Height for age z score and cognitive function are associated with Academic performance among school children aged 8–11 years old. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Haile, Demewoz; Nigatu, Dabere; Gashaw, Ketema; Demelash, Habtamu
• Is Part Of: Archives of public health. Volume 74:Issue 1(2016)
• Page Start: 1
• Page End: 7
• Publication Date: 2016-12
• Subjects: Public health -- Periodicals; Public health -- Belgium -- Periodicals; 362.1
• DOI: 10.1186/s13690-016-0129-9
• Languages: English
• ISSNs: 2049-3258

Abstract

Abstract Background Academic achievement of school age children can be affected by several factors such as nutritional status, demographics, and socioeconomic factors. Though evidence about the magnitude of malnutrition is well established in Ethiopia, there is a paucity of evidence about the association of nutritional status with academic performance among the nation's school age children. Hence, this study aimed to determine how nutritional status and cognitive function are associated with academic performance of school children in Goba town, South East Ethiopia. Methods An institution based cross-sectional study was conducted among 131 school age students from primary schools in Goba town enrolled during the 2013/2014 academic year. The nutritional status of students was assessed by anthropometric measurement, while the cognitive assessment was measured by the Kaufman Assessment Battery for Children (KABC-II) and Ravens colored progressive matrices (Raven's CPM) tests. The academic performance of the school children was measured by collecting the preceding semester academic result from the school record. Descriptive statistics, bivariate and multivariable linear regression were used in the statistical analysis. Results This study found a statistically significant positive association between all cognitive test scores and average academic performance except for number recall (p = 0.12) and hand movements (p = 0.08). The correlation between all cognitive test scores and mathematics score was found positive and statistically significant (p < 0.05). In the multivariable linear regression model, better wealth index was significantly associated with higher mathematics score (ß = 0.63; 95 % CI: 0.12–0.74). Similarly a unit change in height for age z score resulted in 2.11 unit change in mathematics score (ß = 2.11; 95 % CI: 0.002–4.21). A single unit change of wealth index resulted 0.53 unit changes in average score of all academic subjects among school age children (ß = 0.53; 95 % CI: 0.11–0.95). A single unit change of age resulted 3.23 unit change in average score of all academic subjects among school age children (ß = 3.23; 95 % CI: 1.20–5.27). Conclusion Nutritional status (height for age Z score) and wealth could be modifiable factors to improve academic performance of school age children. Moreover, interventions to improve nutrition for mothers and children may be an important contributor to academic success and national economic growth in Ethiopia. Further study with strong design and large sample size is needed.