B3269 - SOCIOMENT Socioeconomic inequalities in childrens mental health disentangling social causation and selection - 07/03/2019

B number: 
B3269
Principal applicant name: 
Vera Skalicka | Norwegian University of Science and Technology (Norge)
Co-applicants: 
Prof. Lars Wichstrøm, Professor Terje Andreas Eikemo
Title of project: 
SOCIOMENT: Socioeconomic inequalities in children’s mental health – disentangling social causation and selection
Proposal summary: 

Children of parents who have limited education, occupational status and/or income are more likely to develop mental health problems than their more advantaged counterparts. However, we do not know whether it is parental socioeconomic position (SEP) which causes children to develop mental health problems, or whereas some other factors, such as parental personality, cause both parental SEP and children's mental health. The aim of this project is to provide new knowledge on the impact of parental SEP and other parental characteristics on children’s mental health and the extent to which psychosocial pathways influence development of children’s mental health, depending on parental SEP. We will analyze the data using a statistical method of dynamic panel modelling, which substantially enhances the prospect that the observed associations are causal.
We will take the advantage of our on-going longitudinal study, the Trondheim Early Secure Study, of 997 children from a community sample (age 4-16) and will compare the results across countries, employing also the ALSPAC data.

Impact of research: 
The research will inform policies to reduce social inequalities in mental health, and inter-generational transmission of social inequalities.
Date proposal received: 
Wednesday, 6 March, 2019
Date proposal approved: 
Thursday, 7 March, 2019
Keywords: 
Social Science, Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Mental health, Statistical methods, Childhood - childcare, childhood adversity, Cognition - cognitive function, Parenting, Psychology - personality, Statistical methods