- Volume 16 Issue 17
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Colorectal Cancer Mortality Characteristics and Predictions in China, 1991-2011
- Fang, Jia-Ying ;
- Dong, Hong-Li ;
- Sang, Xue-Jin ;
- Xie, Bin ;
- Wu, Ku-Sheng ;
- Du, Pei-Ling ;
- Xu, Zhen-Xi ;
- Jia, Xiao-Yue ;
- Lin, Kun
- Published : 2015.12.03
Background: To identify the epidemiological characteristics of colorectal cancer mortality in China during the period of 1991-2011, and forecast the future five-year trend. Materials and Methods: Mortality data for colorectal cancer in China from 1991 to 2011 was used to describe epidemiological characteristics in terms of age group, gender, and rural/urban residence. Trend surface analysis was performed to analyze the geographical distribution of colorectal cancer. Four models including curve estimation, time series modeling, gray modeling and joinpoint regression were applied to forecast the trends for the future five years. Results: Since 1991 the colorectal cancer mortality rate increased yearly, and our results showed that the trend would continue to increase in the ensuing 5 years. The mortality rate in males was higher than that of females and the rate in urban areas was higher than in rural areas. The mortality rate was relatively low for individuals less than 60 years of age, but increased dramatically afterwards. People living in the northeastern China provinces or in eastern China had a higher mortality rate for colorectal cancer than those living in middle or western China provinces. Conclusions: The steadily increasing mortality of colorectal cancer in China will become a substantial public health burden in the foreseeable future. For this increasing trend to be controlled, further efforts should concentrate on educating the general public to increase prevention and early detection by screening. More effective prevention and management strategies are needed in higher mortality areas (Eastern parts of China) and high-risk populations (60+ years old).
Colorectal cancer;mortality;epidemiological characteristics;geographic distribution;prediction
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Supported by : National Science Foundation of China