Vigilancia de la obesidad infantil: cuando medir no es suficiente. De COSI a ALADINO.

Conferencia científica plenaria en el 23 Congres foro AdENyD (Asociación de Enfermería, Nutrición y Dietética)La obesidad infantil constituye un problema de salud pública de primera magnitud, ya que determina en muchos casos la obesidad en la edad adulta, asociada con algunas de las enfermedades de mayor mortalidad, morbilidad y discapacidad. La vigilancia de la obesidad infantil es una actividad de gran relevancia porque permite monitorizar la prevalencia de la misma, así como la deteción de cambios y de ese modo facilita las intervenciones en prevención. Sin embargo, la vigilancia de la obesidad infantil es compleja porque no existen unos criterios diagnósticos homogéneos para su diagnóstico. Hay disponibilidad de múltiples punto de corte de índice de masa corporal (IMC) que hacen estimaciones muy diferentes, y este hecho provoca confusión acerca de la verdadera prevalencia de la obesidad infantil. La Oficina para la Región Europea de la Organización Mundial de la Salud (OMS) puso en marcha la Childhood Obesity Surveillance Initiative (COSI) con el objetivo de armonizar una metodología y criterios para el diagnóstico y vigilancia de la obesidad infantil en Europa. España participó en esta iniciativa desde su comienzo a través del estudio ALADINO (Vigilancia del Crecimiento, Alimentación, Actividad Física, Desarrollo Infantil y Obesidad), y ha producido información en cuatro sucesivas recogidas de datos. Además del estudio ALADINO, existen otras iniciativas de vigilancia de la obesidad infantil en España. La más reciente es el Estudio PASOS (Physical Activity, sedentarism, lifestyles and obesity in Spanish youth), auspiciado por la Gasol Foundation. A pesar de todos estos recursos de vigilancia es necesario tratar de armonizar los criterios de diagnóstico para poder optimizar las actividades de prevención de la obesidad infantil.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Biología y control de "Aubeonymus mariaefranciscae" Roudier (Coleoptera, curculionidae), plaga de la remolacha azucarera

El coleóptero Aubeonymus mariaefranciscae Roudier,perteneciente a la famila de los curculiónidos, constituye una plaga principal de la remolacha azucarera en el sur de España. Su cilco en el campo está perfectamente acoplado al de la remolacha en la zona Sur. Los daños causado pueden ser muy graves, especialmente los ocasionados por los adultos en otoño, aunque tanto los adultos como las larvas producen también daños en primavera. Se ha puesto a punto una nueva dieta artificial para su cría en el laboratorio, con la que se desarrollan satisfactoriamente desde larvas neonatas hasta la emergencia del adulto, obteniéndose un porcentaje de supervivencia del 78%. Se han estudiado distintos aspectos de la biología reproductora, tales como la preferencia de lugares de oviposición, factores que influyen en la fecundidad y fertilidad y la estimación de la duración de los períodos de preoviposición y oviposición. Se ha determinado el efecto de la combinación de condiciones constantes de temperatura y fotoperiodo sobre el desarrollo larvario de A. Mariaefranciscae, encontrándose interacciones entre las dos variables que afectaron fuertemente al último estadio larvario. Se han ensayado tres reguladores del crecimiento de isnectos (RCIs) condistintos modos de acción sobre adultos de A. Mariaefranciscae en codiciones de laboratorio. El hexaflumurón, inhibidor de la síntesis de qutina, disminuyó la fertilidad de los huevos; el periproxifén, análogo de la hormona juvenil, no afectó a la reproducción ni la descendencia, y el halofenocida, análogo de la hormona de la muda, redujo la supervivencia de la progenie. Por último, distintos inhibidores de serín proteasas se ensayaron in vivo para estudiar su potencial como factores de resistencia frente a A. Mariaefranciscae. Las larvas alimentadas sobre dietas que contenían distintos inhibidores mostraron bajas tasas de supervivencia,retrasos en el tiempo de desarrollo y dificultades en el momento de la pupación y emergencia del adult

Influencia del estrés en el origen de lesiones en voleibol de competición

The objective was to evaluate the influence of perceived stress in injuries in competition volleyball players, as well as to evaluate a possible association with sex, age, competition level, kind of injury and duration (an issue increasingly studied in the sports world). 216 volleyball players of both sexes and an average age of 23 years (SD = 5.6%) and from different Spanish clubs participated in the study by answering a telematic questionnaire about perceived stress, injuries and other classification data. The 58.3% suffered an injury in the last season, and its average duration was 5.9 weeks. The average punctuation of stress was 45.3 points (43.3 in men and 46.7 in women, p = 0.011). In conclusion, higher levels of perceived stress mean higher risk of suffering an injury; and higher competition level means higher risk of injury.El objetivo fue evaluar la influencia del estrés percibido en las lesiones de los deportistas de voleibol de competición, así como evaluar una posible asociación con el sexo, edad, el nivel de competición, el tipo de lesión y su duración (un tema cada vez más estudiado en el mundo deportivo). 216 jugadores de voleibol de ambos sexos y de una media de 23 años (DT = 5,6%) y de diferentes clubes de España participaron en el estudio respondiendo un cuestionario telemático sobre estrés percibido, lesiones y otros datos de clasificación. El 58,3 % sufrió lesión en la última temporada, y su duración media fue de 5,9 semanas. La puntuación media de estrés fue de 45,3 puntos (43,3 en hombres y 46,7 en mujeres, p = 0,011). Como conclusión, a mayores niveles de estrés percibido, mayor riesgo de sufrir lesión y a mayor nivel de competición, mayor riesgo de lesión

Do Spanish IPO firms fit the continental European model for going public?

Este trabajo analiza los determinantes de la decisión de salir a bolsa en el mercado español de una muestra de empresas no financieras que llevaron a cabo una oferta pública inicial (OPI) de acciones en el período 1997-2013. Para ello, empleamos una serie de características relacionadas con las empresas y el entorno económico y los métodos de regresión logit para obtener el modelo que mejor se ajusta a nuestros datos, utilizando como muestra de control las empresas que podrían haber salido a bolsa en el mismo período, pero optaron por no hacerlo. En España, las empresas que salieron a bolsa se caracterizaron por ser relativamente más grandes y más arriesgadas que las que no lo hicieron. Además, sus OPI se produjeron después de un período de inversión y crecimiento, aunque no parece que tuvieran la intención de reequilibrar su estructura financiera o reducir sus costes financieros. Asimismo, nuestros resultados son robustos a diferentes análisis de sensibilidad. La evidencia obtenida sugiere que las compañías españolas que realizaron una OPI no se ajustan al modelo de Europa continental para salir a bolsa. Por lo tanto, parece que las diferencias entre el modelo europeo continental y el modelo anglosajón se están desvaneciendo. This paper analyses the determinants of the going public decision of the non-financial firms that were listed in the Spanish Continuous Market through an Initial Public Offering of shares (IPO) in the period 1997-2013. We employ series of characteristics related to the firms and the economic environment and logit regression methods in order to find the model that best fits the firms that went public, using the firms that could have gone public in the same period, but opted not to, as a control sample. In Spain, the firms that went public were characterized by being relatively larger and riskier than those that did not. In addition, their IPOs came after a period of investment and growth, although it does not appear that they intended to rebalance their financial structure or reduce their financial costs. Likewise, our results are robust across different sensitivity analyses. Our results suggest that Spanish IPO firms do not fit the Continental European model for going public. Therefore, it seems that differences between the Continental European and the Anglo-Saxon model are fading

Duración de sueño en personas mayores con síndrome metabólico

Sleep is a quality-of-life indicator. Sleep alterations have health consequences. The objective of the study was to analyze the sleep pattern in elderly people with metabolic syndrome. A cross-sectional study was carried out on a sample of 326 participants of node 01 of the PREDIMEDPLUS study (University of Malaga). The hours of sleep were quantified objectively with an accelerometer, and subjectively, with a self-reported questionnaire. The average duration of sleep (hours) measured with the accelerometer was higher in women (6.6±0.1) than in men (6.2±0.1); these data differ from self-reported data of 6.7h±0.1 hours in men and 7.3h±0.1 in women. 43% of men and 30% of women sleep less than 6 hours. A high percentage of participants have a poor sleep. In addition, future methodological investigations of sleep assessment are needed.El sueño es un indicador de la calidad de vida. Sus alteraciones pueden afectar la salud. El objetivo del estudio fue analizar el patrón de sueño en personas mayores con síndrome metabólico. Se realizó un estudio transversal en 326 participantes del nodo 01 del Estudio PREDIMEDPLUS (Universidad de Málaga). Las horas de sueño se cuantificaron de forma objetiva con un acelerómetro, y de manera subjetiva, a partir de un cuestionario. La duración media del sueño (horas) medida con el acelerómetro fue mayor en mujeres (6,6 ± 0,1) que en hombres (6,2 ± 0,1); estos datos difieren de los auto-declarados de 6,7 ± 0,1 horas en hombres y 7,3 ± 0,1 en mujeres. Un 43 % de hombres y un 30 % de mujeres duermen menos de 6 horas. Un alto porcentaje de los participantes tienen un sueño deficiente. Además, se necesitan futuras investigaciones metodológicas de la evaluación del sueño

Differences in the prevalence of diagnosis of overweight-obesity in Spanish children according to the diagnostic criteria set used

Objective: To examine relevant differences in the prevalence of overweight and obesity in children aged 2-15 years according to different sets of criteria (Orbegozo Foundation, International Obesity Task Force and World Health Organization), and how their use affects the trends in obesity recorded for both sexes between 1995 and 2011 in Spain. Method: Cross-sectional study, a population between 2 and 15 years. Three diagnosis criteria of overweight and obesity were be used. Results: The boys according to the three criteria, showed higher values of overweight and obesity compared to the girls. The lowest levels of overweight and obesity were observed using the Orbegozo tables. Discussion: The prevalence of overweight and obesity varies significantly according to the criteria used to define overweight and obesity. The percentiles of the Foundation Orbegozo gave the lowest estimates and the standards of growth of the World Health Organization were higher

Distance learning ects and flipped classroom in the anatomy learning: comparative study of the use of augmented reality, video and notes

Background: The establishment of the ECTS (European Credit Transfer System) is one of the pillars of the European Space of Higher Education. This way of accounting for the time spent in training has two essential parts, classroom teaching (work with the professor) and distance learning (work without the professor, whether in an individual or collective way). Much has been published on the distance learning part, but less on the classroom teaching section. In this work, the authors investigate didactic strategies and associated aids for distance learning work in a concept based on flipped classroom where transmitting information is carried out with aids that the professor prepares, so that the student works in an independent way before the classes, thus being able to dedicate the classroom teaching time to more complex learning and being able to count on the professor’s help. Methods: Three teaching aids applied to the study of anatomy have been compared: Notes with images, videos, and augmented reality. Four dimensions have been compared: the time spent, the acquired learnings, the metacognitive perception, and the prospects of the use of augmented reality for study. Results: The results show the effectiveness, in all aspects, of augmented reality when compared with the rest of aids. The questionnaire assessed the acquired knowledge through a course exam, where 5.60 points were obtained for the notes group, 6.54 for the video group, and 7.19 for the augmented reality group. That is 0.94 more points for the video group compared with the notes and 1.59 more points for the augmented reality group compared with the notes group. Conclusions: This research demonstrates that, although technology has not been sufficiently developed for education, it is expected that it can be improved in both the autonomous work of the student and the academic training of health science students and that we can teach how to learn. Moreover, one can see how the grades of the students who studied with augmented reality are more grouped and that there is less dispersion in the marks compared with other materials.Financial support of the Foundation “Prevere Bernat Beny”.Pedagogí

Survival analysis of author keywords: An application to the library and information sciences area

"This is the peer reviewed version of the following article: Peset, F, F Garzón-Farinós, LM González, X García-Massó, A Ferrer-Sapena, JL Toca-Herrera, and EA Sánchez-Pérez. 2019. "Survival Analysis of Author Keywords: An Application to the Library and Information Sciences Area." Journal of the Association for Information Science and Technology 71 (4). Wiley: 462-73. doi:10.1002/asi.24248, which has been published in final form at https://doi.org/10.1002/asi.24248. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] Our purpose is to adapt a statistical method for the analysis of discrete numerical series to the keywords appearing in scientific articles of a given area. As an example, we apply our methodological approach to the study of the keywords in the Library and Information Sciences (LIS) area. Our objective is to detect the new author keywords that appear in a fixed knowledge area in the period of 1 year in order to quantify the probabilities of survival for 10 years as a function of the impact of the journals where they appeared. Many of the new keywords appearing in the LIS field are ephemeral. Actually, more than half are never used again. In general, the terms most commonly used in the LIS area come from other areas. The average survival time of these keywords is approximately 3 years, being slightly higher in the case of words that were published in journals classified in the second quartile of the area. We believe that measuring the appearance and disappearance of terms will allow understanding some relevant aspects of the evolution of a discipline, providing in this way a new bibliometric approach.Peset Mancebo, MF.; Garzón Farinós, MF.; Gonzalez, L.; García-Massó, X.; Ferrer Sapena, A.; Toca-Herrera, JL.; Sánchez Pérez, EA. (2020). Survival analysis of author keywords: An application to the library and information sciences area. Journal of the Association for Information Science and Technology (Online). 71(4):462-473. https://doi.org/10.1002/asi.24248S462473714Aharony, N. (2011). Library and Information Science research areas: A content analysis of articles from the top 10 journals 2007–8. Journal of Librarianship and Information Science, 44(1), 27-35. doi:10.1177/0961000611424819Aizawa, A., & Kageura, K. (2003). Calculating association between technical terms based on co-occurrences in keyword lists of academic papers. Systems and Computers in Japan, 34(3), 85-95. doi:10.1002/scj.1197Athukorala, K., Hoggan, E., Lehtiö, A., Ruotsalo, T., & Jacucci, G. (2013). Information-seeking behaviors of computer scientists: Challenges for electronic literature search tools. Proceedings of the American Society for Information Science and Technology, 50(1), 1-11. doi:10.1002/meet.14505001041The View from Here. (2007). Scholarship in the Digital Age. doi:10.7551/mitpress/7434.003.0012Box-Steffensmeier, J. M., Cunha, R. C., Varbanov, R. A., Hoh, Y. S., Knisley, M. L., & Holmes, M. A. (2015). Survival Analysis of Faculty Retention and Promotion in the Social Sciences by Gender. PLOS ONE, 10(11), e0143093. doi:10.1371/journal.pone.0143093Brophy, J., & Bawden, D. (2005). Is Google enough? Comparison of an internet search engine with academic library resources. Aslib Proceedings, 57(6), 498-512. doi:10.1108/00012530510634235Buckland, M. K. (2012). Obsolescence in subject description. Journal of Documentation, 68(2), 154-161. doi:10.1108/00220411211209168Chang, Y.-W., Huang, M.-H., & Lin, C.-W. (2015). Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses. Scientometrics, 105(3), 2071-2087. doi:10.1007/s11192-015-1762-8Chen, G., & Xiao, L. (2016). Selecting publication keywords for domain analysis in bibliometrics: A comparison of three methods. Journal of Informetrics, 10(1), 212-223. doi:10.1016/j.joi.2016.01.006Cheng, F.-F., Huang, Y.-W., Yu, H.-C., & Wu, C.-S. (2018). Mapping knowledge structure by keyword co-occurrence and social network analysis. Library Hi Tech, 36(4), 636-650. doi:10.1108/lht-01-2018-0004Colley, A., & Maltby, J. (2008). Impact of the Internet on our lives: Male and female personal perspectives. Computers in Human Behavior, 24(5), 2005-2013. doi:10.1016/j.chb.2007.09.002Dehdarirad, T., Villarroya, A., & Barrios, M. (2014). Research trends in gender differences in higher education and science: a co-word analysis. Scientometrics, 101(1), 273-290. doi:10.1007/s11192-014-1327-2Ding, Y., Chowdhury, G. G., & Foo, S. (2001). Bibliometric cartography of information retrieval research by using co-word analysis. Information Processing & Management, 37(6), 817-842. doi:10.1016/s0306-4573(00)00051-0Dotsika, F., & Watkins, A. (2017). Identifying potentially disruptive trends by means of keyword network analysis. Technological Forecasting and Social Change, 119, 114-127. doi:10.1016/j.techfore.2017.03.020Figuerola, C. G., García Marco, F. J., & Pinto, M. (2017). Mapping the evolution of library and information science (1978–2014) using topic modeling on LISA. Scientometrics, 112(3), 1507-1535. doi:10.1007/s11192-017-2432-9Gil-Leiva, I., & Alonso-Arroyo, A. (2007). Keywords given by authors of scientific articles in database descriptors. Journal of the American Society for Information Science and Technology, 58(8), 1175-1187. doi:10.1002/asi.20595Halevi, G., & Moed, H. F. (2013). The thematic and conceptual flow of disciplinary research: A citation context analysis of thejournal of informetrics, 2007. Journal of the American Society for Information Science and Technology, 64(9), 1903-1913. doi:10.1002/asi.22897Michael Hall, C. (2011). Publish and perish? Bibliometric analysis, journal ranking and the assessment of research quality in tourism. Tourism Management, 32(1), 16-27. doi:10.1016/j.tourman.2010.07.001Han H. Gui J. &Xu S.(2014).Revealing research themes and their evolutionary trends using bibliometric data based on strategic diagrams (pp. 653–659).https://doi.org/10.1109/ISCC-C.2013.121Hjørland, B. (2000). Library and information science: practice, theory, and philosophical basis. Information Processing & Management, 36(3), 501-531. doi:10.1016/s0306-4573(99)00038-2Hjørland B. (2017).Library and information science (LIS). In Encyclopedia of Knowledge Organization. Retrieved fromhttp://www.isko.org/cyclo/lis.Hjørland, B., & Albrechtsen, H. (1995). Toward a new horizon in information science: Domain-analysis. Journal of the American Society for Information Science, 46(6), 400-425. doi:10.1002/(sici)1097-4571(199507)46:63.0.co;2-yHu, C.-P., Hu, J.-M., Deng, S.-L., & Liu, Y. (2013). A co-word analysis of library and information science in China. Scientometrics, 97(2), 369-382. doi:10.1007/s11192-013-1076-7Kevork, E. K., & Vrechopoulos, A. P. (2009). CRM literature: conceptual and functional insights by keyword analysis. Marketing Intelligence & Planning, 27(1), 48-85. doi:10.1108/02634500910928362Khan, G. F., & Wood, J. (2015). Information technology management domain: emerging themes and keyword analysis. Scientometrics, 105(2), 959-972. doi:10.1007/s11192-015-1712-5Lee, S. (2016). A Study on Research Trends in Public Library Research in Korea Using Keyword Networks. Libri, 66(4). doi:10.1515/libri-2016-0052Leung, X. Y., Sun, J., & Bai, B. (2017). Bibliometrics of social media research: A co-citation and co-word analysis. International Journal of Hospitality Management, 66, 35-45. doi:10.1016/j.ijhm.2017.06.012Li, M. (2018). Classifying and ranking topic terms based on a novel approach: role differentiation of author keywords. Scientometrics, 116(1), 77-100. doi:10.1007/s11192-018-2741-7Liu, J., Tian, J., Kong, X., Lee, I., & Xia, F. (2018). Two decades of information systems: a bibliometric review. Scientometrics, 118(2), 617-643. doi:10.1007/s11192-018-2974-5McClure, C. R., & Bishop, A. (1989). The Status of Research in Library/Information Science: Guarded Optimism. College & Research Libraries, 50(2), 127-143. doi:10.5860/crl_50_02_127Mela, C. F., Roos, J., & Deng, Y. (2013). Invited Paper—A Keyword History of Marketing Science. Marketing Science, 32(1), 8-18. doi:10.1287/mksc.1120.0764Milojević, S., Sugimoto, C. R., Yan, E., & Ding, Y. (2011). The cognitive structure of Library and Information Science: Analysis of article title words. Journal of the American Society for Information Science and Technology, 62(10), 1933-1953. doi:10.1002/asi.21602Niu, X., & Hemminger, B. M. (2011). A study of factors that affect the information-seeking behavior of academic scientists. Journal of the American Society for Information Science and Technology, 63(2), 336-353. doi:10.1002/asi.21669Nosek, B. A., Spies, J. R., & Motyl, M. (2012). Scientific Utopia. Perspectives on Psychological Science, 7(6), 615-631. doi:10.1177/1745691612459058O’Mara-Eves, A., Thomas, J., McNaught, J., Miwa, M., & Ananiadou, S. (2015). Using text mining for study identification in systematic reviews: a systematic review of current approaches. Systematic Reviews, 4(1). doi:10.1186/2046-4053-4-5Onyancha, O. B. (2018). Forty-Five Years of LIS Research Evolution, 1971–2015: An Informetrics Study of the Author-Supplied Keywords. Publishing Research Quarterly, 34(3), 456-470. doi:10.1007/s12109-018-9590-3Peset F. Garzón‐Farinos F. González L. García‐Massó X. Ferrer‐Sapena A. Toca‐Herrera J. &Sánchez‐Perez E. (2018f). Supplementary material S6. Survival analysis (Porter Stemmer method). Retrieved fromhttps://figshare.com/s/ec0e34e0aebf5df48a7bRadhakrishnan, S., Erbis, S., Isaacs, J. A., & Kamarthi, S. (2017). Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature. PLOS ONE, 12(3), e0172778. doi:10.1371/journal.pone.0172778Rayward, W. B. (2005). The historical development of information infrastructures and the dissemination of knowledge: A personal reflection. Bulletin of the American Society for Information Science and Technology, 31(4), 19-22. doi:10.1002/bult.1720310407Runkler T.A.&Bezdek J.C.(2000).Automatic keyword extraction with relational clustering and Levenshtein distances. Ninth IEEE International Conference on Fuzzy Systems. FUZZ‐ IEEE 2000 (Cat. No.00CH37063). Vol.2 (pp.636–640).https://doi.org/10.1109/FUZZY.2000.839067Santos, J. B., & Irizo, F. J. O. (2005). Modelling citation age data with right censoring. Scientometrics, 62(3), 329-342. doi:10.1007/s11192-005-0025-5Scimago Journal & Country Rank. (n.d.). Retrieved fromhttp://www.scimagojr.com/Singer, J. D., & Willett, J. B. (1993). It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events. Journal of Educational Statistics, 18(2), 155-195. doi:10.3102/10769986018002155Su, H.-N., & Lee, P.-C. (2010). Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight. Scientometrics, 85(1), 65-79. doi:10.1007/s11192-010-0259-8SUN, J. (1997). REGRESSION ANALYSIS OF INTERVAL-CENSORED FAILURE TIME DATA. Statistics in Medicine, 16(5), 497-504. doi:10.1002/(sici)1097-0258(19970315)16:53.0.co;2-jTang, R. (2005). Evolution of the interdisciplinary characteristics of information and library science. Proceedings of the American Society for Information Science and Technology, 41(1), 54-63. doi:10.1002/meet.1450410107Tuomaala, O., Järvelin, K., & Vakkari, P. (2014). Evolution of library and information science, 1965-2005: Content analysis of journal articles. Journal of the Association for Information Science and Technology, 65(7), 1446-1462. doi:10.1002/asi.23034Uddin, S., & Khan, A. (2016). The impact of author-selected keywords on citation counts. Journal of Informetrics, 10(4), 1166-1177. doi:10.1016/j.joi.2016.10.004Vakkari, P. (1994). Library and Information Science: Its Content and Scope. Advances in Librarianship, 1-55. doi:10.1108/s0065-2830(1994)0000018003Walters, W. H., & Wilder, E. I. (2015). Disciplinary, national, and departmental contributions to the literature of library and information science, 2007-2012. Journal of the Association for Information Science and Technology, 67(6), 1487-1506. doi:10.1002/asi.23448Wang, M., & Chai, L. (2018). Three new bibliometric indicators/approaches derived from keyword analysis. Scientometrics, 116(2), 721-750. doi:10.1007/s11192-018-2768-9Wang, Z.-Y., Li, G., Li, C.-Y., & Li, A. (2011). Research on the semantic-based co-word analysis. Scientometrics, 90(3), 855-875. doi:10.1007/s11192-011-0563-yXu, J., Bu, Y., Ding, Y., Yang, S., Zhang, H., Yu, C., & Sun, L. (2018). Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention. Scientometrics, 117(2), 973-995. doi:10.1007/s11192-018-2897-1Yang, S., Han, R., Wolfram, D., & Zhao, Y. (2016). Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis. Journal of Informetrics, 10(1), 132-150. doi:10.1016/j.joi.2015.12.003Zhang, J., Yu, Q., Zheng, F., Long, C., Lu, Z., & Duan, Z. (2015). Comparing keywords plus of WOS and author keywords: A case study of patient adherence research. Journal of the Association for Information Science and Technology, 67(4), 967-972. doi:10.1002/asi.2343

Género e influencia de factores socioeconómicos sobre la obesidad en España

Análisis realizado a partir de la recientemente publicada Encuesta Nacional de Salud 2017. Los datos son originales e inéditos.Introducción. La obesidad es un problema de salud pública. Algunos determinantes socioeconómicos pueden influir sobre la obesidad. Es necesario evaluar si afectan igualmente a hombres y mujeres. Metodología. Encuesta Nacional de Salud 2017 (10.031 hombres y 11.393 mujeres con 18 o más años). Variables dependientes: sobrepeso (IMC>=25 Kg/m2); obesidad (IMC>=30 Kg/m2). Variables independientes: nivel de educación, clase social e ingresos mensuales por persona y hogar. Se calcularon prevalencias de sobrepeso y obesidad por sexo y grupos de edad. Se evaluó el efecto de las variables independientes mediante modelos de regresión logística. Se evaluó la asociación entre sobrepeso, obesidad, y salud autopercibida mediante modelos de regresión logística. Todos los análisis se realizaron por separado para hombres y mujeres. Resultados. Prevalencia de sobrepeso: 56,5% (48,7 % en mujeres; 65,2 % en hombres). Prevalencia de obesidad: 18,2 % (17,5 % en mujeres; 18,9 % en hombres). En los hombres no se encontró asociación entre clase social y sobrepeso u obesidad; los ingresos mensuales menores de 600 € se asociaron con obesidad. En las mujeres, las asociaciones entre las tres variables socioeconómicas y sobrepeso y obesidad resultaron estadísticamente significativas. La OR de salud autopercibida mala era 1,42 entre personas con sobrepeso (1,16 en hombres; 1,64 en mujeres), y 1,69 entre personas con obesidad (1,49 en hombres; 1,91 en mujeres). Todas las OR resultaron estadísticamente significativas. Conclusiones. La influencia de factores socioeconómicos sobre sobrepeso y obesidad no es igual en hombres y mujeres. Es necesario tener en cuenta el género a la hora de planificar actuaciones contra la obesidad.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis

[EN] The spread of the SARS-CoV-2 virus has transformed many aspects of people's daily life, including sports. Social networks have been flooded on these issues. The present study aims to analyze the tweets produced relating to sports and COVID-19. From the end of January to the beginning of May 2020, over 4,000,000 tweets on this subject were downloaded through the Twitter search API. Once the duplicates, replicas, and retweets were removed, 119,253 original tweets were analyzed. A quantitative-qualitative content analysis was used to study the selected tweets. Posts dynamics regarding sport and exercise evolved according to the COVID-19 pandemic and subsequent lockdown, shifting from considering sport as a healthy bastion to an activity exposed to disease like any other. Most media professional sporting events received great attention on Twitter, while grassroots and women's sport were relegated to a residual role. The analysis of the 30 topics identified focused on the social, sporting, economic and health impact of the pandemic on the sport. Sporting cancellations, leisure time and socialization disruptions, club bankruptcies, sports training and athletes' uncertain career development were the main concerns. Although general health measures appeared in the tweets analyzed, those addressed to sports practice were relatively scarce. Finally, this study shows the importance of Twitter as a means of conveying social attitudes towards sports and COVID-19 and its potential to generate alternative responses in future stages of the pandemic.González, L.; Devis-Devis, J.; Pellicer-Chenoll, M.; Pans, M.; Pardo-Ibáñez, A.; García-Massó, X.; Peset Mancebo, MF.... (2021). The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis. International Journal of Environmental research and Public Health (Online). 18(9):1-20. https://doi.org/10.3390/ijerph18094554S12018