From Gram-Negative Strains to Mortality: Understanding Bacterial Resistance in Mainland China

Background Carbapenem-resistant Gram-negative bacteria significantly threaten public health due to limited treatment options and high mortality rates. Understanding the factors influencing their detection and resistance rates is crucial for effective interventions. Objective: This study aimed to investigate the detection and carbapenem resistance rates of Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii in China and identify associations with climate, agriculture, economy, and diet. Method Data were sourced from CARSS, NBS, and CMDC, covering 1435 hospitals. Descriptive statistics and double fixed effect regression models analyzed associations, using SPSS, RStudio, StataMP, and Python. Results From 2014 to 2021, bacterial counts increased from 2,227,420 to 3,743,027, with Gram-negative bacteria constituting 70.3–71.5%. Escherichia coli (29.2–29.9%), Klebsiella pneumoniae (19.4–20.7%), Pseudomonas aeruginosa (11.8–12.7%), and Acinetobacter baumannii (9.1–10.8%) were the most prevalent. Environmental data indicated significant geographic distributions, with median humidity at 65%, median temperature at 15.75°C, and median annual rainfall at 1164.50 mm. Regional disparities in detection and resistance rates were observed, with Escherichia coli showing a median resistance rate of 1.40%, Pseudomonas aeruginosa 18.55%, Klebsiella pneumoniae 6.10%, and Acinetobacter baumannii 55.30%. Factors like hospital environment and food consumption significantly affected detection rates, while GDP per capita impacted resistance rates. Detection rates of Pseudomonas aeruginosa correlated significantly with increased mortality (coefficient 0.2007). Conclusion This study highlights the significant regional disparities and factors influencing the detection and resistance rates of carbapenem-resistant bacteria in China, emphasizing the need for targeted interventions considering local climatic, economic, and dietary conditions. Detection and resistance profiles did not significantly affect birth rates and population growth.