Toward a comprehensive life-cycle carcinogenic impact assessment: A statistical regression approach based on cancer burden

Abstract

The current approach to life cycle carcinogenic impact assessment (LCCA) is hindered by its static and linear characteristics. This situation prevents the accurate prediction of the incidence, associated damage, and potential economic burden of cancer. This study explores a highly comprehensive pathway for LCCA assessment. It uses the impacts of Tracheal, bronchus, and lung (TBL) predicted by the LCCA of China's coal power industry through a screened statistical regression model as the research target. The latest global burden of disease estimates is utilized to quantify the health damage from TBL incidence, whereas an approach combining the actual cost of health and human capital is applied to further assess the economic burden of TBL. Findings indicate that the traditional and static LCCA method, which relies on animal toxicity data, can lead to underestimations in actual LCCA. The interaction among spatiotemporal meteorological factors, epidemiological cancer disease burden, and socioeconomic behaviors allows exhibits nonlinearity due to the changes in the combined toxicity of mixed key substances. Following the active implementation of ultralow emission and energy-saving transformations in China's coal power industry, the national percentage of TBL cancer incidence caused by pollutants from the coal power industry decreased from 25.2 % in 2004 to 11.5 % in 2020. Results indicate that the established dynamic LCCA model based on temporal and spatial climate, socioeconomic, and epidemiological cancer data can be feasibly employed for the accurate impact evaluation and mitigation of carcinogens in practical applications.

Keywords: Climate change; Life cycle carcinogenic impact; Socio-economic factors; Statistical regression; TBL cancer.