title: Assessing the reporting of categorised quantitative variables in observational epidemiological studies.
abstract: One aspect to consider when reporting results of observational studies in epidemiology is how quantitative risk factors are analysed. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines recommend that researchers describe how they handle quantitative variables when analysing data. For categorised quantitative variables, the authors are required to provide reasons and justifications informing their practice. We investigated and assessed the practices and reporting of categorised quantitative variables in epidemiology.
  
  
  
  The assessment was based on five medical journals that publish epidemiological research. Observational studies published between April and June 2015 and investigating the relationships between quantitative exposures (or risk factors) and the outcomes were considered for assessment. A standard form was used to collect the data, and the reporting patterns amongst eligible studies were quantified and described.
  
  
  
  Out of 61 articles assessed for eligibility, 23 observational studies were included in the assessment. Categorisation of quantitative exposures occurred in 61% of these studies and reasons informing the practice were rarely provided. Only one article explained the choice of categorisation in the analysis. Transformation of quantitative exposures into four or five groups was common and dominant amongst studies using equally spaced categories. Dichotomisation was not popular; the practice featured in one article. Overall, the majority (86%) of the studies preferred ordered or arbitrary group categories. Other criterions used to decide categorical boundaries were based on established guidelines such as consensus statements and WHO standards.
  
  
  
  Categorisation of continuous variables remains a dominant practice in epidemiological studies. The reasons informing the practice of categorisation within published work are limited and remain unknown in most articles. The existing STROBE guidelines could provide stronger recommendations on reporting quantitative risk factors in epidemiology.
authors.affiliation: Division of Epidemiology and Biostatistics, LICAMM, School of Medicine, University of Leeds, Leeds, UK. umovm@leeds.ac.uk.
authors.forename: Onkabetse V
authors.initials: OV
authors.lastname: Mabikwa
authors.affiliation: Division of Epidemiology and Biostatistics, LICAMM, School of Medicine, University of Leeds, Leeds, UK.
authors.forename: Darren C
authors.initials: DC
authors.lastname: Greenwood
authors.affiliation: Division of Epidemiology and Biostatistics, LICAMM, School of Medicine, University of Leeds, Leeds, UK.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Baxter
authors.affiliation: Section of Epidemiology and Biostatistics, LICAP, School of Medicine, University of Leeds, Leeds, UK.
authors.forename: Sarah J
authors.initials: SJ
authors.lastname: Fleming
mesh_terms: D016021:Epidemiologic Studies; D019983:Guideline Adherence; D017408:Guidelines as Topic; D006801:Humans; D064887:Observational Studies as Topic / Q000379:methods* / Q000592:standards; D012107:Research Design; D012307:Risk Factors
keywords: Categorisation; Observational studies; Quantitative or continuous variables; STOBE guidelines