NUTRISOL: un programa informático para la evaluación nutricional comunitaria y hospitalaria de acceso libre.

We have developed the computer programme NUTRISOL, a nutritional programme destined to analysis of dietary intake by means of the food transformation to nutrient. It has been performed under Windows operative system, using Visual Basic 6.0. It is presented in a CD-Rom. We have used the Spanish CSIC Food Composition Table and domestic food measures commonly used in Spain which could be modified and updated. Diverse kind of diets and reference anthropometric data are also presented. The results may be treated using various statistical programmes. The programme contains three modules: 1) Nutritional epidemiology, which allows to create or open a data base, sample management, analyse food intake, consultation of nutrient content and exportation of data to statistical programmes. 2) Analyses of diets and recipes, creation or modification of new ones. 3) To ask different diets for prevalent pathologies. Independent tools for modifying the original tables, calculate energetic needs, recommend nutrient intake and anthropometric indexes are also offered. In conclusion, NUTRISOL Programme is an application which runs in PC computers with minimal equipment in a friendly interface, of easy use, freeware, which may be adapted to each country, and has demonstrated its usefulness and reliability in different epidemiologic studies. Furthermore, it may become an efficient instrument for clinical nutrition and health promotion.

Hábitos y estilos de vida modificables en niños con sobrepeso y obesidad.

INTRODUCTION In the prevention for being overweight and for obesity, much attention is given to the influence of dietary factors, making the joint evaluation with other modifiable factors necessary. OBJECTIVES The aim of this project is to study the association between modifiable factors (physical activity, sedentary lifestyle, and dietary habits) with the prevalence of being overweight or obese in the youth population. METHODS Cross-Sectional study of 1283 school children between the ages of 3 and 16 years old, with measurements of the MBI, dietary habits, physical activity, sedentary lifestyle and family history of being overweight. Physical activity measured in MET was classified according to Pate criteria. RESULTS 22.4% of the boys and 32.9% of the girls were overweight. The presence of a BMI>25 in parents multiplied by 2.4 the risk of being overweight in children (OR CI 95% 1.5-3.7). 63.6% of overweight boys meet physical activity recommendations compared with 52.2% of girls, although in their case, it was greater than the average (45%). Sedentary time was 141 minutes for men and 128 minutes for women, with more sedentary behaviors associated with being overweight, especially in girls over 12 years of age (66.7%). Consuming cereal (OR 0.8) and having five meals per day (OR 0.5) act as protective factors. CONCLUSIONS In subjects with overweight, the levels of physical activity are close to those recommended levels, so which the values of a sedentary lifestyle together with dietary habits (if the parents have overweight) acquire a new relevance in intervention strategies of this problem.

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.