Abstract
BACKGROUND: Antimicrobial resistance (AMR) represents an escalating global health challenge, with socioeconomic status (SES) being a significant influencing factor. This study aimed to quantify area-level SES and assess its association with drug-resistant bacteria in China. METHODS: AMR data were collected from China Antimicrobial Resistance Surveillance System (CARSS, 2014-2023). Area-level SES across China was captured by County-level Area Deprivation Index (CADI) and Townsend Deprivation Index (TDI). Spatiotemporal distributions of drug-resistant bacteria were explored by spatial autocorrelation and spatiotemporal scan analyses. Key AMR risk factors were identified by GeoDetector analysis. Six Bayesian models were established through the Bayesian spatiotemporal modelling analysis. The Bayesian Spatiotemporal Interaction Hierarchy Model (BSTIHM), demonstrating superior estimative accuracy, was selected to forecast nationwide AMR patterns. FINDINGS: AMR profiles were obtained for totally 34,442,268 isolates of thirteen types of drug-resistant bacteria. The distributions of these bacteria exhibited manifest spatiotemporal heterogeneity nationwide. Both CADI and TDI consistently revealed a distinct socioeconomic gradient, with low area-level SES in western regions, medium in central regions, and high in eastern regions. Spatiotemporal clusters of drug-resistant bacteria were mainly observed in low SES regions. Lower area-level SES (odds ratio (OR) range: 1.054-1.254) and higher antimicrobial usage intensity (OR range: 1.022-1.174) contributed to higher risk of all thirteen types of drug-resistant bacteria. Meanwhile, total wastewater discharge (OR range: 1.064-1.280), PM(2.5) (OR range: 1.031-1.135), and number of healthcare technicians per 10,000 people (OR range: 1.035-1.310) were correlated with risks of most drug-resistant bacteria. Estimated risks for all thirteen types of drug-resistant bacteria were increased in low and middle area-level SES regions based on the BSTIHM. INTERPRETATION: Area-level SES is a pivotal driver of AMR risk, which might be caused by antibiotic overuse and environmental pollution. Targeted investments in healthcare and environmental systems in lower area-level SES regions are essential to effectively reduce AMR burden. FUNDING: National Key R&D Program of China, National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province, and Natural Science Foundation of Jiangsu Province.