Air Pollution and In-Hospital Mortality of Ischemic Heart Disease Patients

MATERIALS AND METHODS

Study population: The study was conducted in THC. Patients admitted to THC are mainly residents of Tehran.

Study design: This is a cross sectional study. The exposure level of IHD patients expired in hospital during the Autumn 2005 was compared to that of IHD patients discharged alive during the same period.

Patients admitted in THC during the Autumn 2005 (23 September until 21 December 2005) with primary diagnosis of IHD, were recruited into the study. This period of time spanned duration of air pollution crisis. In case electrophysiological and enzymatic investigation did not confirmed IHD diagnosis for a patient, he/she was excluded from the study.

Patients' data were gathered from the hospital databank which contains demographic, clinical and paraclinical data of all patients admitted since January 2003 (the beginning of the hospital activity) under rigid quality control supervision.

The study was ethically approved in THC board of review. The ethical committee waived the need for patients' written consent considering all data were gathered from hospital databank and the fact that patients had already permit the hospital by written consent to use their data anonymously for research purposes.

Exposure measurement: Meteorological data from 23 September until 21 December 2005 (Autumn 2005) were obtained from AQCC. The daily mean concentration of the air pollutants over the whole city was used as exposure level. The acquired data included hourly concentration of nitrogen dioxide (NO₂), nitrous oxide (NO), other nitrogen compounds (NOx), sulfur dioxide (SO₂), carbon monoxide (CO), 8 h ground level ozone (O₃), dust (including particulate pollutants with diameter 2.5 to 10 μm), hydrocarbons (CH) and non-methane hydrocarbons (NMHC).

We used two different indices as exposure level. The first was the daily mean concentration of air pollutants at the date of admission of patients. The second measure was mean concentration of air pollutants at the date of admission and the three following days which was calculated for every patient.

To control the effect of age and AMI on relationship between air pollution level and in hospital mortality, logistic regression approach was used. We considered in hospital mortality as dependant variable and forced AMI and age into the model then put air pollutants in the logistic model. Considering the correlation of every air pollutant with other pollutants, we did not put all pollutants in the same model instead; we fitted several models each containing age, AMI and daily mean concentration of one single pollutant.

The p-value <0.05 was considered significant.

RESULTS

During the Autumn, 1242 patients eligible to this study were admitted to THC; they were consisted of 557 (44.8%) female and 685 (55.2%) males. The mean age of male patients was 60.4 (SD:12.76) years and that of females was 63.8 (SD: 10.95); the difference was statistically significant (p<0.001). Twenty three patients expired in hospital during the Autumn 2005. The general in-hospital mortality rate was similar in both genders: 1.9% for men and 1.8% for women. The AMI was more common in men (31.1%) compared to women (14.7%) (p<0.001). Patients expired in hospital were older than patients discharged alive and the difference was statistically significant (Table 1).

Table 2 shows the daily mean concentration of air pollutants at admission date of patients died in hospital compared to patients discharged alive. The mean concentration of CO, dust, NO, NOx and SO₂ were significantly higher at admission date of died patients. There was not statistically significant difference in wind speed and mean concentration of hydrocarbons and O₃ at admission date of died patients compared to others.

To control the effect of AMI and age on the association between mortality and air pollutants we used logistic regression. The association between daily mean concentration of CO, dust, NO, NOx and SO₂ remained statistically significant after controlling the effect of AMI and age (p<0.05).

We attempted to determine either the air pollution level at the admission date or the air pollution during hospitalization had more strong relationship with in-hospital mortality.

Table 1:	Characteristics of IHD patients died in hospital and patients discharged alive
SD: Standard deviation; AMI: Acute myocardial infarction

Table 2:	Daily mean concentration of air pollutants at admission date of patients died in hospital and patients discharged alive
CH: Hydrocarbon, CO: Carbon monoxide, NO: Nitrous monoxide, NOx: Nitrous oxide, SO2: Sulfur dioxide, ppm: Part per million

Table 3:	Mean concentration of air pollutants in first 4 days of admission of patients died in hospital and patients discharged alive
CH: Hydrocarbon, CO: Carbon monoxide, NO: Nitrous monoxide, NOx: Nitrous oxide, SO2: Sulfur dioxide, ppm: Part per million

We calculated mean concentration of the air pollutants at the date of admission and three subsequent days for every patient as another measurement of exposure level (Table 3). The mean concentrations of NO, NO₂, NOx, SO₂, dust and CH were significantly higher at admission date and three following days of patients died in hospital.

DISCUSSION

Occurrence of air pollution crisis in Autumn 2005 triggered the present study to evaluate the effect of air pollution on the IHD patients' mortality as vulnerable people to air pollution. In this study, we did not intend to evaluate underlying mechanism of relationship between air pollution and mortality; instead, we documented this relationship specifically on in-hospital mortality. According to our findings, there is a significant relationship between air pollution and in-hospital mortality. This finding is in agreement with some other studies (Zeller et al., 2006).

There are some explanations for such a relationship in the literature. Atherothrombotic effect of air pollutants could lead to myocardial infarction and ischemic stroke (Zeller et al., 2006). Many studies proposed different underlying mechanisms including inflammatory responses leading to plasma histamine activity and thrombotic tendency (Nemmar et al., 2001, 2002, 2005; Hoek et al., 2001; Khandoga et al., 2004) increased volume and advanced phenotype of coronary atherosclerosis (Suwa et al., 2002), altered endothelial function and activated sympathetic response (Rajagopalan et al., 2005).

A study by Peters et al. (2001) concluded that age older than 60 years is a risk factor for cardiovascular mortality after exposure to air pollution. The mean age of patients admitted in THC was more than 60 years.

Air pollution might cause deterioration of health status of patients with lower cardiovascular reservoir. This may increase frequency of refer of patients with serious cardiovascular diseases to the hospital, which in turn results in increased in-hospital mortality. Other explanations of increased in hospital mortality following air pollution crisis might be as following: increased risk of myocardial infarction following exposure of susceptible persons to air pollution (Peters et al., 2004; Vermylen et al., 2005), heart rate variability in AMI patients exposed to air pollution (Wheeler et al., 2006), increased risk of MI among patients exposed to pollution (D'Ippolitti et al., 2003; Von klot et al., 2005) and increased mortality in MI patients (Biggeri et al., 2004). Adjustment of the effect of AMI and age did not remove the difference in air pollutants level among cases and controls. We conclude that air pollution has an independent effect on in-hospital mortality. As mentioned above, we did not intend to investigate the probable underlying mechanism of impact of air pollution on cardiovascular mortality; but as a presumable cause we can lay stress on arrhythmias (Wheeler et al., 2006; Anderson et al., 2003), aggravation of baseline risk factors (Anderson et al., 2003) and cytokines derangement (Brook et al., 2004).

Besides, another probable explanation for raised in-hospital mortality might be the effect of indoor air pollution. Although, THC has utilized HEPA filtering system which purifies dust and particulate matters, it is not capable of absorption of gaseous pollutants including CO, SO₂, NO and NOx. The higher mean concentration of pollutants in the first 4 days of admission of died patients, is consistent with this hypothesis. According to a detailed study by department of environment of Australia, indoor air pollution (especially NO₂, CO and CH) is 3-5 times more than outdoors. The reason is simple: there is no source of air production within buildings and the air inside buildings originates from outdoors atmosphere.

Barnett et al. (2006) showed that CO, NO₂ and particulate pollutants significantly influence on cardiovascular admissions in the elderly. This could partly explain the association of air pollution and in hospital death. Meanwhile, increased admission of elderly could not be considered the only reason of relationship between air pollution and in-hospital mortality as the association remained significant after adjustment for age.

PM10 is represented to be responsible for higher admission for cardiovascular diseases, AMI occurrence and increases cardiovascular mortality (Brook et al., 2004). In the present study, we failed to separate the components of dust, but since dust is composed of particulate matters (including PM2.5 and PM10) we may extend our finding about dust to the particulate pollutants.

Present study was subject to limitations. We did not measure the air pollution level of admitted patients' home. Patients' exposure to air pollution at their home or work place may affect their hospitalization outcome and we were not able to measure it. It was not possible to differentiate Particulate Matter pollution according to particle size. We measured all particulate matters generally as dusts.

CONCLUSION

We found significant direct association between air pollution level (mostly CO, dust, NO, NOx and SO₂) and in-hospital mortality of ischemic heart disease patients. This association remained significant after adjustment for AMI and age of patients.

ACKNOWLEDGMENTS

We appreciate AQCC, especially Yusef Rashidi, CEO of AQCC, Solmaz Ahadi and Shima Almasi (both in charge of data monitoring). We also especially thank Zohre Mansour Khosravi (Senior Meteorologist and in charge of Tehran province weather prediction, Islamic Republic of Iran Meteorological Organization). This study is funded by Clinical and Experimental Research Unit, Tehran Heart Center hospital, Tehran University of Medical Sciences.