961 resultados para Few-body problem
Resumo:
Recurrent wheezing or asthma is a common problem in children that has increased considerably in prevalence in the past few decades. The causes and underlying mechanisms are poorly understood and it is thought that a numb er of distinct diseases causing similar symptoms are involved. Due to the lack of a biologically founded classification system, children are classified according to their observed disease related features (symptoms, signs, measurements) into phenotypes. The objectives of this PhD project were a) to develop tools for analysing phenotypic variation of a disease, and b) to examine phenotypic variability of wheezing among children by applying these tools to existing epidemiological data. A combination of graphical methods (multivariate co rrespondence analysis) and statistical models (latent variables models) was used. In a first phase, a model for discrete variability (latent class model) was applied to data on symptoms and measurements from an epidemiological study to identify distinct phenotypes of wheezing. In a second phase, the modelling framework was expanded to include continuous variability (e.g. along a severity gradient) and combinations of discrete and continuo us variability (factor models and factor mixture models). The third phase focused on validating the methods using simulation studies. The main body of this thesis consists of 5 articles (3 published, 1 submitted and 1 to be submitted) including applications, methodological contributions and a review. The main findings and contributions were: 1) The application of a latent class model to epidemiological data (symptoms and physiological measurements) yielded plausible pheno types of wheezing with distinguishing characteristics that have previously been used as phenotype defining characteristics. 2) A method was proposed for including responses to conditional questions (e.g. questions on severity or triggers of wheezing are asked only to children with wheeze) in multivariate modelling.ii 3) A panel of clinicians was set up to agree on a plausible model for wheezing diseases. The model can be used to generate datasets for testing the modelling approach. 4) A critical review of methods for defining and validating phenotypes of wheeze in children was conducted. 5) The simulation studies showed that a parsimonious parameterisation of the models is required to identify the true underlying structure of the data. The developed approach can deal with some challenges of real-life cohort data such as variables of mixed mode (continuous and categorical), missing data and conditional questions. If carefully applied, the approach can be used to identify whether the underlying phenotypic variation is discrete (classes), continuous (factors) or a combination of these. These methods could help improve precision of research into causes and mechanisms and contribute to the development of a new classification of wheezing disorders in children and other diseases which are difficult to classify.
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Wernicke encephalopathy (WE) is a serious complication of bariatric surgery with significant morbidity and mortality. A few cases have been reported in the literature, mainly in patients after a Roux-en-Y gastric bypass. Since sleeve gastrectomy (SG) has become a more established and popular bariatric procedure, WE is expected to appear more frequently after SG. We performed a literature review on WE after SG, and 13 cases have been found to be sufficiently documented. The risk of WE needs to be considered in patients with a prolonged vomiting episode and any type of neurological symptoms, independent of the presence of any surgical complications.
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This dissertation was written in the format of three journal articles. Paper 1 examined the influence of change and fluctuation in body mass index (BMI) over an eleven-year period, on changes in serum lipid levels (total, HDL, and LDL cholesterol, triglyceride) in a population of Mexican Americans with type 2 diabetes. Linear regression models containing initial lipid value, BMI and age, BMI change (slope of BMI), and BMI fluctuation (root mean square error) were used to investigate associations of these variables with change in lipids over time. Increasing BMI over time was associated with gains in total and LDL cholesterol and triglyceride levels in women. Fluctuation of BMI was not associated with detrimental lipid profiles. These effects were independent of age and were not statistically significant in men. In Mexican-American women with type 2 diabetes, weight reduction is likely to result in more favorable levels of total and LDL cholesterol and triglyceride, without concern for possible detrimental effects of weight fluctuation. Weight reduction may not be as effective in men, but does not appear to be harmful either. ^ Paper 2 examined the associations of upper and total body fat with total cholesterol, HDL and LDL cholesterol, and triglyceride levels in the same population. Multilevel analysis was used to predict serum lipid levels from total body fat (BMI and triceps skinfold) and upper body fat (subscapular skinfold), while controlling for the effects of sex, age and self-correlations across time. Body fat was not strikingly associated with trends in serum lipid levels. However, upper body fat was strongly associated with triglyceride levels. This suggests that loss of upper body fat may be more important than weight loss in management of the hypertriglyceridemia commonly seen in type 2 diabetes. ^ Paper 3 was a review of the literature reporting associations between weight fluctuation and lipid levels. Few studies have reported associations between weight fluctuation and total, LDL, and HDL cholesterol and triglyceride levels. The body of evidence to date suggests that weight fluctuation does not strongly influence levels of total, LDL and HDL cholesterol and triglyceride. ^
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Hepatitis B infection is a major public health problem of global proportions. It is estimated that 2 billion people worldwide are infected by the Hepatitis B virus (HBV) at some point, and 350 million are chronic carriers. The Centers for Disease Control and Prevention (CDC) report an incidence in the United States of 140,000–320,000 infections each year (asymptomatic and symptomatic), and estimate 1–1.25 million people are chronically infected. Hepatitis B and its chronic complications (cirrhosis of the liver, liver failure, hepatocellular carcinoma) responsible for 4,000–5,000 deaths in America each year. ^ One quarter of those who become chronic carriers develop progressive liver disease, and chronic HBV infection is thought to be responsible for 60 million cases of cirrhosis worldwide, surpassing alcohol as a cause of liver disease. Since there are few treatment options for the person chronically infected with Hepatitis B, and what is available is expensive, prevention is clearly best strategy for combating this disease. ^ Since the approval of the Hepatitis B vaccine in 1981, national and international vaccination campaigns have been undertaken for the prevention of Hepatitis B. Despite encouraging results, however, studies indicate that prevalence rates of Hepatitis B infection have not been significantly reduced in certain high risk populations because vaccination campaigns targeting those groups do not exist and opportunities for vaccination by individual physicians in clinical settings are often missed. Many of the high-risk individuals who go unvaccinated are women of childbearing age, and a significant proportion of these women become infected with the Hepatitis B virus (HBV) during pregnancy. Though these women are often seen annually or for prenatal care (because of the close spacing of their children and their high rate of fertility), the Hepatitis B vaccine series is seldom recommended by their health care provider. In 1993, ACOG issued a statement recommending Hepatitis B vaccination of pregnant women who were defined as high-risk by diagnosis of a sexually transmitted disease. ^ Hepatitis B vaccine has been extensively studied in the non-pregnant population. The overall efficacy of the vaccine in infants, children and adults is greater than 90%. In the small clinical trials to date, the vaccine seemed to be effective in those pregnant women receiving 3 doses; however, by using the usual 0, 1 and 6 month regimen, most pregnant women were unable to complete a full series during pregnancy. There is data now available supporting the use of an "accelerated" dosing schedule at 0, 1 and 4 months. This has not been evaluated in pregnant women. A clinical trial proving the efficacy of the 0, 1, 4 schedule and its feasibility in this population would add significantly to the body of research in this area, and would have implications for public health policy. Such a trial was undertaken in the Parkland Memorial Hospital Obstetrical Infectious Diseases clinic. In this study, the vaccine was very well tolerated with no major adverse events reported, 90% of fully vaccinated patients achieved immunity, and only Body Mass Index (BMI) was found to be a significant factor affecting efficacy. This thesis will report the results of the trial and compare it to previous trials, and will discuss barriers to implementation, lessons learned and implications for future trials. ^
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Background. In over 30 years, the prevalence of overweight for children and adolescents has increased across the United States (Barlow et al., 2007; Ogden, Flegal, Carroll, & Johnson, 2002). Childhood obesity is linked with adverse physiological and psychological issues in youth and affects ethnic/minority populations in disproportionate rates (Barlow et al., 2007; Butte et al., 2006; Butte, Cai, Cole, Wilson, Fisher, Zakeri, Ellis, & Comuzzie, 2007). More importantly, overweight in children and youth tends to track into adulthood (McNaughton, Ball, Mishra, & Crawford, 2008; Ogden et al., 2002). Childhood obesity affects body functions such as the cardiovascular, respiratory, gastrointestinal, and endocrine systems, including emotional health (Barlow et al., 2007, Ogden et al., 2002). Several dietary factors have been associated with the development of obesity in children; however, these factors have not been fully elucidated, especially in ethnic/minority children. In particular, few studies have been done to determine the effects of different meal patterns on the development of obesity in children. Purpose. The purpose of the study is to examine the relationships between daily proportions of energy consumed and energy derived from fat across breakfast, lunch, dinner, and snack, and obesity among Hispanic children and adolescents. Methods. A cross-sectional design was used to evaluate the relationship between dietary patterns and overweight status in Hispanic children and adolescents 4-19 years of age who participated in the Viva La Familia Study. The goal of the Viva La Familia Study was to evaluate genetic and environmental factors affecting childhood obesity and its co-morbidities in the Hispanic population (Butte et al., 2006, 2007). The study enrolled 1030 Hispanic children and adolescents from 319 families and examined factors related to increased body weight by focusing on a multilevel analysis of extensive sociodemographic, genetic, metabolic, and behavioral data. Baseline dietary intakes of the children were collected using 24-hour recalls, and body mass index was calculated from measured height and weight, and classified using the CDC standards. Dietary data were analyzed using a GEE population-averaged panel-data model with a cluster variable family identifier to include possible correlations within related data sets. A linear regression model was used to analyze associations of dietary patterns using possible covariates, and to examine the percentage of daily energy coming from breakfast, lunch, dinner, and snack while adjusting for age, sex, and BMI z-score. Random-effects logistic regression models were used to determine the relationship of the dietary variables with obesity status and to understand if the percent energy intake (%EI) derived from fat from all meals (breakfast, lunch, dinner, and snacks) affected obesity. Results. Older children (age 4-19 years) consumed a higher percent of energy at lunch and dinner and less percent energy from snacks compared to younger children. Age was significantly associated with percentage of total energy intake (%TEI) for lunch, as well as dinner, while no association was found by gender. Percent of energy consumed from dinner significantly differed by obesity status, with obese children consuming more energy at dinner (p = 0.03), but no associations were found between percent energy from fat and obesity across all meals. Conclusions. Information from this study can be used to develop interventions that target dietary intake patterns in obesity prevention programs for Hispanic children and adolescents. In particular, intervention programs for children should target dietary patterns with energy intake that is spread throughout the day and earlier in the day. These results indicate that a longitudinal study should be used to further explore the relationship of dietary patterns and BMI in this and other populations (Dubois et al., 2008; Rodriquez & Moreno, 2006; Thompson et al., 2005; Wilson et al., in review, 2008). ^
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Problem. Recent statistics show that over a fifth of children aged 2-5 years in 2006-2008 were overweight, with 7% above the 97 th percentile of the BMI-for-age growth charts (extreme obesity). Because poor diet is an important environmental determinant of obesity and the preschool years are crucial developmentally, examination of factors related to diet in the pre-school years is important for obesity prevention efforts. ^ Objective. The goals of this study were to determine the association between BMI of the parents and the number of servings of fruits, vegetables, and whole grains (FVWG) packed; the nutrient content of preschool children’s lunches; and norms and expectations about FVWG intake.^ Methods. This study was a cross sectional analysis of parents enrolled in the Lunch is in the Bag program at baseline. The independent measure was weight status of the parents/caregivers, which was determined using body mass index (BMI) calculated from self-reported height and weight. BMI was classified as healthy weight (BMI <25) or overweight/obese (BMI ≥25). Outcomes for the study included the number of servings of fruits, vegetables and whole grains (FVWG) in sack lunches, as well as the nutrient content of the lunches, and psychosocial constructs related to FVWG consumption. Linear regression analysis was conducted and adjusted for confounders to examine the associations of these outcomes with parental weight status, the main predictor. ^ Results. A total of 132 parent/child dyads were enrolled in the study; 59.09% (n=78) of the parents/caregivers were healthy weight and 39.01% (n=54) of the parents/caregivers were overweight/obese. Parents/caregivers in the study were predominantly white (68%, n=87) and had at least some college education (98%, n=128). No significant associations were found between the weight status of the parents and the servings of fruits, vegetables and whole grain packed in preschool children’s lunchboxes. The results were similar for the association of parental weight status and the nutrient contents of the packed lunches. Both healthy weight and overweight/obese parents packed less than the recommended amounts of vegetables (mean servings = 0.49 and 0.534, respectively) and whole grains (mean servings = 0.58 and 0.511, respectively). However, the intentions of the obese/overweight parents were higher compare to the healthy for vegetables and whole grains.^ Conclusion. Results from this study indicate that there are few differences in the servings of fruits, vegetables and whole grains packed by healthy weight parents/caregivers compared to overweight/obese parents/caregivers in a high income, well-educated population, although neither group met the recommended number of servings of vegetables or whole grains. Thus, results indicate the need for behaviorally-based health promotion programs for parents, regardless of their weight status; however, this study should be replicated with larger and more diverse populations to determine if these results are similar with less homogenous populations.^
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There exists an interest in performing pin-by-pin calculations coupled with thermal hydraulics so as to improve the accuracy of nuclear reactor analysis. In the framework of the EU NURISP project, INRNE and UPM have generated an experimental version of a few group diffusion cross sections library with discontinuity factors intended for VVER analysis at the pin level with the COBAYA3 code. The transport code APOLLO2 was used to perform the branching calculations. As a first proof of principle the library was created for fresh fuel and covers almost the full parameter space of steady state and transient conditions. The main objective is to test the calculation schemes and post-processing procedures, including multi-pin branching calculations. Two library options are being studied: one based on linear table interpolation and another one using a functional fitting of the cross sections. The libraries generated with APOLLO2 have been tested with the pin-by-pin diffusion model in COBAYA3 including discontinuity factors; first comparing 2D results against the APOLLO2 reference solutions and afterwards using the libraries to compute a 3D assembly problem coupled with a simplified thermal-hydraulic model.
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Introduction. Most studies have described how the weight loss is when different treatments are compared (1-3), while others have also compared the weight loss by sex (4), or have taken into account psychosocial (5) and lifestyle (6, 7) variables. However, no studies have examined the interaction of different variables and the importance of them in the weight loss. Objective. Create a model to discriminate the range of weight loss, determining the importance of each variable. Methods. 89 overweight people (BMI: 25-29.9 kg?m-2), aged from 18 to 50 years, participated in the study. Four types of treatments were randomly assigned: strength training (S), endurance training (E), strength and endurance training (SE), and control group (C). All participants followed a 25% calorie restriction diet. Two multivariate discriminant models including the variables age, sex, height, daily energy expenditure (EE), type of treatment (T), caloric restriction (CR), initial body weight (BW), initial fat mass (FM), initial muscle mass (MM) and initial bone mineral density (BMD) were performed having into account two groups: the first and fourth quartile of the % of weight loss in the first model; the groups above and below the mean of the % of weight loss in the second model. The discriminant models were built using the inclusion method in SPSS allowing us to find a function that could predict the body weight loss range that an overweight person could achieve in a 6 months weight loss intervention.Results. The first discriminant analysis predicted that a combination of the studied variables would discriminate between the two ranges of body weight loss with 81.4% of correct classification. The discriminant function obtained was (Wilks? Lambda=0.475, p=0.003): Discriminant score=-18.266-(0.060xage)- (1.282xsex[0=female;1=male])+(14.701xheight)+(0.002xEE)- (0.006xT[1=S;2=E;3=SE;4=C])-(0.047xCR)- (0.558xBW)+(0.475xFM)+(0.398xMM)+(3.499xBMD) The second discriminant model obtained would discriminate between the two groups of body weight loss with 74.4% of correct classification. The discriminant function obtained was (Wilks? Lambda=0.725, p=0.005): Discriminant score=-5.021-(0.052xage)- (0.543xsex[0=female;1=male])+(3.530xheight)+(0.001xEE)- (0.493xT[1=S;2=E;3=SE;4=C])+(0.003xCR)- (0.365xBW)+(0.368xFM)+(0.296xMM)+(4.034xBMD) Conclusion. The first developed model could predict the percentage of weight loss in the following way: if the discriminant score is close to 1.051, the range of weight loss will be from 7.44 to -4.64% and if it is close to - 1.003, the range will be from -11.03 to -25,00% of the initial body weight. With the second model if the discriminant score is close to 0.623 the body weight loss will be above -7.93% and if it is close to -0.595 will be below - 7.93% of the initial body weight. References. 1. Brochu M, et al. Resistance training does not contribute to improving the metabolic profile after a 6-month weight loss program in overweight and obese postmenopausal women. J Clin Endocrinol Metab. 2009 Sep;94(9):3226-33. 2. Del Corral P, et al. Effect of dietary adherence with or without exercise on weight loss: a mechanistic approach to a global problem. J Clin Endocrinol Metab. 2009 May;94(5):1602-7. 3. Larson-Meyer DE, et al. Caloric Restriction with or without Exercise: The Fitness vs. Fatness Debate. Med Sci Sports Exerc. 2010;42(1):152-9. 4. Hagan RD, et al. The effects of aerobic conditioning and/or caloric restriction in overweight men and women. Medicine & Science in Sports & Exercise. 1986;18(1):87-94. 5. Teixeira PJ, et al. Mediators of weight loss and weight loss maintenance in middle-aged women. Obesity (Silver Spring). 2010 Apr;18(4):725-35. 6. Bautista-Castano I, et al. Variables predictive of adherence to diet and physical activity recommendations in the treatment of obesity and overweight, in a group of Spanish subjects. Int J Obes Relat Metab Disord. 2004 May;28(5):697-705.
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The developments in materials over the last decade have been considerable within the automotive industry, being one of the leaders in innovative product applications. Sustainable product development of an automotive structure requires a balanced approach towards technological, economical and ecological aspects. The introduction of new materials and processes is dependent on satisfying different factors. Competitive and legislative pressures, creating the need for change, affect these factors considerably. The process, direction and speed of change are often reactive. Current paper shows the application of aluminium alloys, for the use in the bottom structure of a car to face the problem for the weight of the entire bottom structure under static load conditions, including stiffness, strength and buckling constraints. In addition to minimized mass and materials' price, the assessment of an environmental impact of materials-candidates during the entire life cycle of the structure is considered.
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The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps.
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The new user cold start issue represents a serious problem in recommender systems as it can lead to the loss of new users who decide to stop using the system due to the lack of accuracy in the recommenda- tions received in that first stage in which they have not yet cast a significant number of votes with which to feed the recommender system?s collaborative filtering core. For this reason it is particularly important to design new similarity metrics which provide greater precision in the results offered to users who have cast few votes. This paper presents a new similarity measure perfected using optimization based on neu- ral learning, which exceeds the best results obtained with current metrics. The metric has been tested on the Netflix and Movielens databases, obtaining important improvements in the measures of accuracy, precision and recall when applied to new user cold start situations. The paper includes the mathematical formalization describing how to obtain the main quality measures of a recommender system using leave- one-out cross validation.
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Computational fluid dynamic (CFD) methods are used in this paper to predict the power production from entire wind farms in complex terrain and to shed some light into the wake flow patterns. Two full three-dimensional Navier–Stokes solvers for incompressible fluid flow, employing k − ϵ and k − ω turbulence closures, are used. The wind turbines are modeled as momentum absorbers by means of their thrust coefficient through the actuator disk approach. Alternative methods for estimating the reference wind speed in the calculation of the thrust are tested. The work presented in this paper is part of the work being undertaken within the UpWind Integrated Project that aims to develop the design tools for next generation of large wind turbines. In this part of UpWind, the performance of wind farm and wake models is being examined in complex terrain environment where there are few pre-existing relevant measurements. The focus of the work being carried out is to evaluate the performance of CFD models in large wind farm applications in complex terrain and to examine the development of the wakes in a complex terrain environment.
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There is general agreement within the scientific community in considering Biology as the science with more potential to develop in the XXI century. This is due to several reasons, but probably the most important one is the state of development of the rest of experimental and technological sciences. In this context, there are a very rich variety of mathematical tools, physical techniques and computer resources that permit to do biological experiments that were unbelievable only a few years ago. Biology is nowadays taking advantage of all these newly developed technologies, which are been applied to life sciences opening new research fields and helping to give new insights in many biological problems. Consequently, biologists have improved a lot their knowledge in many key areas as human function and human diseases. However there is one human organ that is still barely understood compared with the rest: The human brain. The understanding of the human brain is one of the main challenges of the XXI century. In this regard, it is considered a strategic research field for the European Union and the USA. Thus, there is a big interest in applying new experimental techniques for the study of brain function. Magnetoencephalography (MEG) is one of these novel techniques that are currently applied for mapping the brain activity1. This technique has important advantages compared to the metabolic-based brain imagining techniques like Functional Magneto Resonance Imaging2 (fMRI). The main advantage is that MEG has a higher time resolution than fMRI. Another benefit of MEG is that it is a patient friendly clinical technique. The measure is performed with a wireless set up and the patient is not exposed to any radiation. Although MEG is widely applied in clinical studies, there are still open issues regarding data analysis. The present work deals with the solution of the inverse problem in MEG, which is the most controversial and uncertain part of the analysis process3. This question is addressed using several variations of a new solving algorithm based in a heuristic method. The performance of those methods is analyzed by applying them to several test cases with known solutions and comparing those solutions with the ones provided by our methods.
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In the last few years there has been a heightened interest in data treatment and analysis with the aim of discovering hidden knowledge and eliciting relationships and patterns within this data. Data mining techniques (also known as Knowledge Discovery in Databases) have been applied over a wide range of fields such as marketing, investment, fraud detection, manufacturing, telecommunications and health. In this study, well-known data mining techniques such as artificial neural networks (ANN), genetic programming (GP), forward selection linear regression (LR) and k-means clustering techniques, are proposed to the health and sports community in order to aid with resistance training prescription. Appropriate resistance training prescription is effective for developing fitness, health and for enhancing general quality of life. Resistance exercise intensity is commonly prescribed as a percent of the one repetition maximum. 1RM, dynamic muscular strength, one repetition maximum or one execution maximum, is operationally defined as the heaviest load that can be moved over a specific range of motion, one time and with correct performance. The safety of the 1RM assessment has been questioned as such an enormous effort may lead to muscular injury. Prediction equations could help to tackle the problem of predicting the 1RM from submaximal loads, in order to avoid or at least, reduce the associated risks. We built different models from data on 30 men who performed up to 5 sets to exhaustion at different percentages of the 1RM in the bench press action, until reaching their actual 1RM. Also, a comparison of different existing prediction equations is carried out. The LR model seems to outperform the ANN and GP models for the 1RM prediction in the range between 1 and 10 repetitions. At 75% of the 1RM some subjects (n = 5) could perform 13 repetitions with proper technique in the bench press action, whilst other subjects (n = 20) performed statistically significant (p < 0:05) more repetitions at 70% than at 75% of their actual 1RM in the bench press action. Rate of perceived exertion (RPE) seems not to be a good predictor for 1RM when all the sets are performed until exhaustion, as no significant differences (p < 0:05) were found in the RPE at 75%, 80% and 90% of the 1RM. Also, years of experience and weekly hours of strength training are better correlated to 1RM (p < 0:05) than body weight. O'Connor et al. 1RM prediction equation seems to arise from the data gathered and seems to be the most accurate 1RM prediction equation from those proposed in literature and used in this study. Epley's 1RM prediction equation is reproduced by means of data simulation from 1RM literature equations. Finally, future lines of research are proposed related to the problem of the 1RM prediction by means of genetic algorithms, neural networks and clustering techniques. RESUMEN En los últimos años ha habido un creciente interés en el tratamiento y análisis de datos con el propósito de descubrir relaciones, patrones y conocimiento oculto en los mismos. Las técnicas de data mining (también llamadas de \Descubrimiento de conocimiento en bases de datos\) se han aplicado consistentemente a lo gran de un gran espectro de áreas como el marketing, inversiones, detección de fraude, producción industrial, telecomunicaciones y salud. En este estudio, técnicas bien conocidas de data mining como las redes neuronales artificiales (ANN), programación genética (GP), regresión lineal con selección hacia adelante (LR) y la técnica de clustering k-means, se proponen a la comunidad del deporte y la salud con el objetivo de ayudar con la prescripción del entrenamiento de fuerza. Una apropiada prescripción de entrenamiento de fuerza es efectiva no solo para mejorar el estado de forma general, sino para mejorar la salud e incrementar la calidad de vida. La intensidad en un ejercicio de fuerza se prescribe generalmente como un porcentaje de la repetición máxima. 1RM, fuerza muscular dinámica, una repetición máxima o una ejecución máxima, se define operacionalmente como la carga máxima que puede ser movida en un rango de movimiento específico, una vez y con una técnica correcta. La seguridad de las pruebas de 1RM ha sido cuestionada debido a que el gran esfuerzo requerido para llevarlas a cabo puede derivar en serias lesiones musculares. Las ecuaciones predictivas pueden ayudar a atajar el problema de la predicción de la 1RM con cargas sub-máximas y son empleadas con el propósito de eliminar o al menos, reducir los riesgos asociados. En este estudio, se construyeron distintos modelos a partir de los datos recogidos de 30 hombres que realizaron hasta 5 series al fallo en el ejercicio press de banca a distintos porcentajes de la 1RM, hasta llegar a su 1RM real. También se muestra una comparación de algunas de las distintas ecuaciones de predicción propuestas con anterioridad. El modelo LR parece superar a los modelos ANN y GP para la predicción de la 1RM entre 1 y 10 repeticiones. Al 75% de la 1RM algunos sujetos (n = 5) pudieron realizar 13 repeticiones con una técnica apropiada en el ejercicio press de banca, mientras que otros (n = 20) realizaron significativamente (p < 0:05) más repeticiones al 70% que al 75% de su 1RM en el press de banca. El ínndice de esfuerzo percibido (RPE) parece no ser un buen predictor del 1RM cuando todas las series se realizan al fallo, puesto que no existen diferencias signifiativas (p < 0:05) en el RPE al 75%, 80% y el 90% de la 1RM. Además, los años de experiencia y las horas semanales dedicadas al entrenamiento de fuerza están más correlacionadas con la 1RM (p < 0:05) que el peso corporal. La ecuación de O'Connor et al. parece surgir de los datos recogidos y parece ser la ecuación de predicción de 1RM más precisa de aquellas propuestas en la literatura y empleadas en este estudio. La ecuación de predicción de la 1RM de Epley es reproducida mediante simulación de datos a partir de algunas ecuaciones de predicción de la 1RM propuestas con anterioridad. Finalmente, se proponen futuras líneas de investigación relacionadas con el problema de la predicción de la 1RM mediante algoritmos genéticos, redes neuronales y técnicas de clustering.
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La condición física, o como mejor se la conoce hoy en día el “fitness”, es una variable que está cobrando gran protagonismo, especialmente desde la perspectiva de la salud. La mejora de la calidad de vida que se ha experimentado en los últimos años en las sociedades desarrolladas, conlleva un aumento de la esperanza de vida, lo que hace que cada vez más personas vivan más años. Este rápido crecimiento de la población mayor de 60 años hace que, un grupo poblacional prácticamente olvidado desde el punto de vista de la investigación científica en el campo de la actividad física y del deporte, cobre gran relevancia, con el fin de poder ayudar a alcanzar el dicho “no se trata de aportar años a la vida sino vida a lo años”. La presente memoria de Tesis Doctoral tiene como principal objetivo valorar los niveles de fitness en población mayor española, además de analizar la relación existente entre el fitness, sus condicionantes y otros aspectos de la salud, tales como la composición corporal y el estado cognitivo. Entendemos que para poder establecer futuras políticas de salud pública en relación a la actividad física y el envejecimiento activo es necesario conocer cuáles son los niveles de partida de la población mayor en España y sus condicionantes. El trabajo está basado en los datos del estudio multicéntrico EXERNET (Estudio Multi-céntrico para la Evaluación de los Niveles de Condición Física y su relación con Estilos de Vida Saludables en población mayor española no institucionalizada), así como en los datos de dos estudios, llevados a cabo en población mayor institucionalizada. Se han analizado un total de 3136 mayores de vida independiente, procedentes de 6 comunidades autónomas, y 153 mayores institucionalizados en residencias de la Comunidad de Madrid. Los principales resultados de esta tesis son los siguientes: a) Fueron establecidos los valores de referencia, así como las curvas de percentiles, para cada uno de los test de fitness, de acuerdo a la edad y al sexo, en población mayor española de vida independiente y no institucionalizada. b) Los varones obtuvieron mejores niveles de fitness que las mujeres, excepto en los test de flexibilidad; existe una tendencia a disminuir la condición física en ambos sexos a medida que la edad aumenta. c) Niveles bajos de fitness funcional fueron asociados con un aumento en la percepción de problemas. d) El nivel mínimo de fitness funcional a partir del cual los mayores perciben problemas en sus actividades de la vida diaria (AVD) es similar en ambos sexos. e) Niveles elevados de fitness fueron asociados con un menor riesgo de sufrir obesidad sarcopénica y con una mejor salud percibida en los mayores. f) Las personas mayores con obesidad sarcopénica tienen menor capacidad funcional que las personas mayores sanas. g) Niveles elevados de fuerza fueron asociados con un mejor estado cognitivo siendo el estado cognitivo la variable que más influye en el deterioro de la fuerza, incluso más que el sexo y la edad. ABSTRACT Fitness is a variable that is gaining in prominence, especially from the health perspective. Improvement of life quality that has been experienced in the last few years in developed countries, leads to an expanded life expectancy, increasing the numbers of people living longer. This population consisting of people of over 60 years, an almost forgotten population group from the point of view of scientific research in the field of physical activity and sport, is becoming increasingly important, with the main aim of helping to achieve the saying “do not only add years to life, but also add life to years”. The principal aim of the current thesis was to assess physical fitness levels in Spanish elderly people, of over 65 years, analyzing relationship between physical fitness, its determinants, and other aspects of health such as body composition and cognitive status. In order to establish further public health policies in relation to physical activity and active ageing it is necessary to identify the starting physical fitness levels of the Spanish population and their determinants. The work is based on data from the EXERNET multi-center study ("Multi-center Study for the Evaluation of Fitness levels and their relationship to Healthy Lifestyles in noninstitutionalized Spanish elderly"), and on data from two studies conducted in institutionalized elderly people: a total of 3136 non-institutionalized elderly, from 6 Regions of Spain, and 153 institutionalized elderly in nursing homes of Madrid. The main outcomes of this thesis are: a) sex- and age-specific physical fitness normative values and percentile curves for independent and non-institutionalized Spanish elderly were established. b) Greater physical fitness was present in the elderly men than in women, except for the flexibility test, and a trend toward decreased physical fitness in both sexes as their age increased. c) Lower levels of functional fitness were associated with increased perceived problems. d) The minimum functional fitness level at which older adults perceive problems in their ADLs, is similar for both sexes e) Higher levels of physical fitness were associated with a reduced risk of suffering sarcopenic obesity and better perceived health among the elderly. f) The elderly with sarcopenic obesity have lower physical functioning than healthy counterparts. g) Higher strength values were associated with better cognitive status with cognitive status being the most influencing variable in strength deterioration even more than sex and age.