Fig 1.
Illustration of the boundary detection method.
The figure shows a census tract that neighbors two other census tracts labeled by lines A and B (left). The figure to the right shows that this tract was categorized as one of the least deprived 20% of neighborhoods by the EHI index, as shown in yellow. However, it borders two census tracts classified as the most deprived 20% of census tracts by the EHI.
Table 1.
Descriptive characteristics of key study variables.
Fig 2.
Distribution of Economic Hardship and Inequality.
This figure shows the spatial pattern of the Economic Hardship and Inequality (EHI) Index across Chicago census tracts (A: top left), the locations of tract borders with high EHI differences (B: top right), and the overall distribution of EHI scores (C: bottom panel). Panel A (left) reveals a strong clustering of EHI, with the most disadvantaged tracts mainly on Chicago’s South and West Sides. In contrast, areas with lower EHI scores, indicating greater economic advantage, are visible in the northern and southwest parts of the county. Panel B (right) highlights social frontiers, defined as the boundary lines between neighboring tracts that show differences in EHI. These lines are drawn between tract centers, and the color indicates the size of the EHI difference. High-magnitude frontiers are mostly found along boundaries that separate the most disadvantaged neighborhoods from their wealthier neighbors. These areas mark points of sharp structural inequality and sudden changes in hardship over small distances. Panel C presents a histogram of EHI scores across all tracts, showing a right-skewed distribution with most tracts clustered around moderate hardship levels (85–110) and a smaller number of tracts with very high scores (above 140), highlighting the concentration of severe disadvantage in certain areas.
Fig 3.
Neighborhood Differences in Economic Hardship and Inequality.
Distribution of differences in the Economic Hardship and Inequality (EHI) across pairs of neighboring census tracts (A) and the randomization process used to detect significant differences (B). The peak of the histogram centered around zero represents no difference in EHI between tracts, meaning that two census tracts have the same level of EHI.
Table 2.
Results from the Spatial Discontinuity Models.
Fig 4.
Spatial Frontiers and Child Mortality.
This figure presents the spatial distribution of economic hardship and inequality (EHI) alongside social frontiers and child deaths across Cook County census tracts. Panel A: Tracts are shaded by EHI decile (1st = least hardship, 10th = most hardship). Overlaid green lines indicate the probability that a boundary represents a significant spatial discontinuity in child mortality risk, with line thickness corresponding to the magnitude of the posterior boundary effect. Darker and thicker green lines represent stronger evidence of a risk discontinuity across that boundary. Black lines delineate the municipal boundary of the City of Chicago. Panel B: Infant deaths are plotted as dots over the EHI decile map to show spatial concentration. Darker red shading reflects greater hardship. Infant fatalities cluster heavily in neighborhoods with high EHI on Chicago’s South and West Sides. Panel C: This panel isolates only the most extreme boundaries—those with EHI differences of ≥ 4 deciles (green lines)—and overlays infant death locations. The lines mark transitions between high- and low-hardship neighborhoods and are visually associated with elevated concentrations of infant deaths along neighborhood divides.