Title of article :
Trends in esophageal cancer mortality in China during 1987–2009: Age, period and birth cohort analyzes
Author/Authors :
Guo، نويسنده , , Pi and Li، نويسنده , , Ke، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Pages :
7
From page :
99
To page :
105
Abstract :
Background: Esophageal cancer is one of the most commonly diagnosed malignant tumors in China. The aim of this study was to provide the representative and comprehensive informations about the long-term mortality trends of this disease in China between 1987 and 2009, using joinpoint regression and generalized additive models (GAMs). Methods: Age-standardized mortality rates (ASMR), overall and truncated (35–64 years), were calculated using the direct calculation method, and joinpoint regression was performed to obtain the estimated annual percentage changes (EAPC). GAMs were fitted to study the effects of age, period and birth cohort on mortality trends. Results: ASMR exhibited an overall remarked decline for rural females (EAPC = −2.3 95%CI: −3.3, −1.2), urban males (EAPC = −1.8 95%CI: −2.6, −1.0) and urban females (EAPC = −3.7 95%CI: −4.9, −2.4), but a small drop observed was not statistically significant for rural males (EAPC = −0.9 95%CI: −2.0, 0.3). The declines in ASMR were more noticeable for urban residents in recent years. Among all the residents, age effect showed an progressively increasing trend, whereas cohort effect declined steadily after the year corresponding to the maximum risk value. Period effect seemed to remain substantially unchanged throughout the years. Conclusions: Although variations in mortality rates were observed according to sex and area, the overall decreasing trends in esophageal cancer mortality were found in most Chinese people, aside from rural males. The findings could correspond to the changes in age- and cohort-related factors in the population. Further study is required to understand these potential factors.
Keywords :
Esophageal cancer , mortality , Age–period–cohort analyzes , Generalized additive model
Journal title :
Cancer Epidemiology
Serial Year :
2012
Journal title :
Cancer Epidemiology
Record number :
1765347
Link To Document :
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