A new interministerial strategy for the promotion of healthy eating in Portugal: implementation and initial results

ObjectiveTo describe the implementation, main intervention areas and initial results of the Integrated Strategy for the Promotion of Healthy Eating (EIPAS) in Portugal.MethodsEIPAS was published as a Law, in December of 2017, as a result of a collaboration between several ministries, including the Finance, Internal Affairs, Education, Health, Economy, Agriculture, and Sea Ministries, aiming at improving the dietary habits of the Portuguese population. The working group, led by the Ministry of Health, developed this strategy for over a year. The framework produced was based on WHO and European Commission recommendations as well as on relevant data from the last Portuguese dietary intake survey (2015/2016). EIPAS also reflects the results of a public hearing, including the food industry, among others, and the experience gathered, since 2012, through the National Programme for the Promotion of Healthy Eating. It considers the health in all policies' challenge set by WHO and has four different strategic areas, namely (1) creation of healthier food environments, (2) improvement of the quality and accessibility of healthy food choices for consumers, (3) promotion and development of literacy, in order to encourage healthy food choices, and (4) promotion of innovation and entrepreneurship. In order to achieve these goals, a set of 51 actions was established and assigned to the seven ministries involved.ResultsUnder the scope of this strategy, Portugal has already implemented several actions, including (1) definition of standards for food availability at all public healthcare institutions; (2) implementation of a sugar tax on sweetened beverages; (3) implementation of a voluntary agreement with the food industry sector for food reformulation (work in progress); (4) design of a proposal for an interpretative model of front-of-pack food labelling; (5) improvement of the nutritional quality of food aid programmes for low-income groups; and (6) regulation of marketing of unhealthy foods to children.ConclusionsFor the first time, Portugal has a nutrition policy based on the WHO concept of health in all policies' and on the national data on food intake. The implementing process of all 51 actions and the inherent complexities and difficulties found so far have made this process be an authentic political and social laboratory that deserves to be followed

Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data

BACKGROUND: In recent years, outcome prediction models using artificial neural network and multivariable logistic regression analysis have been developed in many areas of health care research. Both these methods have advantages and disadvantages. In this study we have compared the performance of artificial neural network and multivariable logistic regression models, in prediction of outcomes in head trauma and studied the reproducibility of the findings. METHODS: 1000 Logistic regression and ANN models based on initial clinical data related to the GCS, tracheal intubation status, age, systolic blood pressure, respiratory rate, pulse rate, injury severity score and the outcome of 1271 mainly head injured patients were compared in this study. For each of one thousand pairs of ANN and logistic models, the area under the receiver operating characteristic (ROC) curves, Hosmer-Lemeshow (HL) statistics and accuracy rate were calculated and compared using paired T-tests. RESULTS: ANN significantly outperformed logistic models in both fields of discrimination and calibration but under performed in accuracy. In 77.8% of cases the area under the ROC curves and in 56.4% of cases the HL statistics for the neural network model were superior to that for the logistic model. In 68% of cases the accuracy of the logistic model was superior to the neural network model. CONCLUSIONS: ANN significantly outperformed the logistic models in both fields of discrimination and calibration but lagged behind in accuracy. This study clearly showed that any single comparison between these two models might not reliably represent the true end results. External validation of the designed models, using larger databases with different rates of outcomes is necessary to get an accurate measure of performance outside the development population

Topological Active Volumes

<p/> <p>The topological active volumes (TAVs) model is a general model for 3D image segmentation. It is based on deformable models and integrates features of region-based and boundary-based segmentation techniques. Besides segmentation, it can also be used for surface reconstruction and topological analysis of the inside of detected objects. The TAV structure is flexible and allows topological changes in order to improve the adjustment to object's local characteristics, find several objects in the scene, and identify and delimit holes in detected structures. This paper describes the main features of the TAV model and shows its ability to segment volumes in an automated manner.</p

Racial/Ethnic Differences in Inpatient Palliative Care Consultation for Patients With Advanced Cancer

PURPOSE: Inpatient palliative care consultation (IPCC) may help address barriers that limit the use of hospice and the receipt of symptom-focused care for racial/ethnic minorities, yet little is known about disparities in the rates of IPCC. We evaluated the association between race/ethnicity and rates of IPCC for patients with advanced cancer. PATIENTS AND METHODS: Patients with metastatic cancer who were hospitalized between January 1, 2009, and December 31, 2010, at an urban academic medical center participated in the study. Patient-level multivariable logistic regression was used to evaluate the association between race/ethnicity and IPCC. RESULTS: A total of 6,288 patients (69% non-Hispanic white, 19% African American, and 6% Hispanic) were eligible. Of these patients, 16% of whites, 22% of African Americans, and 20% of Hispanics had an IPCC (overall P < .001). Compared with whites, African Americans had a greater likelihood of receiving an IPCC (odds ratio, 1.21; 95% CI, 1.01 to 1.44), even after adjusting for insurance, hospitalizations, marital status, and illness severity. Among patients who received an IPCC, African Americans had a higher median number of days from IPCC to death compared with whites (25 v 17 days; P = .006), and were more likely than Hispanics (59% v 41%; P = .006), but not whites, to be referred to hospice. CONCLUSION: Inpatient settings may neutralize some racial/ethnic differences in access to hospice and palliative care services; however, irrespective of race/ethnicity, rates of IPCC remain low and occur close to death. Additional research is needed to identify interventions to improve access to palliative care in the hospital for all patients with advanced cancer