Impacts of DRG-Based Prepayment Reform on the Cost and Quality of Patients with Neurologic Disorders: Evidence from a Quasi-Experimental Analysis in Beijing, China.

Purpose: As one of the pioneering pilot cities in China's extensive Diagnosis Related Groups (DRG) -based prepayment reform, Beijing is leading a comprehensive overhaul of the prepayment system, encompassing hospitals of varying affiliations and tiers. This systematic transformation is rooted in extensive patient group data, with the commencement of actual payments on March 15, 2022. This study aims to evaluate the effectiveness of DRG payment reform by examining how it affects the cost, volume, and utilization of care for patients with neurological disorders. Patients and Methods: Utilizing the exogenous shock resulting from the implementation of the DRG-based prepayment system, we adopted the Difference-in-Differences (DID) approach to discern changes in outcome variables among DRG payment cases, in comparison to control cases, both before and following the enactment of the DRG policy. The analytical dataset was derived from patients diagnosed with neurological disorders across all hospitals in Beijing that underwent the DRG-based prepayment reform. Strict data inclusion and exclusion criteria, including reasonableness tests, were applied, defining the pre-reform timeframe as March 15th through October 31st, 2021, and the post-reform timeframe as the corresponding period in 2022. The extensive dataset encompassed 53 hospitals and encompassed hundreds of thousands of cases. Results: The implementation of DRG-based prepayment resulted in a substantial 12.6% decrease in total costs per case and a reduction of 0.96 days in length of stay. Additionally, the reform was correlated with significant reductions in overall in-hospital mortality and readmission rates. Surprisingly, the study unearthed unintended consequences, including a significant reduction in the proportion of inpatient cases classified as surgical patients and the Case Mix Index (CMI), indicating potential strategic adjustments by providers in response to the introduction of DRG payments. Conclusion: The DRG payment reform demonstrates substantial effects in restraining cost escalation and enhancing quality. Nevertheless, caution must be exercised to mitigate potential issues such as patient selection bias and upcoding.

Nonoptimum Temperatures Are More Closely Associated With Fatal Myocardial Infarction Than With Nonfatal Events.

BACKGROUND: Ambient temperatures trigger hospitalisation, mortality, and emergency department visits for myocardial infarction (MI). However, nonoptimum temperature-related risks of fatal and nonfatal MI have not yet been compared. METHODS: From 2007 to 2019, 416,894 MI events (233,071 fatal and 183,823 nonfatal) were identified in Beijing, China. A time-series analysis with a distributed-lag nonlinear model was used to compare the relative and population-attributable risks of fatal and nonfatal MI associated with nonoptimum temperatures. RESULTS: The reference was the optimum temperature of 24.3°C. For single-lag effects, cold (-5.2°C) and heat (29.6°C) effects had associations that persisted for more days for fatal MI than for nonfatal MI. For cumulative-lag effects over 0 to 21 days, cold effects were higher for fatal MI (relative risk [RR] 1.99, 95% confidence interval [CI] 1.68-2.35) than for nonfatal MI (RR 1.60, 95% CI 1.32-1.94) with a P value for difference in effect sizes of 0.048. In addition, heat effects were higher for fatal MI (RR 1.33, 95% CI 1.24-1.44) than for nonfatal MI (RR 0.99, 95% CI 0.91-1.08) with a P value for difference in effect sizes of 0.002. The attributable fraction of nonoptimum temperatures was higher for fatal MI (25.6%, 95% CI 19.7%-30.6%) than for nonfatal MI (19.1%, 95% CI 12.1%-25.0%). CONCLUSIONS: Fatal MI was more closely associated with nonoptimum temperatures than nonfatal MI, as evidenced by single-lag effects that have associations which persisted for more days, higher cumulative-lag effects, and higher attributable risks for fatal MI. Strategies are needed to mitigate the adverse effects of nonoptimum temperatures.

Agent-Based Modeling and Simulation (ABMS)on the influence of adjusting medical service fees on patients' choice of medical treatment.

BACKGROUND: We explored the impact of medical service fee adjustments on the choice of medical treatment for hypertensive patients in Beijing. We hope to provide decision-making reference to promote the realization of hierarchical diagnosis and treatment in Beijing. METHODS: According to the framework of modeling simulation research and based on the data of residents and medical institutions in Beijing, we designed three models of residents model, disease model and hospital model respectively. We then constructed a state map of patients' selection of medical treatment and adjusted the medical service fee to observe outpatient selection behaviors of hypertensive patients at different levels of hospitals and to find the optimal decision-making plan. RESULTS: The simulation results show that the adjustment of medical service fees can affect the proportion of patients seeking medical treatment in primary and tertiary hospitals to a certain extent, but has little effect on the proportion of patients receiving medical treatment in secondary hospitals. CONCLUSIONS: Beijing can make adjustments of the current medical service fees by reducing fees in primary hospitals and slightly increasing fees in tertiary hospitals, and in this way could increase the number of patients with hypertension in the primary hospitals.

Causal Associations of Air Pollution With Cardiovascular Disease and Respiratory Diseases Among Elder Diabetic Patients.

Extensive researches have linked air pollutants with cardiovascular disease (CVD) and respiratory diseases (RD), however, there is limited evidence on causal effects of air pollutants on morbidity of CVD or RD with comorbidities, particularly diabetes mellitus in elder patients. We included hospital admissions for CVD or RD among elder (≥65 years) diabetic patients between 2014 and 2019 in Beijing. A time-stratified case-crossover design based on negative-control exposure was used to assess causal associations of short-term exposure to air pollutants with CVD and RD among diabetic patients with the maximum lag of 7 days. A random forest regression model was used to calculate the contribution magnitude of air pollutants. A total of 493,046 hospital admissions were recorded. Per 10 µg/m3 uptick in PM1, PM2.5, PM10, SO2, NO2, O3, and 1 mg/m3 in CO was associated with 0.29 (0.05, 0.53), 0.14 (0.02, 0.26), 0.06 (0.00, 0.12), 0.36 (0.01, 0.70), 0.21 (0.02, 0.40), -0.08 (-0.25, 0.09), and 4.59 (0.56, 8.61) causal effect estimator for admission of CVD among diabetic patients, corresponding to 0.12 (0.05, 0.18), 0.09 (0.05, 0.13), 0.05, 0.23 (0.06, 0.41), 0.10 (0.02, 0.19), -0.04 (-0.06, -0.01), and 3.91(1.81, 6.01) causal effect estimator for RD among diabetic patients. The effect of gaseous pollutants was higher than particulate pollutants in random forest model. Short-term exposure to air pollution was causally associated with increased admission of CVD and RD among elder diabetic patients. Gaseous pollutants had a greater contribution to CVD and RD among elder diabetic patients.

Geographic Variation in Mortality of Acute Myocardial Infarction and Association With Health Care Accessibility in Beijing, 2007 to 2018.

Background Little is known about geographic variation in acute myocardial infarction (AMI) mortality within fast-developing megacities and whether changes in health care accessibility correspond to changes in AMI mortality at the small-area level. Methods and Results We included data of 94 106 AMI deaths during 2007 to 2018 from the Beijing Cardiovascular Disease Surveillance System in this ecological study. We estimated AMI mortality for 307 townships during consecutive 3-year periods with a Bayesian spatial model. Township-level health care accessibility was measured using an enhanced 2-step floating catchment area method. Linear regression models were used to examine the association between health care accessibility and AMI mortality. During 2007 to 2018, median AMI mortality in townships declined from 86.3 (95% CI, 34.2-173.8) to 49.4 (95% CI, 30.5-73.7) per 100 000 population. The decrease in AMI mortality was larger in townships where health care accessibility increased more rapidly. Geographic inequality, defined as the ratio of the 90th to 10th percentile of mortality in townships, increased from 3.4 to 3.8. In total, 86.3% (265/307) of townships had an increase in health care accessibility. Each 10% increase in health care accessibility was associated with a -0.71% (95% CI, -1.08% to -0.33%) change in AMI mortality. Conclusions Geographic disparities in AMI mortality among Beijing townships are large and increasing. A relative increase in township-level health care accessibility is associated with a relative decrease in AMI mortality. Targeted improvement of health care accessibility in areas with high AMI mortality may help reduce AMI burden and improve its geographic inequality in megacities.

Using street view imagery to examine the association between urban neighborhood disorder and the long-term recurrence risk of patients discharged with acute myocardial infarction in central Beijing, China.

Background: To examine the association between urban neighborhood disorder and the recurrence risk of patients with acute myocardial infarction (AMI) in central Beijing, China. Methods: Recurrent AMI was identified by the Beijing Monitoring System for Cardiovascular Diseases through the end of 2019 for patients discharged with AMI between 2007 and 2017. Cox proportional hazards models were performed to estimate associations between neighborhood disorder and AMI recurrence. Results: Of 66,238 AMI patients, 11,872 had a recurrent event, and 3117 died from AMI during a median followup of 5.92 years. After covariate adjustment, AMI patients living in the high tertile of neighborhood disorder had a higher recurrence risk (hazard ratio [HR] 1.08, 95 % confidence interval [CI], 1.03-1.14) compared with those in the low tertile. A stronger association was noted for fatal recurrent AMI (HR 1.21, 95 % CI 1.10-1.34). The association was mainly observed in females (HR 1.04, 95 % CI: 1.02 to 1.06). Conclusions: Serious neighborhood disorder may contribute to higher recurrence risk, particularly fatal recurrence, among AMI patients. Policies to eliminate neighborhood disorders may play an important role in the secondary prevention of cardiovascular disease.

Association between Covid-19 vaccination and incidence of type 1 diabetes in China: Evidence from 14.14 million registered residents between 2007 and 2021.

AIMS: Reports have suggested that COVID-19 vaccination may cause Type 1 diabetes (T1D), particularly fulminant T1D (FT1D). This study aimed to investigate the incidence of T1D in a general population of China, where>90% of the people have received three injections of inactivated SARS-Cov-2 vaccines in 2021. METHODS: A population-based registry of T1D was performed using data from the Beijing Municipal Health Commission Information Center. Annual incidence rates were calculated by age group and gender, and annual percentage changes were assessed using Joinpoint regression. RESULTS: The study included 14.14 million registered residents, and 7,697 people with newly diagnosed T1D were identified from 2007 to 2021. T1D incidence increased from 2.77 in 2007 to 3.84 per 100,000 persons in 2021. However, T1D incidence was stable from 2019 to 2021, and the incidence rate did not increase when people were vaccinated in January-December 2021. The incidence of FT1D did not increase from 2015 to 2021. CONCLUSIONS: The findings suggest that COVID-19 vaccination did not increase the onset of T1D or have a significant impact on T1D pathogenesis, at least not on a large scale.

Short-Term Effects of Carbon Monoxide on Morbidity of Chronic Obstructive Pulmonary Disease With Comorbidities in Beijing.

The association between CO and chronic obstructive pulmonary disease (COPD) has been widely reported; however, the association among patients with type 2 diabetes mellitus (T2DM) or hypertension has remained largely unknown in China. Over-dispersed generalized additive model was adopted to quantity the associations between CO and COPD with T2DM or hypertension. Based on principal diagnosis, COPD cases were identified according to the International Classification of Diseases (J44), and a history of T2DM and hypertension was coded as E12 and I10-15, O10-15, P29, respectively. A total of 459,258 COPD cases were recorded from 2014 to 2019. Each interquartile range uptick in CO at lag 03 corresponded to 0.21% (95%CI: 0.08%-0.34%), 0.39% (95%CI: 0.13%-0.65%), 0.29% (95%CI: 0.13%-0.45%) and 0.27% (95%CI: 0.12%-0.43%) increment in admissions for COPD, COPD with T2DM, COPD with hypertension and COPD with both T2DM and hypertension, respectively. The effects of CO on COPD with T2DM (Z = 0.77, P = 0.444), COPD with hypertension (Z = 0.19, P = 0.234) and COPD with T2DM and hypertension (Z = 0.61, P = 0.543) were insignificantly higher than that on COPD. Stratification analysis showed that females were more vulnerable than males except for T2DM group (COPD: Z = 3.49, P < 0.001; COPD with T2DM: Z = 0.176, P = 0.079; COPD with hypertension: Z = 2.48, P = 0.013; COPD with both T2DM and hypertension: Z = 2.44, P = 0.014); No statistically significant difference could be found between age groups (COPD: Z = 1.63, P = 0.104; COPD with T2DM: Z = 0.23, P = 0.821; COPD with hypertension: Z = 0.53, P = 0.595; COPD with both T2DM and hypertension: Z = 0.71, P = 0.476); Higher effects appeared in cold seasons than warm seasons on COPD (Z = 0.320, P < 0.001). This study demonstrated an increased risk of COPD with comorbidities related to CO exposure in Beijing. We further provided important information on lag patterns, susceptible subgroups, and sensitive seasons, as well as the characteristics of the exposure-response curves.

Predictive model for early functional outcomes following acute care after traumatic brain injuries: A machine learning-based development and validation study.

INTRODUCTION: Few studies on early functional outcomes following acute care after traumatic brain injury (TBI) are available. The aim of this study was to develop and validate a predictive model for functional outcomes at discharge for TBI patients using machine learning methods. PATIENTS AND METHODS: In this retrospective study, data from 5281 TBI patients admitted for acute care who were identified in the Beijing hospital discharge abstract database were analysed. Data from 4181 patients in 52 tertiary hospitals were used for model derivation and internal validation. Data from 1100 patients in 21 secondary hospitals were used for external validation. A poor outcome was defined as a Barthel Index (BI) score ≤ 60 at discharge. Logistic regression, XGBoost, random forest, decision tree, and back propagation neural network models were used to fit classification models. Performance was evaluated by the area under the receiver operating characteristic curve (AUC), the area under the precision-recall curve (AP), calibration plots, sensitivity/recall, specificity, positive predictive value (PPV)/precision, negative predictive value (NPV) and F1-score. RESULTS: Compared to the other models, the random forest model demonstrated superior performance in internal validation (AUC of 0.856, AP of 0.786, and F1-score of 0.724) and external validation (AUC of 0.779, AP of 0.630, and F1-score of 0.604). The sensitivity/recall, specificity, PPV/precision, and NPV of the model were 71.8%, 69.2%, 52.2%, and 84.0%, respectively, in external validation. The BI score at admission, age, use of nonsurgical treatment, neurosurgery status, and modified Charlson Comorbidity Index were identified as the top 5 predictors for functional outcome at discharge. CONCLUSIONS: We established a random forest model that performed well in predicting early functional outcomes following acute care after TBI. The model has utility for informing decision-making regarding patient management and discharge planning and for facilitating health care quality assessment and resource allocation for TBI treatment.

Driving Time to the Nearest Percutaneous Coronary Intervention-Capable Hospital and the Risk of Case Fatality in Patients with Acute Myocardial Infarction in Beijing.

Timely arrival at a hospital capable of percutaneous coronary intervention (PCI) is critical in treating acute myocardial infarction (AMI). We examined the association between driving time to the nearest PCI-capable hospital and case fatality among AMI patients. A total of 142,474 AMI events during 2013-2019 from the Beijing Cardiovascular Disease Surveillance System were included in this cross-sectional study. The driving time from the residential address to the nearest PCI-capable hospital was calculated. Logistic regression was used to estimate the risk of AMI death associated with driving time. In 2019, 54.5% of patients lived within a 15-min drive to a PCI-capable hospital, with a higher proportion in urban than peri-urban areas (71.2% vs. 31.8%, p < 0.001). Compared with patients who had driving times ≤15 min, the adjusted odds ratios (95% CI, p value) for AMI fatality risk associated with driving times 16-30, 31-45, and >45 min were 1.068 (95% CI 1.033-1.104, p < 0.001), 1.189 (95% CI 1.127-1.255, p < 0.001), and 1.436 (95% CI 1.334-1.544, p < 0.001), respectively. Despite the high accessibility to PCI-capable hospitals for AMI patients in Beijing, inequality between urban and peri-urban areas exists. A longer driving time is associated with an elevated AMI fatality risk. These findings may help guide the allocation of health resources.

Causal effect of PM1 on morbidity of cause-specific respiratory diseases based on a negative control exposure.

BACKGROUND: Extensive studies have linked PM2.5 and PM10 with respiratory diseases (RD). However, few is known about causal association between PM1 and morbidity of RD. We aimed to assess the causal effects of PM1 on cause-specific RD. METHODS: Hospital admission data were obtained for RD during 2014 and 2019 in Beijing, China. Negative control exposure and extreme gradient boosting with SHapley Additive exPlanation was used to explore the causality and contribution between PM1 and RD. Stratified analysis by gender, age, and season was conducted. RESULTS: A total of 1,183,591 admissions for RD were recorded. Per interquartile range (28 µg/m3) uptick in concentration of PM1 corresponded to a 3.08% [95% confidence interval (CI): 1.66%-4.52%] increment in morbidity of total RD. And that was 4.47% (95% CI: 2.46%-6.52%) and 0.15% (95% CI: 1.44%-1.78%), for COPD and asthma, respectively. Significantly positive causal associations were observed for PM1 with total RD and COPD. Females and the elderly had higher effects on total RD, COPD, and asthma only in the warm months (Z = 3.03, P = 0.002; Z = 4.01, P < 0.001; Z = 3.92, P < 0.001; Z = 2.11, P = 0.035; Z = 2.44, P = 0.015). Contribution of PM1 ranked first, second and second for total RD, COPD, and asthma among air pollutants. CONCLUSION: PM1 was causally associated with increased morbidity of total RD and COPD, but not causally associated with asthma. Females and the elderly were more vulnerable to PM1-associated effects on RD.

Overall and gender-specific associations between marital status and out-of-hospital coronary death during acute coronary events: a cross-sectional study based on data linkage in Beijing, China.

OBJECTIVES: To assess overall and gender-specific associations between marital status and out-of-hospital coronary death (OHCD) compared with patients surviving to hospital admission. DESIGN: A cross-sectional study based on linkage of administrative health databases. SETTING: Beijing, China. PARTICIPANTS: From 2007 to 2019, 378 883 patients with acute coronary event were identified in the Beijing Monitoring System for Cardiovascular Diseases, a validated city-wide registration system based on individual linkage of vital registration and hospital discharge data. OUTCOME MEASURES: OHCD was defined as coronary death occurring before admission. Multilevel modified Poisson regression models were used to calculate the prevalence ratios (PR) and 95% CIs. RESULTS: Among 378 883 acute coronary events, OHCD accounted for 33.8%, with a higher proportion in women compared with men (41.5% vs 28.7%, p<0.001). Not being married was associated with a higher proportion of OHCD in both genders, with a stronger association in women (PR 2.18, 95% CI 2.10 to 2.26) than in men (PR 1.97, 95% CI 1.91 to 2.02; p for interaction <0.001). The associations of OHCD with never being married (PR 1.98, 95% CI 1.88 to 2.08) and being divorced (PR 2.54, 95% CI 2.42 to 2.67) were stronger in men than in women (never married: PR 0.98, 95% CI 0.82 to 1.16; divorced: PR 1.47, 95% CI 1.34 to 1.61) (p for interaction <0.001 for both). Being widowed was associated with a higher proportion of OHCD in both genders, with a stronger association in women (PR 2.26, 95% CI 2.17 to 2.35) compared with men (PR 1.89, 95% CI 1.84 to 1.95) (p for interaction <0.001). CONCLUSIONS: Not being married was independently associated with a higher proportion of OHCD and the associations differed by gender. Our study may aid the development of gender-specific public health interventions in high-risk populations characterised by marital status to reduce OHCD burden.

Associations between ambient air pollution, meteorology, and daily hospital admissions for ischemic stroke: a time-stratified case-crossover study in Beijing.

Air pollution and ischemic stroke (IS) are both vital factors affecting the health of Beijing citizens. This study aims at exploring the associations between air pollution, meteorology, and the hospital admission of IS (IS HA). Information on 476,659 IS inpatients in secondary and higher hospitals in Beijing from 2013 to 2018 were collected. A time-stratified case-crossover design with the generalized additive model and the distributed lag nonlinear model were used. In the single-pollutant models, an inter-quartile range increase in O3, SO2, CO, and NO2 resulted in a significant highest increase in IS HA by 2.23% (95% CI: 1.56%, 2.90%), 1.53% (95% CI: 1.12%, 1.95%), 1.05% (95% CI: 0.70%, 1.40%), and 0.51% (95% CI: 0.24%, 0.79%) on the day of pollution, so did PM2.5 and PM10 by 1.13% (95% CI: 0.68%, 1.59%) and 1.19% (95% CI: 0.74%, 1.64%) at a lag of 0-5 days. There was a nonlinear relationship between meteorology and IS HA. In the multivariate model, the cumulative relative risks with a maximum lag time of 21 days of PM2.5 and NO2 were 1.11 (95% CI: 1.04, 1.19) and 0.88 (95% CI: 0.82, 0.94), while the effects of SO2, O3, and meteorology were insignificant. The findings suggested that particulate pollutants could increase the risk of IS, and the elderly were more sensitive to it, while the results of gaseous pollutants are still discordant. The control of air pollution and the protection of susceptible populations should receive higher attention from policymakers.

Acute effect of air pollutants' peak-hour concentrations on ischemic stroke hospital admissions among hypertension patients in Beijing, China, from 2014 to 2018.

Air pollutants' effect on ischemic stroke (IS) has been widely reported. But the effect of high-level concentrations during people's outdoor periods among hypertension patients was unknown. Peak-hour concentrations were defined considering air pollutants' high concentrations as well as people's outdoor periods. We conducted a time-series study and used the generalized additive model to analyze peak-hour concentrations' acute effect. A total of 315,499 IS patients comorbid with hypertension were admitted to secondary and above hospitals in Beijing from 2014 to 2018. A 10 µg/m3 (CO: 1 mg/m3) increase of the peak-hour concentrations was positively associated with IS hospital admissions among hypertension patients. The maximum effect sizes were as follows: for PM2.5, 0.17% (95% confidence interval [CI]: 0.10-0.24%) at Lag0 and 0.22% (95% CI: 0.12-0.33%) at Lag0-5; for PM10, 0.09% (95% CI: 0.05-0.13%) at Lag5 and 0.17% (95% CI: 0.09-0.26%) at Lag0-5; for SO2, 0.87% (95% CI: 0.46-1.29%) at Lag5; for NO2, 0.83% (95% CI: 0.62-1.04%) at Lag0 and 0.86% (95% CI: 0.59-1.13%) at Lag0-1; for CO 1.23% (95% CI: 0.66-1.80%) at Lag0 and 1.33% (95% CI: 0.33-2.35%) at Lag0-5; for O3 0.23% (95% CI: 0.12-0.35%) at Lag0 and 0.20% (95% CI: 0.05-0.34%) at Lag0-1. The effect sizes of PM2.5, NO2, and O3 remained significant after adjusting daily mean. Larger effect sizes were observed for PM2.5 and PM10 in cool season and for O3 in warm season. As significant exposure indicators of air pollution, peak-hour concentrations exposure increased the risk of IS hospital admissions among hypertension patients and it is worthy of consideration in relative environmental standard. It is suggested for hypertension patients to avoid outdoor activity during peak hours. More relevant searches are required to further illustrate air pollutant's effect on chronic disease population.

The association between ozone and ischemic stroke morbidity among patients with type 2 diabetes in Beijing, China.

BACKGROUND: The association between ozone and ischemic stroke has been widely reported; however, the association among patients with type 2 diabetes (T2D) has remained largely unknown. METHODS: The time series data of daily morbidity and concentrations of ozone from 2014 to 2018 were collected in Beijing, China. A time-stratified case-crossover study combined with a distributed lag nonlinear model was used to estimate the ozone effect on stroke morbidity among T2D patients. Based on principal diagnosis, ischemic stroke cases were identified according to the International Classification of Diseases (I63), and a history of T2D was coded as E12. RESULTS: A total of 149,757 hospital admissions for ischemic stroke among T2D patients were recorded in Beijing. Approximately U-shaped exposure-response curves were observed for ozone and ischemic stroke morbidity among T2D patients. With a reference at 54.91 µg/m3, extreme-low (5th: 9.59 µg/m3) ozone was significantly associated with a decreased risk for ischemic stroke [RR = 0.88, 95% confidence interval (CI): 0.80-0.98]. Subgroup analysis showed that extremely low-ozone (5th) level only had a significant protective effect in males and elderly population, with a RR value of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.96), respectively. Extreme-high ozone (99th: 157.06 µg/m3) was significantly associated with an increased risk for ischemic stroke (RR = 1.33, 95% CI: 1.12-1.57). The effect size was 1.34 (95% CI: 1.10-1.63) for males and 1.32 (95% CI: 1.07-1.63) for females, and the difference was not significant (Z = -0.29, P = 0.77). The effect size in younger adults was significantly higher than that in participants aged ≥65 years [1.52 (95% CI: 1.21-1.91) vs. 1.22 (95% CI: 1.01-1.47), Z = -1.62, P < 0.05]. CONCLUSIONS: U-shaped associations were observed between ozone and ischemic stroke morbidity in T2D patients. Men and elderly population are vulnerable to low-ozone level, and the younger adults are more susceptible to extremely high-ozone level than the elderly.

Impact of COVID-19 Pandemic on Hospital Admissions of Acute Coronary Syndrome: A Beijing Inpatient Database Study.

BACKGROUND: Consequences of reduced acute coronary syndrome (ACS) admissions during COVID-19 pandemic periods were reported by different countries. However, admissions, treatments, and prognosis of ACS during and after COVID-19 pandemic in Beijing, China was unknown. METHODS: Information on ACS admissions and heart failure (HF) admission were identified from database of Beijing Municipal Health Commission Information Center. Study period was defined as December 1, 2019 to June 30, 2020, and control period was defined as December 1, 2018 to June 30, 2019. Numbers of admission for HF during the control period, the study period, and seven months after study period were compared to evaluate the consequence of changed ACS care during the COVID-19 pandemic. FINDINGS: Admissions for ST-elevation myocardial infarction (STEMI), Non-ST-elevation myocardial infarction (Non-STEMI), and unstable angina (UAP) reduced by 38·0%, 41·0%, and 63·3% (N = 1953, 1991, 7664 between January 24, 2020 to June 30, 2020 vs. N = 3150, 3373, and 20,868 between January 24, 2019 to June 30, 2019) in study period. Percutaneous coronary intervention performed within 24 h were significantly more frequent during study period in patients with STEMI (37·9% vs. 31·7%, P<0·0001), but significantly less frequent in patients with Non-STEMI (7·9% vs. 9·5%, P = 0·049), and in patients with UAP (1·7% vs. 3·5%, P<0·0001). In-hospital mortality rates in patients with ACS were similar during the study period and the control period (3·1% vs 2·5%, P = 0·174 for STEMI; 2·7% vs 2·3%, P = 0·429 for Non-STEMI; 0·2% vs 0·1%, P = 0·222 for UAP). A fall by 23.9% for HF admissions was also observed during the seven months following the study period than equivalent period in 2019. INTERPRETATION: During COVID-19 pandemic, ACS admissions reduced significantly in Beijing; however, increase of HF admissions was not observed within seven months post-pandemic period, implying the pandemic didn't deteriorate the short-term prognosis for ACS. FUNDING: the National Natural Science Foundation of China (82,103,904), the National Key Research and Development Program of China (Grant number: 2020YFC2004803).

Trends and Inequalities in the Incidence of Acute Myocardial Infarction among Beijing Townships, 2007-2018.

Acute myocardial infarction (AMI) poses a serious disease burden in China, but studies on small-area characteristics of AMI incidence are lacking. We therefore examined temporal trends and geographic variations in AMI incidence at the township level in Beijing. In this cross-sectional analysis, 259,830 AMI events during 2007-2018 from the Beijing Cardiovascular Disease Surveillance System were included. We estimated AMI incidence for 307 consistent townships during consecutive 3-year periods with a Bayesian spatial model. From 2007 to 2018, the median AMI incidence in townships increased from 216.3 to 231.6 per 100,000, with a greater relative increase in young and middle-aged males (35-49 years: 54.2%; 50-64 years: 33.2%). The most pronounced increases in the relative inequalities was observed among young residents (2.1 to 2.8 for males and 2.8 to 3.4 for females). Townships with high rates and larger relative increases were primarily located in Beijing's northeastern and southwestern peri-urban areas. However, large increases among young and middle-aged males were observed throughout peri-urban areas. AMI incidence and their changes over time varied substantially at the township level in Beijing, especially among young adults. Targeted mitigation strategies are required for high-risk populations and areas to reduce health disparities across Beijing.

Acute effect of particulate matter pollution on hospital admissions for cause-specific respiratory diseases among patients with and without type 2 diabetes in Beijing, China, from 2014 to 2020.

BACKGROUND: Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. METHODS: A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM2.5 and PM10 were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. RESULTS: A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM2.5 corresponded to 1.91% (95% CI: 1.33-2.49%), 2.16% (95% CI: 1.08-3.25%), and 1.92% (95% CI: 1.46-2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0-8 days, lag 8 days, and lag 8 days. The effect size of PM2.5 was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P < 0.01). The effect sizes of PM10 were 3.86% (95% CI: 2.48-5.27%), 3.73% (95% CI: 1.72-5.79%), and 3.92% (95% CI: 2.65-5.21%), respectively, at lag 0-13 days, lag 13 days, and lag 13 days, respectively, and no statistically significant difference was observed between T2D groups (z = 0.24, P = 0.81). Significant difference was not observed between T2D groups for the associations of PM and different RD and could be found between three groups for effects of PM10 on RD without T2D. The E-R curves varied by sex, age and T2D condition subgroups for the associations between PM and daily RD admissions. CONCLUSIONS: Short-term PM exposure was associated with increased RD admission with and without T2D, and the effect size of PM2.5 was higher in patients with T2D than those without T2D.

Risk of Cardiovascular Hospital Admission After Exposure to Fine Particulate Pollution.

BACKGROUND: Heavy fine particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) pollution events continue to occur frequently in developing countries. OBJECTIVES: The authors conducted a case-crossover study aimed at exploring the association between heavy PM2.5 pollution events and hospital admission for cardiovascular diseases. METHODS: Hospital admissions for cardiovascular diseases were observed by Beijing Municipal Commission of Health and Family Planning Information Center from 2013 to 2017. Air pollution data were collected from the Beijing Municipal Environmental Monitoring Center. Distinct definitions were used to identify heavy and extremely heavy fine particulate pollution events. A conditional logistic regression model was used. The hospital admission burdens for cardiovascular disease were also estimated. RESULTS: A total of 2,202,244 hospital admissions for cardiovascular diseases and 222 days of extremely heavy PM2.5 pollution events (PM2.5 concentration ≥150 µg/m3) were observed. The ORs associated with extremely heavy PM2.5 pollution events lasting for 3 days or more for total cardiovascular disease, angina, myocardial infarction, ischemic stroke, and heart failure were 1.085 (95% CI: 1.077-1.093), 1.112 (95% CI: 1.095-1.130), 1.068 (95% CI: 1.037-1.100), 1.071 (95% CI: 1.053-1.090), and 1.060 (95% CI: 1.021-1.101), respectively. The numbers and days of cardiovascular disease hospital admission annually related to extremely heavy PM2.5 pollution events lasting for 1 day or more were 3,311 (95% CI: 2,969-3,655) and 37,020 (95% CI: 33,196-40,866), respectively. CONCLUSIONS: Heavy and extremely heavy PM2.5 pollution events resulted in substantial increased hospital admission risk for cardiovascular disease. With higher PM2.5 concentration and longer duration of heavy PM2.5 pollution events, a greater risk of cardiovascular hospital admission was observed.