Mapping the mortality niche of chronic lower respiratory diseases complicated by respiratory failure: a multiscale spatial analysis of environmental and social drivers

Background Chronic lower respiratory diseases complicated by respiratory failure as a multiple cause of death, denoted as RF-CLRD, represent a critical public health challenge with significant spatial heterogeneity across the United States. Although bioclimatic factors, air pollution, and social vulnerability are known determinants of respiratory health, traditional global models assume these risk factors operate uniformly across space, obscuring their spatial non-stationarity and region-specific impacts. Methods We utilized county-level data from the contiguous United States (2010–2019) to quantify mortality rates of RF-CLRD complicated by respiratory failure. Spatial clustering was evaluated using Moran's I and Local Indicators of Spatial Association (LISA) statistics. To capture process spatial heterogeneity, we developed a Multiscale Geographically Weighted Regression (MGWR) model integrating bioclimatic, pollution, and socioeconomic variables. Results RF-CLRD mortality rates exhibited marked spatial heterogeneity with multi-centric clustering across the contiguous United States. High-mortality hotspots were not limited to the Appalachian and Ozark highlands and the Deep South, but also formed distinct clusters in the Intermountain West and Northern Maine. The MGWR model significantly outperformed global OLS (Adjusted R 2 : 0.66 vs. 0.39), effectively capturing non-stationarity. The analysis identified a dual-scale mechanism: bioclimatic factors, PM 2.5 , and social vulnerability acted as broad, stable stressors (global scale), whereas population aging and smoking prevalence operated as localized amplifiers (regional scale). Notably, MGWR revealed that smoking's impact was spatially variable—strong in northern and coastal peripheries but insignificant in the South Central region. Conclusion The spatial heterogeneity of RF-CLRD mortality rates arises from the interplay between a stable macro-environmental niche and localized demographic amplifiers. This scale-dependent structure necessitates a transition from uniform national strategies to place-based precision policies. Interventions should prioritize climate adaptation and pollution mitigation in environmentally vulnerable regions where structural risks dominate, while targeting smoking cessation and geriatric care in specific behavioral hotspots.