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Decomposing contribution of age and non-age factors to rapid growth of lung cancer in Xuanwei over past 30 years

Overview of attention for article published in BMC Public Health, November 2015
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Title
Decomposing contribution of age and non-age factors to rapid growth of lung cancer in Xuanwei over past 30 years
Published in
BMC Public Health, November 2015
DOI 10.1186/s12889-015-2482-y
Pubmed ID
Authors

Yang Chen, Yize Xiao, Yongfang Yang, Jing Duan, Wen Xu

Abstract

From 1973 to 2005, the lung cancer mortality in Xuanwei had increased constantly. Effect analysis of age and non-age factors on lung cancer is important for local policy-making. Demographic and death data was collected and used. Factors of lung cancer were classified into age and non-age factors. The contribution of the two factors to lung cancer was evaluated by method of decomposing the differences of mortality rate. For males, the non-age factors were the major contributor to growth of lung cancer mortality, and 78.46 % of all growth was attributed to non-age factors. For females, the non-age factors were the absolute contributor to growth of lung cancer in 1973-1992. From 1992 to 2005, the contribution proportion had reduced to 75.39 %. Aging was one of risk factors for lung cancer in Xuanwei, but not the main factor. It was supposed that multiple environmental risk factors were related with high growth of lung cancer in Xuanwei. Policy-making should focus on the non-age factors.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 18%
Student > Ph. D. Student 2 18%
Researcher 2 18%
Student > Master 1 9%
Student > Postgraduate 1 9%
Other 0 0%
Unknown 3 27%
Readers by discipline Count As %
Medicine and Dentistry 5 45%
Nursing and Health Professions 2 18%
Environmental Science 1 9%
Unknown 3 27%