ESTIMATING AND FORECASTING THE SMOKING-ATTRIBUTABLE MORTALITY FRACTION FOR BOTH GENDERS JOINTLY IN OVER 60 COUNTRIES
成果类型:
Article
署名作者:
Li, Yicheng; Raftery, Adrian E.
署名单位:
University of Washington; University of Washington Seattle
刊物名称:
ANNALS OF APPLIED STATISTICS
ISSN/ISSBN:
1932-6157
DOI:
10.1214/19-AOAS1306
发表日期:
2020
页码:
381-408
关键词:
lung-cancer mortality
emerging tobacco hazards
probabilistic projections
UNITED-STATES
hong-kong
TRENDS
PREVALENCE
disease
death
CHINA
摘要:
Smoking is one of the leading preventable threats to human health and a major risk factor for lung cancer, upper aerodigestive cancer and chronic obstructive pulmonary disease. Estimating and forecasting the smoking attributable fraction (SAF) of mortality can yield insights into smoking epidemics and also provide a basis for more accurate mortality and life expectancy projection. Peto et al. (Lancet 339 (1992) 1268-1278) proposed a method to estimate the SAF using the lung cancer mortality rate as an indicator of exposure to smoking in the population of interest. Here, we use the same method to estimate the all-age SAF (ASAF) for both genders for over 60 countries. We document a strong and cross-nationally consistent pattern of the evolution of the SAF over time. We use this as the basis for a new Bayesian hierarchical model to project future male and female ASAF from over 60 countries simultaneously. This gives forecasts as well as predictive distributions that can be used to find uncertainty intervals for any quantity of interest. We assess the model using out-of-sample predictive validation and find that it provides good forecasts and well-calibrated forecast intervals, comparing favorably with other methods.
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