Relationships between Math Skills, Motor Skills, Physical Activity, and Obesity in Typically Developing Preschool Children.

There is evidence of a relationship between motor and cognitive development. The literature has shown that of all the motor skills, fine motor skills are those that contribute most to mathematical performance in preschool children. As this is a sensitive period in the development of motor skills, low levels of physical activity in this period can compromise their development and contribute to weight gain and obesity. The aim of this study was therefore to analyze the relationship between mathematical and motor skills, physical activity levels, and obesity. The sample consisted of 62 preschool children (32 males) with an average age of 4.63 ± 0.81. The Weschler preschool and primary scale of intelligence-revised arithmetic test was used to assess mathematical skills. The tests to assess fine motor skills were the "Adapted Threading Beads Test" and the "Adapted Visuomotor Integration Test". The movement assessment battery for children-2, band 1, "Aiming & Catching", and "Balance" tests were used to assess gross motor skills. Levels of physical activity were assessed using the "Preschool-age physical activity questionnaire" and obesity using the body mass index. The results indicated that only the fine motor skills of visuomotor integration were included in the multiple linear regression model (F < 0.001; r = 0.464; R2 = 0.215; p < 0.001), with the exclusion of gross motor skills, physical activity levels, and obesity levels. Thus, it was concluded that mathematical skills were only directly and significantly influenced by visuomotor integration. However, visuomotor integration was positively and significantly associated with gross motor skills (r = 0.269; p < 0.05) and not with levels of physical activity and obesity. Thus, gross motor skills could contribute to improving visuomotor integration directly and consequently mathematical skills indirectly. The results of this study suggest that the implementation of structured physical activity programs can contribute to mathematical performance.

Prevalencia y factores de riesgo asociados con la inactividad física en estudiantes universitarios de Ceará, Brasil / Prevalence and risk factors associated with physical inactivity amonguniversity students from Ceará, Brazil

OBJETIVO: Conocer los factores sociodemográficos y los vínculos con la universidad asociados con la inactividad física en estudiantes universitarios de Brasil. MATERIAL Y MÉTODOS: Estudio transversal y descriptivo. Muestra estratificada y proporcional compuesta por 324 estudiantes universitarios a los que se les aplicó el cuestionario "Indicadores de Saúde e Qualidade de Vida de Acadêmicos". RESULTADOS Y CONCLUSIONES: 42% de los estudiantes eran inactivos. Estudiantes con 5 años de asistencia universitaria, que asisten al turno de la tarde y de la noche son más propensos a estar inactivos. Las estudiantes que trabajan durante 40 horas o más, con más años en la universidad y que asisten al turno nocturno tienen más probabilidades de estar inactivas. Las alumnas tienen más probabilidades de ser inactivas que los alumnos. Es imperativo desarrollar políticas efectivas de promoción de la salud en el contexto universitario que proporcionen cambios que lleven a mayor calidad de vida

INTRODUCTION: Unhealthy lifestyles are observed in different populations, including university students. Sedentary behavior is seen as a habit that raises serious public health concerns. The university should present itself as an environment for experimentation, exploration and reflection that promotes the life, health and well-being of its students. OBJECTIVE: To know the sociodemographic factors and the links with the university associated with physical inactivity in university students in Brazil. MATERIAL AND METHODS: Cross-sectional and descriptive study. Stratified and proportional sample composed of 322 university students to whom the questionnaire "Indicadores de Saúde e Qualidade de Vida de Académicos" was applied. RESULTS: 42% of the students were inactive. Students with 5 years of college attendance, those who attend the afternoon and evening classes are more likely to be inactive. Female students who work 40 hours or more, have been in college for more years, and attend the night classes are more likely to be inactive. Female students are more likely to be inactive than male students. CONCLUSION: University students have a high prevalence of physical inactivity. The variables sex, hours of work and study and number of years in university are associated with physical inactivity. The university space does not present itself as a health promoter. It is imperative to develop effective health promotion policies in the university context with the intention of providing changes that lead to a higher quality of life

BMI and self-perceived body shape in Portuguese children

Objetivos: Este estudio examinó la relación entre la percepción subjetiva forma del cuerpo (silueta) y el índice de masa corporal (IMC) en niños portugueses, de acuerdo con el género, y se determinaron los valores del IMC para cada una de las siluetas. Método: Participó una muestra de 4211 niños, de entre 7 y 10 años de edad. La imagen corporal se evaluó utilizando las Siluetas de Imagen Corporal de Collins de la imagen corporal y se utilizaron las Curvas de Cole et al. para definir la obesidad. Resultados: La media del IMC fue mayor cuando el número de la silueta seleccionado aumentaba, excepto en las siluetas 2 y 7 para los niños y para la 7 en las niñas. La mayoría de las personas que seleccionaron la silueta número 5 o superior eran obesos/as. El ANOVA mostró diferencias significativas en el IMC según las figuras seleccionadas en ambos sexos (p < .001). El coeficiente de correlación entre las siluetas de la imagen corporal y el IMC fue de .54 (p < .001) para la muestra total; de .50 (p < .001) para los niños, y de .57 (p < .001) para las niñas. En los modelos de regresión, el porcentaje de varianza explicada del IMC por las imágenes seleccionadas fue del 25.6% en los varones y del 30.8% en las niñas. Conclusiones: El presente estudio sugiere que en la infancia (7-10 años), la conciencia de la forma del cuerpo no se halla estabilizada, y que las niñas son más precisas que los niños. La forma del cuerpo evaluado por la escala correlacionó moderadamente con el IMC, lo que sugiere que las Siluetas de Collins podrían ser una medida válida para evaluar la obesidad en niños portugueses (AU)

Objectives: This study examined the relationship between Portuguese children’s self-perceived body shape and body mass index (BMI) by gender, and BMI values were determined for each silhouette. Method: A sample of 4,211 children aged 7-10 was used. Their body image was assessed using Collins’s body image silhouettes, while cole et al.’s cutoffs were used to define obesity. Results: The higher the number of the selected silhouette, the higher the mean BMI, except in the case of silhouettes 2 and 7 for boys and 7 for girls. Most of the individuals who selected silhouette number 5 or higher were obese. For both sexes, the ANOVA showed significant differences in the BMI depending on the selected figures (p < .001). The correlation coefficient between the body image silhouettes and the BMI was .54 (p < .001) for the total sample, .50 (p < .001) for males and .57 (p < .001) for females. in the regression models, the percentage of variance in the BMI explained by the selected images was 25.6% in boys and 30.8% in girls. Conclusion: The study suggested that in childhood (7-10 years), no stable awareness of body shape has been developed, with girls being more accurate than boys. The body shape obtained with the scale was moderately correlated with the BMI, suggesting that Collins’ silhouettes could be a valid measure for assessing obesity in Portuguese children (AU)

Análise da evolução da carreira desportiva de nadadores do gênero feminino utilizando a modelação matemática / Mathematical modeling analysis of the performance evolution along the career-span of female swimmers

A performance desportiva em crianças e jovens deve sempre ter em consideração os processos de crescimento, maturação(1) e a influência na taxa de crescimento dos resultados desportivos. Nesse âmbito, com este estudo, procuramos estudar a taxa de crescimento dos resultados desportivos desde a formação até à etapa de alto nível desportivo em todas as provas do calendário olímpico, tentando estabelecer relações de associação com o crescimento, maturação e treino, para as nadadoras do sexo feminino. Foi utilizada uma amostra constituída pelas nadadoras presentes nos rankings portugueses de natação durante quatro anos (1998 a 2002), num total aproximado de 6.000 dados. A taxa de crescimento dos resultados desportivos foi calculada com base no seguinte algoritmo: (tempo inicial-tempo final)/tempo inicial*100. Pela análise dos resultados relativos às taxas de crescimento (TC) dos resultados, verificamos que se verifica: (i) tendência geral da TC dos resultados aumentar dos 11 para os 12 anos e dos 14 aos 15 anos em piscina de 25m; (ii) tendência similar à verificada em piscina de 25 para a piscina de 50m, mas com tendências de crescimento superiores, quer aos 10-11 anos e 14-15 anos. Com base na análise dos resultados, concluímos que a evolução dos resultados desportivos na natação está dependente, fortemente, para além de outros, do ritmo de crescimento, desenvolvimento e maturação das nadadoras.

Children and youth sports performance should always considerer the growth and maturation processes(1), and their influence in the growth rate of results along the sports career. In this extent, the purpose of this work was to study, on one hand, the growth rate of results in all swimming events of female Olympic calendar from the initial sports education till the stage of high level performance and, on the other hand, try to establish a relationship with the growth, maturation and training process of female swimmers. For this purpose a sample constituted by female swimmers in Portuguese swimming Rankings over the last four years (1998 to 2002) in an approximately amount of 6,000 data was used. The growth rate of results (GRR) was calculated based in the following algorithm: (initial time-final time)/initial time. The results pointed out, let us conclude that: (i) a general tendency of GRR. Increasing was verified from 11 to 12 years and from 14 to 16 years in 25 m swimming pool; (ii) a similar tendency was verified in 50 m swimming pool, but with superior GRR tendencies. Those results can be explained, more than by the training process, by the growth, development and maturation process.