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

Epidemiology and SARIMA model of deaths in a tertiary comprehensive hospital in Hangzhou from 2015 to 2022

BACKGROUND

By analysing the deaths of inpatients in a tertiary hospital in Hangzhou, this study aimed to understand the epidemiological distribution characteristics and the composition of the causes of death. Additionally, this study aimed to predict the changing trend in the number of deaths, providing valuable insights for hospitals to formulate relevant strategies and measures aimed at reducing mortality rates.

METHODS

In this study, data on inpatient mortality at a tertiary hospital in Hangzhou from 2015 to 2022 were obtained via the population information registration system of the Chinese Center for Disease Control and Prevention. The death data of inpatients were described and analysed through a retrospective study. Excel 2016 was utilized for data sorting, and SPSS 22.0 software was employed for data analysis. The statistical inference of single factor differences was conducted via χ2 tests. The SARIMA model was established via the forecast, aTSA, and tseries software packages (version 4.3.0) to forecast future changes in the number of deaths.

RESULTS

A total of 1938 inpatients died at the tertiary hospital in Hangzhou, with the greatest number of deaths occurring in 2022 (262, 13.52%). The sex ratio was 2.22:1, and there were significant differences between sexes in terms of age, marital status, educational level, and place of residence (P < 0.05). The percentage of males in the groups aged of 20 to 29 and 30 to 39 years was significantly greater than that of females (χ2 = 46.905, P < 0.001). More females than males died in the widowed group, and divorced and married males experienced a greater number of deaths than divorced and married females did (χ2 = 61.130, P < 0.001). The proportions of male students with a junior college and senior high school education were significantly greater than that of female students (χ2 = 12.310, P < 0.05). The primary causes of mortality within the hospital setting included circulatory system diseases, injury, poisoning, tumours, and respiratory system diseases. These leading factors accounted for 86.12% of all recorded deaths. Finally, the SARIMA (2, 1, 1) (1, 1, 1)12 model was determined to be the optimal model, with an AIC of 380.23, a BIC of 392.79, and an AICc of 381.81. The MAPE was 14.99%, indicating a satisfactory overall fit of this model. The relative error between the predicted and actual number of deaths in 2022 was 8.02%. Therefore, the SARIMA (2, 1, 1) (1, 1, 1)12 model demonstrates good predictive performance.

CONCLUSIONS

Hospitals should enhance the management of sudden cardiac death, acute myocardial infarction, severe craniocerebral injury, lung cancer, and lung infection to reduce the mortality rate. The SARIMA model can be employed for predicting the number of deaths.

Trends of gastric cancer burdens attributable to risk factors in China from 2000 to 2050

Background

The incidence of gastric cancer (GC) decreased in past decades, which was thought largely attributable to risk factors control, yet China still accounts for 44% of global GC burdens. We aimed to estimate changing trajectories of proportions of GC burdens attributable to modifiable risk factors from 2000 to 2050 in China, to inform future targeted preventive strategies.

Methods

The incidence and new cases of GC were predicted to 2050 using Bayesian age-period-cohort model based on incidence data by anatomical subsites drawn from 682 cancer registries from National Central Cancer Registry. Population attributable fractions (PAFs) were calculated based on prevalence of risk factors and relative risks with GC. Temporal trends of PAFs were described by sex and categories of risk factors using joinpoint analysis.

Findings

We observed declining trends of PAFs of Helicobacter pylori (H. pylori) infection, smoking, pickled vegetable and alcohol consumption, but increasing trends of PAFs of unhealthy body mass index and diabetes for GC in China. The combined PAFs of these risk factors were estimated to decrease by 10.57% from 2000 to 2050 for GC. We estimated there will be 279,707 GC (122,796 cardia gastric cancer [CGC] and 156,911 non-cardia gastric cancer [NCGC]) cases in 2050. Out of these cases, 70.18% of GC cases could be attributable to modifiable risk factors, while H. pylori infection was predicted to be responsible for 40.7% of CGC and 62.1% of NCGC cases in 2050.

Interpretation

More than half of GC remained attributable to modifiable risk factors in China. Continued effective strategies on risk factors control are needed to reduce the burden of this highly life-threatening cancer in future.

Funding

Beijing Nova Program (No. Z201100006820069), CAMS Innovation Fund for Medical Sciences (CIFMS, grant No. 2021-I2M-1-023), CAMS Innovation Fund for Medical Sciences (CIFMS, grant No. 2021-I2M-1-010), Talent Incentive Program of Cancer Hospital Chinese Academy of Medical Sciences (Hope Star).

All-Cause Mortality Risk Associated With Solid Fuel Use Among Chinese Elderly People: A National Retrospective Longitudinal Study

Background: The adverse health effects of air pollutants are widely reported, and the elderly are susceptible to toxic environments. This study aimed to evaluate the association between use of solid fuels for cooking and mortality among the elderly. Methods: A total of 5,732 and 3,869 participants from the Chinese Longitudinal Healthy Longevity Survey were enrolled in two (2014 and 2018) and three surveys (2011, 2014, and 2018) of survey. Cooking fuel was divided into clean and solid fuel. Cox proportional hazards models were used to estimate the mortality hazard ratio (HR). Subgroup analyses were performed to assess the potential interaction effect. Results: Among the participants in the 2011-2018 survey, 53% reported using solid fuel. Such group was associated with a 9% increase in mortality risk relative to clean fuel users (HR = 1.09, 95% CI = 1.01-1.18). Among participants in the 2014-2018 survey, 339 reported a switch from solid to clean fuels and they were not at increased mortality risk relative to the 488 people that reported a stable use of clean fuels (HR = 1.14, 95% CI = 0.99-1.31) although the estimated HR was similar to the one for stable solid fuel users (HR = 1.19, 95%CI = 1.04-1.36 n = 509). Interaction and stratified analyses showed that solid fuel use had an impact on mortality in participants who were non-current smokers, had low dietary diversity scores, and were living in areas with high PM2.5 concentrations (>50 μg/m3) and city population below 8 million (P for interaction < 0.05). The association was robust in the three sensitivity analyses. Conclusion: The finding showed a clear association between solid fuel use and mortality among older Chinese, and an even stronger association between risk of mortality and solid fuel use among individuals exposed to high levels of PM2.5.