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Original research
Dental attendance and behavioural pathways to adult oral health inequalities
  1. Carol C Guarnizo-Herreño1,
  2. Shaun Scholes2,
  3. Anja Heilmann2,
  4. Rhiannon O'Connor3,
  5. Elizabeth Fuller4,
  6. Jing Shen5,6,
  7. Richard G Watt2,
  8. Steve Morris7,
  9. John Wildman5,
  10. Georgios Tsakos2
  1. 1 Departamento de Salud Colectiva, Facultad de Odontología, Universidad Nacional de Colombia, Bogotá, Colombia
  2. 2 Department of Epidemiology and Public Health, University College London, London, UK
  3. 3 School of Dental Sciences and Centre for Oral Health Research, Newcastle University, Newcastle upon Tyne, UK
  4. 4 National Centre for Social Research NatCen, London, UK
  5. 5 Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
  6. 6 GlaxoSmithKline, Wavre, Belgium (Although Jing Shen works now for GSK, the work associated with the paper was conducted during her time at Newcastle University)
  7. 7 Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
  1. Correspondence to Dr Carol C Guarnizo-Herreño, Universidad Nacional de Colombia, Bogotá, Colombia; ccguarnizoh{at}unal.edu.co

Abstract

Background While inequalities in oral health are documented, little is known about the extent to which they are attributable to potentially modifiable factors. We examined the role of behavioural and dental attendance pathways in explaining oral health inequalities among adults in England, Wales and Northern Ireland.

Methods Using nationally representative data, we analysed inequalities in self-rated oral health and number of natural teeth. Highest educational attainment, equivalised household income and occupational social class were used to derive a latent socioeconomic position (SEP) variable. Pathways were dental attendance and behaviours (smoking and oral hygiene). We used structural equation modelling to test the hypothesis that SEP influences oral health directly and also indirectly via dental attendance and behavioural pathways.

Results Lower SEP was directly associated with fewer natural teeth and worse self-rated oral health (standardised path coefficients, −0.21 (SE=0.01) and −0.10 (SE=0.01), respectively). We also found significant indirect effects via behavioural factors for both outcomes and via dental attendance primarily for self-rated oral health. While the standardised parameters of total effects were similar between the two outcomes, for number of teeth, the estimated effect of SEP was mostly direct while for self-rated oral health, it was almost equally split between direct and indirect effects.

Conclusion Reducing inequalities in dental attendance and health behaviours is necessary but not sufficient to tackle socioeconomic inequalities in oral health.

  • oral health
  • epidemiology
  • health inequalities
  • health services

Data availability statement

ADHS 2009 data are provided upon request by the Office for National Statistics’ under the UK Data Service’s End User Licence at https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=6884.

https://doi.org/10.1136/jech-2020-216072

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    Data availability statement

    ADHS 2009 data are provided upon request by the Office for National Statistics’ under the UK Data Service’s End User Licence at https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=6884.

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    Footnotes

    • Contributors All authors meet the ICMJE authorship criteria. CG-H contributed to conception, design, analysis and interpretation, drafted and critically revised the manuscript; SS contributed to analysis and interpretation, and critically revised the manuscript; AH, RO’C, EF, JS, RGW, SM critically revised the manuscript; JW contributed to data acquisition, analysis and interpretation, and critically revised the manuscript; GT contributed to conception, design, analysis and interpretation, and critically revised the manuscript. All authors approved the final manuscript.

    • Funding This work was supported by the UK Economic and Social Research Council [Grant Number ES/K004689/1] as part of the Secondary Data Analysis Initiative.

    • 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.