# Assessing nonresponse bias in a 30-year study of gulf war and gulf era veterans

## TL;DR

This study examines how nonresponse bias affects health data from a long-term study of Gulf War veterans, finding that adjustments reduce bias in key variables.

## Contribution

The study introduces a method to assess and adjust for nonresponse bias in longitudinal veteran health data.

## Key findings

- Response rates remained relatively high in Wave 4, with older, White, deployed, and married veterans more likely to respond.
- Weighting adjustments reduced bias in demographic and military characteristics, but alcohol and drug dependence may still be underestimated.
- Nonresponse adjustments were effective for key variables, supporting continued insights into long-term health effects.

## Abstract

Cohort studies of veterans are critical for understanding the long-term health effects of deployment and toxic exposures. However, longitudinal research is susceptible to attrition and potential nonresponse bias. The Gulf War Era Cohort Study (GWECS) is the largest and longest-running longitudinal cohort study of 1990–1991 Gulf War veterans. In this paper, we identify demographic and military service characteristics associated with patterns of response over time and examine the extent to which accounting for nonresponse bias in Wave 4, conducted more than 30 years after the Gulf War, might impact the estimates of health conditions.

Multivariate multinomial logistic regression analysis was used to identify demographic and military service characteristics associated with response patterns over time (always responder, current responder, past responder, never responder). To adjust for nonresponse at Wave 4, a search algorithm was used to identify predictors of response and form weighting class cells. The effectiveness of nonresponse adjustments was evaluated by (1) comparing estimates of demographic and military characteristics before and after weighting, (2) examining the correlation between the weighting classes and health outcomes, and (3) comparing early and late responders on health outcomes.

Wave 4 obtained a response rate of 47%, close to the 50% response rate obtained in Wave 3 over a decade earlier. Veterans most likely to respond to the survey over time and in Wave 4 were older, White, deployed, officers, and married in 1991. Weighting adjustments accounted for these differences and reduced bias in demographic and military characteristics, as well as in survey variables related to those characteristics. However, differences observed between early and late responders on alcohol and drug dependence suggest that these conditions may be underestimated.

GWECS achieved a relatively high response rate in the most recent follow-up. Although differential response occurred, nonresponse adjustments effectively reduced bias in the key variables examined. This cohort continues to provide insight into the long-term health effects of Gulf War deployment, including cancer and chronic conditions, as the cohort ages.

The online version contains supplementary material available at 10.1186/s12874-025-02761-5.