Effects of Bifidobacterium longum 35624 in Children and Adolescents with Irritable Bowel Syndrome.

Irritable bowel syndrome (IBS) and vitamin D deficiency are common among children in Latin America. Previous studies show that Bifidobacterium longum35624TM improves IBS symptoms in adults. This real-world, single-arm, open-label study conducted in Chile investigated the effects of B. longum 35624 (1 × 109 colony-forming units, 12 weeks) on gastrointestinal symptoms (adapted IBS severity scoring system [IBS-SSS]; adapted Questionnaire on Pediatric Gastrointestinal Symptoms [QPGS], and Bristol Stool Form Scale) in 64 children and adolescents (8-18 years) and explored the relationship with baseline vitamin D status. Improvements in all IBS-SSS domains and composite score were observed at week 6 and 12 (p < 0.0007 versus baseline), with 98.3% of participants experiencing numerical improvements in ≥3 domains. Clinically meaningful improvement was seen in 96.6% of participants. The distribution of IBS-SSS severity categories shifted from moderate/severe at baseline to mild/remission (p < 0.0001). Improvements were not maintained during the two-week washout. Low baseline serum vitamin D levels did not correlate to IBS severity or probiotic response. QPGS significantly decreased from baseline to week 6 (p = 0.0005) and 12 (p = 0.02). B. longum 35624 may improve IBS symptoms in children and adolescents, even those with vitamin D deficiency. A confirmatory randomized controlled trial and further exploration of probiotic response and vitamin D status are needed.

[Dietary patterns and its relation with overweight and obesity in Chilean girls of medium-high socioeconomic level]. / Patrones alimentarios y su relación con sobrepeso y obesidad en niñas chilenas de nivel socioeconómico medio alto.

The aim of the present study was to identify dietary patterns in girls and to assess their association with obesity or overweight. A school-based sample of 108 girls between 8 and 11 years of medium-high socioeconomic level was selected in Santiago, Chile. The body mass index was calculated and a quantified food frequency and physical activity questionnaires (validated in the FAO/MINEDUC/INTA Project Nutritional Education in primary schools) were applied. Four distinct dietary factors or patterns were obtained explaining 54% of the total variation using factorial analysis. The first factor was characterized by an energy-dense diet (high consumption of fat foods, ice creams, chocolates, French fries, snacks). The second factor represented a healthy diet (dairy products, fruits and salads). The third factor represented intake of soft drinks (either with or without sugar). The fourth factor represented a diet rich in calories and sugars (bread, sausages, sweets). The association between the four dietary factors and overweight/obesity was assessed through logistic regression models. The first factor, energy-dense foods, was the only one significantly associated with the presence of obesity (OR = 1.86; 95% CI: 1.12 - 3.09). The results of this research about dietary patterns are consistent with studies carried out in other countries.

Patrones alimentarios y su relación con sobrepeso y obesidad en niñas chilenas de nivel socioeconómico medio alto / Dietary patterns and its relation with overweight and obesity in Chilean girls of medium-high socioeconomic level

El objetivo del presente estudio fue la identificación de patrones alimentarios y su asociación con la presencia de obesidad o sobrepeso en niñas. Se seleccionó una muestra de 108 niñas entre 8 y 11 años de nivel socioeconómico medio alto en un colegio privado de Santiago de Chile. A estas niñas se les determinó el índice de masa corporal y se les aplicó una encuesta de frecuencia de consumo de alimentos cuantificada y de actividad física (validada en el Proyecto FAO/MINEDUC/INTA "Educación en nutrición en la enseñanza básica"). Por medio del análisis factorial se obtuvieron cuatro factores que representan patrones alimentarios diferentes, y explican 54 por ciento de la variación total. El primer factor se caracterizó por una dieta basada en el consumo de alimentos de alta densidad energética (comida rápida, helados, chocolates, papas fritas, "snacks"); el segundo por una dieta saludable (lácteos, frutas y verduras); el tercero por la ingesta de bebidas gaseosas (con y sin azúcar) y el cuarto por una dieta rica en alimentos de alta densidad energética y azúcares (pan, cecinas, dulces). Los cuatro patrones alimentarios se relacionaron mediante una regresión logística con la presencia o no de sobrepeso y obesidad, obteniéndose que el primer patrón, alimentos de alta densidad energética, se asoció significativamente con la presencia de obesidad (OR= 1,86; 95por ciento IC: 1,12 - 3,09). Los resultados de este estudio son consistentes con los obtenidos en otros países

[Influence of data structure on the selection of statistic analysis methods]. / Influencia de la estructura de los datos en la selección de los métodos de análisis estadísticos.

In medical research, data is grouped either as per the design of the study or the selection of the sample. This structure must be taken into account in order to make correct estimates of the of the parameters and standard errors involved. This study is of the methodological type and is aimed at illustrating methods for estimating population-related methods and regression models with grouped data. For this purpose, nine variables from the First National Risk Factor and Preventive Measure Survey conducted in Cuba in 1995 are employed. The prevalence of high blood pressure is overestimated by 15% when the conventional estimators are used as compared with the weight-based and adjusted analysis. In the regression models for the body mass index based on the conventional procedures, sex, degree of schooling, degree of sedentariness, smoking habit, diastolic and systolic blood pressure were found to be significant. However, when the method taking into account the structure of conglomerates was employed, the degree of schooling and sedentariness ceased to be significant. When the random intercept model was adjusted, the 91.3% total variability was found to be explained by individual variables, the 8.7% variability being attributed to larger units. When estimating population-related parameters based on conglomerate-structure data involving inconsistent selection probabilities, the use of sample-related weights and analysis methods that take in the correlation among subjects (potential) for one same conglomerate. When adjusting regression models, it is not only important to efficiently estimate the coefficients, but rather the focus (aggregated or disaggregated) must be taken into account for modeling the problem under study.

Influencia de la estructura de los datos en la selección de los métodos de análisis estadísticos / The Influence of Data Structure for Selecting Statistical Analysis Methods

En las investigaciones médicas se encuentran datos agrupados ya sea por el diseño del estudio o la selección de la muestra. Esta estructura debe ser considerada para obtener estimaciones apropiadas de los parámetros y sus errores estándares. El presente trabajo es de naturaleza metodológica y se destina a ilustrar métodos para estimar parámetros poblacionales y modelos de regresión con datos agrupados. Para ello se utilizan nueve variables de la I Encuesta Nacional de Factores de Riesgo y Actividades Preventivas, realizada en Cuba en 1995. La prevalencia de hipertensión arterial se sobreestima en un 15 per cent cuando se utilizan los estimadores convencionales comparado con el análisis con pesos y el ajustado. En los modelos de regresión para el índice de masa corporal se encontró que con los procedimientos convencionales: sexo, nivel de educacional, condición de sedentarismo, tabaquismo, tensión diastólica y sistólica resultaron significativas. Sin embargo, con el método que considera la estructura de conglomerados dejaron de ser significativas el nivel educacional y la condición de sedentarismo. Al ajustar el modelo de intercepto aleatorios se encontró que el 91,3 per cent de la variabilidad total se explica por variables individuales y el 8,7 per cent se atribuye a unidades superiores. Al estimar parámetros poblacionales en datos con estructura de conglomerados y con desigualdad en las probabilidades de selección hay que considerar el uso de pesos muestrales y métodos de análisis que contemplen la correlación entre sujetos (potencial) de un mismo conglomerado. Al ajustar modelos de regresión no sólo importa obtener eficiencia en la estimación de los coeficientes sino que se debe considerar el enfoque (agregado o desagregado) para modelar el problema objeto de estudio (AU)

In medical research, data is grouped either as per the design of the study or the selection of the sample. This structure must be taken into account in order to make correct estimates of the of the parameters and standard errors involved.. This study is of the methodological type and is aimed at illustrating methods for estimating population-related methods and regression models with grouped data. For this purpose, nine variables from the First National Risk Factor and Preventive Measure Survey conducted in Cuba in 1995 are employed. The prevalence of high blood pressure is overestimated by 15% when the conventional estimators are used as compared with the weight-based and adjusted analysis. In the regression models for the body mass index based on the conventional procedures, sex, degree of schooling, degree of sedentariness, smoking habit, diastolic and systolic blood pressure were found to be significant. However, when the method taking into account the structure of conglomerates was employed, the degree of schooling and sedentariness ceased to be significant. When the random intercept model was adjusted, the 91.3% total variability was found to be explained by individual variables, the 8.7% variability being attributed to larger units. When estimating population-related parameters based on conglomerate-structure data involving inconsistent selection probabilities, the use of sample-related weights and analysis methods that take in the correlation among subjects (potential) for one same conglomerate. When adjusting regression models, it is not only important to efficiently estimate the coefficients, but rather the focus (aggregated or disaggregated) must be taken into account for modeling the problem under study (AU)