Related Experiment Video
Updated: Mar 14, 2026
Experimental Human Pneumococcal Carriage
Published on: February 15, 2013
Bias with respect to socioeconomic status: A closer look at zip code matching in a pneumococcal vaccine effectiveness
Ruth Link-Gelles1, Daniel Westreich2, Allison E Aiello2
1National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, 1600 Clifton Road, MS C-25, Atlanta, GA 30329, USA; Department of Epidemiology, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27516, USA.
Insights
Zip code is an adequate proxy for socioeconomic status in post-licensure vaccine effectiveness studies. This study found zip code matching minimally impacted 13-valent pneumococcal conjugate vaccine (PCV13) effectiveness estimates.
Area of Science:
- Epidemiology
- Public Health
- Vaccinology
Background:
- The 13-valent pneumococcal conjugate vaccine (PCV13) was introduced in the US in 2010 for pediatric invasive pneumococcal disease prevention.
- Individual socioeconomic status (SES) is a potential confounder in vaccine effectiveness studies.
- Zip code is often used as a proxy for SES in observational research.
Purpose of the Study:
- To assess the utility of zip code matching for controlling socioeconomic status (SES) confounding.
- To evaluate the impact of SES control on post-licensure vaccine effectiveness estimates for PCV13.
Main Methods:
- Utilized a directed acyclic graph to identify confounder subsets.
- Collected SES data from birth certificates, geo-coding, parent interviews, and medical records.
- Calculated PCV13 effectiveness using matched odds ratios ([1-matched odds ratio]*100).
Main Results:
- Cases were generally more affluent than eligible controls but less affluent than enrolled controls.
- Controlling for SES confounder subsets did not significantly alter the estimated vaccine effectiveness.
- Original effectiveness estimate: 85.1% (95% CI 74.8-91.9%); Adjusted estimate: 82.5% (95% CI 65.6-91.1%).
Conclusions:
- Zip code serves as an adequate, though imperfect, proxy for individual SES in post-licensure vaccine effectiveness studies.
- The use of zip code matching minimally affected PCV13 effectiveness estimates, suggesting its utility in controlling for SES confounding.
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, geo-coding, 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.
More Related Videos
Related Concept Videos
01:14Wilcoxon Signed-Ranks Test for Median of Single Population
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
01:20Sputum Studies II: Culture and Sensitivity
Sputum culture and sensitivity is a medical procedure used to diagnose bacterial infections in the respiratory tract and select the most appropriate antibiotics for treatment. This process involves analyzing sputum samples of thick and opaque secretions produced in the lungs and airways. These samples are collected from patients and then sent to the laboratory for analysis.
The test can identify various pathogens responsible for respiratory infections, including Streptococcus,...
01:26Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
01:29Bias in Epidemiological Studies
01:18Factors Affecting Illness
For instance, risk factors are connected to illness,...