 and 1.28), for diseases of the digestive system (1.13 and 1.21), for all cancers (1.04 and 1.09). Liver cancer deaths were also in excess in both sexes (SMRs 1.18 and 1.21). The latter finding is confirmed by incidence rates from the local cancer registry. Among industrial areas, Porto Torres was also the one with a stronger evidence of an excess of deaths from lymphohaemopoietic cancer in males (obs/exp 99/83.60) and females (73/68.20). MINING AREAS: These areas are characterized by statistically significant excesses of mortality in males, largely caused by non neoplastic respiratory conditions (obs/exp 119/86.41 in Iglesias and 156/62.55 in Arbus). In recent years, deaths from pneumoconiosis averaged 20 per year in Arbus and 10 per year in Iglesias. Lung cancer in males was also significantly in excess in both areas (obs/exp 72/56.38 in Arbus and 108/72.14 in Iglesias). There is a time trend (1981-2001) towards a decrease of mortality from respiratory conditions, which nevertheless remains largely in excess over the regional average also in the most recent period. MILITARY AREAS: Statistically significant excesses of deaths and hospital discharges for non Hodgkin lymphoma were detected in La Maddalena (mortality, 1981-2001, in males 17 observed cases vs 6.13 expected, in females 8/5.64). In Salto di Quirra in 1997-2001 deaths from myeloma (in males 5/2.3) and leukaemias were increased in both sexes (total obs/exp 20/13.3, statistically non significant). URBAN AREAS: Urban areas in Sardinia are relatively well developed with high values of socioeconomic indicators. The health profile in Cagliari and Sassari is typical of towns of the Western world. In Cagliari there is a higher mortality for colorectal, breast, cervical and lung cancer. CONCLUSIONS: Environmental (non occupational) pollution might explain some of the observed excesses of disease in the investigated industrial areas of Sardinia, particularly in women, less likely to be exposed to hazards in the work environment, whereas in the mining areas studied the disease pattern suggests a major role of occupational exposures. On the other hand, the causal links between disease occurrence and exposures in the screened military areas remain uncertain. The disease patterns in the cities of Sardinia are likely to be associated with lifestyle and urban pollution. Historically, southern Italian Regions have been characterized by an advantage over the rest of the country in terms of health, but during the last decade such advantage tended to vanish. Sardinia confirms this secular trend. However in the most recent years studied, overall age-standardized mortality rate in Sardinian females still remains lower than Italian average, but this is not the case for males any more. Differences in the health profile between residents in different areas of Sardinia have been found to be far greater than the difference between Sardinia as a whole and Italy. A major contribution to intraregional differences is given by the 18 investigated areas where excesses were registered for: respiratory diseases (including cancer) in the industrial areas of Portoscuso, Sarroch and Porto Torres, and in the mining areas; diseases of the digestive tract, liver cancer and lymphohaemopoietic cancer in the area of Porto Torres; cancer of the lymphohaemopoietic system in some military areas; cancers of the colon and rectum, lung, breast and uterus in some of the major cities of the Region.

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