Effect of endurance, speed and strength training on skin temperature measured by infrared thermography = Efecto del entrenamiento de resistencia, velocidad y fuerza en la temperatura de la piel a través de la termografía infrarroja

La termografía infrarroja (TI) es una técnica no invasiva y de bajo coste que permite, con el simple acto de tomar una fotografía, el registro sin contacto de la energía que irradia el cuerpo humano (Akimov & Son’kin, 2011, Merla et al., 2005, Ng et al., 2009, Costello et al., 2012, Hildebrandt et al., 2010). Esta técnica comenzó a utilizarse en el ámbito médico en los años 60, pero debido a los malos resultados como herramienta diagnóstica y la falta de protocolos estandarizados (Head & Elliot, 2002), ésta se dejó de utilizar en detrimento de otras técnicas más precisas a nivel diagnóstico. No obstante, las mejoras tecnológicas de la TI en los últimos años han hecho posible un resurgimiento de la misma (Jiang et al., 2005, Vainer et al., 2005, Cheng et al., 2009, Spalding et al., 2011, Skala et al., 2012), abriendo el camino a nuevas aplicaciones no sólo centradas en el uso diagnóstico. Entre las nuevas aplicaciones, destacamos las que se desarrollan en el ámbito de la actividad física y el deporte, donde recientemente se ha demostrado que los nuevos avances con imágenes de alta resolución pueden proporcionar información muy interesante sobre el complejo sistema de termorregulación humana (Hildebrandt et al., 2010). Entre las nuevas aplicaciones destacan: la cuantificación de la asimilación de la carga de trabajo físico (Čoh & Širok, 2007), la valoración de la condición física (Chudecka et al., 2010, 2012, Akimov et al., 2009, 2011, Merla et al., 2010), la prevención y seguimiento de lesiones (Hildebrandt et al., 2010, 2012, Badža et al., 2012, Gómez Carmona, 2012) e incluso la detección de agujetas (Al-Nakhli et al., 2012). Bajo estas circunstancias, se acusa cada vez más la necesidad de ampliar el conocimiento sobre los factores que influyen en la aplicación de la TI en los seres humanos, así como la descripción de la respuesta de la temperatura de la piel (TP) en condiciones normales, y bajo la influencia de los diferentes tipos de ejercicio. Por consiguiente, este estudio presenta en una primera parte una revisión bibliográfica sobre los factores que afectan al uso de la TI en los seres humanos y una propuesta de clasificación de los mismos. Hemos analizado la fiabilidad del software Termotracker, así como su reproducibilidad de la temperatura de la piel en sujetos jóvenes, sanos y con normopeso. Finalmente, se analizó la respuesta térmica de la piel antes de un entrenamiento de resistencia, velocidad y fuerza, inmediatamente después y durante un período de recuperación de 8 horas. En cuanto a la revisión bibliográfica, hemos propuesto una clasificación para organizar los factores en tres grupos principales: los factores ambientales, individuales y técnicos. El análisis y descripción de estas influencias deben representar la base de nuevas investigaciones con el fin de utilizar la TI en las mejores condiciones. En cuanto a la reproducibilidad, los resultados mostraron valores excelentes para imágenes consecutivas, aunque la reproducibilidad de la TP disminuyó ligeramente con imágenes separadas por 24 horas, sobre todo en las zonas con valores más fríos (es decir, zonas distales y articulaciones). Las asimetrías térmicas (que normalmente se utilizan para seguir la evolución de zonas sobrecargadas o lesionadas) también mostraron excelentes resultados pero, en este caso, con mejores valores para las articulaciones y el zonas centrales (es decir, rodillas, tobillos, dorsales y pectorales) que las Zonas de Interés (ZDI) con valores medios más calientes (como los muslos e isquiotibiales). Los resultados de fiabilidad del software Termotracker fueron excelentes en todas las condiciones y parámetros. En el caso del estudio sobre los efectos de los entrenamientos de la velocidad resistencia y fuerza en la TP, los resultados muestran respuestas específicas según el tipo de entrenamiento, zona de interés, el momento de la evaluación y la función de las zonas analizadas. Los resultados mostraron que la mayoría de las ZDI musculares se mantuvieron significativamente más calientes 8 horas después del entrenamiento, lo que indica que el efecto del ejercicio sobre la TP perdura por lo menos 8 horas en la mayoría de zonas analizadas. La TI podría ser útil para cuantificar la asimilación y recuperación física después de una carga física de trabajo. Estos resultados podrían ser muy útiles para entender mejor el complejo sistema de termorregulación humano, y por lo tanto, para utilizar la TI de una manera más objetiva, precisa y profesional con visos a mejorar las nuevas aplicaciones termográficas en el sector de la actividad física y el deporte Infrared Thermography (IRT) is a safe, non-invasive and low-cost technique that allows the rapid and non-contact recording of the irradiated energy released from the body (Akimov & Son’kin, 2011; Merla et al., 2005; Ng et al., 2009; Costello et al., 2012; Hildebrandt et al., 2010). It has been used since the early 1960’s, but due to poor results as diagnostic tool and a lack of methodological standards and quality assurance (Head et al., 2002), it was rejected from the medical field. Nevertheless, the technological improvements of IRT in the last years have made possible a resurgence of this technique (Jiang et al., 2005; Vainer et al., 2005; Cheng et al., 2009; Spalding et al., 2011; Skala et al., 2012), paving the way to new applications not only focused on the diagnose usages. Among the new applications, we highlighted those in physical activity and sport fields, where it has been recently proven that a high resolution thermal images can provide us with interesting information about the complex thermoregulation system of the body (Hildebrandt et al., 2010), information than can be used as: training workload quantification (Čoh & Širok, 2007), fitness and performance conditions (Chudecka et al., 2010, 2012; Akimov et al., 2009, 2011; Merla et al., 2010; Arfaoui et al., 2012), prevention and monitoring of injuries (Hildebrandt et al., 2010, 2012; Badža et al., 2012, Gómez Carmona, 2012) and even detection of Delayed Onset Muscle Soreness – DOMS- (Al-Nakhli et al., 2012). Under this context, there is a relevant necessity to broaden the knowledge about factors influencing the application of IRT on humans, and to better explore and describe the thermal response of Skin Temperature (Tsk) in normal conditions, and under the influence of different types of exercise. Consequently, this study presents a literature review about factors affecting the application of IRT on human beings and a classification proposal about them. We analysed the reliability of the software Termotracker®, and also its reproducibility of Tsk on young, healthy and normal weight subjects. Finally, we examined the Tsk thermal response before an endurance, speed and strength training, immediately after and during an 8-hour recovery period. Concerning the literature review, we proposed a classification to organise the factors into three main groups: environmental, individual and technical factors. Thus, better exploring and describing these influence factors should represent the basis of further investigations in order to use IRT in the best and optimal conditions to improve its accuracy and results. Regarding the reproducibility results, the outcomes showed excellent values for consecutive images, but the reproducibility of Tsk slightly decreased with time, above all in the colder Regions of Interest (ROI) (i.e. distal and joint areas). The side-to-side differences (ΔT) (normally used to follow the evolution of some injured or overloaded ROI) also showed highly accurate results, but in this case with better values for joints and central ROI (i.e. Knee, Ankles, Dorsal and Pectoral) than the hottest muscle ROI (as Thigh or Hamstrings). The reliability results of the IRT software Termotracker® were excellent in all conditions and parameters. In the part of the study about the effects on Tsk of aerobic, speed and strength training, the results of Tsk demonstrated specific responses depending on the type of training, ROI, moment of the assessment and the function of the considered ROI. The results showed that most of muscular ROI maintained warmer significant Tsk 8 hours after the training, indicating that the effect of exercise on Tsk last at least 8 hours in most of ROI, as well as IRT could help to quantify the recovery status of the athlete as workload assimilation indicator. Those results could be very useful to better understand the complex skin thermoregulation behaviour, and therefore, to use IRT in a more objective, accurate and professional way to improve the new IRT applications for the physical activity and sport sector.

Injuries in strength training: review and practical application

Purpose: This systematic review examines what is known about injuries in strength training. Methods: A systematic search was performed in PubMed and SportDiscus. Studies were included if they examined powerlifters, weightlifters, strongman athletes, bodybuilding athletes, individuals who undertook recreational weight training or weight training to complement athletic performance. Exposure variables were incidence, severity and body part injury. Results: After examining 1214 titles and abstracts, 62 articles were identified as potentially relevant. Finally, 11 were included in this systematic review. Conflicting results were reported on the relationships between injury definition and incidence or severity recorded. The lower back followed by the shoulder and knee are the most frequently affected areas in strength sports. Conclusion: Strength training is safe. However, the variety of injury definitions has makes it difficult to compare different studies in this field. New styles of reporting injuries have appeared, and could make increases these ratios. If methodological limitations in measuring incidence rate and severity injuries can be resolved, more work can be conducted to define the real incidence rate, compare it with others sports, and explore cause and effect relationships in randomized controlled trials. Key Words: strength training, injuries, specific strength sports, severity

Validation of an instrument for injury data collection in strength training

Purpose: To provide for the basis for collecting strength training data using a rigorously validated injury report form. Methods: A group of specialist designed a questionnaire of 45 item grouped into 4 dimensions. Six stages were used to assess face, content, and criterion validity of the weight training injury report form. A 13 members panel assessed the form for face validity, and an expert panel assessed it for content and criterion validity. Panel members were consulted until consensus was reached. A yardstick developed by an expert panel using Intraclass correlation technique was used to assess the reability of the form. Test-retest reliability was assessed with the intraclass correlation coefficient (ICC).The strength training injury report form was developed, and the face, content, and criterion validity successfully assessed. A six step protocol to create a yardstick was also developed to assist in the validation process. Both inter-rater and intra rater reliability results indicated a 98% agreement. Inter-rater reliability agreement of 98% for three injuries. Results: The Cronbach?s alpha of the questionnaire was 0.944 (pmenor que0.01) and the ICC of the entire questionnaire was 0.894 (pmenor que0.01). Conclusion: The questionnaire gathers together enough psychometric properties to be considered a valid and reliable tool for register injury data in strength training, and providing researchers with a basis for future studies in this area. Key Words: data collection; validation; injury prevention; strength training

MCT1 T1470A polymorphism influences adherence to strength training in overweight and obese men following a weight loss program

The monocarboxylate transporter (MCT) family member MCT1 transports lactate into and out of myocytes. Oxidative cells import lactate through MCT1 as a substrate, being the role of MCT1 in glycolysis-derived lactate efflux less clear. MCT1 T1470A polymorphism (rs1049434), which has been related with lactate metabolism and sports specialty 1, 2, could be an influencing factor for exercise adherence. Therefore the aim of this study was to relate the adherence to different training modalities with the T1470A MCT1 polymorphism in overweight and obese men following a weight loss program (WLP).

Combined exercise effects on metabolic syndrome

Few randomized trials have examined the optimal mode of exercise or combination of modalities for specific cardiometabolic health benefits [1-3] . Therefore, questions remain unaddressed whether strength training or endurance training alone improves cardiometabolic health in overweight adults; whether a combination of both provides additional improvements [4, 5].

Determinant factors to discriminate the body weight loss in overweight people

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.

Effect of different exercise modalities plus a hypocaloric diet on inflammation markers in overweight patients

Summary Background & aims Inflammation markers (IM) have been associated with the development of chronic diseases. This study compares the effects on IM of three exercise programs combined with a hypocaloric diet. Methods 119 overweight participants (73 women, 46 men) aged 18–50 years were randomised into four treatment groups: strength training (S; n = 30), endurance training (E; n = 30), combined S + E (SE; n = 30), and a diet and physical activity recommendations group (D; n = 29). Energy intake, anthropometric variables (AV), training variables (VO2peak, strength index, dynamometric strength index [DSI]) and plasma IM were recorded at baseline and after 22 weeks of treatment. Results 84 participants completed the study. At 22 weeks, all groups showed a significantly reduced energy intake (P < 0.001) and improved AV (P < 0.001). VO2peak significantly increased in all groups (P < 0.01). DSI increased in the exercise groups only (P < 0.05). Plasma leptin fell significantly (P < 0.001) in the S and E groups, but not significantly in the SE group (P = 0.029) (no significant differences between these groups). Tumour necrosis factor-α (TNF-α), and C-reactive protein (CRP) concentrations decreased in all groups when examined together, but not when examined separately. No significant differences were seen in interleukin-6 (IL-6). Conclusions Combining strength or endurance training with a hypocaloric diet improved AV and reduced plasma leptin concentrations. No differences were seen between groups in terms of TNF-α, IL-6 or CRP reduction. This trial was registered at clinical trials.gov as NCT01116856. http://clinicaltrials.gov/.

Nutrition and physical activity programs for obesity treatment (PRONAF study). methodological approach of the project

Este trabajo aborda la metodología seguida para llevar a cabo el proyecto de investigación PRONAF (Clinical Trials Gov.: number NCT01116856.) Background: At present, scientific consensus exists on the multifactorial etiopatogenia of obesity. Both professionals and researchers agree that treatment must also have a multifactorial approach, including diet, physical activity, pharmacology and/or surgical treatment. These two last ones should be reserved for those cases of morbid obesities or in case of failure of the previous ones. The aim of the PRONAF study is to determine what type of exercise combined with caloric restriction is the most appropriate to be included in overweigth and obesity intervention programs, and the aim of this paper is to describe the design and the evaluation methods used to carry out the PRONAF study. Methods/design: One-hundred nineteen overweight (46 males) and 120 obese (61 males) subjects aged 18–50 years were randomly assigned to a strength training group, an endurance training group, a combined strength + endurance training group or a diet and physical activity recommendations group. The intervention period was 22 weeks (in all cases 3 times/wk of training for 22 weeks and 2 weeks for pre and post evaluation). All subjects followed a hypocaloric diet (25-30% less energy intake than the daily energy expenditure estimated by accelerometry). 29–34% of the total energy intake came from fat, 14–20% from protein, and 50–55% from carbohydrates. The mayor outcome variables assesed were, biochemical and inflamatory markers, body composition, energy balance, physical fitness, nutritional habits, genetic profile and quality of life. 180 (75.3%) subjects finished the study, with a dropout rate of 24.7%. Dropout reasons included: personal reasons 17 (28.8%), low adherence to exercise 3 (5.1%), low adherence to diet 6 (10.2%), job change 6 (10.2%), and lost interest 27 (45.8%). Discussion: Feasibility of the study has been proven, with a low dropout rate which corresponds to the estimated sample size. Transfer of knowledge is foreseen as a spin-off, in order that overweight and obese subjects can benefit from the results. The aim is to transfer it to sports centres. Effectiveness on individual health-related parameter in order to determine the most effective training programme will be analysed in forthcoming publications.

Effects of dietary restriction combined with different exercise programs or physical activity recommendations on blood lipids in overweight adults

Background and aim: Many exercise studies, although generally showing the beneficial effects of supervised aerobic, resistance or combined exercise on blood lipids, have sometimes reached equivocal conclusions. The aim of this study is to evaluate the impact of different programs that combined exercise and dietary restriction on blood lipids versus a clinical practice intervention for weight loss, in overweight adults. Methods: For this study 66 subjects participated in a supervised 22 weeks training program, composed of three sessions per week and they were randomized in three groups: strength training (S; n = 19), endurance training (E; n = 25), a combination of E and S (SE; n = 22). Eighteen subjects served as physical activity group (PA) that followed a clinical intervention consisted of physical activity recommendations. All groups followed the same dietary treatment, and blood samples were obtained for lipids measurements, at the beginning and end of the study. Results: Lipid profile improved in all groups. No significant differences for baseline and post-training values were observed between groups. In general, SE and PA decreased low-density lipoprotein cholesterol (LDL-C) values (p menor que 0.01). S decreased triglyceride levels (p menor que 0.01) and E, SE, and PA decreased total cholesterol levels (p menor que 0.05, p menor que 0.01 and p menor que 0.01, respectively). Conclusions: These results suggest that an intervention program of supervised exercise combined with diet restriction did not achieved further improvements in blood lipid profile than diet restriction and physical activity recommendations, in overweight adults. (Clinical Trials gov number: NCT01116856).

1RM prediction: a data mining case study

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.

Análisis de los efectos de un programa nutricional y de ejercicio físico sobre el perfil lipídico en personas con sobrepeso y obesidad

Introducción. Las enfermedades cardiovasculares (ECV) son la principal causa de muerte en nuestro país. Entre los factores independientes más importantes para el desarrollo de ECV se encuentran en primer lugar las alteraciones del perfil lipídico como el aumento del colesterol total (TC), las lipoproteínas de baja densidad (LDL) y los triglicéridos (TG) y/o la disminución de las lipoproteínas de alta densidad (HDL). Entre las diferentes formas de abordar el problema para prevenir y tratar estas patologías se encuentra la modificación de los hábitos de vida a través de un programa combinado de dieta y ejercicio. La evidencia confirma la efectividad de la primera variable, sin embargo, en el empleo del ejercicio se encuentran discrepancias acerca de cuál es el modo más eficaz para mejorar el perfil lipídico. Objetivo. Estudiar los cambios en las variables del perfil lipídico y los índices lipoproteicos comparando cuatro tipos de intervención que combinan dieta y diferentes modos de ejercicio, así como, analizar otras variables independientes (género, edad y genotipo ApoE) que pueden tener influencia sobre estos cambios. Diseño de la investigación. Los datos analizados en esta tesis forman parte del estudio “PROgramas de Nutrición y Actividad Física para el tratamiento de la obesidad” (PRONAF). Se trata de un estudio clínico desarrollado en España entre el 2008 y el 2011. La metodología del estudio nos permite comparar cuatro tipos de intervención para la pérdida de peso y evaluar su impacto sobre el perfil lipídico. El diseño fue experimental aleatorizado donde a todos los participantes se les sometió a un programa de dieta equilibrada hipocalórica junto a uno de los tres modos de ejercicio (grupo de entrenamiento de fuerza, grupo de entrenamiento de resistencia y grupo de entrenamiento combinado de los modos anteriores; los cuales fueron igualados en volumen e intensidad) o grupo de recomendaciones de actividad física. Las principales variables analizadas en los estudios que comprende esta tesis doctoral fueron: HDL, LDL, TG y TC, los índices derivados de estas y variables de la composición corporal y del entrenamiento. Conclusiones. Los cuatro tipos de intervención mostraron ser favorables para mejorar las variables del perfil lipídico y los índices lipoproteicos, sin diferencias significativas entre ellos. Tras la intervención, los varones mostraron una respuesta más favorable en los cambios del perfil lipídico. El genotipo ApoE2 obtuvo una reducción mayor en la concentración de TG y TC que el genotipo ApoE3 y ApoE4. Por último, los índices lipoproteicos mejoraron tras un programa de pérdida de peso, obteniéndose mayores cambios en el grupo de dieta más entrenamiento aeróbico para los índices ApoB/ApoA-1, TG/HDL y LDL/ApoB. ABSTRACT Introduction. The main cause of death in our country is cardiovascular disease (CVD). The most important independent factors for the development of CVD are the lipid profile alterations: increased total cholesterol (TC), low density lipoprotein (LDL) and triglycerides (TG) and/or decreased high-density lipoprotein (HDL). Among the different approaches to prevent and treat these diseases is modifying the lifestyle combining a diet and exercise program. The evidence confirms the effectiveness of the first variable, however, there is still controversy about the most effective mode of exercise combined with diet to achieve improvements. Objective. To study changes in lipoprotein profile comparing four types of intervention combining diet with different modes of exercise, and to analyze the independent variables (gender, age, and ApoE genotype) that can influence these changes. Research design. The data analized in this thesis are part of the study Nutrition and Physical Activity Programs for Obesity Treatments (the PRONAF study according to its Spanish initials). This is a clinical research carried out in Spain between 2008 and 2011. The aim of this study was to compare four types of intervention to weight loss with diet combining exercise. The design was experimental randomized where all participants were subjected to follow a hypocaloric balanced diet along one of the three modes of exercise (strength training group, resistance training group and combined training group of the above modes, which were matched by volume and intensity) or physical activity recommendations group. The main variables under investigation in this thesis were: HDL, LDL, TG and TC, the lipoprotein ratios, body composition and training variables. Main outcomes. The four types of interventions shown to be favorable to improve the lipid profile and lipoprotein level, with no significant differences between intervention groups. After the intervention, the men showed a more favorable respond in lipid profile changes. The genotype ApoE2 obtained more positive changes in the concentration of TG and TC than ApoE3 and ApoE4 genotype. Last, the lipoprotein ratios improve after weight loss treatment with diet combined different modes exercise. Our results reflected greater changes for E group in apoB/ApoA1, TG/HDL and LDL/ApoB compared within different intervention groups.