# Occupational Exposure to Ionizing Radiation: Models for Policy Making

> **NIH ALLCDC R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $270,957

## Abstract

ABSTRACT
 There are an estimated 1.5 million U.S. workers occupationally exposed to ionizing radiation each year. Of
this number, approximately 120,000 workers are monitored annually for radiation exposure at United States
Department of Energy facilities, while hundreds of thousands of others are exposed while working with medical
sources of radiation, nuclear power generation, and industrial processes such as radiography and food
irradiation. In contrast to many other established occupational carcinogens, which have been removed from
US workplaces over time, the number of radiation-exposed workers has not diminished, but rather has grown
with the emergence of new uses of radiation in medicine and other industrial settings. Our understanding of
the health effects of radiation exposure comes from a variety of sources, including laboratory research, studies
of medical irradiation, and studies of atomic bomb survivors. However, epidemiological studies of workers hold
a special place because such studies allow direct evaluation of evidence that does not require extrapolation
from cells to organisms, between species, or across populations and exposure conditions.
 Until recently, epidemiological studies of radiation workers tended to result in imprecise risk estimates with
confidence intervals that often spanned the null. Consequently, epidemiological analyses of Japanese atomic
bomb survivors have served as the primary quantitative basis for radiation protection standards. However,
recent epidemiological studies that pool cohort data have yielded radiation risk estimates with relatively tight
confidence intervals. To strengthen the basis for protection of contemporary radiation workers, and to improve
compensation decisions for workers exposed in the past, we propose state-of-the-art statistical analysis using
parametric g-formula methods applied to data that recently have been assembled as part of a major
international effort to pool data for nuclear workers employed in the United Kingdom, France, and USA.
Specifically, we propose to assess: 1) temporal modifiers of radiation effects (time-since-exposure, age-at-
exposure, and attained age); 2) variation in radiation effects by type of cancer; and, 3) radiation effects on non-
cancer causes of death. In addition, we propose Bayesian methods to evaluate 4) dose and dose-rate effects;
and, 5) bias due to outcome misclassification. Because a causal interpretation of epidemiological findings is
strengthened by evidence of reproducibility and consistency, we will assess the consistency of results derived
from these international cohorts. The proposed methods allow us to minimize bias, including healthy worker
survivor bias, formally combine information from different studies, and leverage these recently pooled nuclear
worker cohort data. The findings of this research project are expected to have substantial impact on
understanding of the effects occupational radiation exposures. The work will address NOR...

## Key facts

- **NIH application ID:** 10176134
- **Project number:** 5R01OH011409-03
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** DAVID B RICHARDSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2021
- **Award amount:** $270,957
- **Award type:** 5
- **Project period:** 2019-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10176134

## Citation

> US National Institutes of Health, RePORTER application 10176134, Occupational Exposure to Ionizing Radiation: Models for Policy Making (5R01OH011409-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10176134. Licensed CC0.

---

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