Setting policy priorities in both developing and industrialized countries is influenced by whether income or education is the most important underlying determinant of mortality decline. The answer matters for choosing between programs that directly promote income growth and those that enhance school enrollment and quality of schooling. While one would ideally promote both of these goals along with good health services, reality often necessitates choices between these priorities.
Since improving health, income, and education are closely inter-woven, it appears difficult to determine the exact patterns of causation. As causes must however always precede consequences, and observed increases in schooling come decades before the resulting higher educational attainment of adults, this problem can be resolved. It is not the fact of being in school but rather the consequent adult skills and knowledge, which results in the behaviors that tend to bring down mortality.
The analysis discussed in this brief shows that better education has positive consequences on both higher income and higher life expectancy, thus resulting in a not necessarily causal association between the two. Better education also tends to lead to improved cognition, which is in turn associated with longer planning horizons and more conscious choices of health-related behaviors. These mental factors become increasingly important as the burden of disease shifts from infectious to chronic diseases more closely associated with lifestyle decisions.
IIASA Policy Briefs present the latest research for policymakers from IIASA - an international, interdisciplinary research institute with National Member Organizations (NMOs) in 23 countries in Africa, the Americas, Asia, and Europe. The views expressed herein are those of the researchers and not necessarily those of IIASA or its NMOs.
Last edited: 16 April 2018
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Steiber N (2019). Intergenerational educational mobility and health satisfaction across the life course: Does the long arm of childhood conditions only become visible later in life? Social Science and Medicine 242: e112603. DOI:10.1016/j.socscimed.2019.112603.
Striessnig E ORCID: https://orcid.org/0000-0001-5419-9498, Gao J, O'Neill B, & Jiang L (2019). Empirically-based spatial projections of U.S. population age structure consistent with the shared socioeconomic pathways. Environmental Research Letters 14 DOI:10.1088/1748-9326/ab4a3a.
Ediev D ORCID: https://orcid.org/0000-0001-7503-5142 (2019). On the sources of instability of the Mitra model for years of life at old-age. Communications in Statistics: Case Studies, Data Analysis and Applications: 1-11. DOI:10.1080/23737484.2019.1682485. (In Press)
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