Reporting of data on participant ethnicity and socioeconomic status in high-impact medical journals: A targeted literature review

Abstract

Objectives: To assess the frequency of reporting of ethnicity (or ‘race’) and socioeconomic status (SES) indicators in high-impact journals. Design: Targeted literature review Data sources: The 10 highest ranked general medical journals using Google scholar h5 index. Eligibility criteria: Inclusion criteria were, human research, reporting participant level data. Exclusion criteria were non-research article, animal/other non-human participant/subject; or no participant characteristics reported. Data extraction and synthesis: Working backwards from 19/04/2021 in each journal, two independent reviewers selected the 10 most recent articles meeting inclusion/exclusion criteria, to create a sample of 100 articles. Data on the frequency of reporting of ethnicity (or ‘race’) and SES indicators were extracted and presented using descriptive statistics. Results: Of one hundred research articles included, 35 reported ethnicity and 13 SES. By contrast, 99 reported age, and 97 reported sex or gender. Among the articles not reporting ethnicity only 3 (5%) highlighted this as a limitation, and only 6 (7%) where SES data were missing. Median number of articles reporting ethnicity per journal was 2.5/10 (range 0 to 9). Only 2 journals explicitly requested reporting of ethnicity (or race), and 1 requested SES. Conclusions: The majority of research published in high-impact medical journals does not include data on the ethnicity and socioeconomic status of participants, and this omission is rarely acknowledged as a limitation. This situation persists despite the well-established importance of this issue and ICMJE recommendations to include relevant demographic variables to ensure representative samples. Standardized explicit minimum standards are required. Strengths and Limitations of this study - This study included recent studies from a range of the highest impact general medical journals. - Different inclusion/exclusion criteria for articles could be justifiably used which may have produced different results. - We identified high-impact journals using the google scholar h5 index, however various other equally valid impact metrics exist, which could change the journals considered. - Our analysis focused on if ethnicity and/or race was reported, but not how they are reported which is an important and related area for discussion and research to that covered in this study.