# Bayesian exposure-response analysis for immunoassays data with measurement errors

> **NIH NIH R21** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $200,841

## Abstract

PROJECT SUMMARY
The prevalence of allergic diseases and asthma among children is increasing worldwide. For sensitized individuals
with allergic asthma and rhinitis, continued exposure to indoor allergens will produce symptoms and exacerbation. Despite numerous epidemiological studies, the exposure-response relationships between indoor allergens and
asthma morbidity remain poorly understood. The goal of the proposed research is to develop new Bayesian methods and software to study exposure-response relationships between indoor allergen concentrations and asthma
morbidity among inner-city children with asthma. The new methods will correct measurement errors in the indoor allergen measurements using the standards data analyzed in immunoassays and provide estimates of allergen
concentrations at the extreme ends of calibration curves that would previously have been identified as below limits
of detection. In addition, the proposed methods will allow for assessing nonlinear exposure-response relationships
between a single allergen and a binary health outcome as well as the combined health effect of co-exposure to
multiple allergens and allow for inclusion of other covariates. Using Markov chain Monte Carlo simulations, we can
predict the health effects of exposures to indoor allergens and obtain imputations of the allergen concentrations
for those below limits of detection. We will apply the proposed methods to the data from the New York City
Neighborhood Asthma and Allergy Study (NAAS) among 7-8 years old asthmatic children living in New York
City. We will provide a user-friendly R package that implements the proposed methods and a Shiny app that
allows interactive data exploration. This will make our work more accessible, reproducible and directly useful.
Once completed, the proposed research will move forward not only statistical tools for analyzing immunoassay data
measured with errors and exposure-response analysis of such data but also research in indoor allergen exposure
and asthma morbidity among asthmatic children.

## Key facts

- **NIH application ID:** 9978057
- **Project number:** 5R21ES029668-02
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Qixuan Chen
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $200,841
- **Award type:** 5
- **Project period:** 2019-07-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9978057

## Citation

> US National Institutes of Health, RePORTER application 9978057, Bayesian exposure-response analysis for immunoassays data with measurement errors (5R21ES029668-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9978057. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*