Mapping local variation in educational attainment across Africa

Nature

Volumn 555, Issue 7694, 2018, Pages 48-53

  Graetz, Nicholas ^a   Friedman, Joseph ^a   Osgood Zimmerman, Aaron ^a   Burstein, Roy ^a   Biehl, Molly H ^a   Shields, Chloe ^a   Mosser, Jonathan F ^a   Casey, Daniel C ^a   Deshpande, Aniruddha ^a   Earl, Lucas ^a   Reiner, Robert C ^a   Ray, Sarah E ^a   Fullman, Nancy ^a   Levine, Aubrey J ^a   Stubbs, Rebecca W ^a   Mayala, Benjamin K ^a   Longbottom, Joshua ^b   Browne, Annie J ^b   Bhatt, Samir ^c   Weiss, Daniel J ^b   Gething, Peter W ^b   Mokdad, Ali H ^a   Lim, Stephen S ^a   Murray, Christopher J L ^a   Gakidou, Emmanuela ^a   Hay, Simon I ^a,b   more..

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF OXFORD   (United Kingdom)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AGE; EDUCATION POLICY; EDUCATIONAL ATTAINMENT; FERTILITY; MAPPING; PRECISION; REPRODUCTIVE HEALTH; RURAL POPULATION; SOCIOECONOMIC CONDITIONS; SUSTAINABLE DEVELOPMENT;

ACADEMIC ACHIEVEMENT; AFRICA; AGE DETERMINATION; ARTICLE; COMPARATIVE STUDY; DECISION MAKING; EDUCATIONAL STATUS; GOAL ATTAINMENT; HEALTH EDUCATION; HUMAN; PREDICTION; PRIORITY JOURNAL; PUBLIC HEALTH; SEX DIFFERENCE; SUSTAINABLE DEVELOPMENT; ADOLESCENT; ADULT; FEMALE; INTERNATIONAL COOPERATION; MALE; MIDDLE AGED; MOTIVATION; PROBABILITY; SEX FACTOR; WORLD HEALTH ORGANIZATION; YOUNG ADULT;

SAHEL [SUB-SAHARAN AFRICA];

ADOLESCENT; ADULT; AFRICA; EDUCATIONAL STATUS; FEMALE; GOALS; HUMANS; INTERNATIONALITY; MALE; MIDDLE AGED; PROBABILITY; SEX FACTORS; WORLD HEALTH ORGANIZATION; YOUNG ADULT;

EID: 85042803412     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/nature25761     Document Type: Article

References (54)

1. UNESCO. Global Education Monitoring Report. (UNESCO, 2016).
2. United Nations. Transforming our World: The 2030 Agenda for Sustainable Development. (United Nations, 2015).
3. United Nations. Goal 4: Ensure Inclusive and Quality Education for All and promote Lifelong Learning. (United Nations, 2016).
4. Klasen, S. Does Gender Inequality Reduce Growth and Development: Evidence from Cross-Country Regressions. Working Paper Series No. 7 (World Bank, 2000).
5. Klasen, S. Low schooling for girls, slower growth for all?. Cross-country evidence on the effect of gender inequality in education on economic development. World Bank Econ. Rev. 16, 345-373 (2002).
6. Klasen, S. & Lamanna, F. The impact of gender inequality in education and employment on economic growth: new evidence for a panel of countries. Fem. Econ. 15, 91-132 (2009).
7. UNESCO. Reducing Global Poverty through Universal Primary and Secondary Education. Policy Paper 32 (UNESCO, 2017).
8. Abel, G. J., Barakat, B., Kc, S. & Lutz, W. Meeting the Sustainable Development Goals leads to lower world population growth. Proc. Natl Acad. Sci. USA 113, 14294-14299 (2016).
9. Gakidou, E., Cowling, K., Lozano, R. & Murray, C. J. Increased educational attainment and its effect on child mortality in 175 countries between 1970 and 2009: A systematic analysis. Lancet 376, 959-974 (2010).
10. Caldwell, J. C. How is greater maternal education translated into lower child mortality?. Health Transit. Rev. 4, 224-229 (1994).
11. Caldwell, J. C. Education as a factor in mortality decline: An examination of Nigerian data. Popul. Stud. (NY) 33, 395 (1979).
12. Jejeebhoy, S. J. Women's Education, Autonomy, and Reproductive Behaviour: Experience from Developing Countries (Clarendon, 1995).
13. Desai, S. & Alva, S. Maternal education and child health: Is there a strong causal relationship?. Demography 35, 71-81 (1998).
14. Basu, A. M. & Stephenson, R. Low levels of maternal education and the proximate determinants of childhood mortality: A little learning is not a dangerous thing. Soc. Sci. Med. 60, 2011-2023 (2005).
15. Fuchs, R., Pamuk, E. & Lutz, W. Education or wealth: which matters more for reducing child mortality in developing countries?. Vienna Yearb. Popul. Res. 8, 175-199 (2010).
16. Boyle, M. H. et al. The influence of economic development level, household wealth and maternal education on child health in the developing world. Soc. Sci. Med. 63, 2242-2254 (2006).
17. Pamuk, E. R., Fuchs, R. & Lutz, W. Comparing relative effects of education and economic resources on infant mortality in developing countries. Popul. Dev. Rev. 37, 637-664 (2011).
18. Kravdal, Ø. Child mortality in India: The community-level effect of education. Popul. Stud. 58, 177-192 (2004).
19. LeVine, R. A., LeVine, S., Schnell-Anzola, B., Rowe, M. L. & Dexter, E. Literacy and Mothering: How Women's Schooling Changes the Lives of the World's Children, Oxford Univ. Press, 2012).
20. Makate, M. & Makate, C. The causal effect of increased primary schooling on child mortality in Malawi: Universal primary education as a natural experiment. Soc. Sci. Med. 168, 72-83 (2016).
21. UNESCO. Aid to Education Is Stagnating and Not Going to Countries Most in Need. (UNESCO, 2017).
22. UNESCO. Education 2030. World Educ. Forum 2015 (UNESCO, 2015).
23. UNESCO. Is real progress being made in the equitable provision of education?. #PISAresults. http://www.iiep.unesco.org/en/real-progress-being-madeequitable-provision-education-pisaresults-3915 (IIEP UNESCO, 2017).
24. Dowell, S. F., Blazes, D. & Desmond-Hellmann, S. Four steps to precision public health. Nature 540, 189-191 (2016).
25. Bosco, C. et al. Exploring the high-resolution mapping of gender-disaggregated development indicators. J. R. Soc. Interface 14, 20160825 (2017).
26. Roberts, D. A. et al. Benchmarking health system performance across regions in Uganda: A systematic analysis of levels and trends in key maternal and child health interventions, 1990-2011. BMC Med. 13, 285 (2015).
27. Gething, P. W. et al. Mapping Plasmodium falciparum mortality in Africa between 1990 and 2015. N. Engl. J. Med. 375, 2435-2445 (2016).
28. Bhatt, S. et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature 526, 207-211 (2015).
29. Diggle, P. & Ribeiro, P. J. Model-based Geostatistics (Springer, 2007).
30. United Nations. Sustainable Development Goals - United Nations (United Nations, 2015).
31. UNESCO. UNESCO Operational Definition Of Basic Education Thematic Framework (UNESCO, 2007).
32. Tatem, A. J. WorldPop, open data for spatial demography. Sci. Data 4, 170004 (2017).
33. The World Bank. World Bank Group President Jim Yong Kim Speech at the 2017 Annual Meetings Plenary; http://www.worldbank.org/en/news/speech/2017/10/13/wbg-president-jim-yong-kim-speech-2017-annualmeetings-plenary-session (2017).
34. Nilsson, M., Griggs, D. & Visbeck, M. Policy: Map the interactions between Sustainable Development Goals. Nature 534, 320-322 (2016).
35. Osgood-Zimmerman, A. et al. Mapping child growth failure in Africa between 2000 and 2015. Nature https://doi.org/10.1038/nature25760 (2018).
36. GeoNetwork. Global Administrative Unit Layers (GAUL); http://www.fao.org/geonetwork/srv/en/metadata.show?id= 12691 (2015).
37. LP DAAC. Combined MODIS 5.1 dataset; available at: Https://lpdaac.usgs.gov/dataset-discovery/modis/modis-products-table/mcd12q1 (accessed 1 June 2017).
38. World Wildlife Fund. Global Lakes and Wetlands Database Level 3 (2004); https://www.worldwildlife.org/pages/global-lakes-and-wetlands-database (accessed 1 June 2017).
39. Lehner, B. & Döll, P. Development and validation of a global database of lakes, reservoirs and wetlands. J. Hydrol. (Amst.) 296, 1-22 (2004).
40. WorldPop. WorldPop dataset; available at: Http://www.worldpop.org.uk/data/get-data/(accessed 7 July 2017).
41. ICF. The DHS Program, Data. http://dhsprogram.com/data/(1998).
42. UNICEF. Multiple Indicator Cluster Survey (MICS). https://www.unicef.org/statistics/index-24302.html (UNICEF, 2010).
43. Minnesota Population Center. IPUMS International; https://international.ipums. org/international (2015).
44. Barro, R. J. & Lee, J.-W. International Comparisons of Educational Attainment. NBER Working Paper No. 4349 (NBER, 1993).
45. Barro, R. J. & Lee, J.-W. A New Data Set of Educational Attainment in the World, 1950-2010. NBER Working Paper No. 15902 (NBER, 2010).
46. UNESCO. ISCED Mappings; http://uis.unesco.org/en/isced-mappings (UNESCO, 2016).
47. Lumley. T. Complex Surveys: A Guide to Analysis Using R (Wiley-Blackwell, 2014).
48. Bhatt, S. et al. Improved prediction accuracy for disease risk mapping using Gaussian process stacked generalisation. J. R. Soc. Interface 14, 20170520 (2016).
49. Murray, C. J. et al. GBD 2010: Design, definitions, and metrics. Lancet 380, 2063-2066 (2012).
50. Stein, M. L. Interpolation of Spatial Data (Springer, 1999).
51. Waller, L. & Carlin, B. in Handbook of Spatial Statistics (eds Gelfand, A. et al.) 217-243 (CRC, 2010).
52. Rue, H., Martino, S. & Chopin, N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J. R. Stat. Soc. B 71, 319-392 (2009).
53. Patil, A. P., Gething, P. W., Piel, F. B. & Hay, S. I. Bayesian geostatistics in health cartography: The perspective of malaria. Trends Parasitol. 27, 246-253 (2011).
54. GBD 2015 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet 388, 1603-1658 (2016).