07. Access Under Uncertainty: Examining Measurement Error When Evaluating Food Equity

The concentration curve and closely related concentration index are methods that can be used to visualize and quantify the distribution of a health outcome versus another variable, such as measures of socioeconomic status or access to health-related resources. However, when fitting these models to real-world data, the data are often error-prone. One area where this issue arises is when investigating food access and individual dietary inflammation scores (DIS), as access to healthy foods is a neighborhood-level determinant of diet quality that is subject to multiple sources of error. To approach this issue, we conduct simulation studies to assess the impact of various sources of error in measuring access to healthy foods, such as errors that are dependent on other neighborhood-level factors like rural vs. non-rural geographies or the DIS outcome. We then compare these simulated results to the theoretical values of the concentration index under each of these conditions. Building on current measurement error literature, we seek to demonstrate how error-prone measures may bias a measure like the concentration index to direct future work in addressing this issue.

food access

measurement error

simulation

concentration index 

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Women in Statistics and Data Science 2025