Latent Spatial Heterogeneity in U.S. Cancer Mortality: A Multi-Site Clustering and Spatial Autocorrelation Analysis
Abstract
This research set out to explore and delineate spatial patterns and mortality distributions for various cancer types across U.S. states between 1999 and 2021. The aim was to uncover region-specific cancer burdens and inform geographically targeted prevention efforts. We analyzed state-level cancer mortality records sourced from the CDC WONDER platform, concentrating on cancer sites consistently reported across the 48 contiguous states and Washington, D.C., excluding Hawaii, Alaska, and Puerto Rico. Multivariate clustering using Mahalanobis distance grouped states according to similarities in mortality profiles. Spatial autocorrelation was examined for each cancer type using both Global Moran's I and Local Indicators of Spatial Association (LISA). Additionally, the Getis-Ord statistic was applied to detect cancer-specific hotspots and cold spots.
Keywords
Cite
@article{arxiv.2508.12188,
title = {Latent Spatial Heterogeneity in U.S. Cancer Mortality: A Multi-Site Clustering and Spatial Autocorrelation Analysis},
author = {E. Kubuafor and D. Baidoo and A. Duah and R. Amevor and O. J. Okeke and D. Quaye and P. O. Appiah},
journal= {arXiv preprint arXiv:2508.12188},
year = {2025}
}
Comments
15 pages, 4 figures