Ambient particulate matter pollution of different sizes associated with recurrent stroke hospitalization in China: A cohort study of 1.07 million stroke patients

Geospatial analysis of short-term exposure to air pollution and risk of cardiovascular diseases and mortality-A systematic review

The cardiovascular risk associated with short-term ambient air pollution exposure is well-documented. However, recent advancements in geospatial techniques have provided new insights into this risk. This systematic review focuses on short-term exposure studies that applied advanced geospatial pollution modelling to estimate cardiovascular disease (CVD) risk and accounted for additional unconventional neighbourhood-level confounders to analyse their modifier effect on the risk. Four databases were investigated to select publications between 2018 and 2023 that met the inclusion criteria of studying the effect of particulate matter (PM2.5 and PM10), SO2, NOx, CO, and O3 on CVD mortality or morbidity, utilizing pollution modelling techniques, and considering spatial and temporal confounders. Out of 3277 publications, 285 were identified for full-text review, of which 34 satisfied the inclusion criteria for qualitative analysis, and 12 of them were chosen for additional quantitative analysis. Quality assessment revealed that 28 out of 34 included articles scored 4 or above, indicating high quality. In 30 studies, advanced pollution modelling techniques were used, while in 4 only simpler methods were applied. The most pertinent confounders identified were socio-demographic variables (e.g., socio-economic status, population percentage by race or ethnicity) and neighbourhood-level built environment variables (e.g., urban/rural area, percentage of green space, proximity to healthcare), which exhibited varying modifier effects depending on the context. In the quantitative analysis, only PM 2.5 showed a significant positive association to all-cause CVD-related hospitalisation. Other pollutants did not show any significant effect, likely due to the high inter-study heterogeneity and a limited number of cases. The application of advanced geospatial measurement and modelling of air pollution exposure, as well as its risk, is increasing. This review underscores the importance of accounting for unconventional neighbourhood-level confounders to enhance the understanding of the CVD risk associated with short-term pollution exposure.

Modifying effects of green space on the relationships between air pollution and ischemic cerebrovascular event recurrence in Tianjin, China

This study aimed to explore how air pollution and green space influence ICE recurrence and whether they might interact with each other. A case-cross design was used in this study, which was carried out in Tianjin, China. A total of 8306 patients with recurrent ICE were collected from 2019 to 2020. The maximum effects of PM2.5, PM10, SO2, NO2, CO were 1.012 (95%CI: 1.004, 1.019), 1.010 (95%CI: 1.004, 1.016), 1.035 (95%CI: 0.982, 1.091), 1.067 (95%CI: 1.043, 1.091) and 1.012 (95%CI: 1.004, 1.021)  , respectively, and the risk was higher in males and in the 50-60 age group. In the stratification of greening, it was found that air pollution except O3 had the highest risk of ICE recurrence for those with lower green space. Our study found that air pollution (except O3) can increase the risk of ICE recurrence, and this risk can be reduced by increasing green space.

Associations between air pollution and the risk of first admission and multiple readmissions for cardiovascular diseases

OBJECTIVES

We aimed to investigate the associations between air pollutants and the risk of admission and multiple readmission events for cardiovascular disease (CVD).

METHODS

A total of 285 009 participants free of CVD at baseline from the UK Biobank were included in this analysis. Four major cardiovascular admission events were identified during the follow-up: chronic ischaemic heart disease (CIHD), cerebrovascular disease, atrial fibrillation and heart failure. We used Prentice, Williams and Peterson-Total Time model to examine the association between ambient air pollution and first admission, as well as multiple readmissions for these CVDs.

RESULTS

During a median follow-up of 12 years, 17 176 (6.03%) participants were hospitalised with CVDs, and 6203 (36.11%) patients with CVD had subsequent readmission events for CVDs. We observed significant associations between air pollution and both first admission and readmission for CVDs, with generally stronger associations on readmission for cardiovascular events. For example, the adjusted HRs for the first admission and subsequent readmission for cerebrovascular disease were 1.130 (95% CI 1.070 to 1.194) and 1.270 (95% CI 1.137 to 1.418) for each IQR increase of particulate matter with a diameter ≤2.5 µm. The corresponding HRs for CIHD were 1.060 (95% CI 1.008 to 1.114) and 1.120 (95% CI 1.070 to 1.171). Sex stratified analyses showed that the associations were generally more pronounced among females than males.

CONCLUSION

This study provides evidence that ambient air pollutants might play an important role in both first admission and readmission for cardiovascular events. In addition, patients with pre-existing CVDs may be more vulnerable to air pollution compared with healthy population.

Ambient fine particulate matter chemical composition associated with in-hospital case fatality, hospital expenses, and length of hospital stay among patients with heart failure in China

*Joint senior authorship.

BACKGROUND

Previous studies have observed the adverse effects of ambient fine particulate matter pollution (PM2.5) on heart failure (HF). However, evidence regarding the impacts of specific PM2.5 components remains scarce.

METHODS

We included 58 129 patients hospitalised for HF between 2013 and 2017 in 11 cities of Shanxi, China from inpatient discharge database. We evaluated exposure to PM2.5 and its components ((sulphate (SO42-), nitrate (NO3-), ammonium (NH4+), organic matter (OM) and black carbon (BC)), along with meteorological factors using bilinear interpolation at each patients' residential address. We used multivariable logistic and linear regression models to assess the associations of these components with in-hospital case fatality, hospital expenses, and length of hospital stay.

RESULTS

Increase equivalents to the interquartile range (IQR) in OM (odds ratio (OR) = 1.13; 95% confidence interval (CI) = 1.02, 1.26) and BC (OR = 1.14; 95% CI = 1.02, 1.26) were linked to in-hospital case fatality. Per IQR increments in PM2.5, SO42-, NO3-, OM, and BC were associated with cost increases of 420.62 (95% CI = 285.75, 555.49), 221.83 (95% CI = 96.95, 346.71), 214.93 (95% CI = 68.66, 361.21), 300.06 (95% CI = 176.96, 423.16), and 303.09 (95% CI = 180.76, 425.42) CNY. Increases of 1 IQR in PM2.5, SO42-, OM, and BC were associated with increases in length of hospital stay of 0.10 (95% CI = 0.02, 0.19), 0.09 (95% CI = 0.02, 0.17), 0.10 (95% CI = 0.03, 0.17), and 0.16 (95% CI = 0.08, 0.23) days.

CONCLUSIONS

Our findings suggest that ambient SO42-, OM, and BC might be significant risk factors for HF, emphasising the importance of formulating customised guidelines for the chemical constituents of PM and controlling the emissions of the most dangerous components.

Predicting preterm birth using auto-ML frameworks: a large observational study using electronic inpatient discharge data

Background

To develop and compare different AutoML frameworks and machine learning models to predict premature birth.

Methods

The study used a large electronic medical record database to include 715,962 participants who had the principal diagnosis code of childbirth. Three Automatic Machine Learning (AutoML) were used to construct machine learning models including tree-based models, ensembled models, and deep neural networks on the training sample (N = 536,971). The area under the curve (AUC) and training times were used to assess the performance of the prediction models, and feature importance was computed via permutation-shuffling.

Results

The H2O AutoML framework had the highest median AUC of 0.846, followed by AutoGluon (median AUC: 0.840) and Auto-sklearn (median AUC: 0.820), and the median training time was the lowest for H2O AutoML (0.14 min), followed by AutoGluon (0.16 min) and Auto-sklearn (4.33 min). Among different types of machine learning models, the Gradient Boosting Machines (GBM) or Extreme Gradient Boosting (XGBoost), stacked ensemble, and random forrest models had better predictive performance, with median AUC scores being 0.846, 0.846, and 0.842, respectively. Important features related to preterm birth included premature rupture of membrane (PROM), incompetent cervix, occupation, and preeclampsia.

Conclusions

Our study highlights the potential of machine learning models in predicting the risk of preterm birth using readily available electronic medical record data, which have significant implications for improving prenatal care and outcomes.

Ambient particulate matter and in-hospital case fatality of acute myocardial infarction: A multi-province cross-sectional study in China

The acute myocardial infarction (AMI) outcomes have been extensively linked with ambient particulate matter (PM). However, whether a smaller particle has greater impact and the consequent attributable burden associated with PM of different sizes remain unclear. We conducted a multi-province cross-sectional study among AMI patients using the inpatient discharge datasets from four Chinese provinces (Shanxi, Sichuan, Guangxi, and Guangdong) from 2014 to 2019. Ambient PM exposure for each patient was assessed using the ChinaHighAirPollutants dataset. We employed the mixed-effects logistic regression models to evaluate the association of PM of different sizes (PM1, PM2.5, PM10) on in-hospital case fatality. The potential reducible fractions in in-hospital case fatality were estimated through counterfactual analyses. Of 177,749 participants, 125,501 (70.6 %) were male and the in-hospital case fatality rate was 4.9%. For short-term (7-day average) exposure, the odds ratios (ORs) for PM1, PM2.5, and PM10 (per 10 µg/m3) were 1.052 (95 % confidence interval [CI], 1.032-1.071), 1.026 (95 % CI, 1.014-1.037), and 1.016 (95% CI, 1.008-1.024), respectively. The estimated ORs for long-term exposure (annual average) were 1.303 (95 % CI, 1.252-1.356) for PM1, 1.209 (95 % CI, 1.178-1.241) for PM2.5, 1.157 (95 % CI, 1.134-1.181) for PM10. Short-term exposure to PM1 showed the highest potential reducible fraction (8.5 %, 95 % CI, 5.0-11.7 %), followed by PM2.5 and PM10, while the greatest potential reducible fraction of long-term exposure was observed in PM10 (30.9 %, 95 % CI, 27.2-34.4%), followed by PM2.5 and PM1. In summary, PM with smaller size had a more pronounced impact on in-hospital AMI case fatality, with PM1 exhibiting greater effects than PM2.5 and PM10. Substantial health benefits for AMI patients could be achieved by mitigating ambient PM exposure.

Short-Term Ambient Air Pollution and Urticaria in Guangzhou, China: Estimating the Association and Population Attributable Fraction

Limited evidence is available regarding the association between acute exposure to ambient air pollutants and the risk of urticaria, even though the skin is an organ with direct contact with the external environment. This study utilized generalized additive models to investigate the association between particulate matter with an aerodynamic diameter smaller than 10 μm (PM10) and 2.5 μm (PM2.5), nitrogen dioxide (NO2) and sulfur dioxide (SO2), and daily outpatient visits for urticaria in Guangzhou, China from 2013 to 2017. We also estimated the attributable fraction of urticaria outpatient visits due to air pollution. A total of 216,648 outpatient visits due to urticaria occurred during the study period. All air pollutants were significantly associated with an increased excess risk of urticaria. Each 10 μg/m3 increase in PM2.5, PM10, NO2, and SO2 was associated with an increase of 1.23% (95% CI: 0.42%, 2.06%), 0.88% (95% CI: 0.28%, 1.49%), 3.09% (95% CI: 2.16%, 4.03%), and 2.82% (95% CI: 0.93%, 4.74%) in hospital visits for urticaria at lag05, respectively. It was estimated that 3.77% (95% CI: 1.26%, 6.38%), 1.91% (95% CI: 0.60%, 3.26%), 6.36% (95% CI: 4.38%, 8.41%), and 0.08% (95% CI: 0.03%, 0.14%) of urticaria outpatient visits were attributable to PM2.5, PM10, NO2, and SO2 using the World Health Organization's air quality guideline as the reference. Relatively stronger associations were observed during the cold season. This study indicates that short-term air pollution may play a significant role in outpatient visits for urticaria, and that such relationships could be modified by season.

China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment

Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.

Associations of Life's Essential 8 and fine particulate matter pollution with the incidence of atrial fibrillation

Both unhealthy lifestyle factors and ambient air pollution have been closely linked with the risk of atrial fibrillation (AF). We retrieved 250,898 participants without AF at baseline from UK Biobank. LE8 was determined by 8 metrics, and was characterized as low, moderate and high cardiovascular health (CVH). Exposure to PM2.5 was estimated at the geocoded residential address of each participant. During a median follow-up of 12.46 years, we identified 14,743 (5.9%) incident AF cases. Participants with moderate and high CVH showed a decreased risk of incident AF compared to those with low CVH. Of the LE8 metrics, ideal body mass index (BMI) and blood pressure (BP) were associated with a decrease of 11.57% and 11.46% AF cases. High PM2.5 exposure was associated with an 8% increased risk of AF as compared to low PM2.5 exposure. Compared with those who had low CVH and high PM2.5 exposure, participants with a high CVH and low PM2.5 exposure had the lower AF incidence. Our study found higher CVH is protective, while higher PM2.5 might be one risk factor of AF. Adherence to the LE8 guidelines may help reduce the incidence of AF, especially in those with lower PM2.5 exposure.

Impact of Environmental Factors on Hypertension and Associated Cardiovascular Disease

Hypertension is the primary cause of cardiovascular diseases and is responsible for nearly 9 million deaths worldwide annually. Increasing evidence indicates that in addition to pathophysiologic processes, numerous environmental factors, such as geographic location, lifestyle choices, socioeconomic status, and cultural practices, influence the risk, progression, and severity of hypertension, even in the absence of genetic risk factors. In this review, we discuss the impact of some environmental determinants on hypertension. We focus on clinical data from large population studies and discuss some potential molecular and cellular mechanisms. We highlight how these environmental determinants are interconnected, as small changes in one factor might affect others, and further affect cardiovascular health. In addition, we discuss the crucial impact of socioeconomic factors and how these determinants influence diverse communities with economic disparities. Finally, we address opportunities and challenges for new research to address gaps in knowledge on understanding molecular mechanisms whereby environmental factors influence development of hypertension and associated cardiovascular disease.

Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal

Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.

Stroke burden and attributable risk factors in China, 1990-2019

Background and purpose

Understanding the temporal trends of stroke burden and its attributable risk factors are essential for targeted prevention strategies. We aimed to describe the temporal trends and attributable risk factors of stroke in China.

Methods

Data on the stroke burden [incidence, prevalence, mortality, and disability-adjusted life years (DALYs)] and the population-attributable fraction for stroke risk factors from 1990 to 2019 were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We analyzed trends in the burden of stroke and its attributable risk factors from 1990 to 2019, and the characteristics of stroke-attributable risk factors by sex, age group, and stroke subtype.

Results

From 1990 to 2019, the age-standardized incidence, mortality, and DALY rates for total stroke decreased by 9.3% (3.3, 15.5), 39.8% (28.6, 50.7), and 41.6% (30.7, 50.9) respectively. The corresponding indicators all decreased for intracerebral hemorrhage and subarachnoid hemorrhage. The age-standardized incidence rate of ischemic stroke increased by 39.5% (33.5 to 46.2) for male patients and by 31.4% (24.7 to 37.7) for female patients, and the age-standardized mortality and DALY rates remained almost unchanged. The three leading stroke risk factors were high systolic blood pressure, ambient particulate matter pollution, and smoking. High systolic blood pressure has remained the leading risk factor since 1990. The attributable risk of ambient particulate matter pollution shows a clear upward trend. Smoking and alcohol consumption were important risk factors for men.

Conclusion

This study reinforced the findings of an increased stroke burden in China. Precise stroke prevention strategies are needed to reduce the disease burden of stroke.

Air pollution and stroke hospitalization in the Beibu Gulf Region of China: A case-crossover analysis

BACKGROUND

The relationship between air pollution and stroke has been extensively studied, however, the evidence regarding the association between air pollution and hospitalization due to stroke and its subtypes in coastal areas of China is limited.

OBJECTIVE

To estimate the associations between air pollution and hospitalizations of stroke and its subtypes in the Beibu Gulf Region of China.

METHODS

We conducted a time-stratified case-crossover study in 15 cities in Beibu Gulf Region in China from 2013 to 2016. Exposures to PM₁, PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO on the case and control days were assessed at residential addresses using bilinear interpolation. Conditional logistic regressions were constructed to estimate city-specific associations adjusting for meteorological factors and public holidays. Meta-analysis was further conducted to pool all city-level estimates.

RESULTS

There were 271,394 case days and 922,305 control days. The odds ratios (ORs) for stroke hospitalizations associated with each interquartile range (IQR) increase in 2-day averages of SO₂ (IQR: 10.8 µg/m³), NO₂ (IQR: 11.2 µg/m³), and PM₁₀ (IQR: 37 µg/m³) were 1.047 (95 % CI [confidence interval]: 1.015-1.080), 1.040 (95 % CI: 1.027-1.053), and 1.018 (95 % CI: 1.004-1.033), respectively. The associations with hospitalizations of ischemic stroke were significant for all seven pollutants, while the association with hemorrhagic stroke was significant only for CO. The associations of SO₂, NO₂, and O₃ with stroke hospitalization were significantly stronger in the cool season.

CONCLUSIONS

Short-term increase in SO₂, NO₂, and PM₁₀ might be important triggers of stroke hospitalization. All seven air pollutants were associated with ischemic stroke hospitalization, while only CO was associated with hemorrhagic stroke hospitalization. These results should be considered in public health policy.

Short-term air pollution exposure associated with death from kidney diseases: a nationwide time-stratified case-crossover study in China from 2015 to 2019

BACKGROUND

Long-term exposure to air pollution has been associated with the onset and progression of kidney diseases, but the association between short-term exposure to air pollution and mortality of kidney diseases has not yet been reported.

METHODS

A nationally representative sample of 101,919 deaths from kidney diseases was collected from the Chinese Center for Disease Control and Prevention from 2015 to 2019. A time-stratified case-crossover study was applied to determine the associations. Satellite-based estimates of air pollution were assigned to each case and control day using a bilinear interpolation approach and geo-coded residential addresses. Conditional logistic regression models were constructed to estimate the associations adjusting for nonlinear splines of temperature and relative humidity.

RESULTS

Each 10 µg/m³ increment in lag 0-1 mean concentrations of air pollutants was associated with a percent increase in death from kidney disease: 1.33% (95% confidence interval [CI]: 0.57% to 2.1%) for PM₁, 0.49% (95% CI: 0.10% to 0.88%) for PM_2.5, 0.32% (95% CI: 0.08% to 0.57%) for PM₁₀, 1.26% (95% CI: 0.29% to 2.24%) for NO₂, and 2.9% (95% CI: 1.68% to 4.15%) for SO₂.  CONCLUSIONS: Our study suggests that short-term exposure to ambient PM₁, PM_2.5, PM₁₀, NO₂, and SO₂ might be important environmental risk factors for death due to kidney diseases in China.

Association between sedentary time and metabolic syndrome: A cross-sectional study among Chinese Garze Tibetans

Background

Chinese Tibetans have long hours of sitting without much physical activity given their religious behavior, raising potential harmful health hazards. However, the relationship between sedentary time and metabolic syndrome (MetS) has not been investigated in Chinese Tibetans.

Methods

From Jan 2021 to Jun 2022, residents in Garze Tibetan Autonomous Prefecture in Southwest China's Sichuan province were recruited using a multi-stage, stratified, random-cluster sampling strategy. MetS were ascertained using definition proposed by the International Diabetes Federation. Associations between sedentary time and the prevalence of MetS in the total sample and by age and sex were estimated using logistic regression models.

Results

Among 971 Chinese Tibetan participants (mean age 41.1 years and 73.8% female), 319 (32.9%) were diagnosed as having MetS. We found positive associations of sedentary time over 11 h per day with the prevalence of MetS in crude (OR: 1.23; 95% CI: 1.12-1.36, p < 0.001), age and sex adjusted (OR: 1.18; 95% CI: 1.08-1.29, p < 0.001), and fully adjusted (OR: 1.17; 95% CI: 1.08-1.29, p < 0.001) models, compared to those who had <8 h of sedentary time per day. Sensitivity analyses suggest consistent positive association between sedentary time and each metric of MetS.

Conclusions

Sedentary time longer than 11 h per day is significantly associated with increased risk of MetS, suggesting that polices to advocate health education may alleviate the health burden of MetS among Tibetans in China.