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.

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.

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.

A sequence analysis of hospitalization patterns and service utilization in patients with major psychiatric disorders in China.

BACKGROUND: Understanding the long-term inpatient service cost and utilization of psychiatric patients may provide insight into service demand for these patients and guide the design of targeted mental health programs. This study assesses 3-year hospitalization patterns and quantifies service utilization intensity of psychiatric patients in Beijing, China. METHODS: We identified patients admitted for one of three major psychiatric disorders (schizophrenia, bipolar and depressive disorders) between January 1 and December 31, 2013 in Beijing, China. Inpatient admissions during the following 3 years were extracted and analyzed using sequence analysis. Clinical characteristics, psychiatric and non-psychiatric service use of included patients were analyzed. RESULTS: The study included 3443 patients (7657 hospitalizations). The patient hospitalization sequences were grouped into 4 clusters: short stay (N = 2741 (79.61% of patients), who had 126,911 or 26.82% of the hospital days within the sample), repeated long stay (N = 404 (11.73%), 76,915 (16.26%) days), long-term stay (N = 101 (2.93%), 59,909 (12.66%) days) and permanent stay (N = 197 (5.72%), 209,402 (44.26%) days). Length and frequency of hospitalization, as well as readmission rates were significantly different across the 4 clusters. Over the 3-year period, hospitalization days per year decreased for patients in the short stay and repeated long stay clusters. Patients with schizophrenia (1705 (49.52%)) had 78.4% of cumulative psychiatric stays, with 11.14% of them in the permanent stay cluster. Among patients with depression, 23.11% had non-psychiatric hospitalizations, and on average 46.65% of their total inpatient expenses were for non-psychiatric care, the highest among three diagnostic groups. CONCLUSION: Hospitalization patterns varied significantly among psychiatric patients and across diagnostic categories. The high psychiatric care service use of the long-term and permanent stay patients underlines the need for evidence-based interventions to reduce cost and improve care quality.

Acute effect of particulate matter pollution on hospital admissions for stroke among patients with type 2 diabetes in Beijing, China, from 2014 to 2018.

BACKGROUND: The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown. METHODS: A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM2.5) and inhalable particulate matter (PM10) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends. RESULTS: A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM2.5 and PM10 in relation to stroke admissions among T2D patients. A 10 µg/m3 increase in the four-day moving average of PM2.5 and PM10 was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 µg/m3 increase in PM2.5 in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 µg/m3 increase in PM10 in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke. CONCLUSIONS: High particulate matter might be a risk factor for stroke among patients with T2D. PM2.5 and PM10 have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.

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.

Short-term effects of extreme temperatures on cause specific cardiovascular admissions in Beijing, China.

Extreme temperature-related cardiovascular diseases (CVDs) have become a growing public health concern. However, the impact of temperature on the cause of specific CVDs has not been well studied in the study area. The objective of this study was to assess the impact of temperature on cause-specific cardiovascular hospital admissions in Beijing, China. We obtained data from 172 large general hospitals from the Beijing Public Health Information Center Cardiovascular Case Database and China. Meteorological Administration covering 16 districts in Beijing from 2013 to 2017. We used a time-stratified case crossover design with a distributed lag nonlinear model (DLNM) to derive the impact of temperature on CVD in hospitals back to 27 days on CVD admissions. The temperature data were stratified as cold (extreme and moderate ) and hot (moderate and extreme ). Within five years (January 2013-December 2017), a total of 460,938 (male 54.9% and female 45.1%) CVD admission cases were reported. The exposure-response relationship for hospitalization was described by a "J" shape for the total and cause-specific. An increase in the six-day moving average temperature from moderate hot (30.2 °C) to extreme hot (36.9 °C) resulted in a significant increase in CVD admissions of 16.1%(95% CI = 12.8%-28.9%). However, the effect of cold temperature exposure on CVD admissions over a lag time of 0-27 days was found to be non significant, with a relative risk of 0.45 (95% CI = 0.378-0.55) for extreme cold (-8.5 °C)and 0.53 (95% CI = 0.47-0.60) for moderate cold (-5.6 °C). The results of this study indicate that exposure to extremely high temperatures is highly associated with an increase in cause-specific CVD admissions. These finding may guide to create and raise awareness of the general population, government and private sectors regarding on the effects of current weather conditions on CVD.

Factors associated with 30-day and 1-year readmission among psychiatric inpatients in Beijing China: a retrospective, medical record-based analysis.

BACKGROUND: Psychiatric readmissions negatively impact patients and their families while increasing healthcare costs. This study aimed at investigating factors associated with psychiatric readmissions within 30 days and 1 year of the index admissions and exploring the possibilities of monitoring and improving psychiatric care quality in China. METHODS: Data on index admission, subsequent admission(s), clinical and hospital-related factors were extracted in the inpatient medical record database covering 10 secondary and tertiary psychiatric hospitals in Beijing, China. Logistic regressions were used to examine the associations between 30-day and 1-year readmissions plus frequent readmissions (≥3 times/year), and clinical variables as well as hospital characteristics. RESULTS: The 30-day and 1-year psychiatric readmission rates were 16.69% (1289/7724) and 33.79% (2492/7374) respectively. 746/2492 patients (29.34%) were readmitted 3 times or more within a year (frequent readmissions). Factors significantly associated with the risk of both 30-day and 1-year readmission were residing in an urban area, having medical comorbidities, previous psychiatric admission(s), length of stay > 60 days in the index admission and being treated in tertiary hospitals (p < 0.001). Male patients were more likely to have frequent readmissions (OR 1.30, 95%CI 1.04-1.64). Receiving electroconvulsive therapy (ECT) was significantly associated with a lower risk of 30-day readmission (OR 0.72, 95%CI 0.56-0.91) and frequent readmissions (OR 0.60, 95%CI 0.40-0.91). CONCLUSION: More than 30% of the psychiatric inpatients were readmitted within 1 year. Urban residents, those with medical comorbidities and previous psychiatric admission(s) or a longer length of stay were more likely to be readmitted, and men are more likely to be frequently readmitted. ECT treatment may reduce the likelihood of 30-day readmission and frequent admissions. Targeted interventions should be designed and piloted to effectively monitor and reduce psychiatric readmissions.

Hospitalization Pattern, Inpatient Service Utilization and Quality of Care in Patients With Alcohol Use Disorder: A Sequence Analysis of Discharge Medical Records.

AIMS: To identify and group hospitalization trajectory of alcohol use disorder (AUD) patients and its associations with service utilization, healthcare quality and hospital-level variations. METHODS: Inpatients with AUD as the primary diagnosis from 2012 to 2014 in Beijing, China, were identified. Their discharge medical records were extracted and analyzed using the sequence analysis and the cluster analysis. RESULTS: Eight-hundred thirty-one patients were included, and their hospitalization patterns were grouped into four clusters: short stay (n = 565 (67.99%)), mean psychiatric length of stay in 3 years: (32.25 ± 18.69), repeated short stay (n = 211 (25.39%), 137.76 ± 88.8 days), repeated long stay (n = 41 (4.93%), 405.44 ± 146.54 days), permanent stay (n = 14 (1.68%), 818.14 ± 225.22 days). The latter two clusters (6.61% patients) used 37.26% of the total psychiatric hospital days and 33.65% of the total psychiatric hospitalization expenses. All the patients in the permanent stay cluster and 41.77% of the patients in the short stay cluster were readmitted at least once within 3 years. Two-hundred thirty-four patients (28.16%) were admitted at least once for non-psychiatric reasons, primarily for diseases of circulatory and digestive systems. Cluster composition varied significantly among different hospitals. CONCLUSION: Hospitalization pattern of patients with AUD varies greatly, and while most (>2/3) hospitalizations were short stay, those with repeated long stay and permanent stay used more than one third of the hospital days and expenses. Our findings suggest interventions targeting at certain patients may be more effective in reducing resource utilization.

[Meta-analysis of acute health effects caused by atmospheric particulate matter and the implementation with R software].

OBJECTIVE: To introduce the Meta-analysis of acute health effects caused by atmospheric particulate matter and explore the R software implementation. METHODS: Used literature data as an example, pooled the risk estimates of mortality due to respiratory disease exposure to PM_(10) in the Chinese population from 1990 to 2013 using R software. RESULTS: The overall risk estimates RR was 1. 0041(95% CI 1. 0028-1. 0054), there was publication bias, the RR was reduced to 1. 0015(95%CI 1. 0002-1. 0029)after adjust the asymmetry with the trim-and-fill method. CONCLUSION: R software has relatively abundant software packages to conduct the Meta-analysis for assessing the acute health impact exposure to atmospheric particulate matter.

[Changes of hospitalization rates and in-hospital mortality for coronary heart disease in Beijing from 2007-2012].

OBJECTIVE: To observe the changes of hospitalization rates and in-hospital mortality for coronary heart disease (CHD) in Beijing from 2007-2012. METHODS: Patients hospitalized for CHD in Beijing from 1 January 2007 to 31 December 2012 were identified from"The Cardiovascular Disease Surveillance System in Beijing". In total, 421 929 patients aged ≥25 years of permanent Beijing residents were admitted for CHD in Beijing during the 6 years. After excluding duplicate records and validation for the completeness and accuracy of the records, the hospitalization rates for CHD and in-hospital CHD mortality were analyzed. Trends in hospitalization rates and the in-hospital mortality for CHD were analyzed with Poisson regression models. RESULTS: The age-standardized average hospitalization rate of CHD was 515.3 per 100 000 population in patients aged ≥25 years in Beijing. During the six years, an increasing trend was observed in the hospitalization rates for CHD after adjusting the age and gender (P<0.001). The age-standardized hospitalization rates of CHD increased by 43.0% in the past six years. The greatest increases of hospitalization rates were noted in both men and women between 45 to 54 years. The age-standardized in-hospital mortality decreased from 3.3% to 2.2% over the time (P<0.001), with a in-hospital mortality reduction for acute myocardial infarction from 11.3% to 8.5%. CONCLUSIONS: An increasing trend in hospitalization rate was observed during 2007-2012 for Beijing residents aged ≥25 years, indicating an urgent need in CHD prevention in Beijing. The in-hospital mortality reduction during this period might reflect the improvement in the in-hospital treatment modalities of CHD.

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.

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.

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.

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.

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.

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.

[Hospitalization rates for coronary heart disease from 2007 to 2009 in Beijing].

OBJECTIVE: To examine the distribution and trends of hospitalization rates for coronary heart disease (CHD) from 2007 to 2009 in Beijing. METHODS: We calculated hospitalization rates for CHD using data from Beijing Hospital Discharge Information System. Information of census registered population in Beijing was obtained from Beijing Municipal Bureau of Statistics. CHD includes acute myocardial infarction, unstable angina and other forms of CHD. Age-standardized hospitalization rates for CHD per 100 000 population aged 25 years or more were calculated. RESULTS: During 2007 - 2009, a total of 248 049 patients aged 25 years or more hospitalized in Beijing with the primary discharge diagnosis of CHD were enrolled, of whom 73.7% were permanent registered Beijing citizens. The average hospitalization rate for CHD in 2007 - 2009 was 651.2/100 000 for the permanent residences in Beijing (741.2/100 000 in men, 560.9/100 000 in women). The highest average hospitalization rate (671.9/100 000) was seen in exurban area compared to other areas in Beijing. The average hospitalization rate for acute myocardial infarction, unstable angina, and other CHD was 126.4/100 000, 226.4/100 000 and 298.4/100 000, respectively. The hospitalization rate for CHD increased 18.1% from 2007 to 2009 (from 598.1/100 000 to 706.5/100 000). The same trend was seen in women (20.2%) and men (16.6%). The hospitalization rates of CHD in the urban, suburban, and exurban areas of Beijing all increased in the three years, and the greatest increase (36.6%) was found in exurban area. Hospitalization rates of acute myocardial infarction and unstable angina increased 24.5% and 55.3%, respectively, in the three years, while hospitalization rates of other CHD decreased 5.7%. CONCLUSIONS: The hospitalization rate of CHD is higher in men than in women in Beijing. The hospitalization rates for CHD increased from the observation period, especially in those living in exurban area. Awareness of the magnitudes and trends of CHD hospitalization rates is of great importance in evaluating the burden of cardiovascular disease, allocating and utilizing health care resources, and estimating the health insurance for Beijing.