scholarly journals Child stature, maternal education, and early childhood development in Nigeria

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260937
Author(s):  
Emmanuel Skoufias ◽  
Katja Vinha

Data from the 2016–17 Multiple Indicator Cluster Survey from Nigeria are used to study the relationship between child stature, mother’s years of education, and indicators of early childhood development (ECD). The relationships are contrasted between two empirical approaches: the conventional approach whereby control variables are selected in an ad-hoc manner, and the double machine-learning (DML) approach that employs data-driven methods to select controls from a much wider set of variables and thus reducing potential omitted variable bias. Overall, the analysis confirms that maternal education and the incidence of chronic malnutrition have a significant direct effect on measures of early childhood development. The point estimates based on the ad-hoc specification tend to be larger in absolute value than those based on the DML specification. Frequently, the point estimates based on the ad-hoc specification fall inside the confidence interval of the DML point estimates, suggesting that in these cases the omitted variable bias is not serious enough to prevent making causal inferences based on the ad-hoc specification. However, there are instances where the omitted variable bias is sufficiently large for the ad hoc specification to yield a statistically significant relationship when in fact the more robust DML specification suggests there is none. The DML approach also reveals a more complex picture that highlights the role of context. In rural areas, mother’s education affects early childhood development both directly and indirectly through its impact on the nutritional status of both older and younger children. In contrast, in urban areas, where the average level of maternal education is much higher, increases in a mother’s education have only a direct effect on child ECD measures but no indirect effect through child nutrition. Thus, DML provides a practical and feasible approach to reducing threats to internal validity for robust inferences and policy design based on observational data.

2019 ◽  
Vol 4 (6) ◽  
pp. e001724 ◽  
Author(s):  
Ann M Weber ◽  
Marta Rubio-Codina ◽  
Susan P Walker ◽  
Stef van Buuren ◽  
Iris Eekhout ◽  
...  

IntroductionEarly childhood development can be described by an underlying latent construct. Global comparisons of children’s development are hindered by the lack of a validated metric that is comparable across cultures and contexts, especially for children under age 3 years. We constructed and validated a new metric, the Developmental Score (D-score), using existing data from 16 longitudinal studies.MethodsStudies had item-level developmental assessment data for children 0–48 months and longitudinal outcomes at ages >4–18 years, including measures of IQ and receptive vocabulary. Existing data from 11 low-income, middle-income and high-income countries were merged for >36 000 children. Item mapping produced 95 ‘equate groups’ of same-skill items across 12 different assessment instruments. A statistical model was built using the Rasch model with item difficulties constrained to be equal in a subset of equate groups, linking instruments to a common scale, the D-score, a continuous metric with interval-scale properties. D-score-for-age z-scores (DAZ) were evaluated for discriminant, concurrent and predictive validity to outcomes in middle childhood to adolescence.ResultsConcurrent validity of DAZ with original instruments was strong (average r=0.71), with few exceptions. In approximately 70% of data rounds collected across studies, DAZ discriminated between children above/below cut-points for low birth weight (<2500 g) and stunting (−2 SD below median height-for-age). DAZ increased significantly with maternal education in 55% of data rounds. Predictive correlations of DAZ with outcomes obtained 2–16 years later were generally between 0.20 and 0.40. Correlations equalled or exceeded those obtained with original instruments despite using an average of 55% fewer items to estimate the D-score.ConclusionThe D-score metric enables quantitative comparisons of early childhood development across ages and sets the stage for creating simple, low-cost, global-use instruments to facilitate valid cross-national comparisons of early childhood development.


1988 ◽  
Vol 33 (8) ◽  
pp. 730-730
Author(s):  
No authorship indicated

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