Analysis of the Incidence and Mortality Trends of Lung Cancer in China from 1990 to 2021 and Prediction for 2035
Abstract
Background Lung cancer is a major global public health issue. As one of the countries with a high lung cancer burden, China's trends in incidence and mortality are influenced by environmental, economic, and behavioral factors, with significant regional variations. Understanding the spatiotemporal drivers of lung cancer burden and proposing precise prevention and control strategies are crucial for achieving the "Healthy China 2030" goal. Objective To analyze and predict the incidence and mortality trend of lung cancer in China from 1990 to 2021, explore the spatial heterogeneity of regional environmental and economic factors on the epidemic trend of lung cancer, and put forward suggestions for precise prevention and control. Methods Based on the Global Burden of Disease (GBD) data, the number of lung cancer cases and deaths, age-standardized incidence rate and age-standardized mortality rate of different genders and ages in China from 1990 to 2021 were extracted. The trend turning points were identified using the age-period-ecological model, the breakpoint regression (JPR) model, and the Holt exponential smoothing model. Environmental factors (PM2.5, industrial pollution) and economic factors (per capita GDP, medical resources) were integrated, and the spatial Durbin model was used to analyze regional heterogeneity. The Holt exponential smoothing model was employed to forecast the trend in 2035. Results The JPR model showed that from 1990 to 2021, the age-standardized incidence rate of lung cancer in China increased by an average of 0.94% annually (95%CI=0.87%-1.01%), with the age-standardized mortality rate increasing by 0.38% (95%CI=0.31%-0.45%). The incidence of lung cancer showed significant spatial clustering (P
Fields of Study & Subjects
Advanced Technologies in Various Fields
Data-Driven Disease Surveillance
Radiomics and Machine Learning in Medical Imaging
Publication details
- Journal / source
- DOAJ (DOAJ: Directory of Open Access Journals)
- Publication date
- 1 January 2026
- Language
- ZH