Women with HIV: gender violence and suicidal ideation

OBJECTIVE To analyze the relationship between gender violence and suicidal ideation in women with HIV. METHODS A cross-sectional study with 161 users of specialized HIV/AIDS care services. The study investigated the presence of gender violence through the Brazilian version of the World Health Organization Violence against Women instrument, and suicidal ideation through the Suicidal Ideation Questionnaire. Statistical analyses were performed with the SPSS software, using the Chi-square test and Poisson multiple regression model. RESULTS Eighty-two women with HIV reported suicidal ideation (50.0%), 78 (95.0%) of who had suffered gender violence. Age at first sexual intercourse < 15 years old, high number of children, poverty, living with HIV for long, and presence of violence were statistically associated with suicidal ideation. Women who suffered gender violence showed 5.7 times more risk of manifesting suicidal ideation. CONCLUSIONS Women with HIV showed a high prevalence to gender violence and suicidal ideation. Understanding the relationship between these two grievances may contribute to the comprehensive care of these women and implementation of actions to prevent violence and suicide.

Maternal mental health and nutritional status of six-month-old infants

ABSTRACT OBJECTIVE To analyze if maternal mental health is associated with infant nutritional status at six month of age. METHODS A cross-sectional study with 228 six-month-old infants who used primary health care units of the city of Rio de Janeiro, Southeastern Brazil. Mean weight-for-length and mean weight-for-age were expressed in z-scores considering the 2006 World Health Organization reference curves. Maternal mental health was measured by the 12-item General Health Questionnaire. The following cutoff points were used: ≥ 3 for common mental disorders, ≥ 5 for more severe mental disorders, and ≥ 9 for depression. The statistical analysis employed adjusted linear regression models. RESULTS The prevalence of common mental disorders, more severe mental disorders and depression was 39.9%, 23.7%, and 8.3%, respectively. Children of women with more severe mental disorders had, on average, a weight-for-length 0.37 z-scores lower than children of women without this health harm (p = 0.026). We also observed that the weight-for-length indicator of children of depressed mothers was, on average, 0.67 z-scores lower than that of children of nondepressed women (p = 0.010). Maternal depression was associated with lower mean values of weight-for-age z-scores (p = 0.041). CONCLUSIONS Maternal mental health is positively related to the inadequacy of the nutritional status of infants at six months.

Health self-assessment by hemodialysis patients in the Brazilian Unified Health System

ABSTRACT OBJECTIVE To examine whether the level of complexity of the services structure and sociodemographic and clinical characteristics of patients in hemodialysis are associated with the prevalence of poor health self-assessment. METHODS In this cross-sectional study, we evaluated 1,621 patients with chronic terminal kidney disease on hemodialysis accompanied in 81 dialysis services in the Brazilian Unified Health System in 2007. Sampling was performed by conglomerate in two stages and a structured questionnaire was applied to participants. Multilevel multiple logistic regression was used for data analysis. RESULTS The prevalence of poor health self-assessment was of 54.5%, and in multivariable analysis it was associated with the following variables: increasing age (OR = 1.02; 95%CI 1.01–1.02), separated or divorced marital status (OR = 0.62; 95%CI 0.34–0.88), having 12 years or more of study (OR = 0.51; 95%CI 0.37–0.71), spending more than 60 minutes in commuting between home and the dialysis service (OR = 1.80; 95%CI 1.29–2.51), having three or more self-referred diseases (OR = 2.20; 95%CI 1.33–3.62), and reporting some (OR = 2.17; 95%CI 1.66–2.84) or a lot of (OR = 2.74; 95%CI 2.04–3.68) trouble falling asleep. Individuals in treatment in dialysis services with the highest level of complexity in the structure presented less chance of performing a self-assessment of their health as bad (OR = 0.59; 95%CI 0.42–0.84). CONCLUSIONS We showed poor health self-assessment is associated with age, years of formal education, marital status, home commuting time to the dialysis service, number of self-referred diseases, report of trouble sleeping, and also with the level of complexity of the structure of health services. Acknowledging these factors can contribute to the development of strategies to improve the health of patients in hemodialysis in the Brazilian Unified Health System.

The making of saudade. National identity and ethnic psychology in Portugal

Roots and rituals.The construction of ethnic identities, Ton Dekker, John Helsloot Carla Wijers editors, p. 267-268; Selected papers of the 6TH SIEF conference on 'Roots & rituals', Amsterdam 20-25 April 1998.

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.

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”

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

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.

Hopelessness and Related Variables among Cancer Patients in the Southern European Psycho-Oncology Study (SEPOS).

BACKGROUND: Although hopelessness has been studied in cancer, no data are available in non-English-speaking countries. OBJECTIVE: The authors sought to amass data from Southern European countries (Italy, Portugal, Spain, and Switzerland) in order to fill this void. METHOD: A group of 312 cancer patients completed the Mini-MAC Hopelessness subscale, the Hospital Anxiety and Depression Scale (HADS), the Cancer Worry Inventory (CWI), and a six-item Visual Analog scale (VAS) to measure intensity of physical symptoms, general well-being, difficulty in coping with cancer, intensity of social support from close relationships, leisure activity, and support from religious beliefs. RESULTS: Regression analysis indicated that HADS-Depression, VAS Maladaptive Coping and Well-Being, and the CWI explained 42% of the variance. CONCLUSION: Hopelessness in cancer patients seems not exclusively to correspond to depression, but is related to various other psychosocial factors, such as maladaptive coping, as well.

Análise espacial dos resultados eleitorais em Portugal – Aplicação do Geographically Weighted Regression

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.

Análise espacial dos resultados eleitorais em Portugal – Aplicação do Geographically Weighted Regression

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.

Psychosocial Determinants of Quality of Life 6 Months After Transplantation: Longitudinal Prospective Study

OBJECTIVES: We sought to investigate the psychosocial determinants of quality of life at 6 months after transplantation. METHODS: A sample of liver transplant candidates (n = 60), composed of consecutive patients (25% with familial amyloid polyneuropathy [FAP]) attending outpatient clinics was assessed in the pretransplant period using the Neo Five Factor Inventory, Hospital Anxiety and depression Scale (HADS), Brief COPE, and SF-36, a quality-of-life, self-rating questionnaire. Six months after transplantation, these patients were assessed by means of the SF-36. RESULTS: Psychosocial predictors where found by means of multiple regression analysis. The physical component of quality of life at 6 months after transplantation was determined based upon coping strategies and physical quality of life in the pretransplant period (this model explained 32% of variance). The mental component at 6 months after transplantation was determined by depression in the pretransplant period and by clinical diagnoses of patients. Because FAP patients show a lower mental component of quality of life, this diagnosis explained 25% of the variance. CONCLUSIONS: Our findings suggested that coping strategies and depression measured in the pretransplant period are important determinants of quality of life at 6 months after liver transplantation.

Health-Related Quality of Life Impact of a Triple Combination of Olmesartan Medoxomil, Amlodipine Besylate and Hydrochlorotiazide in Subjects with Hypertension

BACKGROUND: A post-hoc analysis was performed on the data from a 54 weeks phase III study (ClinicalTrials.gov identifier: NCT00923091) to measure changes in the health-related quality of life (HRQoL) of 2,690 patients aged ≥18 with moderate-to-severe hypertension who received one of six doses of olmesartan/amlodipine/hydrochlorothiazide (OLM/AML/HCTZ), using the MINICHAL and EQ-5D instruments. METHODS: Descriptive statistics were used to assess blood pressure and HRQoL scores over the study period. Analysis of covariance (ANCOVA) was used to identify those factors that could possibly have influenced HRQoL. Linear regression was used to assess the relationship between changes in blood pressure and HRQoL scores. RESULTS: Patients' baseline MINICHAL mood and somatic domains scores were 5.5 and 2.6. Over the study period HRQoL improved as both MINICHAL scores decreased by 31-33%. Patients' baseline EQ-5D index and VAS scores were 0.9 and 73.4 respectively, increasing by 6% and 12% over the study period. Patients' QALY gain over the 54 weeks study period was estimated to be 0.029 QALYs. The ANCOVA showed that changes in patients' HRQoL was likely to have been influenced by patients' achievement of blood pressure control, the amount of concomitant medication and patients' last used dosage strength of antihypertensive. Linear regression showed that blood pressure improvement may have been associated with improved HRQoL. CONCLUSIONS: This study showed that OLM/AML/HCTZ reduced blood pressure and significantly increased blood pressure control whilst improving patients' HRQoL. Achieving blood pressure control, amount of concomitant medication and dosage strength of antihypertensive impacted on patients' HRQoL.