Un’analisi statistico – economica dell’impatto delle norme WHO su nutrizione e salute

I comportamenti nutrizionali stanno assumendo sempre maggiore rilievo all’interno delle politiche comunitarie e questo sottolinea che la dieta sta avendo, negli ultimi anni, una maggiore importanza come fattore di causa e allo stesso tempo prevenzione nella diffusione di malattie croniche come il cancro, malattie cardiovascolari, diabete, osteoporosi e disturbi dentali. Numerosi studi mostrano infatti che i tassi di obesità sono triplicati nelle ultime due decadi e si è stimato che, se i livelli di obesità continueranno a crescere allo stesso tasso del 1990, nel 2010 il numero di persone obese raggiungerà i 150 milioni tra gli adulti e i 15 milioni tra bambini e adolescenti. I governi nazionali stanno quindi cercando di risolvere questo problema, a cui sono inoltre legati alti costi nazionali, tramite l’implementazione di politiche nutrizionali. Analisi di tipo cross-section sono già state evidenziate da studiosi come Schmidhuber e Traill (2006), i quali hanno effettuato un’analisi di convergenza a livello europeo per esaminare la distanza tra le calorie immesse da 426 prodotti diversi. In quest’analisi hanno così dimostrato la presenza di una similarità distinta e crescente tra i paesi europei per quanto riguarda la composizione della dieta. Srinivasan et al. invece hanno osservato la relazione esistente tra ogni singolo prodotto alimentare consumato e le norme nutrizionali dell’ Organizzazione Mondiale della Sanità (World Health Organization, WHO) Lo scopo di questa tesi è quello di evidenziare il problema a livello di aggregati nutritivi e di specifiche componenti nutrizionali come zucchero, frutta e verdura e non relativamente ad ogni singolo prodotto consumato. A questo proposito ci si è basati sulla costruzione di un indicatore (Recommendation Compliance Index) in modo da poter misurare le distanze tra la dieta media e le raccomandazioni del WHO. Lo scopo è quindi quello di riuscire a quantificare il fenomeno del peggioramento della dieta in diverse aree del mondo negli ultimi quattro decenni, tramite un’analisi panel, basandosi sui dati sui nutrienti consumati, provenienti dal database della FAO (e precisamente dal dataset Food Balance Sheets – FBS). Nella prima fase si introduce il problema dell’obesità e delle malattie croniche correlate, evidenziando dati statistici in diversi paesi europei e mondiali. Si sottolineano inoltre le diverse azioni dei governi e del WHO, tramite l’attuazione di campagne contro l’obesità e in favore di una vita più salutare e di una maggiore attività fisica. Nella seconda fase si è costruito un indicatore aggregato (Recommendation Compliance Index) in modo da analizzare le caratteristiche nella dieta dei diversi Paesi a livello mondiale rispetto alle norme del WHO. L’indicatore si basa sui dati ottenuti da FAOSTAT ed è calcolato per 149 paesi del database dell’FBS per il periodo 1961-2002. Nell’analisi si sono utilizzati i dati sulle percentuali di energia prodotta dalle varie componenti nutritive, quali grassi, grassi saturi e transaturi, zuccheri, carboidrati, proteine e le quantità di frutta e verdura consumate. Inoltre si è applicato un test statistico per testare se il valore del RCI è significativamente cambiato nel tempo, prendendo in considerazione gruppi di Paesi (Paesi OECD, Paesi in via di sviluppo e sottosviluppati). Si è voluto poi valutare la presenza o meno di un processo di convergenza, applicando l’analisi di σ-convergenza per osservare ad esempio se la variabilità è diminuita nel tempo in modo significativo. Infine si è applicato l’indicatore ad un livello micro, utilizzando il database del National Diet and Nutrition Survey, che raccoglie dati di macrocomponenti nutritive e misure antropometriche della popolazione inglese dai 16 ai 64 anni per il periodo 2000-2001. Si sono quindi effettuate analisi descrittive nonché analisi di correlazione, regressione lineare e ordinale per osservare le relazioni tra l’indicatore, i macronutrienti, il reddito e le misure antropometriche dell’ Indice di Massa Corporea (Body Mass Index, BMI) e del rapporto vita-fianchi (Waist-hip ratio, WHR).

Effetti degli accordi Euro-Mediterrani sul comparto dell'ortofrutta fresca

In 1995, the European Union (EU) Member States and 12 Mediterranean countries launched in Barcelona a liberalization process that aims at establishing a free trade area (to be realized by 2010) and at promoting a sustainable and balanced economic development by the adoption of a new generation of Agreements: the Euro-Mediterranean Agreements (EMA). For the Mediterranean partner countries, the main concern is a better access for their fruit and vegetable exports to the European market. These products represent the main exports of these countries, and the EU is their first trading partner. On the other side, for the EU the main issue is not only the promotion of its products, but also the protection of its fruit and vegetables producers. Moreover, the trade with third countries is the key element of the Common Market Organization of the sector. Fruit and vegetables represent a very sensitive sector since their high seasonality, high perishability, and especially since the production of the Mediterranean countries is often similar to the European Mediterranean’s countries one. In fact, the agreements define preferences at the entrance of the EU market providing limited concessions for each partner, for specific products, limited quantities and calendars. This research tries to analyze the bilateral trade volume for fresh fruit and vegetables in the European and Italian markets in order to assess the effects of Mediterranean liberalization on this sector. Free trade of agricultural products represents a very actual topic in international trade and the Mediterranean countries, recognised as big producers of fruit and vegetables, as big exporters of their crops and actually significantly present on the European market, could be high competitors with the inward production because the outlet could be the same. The goal of this study is to provide some considerations about the competitiveness of mediterranean fruit and vegetables productions after Barcelona Process, in a first step for the European market and then also for the Italian one. The aim is to discuss the influence of the euro-mediterranean agreements on the fruit and vegetables trade between 10 foreign Mediterranean countries (Algeria, Egypt, Israel, Jordan, Libya, Lebanon, Morocco, Tunisia, Syria, and Turkey) and 15 EU countries in the period 1995-2007, by means of a gravity model, which is a widespread methodology in international trade analysis. The basic idea of gravity models is that bilateral trade from one country to another (as the dependent variable) can be explained by a set of factors: - factors that capture the potential of a country to export goods and services; - factors that capture the propensity of a country to imports goods and services; - any other forces that either attract or inhibit bilateral trade. This analysis compares only imports’ flows by Europe and by Italy (in volumes) from Mediterranean countries, since the exports’ flows toward those foreign countries are not significant, especially for Italy. The market of fruit and vegetables appears as a high heterogeneous group so it is very difficult to show a synthesis of the analysis performed and the related results. In fact, this sector includes the so called “poor products” (such as potatoes and legumes), and the “rich product”, such as nuts or exotic fruit, and there are a lot of different goods that arouse a dissimilar consumer demand which directly influence the import requirements. Fruit and vegetables sector includes products with extremely different biological cycles, leading to a very unlike seasonality. Moreover, the Mediterranean area appears as a highly heterogeneous bloc, including countries which differ from the others for economic size, production potential, capability to export and for the relationships with the EU. The econometric estimation includes 68 analyses, 34 of which considering the European import and 34 the Italian import and the products are examined in their aggregated form and in their disaggregated level. The analysis obtains a very high R2 coefficient, which means that the methodology is able to assess the import effects on fruit and vegetables associated to the Association Agreements, preferential tariffs, regional integration, and others information involved in the equation. The empirical analysis suggests that fruits and vegetables trade flows are well explained by some parameters: size of the involved countries (especially GDP and population of the Mediterranean countries); distances; prices of imported products; local production for the aggregated products; preferential expressed tariffs like duty free; sub-regional agreements that enforce the export capability. The euro-mediterranean agreements are significant in some of the performed analysis, confirming the slow and gradual evolution of euro- Mediterranean liberalization. The euro-mediterranean liberalization provides opportunities from one side, and imposes a new important challenge from the other side. For the EU the chance is that fruit and vegetables imported from the mediterranean area represent a support for local supply and a possibility to increase the range of products existing on the market. The challenge regards the competition of foreign products with the local ones since the types of productions are similar and markets coincide, especially in the Italian issue. We need to apply a strategy based not on a trade antagonism, but on the realization of a common plane market with the Mediterranean countries. This goal could be achieved enhancing the industrial cooperation in addition to commercial relationships, and increasing investments’ flows in the Mediterranean countries aiming at transforming those countries from potential competitors to trade partners and creating new commercial policies to export towards extra European countries.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

Ruolo delle specie reattive dell'ossigeno e di caveole/raft lipidici nella biosegnalazione in linee cellulari umane

Membrane lipid rafts are detergent-resistant microdomains containing glycosphingolipids, cholesterol and glycosylphosphatidylinositol-linked proteins; they seem to be actively involved in many cellular processes including signal transduction, apoptosis, cell adhesion and migration. Lipid rafts may represent important functional platforms where redox signals are produced and transmitted in response to various agonists or stimuli. In addition, a new concept is emerging that could be used to define the interactions or amplification of both redox signalling and lipid raft-associated signalling. This concept is characterized by redox-mediated feed forward amplification in lipid platforms. It is proposed that lipid rafts are formed in response to various stimuli; for instance, NAD(P)H oxidase (Nox) subunits are aggregated or recruited in these platforms, increasing Nox activity. Superoxide and hydrogen peroxide generation could induce various regulatory activities, such as the induction of glucose transport activity and proliferation in leukaemia cells. The aim of our study is to probe: i) the involvement of lipid rafts in the modulation of the glucose transporter Glut1 in human acute leukemia cells; ii) the involvement of plasma membrane caveolae/lipid rafts in VEGF-mediated redox signaling via Nox activation in human leukemic cells; iii) the role of p66shc, an adaptor protein, in VEGF signaling and ROS production in endothelial cells (ECs); iv) the role of Sindecan-2, a transmembrane heparan sulphate proteoglycan, in VEGF signaling and physiological response in ECs and v) the antioxidant and pro-apoptotic activities of simple dietary phenolic acids, i. e. caffeic, syringic and protocatechuic acids in leukemia cells, characterized by a very high ROS content. Our results suggest that the role played by NAD(P)H oxidase-derived ROS in the regulation of glucose uptake, proliferation and migration of leukaemia and endothelial cells could likely occur through the control of lipid raft-associated signalling.

Atomic Force Microscopy Studies of the Amyloidogenic Processes of Intrinsically Unstructured Proteins related to Neurodegenerative Diseases

Protein aggregation and formation of insoluble aggregates in central nervous system is the main cause of neurodegenerative disease. Parkinson’s disease is associated with the appearance of spherical masses of aggregated proteins inside nerve cells called Lewy bodies. α-Synuclein is the main component of Lewy bodies. In addition to α-synuclein, there are more than a hundred of other proteins co-localized in Lewy bodies: 14-3-3η protein is one of them. In order to increase our understanding on the aggregation mechanism of α-synuclein and to study the effect of 14-3-3η on it, I addressed the following questions. (i) How α-synuclein monomers pack each other during aggregation? (ii) Which is the role of 14-3-3η on α-synuclein packing during its aggregation? (iii) Which is the role of 14-3-3η on an aggregation of α-synuclein “seeded” by fragments of its fibrils? In order to answer these questions, I used different biophysical techniques (e.g., Atomic force microscope (AFM), Nuclear magnetic resonance (NMR), Surface plasmon resonance (SPR) and Fluorescence spectroscopy (FS)).

Mitochondrial inheritance and germ line determination in a bivalve species with Doubly Uniparental Inheritance (DUI)

Mitochondria are inherited maternally in most metazoans. However, in some bivalves, two mitochondrial lineages are present: one transmitted through eggs (F), the other through sperm (M). This is called Doubly Uniparental Inheritance (DUI). During male embryo development, spermatozoon mitochondria aggregate and end up in the primordial germ cells, while they are dispersed in female embryos. The molecular mechanisms of segregation patterns are still unknown. In the DUI species Ruditapes philippinarum, I examined sperm mitochondria distribution by MitoTracker, microtubule staining and TEM, and I localized germ line determinants with immunocytochemical analysis. I also analyzed the gonad transcriptome, searching for genes involved in reproduction and sex determination. Moreover, I analyzed an M-type specific open reading frame that could be responsible for maintenance/degradation of M mitochondria during embryo development. These transcripts were also localized in tissues using in situ hybridization. As in Mytilus, two distribution patterns of M mitochondria were detected in R. philippinarum, supporting that they are related to DUI. Moreover, the first division midbody concurs in positioning aggregated M mitochondria on the animal-vegetal axis of the male embryo: in organisms with spiral segmentation this zone is not involved in further cleavages, so aggregation is maintained. Moreover, sperm mitochondria reach the same embryonic area where germ plasm is transferred, suggesting their contribution in male germ line formation. The finding of reproduction and ubiquitination transcripts led to formulate a model in which ubiquitination genes stored in female oocytes during gametogenesis would activate sex-gene expression in the early embryonic developmental stages (preformation). Only gametogenetic cells were labeled by in situ hybridization, proving their specific transcription in developing gametes. Other than having a role in sex determination, some ubiquination factors could also be involved in mitochondrial inheritance, and their differential expression could be responsible for the different fate of sperm mitochondria in the two sexes.

An Analysis of Living Conditions in Rural Villages in China. A New Geography of the Country.

Analysts, politicians and international players from all over the world look at China as one of the most powerful countries on the international scenario, and as a country whose economic development can significantly impact on the economies of the rest of the world. However many aspects of this country have still to be investigated. First the still fundamental role played by Chinese rural areas for the general development of the country from a political, economic and social point of view. In particular, the way in which the rural areas have influenced the social stability of the whole country has been widely discussed due to their strict relationship with the urban areas where most people from the countryside emigrate searching for a job and a better life. In recent years many studies have mostly focused on the urbanization phenomenon with little interest in the living conditions in rural areas and in the deep changes which have occurred in some, mainly agricultural provinces. An analysis of the level of infrastructure is one of the main aspects which highlights the principal differences in terms of living conditions between rural and urban areas. In this thesis, I first carried out the analysis through the multivariate statistics approach (Principal Component Analysis and Cluster Analysis) in order to define the new map of rural areas based on the analysis of living conditions. In the second part I elaborated an index (Living Conditions Index) through the Fuzzy Expert/Inference System. Finally I compared this index (LCI) to the results obtained from the cluster analysis drawing geographic maps. The data source is the second national agricultural census of China carried out in 2006. In particular, I analysed the data refer to villages but aggregated at province level.

Spatial Disparity and Dynamic Trajectory of Convergence in China: Construction and Application of a Composite Index of Regional Development

China is a large country characterized by remarkable growth and distinct regional diversity. Spatial disparity has always been a hot issue since China has been struggling to follow a balanced growth path but still confronting with unprecedented pressures and challenges. To better understand the inequality level benchmarking spatial distributions of Chinese provinces and municipalities and estimate dynamic trajectory of sustainable development in China, I constructed the Composite Index of Regional Development (CIRD) with five sub pillars/dimensions involving Macroeconomic Index (MEI), Science and Innovation Index (SCI), Environmental Sustainability Index (ESI), Human Capital Index (HCI) and Public Facilities Index (PFI), endeavoring to cover various fields of regional socioeconomic development. Ranking reports on the five sub dimensions and aggregated CIRD were provided in order to better measure the developmental degrees of 31 or 30 Chinese provinces and municipalities over 13 years from 1998 to 2010 as the time interval of three “Five-year Plans”. Further empirical applications of this CIRD focused on clustering and convergence estimation, attempting to fill up the gap in quantifying the developmental levels of regional comprehensive socioeconomics and estimating the dynamic convergence trajectory of regional sustainable development in a long run. Four clusters were benchmarked geographically-oriented in the map on the basis of cluster analysis, and club-convergence was observed in the Chinese provinces and municipalities based on stochastic kernel density estimation.

Decomposition Methods and Network Design Problems

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).