Hormone replacement therapy and risk of hip fracture: population based case-control study

Objective: To determine the relative risk of hip fracture associated with postmenopausal hormone replacement therapy including the effect of duration and recency of treatment, the addition of progestins, route of administration, and dose.

An increased risk of Crohn's disease in individuals who inherit the HLA class II DRB3*0301 allele.

The role of inflammatory T cells in Crohn's disease suggests that inherited variations in major histocompatibility complex (MHC) class II genes may be of pathogenetic importance in inflammatory bowel disease. The absence of consistent and strong associations with MHC class II genes in Caucasian patients with inflammatory bowel disease probably reflects the use of less precise typing approaches and the failure to type certain loci by any means. A PCR-sequence-specific oligonucleotide-based approach was used to type individual alleles of the HLA class II DRB1, DRB3, DRB4, and DRB5 loci in 40 patients with ulcerative colitis, 42 Crohn's disease patients, and 93 ethnically matched healthy controls. Detailed molecular typing of the above alleles has previously not been reported in patients with inflammatory bowel disease. A highly significant positive association with the HLA-DRB3*0301 allele was observed in patients with Crohn's disease (P = 0.0004) but not in patients with ulcerative colitis. The relative risk for this association was 7.04. Other less significant HLA class II associations were also noted in patients with Crohn's disease. One of these associations involved the HLA-DRB1*1302 allele, which is known to be in linkage disequilibrium with HLA-DRB3*0301. These data suggest that a single allele of an infrequently typed HLA class II locus is strongly associated with Crohn's disease and that MHC class II molecules may be important in its pathogenesis.

The effect of extreme cold temperatures on the risk of death in the two major Portuguese cities

It is well known that meteorological conditions influence the comfort and human health. Southern European countries, including Portugal, show the highest mortality rates during winter, but the effects of extreme cold temperatures in Portugal have never been estimated. The objective of this study was the estimation of the effect of extreme cold temperatures on the risk of death in Lisbon and Oporto, aiming the production of scientific evidence for the development of a real-time health warning system. Poisson regression models combined with distributed lag non-linear models were applied to assess the exposure-response relation and lag patterns of the association between minimum temperature and all-causes mortality and between minimum temperature and circulatory and respiratory system diseases mortality from 1992 to 2012, stratified by age, for the period from November to March. The analysis was adjusted for over dispersion and population size, for the confounding effect of influenza epidemics and controlled for long-term trend, seasonality and day of the week. Results showed that the effect of cold temperatures in mortality was not immediate, presenting a 1–2-day delay, reaching maximumincreased risk of death after 6–7 days and lasting up to 20–28 days. The overall effect was generally higher and more persistent in Lisbon than in Oporto, particularly for circulatory and respiratory mortality and for the elderly. Exposure to cold temperatures is an important public health problem for a relevant part of the Portuguese population, in particular in Lisbon.

Price stabilization and the risk-averse firm

An analytically simple and tractable approach to firm-level welfare analysis of complete and partial mean-preserving price stabilization for producers with general risk-averse preferences facing a stochastic technology is developed. Necessary and sufficient conditions for price stabilization to be welfare enhancing are derived under different assumptions of the producer's preferences and the producer's technology. Existing stabilization results for the risk-averse firm are shown to be corollaries of these more general results.

Effect of conditional release from hospitalization on mortality risk

Objectives: This study considered the protective value provided by conditional release. It assessed the contribution of conditional release to mortality risk among patients with mental disorders severe enough to require psychiatric hospitalization during a mental health treatment span of 13.5 years in Victoria, Australia. Methods: Death records were obtained from the Australian National Death Index for a sample of 24,973 Victorian Psychiatric Case Register patients with a history of psychiatric hospitalizations: 8,879 had experienced at least one conditional release during community care intervals and 16,094 had not. Risk of death was assessed with standardized mortality ratios of the general population of Victoria. Relative risk of death among patients with and without past experience of conditional release was computed with risk and odds ratios. The contribution of conditional release to mortality, taking into account use of community care services, age, gender, inpatient experience, and diagnosis, as well as other controls, was assessed with logistic regression. Results: Patients who had been hospitalized showed higher mortality risk than the general population. Sixteen percent ( 4,034) died. Patients exposed to conditional release, however, had a 14 percent reduction in probability of noninjury-related death and a 24 percent reduction per day on orders in the probability of death from injury compared with those not offered such oversight throughout their mental health treatment, all other factors taken into account. Conclusions: Conditional release can offer protective oversight for those considered dangerous to self or others and appears to reduce mortality risk among those with disorders severe enough to require psychiatric hospitalization.

Theory of foreign portfolio investment

This dissertation examines one category of international capital flows, private portfolio investments (private refers to the source of capital). There is an overall lack of a coherent and consistent definition of foreign portfolio investment. We clarify these definitional issues.^ Two main questions that pertain to private foreign portfolio investments (FPI) are explored. The first problem is the phenomenon of home preference, often referred to as home bias. Related to this are the observed cross-investment flows between countries that seem to contradict the textbook rendition of private FPI. A description of the theories purporting to resolve the home preference puzzle (and the cross-investment one) are summarized and evaluated. Most of this literature considers investors from major developed countries. I consider--as well--whether investors in less developed countries have home preference.^ The dissertation shows that home preference is indeed pervasive and profound across countries, in both developed and emerging markets. For the U.S., I examine home bias in both equity and bond holdings as well. I find that home bias is greater when we look at equity and bond holdings than equity holdings solely.^ In this dissertation a model is developed to explain home bias. This model is original and fills a gap in the literature as there have been no satisfactory models that handle at the same time both home preference and cross-border holdings in the context of information asymmetries. This model reflects what we see in the data and permits us to reach certain results by the use of comparative statics methods. The model suggests, counter-intuitively, that as the rate of return in a country relative to the world rate of return increases, home preference decreases. In the context of our relatively simple model we ascribe this result to the higher variance of the now higher return for home assets. We also find, this time as intended, that as risk aversion increases, investors diversify further so that home preference decreases.^ The second question that the dissertation deals with is the volatility of private foreign portfolio investment. Countries that are recipients of these flows have been wary of such flows because of their perceived volatility. Often the contrast is made with the perceived absence of volatility in foreign direct investment flows. I analyze the validity of these concerns using first net flow data and then gross flow data. The results show that FPI is not, in relative terms, more volatile than other flows in our sample of eight countries (half were developed countries and the rest were emerging markets).^ The implication therefore is that restricting FPI flows may be harmful in the sense that private capital may not be allocated efficiently worldwide to the detriment of capital poor economies. More to the point, any such restrictions would in fact be misguided. ^

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Risk Preferences and the Role of Emotions

There is a large volume of research showing that emotions have relevant effects on decision-making. We contribute to this literature by experimentally investigating the impact of four specific emotional states - joviality, sadness, fear, and anger - on risk attitudes. In order to do so, we fit two models of behavior under risk: the Expected Utility model (EU) and the Rank Dependent Expected Utility model (RDEU), assuming several functional forms of the weighting function. Our results indicate that all emotional states mitigate risk aversion. Furthermore, we show that there are some differences across gender and participants' experience in laboratory experiments.

Troponin I and cardiovascular risk prediction in the general population: the BiomarCaRE consortium

AIMS: Our aims were to evaluate the distribution of troponin I concentrations in population cohorts across Europe, to characterize the association with cardiovascular outcomes, to determine the predictive value beyond the variables used in the ESC SCORE, to test a potentially clinically relevant cut-off value, and to evaluate the improved eligibility for statin therapy based on elevated troponin I concentrations retrospectively.

METHODS AND RESULTS: Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project, we analysed individual level data from 10 prospective population-based studies including 74 738 participants. We investigated the value of adding troponin I levels to conventional risk factors for prediction of cardiovascular disease by calculating measures of discrimination (C-index) and net reclassification improvement (NRI). We further tested the clinical implication of statin therapy based on troponin concentration in 12 956 individuals free of cardiovascular disease in the JUPITER study. Troponin I remained an independent predictor with a hazard ratio of 1.37 for cardiovascular mortality, 1.23 for cardiovascular disease, and 1.24 for total mortality. The addition of troponin I information to a prognostic model for cardiovascular death constructed of ESC SCORE variables increased the C-index discrimination measure by 0.007 and yielded an NRI of 0.048, whereas the addition to prognostic models for cardiovascular disease and total mortality led to lesser C-index discrimination and NRI increment. In individuals above 6 ng/L of troponin I, a concentration near the upper quintile in BiomarCaRE (5.9 ng/L) and JUPITER (5.8 ng/L), rosuvastatin therapy resulted in higher absolute risk reduction compared with individuals <6 ng/L of troponin I, whereas the relative risk reduction was similar.

CONCLUSION: In individuals free of cardiovascular disease, the addition of troponin I to variables of established risk score improves prediction of cardiovascular death and cardiovascular disease.

Prevalence and risk of Down syndrome in monozygotic and dizygotic multiple pregnancies in Europe: implications for prenatal screening

OBJECTIVE: To determine risk of Down syndrome (DS) in multiple relative to singleton pregnancies, and compare prenatal diagnosis rates and pregnancy outcome.

DESIGN: Population-based prevalence study based on EUROCAT congenital anomaly registries.

SETTING: Eight European countries.

POPULATION: 14.8 million births 1990-2009; 2.89% multiple births.

METHODS: DS cases included livebirths, fetal deaths from 20 weeks, and terminations of pregnancy for fetal anomaly (TOPFA). Zygosity is inferred from like/unlike sex for birth denominators, and from concordance for DS cases.

MAIN OUTCOME MEASURES: Relative risk (RR) of DS per fetus/baby from multiple versus singleton pregnancies and per pregnancy in monozygotic/dizygotic versus singleton pregnancies. Proportion of prenatally diagnosed and pregnancy outcome.

STATISTICAL ANALYSIS: Poisson and logistic regression stratified for maternal age, country and time.

RESULTS: Overall, the adjusted (adj) RR of DS for fetus/babies from multiple versus singleton pregnancies was 0.58 (95% CI 0.53-0.62), similar for all maternal ages except for mothers over 44, for whom it was considerably lower. In 8.7% of twin pairs affected by DS, both co-twins were diagnosed with the condition. The adjRR of DS for monozygotic versus singleton pregnancies was 0.34 (95% CI 0.25-0.44) and for dizygotic versus singleton pregnancies 1.34 (95% CI 1.23-1.46). DS fetuses from multiple births were less likely to be prenatally diagnosed than singletons (adjOR 0.62 [95% CI 0.50-0.78]) and following diagnosis less likely to be TOPFA (adjOR 0.40 [95% CI 0.27-0.59]).

CONCLUSIONS: The risk of DS per fetus/baby is lower in multiple than singleton pregnancies. These estimates can be used for genetic counselling and prenatal screening.

Risque de prix et décisions de production et d'exportation : le cas de l'agriculture au Québec

Cette thèse porte sur l’effet du risque de prix sur la décision des agriculteurs et les transformateurs québécois. Elle se divise en trois chapitres. Le premier chapitre revient sur la littérature. Le deuxième chapitre examine l’effet du risque de prix sur la production de trois produits, à savoir le maïs grain, la viande de porc et la viande d’agneau dans la province Québec. Le dernier chapitre est centré sur l’analyse de changement des préférences du transformateur québécois de porc pour ce qui est du choix de marché. Le premier chapitre vise à montrer l’importance de l’effet du risque du prix sur la quantité produite par les agriculteurs, tel que mis en évidence par la littérature. En effet, la littérature révèle l’importance du risque de prix à l’exportation sur le commerce international. Le deuxième chapitre est consacré à l’étude des facteurs du risque (les anticipations des prix et la volatilité des prix) dans la fonction de l’offre. Un modèle d’hétéroscédasticité conditionnelle autorégressive généralisée (GARCH) est utilisé afin de modéliser ces facteurs du risque. Les paramètres du modèle sont estimés par la méthode de l’Information Complète Maximum Vraisemblance (FIML). Les résultats empiriques montrent l’effet négatif de la volatilité du prix sur la production alors que la prévisibilité des prix a un effet positif sur la quantité produite. Comme attendu, nous constatons que l’application du programme d’assurance-stabilisation des revenus agricoles (ASRA) au Québec induit une plus importante sensibilité de l’offre par rapport au prix effectif (le prix incluant la compensation de l’ASRA) que par rapport au prix du marché. Par ailleurs, l’offre est moins sensible au prix des intrants qu’au prix de l’output. La diminution de l’aversion au risque de producteur est une autre conséquence de l’application de ce programme. En outre, l’estimation de la prime marginale relative au risque révèle que le producteur du maïs est le producteur le moins averse au risque (comparativement à celui de porc ou d’agneau). Le troisième chapitre consiste en l’analyse du changement de préférence du transformateur québécois du porc pour ce qui est du choix de marché. Nous supposons que le transformateur a la possibilité de fournir les produits sur deux marchés : étranger et local. Le modèle théorique explique l’offre relative comme étant une fonction à la fois d’anticipation relative et de volatilité relative des prix. Ainsi, ce modèle révèle que la sensibilité de l’offre relative par rapport à la volatilité relative de prix dépend de deux facteurs : d’une part, la part de l’exportation dans la production totale et d’autre part, l’élasticité de substitution entre les deux marchés. Un modèle à correction d’erreurs est utilisé lors d’estimation des paramètres du modèle. Les résultats montrent l’effet positif et significatif de l’anticipation relative du prix sur l’offre relative à court terme. Ces résultats montrent donc qu’une hausse de la volatilité du prix sur le marché étranger par rapport à celle sur le marché local entraine une baisse de l’offre relative sur le marché étranger à long terme. De plus, selon les résultats, les marchés étranger et local sont plus substituables à long terme qu’à court terme.

Major depression: does gender influence the risk of recurrence? A systematic review

Background and Objectives: A woman's lifetime risk of major depression is almost twice as high as that of a man. Major depression is associated with a high risk of recurrence, but the question of a differential risk of recurrence between genders is unclear. Based on a systematic review of the literature, this paper attempts to answer the following question: "Following a major depressive episode, do women and men have the same risk of recurrence?". Methods: We prospectively collected all studies from the period 2005-2014 where the variable gender was considered a potential predictor of recurrence. The database has also been expanded with articles cited in the bibliography of the prospectively collected articles and with a PubMed Database search covering the period January 2005-August 2014. Results: Of the prospective studies (n = 98), most found no influence of gender on recurrence risk, but a minority, mostly large sample studies, found that female gender is a statistically significant risk factor for recurrence. Results suggest a probable female-to-male relative risk of recurrence between 1.0 and 1.2. Given the heterogeneity of the studies (length of follow-up, populations, nature of the studies, choice of dependant variables, statistical methods, and available data) no meta-analyses were performed. There are many interfering variables (age of onset, subchronic evolution, treatments, etc.) that can influence the results of prospective studies. Conclusions: Women probably have a slightly higher risk of recurrence after a major depressive episode than men. This increased risk is much smaller than women's much higher lifetime risk of depression.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Risk management for mathematical optimization under uncertainty

We present a general multistage stochastic mixed 0-1 problem where the uncertainty appears everywhere in the objective function, constraints matrix and right-hand-side. The uncertainty is represented by a scenario tree that can be a symmetric or a nonsymmetric one. The stochastic model is converted in a mixed 0-1 Deterministic Equivalent Model in compact representation. Due to the difficulty of the problem, the solution offered by the stochastic model has been traditionally obtained by optimizing the objective function expected value (i.e., mean) over the scenarios, usually, along a time horizon. This approach (so named risk neutral) has the inconvenience of providing a solution that ignores the variance of the objective value of the scenarios and, so, the occurrence of scenarios with an objective value below the expected one. Alternatively, we present several approaches for risk averse management, namely, a scenario immunization strategy, the optimization of the well known Value-at-Risk (VaR) and several variants of the Conditional Value-at-Risk strategies, the optimization of the expected mean minus the weighted probability of having a "bad" scenario to occur for the given solution provided by the model, the optimization of the objective function expected value subject to stochastic dominance constraints (SDC) for a set of profiles given by the pairs of threshold objective values and either bounds on the probability of not reaching the thresholds or the expected shortfall over them, and the optimization of a mixture of the VaR and SDC strategies.

Attitudes towards risk in financial decision making

Doutoramento em Gestão