The Use of Race and Socioeconomic Status Variables in Published Otolaryngologic Research

Ann Otol Rhinol Laryngol. 2023 Jul;132(7):721-730. doi: 10.1177/00034894221111323. Epub 2022 Jul 21.

Abstract

Objective: To characterize the use of race and socioeconomic status (SES) variables in clinical otolarynogologic research.

Methods: Databases were queried for all articles published in 2016 issues of 5 major otolaryngologic journals. One thousand, one hundred and forty of 1593 articles abstracted met inclusion criteria for analysis.

Results: In total, 244 (21.4%) studies specified race as a variable. The subspecialty of Head and Neck cancer specified race at statistically higher rates compared to other subspecialties (P = .002). Two hundred nine (34.0%) domestic studies specified race compared to 35 (6.7%) international studies. Of the 244 studies that specified race, 79 (32.4%) defined race using racial and ethnic categories interchangeably. Two hundred twenty-four (91.8%) studies reported data by race, 145 (59.4%) analyzed the data, and 112 (45.9%) discussed race-based results.In total, 94 (8.2%) studies specified SES. All subspecialties specified SES at statistically similar rates. Seventy (11.4%) domestic studies specified SES compared to 24 (4.6%) international studies. Of the 94 studies that specified SES, 42 (44.7%) defined SES using insurance status, 35 (37.2%) used education, and 32 (34.0%) used income. Seventy-eight (83.0%) studies reported data by SES, 71 (75.5%) analyzed the data, and 68 (72.3%) discussed SES-based results.

Conclusion: In clinical otolaryngologic research, the study of race and SES is limited. To improve quality of research and patient care for all patients, investigators should clearly justify their use of race and SES variables, carefully select their measures of race and SES (if the use of these variables is justified), and study race/SES-based data beyond just a superficial level.

Keywords: health disparities; patient outcomes; race; research bias; socioeconomic status.

MeSH terms

  • Educational Status
  • Ethnicity*
  • Healthcare Disparities
  • Humans
  • Research Design
  • Social Class*
  • Socioeconomic Factors