Alimentação e saúde : uma abordagem epidemiológica de estudantes universitários

Resumo: A alimentação e o estado nutricional são factores determinantes do estado de saúde e sabe-se hoje que os mecanismos da patogénese de várias doenças crónicas não-transmissíveis podem ocorrer no início da idade adulta. A alimentação é influenciada por uma multiplicidade de factores, entre os quais se contam a importância atribuída à alimentação, o peso e imagem corporal e a percepção dos riscos associados à escolha de alimentos. Esta investigação teve como objectivos analisar, em estudantes universitários até aos 30 anos de idade, o estado nutricional, a importância atribuída a alimentação, as percepções do peso e da imagem corporal e a percepção do risco de doença relacionada com a alimentação. Os objectivos foram cumpridos através de dois desenhos de estudo distintos: estudo descritivo transversal e estudo de caso-controlo. Avaliou-se o peso, altura e os perímetros da cintura e da anca e construiu-se um questionário de auto-preenchimento para recolher a restante informação. Encontraram-se valores para a prevalência de obesidade e excesso de peso de, respectivamente, 6,5% e 24,3% e concluiu-se que existe uma percepção incorrecta do peso e da imagem corporal, mais frequente entre os indivíduos obesos. Os obesos também consideram a alimentação menos importante que os indivíduos normoponderais. A análise da percepção dos riscos revela que os inquiridos consideram que factores como a obesidade e a inactividade física são menos prejudiciais para a saúde do que factores como as alterações climáticas ou as radiações de telefones móveis. Verificaram-se também diferenças entre sexos nos parâmetros estudados: relativamente às mulheres, os homens sobrestimam mais frequentemente o peso e a imagem corporal, consideram a alimentação menos importante, julgam-se em menor risco de doença e classificam os factores de risco estudados como menos prejudiciais. Conclui-se que as estratégias de educação alimentar e de promoção da saúde devem considerar as diferenças registadas entre sexos e a importância atribuída à alimentação e as percepções do risco, do peso e da imagem corporal. Abstract: Nutrition and nutritional status are health determinants and it’s accepted that the mechanisms for the pathogenesis of several chronic non-communicable diseases can occur in early adult age. Nutrition is influenced by a large number of factors, including the value placed on food, weight and body image and the risk perception associated with food choice. Consequently, the analysis of the factors that can influence food behaviour and food choice in young adults can be useful for the control and prevention of nutrition related disease. The objectives of this research were to analyse, in college students up to 30 years of age, nutritional status, value placed on nutrition, weight and body image perceptions and the risk perception of nutrition related disease. Two study designs were used: cross-sectional and case-control. Weight, height and waist and hip circumference were measured and a questionnaire was built to collect the remaining information. Prevalences of 6,5% for obesity and 24,3% for excess weight were found, along with the existence of biased weight and body image perceptions, more frequent in obese subjects. Obese subjects also placed less value on nutrition than non-obese. Risk perception analysis shows that risk factors like obesity and physical inactivity are considered less hazardous than risk factors like climate changes and mobile phone radiation. Men, comparatively to women, overestimated more frequently their weight and body image, placed less value in nutrition, considered themselves less disease susceptible and classified the risk factors studied as less hazardous. The conclusions of this study show that nutrition education and health promotion strategies should consider the gender related differences reported and, also, the value placed on nutrition and weigh, body image and risk perceptions.

Corporate social responsibility and its effect on image and reputation: The case of L’Oréal and its acquisition of The Body Shop

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.