Bias with respect to socioeconomic status: A closer look at zip code matching in a pneumococcal vaccine effectiveness study

• Authors: Ruth Link-Gelles, Centers for Disease Control and Prevention; Daniel Westreich, University of North Carolina at Chapel Hill; Allison E. Aiello, University of North Carolina at Chapel Hill; Nong Shang, University of North Carolina at Chapel Hill; David J. Weber, University of North Carolina at Chapel Hill; Corinne Holtzman, Minnesota Department of Health; Karen Scherzinger, University of New Mexico; Arthur Reingold, California Emerging Infections Program; William Schaffner, Vanderbilt University; Lee H. Harrison, Johns Hopkins Bloomberg School of Public Health; Jennifer B. Rosen, New York City Department of Health and Mental Hygiene; Susan Petit, Connecticut Department of Public Health; Monica Farley, Emory University; Ann Thomas, Oregon Public Health Division; Jeffrey Eason, Utah Department of Health; Christine Wigen, Los Angeles County Department of Public Health; Meghan Barnes, Colorado Emerging Infections Program; Ola Thomas, Los Angeles County Department of Public Health; Shelley Zansky, New York State Department of Health; Bernard Beall, Centers for Disease Control and Prevention; Cynthia G. Whitney, Centers for Disease Control and Prevention; Matthew R. Moore, Centers for Disease Control and Prevention
• Journal Title: SSM - Population Health
• Volume: Volume 2
• Publisher: Elsevier: Creative Commons Attribution Non-Commercial No-Derivatives License | 2016-12-01, Pages 587-594
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1016/j.ssmph.2016.08.005
• Subjects: Health Sciences, Public Health; Health Sciences, Epidemiology
• Keywords: Matched case-control; PCV13; Pneumococcal vaccine; Pneumococcus; Socioeconomic status; Vaccine effectiveness

Abstract

In 2010, 13-valent pneumococcal conjugate vaccine (PCV13) was introduced in the US for prevention of invasive pneumococcal disease in children. Individual-level socioeconomic status (SES) is a potential confounder of the estimated effectiveness of PCV13 and is often controlled for in observational studies using zip code as a proxy. We assessed the utility of zip code matching for control of SES in a post-licensure evaluation of the effectiveness of PCV13 (calculated as [1-matched odds ratio] *100). We used a directed acyclic graph to identify subsets of confounders and collected SES variables from birth certificates, geocoding, a parent interview, and follow-up with medical providers. Cases tended to be more affluent than eligible controls (for example, 48.3% of cases had private insurance vs. 44.6% of eligible controls), but less affluent than enrolled controls (52.9% of whom had private insurance). Control of confounding subsets, however, did not result in a meaningful change in estimated vaccine effectiveness (original estimate: 85.1%, 95% CI 74.8–91.9%; adjusted estimate: 82.5%, 95% CI 65.6–91.1%). In the context of a post-licensure vaccine effectiveness study, zip code appears to be an adequate, though not perfect, proxy for individual SES.