Prevalencia y factores asociados al embarazo y su reincidencia en adolescentes colombianas

Introducción: El embarazo en adolescentes es uno de los problemas de salud pública más relevantes a nivel mundial. En Colombia, las políticas no han sido efectivas para disminuir la tasa de embarazo en edades tempranas, ni para impedir la reincidencia de la gestación. Este estudio caracteriza esta problemática determinando la prevalencia y los factores asociados tanto del embarazo en adolescentes como de su reincidencia. Métodos: Estudio de corte transversal comparativo a partir de 13,313 adolescentes colombianas respondientes de la Encuesta Nacional de Demografía y Salud, 2010. Se realizaron regresiones multinomiales para comparar el grupo de adolescentes no embarazadas con las que tuvieron uno o varios embarazos y regresión logística para comparar el grupo de embarazo único y el reincidente. Resultados: El 13.3% tuvieron un embarazo y el 3.5% más de uno. Al comparar con las adolescentes que no se embarazaron: a) las adolescentes que tuvieron un embarazo fueron mayores, convivían con su pareja, vivían con más personas, fuera de la familia de origen y habían sido víctimas de abuso sexual y maltrato físico. La probabilidad de embarazo disminuyo en aquellas adolescentes que tenían más recursos económicos, deseaban un menor número de hijos, asistían al colegio, habían usado planificación familiar y recibido educación sexual. b) En las adolescentes que tuvieron más de un embarazo se asociaron los mismos factores sin embargo no hubo diferencias regionales ni asociación con el número deseado de hijos, se encontraron otros factores como el menor nivel educativo y las mujeres de raza negra. La reincidencia también se asocio con la edad mayor del primer compañero sexual, la ausencia de control prenatal y haber tenido un recién nacido prematuro. Conclusiones: Este estudio utilizó una muestra representativa de las adolescentes colombianas. Demuestra tanto las dimensiones del problema como los factores que se encuentran asociados al mismo con lo cual se podrán direccionar programas de prevención adecuados

Log-Burr XII regression models with censored data

In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.

Comportamento dos níveis plasmáticos do Peptídeo Natriurético tipo-B em idosos com função sistólica do ventrículo esquerdo preservada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Prevalência e fatores associados a comportamentos sugestivos de transtornos alimentares entre estudantes de medicina, enfermagem e nutrição

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Prevalence and vulnerability of homeless people to HIV infection in Sao Paulo, Brazil

OBJECTIVE: To assess the prevalence and vulnerability of homeless people to HIV infection. METHODS: Cross-sectional study conducted with a non-probabilistic sample of 1,405 homeless users of shelters in the city of Sao Paulo, southeastern Brazil, from 2006 to 2007. They were all tested for HIV and a structured questionnaire was applied. Their vulnerability to HIV was determined by the frequency of condom use: those who reported using condoms only occasionally or never were considered the most vulnerable. Multinomial and logistic regression models were used to estimate effect measures and 95% confidence intervals. RESULTS: There was a predominance of males (85.6%), with a mean age of 40.9 years, 72.0% had complete elementary schooling, and 71.5% were non-white. Of all respondents, 15.7% reported being homosexual or bisexual and 62,0% reported having casual sex. The mean number of sexual partners in the last 12 months was 5.4. More than half (55.7%) of the respondents reported lifetime drug use, while 25.7% reported frequent use. Sexually-transmitted disease was reported by 39.6% of the homeless and 38.3% reported always using condoms. The prevalence of HIV infection was 4.9% (17.4% also tested positive for syphilis) and about half of the respondents (55.4%) had access to prevention programs. Higher HIV prevalence was associated with younger age (18-29 years, OR = 4.0 [95% CI 1.54; 10.46]); past history of sexually-transmitted disease (OR = 3.3 [95% CI 1.87; 5.73]); homosexual sex (OR = 3.0 [95% CI 1.28; 6.92]); and syphilis (OR = 2.4 [95% CI 1.13; 4.93]). Increased vulnerability to HIV infection was associated with being female; young; homosexual sex; having few partners or a steady partner; drug and alcohol use; not having access to prevention programs and social support. CONCLUSIONS: The HIV epidemic has a major impact on homeless people reflecting a cycle of exclusion, social vulnerability, and limited access to prevention.

Preditores da realização de consultas odontológicas de rotina e por problema em pré-escolares

OBJETIVO: Estimar a prevalência do uso de serviços odontológicos por pré- escolares e fatores associados. MÉTODOS: Estudo transversal com 1.129 crianças de cinco anos de idade da Coorte de Nascimentos de Pelotas 2004, RS, de setembro de 2009 a janeiro de 2010. Registrou-se o uso de serviço odontológico pelo menos uma vez na vida e o motivo para a primeira consulta odontológica da criança. As categorias do desfecho foram: ter feito a primeira consulta por rotina, para resolver um problema ou nunca ter ido ao dentista. Os exames bucais e as entrevistas foram realizados nos domicílios. Aspectos socioeconômicos e variáveis independentes ligadas à mãe e à criança foram analisados por meio de regressão logística multinomial. RESULTADOS: A prevalência de uso por qualquer motivo foi 37,0%. Os principais preditores para consulta de rotina foram nível econômico mais elevado, mãe com maior escolaridade e ter recebido orientação sobre prevenção. Principais preditores para consulta por problema foram ter sentido dor nos últimos seis meses, mãe com maior escolaridade e ter recebido orientação sobre prevenção. Cerca de 45,0% das mães receberam orientação de como prevenir cárie, principalmente fornecida por dentistas. Filhos de mães com história de maior aderência a programas de saúde tiveram maior probabilidade de ter feito uma consulta odontológica de rotina. CONCLUSÕES: A taxa de utilização dos serviços odontológicos por pré- escolares foi inferior às de consultas médicas (puericultura). Além da renda e da escolaridade, comportamentos maternos têm papel importante no uso por rotina. Relato de dor nos últimos seis meses e número elevado de dentes afetados por cárie, independentemente dos demais fatores, estiveram associados ao uso para resolver problema. É necessária a integração de ações de saúde bucal nos programas materno-infantis.

Diagnostic utility of immunohistochemistry in distinguishing trichoepithelioma and basal cell carcinoma: evaluation using tissue microarray samples

Trichoepithelioma is a benign neoplasm that shares both clinical and histological features with basal cell carcinoma. It is important to distinguish these neoplasms because they require different clinical behavior and therapeutic planning. Many studies have addressed the use of immunohistochemistry to improve the differential diagnosis of these tumors. These studies present conflicting results when addressing the same markers, probably owing to the small number of basaloid tumors that comprised their studies, which generally did not exceed 50 cases. We built a tissue microarray with 162 trichoepithelioma and 328 basal cell carcinoma biopsies and tested a panel of immune markers composed of CD34, CD10, epithelial membrane antigen, Bcl-2, cytokeratins 15 and 20 and D2-40. The results were analyzed using multiple linear and logistic regression models. This analysis revealed a model that could differentiate trichoepithelioma from basal cell carcinoma in 36% of the cases. The panel of immunohistochemical markers required to differentiate between these tumors was composed of CD10, cytokeratin 15, cytokeratin 20 and D2-40. The results obtained in this work were generated from a large number of biopsies and resulted in the confirmation of overlapping epithelial and stromal immunohistochemical profiles from these basaloid tumors. The results also corroborate the point of view that trichoepithelioma and basal cell carcinoma tumors represent two different points in the differentiation of a single cell type. Despite the use of panels of immune markers, histopathological criteria associated with clinical data certainly remain the best guideline for the differential diagnosis of trichoepithelioma and basal cell carcinoma. Modern Pathology (2012) 25, 1345-1353; doi: 10.1038/modpathol.2012.96; published online 8 June 2012

Rates Of Obesity And Incidence Of Diabetes In Hispanics In The United States: An Examination Of The Epidemiological Paradox

Using pooled data from the 2008-2011 National Health Interview Survey and employing multinomial and binomial logistic regression methods, this research examines disparities in rates of obesity and incidence of diabetes between individual Hispanic subgroups in comparison to non-Hispanic whites and blacks. Immigration status(including nativity, duration in the United States, and citizenship status) is hypothesized to play a central role in rates and obesity and incidence of diabetes. Unlike Cuban-Americans, Mexican-Americans, Puerto Ricans, and other Hispanics were more likely to be overweight as well as obese when compared to non-Hispanic whites. Mexican-Americans had the only significance in prevalence of type 2 diabetes in comparison to non-Hispanic whites. Both of these health outcomes are strongly associated with the various immigration variables.

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Systematic analysis of factors associated with progression and regression of ulcerative colitis in 918 patients.

BACKGROUND Studies that systematically assess change in ulcerative colitis (UC) extent over time in adult patients are scarce. AIM To assess changes in disease extent over time and to evaluate clinical parameters associated with this change. METHODS Data from the Swiss IBD cohort study were analysed. We used logistic regression modelling to identify factors associated with a change in disease extent. RESULTS A total of 918 UC patients (45.3% females) were included. At diagnosis, UC patients presented with the following disease extent: proctitis [199 patients (21.7%)], left-sided colitis [338 patients (36.8%)] and extensive colitis/pancolitis [381 (41.5%)]. During a median disease duration of 9 [4-16] years, progression and regression was documented in 145 patients (15.8%) and 149 patients (16.2%) respectively. In addition, 624 patients (68.0%) had a stable disease extent. The following factors were identified to be associated with disease progression: treatment with systemic glucocorticoids [odds ratio (OR) 1.704, P = 0.025] and calcineurin inhibitors (OR: 2.716, P = 0.005). No specific factors were found to be associated with disease regression. CONCLUSIONS Over a median disease duration of 9 [4-16] years, about two-thirds of UC patients maintained the initial disease extent; the remaining one-third had experienced either progression or regression of the disease extent.

A significant effect of the KIR ligand HLA-C on fibrosis progression in chronic C hepatitis with or without liver transplantation.

BACKGROUND & AIMS The interaction of KIR with their HLA ligands drives the activation and inhibition of natural killer (NK) cells. NK cells could be implicated in the development of liver fibrosis in chronic hepatitis C. METHODS We analysed 206 non-transplanted and 53 liver transplanted patients, selected according to their Metavir fibrosis stage. Several variables such as the number of activator KIR or the HLA ligands were considered in multinomial and logistic regression models. Possible confounding variables were also investigated. RESULTS The KIRs were not significant predictors of the fibrosis stage. Conversely, a significant reduction of the HLA-C1C2 genotype was observed in the most advanced fibrosis stage group (F4) in both cohorts. Furthermore, the progression rate of fibrosis was almost 10 times faster in the subgroup of patients after liver transplantation and HLA-C1C2 was significantly reduced in this cohort compared to non-transplanted patients. CONCLUSION This study suggests a possible role of KIR and their ligands in the development of liver damage. The absence of C1 and C2 ligands heterozygosity could lead to less inhibition of NK cells and a quicker progression to a high level of fibrosis in patients infected by HCV, especially following liver transplantation. This article is protected by copyright. All rights reserved.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

The effect of maternal employment on adolescents' transition to young adulthood

The purpose of this study was to examine relationships between multiple characteristics of maternal employment, parenting practices, and adolescents’ transition outcomes to young adulthood. The research addressed four main research questions. First, are the characteristics of maternal work (i.e., hours worked, multiple jobs held, work schedules, earnings, and occupation) related to adolescents’ enrollment in post-secondary education, employment, or involvement in neither of these types of activities as young adults? Second, are the work characteristics related to parental involvement and monitoring, and are the parenting practices related to adolescents’ transition outcomes? Third, do parental involvement and monitoring mediate any relationships between the characteristics of maternal employment and adolescents’ transition outcomes? Finally, do any associations between characteristics of maternal employment and parenting practices and adolescents’ transition outcomes vary by poverty status, race/ethnicity, or gender? To address these research questions, secondary data analysis was conducted, using data from the National Longitudinal Survey of Youth (NLSY) from 1998 through 2004. The study sample consisted of 849 youths who were 15 through 17 years of age in either 1998 or 2000, and were 19 through 21 years of age when their transition outcomes in young adulthood were measured four years later. Multinomial logistic and ordinary least squares regression models were estimated to answer the research questions. Study findings indicated that of the maternal work characteristics, mothers’ multiple jobs held, occupation, and work schedule were significantly related to the youths’ transition outcomes. When mothers held multiple jobs for 1 to 25 weeks per year, and when mothers held jobs involving lower levels of occupational complexity, their youths were more likely to experience employment rather than post-secondary education. Adolescents whose mothers worked a standard work schedule were less likely to experience other types of transitions than post-secondary education. With regard to the effects of maternal employment on parenting practices, none of the maternal work variables were related to parental involvement, and only one variable, mothers working less than 40 hours per week, was negatively related to parental monitoring. In addition, when parents were more involved with their youths’ education, the youths were less likely to transition into employment and other types of transitions rather than post-secondary education. The parenting practices did not mediate the relation between the significant work variables (holding multiple jobs, work schedule, and occupation) and youths’ transition outcomes. Finally, none of the interactions between maternal work characteristics and poverty status, race/ethnicity, and gender met the criteria for determining significance; but in a series of sub-group analyses, some differences according to poverty status and gender were found. Despite the lack of mediation and moderation, the findings of this study have important implications for social policy and social work intervention. Based on the findings, suggestions are made in these areas to improve working mothers’ lives and their adolescents’ development and successful transition to adulthood. Finally, directions for future research are discussed.