Abstract
AbstractEducation is a human right and a driver of development, but, is still not accessible for a vast number of adolescents and school-age-youths. Out-of-school adolescents and youth rates (SDG 4.3.1) in lower and middle-income countries have been at a virtual halt for almost a decade. Thus, there is an increasing need to understand geographic variation on accessibility and school attendance to aid in reducing inequalities in education. Here, the aim was to estimate physical accessibility and secondary school non-attendance amongst adolescents and school-age youths in Tanzania, Cambodia, and the Dominican Republic. Community cluster survey data were triangulated with the spatial location of secondary schools, non-proprietary geospatial data and fine-scale population maps to estimate accessibility to all levels of secondary school education and the number of out-of-school. School attendance rates for the three countries were derived from nationally representative household survey data, and a Bayesian model-based geostatistical framework was used to estimate school attendance at high resolution. Results show a sub-national variation in accessibility and secondary school attendance rates for the three countries considered. Attendance was associated with distance to the nearest school (R2 > 70%). These findings suggest increasing the number of secondary schools could reduce the long-distance commuted to school in low-income and middle-income countries. Future work could extend these findings to fine-scale optimisation models for school location, intervention planning, and understanding barriers associated with secondary school non-attendance at the household level.
Publisher
Springer Science and Business Media LLC
Subject
General Economics, Econometrics and Finance,General Psychology,General Social Sciences,General Arts and Humanities,General Business, Management and Accounting
Reference62 articles.
1. Anderson JE, Cleland JG (1984) The world fertility survey and contraceptive prevalence surveys: a comparison of substantive results. Stud Fam Plann 15:1–13
2. Arino O, Gross D, Ranera F, Bourg L, Leroy M, Bicheron P, Latham J, Di Gregorio A, Brockman C, Witt R et al. (2007) GlobCover: ESA service for global land cover from MERIS. In: Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS) 2007. IEEE International, Barcelona
3. Ayad M, Barrere B, Otto J (1997) Demographic and socioeconomic characteristics of households. DHS comparative studies no. 26. Macro International, Calverton
4. Banerjee S, Carling PB, Gelfand AE (2004) Hierarchical modeling and analysis for spatial data. Chapman & Hall/CRC, London
5. Breiman L, Spector P (1992) Submodel selection and evaluation in regression. The X-random case. Int Stat Rev/Rev Int Stat 60:291–319
Cited by
10 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献