Dataset Information

Predicting the mortality of smoking attributable to cancer in Qingdao, China: A time-series analysis.

ABSTRACT: Smoking is the leading preventable cause of death and disability from cancer in China. To provide a scientific basis for tobacco control strategies and measures, this study investigated cancer deaths attributed to smoking from 2005 to 2017 and predicted mortality trends from 2018 to 2020 in Qingdao. We used time series analysis to evaluate the number of deaths attributed to smoking among residents over 35 years old in Qingdao and predicted mortality trends. The number of cancer deaths attributed to smoking in Qingdao from 2005 to 2016 was between 170 and 407, showing an upward trend and a certain periodicity. The best model is the ARIMA (2,1,0)×(3,1,0)12, with the lowest BIC (6.640) and the highest stationary R2 (0.500). The predicted cancer deaths curve attributed to smoking in 2017 is consistent with the actual curve, with an average relative error of 5.74%. Applying this model to further predict the number of cancer deaths attributed to smoking in Qingdao from January 2018 to December 2020, the predicted results were 5,249, 5,423 and 6,048, respectively. The findings emphasized the need to further strengthen tobacco control measures to reduce the burden of disease caused by tobacco.

SUBMITTER: Qi F

PROVIDER: S-EPMC7833131 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Predicting the mortality of smoking attributable to cancer in Qingdao, China: A time-series analysis.

Qi Fei F Xu Zhenshi Z Zhang Hua H Wang Rui R Wang Yani Y Jia Xiaorong X Lin Peng P Geng Meiyun M Huang Yiqing Y Li Shanpeng S Yang Jun J

PloS one 20210125 1

Smoking is the leading preventable cause of death and disability from cancer in China. To provide a scientific basis for tobacco control strategies and measures, this study investigated cancer deaths attributed to smoking from 2005 to 2017 and predicted mortality trends from 2018 to 2020 in Qingdao. We used time series analysis to evaluate the number of deaths attributed to smoking among residents over 35 years old in Qingdao and predicted mortality trends. The number of cancer deaths attributed ...[more]

PMID: 33493221

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Project description:ObjectiveTo examine the total non-accidental mortality burden attributable to ambient temperatures and assess the effect modification of the burden by specific causes of death and individual characteristics in a high plateau area in southwest China.MethodsUsing daily mortality and meteorological data from 2009 to 2016, we applied a quasi-Poisson model combined with a distributed lag non-linear model to estimate the temperature-mortality association with the assessment of attributable fraction and number. We calculated attributable fractions and deaths with 95% empirical CIs (eCIs), that were due to cold and heat, defined as temperatures below and above the median temperature, and for mild and extreme temperatures, defined by cut-offs at the 2.5th and 97.5th temperature percentiles.ResultsWe analysed 89 467 non-accidental deaths; 4131 were attributable to overall temperatures, with an attributable fraction of 4.75% (95% eCI 2.33% to 6.79%). Most of the mortality burden was caused by cold (4.08%; 0.86% to 7.12%), whereas the burden due to heat was low and non-significant (0.67%; -2.44% to 3.64%). Extreme cold (1.17%; 0.58% to 1.69%) was responsible for 24.6% (ie, 1.17% divided by 4.75%) of the total death burden. In the stratification analyses, attributable risk due to cold was higher for cardiovascular than respiratory disease (6.18% vs 3.50%). We found a trend of risk of increased death due to ambient temperatures with increasing age, with attributable fractions of 1.83%, 2.27% and 6.87% for age ≤64, 65-74 and ≥75 years old, respectively. The cold-related burden was slightly greater for females, farmers, ethnic minorities and non-married individuals than their corresponding categories.ConclusionsMost of the burden of death was attributable to cold, and specific causes and individual characteristics might modify the mortality burden attributable to ambient temperatures. The results may help make preventive measures to confront climate change for susceptible population in this region.

Project description:BackgroundPrevious studies have shown decreases in cardiovascular mortality following the implementation of comprehensive smoking bans. It is not known whether cerebrovascular or respiratory mortality decreases post-ban. On March 29, 2004, the Republic of Ireland became the first country in the world to implement a national workplace smoking ban. The aim of this study was to assess the effect of this policy on all-cause and cause-specific, non-trauma mortality.MethodsA time-series epidemiologic assessment was conducted, utilizing Poisson regression to examine weekly age and gender-standardized rates for 215,878 non-trauma deaths in the Irish population, ages ?35 years. The study period was from January 1, 2000, to December 31, 2007, with a post-ban follow-up of 3.75 years. All models were adjusted for time trend, season, influenza, and smoking prevalence.ResultsFollowing ban implementation, an immediate 13% decrease in all-cause mortality (RR: 0.87; 95% CI: 0.76-0.99), a 26% reduction in ischemic heart disease (IHD) (RR: 0.74; 95% CI: 0.63-0.88), a 32% reduction in stroke (RR: 0.68; 95% CI: 0.54-0.85), and a 38% reduction in chronic obstructive pulmonary disease (COPD) (RR: 0.62; 95% CI: 0.46-0.83) mortality was observed. Post-ban reductions in IHD, stroke, and COPD mortalities were seen in ages ?65 years, but not in ages 35-64 years. COPD mortality reductions were found only in females (RR: 0.47; 95% CI: 0.32-0.70). Post-ban annual trend reductions were not detected for any smoking-related causes of death. Unadjusted estimates indicate that 3,726 (95% CI: 2,305-4,629) smoking-related deaths were likely prevented post-ban. Mortality decreases were primarily due to reductions in passive smoking.ConclusionsThe national Irish smoking ban was associated with immediate reductions in early mortality. Importantly, post-ban risk differences did not change with a longer follow-up period. This study corroborates previous evidence for cardiovascular causes, and is the first to demonstrate reductions in cerebrovascular and respiratory causes.

Dataset Information

Predicting the mortality of smoking attributable to cancer in Qingdao, China: A time-series analysis.

Publications

Predicting the mortality of smoking attributable to cancer in Qingdao, China: A time-series analysis.

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