Global, regional and national burden of lung cancer attributable to occupational carcinogens, 1990-2019: A study of trends, inequalities and predictions based on GBD 2019

Zongjie Wang; Junmin Zhu; Yafei Wu; Chongtao Wei; Ya Fang

doi:10.1016/j.canep.2024.102737

Global, regional and national burden of lung cancer attributable to occupational carcinogens, 1990-2019: A study of trends, inequalities and predictions based on GBD 2019

Cancer Epidemiol. 2024 Dec 22:94:102737. doi: 10.1016/j.canep.2024.102737. Online ahead of print.

Authors

Zongjie Wang¹, Junmin Zhu¹, Yafei Wu², Chongtao Wei¹, Ya Fang³

Affiliations

¹ School of Public Health, Xiamen University, Xiamen, Fujian, China; Key Laboratory of Health Technology Assessment of Fujian Province, Xiamen University, Xiamen, Fujian, China.
² School of Public Health, Xiamen University, Xiamen, Fujian, China; School of Nursing, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China.
³ School of Public Health, Xiamen University, Xiamen, Fujian, China; Key Laboratory of Health Technology Assessment of Fujian Province, Xiamen University, Xiamen, Fujian, China; National Institute of Big Data for Health Care, Xiamen University, Xiamen, Fujian, China. Electronic address: fangya@xmu.edu.cn.

PMID: 39718282
DOI: 10.1016/j.canep.2024.102737

Abstract

Background: Lung cancer, a leading cause of cancer-related mortality, is significantly influenced by occupational carcinogens. This study aimed to assess and predict global, regional and national trends of lung cancer burden attributable to occupational carcinogens.

Methods: Data on the lung cancer burden attributable to nine occupational carcinogens were obtained from the Global Burden of Disease Study 2019. Regions were categorized by the Socio-Demographic Index (SDI). Descriptive statistics, Joinpoint regression, and Age-Period-Cohort (APC) models were employed to analyze trends in mortality and Disability-Adjusted Life Years (DALYs). Using the Slope Index of Inequality and Concentration Index, health inequalities were quantified. The ARIMA-LSTM model was developed to predict the burden from 2020 to 2030.

Results: From 1990-2019, lung cancer deaths and DALYs due to occupational carcinogens increased. Global age-standardized mortality (ASMR) and DALY (ASDR) rates declined, while middle and lower SDI regions increased. Joinpoint regression and APC analysis revealed that the local drift, period, and cohort effects exhibited increasingly unfavorable trends in lower SDI regions, while they were decreasing trends in higher SDI regions. Conversely, age effects increased similarly across all SDI regions. Health inequalities worsened over time. The ARIMA-LSTM model demonstrated global ASMR and ASDR would decrease, while low-middle and low SDI regions were expected to experience substantial increases from 2020 to 2030.

Conclusion: Health inequality of lung cancer burden attributable to occupational carcinogens remained a critical concern, underscoring the urgent need for targeted occupational health policies for low and low-middle SDI regions.

Keywords: Age-period-cohort analysis; Health inequity; Lung cancer; Occupational carcinogens; Prediction.