Bayesian Age-Period-Cohort Model of Lung Cancer Mortality
作者： Chris P. Tsokos , Ram C. Kafle , Bhikhari P. Tharu
DOI: 10.2427/11444
关键词: Lung cancer 、 Poisson regression 、 Medicine 、 Demography 、 Smoking cessation 、 Calendar period 、 Population 、 Mortality rate 、 Bayesian probability 、 Statistics 、 Age period cohort
摘要: Background The objective of this study was to analyze the time trend for lung cancer mortality in population USA by 5 years based on most recent available data namely 2010. knowledge rates temporal trends is necessary understand burden. Methods Bayesian Age-Period-Cohort model fitted using Poisson regression with histogram smoothing prior decompose age at death, period and birth-cohort. Results Mortality from increased more rapidly 52 years. It ended up 325 deaths annually 82 average. younger cohorts lower than older cohorts. risk lowered 1993 periods. Conclusions capable explaining rate cancer. reduction carcinogens cigarettes increase smoking cessation around 1960 might led decreasing after calendar 1993.
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