Spatial distribution, clustering patterns, and economic burden of comorbidities among hospitalised pulmonary tuberculosis patients in Guangdong province: a spatial epidemiological study based on inpatient big data

Background: Comorbidities may complicate the treatment of pulmonary tuberculosis and exacerbate both the clinical and economic burden. We aimed to examine comorbidity patterns, spatial clustering, and economic burden in hospitalised pulmonary tuberculosis (PTB) patients in Guangdong Province, supporting targeted prevention strategies. Methods: Based on the Hospital Discharge Records Database of Guangdong Province from 2016 to 2024, we collected data on hospitalised PTB patients to analyse the characteristics and temporal trends of comorbidity spectra. We used Global Moran's I and local indicators of spatial association analyses to examine the spatial clustering patterns of major comorbidity pairs. Generalised linear models evaluated the impact of comorbidity count and spatial clustering patterns on economic burden among hospitalised PTB patients. Results: A total of 646,114 hospitalised PTB patients were included from 2016 to 2024, of whom 66.42% had at least one comorbidity. Hypertension (HTN), diabetes mellitus (DM), and chronic obstructive pulmonary disease (COPD) were the top three comorbidities among hospitalised PTB patients. Spatial analysis indicated that high-high clusters of PTB-HTN were mainly concentrated in the central Pearl River Delta; high-high clusters of PTB-DM in eastern Guangdong and low-low clusters in western Guangdong. High-high clusters of PTB-COPD were primarily located in eastern and northern Guangdong, while low-low clusters remained relatively stable in several cities of the Pearl River Delta region. Among hospitalised PTB patients, the number of comorbidities was significantly positively associated with both direct and indirect economic burden (P < 0.001), with economic burden progressively increasing as the number of comorbidities increased, and the impact of spatial clustering patterns on economic burden exhibited heterogeneity across different comorbidity types. Conclusions: The burden of comorbidities among hospitalised PTB patients in Guangdong Province is substantial, with significant spatial clustering characteristics closely linked to direct and indirect economic burden. It is recommended to incorporate regional comorbidity epidemiological characteristics into PTB comorbidity management and resource allocation optimisation. In addition, both direct medical costs and productivity losses should be considered in prevention and control strategies to reduce the socioeconomic burden associated with PTB.