You are here

  • Home
  • Online First
  • Exploring interaction effects of social determinants of health with hospital admission type on academic performance: a data linkage study

Article Text

Article menu
Download PDFPDF
Original research
Exploring interaction effects of social determinants of health with hospital admission type on academic performance: a data linkage study
  1. Joanna F Dipnall1,2,
  2. Jane Lyons1,3,4,5,
  3. Ronan Lyons1,3,5,
  4. Shanthi Ameratunga1,6,7,
  5. Marianna Brussoni8,9,10,
  6. Frederick P Rivara11,
  7. Fiona Lecky12,13,
  8. Amy Schneeberg9,14,
  9. James E Harrison15,
  10. Belinda J Gabbe1,3
  1. 1School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
  2. 2Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin University, Geelong, Victoria, Australia
  3. 3Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
  4. 4Administrative Data Research Wales, Wales, UK
  5. 5National Centre for Population Health and Wellbeing Research, Swansea University, Swansea, UK
  6. 6School of Population Health, University of Auckland, Auckland, New Zealand
  7. 7Population Health Gain, Te Whatu Ora (Health New Zealand) – Service Improvement and Innovation, Auckland, New Zealand
  8. 8Department of Pediatrics, School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
  9. 9British Columbia Children’s Hospital Research Institute, British Columbia Injury Research and Prevention Unit, Vancouver, British Columbia, Canada
  10. 10Human Early Learning Partnership, University of British Columbia, Vancouver, British Columbia, Canada
  11. 11Departments of Pediatrics and Epidemiology, Harborview Injury Prevention and Research Center, University of Washington, Seattle, Washington, USA
  12. 12Centre for Urgent and Emergency Care Research, School of Medicine and Population Health, University of Sheffield, Sheffield, UK
  13. 13Emergency Department, Salford Royal Hospital, Salford, UK
  14. 14School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
  15. 15Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Austrlia
  1. Correspondence to Dr Joanna F Dipnall; joanna.dipnall{at}monash.edu

Abstract

Objective To investigate the moderating effects of socio-demographic social determinants of health (SDH) in the relationship between types of childhood hospitalisation (ie, none, injury, non-injury, injury+non-injury) and academic performance.

Design, setting and patients Children residing in Wales 2009–2016 (N=369 310). Secure Anonymised Information Linkage databank linked Tagged Electronic Cohort Cymru (five data sources) from the Wales Electronic Cohort for Children.

Main outcome measure Binary educational achievement (EA) measured across three key educational stage time points: grade 6 (mean age 11 years, SD 0.3), 9 (mean age 14 years, SD 0.3) and 11 (mean age 16 years, SD 0.3).

Results Of the 369 310 children, 51% were males, 25.4% of children were born in the lowest two Townsend deciles. Females were more likely to meet EA than males (adjusted risk ratio (aRR) (95% CI): 1.047 (1.039, 1.055)). EA was lower for injury admissions in males and any admission type in females (interactions: female×non-injury 0.982 (0.975, 0.989); female×injury+non-injury 0.980 (0.966, 0.994)). Children born into a more deprived decile were less likely to achieve EA (0.979 (0.977, 0.980)) and worsened by an injury admission (interactions: townsend×injury 0.991 (0.988, 0.994); Townsend×injury+non-injury 0.997 (0.994, 1.000)). Children with special educational needs (SEN) were less likely to meet EA (0.471 (0.459, 0.484) especially for an injury admission (interactions: SEN×injury 0.932 (0.892, 0.974)).

Conclusion SDH moderated the impact of hospital admission type on educational outcomes prompting future investigation into the viability of in-hospital routine screening of families for SDH and relevant post-hospital interventions to help reduce the impact of SDH on educational outcomes post-hospitalisation.

  • Adolescent Health
  • Child Health
  • Emergency Service, Hospital
  • Healthcare Disparities
  • Paediatrics

Data availability statement

Data are available upon reasonable request. This study makes use of anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. We would like to acknowledge all the data providers who make anonymised data available for research. Data are available from the SAIL Databank at HDRUK Swansea University https://saildatabank.com/ or contact SAILDatabank@swansea.ac.uk. For further information on access including training required see website: https://saildatabank.com/data/apply-to-work-with-the-data/. We confirm that the authors did not have any special access privileges.

https://doi.org/10.1136/archdischild-2024-327096

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Data availability statement

    Data are available upon reasonable request. This study makes use of anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. We would like to acknowledge all the data providers who make anonymised data available for research. Data are available from the SAIL Databank at HDRUK Swansea University https://saildatabank.com/ or contact SAILDatabank@swansea.ac.uk. For further information on access including training required see website: https://saildatabank.com/data/apply-to-work-with-the-data/. We confirm that the authors did not have any special access privileges.

    View Full Text

    Footnotes

    • Contributors JFD contributed to the study design, designed and performed the analysis, drafted the initial manuscript, critically reviewed and revised the manuscript and is responsible for the overall content as a guarantor. JL critically reviewed and revised the manuscript. RL, SA,MB, FPR, FL, JEH and BJG conceptualised and designed the study critically reviewed and revised the manuscript. AS critically reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agreed to be accountable for all aspects of the work.

    • Funding VIBES-Junior project: National Health and Medical Research Council of Australia (NHMRC-APP1142325); The Wales Electronic Cohort for Children (WECC) study was funded through Health and Care Research Wales (TRP08-006). Professor Lyons is supported by grants Health Data Research UK (HDR-9006) and UKRI-Economic and Social Research Council (ES/W012227/1). Jane Lyons is supported by grants from Health Data Research UK (HDR-9006) and UKRI-Economic and Social Research Council (ES/W012227/1). Professor Gabbe is supported by an NHMRC Investigator Grant (ID 2009998). The other authors received no additional funding.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.