Nutrition (Burbank, Los Angeles County, Calif.) · 2018
Impact of anthropometric nutritional parameters on the university selection test in Chile: A multifactorial approach.
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Ivanovic Daniza M, Valenzuela Rodrigo B, Almagià Atilio F, Barrera Cynthia R, Arancibia Violeta C, Larraín Cristián G, Silva Claudio F A, Billeke Pablo B, Zamorano Francisco M, Villagrán Francisca S, Orellana Yasna Z, Martínez Víctor C
Аннотация
OBJECTIVES: Scholastic achievement (SA) is a multifactorial problem that depends on factors related to the child, the child's family, and the educational system. The aim of this study was to quantify the relative impact of significant variables at the beginning of high school during 2010 (first grade of high school [1 HSG]) on 2013 university selection test (Prueba de Seleccion Universitaria [PSU]) outcomes, both in language scholastic achievement (LSA) and mathematics scholastic achievement (MSA), when students graduated from high school (4 HSG). This was done at the time of university admission with a multicausal approach. The purpose was to confirm the hypothesis that the level of educational establishment SA, intellectual ability, sex, parental schooling levels, and head circumference for age Z-score at the onset of high school are the most relevant parameters associated with 2013 PSU outcomes, both in LSA and MSA.
METHODS: A representative, proportional, and stratified sample of 671 children of both sexes who enrolled in 1 HSG in 2010 (mean age: 14.8 ± 0.6 y) participated in the study. Nutritional, intellectual, brain developmental, cardiovascular risk, socio-to-economic, demographic, and educational variables were quantitated. SA was assessed at 4 HSG with the 2013 PSU tests. Data were analyzed with SAS software.
RESULTS: Educational establishment SA, intellectual ability, maternal schooling, and age Z-score were the most relevant parameters to explain LSA (R2 = 0.493; P < 0.0001) and MSA variance in addition to sex (male), but only in MSA (R2 = 0.600; P < 0.0001).
CONCLUSIONS: These findings confirm the hypothesis and can be useful to support nutritional, health, and educational planning.
METHODS: A representative, proportional, and stratified sample of 671 children of both sexes who enrolled in 1 HSG in 2010 (mean age: 14.8 ± 0.6 y) participated in the study. Nutritional, intellectual, brain developmental, cardiovascular risk, socio-to-economic, demographic, and educational variables were quantitated. SA was assessed at 4 HSG with the 2013 PSU tests. Data were analyzed with SAS software.
RESULTS: Educational establishment SA, intellectual ability, maternal schooling, and age Z-score were the most relevant parameters to explain LSA (R2 = 0.493; P < 0.0001) and MSA variance in addition to sex (male), but only in MSA (R2 = 0.600; P < 0.0001).
CONCLUSIONS: These findings confirm the hypothesis and can be useful to support nutritional, health, and educational planning.