ArticleGeoHealth2026
Spatial Analysis of Flood Risk, Neighborhood Characteristics, and Chronic Health Conditions in North Carolina.
Article in GeoHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Climate change will continue to increase the frequency and intensity of flood events in North Carolina for the foreseeable future. The extreme flooding in Western North Carolina caused by Tropical Storm Helene in September of 2024 is a recent and devastating example of this trend. Communities of color and low-income populations are more likely to reside in flood-prone areas due to structural factors, including residential racial segregation and economic inequality. As such, the adverse health and financial consequences of flood exposure overburden historically marginalized communities, which may have a more limited adaptive capacity to anticipate, respond to, and recover from flood events. Exposure to severe flooding further exacerbates chronic health conditions by impeding access to vital healthcare infrastructure and services. This study examines the spatial patterning of coastal and inland flood risk, neighborhood-level structural determinants (i.e., racial and economic inequality), and flood-sensitive health conditions in North Carolina using bivariate local indicators of spatial autocorrelation (LISA) statistics. High-high clusters capture areas where neighborhoods with high racial or economic inequality surround elevated flood risks. These clusters are distinguished by select sociodemographic characteristics and concentrated in the eastern coastal and western mountainous regions of North Carolina. Cluster locations are priority areas for targeted resource allocation and interventions that strengthen the adaptive capacity of these communities in the context of climate change.
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