Determining Risk of Cancer Risk Through Residential Histories
With Seed Funding from the P3RC, researchers at UIC School of Public, and the UIC College of Medicine are creating a process to better understand how a person’s environment, as measured by their place of residence, might affect their risk of cancer. If someone lives in an area with high air, water, and soil pollution, these factors can increase their risk of exposure to carcinogenic risk factors. In other words, in the absence of specific risk factor exposure data for a patient, we know that their residence in a high pollution area puts them “at risk of being at risk” for cancer. We can further estimate a person’s risk by looking at their residential history backwards for up to thirty years to understand how cumulative risk of being at risk affects cancer incidence, and looking forward to understand how post-diagnostic risk of being at risk affects survival outcomes. Our general approach follows four steps:
- Focus on policy drivers rather than behavioral factors (focus on risk of being at risk).
- Use existing secondary data sources on geospatial risk of being at risk.
- Use residential histories to create longer-term, cumulative measures of risk of being at risk.
- Reduce confounding variables through the creation of measures across multiple domains to allow for mutually-adjusted associations, so as not to be misled by confounding due to correlated measures.
Case Example: Calculating Risk of Being at Risk for Colon Cancer Using Residential Histories
Poor diet plays a significant role in the incidence of colon cancer. We might step back and ask whether residential proximity to unhealthy sources of food or residence in a food desert puts an individual at risk of having a poor diet that might lead to colon cancer. In other words, we explore whether a person’s residence puts them at risk for being at risk for colon cancer. This question shifts our focus away from purely behavioral risks and instead frames the problem in terms of policies related to food access. Second, we reconstruct a patient’s residential history by linking patient identifiers to address data available from a proprietary database developed by LexisNexis specifically for this purpose. Third, we can take advantage of data from the National Establishments Time Series Database to link patient residential histories to data on locations and types of food outlets as far back as 1990 and create long term cumulative measures of residential proximity to healthy and less healthy sources of foods. Finally, we can do the same for other domains of risk of being at risk (e.g., healthcare accessibility, socioeconomic status, chronic stress, pollution, etc.). Through this approach, we can account for the confounding effects of other domains in our statistical models. This is vital, since measures of the social and physical environment tend to be highly correlated and an association of one domain with a health outcome could in fact be due to the effect of another domain on that health outcome. Mutual adjustment for domains minimizes this possible mistake.
During calendar year 2024, we plan to link as many as 75,000 patients to their residential histories. Linked data will be stored at the UICC Cancer Data Shelter. We hope to make at least some of these data available to researchers by the fall of 2024, through requests through UICC Cancer Data Shelter. Through this project, we hope to create a rich infrastructure for studying the role of cumulative, longer-term exposures on cancer risk and outcomes, and that this work will draw interest from researchers across disciplines within the UI Cancer Center.
About the Author
Garth Rauscher is associate professor of epidemiology in the Division of Epidemiology and Biostatistics at the UIC School of Public Health and conducts research on the role social determinants of health and structural racism on cancer disparities.