Background: Primary prevention efforts for both gastroschisis and omphalocele are limited by the lack of known risk factors. Our objective was to investigate associations between potential maternal risk factors and gastroschisis and omphalocele within a large population-based sample of participants enrolled in the National Birth Defects Prevention Study (NBDPS). Methods: Demographic, health-related, and environmental exposure data from the NBDPS were collected from women with expected delivery dates between October 1997 and December 2003. Data were collected on 485 cases of gastroschisis, 168 cases of omphalocele, and 4967 controls. Results: Women who had offspring with gastroschisis were younger (adjusted odds ratio [AOR], 0.84; 95% confidence interval [CI], 0.81-0.86) and less likely to be black (AOR, 0.54; 95% CI, 0.34-0.85) than controls. They also were more likely to have smoked (AOR, 1.51; 95% CI, 1.12-2.03), taken ibuprofen (AOR, 1.61; 95% CI, 1.23-2.10), and consumed alcohol (AOR, 1.38; 95% CI, 1.06-1.79) than controls. Women who had offspring with omphaloceles were more likely to have consumed alcohol (AOR, 1.53; 95% CI, 1.04-2.25) and be heavy smokers (AOR, 4.26; 95% CI, 1.58-11.52) than controls. Conclusions: Our results suggest a moderately increased risk of gastroschisis among women who used tobacco, alcohol, and ibuprofen during early pregnancy. A modestly elevated risk was observed for omphaloceles among women who used alcohol during the first trimester and among women who were heavy smokers.

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No description available.

Background/Aims: Case-control designs are commonly employed in genetic association studies. In addition to the primary trait of interest, data on additional secondary traits, related to the primary trait, are often collected. Traditional association analyses between genetic variants and secondary traits can be biased in such cases, and several methods have been proposed to address this issue, including the inverse-probability-of-sampling-weighted (IPW) approach and semi-parametric maximum likelihood (SPML) approach. Methods: Here, we propose a set of new estimating equation based approach that combines observed and counter-factual outcomes to provide unbiased estimation of genetic associations with secondary traits. We extend the estimating equation framework to both generalized linear models (GLM) and non-parametric regressions, and compare it with the existing approaches. Results: We demonstrate analytically and numerically that our proposed approach provides robust and fairly efficient unbiased estimation in all simulations we consider. Unlike existing methods, it is less sensitive to the sampling scheme and underlying disease model specification. In addition, we illustrate our new approach using two real data examples. The first one is to analyze the binary secondary trait diabetes under GLM framework using a stroke case-control study. The second one is to analyze the continuous secondary trait serum IgE levels under linear and quantile regression models using an asthma case-control study. Conclusion: The proposed new estimating equation approach is able to accommodate a wide range of regressions, and it outperforms the existing approaches in some scenarios we consider.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / This letter has the purpose to comment the article by Marwaha et al. regarding affective instability and mental disorders. We wish to highlight the importance to report the proper measures of association in case-control studies, and the impact of adjusting the results when finding associations with possible confounders in the bivariate analysis. / Revisión por pares / Revisión por pares

Background: Despite a declining trend in the incidence of gastric cancer (GC), it is still a major global public health concern of the 21st century. It afflicts one million people and kills 750,000 annually. It is believed that both genetic and environmental factors contribute to the gastric carcinogenesis. However geographic variation and immigrant studies highlight the role of environmental factors. Objective: To evaluate the association of GC with the environmental factors of diet, helicobacter pylori (H. pylori) infection, lifestyle and occupation as well as family history in Iran. Methodology: A population based case-control study was conducted in the Northwest of Iran where one of the highest incidence rates of the world has been reported. Two hundred and seventeen cases of GC and 394 age and gender matched controls were recruited. Participants were interviewed using a structured questionnaire which elicited information on demographic characteristics, socioeconomic status, family and medical history, lifestyle (smoking, alcohol drinking and substance abuse) and occupation. Ten milliliters of each subject???s blood was collected for blood grouping and to investigate presence of IgG antibodies against H. pylori using an ELISA kit which had been locally validated for this study. Results: Diet and H. pylori infection were found to be the most important determinants of GC in this study. High intake of allium vegetables and fruit, especially citrus fruit, appears to play a protective role. In addition to the consumption of fruit and vegetables, consumption of fresh fish was also inversely associated with GC. On the other, hand consumption of red meat and dairy products were positively associated with the risk of GC. Other dietary practices were also found to be important factors in the etiology of GC. People who had a preference for higher salt intake and drinking strong and hot tea were at higher risk. Finally, H. pylori infection was found to increase the risk of GC. Conclusion: This study has provided important and original information about the etiology of gastric cancer particularly in the Iranian context. These findings could be used in planning preventive strategies for this malignancy, which is a major health problem in Iran.

Postpartum depression is by definition a major depression with an onset during the first weeks after delivery. In practice, however, the term, postpartum depression is used to characterize all kinds of depressive symptoms after childbirth. The aims of this thesis were to investigate the prevalence of depressive symptoms during late pregnancy, in the puerperium and four years after delivery, and to analyze the mothers’ estimation of personal health and their children’s behavior at the age of four. Additional goals were to test the predictive power of potential associated factors of postpartum depression during pregnancy and the puerperium and finally, to elucidate possible genetic or neuropeptidergic explanatory variables behind the development of postpartum depression. A population-based sample of 1489 women was screened with the Edinburgh Postnatal Depression Scale and the prevalence of depressive symptoms was 17% in late pregnancy and 13% postpartum. Antenatal depressed mood was related to postpartum depression. In a cross-sectional study we later found that postpartum depression was associated with subsequent depressive symptoms and current health problems four years after childbirth. Four-year-old boys of postpartum depressed mothers and children of mothers with a subsequent depressive status had more behavior problems than children of non-symptomatic mothers did, according to the mothers’ opinion. The strongest associated factors for postpartum depression, in a case-control study, were sick leave during pregnancy mainly due to pregnancy complications, e.g. hyperemesis and premature contractions and a high number of visits to the antenatal care clinic. There was no association between delivery complications or complications in the perinatal period and postpartum depression. The theory that depressive symptoms in late pregnancy or postpartum are connected with CYP2D6 genotype could not be confirmed. In a rat model, we found that pregnancy and parturition influence the concentrations of neuropeptide Y, cholecystokinin, substance P and galanin in the rat brain. This result supports the hypothesis that neuropeptidergic systems in the brain influence the mood changes around childbirth. In conclusion, postpartum depression is a common feature with influence on both maternal and child well being. / Pages 26 and 57 containing illustrations are removed from the electronic version. On the day of the public defence the status of article IV was: Accepted for publication.

This dissertation consists of five independent projects. In each project, a novel statistical method was developed to address a practical problem encountered in genomic contexts. For example, we considered testing for constant nonparametric effects in a general semiparametric regression model in genetic epidemiology; analyzed the relationship between covariates in the secondary analysis of case-control data; performed model selection in joint modeling of paired functional data; and assessed the prediction ability of genes in gene expression data generated by the CodeLink System from GE. In the first project in Chapter II we considered the problem of testing for constant nonparametric effects in a general semiparametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. We derived a generalized likelihood ratio test for this hypothesis, showed how to implement it, and gave evidence that it can improve statistical power when compared to standard partially linear models. The second project in Chapter III addressed the issue of score testing for the independence of X and Y in the second analysis of case-control data. The semiparametric efficient approaches can be used to construct semiparametric score tests, but they suffer from a lack of robustness to the assumed model for Y given X. We showed how to adjust the semiparametric score test to make its level/Type I error correct even if the assumed model for Y given X is incorrect, and thus the test is robust. The third project in Chapter IV took up the issue of estimation of a regression function when Y given X follows a homoscedastic regression model. We showed how to estimate the regression parameters in a rare disease case even if the assumed model for Y given X is incorrect, and thus the estimates are model-robust. In the fourth project in Chapter V we developed novel AIC and BIC-type methods for estimating the smoothing parameters in a joint model of paired, hierarchical sparse functional data, and showed in our numerical work that they are many times faster than 10-fold crossvalidation while at the same time giving results that are remarkably close to the crossvalidated estimates. In the fifth project in Chapter VI we introduced a practical permutation test that uses cross-validated genetic predictors to determine if the list of genes in question has “good” prediction ability. It avoids overfitting by using cross-validation to derive the genetic predictor and determines if the count of genes that give “good” prediction could have been obtained by chance. This test was then used to explore gene expression of colonic tissue and exfoliated colonocytes in the fecal stream to discover similarities between the two.

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 33-40).

An important prerequisite for running a successful insurance business is to predict risk. By forecasting the future in as much detail as possible, competitive advantages are created in terms of price differentiation. This work aims at using spatial point processes to provide a proposal for how the geographical position of the customer can be used in developing risk differentiation tools. For spatial variation in claim frequency an approach is presented which is common in spatial epidemiology by considering a group of policyholders, with and without claims, as a realisation of a multivariate Poisson point process in two dimensions. Claim costs are then included by considering the claims as a realisation of a point process with continuous marks. To describe the spatial variation in relative risk, demographic and socio-economic information from Swedish agencies have been used. The insurance data that have been used come from the insurance company If Skadeförsäkring AB, where also the work has been carried out. The result demonstrates problems with parametric modelling of the intensity of policyholders, which makes it difficult to validate the spatial varying intensity of claim frequency. Therefore different proposals of non-parametric estimation are discussed. Further, there are no tendencies that the selected information is able to explain the variation in claim costs. / En viktig förutsättning för att kunna bedriva en framgångsrik försäkringsverksamhet är att prediktera risk. Genom att på en så detaljerad nivå som möjligt kunna förutse framtiden skapas konkurrensfördelar i form av prisdifferentiering. Målet med detta arbete är att med hjälp av spatiala punktprocesser ge ett förslag på hur kunders geografiska position kan utvecklas som riskdifferentieringsverktyg. För spatial variation i skadefrekvens presenteras ett tillvägagångssätt som är vanligt inom spatial epidemiologi genom att betrakta en grupp försäkringstagare, med och utan skador, som en realisering av en multivariat Poissonprocess i två dimensioner. Skadekostnaderna inkluderas sedan genom att betrakta skadorna som en punktprocess med kontinuerliga märken. För att beskriva spatial variation i relativ risk används demografisk och socioekonomisk information från svenska myndigheter. De försäkringsdata som använts kommer från If Skadeförsäkring AB, där också arbetet har utförts. Resultatet påvisar problem med att parametriskt modellera intensiteten för försäkringstagare, vilket medför svårigheter att validera den skattade spatiala variationen i skadefrekvens, varför olika ickeparametriska förslag diskuteras. Vidare upptäcktes inga tendenser till att variationen i skadekostnad kan förklaras med den utvalda informationen.