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[EN] Obesity and overweight represent a public health problem. Its high prevalence and the negative biopsychosocial consequences of overweight in adolescents highlight the need for effective treatment. Intervention through the promotion of healthy habits is a strategy to improve this condition. The aim of this study was to develop a program of healthy habits for adolescents and their parents, looking for changes in the body mass index of adolescents before and after applying the program. Material and Method: A longitudinal, prospective, quasi-experimental and correlational study with non-probabilistic sampling was carried out through a nutritional, psychological, physical and family program involving adolescents between 12 and 15 years of age as well as their parents. Results: A difference was observed in the body mass index of adolescents before and after attending the program. Conclusions: This study showed that taking into account the global aspects of nutrition, psychological, physical and family activity, is an effective solution to this important health problem., [ES] La obesidad y el sobrepeso representan un problema de salud pública. Su alta prevalencia y las consecuencias biopsicosociales negativas del exceso de peso en adolescentes resaltan la necesidad de un tratamiento efectivo. La intervención mediante la promoción de hábitos saludables es una estrategia para mejorar esta condición. El objetivo de este estudio fue desarrollar un programa de hábitos saludables para adolescentes y sus padres, buscando cambios en el índice de masa corporal de los adolescentes antes y después de aplicar el programa.Material y Método: Se realizó un estudio longitudinal, prospectivo, cuasi-experimental y correlacional, con muestreo no probabilístico, mediante un programa nutriológico, psicológico, físico y familiar en el que participaron adolescentes entre 12 y 15 años de edad así como a sus padres.Resultados: Se observó una diferencia en el índice de masa corporal de los adolescentes antes y después de la asistencia al programa.Conclusiones: En este estudio se pudo demostrar que tomar en cuenta los aspectos globales de nutrición, psicológicos, actividad física y familiar, es una solución efectiva para este importante problema de salud.

Online social network (OSN) queries require retrievals of multiple small records generated by different users in the network, and the set of records to be retrieved is time dependent. Current implementation of hash-based partitioning results in accesses at a large number of servers, which significantly degrades response time. Partitioning the OSN friendship graph is difficult as its power-law degree distribution leads to many cross-partition edges. Naive replication requires extra storage that is orders of magnitude larger. In our previous work (2011), we proposed to partition not only the spatial network of social relations, but also in the time dimension so that users who have communicated in a given period are grouped together. We built an activity prediction graph (APG) to keep in one partition newly created data that are highly likely to be accessed together. In this paper, we analyze the distribution of the Facebook wall posts in the New Orleans network. We further emphasize that the objective of partitioning is to keep the two-hop neighborhood of a user in one partition, instead of the one-hop network usually considered. Two-hop neighborhoods are the basic units of retrieval in OSN and can be much larger than one-hop networks. We use a static partitioning method based on KMETIS, and a dynamic local partitioning method that maintains evenness and requires only a small amount of data movement across partitions. For evaluation, the partitioning results are tested with emulation of Facebook page downloads. We show that partitioning on twohop networks yields at lest 19% more local queries than its one-hop counterpart. The static algorithm achieves 5.6 times better data locality than hash-based partitioning and the dynamic algorithm achieves 6.4 times better locality while keeping the number of movements small. Almost all queries are kept in at most 3 partitions for both algorithms.