Association between ambient air pollution and hospital admissions, length of hospital stay and hospital cost for patients with cardiovascular diseases and comorbid diabetes mellitus: Base on 1,969,755 cases in Beijing, China, 2014-2019

Short-term and lagged effects of ambient air pollutants on CVD hospitalization: A two-decade population-based study in Tehran

OBJECTIVES

To evaluate the relationship between short-term exposure to ambient air pollutants and cardiovascular disease (CVD) hospitalizations.

METHODS

A time-series analysis was conducted using data from the Tehran Lipid and Glucose Study cohort of 3454 residents (1880 women) aged 50-70 from District 13 of Tehran. Follow-up data from January 1999 to March 2018 were analyzed. Daily mean temperatures and air pollution levels (CO, O3, PM10, NO2, and SO2) were recorded, and distributed lag non-linear models (DLNMs) assessed the lagged effects on outcome.

RESULTS

Over a median follow-up of 14.7 years, 2200 CVD hospitalizations occurred among 3454 participants (mean age 58.7 years, women = 1880). Among the general population, the DLNM models indicated that PM10 concentrations at 73 μg/m3 was associated with a 12 % increased risk of the outcome, with an RR of 1.12 (95 % CI: 1.01-1.24), and higher PM10 levels corresponded to increasing RRs. PM10 indicated a short-term exposure effect at 1-day lag on the outcome risk. SO2 concentrations reached significance at 24 μg/m3, with an RR of 1.06 (95 % CI: 1.04-1.07); the effect persisted up to 65 μg/m3, with an increased risk of the outcome observed at a 6-day lag. CO showed the highest RR of 1.92 (95 % CI: 1.65-2.23) for the concentration of 5 mg/m3. Exposure to CO was linked to an increased risk of the outcome with a 1-day lag. Sex as well as presence of metabolic syndrome and CKD did not modify the association between air pollutants with the outcome.

CONCLUSIONS

Short-term exposure to PM10, SO2 and CO significantly increased risk of CVD hospitalization.

Short-term associations between ambient PM1, PM2.5, and PM10 and hospital admissions, length of hospital stays, and hospital expenses for patients with cardiovascular diseases in rural areas of Fuyang, East China

Evidence on the impacts of PM1, PM2.5, and PM10 on the hospital admissions, length of hospital stays (LOS), and hospital expenses among patients with cardiovascular disease (CVD) is still limited in China, especially in rural areas. This study was performed in eight counties of Fuyang from 1 January 2015 to 30 June 2017. We use a three-stage time-series analysis to explore the effects of short-term exposure to PM1, PM2.5, and PM10 on hospital admissions, LOS, and hospital expenses for CVDs. An increment of 10 ug/m3 in PM1, PM2.5, and PM10 corresponded to an increment of 1.82% (95% CI: 1.34, 2.30), 0.96% (95% CI: 0.44, 1.48), and 0.79% (95% CI: 0.63%, 0.95%) in CVD hospital admissions, respectively. We observed that daily concentrations of PMs were associated with an increase in hospital admissions, LOS, and expenses for CVDs. Sustained endeavors are required to reduce air pollution so as to attenuate disease burdens from CVDs.

Short-term exposure to PM2.5 and its components and type 2 diabetes-related hospital admissions, length of stay, and hospital costs in Shanghai

The short-term influence of particles with an aerodynamic diameter ≤2.5 μm (PM2.5) and its individual elements on hospital costs, the length of hospital stay (LOS), and hospital admissions caused by type 2 diabetes remains unclear. A generalized additive model (GAM) with quasi-Poisson distribution was utilized to assess the association of individual pollutants and mixtures. For every 10 μg/m3 rise in PM2.5 and a per-SD increase in NH4+at lag0, hospital admissions increased by 0.93% (95% CI: 0.68, 1.19) and 2.81% (95% CI: 2.20, 3.42); hospital costs rose by 24.58 thousands of CNY (95% CI: 5.95, 43.22) and 77.06 thousands of CNY (95% CI: 33.07, 121.04); LOS increased by 9.53 days (95% CI: 0.44, 18.62) and 27.80 days (95% CI: 6.34, 49.27), respectively. Factor analysis showed that mixed-source particulate pollution was significantly associated with an increase in hospital admissions (0.27%, 95% CI: (0.20, 0.34)), LOS (2.87 days, 95% CI: (0.35, 5.40)), and hospital costs (71.68 thousands of CNY, 95% CI: (19.89,123.46)). These findings suggested that short-term exposure to elevated levels of PM2.5 as well as its components increased the risk of hospital costs, LOS, and hospital admissions due to type 2 diabetes.

Association between short-term exposure to ambient PM2.5 and its components with hospital admissions for patients with coronary heart disease and comorbid diabetes mellitus in Beijing, China

Existing researches had primarily investigated the associations between various air pollutants and the risk of coronary heart disease (CHD) or diabetes mellitus (DM) separately. However, the significance and effects of PM2.5 and its components in patients with CHD and comorbid DM (CHD-DM) remain unclear. Patient data was sourced from the Beijing Municipal Health Commission Information Centre between January 1, 2014, and December 31, 2018. We utilized Generalized Additive Models (GAM) to analyze the relationship between daily hospital admissions for CHD-DM patients and PM2.5 exposure. The hospital admissions were treated as count data, offset by the total CHD-DM population, with a logarithmic link function. Smooth functions were included to account for the non-linear effects of time trends and meteorological factors used in both Chinese and WHO air quality guidelines. In Beijing, records show 215,267 hospital admissions for patients with CHD-DM. Every 10 μg/m3 increase of particles with an aerodynamic diameter ≤2.5 μm (PM2.5) corresponded to a 0.62% (95%CI: 0.49 to 0.76) increment for CHD-DM patients' admissions. As for the PM2.5 components: Per 10 μg/m3 increase of SO42- was 2.31% (95%CI: 1.51 to 3.11), NO3- was 3.35% (95%CI: 2.47 to 4.23), for NH4+ the percentage change value was 4.37% (95%CI: 2.99 to 5.77), for OM was 5.36% (95%CI: 4.19 to 6.55), for BC was 36.51% (95%CI: 28.09 to 45.47) increment for CHD-DM patients' admissions. Based on the WHO 2021 air quality guideline, our estimation suggests that a reduction in PM2.5 concentrations could prevent approximately 2.62% (95%CI: 2.04%-3.2%) hospital admissions, corresponding to 5632 (95%CI: 4397 to 6879) CHD-DM patients, could be avoidable. Patients with CHD-DM who were exposed to PM2.5 and its components had an increased risk of hospital admissions. Furthermore, among all PM2.5 components, BC may be the most significant contributor to the association between PM2.5 and hospital admissions among CHD-DM patients.

Individual effects and interactions between ultrafine particles and extreme temperatures on hospital admissions of high burden diseases

BACKGROUND

Health effects of ultrafine particles (UFPs) and their interactions with temperature are less studied. We investigated the risks of UFPs concentrations and extreme temperatures on hospitalizations for high-burden diseases (HBDs) in New York State (NYS).

METHODS

This case-crossover study included hospitalizations for HBDs that contain ischemic heart diseases, diabetes, stroke, kidney diseases, and depression using NYS Hospital Discharge Data (2013-2018). Daily pollutants and temperature data were obtained from a chemical transport model validated by multiple prior studies. UFP changes were measured using interquartile range increase, and extreme heat and cold were defined as temperatures >= 90th% and <=10th% respectively by month and location. Conditional logistic regression was applied controlling for criteria pollutants, relative humidity, and time-varying variables.

RESULTS

Among 1,308,518 cases, significant risk ratios (RR) were observed for UFPs (RRs ranged: 1.009-1.012) and extreme heat (RRs ranged: 1.024-1.028) on overall HBDs, but extreme cold had protective effects on HBDs. The adverse effect of UFPs had significant interactions with extreme cold and was higher in winter and fall. UFPs affected all HBD subtypes except kidney diseases, and extreme heat increased the risks of ischemic heart disease and kidney disease. There were disparities across demographics in exposures-HBDs associations although they were not statistically significant. Elevated UFP concentrations were associated with four clinical indicators (hospital stays, charges etc.).

CONCLUSION

We observe positive associations between elevated UFP concentrations or extreme heat and HBD hospitalizations, but negative associations with extreme cold. The UFPs' risks were higher in children and during cold seasons.

Short-Term Exposure to Ambient Particulate Matter Pollution and Surgical Outcomes

INTRODUCTION

Particulate matter less than 2.5 μm in diameter (PM2.5) can activate inflammatory cascades, cause oxidative damage, and induce cell death. Short-term exposures to PM2.5 have been associated with appendicitis and inflammatory bowel disease presentations, yet it is unclear if exposures may impact surgical recovery.

METHODS

We conducted a retrospective cohort study of adult, colorectal surgery patients from 2006 to 2021. Institutional American College of Surgeons National Surgical Quality Improvement Program data were linked to Environmental Protection Agency PM2.5 concentrations on the day of admission stratified into low, moderately elevated, and high exposures. The environmental justice index chronic environmental burden and social vulnerability modules accounted for chronic stressors. The outcomes included length of stay (LOS), complications, and readmissions. After appropriate bivariate tests, multivariable regression models for the primary outcomes were constructed.

RESULTS

1038 patients were included with the majority experiencing low PM2.5 (53.4%, n = 554). Patients were similar in terms of demographic, clinical, and procedural characteristics across pollution groups, with a median age of 59.6, 53.5% female, 38.3% Black, and 74.5% American Society of Anesthesiologists class 3. The unadjusted outcomes did not differ significantly across groups; however, on adjusted models, higher PM2.5 groups had longer LOS: incident rate ratio 1.12 [95% CI 1.05-1.19] and incident rate ratio 1.37 [95% CI 1.16-1.62] for moderately elevated and high PM2.5, respectively (P < 0.001).

CONCLUSIONS

This study found a novel association between surgical outcomes and short-term ambient air pollution, with higher PM2.5 on the day of admission associated with longer LOS. Notably, this is also the first surgical study to use the environmental justice index to control for social and environmental determinants of health.

Preexisting multimorbidity predicts greater mortality risks related to long-term PM2.5 exposure

Long-term health risk assessments related to ambient fine particulate matter (PM2.5) exposure have been more limited to general population but not towards individuals suffering from multimorbidity. While both multimorbidity and PM2.5 are independently linked to elevated mortality risk, their combined effects and interactions remain practically unexplored. A cross-cohort analysis was undertaken on data from 3 prospective cohorts, initially enrolling 869038 adults aged ≥18 years followed up during 2005-2022. Multimorbidity was identified at baseline surveys through a list of nine common chronic conditions. Cox proportional hazards models were utilized to quantify the associations of long-term PM2.5 exposure with all-cause, cardiovascular, and respiratory mortality among individuals with and without multimorbidity. Joint effects and interactions between baseline multimorbidity and PM2.5 level on the additive and multiplicative scales were examined. Risk differences of PM2.5-induced mortality were analyzed stratified by number of chronic conditions and multimorbidity patterns. Subgroup and sensitivity analyses were carried out to evaluate the consistency of the findings. Among 713119 eligible participants for primary analysis, 65490 prevalent cases of multimorbidity were identified at baseline over a median follow-up of 12.2 years. Compared to individuals without multimorbidity, associations of PM2.5 exposure with all-cause and cardiovascular mortality were more prominent among multimorbidity individuals (P <0.05 for heterogeneity). Our analysis unveiled a significant additive interaction between PM2.5 level and preexisting multimorbidity status, yielding estimated attributable proportions of 11.7%-17.8% and excess risks of 31.1%-72.6% for different mortality outcomes. Sex subgroup and sensitivity analyses consistently produced similar results. This large-scale multicohort analysis demonstrated markedly stronger associations between PM2.5 levels and risks of all-cause and cardiovascular mortality in multimorbidity populations compared to those without multimorbidity. PM2.5 exposure and preexisting multimorbidity showed synergistic effects in triggering mortality events, wherein the joint risks were intensified with elevated PM2.5 levels and an increased number of chronic conditions.

Effects of fine particulate matter and its chemical constituents on influenza-like illness in Guangzhou, China

BACKGROUND

Although the link between fine particulate matter (PM2.5) and influenza-like illness (ILI) is well established, the effect of the chemical constituents of PM2.5 on ILI remains unclear. This study aims to explore this effect in Guangzhou, China.

METHODS

Daily data on ILI cases, PM2.5 levels, and specific PM2.5 constituents (black carbon [BC], chlorine [Cl-], ammonia [NH4+], nitrate [NO3-], and sulfate [SO42-]) in Guangzhou, China, were collected for the period of 2014-2019. Additionally, data on gaseous pollutants and meteorological conditions were obtained. By using quasi-Poisson regression models, the association between exposure to PM2.5 and its constituents and ILI risk was estimated. Stratified subgroup analyses were performed by gender, age, and season to explore in depth the effects of these factors on disease risk.

RESULTS

Single-pollutant modeling results showed that an increase of one interquartile range (IQR) in Cl-, SO42-, PM2.5, NH4+, BC, and NO3- corresponded to relative risks of ILI of 1.046 (95 % CI: 1.004, 1.090) (lag03), 1.098 (95 % CI: 1.058, 1.139) (lag01), 1.091 (95 % CI: 1.054, 1.130) (lag02), 1.093 (95 % CI: 1.049, 1.138) (lag02), 1.111 (95 % CI: 1.074, 1.150) (lag03), and 1.103 (95 % CI: 1.061, 1.146) (lag03), respectively. Notably, the association between ILI and BC remained significant even after adjusting for PM2.5 mass. Subgroup analyses indicated that individuals aged 5-14 and 15-24 years may exhibit higher sensitivity to BC and Cl- exposure than other individuals. Furthermore, stronger associations were observed during the cold season than during the warm season.

CONCLUSIONS

Results showed that the mass and constituents of PM2.5 were significantly correlated with ILI. Specifically, the carbonaceous fractions of PM2.5 were found to have a pronounced effect on ILI. These findings underscore the importance of implementing effective measures to reduce the emission of specific sources of PM2.5 constituents to mitigate the risk of ILI. Nevertheless, limitations such as potential exposure misclassification and regional constraints should be considered.

Estimation of Attributable Risk and Direct Medical and Non-Medical Costs of Major Mental Disorders Associated With Air Pollution Exposures Among Children and Adolescents in the Republic of Korea, 2011-2019

BACKGROUND

Recent studies have reported the burden of attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and depressive disorder. Also, there is mounting evidence on the effects of environmental factors, such as ambient air pollution, on these disorders among children and adolescents. However, few studies have evaluated the burden of mental disorders attributable to air pollution exposure in children and adolescents.

METHODS

We estimated the risk ratios of major mental disorders (ADHD, ASD, and depressive disorder) associated with air pollutants among children and adolescents using time-series data (2011-2019) obtained from a nationwide air pollution monitoring network and healthcare utilization claims data in the Republic of Korea. Based on the estimated risk ratios, we determined the population attributable fraction (PAF) and calculated the medical costs of major mental disorders attributable to air pollution.

RESULTS

A total of 33,598 patients were diagnosed with major mental disorders during 9 years. The PAFs for all the major mental disorders were estimated at 6.9% (particulate matter < 10 μm [PM10]), 3.7% (PM2.5), and 2.2% (sulfur dioxide [SO2]). The PAF of PM10 was highest for depressive disorder (9.2%), followed by ASD (8.4%) and ADHD (5.2%). The direct medical costs of all major mental disorders attributable to PM10 and SO2 decreased during the study period.

CONCLUSION

This study assessed the burden of major mental disorders attributable to air pollution exposure in children and adolescents. We found that PM10, PM2.5, and SO2 attributed 7%, 4%, and 2% respectively, to the risk of major mental disorders among children and adolescents.

Enhancing the health benefits of air quality improvement: a comparative study across diverse scenarios

In many studies, linear methods were used to calculate health benefits of air quality improvement, but the relationship between air pollutants and diseases may be complex and nonlinear. In addition, previous studies using reference number as average number of diseases may overestimate the health benefits. Therefore, the nonlinear model estimation and resetting of the reference number were very important. Hospital admission data for coronary heart disease (CHD), meteorological data, and air pollutant data of Zibo City from 2015 to 2019 were collected. The generalized additive model (GAM) was used to explore the association between air pollutants and hospital admission for CHD, and to evaluate the effects on health benefits under different reference number settings. A total of 21,105 hospitalized cases for CHD were reported in Zibo during the study period. The results of the GAM showed there was a log-linear exposure-response relationship between O3 and hospital admissions for CHD, with RR (relative risk) of 1.0143 (95% CI: 1.0047 ~ 1.0239). There were log-nonlinear exposure-response relationships between PM10, PM2.5, SO2, and hospital admissions for CHD. With the increase of pollutants concentrations, the risk for hospital admission showed a trend of increasing first and then decreasing. Compared with the average hospital admissions as the reference number, health benefits calculated by hospital admissions predicted by the GAM model yielded lower. Using the World Health Organization air quality guidelines as reference, attributable fractions of O3, PM10, and PM2.5 were 1.97% (95% CI: 0.63 ~ 3.40%), 11.82% (95% CI: 8.60 ~ 15.24%), and 11.82% (95% CI: 8.79 ~ 15.04%), respectively. When quantifying health benefits brought by improving air quality, corresponding calculation methods should first be determined according to the exposure-response relationships between air pollutants and outcomes. Then, applying the average hospital admissions as reference number may overestimate health benefits resulting from improved air quality.

Effect of short-term exposure to air pollution on hospital admission for cardiovascular disease: A time-series study in Xiangyang, China

BACKGROUND

Data on the relationship between short-term exposure to air pollution and cardiovascular diseases (CVDs) and the potential modifying factors are limited and inconsistent.

OBJECTIVE

To explore the relationship between short-term exposure to air pollution and CVD risk, and potential modification effect factors.

METHOD

A time series study was conducted on 52,991 hospital admissions for CVD from 2015 to 2019 in Xiangyang City, China. Air pollution data from four national fixed monitoring stations were collected to estimate exposure level in Xiangyang City. A quasi-Poisson generalized additive model incorporating a distributed lag nonlinear model was applied to evaluate the association between air pollution and CVD risk. The potential modification effect of sex, age, and season on the above associations was also evaluated.

RESULTS

CVD risk was positively associated with air pollution. Peak associations in single lag day structures were observed for particulate matter ≤10 μm in aerodynamic (PM10; RR: 1.040, 95 % CI: 0.996-1.087), PM2.5 (1.025, 1.004-1.045), nitrogen dioxide (NO2; 1.074, 1.039-1.111), and sulfur dioxide (SO2; 1.079, 1.019-1.141) at Lag 0 and ozone (O3; 1.018, 1.004-1.031) at Lag 4. In cumulative lag day structures, the highest RRs were 1.225 (1.079,1.392) for PM10 at Lag 06, 1.054 (1.013, 1.098) for PM2.5 at Lag 03, 1.200 (1.119, 1.287) for NO2 at Lag 04, and 1.135 (1.025, 1.257) for SO2 at Lag 02. Moreover, the association between air pollution and CVD risk was modified by sex and age (P < 0.05). Females and individuals aged ≤65 years were more vulnerable to NO2 and had a higher CVD risk.

CONCLUSION

Short-term exposure to air pollution was positively associated with CVD risk. Moreover, sex and age could modify the effect of air pollution on CVD risk. Females and individuals aged ≤65 years had a higher NO2 exposure-induced CVD risk.

Characterization of PAHs bound to ambient ultrafine particles around runways at an international airport

The impact of airport activities on air quality, is not sufficiently documented. In order to better understand the magnitude and properly assess the sources of emissions in the sector, it is necessary to establish databases with real data on those pollutants that could have the greatest impact on both health and the environment. Particulate matter (PM), especially ultrafine particles, are a research priority, not only because of its physical properties, but also because of its ability to bind highly toxic compounds such as polycyclic aromatic hydrocarbons (PAHs). Samples of PM were collected in the ambient air around the runways at Barajas International Airport (Madrid, Spain) during October, November and December 2021. Samples were gathered using three different sampling systems and analysed to determine the concentration of PAHs bound to PM. A high-volume air sampler, a Berner low-pressure impactor, and an automated off-line sampler developed in-house were used. The agreement between the samplers was statistically verified from the PM and PAH results. The highest concentration of PM measured was 31 μg m-3, while the concentration of total PAH was 3 ng m-3, both comparable to those recorded in a semi-urban area of Madrid. The PAHs showed a similar profile to the particle size distribution, with a maximum in the 0.27-0.54 μm size range, being preferentially found in the submicron size fractions, with more than 84% and around 15-20% associated to UFPs. It was found that the ratio [PAHs(m)/PM(m)] was around 10-4 in the warmer period (October), whereas it more than doubled in the colder months (November-December). It is significant the shift in the relative distribution of compounds within these two periods, with a notable increase in the 5 and 6 ring proportions in the colder period. This increase was probably due to the additional contribution of other external sources, possibly thermal and related to combustion processes, as supported by the PAH diagnostic ratios.

Bidirectional modification effects on nonlinear associations of summer temperature and air pollution with first-ever stroke morbidity

High temperature and air pollution may induce stroke morbidity. However, whether associations between high temperature and air pollution with stroke morbidity are modified by each other is still unclear. Data on 23,578 first-ever stroke patients in Shenzhen, China, during the summers of 2014-2018 were collected. Distributed lag nonlinear models were used to assess the modifying effects of air pollution stratified by the median for the associations between summer temperature and stroke morbidity at 0-3 lag days; modifying effects of temperature stratified by the minimum morbidity temperature on the associations between air pollution and stroke morbidity at the same lags were also estimated. The attributable risks of high temperature and high pollution on stroke morbidity were quantified. Stratified analyses of gender, age, migration type, and complication type were conducted to assess vulnerable population characteristics. Summer high temperature may induce stroke morbidity at high-level PM2.5, PM10, O3, SO2, and NO2 conditions, with attributable fraction (AF) of 2.982% (95% empirical confidence interval [eCI]: 0.943, 4.929), 3.113% (0.948, 5.200), 2.841% (0.943, 4.620), 3.617% (1.539, 5.470), and 2.048% (0.279, 3.637), respectively. High-temperature effects were statistically insignificant at corresponding low-level air pollution conditions. High-level PM2.5, PM10, and O3 may induce stroke morbidity at high-temperature conditions, with AF of 3.664% (0.036, 7.196), 4.129% (0.076, 7.963), and 4.574% (1.009, 7.762), respectively. High-level PM2.5, PM10, and O3 were not associated with stroke morbidity at low-temperature conditions. The effects of high temperature and high pollution on stroke morbidity were statistically significant among immigrants and patients with hypertension, dyslipidemia, or diabetes but insignificant among natives and patients without complications. The associations of summer temperature and air pollution with first-ever stroke morbidity may be enhanced bidirectionally. Publicity on the health risks of combined high temperature and high pollution events should be strengthened to raise protection awareness of relevant vulnerable populations.

Identifying interactions among air pollutant emissions on diabetes prevalence in Northeast China using a complex network

BACKGROUND

Low air quality related to ambient air pollution is the largest environmental risk to health worldwide. Interactions between air pollution emissions may affect associations between air pollution exposure and chronic diseases. Therefore, this study aimed to quantify interactions among air pollution emissions and assess their effects on the association between air pollution and diabetes.

METHODS

After constructing long-term emission networks for six air pollutants based on data collected from routine monitoring stations in Northeast China, a mutual information network was used to quantify interactions among air pollution emissions. Multiple linear regression analysis was then used to explore the influence of emission interactions on the association between air pollution exposure and the prevalence of diabetes based on data reported from the Northeast Natural Cohort Study in China.

RESULTS

Complex network analysis detected three major emission sources in Northeast China located in Shenyang and Changchun. The effects of particulate matter (PM2.5 and PM10) and ground-level ozone (O3) emissions were limited to certain communities but could spread to other communities through emissions in Inner Mongolia. Emissions of sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) significantly influenced other communities. These results indicated that air pollutants in different geographic areas can interact directly or indirectly. Adjusting for interactions between emissions changed associations between air pollution emissions and diabetes prevalence, especially for PM2.5, NO2, and CO.

CONCLUSIONS

Complex network analysis is suitable for quantifying interactions among air pollution emissions and suggests that the effects of PM2.5 and NO2 emissions on health outcomes may have been overestimated in previous population studies while those of CO may have been underestimated. Further studies examining associations between air pollution and chronic diseases should consider controlling for the effects of interactions among pollution emissions.

From emissions to incisions and beyond: the repercussions of climate change on surgical disease in low- and-middle-income countries

Climate change has far-reaching repercussions for surgical healthcare in low- and middle-income countries. Natural disasters cause injuries and infrastructural damage, while air pollution and global warming may increase surgical disease and predispose to worse outcomes. Socioeconomic ramifications further strain healthcare systems, highlighting the need for integrated climate and healthcare policies.

Middle-term nitrogen dioxide exposure and electrocardiogram abnormalities: A nationwide longitudinal study

BACKGROUND

Recently, professionals, such as those from the World Health Organization, have recommended a rigorous standard for nitrogen dioxide (NO2), a typical urban air pollutant affected by regular traffic emissions, based on its short-term and long-term cardiorespiratory effects. However, the association between middle-term NO2 exposure and cardiovascular disorders remains unknown.

OBJECTIVES

This study was conducted to examine the relationship between NO2 exposure and its middle-term cardiovascular risks indicated by electrocardiogram (ECG) abnormalities.

METHOD

We included 61,094 subjects (132,249 visits) with repeated ECG observations based on longitudinal data from the China National Stroke Screening Survey (CNSSS). The NO2 exposure concentration was derived from a predictive model, measured as the monthly average concentration in the 6 months of preceding the ECG measurement. We used the generalized estimation equation to assess the association between NO2 exposure and ECG abnormalities.

RESULT

For each 10 µg/m3 increase in monthly average NO2 concentration, the odds ratio of ECG abnormalities was 1.10 (95% confidence interval [CI] 1.09-1.12) after multiple adjustments. Stratified regression analyses of urban and rural residents showed associations between middle-term NO2 exposure and ECG abnormalities in urban (OR 1.09 [95% CI 1.08-1.11]) and rural residents (OR 1.14 [95% CI 1.10-1.19]). The association was robust within different subpopulations. Associations generally remained statistically significant (OR 1.03 [95% CI 1.02-1.05]) after extra adjustment for PM2.5. Exposure-response relationship analysis revealed a nearly linear relationship between NO2 exposure and the risk for ECG abnormalities.

CONCLUSION

Using the variation in ECG signals as a potentially reversible indicator for subclinical risk in cardiovascular systems, our study provides additional evidence on the increased risk posed by middle-term NO2 exposure. Our study showed that policies controlling for NO2 concentrations are beneficial to prevent cardiovascular diseases among Chinese adults.

The impact of ambient air pollution on hospital admissions, length of stay and hospital costs for patients with diabetes mellitus and comorbid respiratory diseases in Panzhihua, Southwest China

Background

There is limited evidence on association between air pollutants and hospital admissions, hospital cost and length of stay (LOS) among patients with diabetes mellitus (DM) and comorbid respiratory diseases (RD), especially in low- and middle-income countries (LMICs) with low levels of air pollution.

Methods

Daily data on RD-DM patients were collected in Panzhihua from 2016 to 2020. A generalised additive model (GAM) was used to explore the effect of air pollutants on daily hospital admissions, LOS and hospital cost. Attributable risk was employed to estimate RD-DM's burden due to exceeding air pollution exposure, using both 0 microgrammes per cubic metre (μg/m3) and WHO's 2021 air quality guidelines as reference.

Results

For each 10 ug/m3 increase of particles with an aerodynamic diameter <2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter <10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3), the admissions of RD-DM patients increased by 7.25% (95% CI = 4.26 to 10.33), 5.59% (95% CI = 3.79 to 7.42), 10.10% (95% CI = 7.29 to 12.98), 12.33% (95% CI = 8.82 to 15.95) and -2.99% (95% CI = -4.08 to -1.90); per 1 milligramme per cubic metre (mg/m3) increase of carbon monoxide (CO) corresponded to a 25.77% (95% CI = 17.88 to 34.19) increment for admissions of RD-DM patients. For LOS and hospital cost, the six air pollutants showed similar effect. Given 0 μg/m3 as the reference, NO2 showed the maximum attributable fraction of 32.68% (95% CI = 25.12 to 39.42%), corresponding to an avoidable burden of 5661 (95% CI = 3611 to 5860) patients with RD-DM.

Conclusions

There is an association between PM2.5, PM10, SO2, NO2, and CO with increased hospital admissions, LOS and hospital cost in patients with RD-DM. Disease burden of RD-DM may be improved by formulating policies related to air pollutants exposure reduction, especially in LMICs with low levels of air pollution.

Long-term effects of particulate matter on incident cardiovascular diseases in middle-aged and elder adults: The CHARLS cohort study

BACKGROUND

Although there is evidence of long-term effects of particulate matter (PM) on cardiovascular diseases (CVD), researches about long-term effects of PM₁ on CVD are limited. We aimed to examine the long-term effects and magnitude of PM, especially PM₁, on incident CVD in China.

METHODS

We included 6016 participants aged ≥ 45 years without CVD at baseline in 2011 from the China Health and Retirement Longitudinal Study. Personal PM (PM₁, PM_2.5, and PM₁₀) concentrations were estimated using geocoded residential address. Generalized linear mixed models and SHapley Additive exPlanation were utilized to calculate the impacts and contributions of PM on CVD. Sensitivity analyses were used to check the robustness.

RESULTS

After a follow up of 4-year, 481 (7.99 %) participants developed CVD. Per 10 μg/m³ uptick in 1-year average concentrations of PM₁, PM_2.5 and PM₁₀ was associated with a 1.20 [95 % confidence interval (CI): 1.05-1.37], 1.13 (95 % CI: 1.11-1.15), and 1.10 (95 % CI: 1.06-1.13) fold risk of incident CVD, respectively. The 2-year average concentrations of PM₁, PM_2.5 and PM₁₀ were associated with incident CVD, corresponding to a 1.03 (95 % CI: 0.96-1.10), 1.11 (95 % CI: 1.02-1.21), and 1.09 (95 % CI: 1.03-1.15) fold risk, respectively. The SHapley Additive exPlanation values of PM₁, PM_2.5, and PM₁₀ were 0.170, 0.153, and 0.053, respectively, corresponding to the first, second, and fifth among all air pollutants. Effects of PM₁, PM_2.5 and PM₁₀ on CVD remained statistically significant in two-pollutant models. The elderly, males, smokers and alcohol drinkers tended to have slightly higher effects, while the differences were not statistically significant (all P-values > 0.05) between subgroups.

CONCLUSION

Long-term exposure to PM₁, PM_2.5, and PM₁₀ was associated with an increased incidence of CVD. The smaller the particle size, the more important it was for incident CVD indicating that emphasis should be placed on small size of PM.

Unexpected association between ambient ozone and adult insomnia outpatient visits: A large-scale hospital-based study

Growing evidence indicates that short-term ozone (O₃) exposure has substantial health consequences, but the relationship between short-term ambient O₃ and insomnia, a common sleep disorder, is not clear. This study aimed to investigate the short-term effects of ambient O₃ exposure on outpatient visits for adult insomnia and to explore the potential modifiers. A large-scale multihospital-based study was carried out in Chongqing, the largest city in Southwest China. Daily data on outpatient visits for adult insomnia, average concentrations of ambient air pollutants and meteorological factors were collected. We conducted quasi-Poisson regression with generalized additive model to assess the association between ambient O₃ and outpatient visits for adult insomnia in varied windows of exposure. Subgroup analyses were applied to identify its modifiers. Totally, 140,159 adult insomnia outpatient visits were identified. The daily maximum 8-h average concentration of O₃ was 69 μg/m³ during the study period, which greatly below the updated Chinese and WHO recommended limits (daily maximum 8-h average, O₃: 100 μg/m³). Short-term O₃ exposure was significantly negatively associated with outpatient visits for adult insomnia in different lag periods and the greatest decrease of outpatient visits for adult insomnia was found at lag 02 [0.93% (95% CI: 0.48%, 1.38%)]. Additionally, stronger links between O₃ and adult insomnia outpatient visits were presented in cool seasons, and we did not observe any significant modified effects of gender and age. Moreover, the negative O₃-insomnia association remained robust after controlling for other common air pollutants and comorbidities. In summary, short-term exposure to lower level of ambient O₃, was associated with reduced daily outpatient visits for adult insomnia and such association showed to be more obvious in cool seasons.

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.