Postpartum depression among women with unintended pregnancy

OBJECTIVE To analyze the association between unintended pregnancy and postpartum depression.METHODS This is a prospective cohort study conducted with 1,121 pregnant aged 18 to 49 years, who attended the prenatal program devised by the Brazilian Family Health Strategy, Recife, PE, Northeastern Brazil, between July 2005 and December 2006. We interviewed 1,121 women during pregnancy and 1,057 after childbirth. Unintended pregnancy was evaluated during the first interview and postpartum depression symptoms were assessed using the Edinburgh Postnatal Depression Screening Scale. The crude and adjusted odds ratios for the studied association were estimated using logistic regression analysis.RESULTS The frequency for unintended pregnancy was 60.2%; 25.9% presented postpartum depression symptoms. Those who had unintended pregnancies had a higher likelihood of presenting this symptoms, even after adjusting for confounding variables (OR = 1.48; 95%CI 1.09;2.01). When the Self Reporting Questionnaire (SRQ-20) variable was included, the association decreased, however, remained statistically significant (OR = 1.42; 95%CI 1.03;1.97).CONCLUSIONS Unintended pregnancy showed association with subsequent postpartum depressive symptoms. This suggests that high values in Edinburgh Postnatal Depression Screening Scale may result from unintended pregnancy.

Incidence and risk factors for intimate partner violence during the postpartum period

OBJECTIVE To estimate the incidence and identify risk factors for intimate partner violence during postpartum.METHODS This prospective cohort study was conducted with women, aged between 18-49 years, enrolled in the Brazilian Family Health Strategy in Recife, Northeastern Brazil, between 2005 and 2006. Of the 1.057 women interviewed during pregnancy and postpartum, 539 women, who did not report violence before or during pregnancy, were evaluated. A theoretical-conceptual framework was built with three levels of factors hierarchically ordered: women’s and partners’ sociodemografic and behavioral characteristics, and relationship dynamics. Incidence and risk factors of intimate partner violence were estimated by Poisson Regression.RESULTS The incidence of violence during postpartum was 9.3% (95%CI 7.0;12.0). Isolated psychological violence was the most common (4.3%; 95%CI 2.8;6.4). The overlapping of psychological with physical violence occurred at 3.3% (95%CI 2.0;5.3) and with physical and/or sexual in almost 2.0% (95%CI 0.8;3.0) of cases. The risk of partner violence during postpartum was increased for women with a low level of education (RR = 2.6; 95%CI 1.3;5.4), without own income (RR = 1.7; 95%CI 1.0;2.9) and those who perpetrated physical violence against their partner without being assaulted first (RR = 2.0; 95%CI 1.2;3.4), had a very controlling partner (RR = 2.5; 95%CI 1.1;5.8), and had frequent fights with their partner (RR = 1.7; 95%CI 1.0;2.9).CONCLUSIONS The high incidence of intimate partner violence during postpartum and its association with aspects of the relationship’s quality between the couple, demonstrated the need for public policies that promote conflict mediation and enable forms of empowerment for women to address the cycle of violence.

Impact of ultra-processed foods on micronutrient content in the Brazilian diet

OBJECTIVE To evaluate the impact of consuming ultra-processed foods on the micronutrient content of the Brazilian population’s diet.METHODS This cross-sectional study was performed using data on individual food consumption from a module of the 2008-2009 Brazilian Household Budget Survey. A representative sample of the Brazilian population aged 10 years or over was assessed (n = 32,898). Food consumption data were collected through two 24-hour food records. Linear regression models were used to assess the association between the nutrient content of the diet and the quintiles of ultra-processed food consumption – crude and adjusted for family incomeper capita.RESULTS Mean daily energy intake per capita was 1,866 kcal, with 69.5% coming from natural or minimally processed foods, 9.0% from processed foods and 21.5% from ultra-processed foods. For sixteen out of the seventeen evaluated micronutrients, their content was lower in the fraction of the diet composed of ultra-processed foods compared with the fraction of the diet composed of natural or minimally processed foods. The content of 10 micronutrients in ultra-processed foods did not reach half the content level observed in the natural or minimally processed foods. The higher consumption of ultra-processed foods was inversely and significantly associated with the content of vitamins B12, vitamin D, vitamin E, niacin, pyridoxine, copper, iron, phosphorus, magnesium, selenium and zinc. The reverse situation was only observed for calcium, thiamin and riboflavin.CONCLUSIONS The findings of this study highlight that reducing the consumption of ultra-processed foods is a natural way to promote healthy eating in Brazil and, therefore, is in line with the recommendations made by the Guia Alimentar para a População Brasileira (Dietary Guidelines for the Brazilian Population) to avoid these foods.

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.

A influência dos sistemas de recompensas sobre a satisfação no trabalho

Mestrado em Contabilidade e Gestão das Instituições Financeiras

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.

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”

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Dual-phase inkjet printed electrochromic layers based on PTA and WOX/TiO2 nanoparticles for electrochromic applications

Thesis submitted in Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa for the degree of Master in Materials Engineering

Determinantes da estrutura de capitais do setor do calçado em Portugal

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação de Mestre Adalmiro Álvaro Malheiro de Castro Andrade Pereira

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

Evaluation of standard reagents for radial-immunodiffusion assays. In vitro control of rabies vaccines

The RID assay is one of the in vitro methods used for in-process control in the production of rabies vaccines for veterinary use. It has been shown to be very useful for determining antigen concentration in the final bulk product. The work presented in this paper, including the production and standardization of candidate standard reagents for use in the Radial Immunodiffusion Assay (RID) was carried out at the Pan American Institute for Food Protection and Zoonoses (INPPAZ/PAHO/WHO). The study was completed with the cooperation of the Faculty of Veterinary Sciences, National University of La Plata (NULP), Argentina, where the validation of the proposed standards and the quality control of samples from 28 different batches of rabies vaccines produced with Pasteur strain rabies virus (PV) in BHK cells were performed. The activity of the vaccines was determined by in vivo (NIH) and in vitro (RID)assays. The results of the candidate reagents for the reagent standardization tests showed stability, sensitivity and reproducibility. The Relative Potency the 1.2 between the problem vaccines and the reference vaccine was estimated by variance and regression analysis. The results of our validation study show that the INPPAZ (PAHO/WHO) is capable of producing and distributing the above-mentioned standard reagents, as well as of providing support for the incorporation of the RID technique (sensitive, rapid and inexpensive) to the laboratories that manufacture rabies vaccines in Latin America and the Caribbean.