Browsing by Author "Silva C."

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    Determinant factors of excess of weight in school children: A multilevel studyFactores determinantes del exceso de peso en escolares: Un estudio multinivel
    (2007) Amigo C. H.; Bustos P.; Erazo M.; Cumsille P.; Silva C.; Amigo C. H.
    Background: Rates of obesity reach high levels in Chile, with geographic, social and school variations. Aim: To identify factors at two levels associated with excessive weight in school children: child-family characteristics and school-neighborhood. Material and methods: Using a cross-sectional and multi-step design, seven counties with the highest prevalence of obesity were identified, and schools were randomly chosen from within the 1st, 3rd and 5th quintiles of the school strata (same level of obesity prevalence). Within each school, twelve 2nd grade children were randomly chosen (n =42 schools and 504 students). Nutritional status, food intake, eating habits and physical activity were measured. Socio demographic, economic characteristics and nutritional status of the parents were assessed. Home size and facilities for children physical activities were assessed, as well as school infrastructure and management. Results: Most of the explained variance (97%) in the Body Mass Index (BMI) was due to individual-level factors: sedentary children behaviour (β coefficient 1.6, standard error (SE) 0.052), maternal obesity (β 0.94; SE 0.25), paternal obesity (β 0.83; SE 0.28) and hours watching television (β 0.789, SE 0.297). The same risk factors were predictive of obesity: child sedentary behaviours odds ratio (OR): 3.98, 95% confidence interval (CI): 2.44-6.48, maternal obesity (OR: 1.91, CI 1.21-3.02) and being woman (OR 1.75, CI: 1.01-2.76). Conclusions: BMI and obesity are associated with children behaviour or biological and cultural conditions of their families and not with school characteristics.
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    Reagent efficiency and analytical sensitivity optimization for a reliable SARS-CoV-2 pool-based testing strategy
    (2025) Miranda Marín, José Patricio; Osorio J.; Silva M.; Silva C.; Madrid V.; Camponovo R.; Henríquez Henríquez, Marcela
    Background: The SARS-CoV-2 pandemic caused millions of infections worldwide. Among the strategies for effective containment, frequent and massive testing was fundamental. Although sample pooling allows multiplying the installed analysis capacity, the definition of the number of samples to include in a pool is commonly guided more by economic parameters than analytical quality. Methods: We developed a mathematical model to determine the pooling conditions that maximize reagent efficiency and analytical sensitivity. We evaluated 30 samples individually and in 2-sample to 12-sample pools. Using Passing Bablok regressions, we estimated the shift of Ct values in the RT-qPCR reaction for each pool size. With this Ct shift, we estimated sensitivity in the context of the distribution of 1,030 individually evaluated positive samples. Findings: Our results showed that the most significant gain in efficiency occurred in the 4-sample pool, while at pools greater than 8-sample, there was no considerable reagent savings. Sensitivity significantly dropped to 87.18 %–92.52 % for a 4-sample pool and reached as low as 77.09 %–80.87 % in a 12-sample pooling. Conclusions: Our results suggest that a 4-sample pooling maximizes reagent efficiency and analytical sensitivity. These considerations are essential to increase testing capacity and efficiently detect and contain contagious.