Peer-reviewed article
Pushing the boundary of child well-being: A spatial examination of child mortality in transition zones of extreme economic inequality and material hardship
Gia Elise Barboza-Salerno, Sharefa Duhaney, Brittany Liebhard, Karla Shockley McCarthy ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This research examines how neighbourhood economic inequality affects child mortality risk in US cities. Using spatial analysis methods, the study found that sharp economic transitions between adjacent neighbourhoods—called 'social frontiers'—are associated with 22% higher child mortality risk. The findings suggest that children living at the boundaries of economically unequal areas face elevated danger from both intentional and unintentional causes of death. The research identifies specific neighbourhoods where targeted prevention efforts could help protect vulnerable children.
Key points
- 413 social frontiers identified where sharp economic transitions between neighbourhoods correlate with 22% increase in relative risk of child mortality
- Effect persists after adjusting for racial segregation, concentrated disadvantage, residential mobility, and immigrant concentration
- Child fatality risk exhibits abrupt spatial shifts across neighbourhood boundaries rather than smooth patterns in urban areas
- Both intentional and unintentional child deaths are concentrated in areas of social disadvantage
Limitations
This is a spatial and observational study showing associations between neighbourhood economic transitions and child mortality, not causal effects. The study does not provide information about specific mechanisms linking economic frontiers to child deaths or evaluate any interventions to reduce this risk.
Abstract
How do patterns of socioeconomic inequality shape the risk of child fatality in urban areas? Research has shown that both intentional and unintentional child deaths are concentrated in areas of social disadvantage. Yet in densely populated cities, child fatality risk may not follow smooth spatial patterns and instead exhibit abrupt shifts across neighborhood boundaries. This study applies a dissimilarity-based Bayesian spatial conditional autoregressive (CAR) model to detect localized discontinuities in child mortality risk associated with structural inequality. Using a continuous dissimilarity function based on differences in Economic Hardship and Inequality (EHI) scores between adjacent census tracts, the model allows spatial smoothing to attenuate across sharp transitions. The model identified 413 spatial boundaries-termed social frontiers-where sharp structural discontinuities in EHI were associated with a 22% increase in the relative risk of child mortality, even after adjusting for racial segregation, concentrated disadvantage, residential mobility, and immigrant concentration. The significance of identifying neighborhoods characterized as social frontiers, where children may benefit from additional preventive interventions, is discussed in this context.