Intimate partner violence after the diagnosis of sexually transmitted diseases

OBJECTIVE To assess the prevalence and factors associated with intimate partner violence after the diagnosis of sexually transmitted diseases.METHODS This cross-sectional study was conducted in Fortaleza, CE, Northeastern Brazil, in 2012 and involved 221 individuals (40.3% male and 59.7% female) attended to at reference health care units for the treatment of sexually transmitted diseases. Data were collected using a questionnaire applied during interviews with each participant. A multivariate analysis with a logistic regression model was conducted using the stepwise technique. Only the variables with a p value < 0.05 were included in the adjusted analysis. The odds ratio (OR) with 95% confidence interval (CI) was used as the measure of effect.RESULTS A total of 30.3% of the participants reported experiencing some type of violence (27.6%, psychological; 5.9%, physical; and 7.2%, sexual) after the diagnosis of sexually transmitted disease. In the multivariate analysis adjusted to assess intimate partner violence after the revelation of the diagnosis of sexually transmitted diseases, the following variables remained statistically significant: extramarital relations (OR = 3.72; 95%CI 1.91;7.26; p = 0.000), alcohol consumption by the partner (OR = 2.16; 95%CI 1.08;4.33; p = 0.026), history of violence prior to diagnosis (OR = 2.87; 95%CI 1.44;5.69; p = 0.003), and fear of disclosing the diagnosis to the partner (OR = 2.66; 95%CI 1.32;5.32; p = 0.006).CONCLUSIONS Individuals who had extramarital relations, experienced violence prior to the diagnosis of sexually transmitted disease, feared disclosing the diagnosis to the partner, and those whose partner consumed alcohol had an increased likelihood of suffering violence. The high prevalence of intimate partner violence suggests that this population is vulnerable and therefore intervention efforts should be directed to them. Referral health care services for the treatment of sexually transmitted diseases can be strategic places to identify and prevent intimate partner violence.

Bullying among adolescents in a Brazilian urban center – “Health in Beagá” Study

OBJECTIVE To analyze the prevalence of bullying and its associated factors in Brazilian adolescents.METHODS Data were used from a population-based household survey conducted by the Urban Health Observatory (OSUBH) utilizing probability sampling in three stages: census tracts, residences, and individuals. The survey included 598 adolescents (14-17 years old) who responded questions on bullying, sociodemographic characteristics, health-risk behaviors, educational well-being, family structure, physical activity, markers of nutritional habits, and subjective well-being (body image, personal satisfaction, and satisfaction with their present and future life). Univariate and multivariate analysis was done using robust Poisson regression.RESULTS The prevalence of bullying was 26.2% (28.0% among males, 24.0% among females). The location of most bullying cases was at or on route to school (70.5%), followed by on the streets (28.5%), at home (9.8%), while practicing sports (7.3%), at parties (4.6%), at work (1.7%), and at other locations (1.6%). Reports of bullying were associated with life dissatisfaction, difficulty relating to parents, involvement in fights with peers and insecurity in the neighborhood.CONCLUSIONS A high prevalence of bullying among participating adolescents was found, and the school serves as the main bullying location, although other sites such as home, parties and workplace were also reported. Characteristics regarding self-perception and adolescent perceptions of their environment were also associated with bullying, thus advancing the knowledge of this type of violence, especially in urban centers of developing countries.

Institutional and matrix support and its relationship with primary healthcare

OBJECTIVE To analyze whether the level of institutional and matrix support is associated with better certification of primary healthcare teams.METHODS In this cross-sectional study, we evaluated two kinds of primary healthcare support – 14,489 teams received institutional support and 14,306 teams received matrix support. Logistic regression models were applied. In the institutional support model, the independent variable was “level of support” (as calculated by the sum of supporting activities for both modalities). In the matrix support model, in turn, the independent variables were the supporting activities. The multivariate analysis has considered variables with p < 0.20. The model was adjusted by the Hosmer-Lemeshow test.RESULTS The teams had institutional and matrix supporting activities (84.0% and 85.0%), respectively, with 55.0% of them performing between six and eight activities. For the institutional support, we have observed 1.96 and 3.77 chances for teams who had medium and high levels of support to have very good or good certification, respectively. For the matrix support, the chances of their having very good or good certification were 1.79 and 3.29, respectively. Regarding to the association between institutional support activities and the certification, the very good or good certification was positively associated with self-assessment (OR = 1.95), permanent education (OR = 1.43), shared evaluation (OR = 1.40), and supervision and evaluation of indicators (OR = 1.37). In regards to the matrix support, the very good or good certification was positively associated with permanent education (OR = 1.50), interventions in the territory (OR = 1.30), and discussion in the work processes (OR = 1.23).CONCLUSIONS In Brazil, supporting activities are being incorporated in primary healthcare, and there is an association between the level of support, both matrix and institutional, and the certification result.

Dietary patterns in pregnancy and birth weight

OBJECTIVE To analyze if dietary patterns during the third gestational trimester are associated with birth weight.METHODS Longitudinal study conducted in the cities of Petropolis and Queimados, Rio de Janeiro (RJ), Southeastern Brazil, between 2007 and 2008. We analyzed data from the first and second follow-up wave of a prospective cohort. Food consumption of 1,298 pregnant women was assessed using a semi-quantitative questionnaire about food frequency. Dietary patterns were obtained by exploratory factor analysis, using the Varimax rotation method. We also applied the multivariate linear regression model to estimate the association between food consumption patterns and birth weight.RESULTS Four patterns of consumption – which explain 36.4% of the variability – were identified and divided as follows: (1) prudent pattern (milk, yogurt, cheese, fruit and fresh-fruit juice, cracker, and chicken/beef/fish/liver), which explained 14.9% of the consumption; (2) traditional pattern, consisting of beans, rice, vegetables, breads, butter/margarine and sugar, which explained 8.8% of the variation in consumption; (3) Western pattern (potato/cassava/yams, macaroni, flour/farofa/grits, pizza/hamburger/deep fried pastries, soft drinks/cool drinks and pork/sausages/egg), which accounts for 6.9% of the variance; and (4) snack pattern (sandwich cookie, salty snacks, chocolate, and chocolate drink mix), which explains 5.7% of the consumption variability. The snack dietary pattern was positively associated with birth weight (β = 56.64; p = 0.04) in pregnant adolescents.CONCLUSIONS For pregnant adolescents, the greater the adherence to snack pattern during pregnancy, the greater the baby’s birth weight.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

A multivariate analysis of socio-demographic factors, water contact patterns and Schistosoma mansoni infection in an endemic area in Brazil

Associations between socio-demographic factors, water contact patterns and Schistosoma mansoni infection were investigated in 506 individuals (87% of inhabitants over 1 year of age) in an endemic area in Brazil (Divino), aiming at determining priorities for public health measures to prevent the infection. Those who eliminated S. mansoni eggs (n = 198) were compared to those without eggs in the stools (n = 308). The following explanatory variables were considered: age, sex, color, previous treatment with schistosomicide, place of birth, quality of the houses, water supply for the household, distance from houses to stream, and frequency and reasons for water contact. Factors found to be independently associated with the infection were age (10-19 and > 20 yrs old), and water contact for agricultural activities, fishing, and swimming or bathing (Adjusted relative odds = 5.0, 2.4, 3.2, 2.1 and 2.0, respectively). This suggests the need for public health measures to prevent the infection, emphasizing water contact for leisure and agricultural activities in this endemic area.

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

The role of functional polymorphisms in immune response genes as biomarkers of BCG Immunotherapy outcome in bladder cancer: Establishment of a predictive profile in a Southern Europe population

OBJECTIVE: To evaluate the predictive value of genetic polymorphisms in the context of BCG immunotherapy outcome and create a predictive profile that may allow discriminating the risk of recurrence. MATERIAL AND METHODS: In a dataset of 204 patients treated with BCG, we evaluate 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY technology. Stepwise multivariate Cox Regression was used for data mining. RESULTS: In agreement with previous studies we observed that gender, age, tumor multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox Regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules (SNPs in TNFA-1031T/C (rs1799964), IL2RA rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, ICAM1 K469E (rs5498), FASL-844T/C (rs763110) and TRAILR1-397T/G (rs79037040) in association with clinicopathological variables. This risk score allows the categorization of patients into risk groups: patients within the Low Risk group have a 90% chance of successful treatment, whereas patients in the High Risk group present 75% chance of recurrence after BCG treatment. CONCLUSION: We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.

Monitoring the ex-vivo expansion of human mesenchymal stem/stromal cells in xeno-free microcarrier-based reactor systems by MIR spectroscopy

Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.

Predicting Xerostomia induced by IMRT treatments: A logistic regression approach

Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”

Relationship between acute diarrhoea and low plasma levels of vitamin A and retinol binding protein

The objective of this study was to assess vitamin A status and association between acute diarrhoea and plasma levels of vitamin A through cross-sectional comparison in children. Plasma vitamin A was measured by colorimetric method of Neeld & Pearson and RBP by radial immunodiffusion technique. Seventy eight children (aged 18-119 months), 26 with current history of diarrhoea and 52 children as controls (outpatient from the Santa Casa de Misericórdia Hospital in metropolitan area of São Paulo City, Brazil) were studied. Children with history of diarrhoea showed significant low levels (mean ± s.e.) as compared to controls, vitamin A (15.87 ± 1.4 µg/dl vs. 21.14 ± 1.15 µg/dl, p < 0.007) and RBP (1.70 ± 0.2 mg/dl vs. 2.52 ±0.11 mg/dl). Multivariate logistic regression adjusted by sex, age, nutritional status and mother education revealed association between diarrhoea and inadequate levels of vitamin A and RBP.

Sucesso terapêutico no controlo da tuberculose em Portugal : determinantes do resultado do tratamento e a sua capacidade preditiva

RESUMO - Enquadramento/objectivos: Apesar do elevado nível de comprometimento em estratégias eficazes para o controlo da tuberculose, em todo o mundo, esta constitui ainda um sério problema de Saúde Pública, com uma estimativa global de 9,4milhões de casos novos em 2008 e 1,8milhões de mortes/ano. O reduzido conhecimento das barreiras e facilitadores para o sucesso terapêutico constitui um importante obstáculo na procura de soluções eficazes de melhoramento da qualidade dos programas de controlo da tuberculose. Este estudo procura contribuir para a identificação atempada de doentes com perfis preditivos de insucesso terapêutico, através da identificação inicial de potenciais determinantes do resultado, com base num modelo epidemiológico e estatístico. Métodos: Foi desenvolvido um estudo de caso-controlo para a população de casos notificados ao Programa Nacional de Controlo da Tuberculose (n=24491), entre 2000-2007. Os factores preditivos de insucesso terapêutico foram identificados na análise bivariada e multivariada, com um nível de significância de 5%; a regressão logística foi utilizada para estimar a odds ratio de insucesso terapêutico, em comparação com o sucesso terapêutico, para diversos factores identificados na literatura, e para os quais os dados se encontravam disponíveis. Resultados: A dependência alcoólica (OR=2,889), o país de origem (OR=3,910), a situação sem-abrigo (OR=3.919), a co-infecção pelo VIH (OR=5,173), a interrupção (OR=60.615) ou falha terapêutica no tratamento anterior (OR=67.345) e a duração do tratamento inferior a 165 dias (OR=1930,133) foram identificados como factores preditivos de insucesso terapêutico. A duração do tratamento inferior a 165 dias provou ser o mais importante determinante do resultado terapêutico. Conclusões: Os resultados sugerem que um doente imigrante, em situação de sem-abrigo, dependente alcoólico, com tratamentos anteriores para a tuberculose e co-infectado pelo VIH apresenta uma elevada probabilidade de insucesso terapêutico. Assim, deverão ser definidas estratégias específicas, centradas no doente por forma a impedir este resultado. A base de dados (SVIG-TB), provou ser uma ferramenta de qualidade para a investigação sobre diversos aspectos do controlo da tuberculose. ------------------------------- ABSTRACT - Background/Objective: Despite the high commitment in good strategies for tuberculosis control worldwide, this is still a serious Public Health problem, with global estimates of 9,4million new cases in 2008 and 1,8million deaths/year. The poor understanding of the barriers and facilitators to treatment success is a major obstacle to find effective solutions to improve the quality of tuberculosis programs. This study tries to contribute to the timely identification of patients with predictive profiles of unsuccessful treatment outcomes, through the initial identification of characteristics probably affecting treatment outcome, found on the basis of an epidemiological and statistical model. Methods: A case-control study was conducted for the population of cases notified to the National Program for Tuberculosis Control (n=24 491), between 2000-2007. Predictive factors for unsuccessful outcome were assessed in a bivariate and multivariate analysis, using a significance level of 5%; a logistic regression was used to estimate the odds-ratio of unsuccessful, as compared to successful outcome, for several factors identified in the literature and to which data was available. Results: Alcohol abuse (OR=2,889), patient´s foreign origin (OR=3,910), homelessness (OR=3,919), HIV co-infection (OR=5,173), interruption (OR=60,615) or unsuccessful outcome in the previous treatment (OR=67,345) and treatment duration below 165 days (OR=1930,133) were identified as predictive of unsuccessful outcomes. A low treatment duration proved to be the most powerful factor affecting treatment outcome. Conclusions: Results suggest that a foreign-born patient, alcohol abuser, who has had a previous treatment for tuberculosis and is co-infected with HIV is very likely to have an unsuccessful outcome. Therefore, specific, patient-centered strategies should be taken to prevent an unsuccessful outcome. The database (SVIG-TB), has proved to be a quality tool on research of various aspects of tuberculosis control.

Double coverage and demand for health care: Evidence from quantile regression

An individual experiences double coverage when he bene ts from more than one health insurance plan at the same time. This paper examines the impact of such supplementary insurance on the demand for health care services. Its novelty is that within the context of count data modelling and without imposing restrictive parametric assumptions, the analysis is carried out for di¤erent points of the conditional distribution, not only for its mean location. Results indicate that moral hazard is present across the whole outcome distribution for both public and private second layers of health insurance coverage but with greater magnitude in the latter group. By looking at di¤erent points we unveil that stronger double coverage e¤ects are smaller for high levels of usage. We use data for Portugal, taking advantage of particular features of the public and private protection schemes on top of the statutory National Health Service. By exploring the last Portuguese Health Survey, we were able to evaluate their impacts on the consumption of doctor visi

Impacto da Obesidade nos Resultados após Angioplastia Primária em Doentes com Enfarte Agudo do Miocárdio com Elevação do Segmento ST

INTRODUCTION: Obesity is an important risk factor for the development of diabetes, hypertension, coronary disease, left ventricular dysfunction, stroke and cardiac arrhythmias. Paradoxically, previous studies in patients undergoing elective coronary angioplasty showed a reduction in hospital and long-term mortality in obese patients. The relation with body mass index (BMI) has been less studied in the context of primary angioplasty. OBJECTIVES: To evaluate the impact of obesity on the results of ST-segment elevation acute myocardial infarction treated by primary angioplasty. METHODS: This was a study of 464 consecutive patients with ST-segment elevation acute myocardial infarction undergoing primary angioplasty, 78% male, mean age 61 +/- 13 years. We assessed in-hospital, 30-day and one-year mortality according to BMI. Patients were divided into three groups according to BMI: normal--18-24.9 kg/m2 (n = 171); overweight--25-29.9 kg/m2 (n = 204); and obese-- > 30 kg/m2 (n = 89). RESULTS: Obese patients were younger (ANOVA, p < 0.001) and more frequently male (p = 0.014), with more hypertension (p = 0.001) and dyslipidemia (p = 0.006). There were no differences in the prevalence of diabetes, previous cardiac history, heart failure on admission, anterior location, multivessel disease, peak total CK or medication prescribed, except that obese patients received more beta-blockers (p = 0.049). In-hospital mortality was 9.9% for patients with normal BMI, 3.4% for overweight patients and 6.7% for obese patients (p = 0.038). Mortality at 30 days was 11 4.4% and 7.8% (p = 0.032) and at one year 12.9%, 4.9% and 9% (p = 0.023), respectively. On univariate analysis, overweight was the only BMI category with a protective effect; however, after multivariate logistic regression analysis, adjusted for confounding variables, none of the BMI categories could independently predict outcome. CONCLUSIONS: Overweight patients had a better prognosis after primary angioplasty for ST-segment elevation acute myocardial infarction compared with other BMI categories, but this was dependent on other potentially confounding variables.