Direct and indirect links between children's socio-economic status and education: pathways via mental health, attitude, and cognition

Abstract

A child's socio-economic environment can profoundly affect their development. While existing literature focusses on simplified metrics and pair-wise relations between few variables, we aimed to capture complex interrelationships between several relevant domains using a broad assessment of 519 children aged 7-9 years. Our analyses comprised three multivariate techniques that complimented each other, and worked at different levels of granularity. First, an exploratory factor analysis (principal component analysis followed by varimax rotation) revealed that our sample varied along continuous dimensions of cognition, attitude and mental health (from parallel analysis); with potentially emerging dimensions speed and socio-economic status (passed Kaiser's criterion). Second, k-means cluster analysis showed that children did not group into discrete phenotypes. Third, a network analysis on the basis of bootstrapped partial correlations (confirmed by both cross-validated LASSO and multiple comparisons correction of binarised connection probabilities) uncovered how our developmental measures interconnected: educational outcomes (reading and maths fluency) were directly related to cognition (short-term memory, number sense, processing speed, inhibition). By contrast, mental health (anxiety and depression symptoms) and attitudes (conscientiousness, grit, growth mindset) showed indirect relationships with educational outcomes via cognition. Finally, socio-economic factors (neighbourhood deprivation, family affluence) related directly to educational outcomes, cognition, mental health, and even grit. In sum, cognition is a central cog through which mental health and attitude relate to educational outcomes. However, through direct relations with all components of developmental outcomes, socio-economic status acts as a great 'unequaliser'.

Supplementary information: The online version contains supplementary material available at 10.1007/s12144-021-02232-2.

Keywords: Anxiety; Child development; Cognitive ability; Depression; Grit; Growth mindset; Maths; Network analysis; Poverty; Reading; Socioeconomic status.

Fig. 1.

(next page) – Network analyses that describe the relationships between variables measured in 519 children aged 7–9 years. Nodes are coloured according to principal components: cognition (chartreuse), attitude (azure), mental health (rose), speed (spring green), socio-economic status (orange). Node positions are determined through multi-dimensional scaling, and edge weights through partial correlation. Spurious partial correlations are filtered through bootstrapping (top-left panel) or LASSO regularisation with parameter selection through 5-fold cross-validation (bottom-left panel). All possible connections and their bootstrapped 95% confidence interval are listed in the right panel. Confidence intervals that include 0 (grey) were considered not statistically significant.

Fig. 2

The left panel shows correlations that are statistically significant after Holm-Bonferroni correction (top-right triangle), and partial correlations (bottom-left triangle) between all measured variables. The middle panel shows high (top-right triangle) and low (bottom-left triangle) bootstrapped 95% confidence intervals for the partial correlations, but only those that do not include 0. The right panel shows connection probabilities estimated through bootstrapping (top-right triangle), and only those that are higher than chance (bottom-left triangle)