Frontiers of Medicine

, Volume 6, Issue 4, pp 388–394

The epidemic status and risk factors of lung cancer in Xuanwei City, Yunnan Province, China


DOI: 10.1007/s11684-012-0233-3

Cite this article as:
Xiao, Y., Shao, Y., Yu, X. et al. Front. Med. (2012) 6: 388. doi:10.1007/s11684-012-0233-3


Xuanwei City (formerly known as Xuanwei County) locates in the northeastern of Yunnan Province and is rich in coal, iron, copper and other mines, especially the smoky (bituminous) coal. Unfortunately, the lung cancer morbidity and mortality rates in this region are among China’s highest, with a clear upward trend from the mid-1970s to mid-2000s. In 2004–2005, the crude death rate of lung cancer was 91.3 per 100 000 in the whole Xuanwei City, while that for Laibin Town in this city was 241.14 per 100 000. The epidemiologic distribution (clustering patterns by population, time, and space) of lung cancer in Xuanwei has some special features, e.g., high incidence in rural areas, high incidence in females, and an early age peak in lung cancer deaths. The main factor that associates with a high rate of lung cancer incidence was found to be indoor air pollution caused by the indoor burning of smoky coal. To a certain extent, genetic defects are also associated with the high incidence of lung cancer in Xuanwei. Taken together, lung cancer in this smoky coal combustion region is a unique model for environmental factor-related human cancer, and the current studies indicate that abandoning the use of smoky coal is the key to diminish lung cancer morbidity and mortality.


lung cancer Xuanwei smoky coal combustion polycyclic aromatic hydrocarbons epidemiology 

Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Yunnan Center for Disease Control and PreventionKunmingChina
  2. 2.Division of Molecular Carcinogenesis and Targeted Therapy for Cancer, State Key Laboratory of Biomembrane and Membrane Biotechnology, Institute of ZoologyChinese Academy of SciencesBeijingChina

Personalised recommendations