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Light at night and lung cancer risk: A worldwide interdisciplinary and time-series study
Runchen Wang1, Qixia Wang2, Jianfu Li1
1Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, Guangdong 510120, China.
Background:
Light at night (LAN) has become a concern in interdisciplinary research in recent years. This global interdisciplinary study aimed to explore the exposure-lag-response association between LAN exposure and lung cancer incidence.
Methods:
LAN data were obtained from the Defense Meteorological Satellite Program's Operational Linescan System. Data of lung cancer incidence, socio-demographic index, and smoking prevalence of populations in 201 countries/territories from 1992 to 2018 were collected from the Global Burden of Disease Study. Spearman correlation tests and population-weighted linear regression analysis were used to evaluate the correlation between LAN exposure and lung cancer incidence. A distributed lag nonlinear model (DLNM) was used to assess the exposure-lag effects of LAN exposure on lung cancer incidence.
Results:
The Spearman correlation coefficients were 0.286-0.355 and the population-weighted linear regression correlation coefficients were 0.361-0.527. After adjustment for socio-demographic index and smoking prevalence, the Spearman correlation coefficients were 0.264-0.357 and the population-weighted linear regression correlation coefficients were 0.346-0.497. In the DLNM, the maximum relative risk was 1.04 (1.02-1.06) at LAN exposure of 8.6 with a 2.6-year lag time. After adjustment for socio-demographic index and smoking prevalence, the maximum relative risk was 1.05 (1.02-1.07) at LAN exposure of 8.6 with a 2.4-year lag time.
Conclusion:
High LAN exposure was associated with increased lung cancer incidence, and this effect had a specific lag period. Compared with traditional individual-level studies, this group-level study provides a novel paradigm of effective, efficient, and scalable screening for risk factors.
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