Abstract
This article engages in the debate on the effects of early childhood health and children’s cognition at preschool and school ages in low- and middle-income countries. On the basis of three rounds of the ‘Young Lives’ panel, it endorses a multidimensional approach to health. A ‘suite of indicators’ of malnutrition and morbidity, and a composite Multidimensional Health Poverty Index (MHPI) are used to measure health. Expanding the informational basis for measuring health helped to capture variations in children’s medium-term cognitive outcomes more effectively. Beyond stunting, our empirical analysis shows that acute malnutrition is an important predictor of children’s lifecourse learning in India, while it has minor or no effects in the other countries. The composite MHPI is also significantly associated with later cognition; however, it is substantially less informative than the suite of indicators. Finally, the article explores some potential channels through which the relationship between early health and mid-term cognitive abilities operates.
Abstract
Cet article discute les effets de la santé des jeunes enfants et ses liens avec le développement cognitif chez les enfants d’âges préscolaire et scolaire dans les pays á faible revenu faible ou intermédiaire. Sur la base des trois séries d’une étude longitudinale de « Young Lives », il utilise une approche multidimensionnelle pour mesurer la santé. Une série d’indicateurs de malnutrition et de morbidité ainsi qu’un indice multidimensionnel composite de pauvreté de la santé (IMPS) sont utilisés pour mesurer la santé. L’ajout de ces indicateurs pour renforcer les informations relatives á la mesure de la santé a permis d’appréhender les variations dans les résultats cognitifs á moyen terme des enfants plus efficacement. Au-delá du retard de croissance, notre analyse empirique montre que la malnutrition aiguë est également un prédicteur important de l'apprentissage tout au long de la vie des enfants en Inde, tout en n’ayant aucun ou peu d’effets dans d’autres pays. Le composite IMPS est également fortement associé á la cognition; cependant, il est beaucoup moins informatif que la série d'indicateurs. Enfin, l'article examine un certain nombre de mécanismes par lesquels la relation entre la santé chez les plus jeunes et les capacités cognitives fonctionne.
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Notes
Another bias may result from the potential non-random attrition of less healthy children from the study, and the consequent selection of a sample of healthier individuals (Yamauchi, 2008). Attrition in the Young Lives sample is extremely low, at 3.6 per cent between Round 1 and Round 3, ranging from 5.8 per cent in Ethiopia to 2.3 and 2.4 per cent in Peru and Vietnam, respectively. Outes-Leon and Dercon (2008) use the first two rounds of data and show that attrition is not a concern when modelling children outcomes; minor problems are present only in Ethiopia. We replicated their probit tests including Round 3 data. Our results confirm previous evidence and highlight that the problem in Ethiopia is even less of a concern with the inclusion of a further round of data: attrition between Round 2 and Round 3 is, in fact, extremely low and not associated to child health.
In combination with household-fixed effects, some authors have identified instrumental variables (IVs) for child height (Alderman et al, 2001, 2006; Yamaouchi, 2008). Only a few studies, however, have adopted this strategy with Young Lives data and, in these cases, the instruments are not entirely convincing. For example, Sanchez (2013) instruments child height with a number of self-reported household shocks occurred 1–3 years before the surveys. The author includes all kinds of shocks – from drought and flood to illness of household members – some of which are likely to affect long-term learning outcomes directly, not only through child health. This is likely to add further endogeneity problems. Moreover, no formal IV tests appear in the paper. Arteaga and Glewwe (2014), instead, instrument child’s height-for-age in Round 2 with child’s height-for-age in Round 1, which goes against the conceptual framework used in our paper. For these reasons, we decided not to pursue the IV route.
A similar index has been used, among others, by Burchi and Passacantilli (2013) to measure household well-being in Peru.
While 99 per cent of children in Andhra Pradesh, Vietnam and Peru are enrolled in school at the age of 8, at that age almost 25 per cent of the Ethiopian sample are not enrolled. Moreover, there is great variation in terms of the grades attained by the Ethiopian children enrolled in school, ranging from 40 per cent of those who did not complete any grade to 2 per cent of those who completed Grade 3. Accordingly, we created a variable for Ethiopia alone that assumes the baseline value of 0 when the child is out of school or has not completed any grade, and the values of 1, 2 and 3 for children who have completed grades 1 and 2 or 3, respectively. For the other countries, the specific grades the children attained vary in the models depending on how the grades were distributed across the children in the sample.
Results are available from the authors upon request.
Child health could influence cognitive skills through other pathways such as the increase in educational aspirations. Dercon and Sanchez (2013) recently provided empirical evidence of the health-aspirations relationship in Young Lives. An increase in school aspirations is likely to influence school achievements and, finally, cognitive skills. However, since Young Lives only collects data on school aspirations for the older cohort of children and we used data for the younger cohort here, we could not test this channel. Our information in the data set is limited to whether or not the parents wanted the child to go to university. But this has two problems: the question is posed to the parents not the child, and it refers to levels of education beyond primary or secondary. Regressions run with this covariate show that this measure of educational aspiration is often a significant predictor of learning abilities, but its inclusion does not modify the significance and magnitude of the coefficients of early-childhood health variables. The results are not presented here because of limitations of space.
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Aurino, E., Burchi, F. Children’s Multidimensional Health and Medium-Term Cognitive Skills in Low- and Middle-Income Countries. Eur J Dev Res 29, 289–311 (2017). https://doi.org/10.1057/ejdr.2016.7
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DOI: https://doi.org/10.1057/ejdr.2016.7