IJPDS International Journal of Population Data Science

A new study from researchers at the University of Manitoba used the remarkable Manitoba Centre population based data to demonstrate how powerful the impact of poverty is on a child’s educational achievement, depending on when it occurs, how long it lasts, and how it is measured.

This adds to the number of research studies that have also shown poverty to have a negative effect on children’s educational outcomes.

‘Poverty and Intellectual Development in Childhood’, published in the International Journal of Population Data Science (IJPDS), followed the educational scores of almost 90,000 children from school entry at age 5. Their achievements were measured again at ages 8, 12, 13, 14 and 17 (when those who stay in school will be in grade 12). 

They tracked exposure to poverty each year (including the year before birth) using both an individual measure (family in receipt of Employment Income Assistance) and a measure of neighborhood poverty (based on census dissemination areas of about 400 individuals) ranging from the lowest income 20% of neighborhoods to the highest 20%. In addition, the mental health of the mothers and the implications for her child’s educational outcomes over this period, were also followed.

The differences in educational outcomes between children never receiving income assistance and those who have (whether for a majority or minority of their years) is striking at age 5 and grows somewhat over time, but not dramatically. Living in a poor neighborhood also has a negative effect, as does having a mother with mental health problems, but neither are as important as living in a poor household.

Lead author Dr. Leslie Roos said “This research highlights the value of population data in tracking individuals and their characteristics over time. Movement in and out of poverty has been shown to be a valuable predictor of educational achievement.”

 

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Roos, L. L., Detillieux, G. and Fransoo, G. (2025) “Poverty and intellectual development in childhood”, International Journal of Population Data Science, 10(1). doi: 10.23889/ijpds.v10i1.2984.