Unplanned readmission within 31 days of discharge after stroke is a useful indicator for monitoring quality of hospital care. We evaluated the risk factors associated with 31-day unplanned readmission of stroke patients in China. We identified 50,912 patients from 375 hospitals in 29 provinces, municipalities or autonomous districts across China who experienced an unplanned readmission after stroke between 2015 and 2016, and extracted data from the inpatients’ cover sheet data from the Medical Record Monitoring Database. Patients were grouped into readmission within 31 days or beyond for analysis. Chi-squared test was used to analyze demographic information, health system and clinical process-related factors according to the data type. Multilevel logistic modeling was used to examine the effects of patient (level 1) and hospital (level 2) characteristics on an unplanned readmission ≤31 days. Among 50,912 patients, 14,664 (28.8%) were readmitted within 31 days after discharge. The commonest cause of readmissions were recurrent stroke (34.8%), hypertension (22.94%), cardio/cerebrovascular disease (13.26%) and diabetes/diabetic complications (7.34%). Higher risks of unplanned readmissions were associated with diabetes (OR = 1.089, P = 0.001), use of clinical pathways (OR = 1.174, P < 0.001), and being discharged without doctor’s advice (OR = 1.485, P < 0.001). Lower risks were associated with basic medical insurances (OR ranging from 0.225 to 0.716, P < 0.001) and commercial medical insurance (OR = 0.636, P = 0.021), compared to self-paying for medical services. And patients aged 50 years old and above (OR ranging from 0.650 to 0.985, P < 0.05), with haemorrhagic stroke (OR = 0.467, P < 0.001), with length of stay more than 7 days in hospital (OR ranging from 0.082 to 0.566, P < 0.001), also had lower risks. Age, type of stroke, medical insurance status, type of discharge, use of clinical pathways, length of hospital stay and comorbidities were the most influential factors for readmission within 31 days.

Background Smoke-free legislation is an effective way to protect the population from the harms of secondhand smoke and has been implemented in many countries. On 31 May 2012, Tianjin became one of the few cities in China to implement smoke-free legislation. We investigated the impact of smoke-free legislation on mortality due to acute myocardial infarction (AMI) and stroke in Tianjin. Methods An interrupted time series design adjusting for underlying secular trends, seasonal patterns, population size changes and meteorological factors was conducted to analyse the impact of the smoke-free law on the weekly mortality due to AMI and stroke. The study period was from 1 January 2007 to 31 December 2015, with a 3.5-year postlegislation follow-up. Results Following the implementation of the smoke-free law, there was a decline in the annual trends of AMI and stroke mortality. An incremental 16% (rate ratio (RR): 0.84; 95% CI: 0.83 to 0.85) decrease per year in AMI mortality and a 2% (RR: 0.98; 95% CI: 0.97 to 0.99) annual decrease in stroke mortality among the population aged ≥35 years in Tianjin was observed. Immediate postlegislation reductions in mortality were not statistically significant. An estimated 10 000 (22%) AMI deaths were prevented within 3.5 years of the implementation of the law. Conclusion The smoke-free law in Tianjin was associated with reductions in AMI mortality. This study reinforces the need for large-scale, effective and comprehensive smoke-free laws at the national level in China.

In the past 20 years, the trends of ischemic heart disease (IHD) mortality in China have been described in divergent claims. This research analyzes mortality trends for IHD by using the data from 102 continuous Disease Surveillance Points (DSP) from 1991 to 2009. The 102 continuous DSP covered 7.3 million people during the period 1991–2000, and then were expanded to a population of 52 million in the same areas for 2004–2009. The data were adjusted by using garbage code redistribution and underreporting rate, mapped from international classification of diseases ICD-9 to ICD-10. The mortality rates for IHD were further adjusted by the crude death proportion multiplied by the total number of deaths in the mortality envelope, which was calculated by using logrt = a + bt. Age-standard death rates (ASDRs) were computed using China’s 2010 census population structure. Trend in IHD was calculated from ASDRs by using a joinpoint regression model. The IHD ASDRs increased in total in regions with an average annual percentage change (AAPC) 4.96%, especially for the Southwest (AAPC = 7.97%) and Northeast areas (AAPC = 7.10%), and for male and female subjects (with 5% AAPC) as well. In rural areas, the year 2000 was a cut-off point for mortality rate with annual percentage change increasing from 3.52% in 1991–2000 to 9.02% in 2000–2009, which was much higher than in urban areas (AAPC = 1.05%). And the proportion of deaths increased in older adults, and more male deaths occurred before age 60 compared to female deaths. By observing a wide range of areas across China from 1991 to 2009, this paper concludes that the ASDR trend for IHD increased. These trends reflect changes in the Chinese standard of living and lifestyle with diets higher in fat, higher blood lipids and increased body weight.

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 30^th, 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.