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Pavithra Manoj , Health Inequalities Lab, LSE Health, London School of Economics and Political Science, London, UK
Mengyao Wang, Yale University
Stergiani Tsoli, London School of Economics and Political Science
James Cole, University College London (UCL)
Emilie Courtin , Department of Health Policy, London School of Economics and Political Science, London, UK
A vast body of research has examined the relationship between educational attainment, cognitive ageing, and brain health. These studies suggest that education might contribute to cognitive reserve. However most evidence remains correlational and susceptible to selection bias and reverse causality. To address these limitations, we propose using the 1972 Raising of the School Leaving Age (ROSLA) reform in Great Britain, which increased the minimum school leaving from 15 to 16 for individuals born since 1st September 1957, as a natural experiment to estimate the causal effect of education on brain ageing. By exploiting the policy-induced variation in schooling duration using data from UK Biobank (UKB), we aim to isolate the effects of education on brain ageing from confounding factors. Brain ageing will be measured using innovative Brain Age estimates derived from pre-trained neural network models-DeepBrainNet and MIDI which uses brain scans as input. We will compute the Brain Age Difference (predicted brain age minus chronological age) as our primary outcome, where a smaller difference indicates healthier brain ageing. To estimate causal effects, we will implement a Regression Discontinuity Design (RDD), comparing individuals born just before and after the reform threshold. We will report both the impact of being eligible to and of taking up longer schooling on brain ageing. We will further describe subgroup differences and employ distributional analyses to understand who might benefit the most from longer schooling. This study aims to provide robust causal evidence on how extended education may shape brain health across the life course.
Presented in Session 51. Health, Morbidity and Wellbeing