Association between Air Pollution and Short-Term Outcome of ST-Segment Elevation Myocardial Infarction

1. Introduction:

The mounting evidence strongly suggests that air pollution has significant health effects, with a particular focus on its impact on the respiratory and cardiovascular systems. [1,2]. Short-term exposure to air pollutants, such as particulate matter <2.5 μm (PM2.5), <10 μm (PM10), and nitrogen dioxide (NO2), has been consistently linked to a higher risk of myocardial infarction (MI) events, emergency department (ED) visits, and stroke, as indicated by epidemiological studies. [3,4,5]. Toxicological studies have also revealed that both short- and long-term exposure to air pollution may result in vascular dysfunction [6,7], lung inflammation [8], and even disturbances in blood pressure regulation [9].

The American Heart Association highlights that ST-segment elevation myocardial infarction (STEMI), a significant cause of global mortality, is primarily triggered by an acute reduction in blood flow within the coronary arteries [10]. Recent studies have shown a noticeable connection between short-term exposure to air pollution, ED visits, hospitalization, and heightened risk of mortality for STEMI [11,12]. While some evidence exists indicating a potential association between short-term exposure to air pollution and pneumonia prognosis [13], there is a scarcity of studies specifically examining the impact of air pollution exposure on the prognosis of STEMI.

However, the health effects of air pollution exhibit seasonal variations. For instance, Ishii et al. discovered a positive correlation between PM2.5 exposures and the risk of MI, with the risk being more pronounced in the spring season [14], and children exhibited increased susceptibility to the effects of NO2 on pneumonia in the context of warm days [15]. Despite growing evidence on the impact of air pollution on health outcomes, its specific effects on the short-term outcomes of STEMI and potential seasonal effects remain unclear. The primary objective of this study was to investigate the relationship between air pollution, weather conditions, and short-term outcomes of STEMI. The aim was to enhance our understanding of the impact of air pollution on the prognosis of STEMI and assess any potential seasonal effects.

2. Materials and Methods

2.1. Study population

This retrospective observational investigation was performed at an urban tertiary medical center in Kaohsiung, Taiwan, with an annual average of 72,000 ED visits and 2500 beds, spanning from January 1, 2012, to December 31, 2017. For this study, we enrolled adult individuals who were over 20 years old, visited the ED with a primary diagnosis of STEMI (International Classification of Diseases, Ninth Revision [ICD-9]: 410; ICD-10: I21.0-I21.3), and subsequently underwent percutaneous coronary intervention (PCI). Both the ED physicians and cardiologists confirmed the diagnosis of STEMI. Patient information, including age, sex, and STEMI prognostic factors such as diabetes, dyslipidemia, current smoking status, Killip classification, body mass index, and clinical outcomes, were obtained from their medical records.

2.2. Pollutant and Meteorological Data

The study collected data on ambient air quality and weather conditions from 11 monitoring stations dedicated to assessing air quality in Kaohsiung City. These monitoring stations were set up by the Taiwanese Environmental Protection Administration in 1994. Kaohsiung, situated in southern Taiwan, is a city characterized by a tropical climate, at an elevation of approximately 9 m above sea level. The measurement of air pollutants was conducted in accordance with the previously described methodology. [16]. Briefly, the monitoring stations employed commercial monitoring instruments manufactured by Thermo Environmental Instruments, Inc. (Franklin, MA, USA) and designated by the United States Environmental Protection Agency (US EPA). The monitoring stations utilized full automation and monitored "criteria" pollutants on an hourly basis. This comprehensive monitoring included particulate matter, specifically PM10 and PM2.5, which were measured using the beta-ray absorption technique. Additionally, nitrogen dioxide (NO2) levels were assessed through ultraviolet fluorescence, while ozone (O3) concentrations were determined using ultraviolet photometry.

The study involved retrieving the residential addresses of the patients from their medical records. In addition, the average levels of these pollutants during a 24-hour period were measured, along with the temperature and mean humidity recorded at the closest monitoring station.

The air pollutant concentration, temperature, and humidity values recorded on the same day as the patient's ED visit were identified as a lag of 0. The values recorded on the day prior to the patient's ED visit were identified as lag 1, and so forth. The mean concentration from lags 0 to 3 was categorized as lag 0-3. The primary outcome of interest was the in-hospital mortality. This study was approved by the Institutional Review Board of the Chang Gung Memorial Hospital (number: 202101652B0C503) and was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki).

2.3. Statistical analyses

The independent variables were analyzed descriptively and presented as percentages or means ± standard deviations (SDs). The relationships between the independent variables and admission were evaluated using χ2, Mann–Whitney U, and Student t tests. To examine the statistical significance of the association between air pollutants and admission, logistic regression analysis was conducted. The odds ratio (OR) and a 95% confidence interval (CI) were computed. A significance level of p < 0.05 was considered statistically significant. The statistical analyses were conducted utilizing SPSS version 25.0 (IBM Corp., Armonk, NY, USA).

3. Results

Over the course of the six-year study period, a total of 1153 patients met the inclusion criteria. Among them, 132 patients were excluded from the analysis as their addresses were not located within Kaohsiung City. Additionally, 18 patients were excluded due to being transferred to other hospitals or being discharged against medical advice. The final study population consisted of 1003 patients. The demographic characteristics and air pollution conditions are presented in Table 1. Table 1 provides the demographic profiles and air pollution conditions. Of the 1003 patients included in this study, 56 (5.6%) died during hospitalization. Most patients who survived until hospital discharge were current smokers (p < 0.001), had a higher frequency of dyslipidemia (p = 0.008), and had lower Killip classification levels (p < 0.001). Patients who died during hospitalization had higher NO2 exposures on lags 2 (p = 0.017), 3 (p = 0.005), and lag 0-3 (p = 0.027).

3.1. Air pollutants and meteorological results

Table 2 presents a comprehensive summary an overview of the meteorological parameters, average daily levels of air pollutants, and weather variables observed in Kaohsiung City during the duration of the study. Throughout the study period, the mean values of PM2.5, PM10, NO2, and O3 concentrations were determined as 31.3 μg/m³, 63.5 μg/m³, 17.1 ppb, and 29.0 ppb, respectively.

3.2. Association between air pollutants exposure and in-hospital mortality for STEMI

To investigate the relationship between exposure to air pollutants and the risk of in-hospital mortality caused by STEMI, a binary logistic regression model was employed. After adjusting for covariates such as current smoker, dyslipidemia, Killip classification, as well as meteorological factors like temperature and humidity, Figure 1 demonstrates that the interquartile range (IQR) increments of NO2 exhibit significant associations with the risk of in-hospital mortality. Specifically, these associations are observed on lag 2 (OR:1.824, 95%CI:1.142-2.313, p=0.012), lag 3 (OR:2.093, 95%CI:1.299-3.371, p=0.002), and lag 0-3 (OR:1.670, 95%CI:1.054-2.646, p=0.029).

To clarify the seasonal effect of each air pollutant on STEMI outcome, a binary logistic regression model was conducted according to the warm season (April to September) and cold season (October to March). Based on the findings presented in Figure 2, it can be observed that during the warm season, there was a significant association between NO2 and the risk of in-hospital mortality on lag 3 (OR: 3.266, 95% CI: 1.203-8.864, p=0.02). However, during the cold season, the effect of NO2 was not statistically significant. During the cold season, PM10 was found to have a significant association with the risk of in-hospital mortality on lag 3 (OR:2.792, 95%CI:1.115-6.993, p=0.028); however, the effect of PM10 was not statistically significant during the warm season.

The relationship between NO2 levels and the risk of STEMI was assessed to determine the exposure-response association. Figure 3 shows that decreased levels of NO2 were significantly associated with a decreased risk of in-hospital mortality compared to higher levels of NO2 (Q4, >21.9 ppb). Compared to Q4 level NO2, exposure to Q1 level (NO2<11.6 ppb), Q2 level (NO2 16.4-16.4 ppb), and Q3 level (NO2 16.4-21.9 ppb) were significantly associated with a decreased risk for in-hospital mortality, and the ORs (95%CIs) were 0.280 (0.093–0.842, p=0.023), 0.355 (0.140–0.898, p=0.029), and 0.386 (0.164–0.906, p=0.029), respectively.

4. Discussion

In this study, we conducted an assessment to determine the impact of air pollution on the short-term prognosis of STEMI. The results indicate that NO2 might have a significant influence on the risk of in-hospital mortality in Kaohsiung, Taiwan. Among the various air pollutants analyzed, higher levels of NO2 exposure were found to be associated with an elevated risk of in-hospital mortality in patients diagnosed with STEMI, especially during the warm season. In contrast, it was observed that higher levels of PM10 exposure were linked to an elevated risk of in-hospital mortality among patients diagnosed with STEMI specifically during the cold season.

Numerous epidemiological studies have provided evidence supporting the detrimental effects of air pollution on MI. Bañeras et al. conducted a population-based study that included all STEMIs in Barcelona and found that PM2.5, PM10, and NO2 were positively associated with the incidence of STEMI [2]. In contrast, a separate study that investigated the relationship between air pollution and acute coronary syndrome found that NO2 exposure was positively associated with STEMI incidence, whereas the association between PM2.5, PM10 exposure and STEMI did not reach statistical significance [17]. A recent article reviewed 56 studies and concluded that PM2.5, PM10, and NO2 were related to an increased risk of hypertension and subsequent MI [5]. However, few studies have focused on the relationship between short-term outcomes of STEMI and air pollution. In the current study, NO2 was positively associated with the risk of in-hospital mortality in patients with STEMI, especially during the warm season, and PM10 exposure levels were associated with an increased risk of in-hospital mortality in patients with STEMI during the cold season. Numerous toxicological studies have attempted to elucidate the mechanisms underlying health hazards caused by air pollution. In terms of pulmonary toxicity, cell-based studies have shown that exposure to PM activates nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and triggers the NF-κB-mediated inflammatory response, leading to an increase in inflammatory cytokines such as interleukin (IL)-6, IL-8, and IL-1β in human tracheal epithelial cells [18], while animal experiments have demonstrated that exposure to PM causes infiltration of inflammatory cells in the lungs, thickening of the tracheal epithelium, and alveolar rupture [8]. These inflammatory substances include cytokines, activated immune cells, and factors that induce vascular activity, such as endotoxins, histamine, and microparticles, which are involved in the inflammatory response and enter extrapulmonary organs through the bloodstream [19,20]. In addition, exposure to NO2 has also been found to increase the levels of inflammation markers in the blood, including C-reactive protein (CRP), tumor necrosis factor-α, IL-6, and coagulation-related factors such as fibrinogen, as well as tissue repair marker hepatocyte growth factor [21]. These inflammatory cytokines and coagulation-related factors may cause vasoconstriction and affect clot formation in vascular endothelial cells [22]. In contrast, ultrafine particles (UFP) and certain components of PM, such as organic compounds and heavy metals, may directly penetrate the alveolar and capillary barriers of the lungs, enter the systemic circulation, and induce vascular injury [23,24]. Furthermore, while causing inflammation in the lungs, the interaction between air pollutants and lung receptors can lead to reflex responses in the autonomic nervous system, resulting in an increased heart rate, vasoconstriction, and other reactions [25,26]. Increased heart rate, vasoconstriction, disturbances in vascular endothelial clot formation, and coagulation biomarkers may affect the outcomes of MI. Animal studies have shown that exposure to NO2 can interfere with the regulation of endothelial nitric oxide synthase and intercellular adhesion molecule 1 in vascular endothelial cells, whereas exposure to PM2.5, has been found to interfere with the regulation of the renin-angiotensin system, which regulates blood pressure, possibly leading to increased blood pressure and enhanced coagulation responses [27,28].

Our study findings support the existence of a positive correlation between NO2 exposure and the in-hospital mortality rate among patients with STEMI, particularly during the warm seasons. In contrast, PM10 was found to be positively associated with the in-hospital mortality rate among patients with STEMI during the cold season. The effects of air pollution on human health exhibit seasonal variations. For example, Hsu et al. found a significant connection between PM2.5, concentration, and hospitalization for cardiovascular diseases, with a particular emphasis on the winter season [29]; while Huang et al. found a correlation between elemental carbon in PM2.5 and the risk of chronic obstructive pulmonary disease (COPD) ED visits, particularly during the warm season [30]. This can be attributed to several factors. First, the sources and composition of PM pollution particles vary across seasons, which may result in different health hazards. For example, PM2.5, measured at roadside locations, contains high levels of metal components, such as copper, zinc, iron, and calcium, from vehicle emissions and road dust, which are more than twice the levels found in urban background locations [31]. PM is composed of particles of different sizes and chemical characteristics, and its health effects may differ depending on the composition of the components. Altemose et al. collected PM2.5, data before, during, and after the 2008 Beijing Olympics and measured coagulation-related biomarkers in the plasma of 128 volunteers as well as oxidative stress indicators in their exhaled breath. The results showed that PM2.5, generated by automobiles, factories, and biomass burning, is positively associated with lung inflammation-related biomarkers. The increase in oxidative stress was related to emissions from factories and vehicles, while coagulation-related biomarkers, such as the von Willebrand Factor (vWF), were positively associated with the combustion of fossil fuels [32]. Hwang et al. obtained data from Taiwan’s National Health Insurance program and found a direct correlation between PM2.5 and asthma, especially for nitrate (NO3-) of PM2.5 [33]. Toxicological evidence also suggests that exposure to water-soluble extracts of PM2.5 could cause a proliferative response in the livers of mice, while insoluble particles can cause an inflammatory response and an increase in apoptosis regulation in the livers of mice [34]. Secondly, different PM components in particulate matter may interact with gaseous pollutants, resulting in different health risks. For instance, the interaction between sulfate and nitrate in PM2.5 and ozone (O3) may elevate the likelihood of pediatric pneumonia ED visits [35]. Third, changes in temperature may have an additive effect on health hazards caused by air pollution. For instance, Imaizumi et al. documented a direct correlation between exposure to PM2.5 and morning hypertension, and noted that this effect was strengthened by low temperatures [36].

4.1. Limitations

This study is subject to several limitations that should be acknowledged and taken into consideration. Firstly, the research was conducted at a single hospital, and the sample size was relatively small. This may restrict the generalizability of the findings to a larger population. Secondly, the study was conducted in a tropical city, and the results may not be applicable to regions with different ethnic compositions and meteorological conditions. Moreover, personal exposure to air pollutants can be influenced by factors such as air-conditioning usage and outdoor activities, which may vary across different geographical locations and can potentially affect the observed associations in this study.

5. Conclusions

To summarize, our study indicates that exposure to NO2 and PM10 might elevate the likelihood of poor prognosis in patients with STEMI. It is worth noting that the effects of NO2 were more pronounced particularly in warm seasons, while the impact of PM10 were more significant during the cold season. These findings highlight the need for targeted regulations aimed at reducing PM10 and NO2 levels to improve the outcomes for patients with STEMI.