Using graphic modelling to identify modifiable mediators of the association between area-based deprivation at birth and offspring unemployment

Bogie, J., Fleming, M. , Cullen, B. , Mackay, D. and Pell, J. P. (2021) Using graphic modelling to identify modifiable mediators of the association between area-based deprivation at birth and offspring unemployment. PLoS ONE, 16(3), e0249258. (doi: 10.1371/journal.pone.0249258) (PMID:33788869) (PMCID:PMC8011734)

Abstract

Background: Deprivation can perpetuate across generations; however, the causative pathways are not well understood. Directed acyclic graphs (DAG) with mediation analysis can help elucidate and quantify complex pathways in order to identify modifiable factors at which to target interventions. Methods and findings: We linked ten Scotland-wide databases (six health and four education) to produce a cohort of 217,226 pupils who attended Scottish schools between 2009 and 2013. The DAG comprised 23 potential mediators of the association between area deprivation at birth and subsequent offspring ‘not in education, employment or training’ status, covering maternal, antenatal, perinatal and child health, school engagement, and educational factors. Analyses were performed using modified g-computation. Deprivation at birth was associated with a 7.3% increase in offspring ‘not in education, employment or training’. The principal mediators of this association were smoking during pregnancy (natural indirect effect of 0·016, 95% CI 0·013, 0·019) and school absences (natural indirect effect of 0·021, 95% CI 0·018, 0·024), explaining 22% and 30% of the total effect respectively. The proportion of the association potentially eliminated by addressing these factors was 19% (controlled direct effect when set to non-smoker 0·058; 95% CI 0·053, 0·063) for smoking during pregnancy and 38% (controlled direct effect when set to no absences 0·043; 95% CI 0·037, 0·049) for school absences. Conclusions: Combining a DAG with mediation analysis helped disentangle a complex public health problem and quantified the modifiable factors of maternal smoking and school absence that could be targeted for intervention. This study also demonstrates the general utility of DAGs in understanding complex public health problems.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Cullen, Dr Breda and Bogie, Dr James and Mackay, Professor Daniel and Fleming, Dr Michael and Pell, Professor Jill

Creator Roles

Bogie, J.: Data curation, Formal analysis, Writing – original draft
Fleming, M.: Data curation, Formal analysis, Writing – review and editing
Cullen, B.: Formal analysis, Writing – original draft
Mackay, D.: Supervision, Writing – review and editing
Pell, J. P.: Conceptualization, Supervision, Visualization, Writing – review and editing

• Authors: Bogie, J., Fleming, M., Cullen, B., Mackay, D., and Pell, J. P.
• College/School: College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health; College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Mental Health and Wellbeing; College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Public Health
• Journal Name: PLoS ONE
• Publisher: Public Library of Science
• ISSN: 1932-6203
• ISSN (Online): 1932-6203
• Copyright Holders: Copyright © 2021 Bogie et al.
• First Published: First published in PLoS ONE 16(3): e0249258
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
303197		Linking education and health data together to study relationships between various health factors and children's educational and health outcomes	Jill Pell	Medical Research Council (MRC)	MR/S003800/1	HW - Public Health