Background The dose‒response relationship-based relative risk (RR) of smoking exposure could better predict the risk of lung cancer than the dichotomous RR. To date, there is a lack of large-scale representative studies illustrating the dose‒response relationship between smoking exposure and lung cancer deaths, and no study has systematically pooled the current evidence in the Chinese population. Objectives To elucidate the dose‒response relationship of smoking and the risk of lung cancer mortality in the Chinese population. Methods Data were derived from studies on dose‒response relationships of smoking exposure and the risk of lung cancer among Chinese adults published before June 30th, 2021. Based on smoking exposure indicators and RR of lung cancer mortality, a series of dose‒response relationship models were developed. For smokers, 10 models were built to fit the dose‒response relationships between pack-years and RR of lung cancer deaths. For quitters, quit-years and corresponding RRs were used, and the pooled dichotomous RR value was used as the starting point to avoid overestimation. Finally, the results were compared with the estimates from 2019 Global Burden of Disease (GBD) study. Results A total of 12 studies were included. Among 10 dose‒response relationship models of pack-years with the RR of lung cancer mortality, the integrated-exposure–response (IER) model achieved the best fit. In all models, less than 60 pack-years presented RRs below 10. For former smokers, the RR decreased to 1 when quit-years reached up to 7 years. Both smokers and quitters had much lower RRs than that of the global level estimated by GBD. Conclusion The risk of lung cancer mortality rose with pack-years and decreased with quit-years among Chinese adults, and both values were far below global level. The results suggested that the dose–response RR of lung cancer deaths associated with smoking in China should be estimated separately.

ObjectivesImproved national Disease Surveillance Points systems (DSPs) in China have clarified mortality causes in the Chinese population. This study aimed to investigate the variations and drivers of multiple mortality causes.DesignThis was a retrospective cross-sectional surveillance study.SettingOriginal data in 1991 and 2000, and secondary data in 2010 and 2019 were collected from DSPs across China.ParticipantsStandardised mortality rates (SMRs) and crude mortality rates (CMRs) of the Chinese population in 1991, 2000, 2010 and 2019 were ascertained.Main outcome measuresChanges in the Gini coefficients (G), computed using SMR, were decomposed into reranking (R) and proportionality (P) to identify variations in communicable, maternal, neonatal and nutritional diseases (CMNN); non-communicable diseases (NCDs) and injury. The CMR difference (in %) was partitioned into the demographic structure and non-demographic factors using the mortality-rate-difference method.ResultsFrom 1991 to 2019, the overall CMR increased from 591.327/100 000 to 674.505/100 000, whereas the SMR continually decreased. An increasing concentration of NCDs contributed to the increased all-cause G from 0.443 to 0.560 during 1991–2019. Between 1991 and 2019, compared with CMNN (R=0.054) and NCDs (R=0.037), the ranking of injury changed the most (R=0.174). The ranking of diabetes, falls and road traffic accidents increased markedly over time. The decreased SMR of NCDs (P=−0.013) was mainly due to low-ranking causes, whereas changes in CMNN (P=0.003) and injury (P=0.131) were due to high-ranking causes. All-cause CMR increased by 14.06% from 1991 to 2019 due to greater contributions from the demographic structure (68.46%) than the non-demographic factors (−54.40%). Demographic structural changes accounted more for CMR increases in males (70.52%) and urban populations (75.58%).ConclusionsPrevention and control measures targeting NCDs and specific causes are imperatively needed, and should be strengthened as the population ages, especially for males and rural populations.