Greenness around Brazilian schools may improve students’ math performance but not science performance
Green spaces play a vital role in the social, economic, and physical well-being of people. To further research on this topic, in this paper, we estimated the association of greenness and academic performance at the school-level in Brazil. We analyzed this association using mixed-effects regression m...
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Veröffentlicht in: | Urban forestry & urban greening 2022-12, Vol.78, p.127768, Article 127768 |
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Zusammenfassung: | Green spaces play a vital role in the social, economic, and physical well-being of people. To further research on this topic, in this paper, we estimated the association of greenness and academic performance at the school-level in Brazil. We analyzed this association using mixed-effects regression models, adjusted for air pollution, SES, and spatiotemporal terms. We used the Normalized Difference Vegetation Index (NDVI) as the exposure variable. Data from the high school national exam in Brazil (at the school level, measured with a score varying from 0 to 1000) was used to represent the academic performance. The primary analysis results indicate that green areas surrounding schools are positively associated with school-level academic performance in math, with an estimated coefficient of 17.18 (95%CI: 10.46; 23.90). The results were statistically insignificant for science, with a coefficient of − 2.39 (95%CI: −7.49; 2.71). Our findings are relevant for policymakers and urban planners to improve the environment surrounding schools to promote public health by making schools healthier.
•This is the first study in Brazil linking green areas and school-level academic performance.•We accounted for a spatio-temporal analysis with a study period of 7 years.•Green areas are positively associated with school-level academic performance in math.•The results were statistically insignificant for science.•Our findings are relevant for policymakers and urban planners to improve the environment surrounding schools. |
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ISSN: | 1618-8667 1610-8167 |
DOI: | 10.1016/j.ufug.2022.127768 |