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Association between daily mortality from respiratory and cardiovascular diseases and air pollution in Taiwan
ARTICLE IN PRESS Environmental Research 109 (2009) 51–58
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Association between daily mortality from respiratory and cardiovascular diseases and air pollution in Taiwan Wen-Miin Liang a,b, Hsing-Yu Wei a, Hsien-Wen Kuo a,c, a b c
Institute of Environmental Health, Department of Public Health, School of Public Health, China Medical University, Taichung, Taiwan, ROC Biostatistics Center, China Medical University, Taichung, Taiwan, ROC Institute of Environmental and Occupational Health Sciences, National Yang-Ming University, No. 155, Sec. 2, Linong Street, Taipei, 112 Taiwan, ROC
a r t i c l e in fo
abstract
Article history: Received 17 April 2007 Received in revised form 24 September 2008 Accepted 1 October 2008 Available online 21 November 2008
Background: Many studies have investigated the effects of air pollutants on disease and mortality. However, the results remain inconsistent and inconclusive. We thought that the impact of different seasons or ages of people may explain these differences. Methods: Measurement of the five pollutants (particulate matter o10 mm in aerodynamic diameter (PM10), SO2, NO2, O3, and CO) was monitored by automated measuring units at five different stations. Monitoring stations were provided by the Taiwan Environmental Protection Agency (EPA) from 1997 to 1999. The subjects in the study were classified in two groups: those 65 years of age and older, and those of all ages (including the subjects in the X65 group). Data on daily mortality caused by respiratory disease, cardiovascular disease, and all other causes including the two aforementioned was collected by the Taiwan Department of Health (DOH). A time-series regression model was used to analyze the relative risk of respiratory and cardiovascular diseases due to air pollution in the summer and winter seasons. Results: Risk of death from all causes and mortality from cardiovascular diseases during winter was significantly positively correlated with levels of SO2, CO, and NO2 for both groups of subjects and additionally with PM10 for the elderly (X65 years old) group. There were significant positive correlations with respiratory diseases and levels of O3 for both groups. However, the only significant positive correlation was with O3 (RR ¼ 1.283) for the elderly group during summer. No other parameters showed significance for either group. Conclusion: Our findings contribute to the evidence of an association between SO2, CO, NO2, and PM10 and mortality from respiratory and cardiovascular diseases, especially among elderly people during the winter season. Crown Copyright & 2008 Published by Elsevier Inc. All rights reserved.
Keywords: Daily mortality Respiratory and cardiovascular disease Air pollution
1. Introduction Previous epidemiological research (Maheswaran et al., 2005; Pinkerton and Joad, 2006; Medina-Ramon et al., 2006) has consistently demonstrated an association between levels of ambient air pollutants and daily mortality, hospital admissions, and emergency room visits from respiratory and cardiovascular disease (CVD). With the exception of particulate matter, the relationship between gaseous air pollutants (ozone, nitrogen dioxide, sulphur dioxide, and carbon monoxide) and mortality has been inconsistently reported in Asia. Studies from Asian
Corresponding author at: Institute of Environmental and Occupational Health Sciences, National Yang-Ming University, No. 155, Sec. 2, Linong Street, Taipei, 112 Taiwan, ROC. Fax: +886 2 28278254. E-mail address: [email protected] (H.-W. Kuo).
countries are scarce, possibly due to incomparable study methods and air quality monitoring equipment, and there has been a lack of assessment of individual exposure to air pollutants and their relationship to mortality. However, recent improvements in economic conditions and environmental awareness in Taiwan have led to the allocation of resources to perform widespread air monitoring on the island. The APHEA-2 project was conducted and tested to determine whether deaths from respiratory and CVDs are advanced by just a few days or possibly many weeks using a multi-city hierarchical modeling approach for all ages and stratified by age groups. This study confirms that most of the effects of air pollution persist for more than a month after exposure and prolonged exposure to air pollution is associated with premature mortality in people suffering from respiratory and CVDs (Zanobetti et al., 2003). In Taiwan, summers are hot with high and humid, whereas winters are typically mild and dry. Urbanization is widespread and a large
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proportion of the population resides in high-rise buildings in close proximity to road traffic. Diesel vehicles are a major source of air pollution in urban areas and contribute a substantial proportion of inhalable particles. Levels of PM10, NOx, and CO in Taiwan are higher than cities of comparable population size in the United States and Europe. In Ohio, USA, a study by Schwartz and Dockery (1992) showed, after controlling for season, temperature and SO2 using Poisson regression, there was a strong positive correlation between total suspended particles (TSP) and daily death rates. When concentrations of TSP increased by 100 mg/m3, the death rate increased by 4% (RR ¼ 1.04). After adjusting for season and meteorological conditions, a 100 mg/m3 increase in PM10 concentration was found to cause a 16% and 17% increase in the daily death rates in St. Louis and East Tennessee, respectively (Dockery et al., 1992). There was a strong positive correlation between PM10 concentrations (5 days prior to recorded death) and nonaccidental death rates. An increase of 100 mg/m3 resulted in a 43% and 20% increase in the daily mortality from respiratory diseases and CVD, respectively. A longitudinal study by Pope et al. (1992) in Philadelphia (1974–1988) shows that after adjusting for season and temperature using Poisson regression, mortality is related to air pollutant concentrations. When TSP, SO2, and O3 increased by 34.7 mg/m3, 12.9 ppb, and 20.2 ppb, respectively, the mortality rate, increased by 1%, 1%, and 2%, respectively. Many studies show a correlation between air pollutants and mortality, yet the relationship remains unclear due to a complex interaction of multiple factors including those temporal and spatial. Moreover, since different populations are exposed to a complex mixture of air pollutants that vary in composition with geography and climatic conditions, much of the recent work in air pollution study has focused on individual components of human health. Unfortunately conclusions based on previous studies are unclear due to heterogeneric study areas that provide inconsistent findings. Few studies have considered the effects of age on deaths caused by air pollution. Since elderly people are more sensitive to their environment, our study considered air pollution-related deaths from respiratory and, CVD and all causes of death in elderly people as well as separately in addition to the all-ages group. Furthermore, by categorizing data into seasons, we were able to more accurately determine the effects of air pollution.
2. Materials and methods 2.1. Settings Our study population comprised of residents from Central Taiwan during 1997–1999. Population density in the study area was high and the area considered a metropolis, geographically situated in a basin. 2.2. Outcomes Daily mortality data was collected by the Taiwan Department of Health (DOH). Cause of death was classified according to the International Classification of Diseases Revision 9 (ICD-9): all causes of death excluding accidents ICD9 code 4800, respiratory disease ICD9 codes 460–519, CVD codes 390–459. Death certificates, the accuracy of which has recently improved, were obtained from the DOH. Nevertheless, our study was a longitudinal study and therefore errors in the raw data are assumed random. 2.3. Air pollutants/exposure assignment Hourly concentration data for particulate matter o10 mm in aerodynamic diameter (PM10), SO2, NO2, O3, and CO were monitored by automated measuring units at five different stations. Monitoring stations were provided by the Taiwan Environmental Protection Agency (EPA). Temperature and dew point were obtained similarly. With the exception of O3 (taken as a maximum 8-h average from 9:00 am to 17:00 pm) and CO (taken as a maximum 8-h average), every 24-h
an arithmetic average reading was determined for each station and an arithmetic average was calculated over all stations. Analysis of air pollution included 24-h concentration averages of SO2 (UV fluorescence), CO (non-dispersive infrared photometry), NO2 (chemiluminescen), PM10 (B-ray attenuation method), and maximum 8-h average O3 (Ultraviolet photometry).
2.3.1. Analysis Analyses of relative risk of respiratory and cardiovascular and all causes of death due to air pollution for both all-ages and X65 groups were determined using a time-series regression model separately for each season, in which the error term is regressed by parameters accounted for autoregressive and moving average effects (Bowerman and O’Connell, 1993). First, a base model was determined by finding appropriate lag and accumulated effects of each single pollutant in assessing its effect on mortality after adjusted for year effect, month effect, week effect, holiday effect, and temperature effect. To observe the influence of the lag effect and accumulative effects for each air pollutant on mortality, under different conditions, such as a 1-day lag with 2 accumulative days, which means we take the average of the values from yesterday and the day before yesterday. In our analysis, we tried each of combinations of ‘‘lag effect (0–5 days)’’ and ‘‘accumulated effect (1–5 days)’’. In a model using lag i accumulated over j days, the covariate is averaged over lags i to i+j1. Among those models for each analysis, the final model was determined according to the minimized value of the AIC (Littell et al., 1996). For example, for mortality of all causes in the summer term, the final base model for PM10 was with 1 day lag and 1 day accumulated for all-ages group, while for SO2, the final base model was with 2 days lag and 3 days accumulated. Secondly, to avoid too many parameters in model which would reduce the prediction power, backward selection method were used to determine the final model according to the p-value removal criteria. The risk ratio (RR) and its 95% confidence interval (CI) for an interquartile range (IQR, between the 25th and 75th percentile) increase of each pollutant from the final model were shown. Since air pollutants vary by season in Taiwan, ‘‘spring season’’ (March–May), ‘‘summer season’’ (June–August), ‘‘autumn season’’ (September–November) and ‘‘winter season’’ (December–February) were categorized and assessed. Based on these seasons, there may be different patterns of relationships between ambient air pollutants and the three causes of mortality. We only show the results from summer and winter since no results from spring and autumn was significant in our analysis. All statistical tests were two-sided. Values of po0.05 were considered statistically significant.
3. Results Mean levels of air pollutants and meteorological variables are presented in Table 1. Values were lowest during summer months with the exception of ozone (O3). Particulate matter and O3 were highest during the fall. Temperatures and dew points were highest in summer, followed by fall, spring, and winter. Figs. 1a–c illustrate mean daily deaths from all causes of death, respiratory disease, and CVD, respectively, according to season. Data on all-ages and elderly participants (X65 years old) are also presented. Death rates were lowest in summer and highest in winter for both the all-ages and elderly groups. Death rates from CVDs and respiratory diseases showed similar trends. Meanwhile, the all-ages group showed little difference in death by respiratory disease between the summer and fall. Correlation values between air pollution parameters are provided in Table 2. PM10 levels were significantly positively correlated with all other air parameters. Other significant positive correlations include SO2 with NO2 (r ¼ 0.70) and CO (r ¼ 0.56) as well as NO2 with CO (r ¼ 0.78). All pollutants with the exception of O3 were found to have a significant negative correlation with temperature and dew point at po0.001. Figs. 2a and b indicate, according to summer and winter weather, the risk of death from all causes associated with each air pollutant when pollutant levels increase per IQR. The values of IQR in each air pollutant were shown in Table 3. With the exception of the ozone pollutants, IQR levels of air pollutants in winter were consistently higher than in the summer. The risk of death during winter was significantly positively correlated with all air pollutants, with the exception of O3, for the all-ages (a) and elderly (X65) (b) groups, and PM10 for the all-ages group. During summer, only two significant positive correlations were evident in
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Table 1 Air pollutants and meteorological variables by season Pollutanta
Season
Number
Meanb
SD
Min
Max
PM10 (mg/m3)
Springc Summer Fall Winter
276 276 272 269
68.70 39.39 69.62 66.70
29.21 17.26 30.45 33.73
18.95 17.64 18.14 17.61
190.44 108.26 184.44 186.69
SO2 (ppb)
Spring Summer Fall Winter
276 276 272 270
4.82 2.84 4.56 4.81
2.31 1.72 2.58 3.09
0.93 0.54 0.60 0.28
14.19 10.42 13.80 19.62
NO2 (ppb)
Spring Summer Fall Winter
276 276 272 270
28.04 17.76 26.89 28.30
7.40 4.54 7.68 7.83
13.53 8.19 9.67 11.68
57.50 37.19 55.26 55.92
CO (ppm)
Spring Summer Fall Winter
276 276 272 270
1.10 0.85 1.12 1.13
0.33 0.28 0.39 0.49
0.48 0.42 0.35 0.37
2.46 2.14 2.51 2.76
O3 (ppb)
Spring Summer Fall Winter
276 276 272 270
40.71 31.20 45.57 28.62
16.39 14.95 17.10 11.50
5.28 5.16 4.22 3.52
96.58 90.03 90.61 64.44
Temperature (1c)
Spring Summer Fall Winter
276 276 272 270
23.51 28.30 25.03 17.47
3.34 1.71 2.62 3.06
14.09 21.94 16.09 7.43
29.28 31.36 30.07 24.67
Dew point (1c)
Spring Summer Fall Winter
276 276 272 270
18.41 23.07 20.19 13.59
2.96 1.61 3.26 3.71
8.22 17.89 6.06 -2.78
23.44 26.61 25.19 20.42
N ¼ 1095 days. a PM10, SO2, NO2: daily mean; CO: 8-h maximum; O3: 8-h mean (9 am–5 pm). b The daily average of air pollutant is from five air monitoring stations. c spring: March–May; Summer: June–Aug.; Fall: September–November; Winter: December–February 12, 1–2 months.
the elderly group between the risk of death with NO2 (RR ¼ 1.058) and CO (RR ¼ 1.054). No other pollutants showed significance for either group. Figs. 3a and b illustrate, according to summer and winter weather, the risk of death from respiratory diseases associated with each air pollutant when pollutant levels increase from 25% to 75%. The risk of death during winter was significantly positively correlated with O3 for both groups and additionally SO2 for the elderly (X65) (b) group. During summer, the only significant positive correlation was with O3 (RR ¼ 1.283) per IQR increase for the elderly group. No other pollutants showed significance for either group. Figs. 4a and b show, according to summer and winter, the risk of death from CVD associated with each air pollutant when pollutant levels increase per IQR. The risk of death during winter was significantly positively correlated with SO2 (RR ¼ 1.087 and RR ¼ 1.150), NO2 (RR ¼ 1.15 and RR ¼ 1.27), and CO (RR ¼ 1.238 and RR ¼ 1.416) per IQR increase for both the all-ages and elderly groups. The elderly group (X65) (b) had an additional correlation with PM10 (RR ¼ 1.194) during winter. During summer, the only significantly positive correlation was with NO2 (RR ¼ 1.188) per IQR increase for the elderly group.
Fig. 1. (a–c) Daily mortality from all causes of death, all respiratory causes and all cardiovascular causes by season and age (scale for all ages shown on the left axis; for X65 ages shown on the right axis) (1997–1999, N ¼ 1095 days).
Table 2 Correlation matrix between air pollutants and meteorological variables, in Taichung (1997–1999) PM10
SO2
NO2
CO
O3
Temperature Dew point
1.00 PM10 SO2 0.69a 1.00 NO2 0.78a 0.70a 1.00 CO 0.64a 0.56a 0.78a 1.00 O3 0.57a 0.42a 0.36a 0.21a 1.00 Temperature 0.12a 0.12a 0.35a 0.15a 0.27a 1.00 Dew point 0.16a 0.15a 0.35a 0.10a 0.12a 0.93a a
1.00
po0.001.
Table 4 shows the best lag effect and cumulative effect using the single pollutant model in summer and winter. We noticed a difference in the lag effect and cumulative effect between summer
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Fig. 2. (a and b) Summer and winter risk estimates of all causes of death (all ages shown on top; X65 ages shown on the bottom) for five pollutants (triangle represents summer; diamond represents winter).
Table 3 Inter-quartile range (IQR) of air pollutants for summer and winter seasons Pollutants Unit Summer Winter
PM10 mg/m3 15.55 39.98
SO2 ppb 1.76 2.70
NO2 ppb 6.09 10.22
CO ppm 0.31 0.70
O3 ppb 14.73 14.87
and winter. Different pollutants showed a difference in the lag effect and cumulative effect in summer and winter. Different causes of death also showed a difference in the lag effect and cumulative effect in summer and winter. The results using multi-pollutant models in summer were not significantly different. Table 5 shows only results using both single and multi-pollutant models in winter. Table 5 shows selected relative risk estimates (75th vs. 25th percentile) for pollutants having significant effects using both the single and multipollutant models. CO and O3 significantly affected all causes of death in winter using multi-pollutant models. In addition, CO also significantly affected all causes of death in winter using the single
pollutant model. Furthermore, O3 significantly affected deaths due to respiratory diseases in winter using both single and multipollutant models. Likewise, CO significantly affected deaths due to CVD in winter using both single and multi-pollutant models. CO also significantly affected deaths due to CVD in winter in people aged 65 and older using both single and multi-pollutant models.
4. Discussion In this study, lag patterns of air pollutants with cause-specific mortality were assessed for each single pollutant model adjusted for year effect, month effect, week effect, holiday effect, and temperature effect separately by season. The patterns were different among cause-specific mortality, age group, pollutant, and season. For respiratory disease in the all-age group, there were no lag effects for PM10, SO2, and NO2, while CO and O3 had a lag effect of 2 days. For CVD in the elderly group, PM10 and O3 showed no lag effects. Generally speaking, our study found that optimal lags ranged from 0 (concurrent) to 2 single lag days and
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Fig. 3. (a and b) Summer and winter risk estimates of all respiratory causes (all ages shown on top; X65 ages shown on the bottom) for five pollutants (triangle represents summer season; diamond represents winter season).
1–3 cumulative lag days. Although our findings are similar to a previous study presented by Wong et al. (2001), we found a significant effect by PM10 on all causes of death and CVD for the elderly group in winter, which was not found in Wong’s study. However, Wong’s study failed to classify different age groups or seasons. Risk estimates for mortality due to CVD for the all-age group and the elderly group were 4.0% and 5.6%, respectively in summer, and 12% and 19.4%, respectively in winter, per IQR increase of PM10. These results are high compared to previous studies by Zanobetti et al. (2003) and Wong et al. (2001) which found values for cardiovascular death of 1.97% and 1.70% per 10 mg/m3, respectively. A 10 mg/m3 increase in PM10 was associated with a 0.72% (95% confidence interval 0.35–1.10%) increase in the rate of admissions for people suffering from congestive heart failure on the same day. Wellenius et al. (2006) found associations between exposure to particles and certain markers of CVD, including decreased heart rate variability. The effects of PM10 appeared to be less severe in patients with secondary diagnoses of hypertension. These different results may be explained by the use of a different basis for measuring PM10 across studies. For example
our study used IQR PM10 values of 15 and 40 mg/m3 in summer and winter, respectively. Therefore, the results of our study indicate that both the negative health effects of PM10 and the fluctuation in its concentration is greater in winter. Our study found that elderly people were at a significantly higher risk of death from all causes and CVDs associated with PM10. Although risk ratios of respiratory deaths per IQR PM10 were greater than one, high fluctuations prevented significant findings in winter. PM10 may invoke alveolar inflammation, release inflammatory mediators, exacerbate lung conditions, and increases the blood’s ability to coagulate, thereby leading to acute episodes of CVDs (Seaton et al., 1995). Mechanisms controlling the effects of air pollutants on cardiovascular mortality and morbidity may be illustrated by changes in the blood’s ability to coagulate and changes in the nervous system’s control of the heart, possibly leading to arrhythmias (Seaton et al., 1995; Peters et al., 2000). Our study findings indicate that increased daily mortality from all causes of death and CVD are associated with SO2, NO2, and CO levels during winter. This result is in agreement with previous studies conducted in Asia (Wong et al., 2002; Chang et al., 2005).
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Fig. 4. (a and b) Summer and winter risk estimates of all cardiovascular causes (all ages shown on top; X65 ages shown on the bottom) for five pollutants (triangle represents summer; diamond represents winter).
Table 4 The best lag effect and cumulative effect in the single pollutant model PM10
SO2
NO2
CO
O3
The best lag effect and cumulative effect in the single pollutant model, in summer All causes of death 1–1 2–4 2–2 2–2 2–2 All deaths X65 age 1–2 2–4 2–2 2–2 2–2 Deaths due to respiratory diseases 0–0 0–0 0–0 2–2 2–3 Deaths due to respiratory diseases X65 age 0–0 2–4 2–4 2–2 2–3 Deaths due to cardiovascular disease 0–0 2–2 2–4 1–3 1–1 Deaths due to cardiovascular disease X65 age 0–0 2–2 2–2 2–2 0–1
The best lag effect and cumulative effect in the single pollutant model, in winter All causes of death 0–1 1–1 0–2 0–2 1–1 All causes of death X65 age 0–1 1–1 0–2 0–2 1–1 Deaths due to respiratory diseases 1–3 1–3 1–1 1–1 2–3 Deaths due to respiratory diseases X65 age 0–0 1–1 1–1 1–1 1–1 Deaths due to cardiovascular disease 0–2 0–2 0–2 0–2 1–1 Deaths due to cardiovascular disease X65 age 0–2 1–2 0–2 0–2 0–0
NO2 is correlated with plasma fibrinogen and augments the incidence of ventricular arrhythmia and ventricular tachycardia in patients with implanted cardiovascular defibrillators (Peters et al., 2000). Mortality increases in patients with angina when they are exposed to moderate levels of CO. CO has been reported to impair myoglobin’s oxygen transport and storage capacity, and even low levels of carboxyhemoglobin exacerbate myocardial ischemia in patients with coronary artery diseases (Allred et al., 1989). In a study conducted on London office workers, increased fibrinogen concentrations were associated with the previous day’s NO2 and CO levels (Pekkanen et al., 2000). However, CO and NO2 have not been associated with increased heart rate or decreased heart rate variability (Gold et al., 2000). SO2 has also been associated with cardiovascular effects and its relationship with increased CVD hospital admissions in Hong Kong (Wong et al., 1999). Alternatively, exposure to extreme temperatures is associated with an increase in daily mortality in different regions (Kunst et al., 1993; Braga et al., 2001). High temperatures have been related to an
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Table 5 Selected relative risk estimates (75th vs. 25th percentile) for pollutant having significant effects in both single and multiple pollutant models in winter PM10
SO2
NO2
CO
O3
0.898 (0.807–0.998) 1.059 (0.999–1.122)
1.026 (0.989–1.064) 1.043a (1.018–1.098)
1.034 (0.9222–1.159) 1.090a (1.027–1.157)
1.148a (1.014–1.300) 1.127a (1.052–1.208)
1.061a (1.005–1.120) 1.045 (0.998–1.095)
1.087 (0.661–1.787) 1.347 (0.990–1.833)
1.095 (0.921–1.301) 1.176 (0.998–1.384)
0.785 (0.550–1.120) 1.101 (0.906–1.351)
1.403 (0.975–2.019) 1.237 (0.993–1.541)
1.395a (1.068–1.823) 1.428a (1.126–1.811)
Cardiovascular death (in winter) Multi-pollutants 0.923 (0.743–1.146) One pollutant 1.12 (0.998–1.258)
1.046 (0.980–1.117) 1.087a (1.025–1.151)
1.021 (0.848–1.228) 1.15a (1.043–1.267)
1.246a (1.017–1.527) 1.238a (1.109–1.381)
0.933 (0.845–1.029) 0.943 (0.862–1.031)
Cardiovascular death X65 age (in winter) Multi-pollutants 0.736 (0.545–0.995) One pollutant 1.194a (1.002–1.425)
1.088 (0.985–1.202) 1.150a (1.053–1.255)
1.098 (0.828–1.455) 1.270a (1.096–1.471)
1.492a (1.101–2.022) 1.416a (1.199–1.672)
1.039 (0.912–1.183) 1.039 (0.910–1.187)
All cause death (in winter) Multi-pollutants One pollutant
Respiratory death (in winter) Multi-pollutants One pollutant
a
po0.05.
increase in the frequency of hospitalization for acute myocardial infarction and congestive heart failure. However, it is also associated with a decrease in the frequency of visits for coronary atherosclosis and pulmonary heart disease among elderly residents (Koken et al., 2003). It has been postulated that the relationship between temperature and cardiovascular mortality and morbidity can be predicted from blood viscosity and cholesterol levels. An increase is related to high temperature, whereas blood pressure and fibrinogen levels increase during winter (Keatinge et al., 1986). Our study used single air pollutant on the daily mortality due to all causes, respiratory and CVDs. Risk of death from all causes and CVD during winter was significantly positively correlated with levels of SO2, CO, and NO2 for both groups of subjects and additionally with PM10 for the elderly (X65 years old) group. There were significant positive correlations with respiratory disease and levels of O3 for both groups during winter. However, the only significantly positive correlations were respiratory disease with O3 (RR ¼ 1.283) and all causes of death with NO2 (RR ¼ 1.058) and CO (RR ¼ 1.054) for the elderly group during summer. No other pollutants showed significance for either group. Because five pollutants had a high correlation with each other, the results from multi-pollutant model had a problem of multicollinearity which was hard to determine the effects of each pollutant on the CVD and respiratory tract (data not shown). Generally speaking, both single and multi-pollutant models consistently showed the daily mortality caused by CVD was significantly affected by CO pollutants, and the daily mortality of respiratory disease was greatly affected by ozone pollutants. These results support our finding that the risk of death was significantly positively correlated with SO2, NO2, and CO for both groups of subjects and additionally with PM10 for the elderly (X65 years old) group, but no significance was found for any pollutant for either group during winter from all causes of death and CVD. Our study provides insight into the adverse effects of air pollution including short-term or long-term exposure for total morality as well as specifically for mortality from respiratory and CVD.
There have not been a lot of reports about cardiovascular effects of O3, and O3 shows a lack of statistical significance. On the other hand, O3 shows a significant difference to respiratory diseases during winter. This finding is similar with a previous study (Gent et al., 2003), which indicated that a 50 ppb increase in 1-h O3 was associated with increased likelihood of wheeze (by 35%) and chest tightness (by 47%). The highest levels of O3 (1- or 8-h averages) were associated with increased shortness of breath and rescue medication use in children with asthma. However, it is likely that the long-term health effects of respiratory and CVD that we observed in this study were due to the mixture of air pollutants rather than just one component. In conclusion, our findings contribute to the evidence of an association between SO2, CO, NO2, and PM10 and mortality from respiratory and CVDs, especially among elderly people during the winter. Development of longitudinal and panel studies is needed to further elucidate the mechanisms of air pollution as they are related to mortality from respiratory diseases and CVD. References Allred, E.N., Bleecker, E.R., Chaitman, B.R., Dahms, T.E., Gottlieb, S.O., Hackney, J.D., Pagano, M., Selvester, R.H., Walden, S.M., Warren, J., 1989. Short-term effects of carbon monoxide exposure on the exercise performance of subjects with coronary artery disease. N. Engl. J. Med. 321, 1426–1432. Bowerman, B.L., O’Connell, R.T., 1993. Forecasting and Time Series: An Applied Approach, third ed. Duxbury, Pacific Grove, CA. Braga, A.L., Zanobetti, A., Schwartz, J., 2001. The lag structure between particulate air pollution and respiratory and cardiovascular deaths in 10 US cities. J. Occup. Environ. Med. 43, 927–933. Chang, C.C., Tsai, S.S., Ho, S.C., Yang, C.Y., 2005. Air pollution and hospital admissions for cardiovascular disease in Taipei, Taiwan. Environ. Res. 98, 114–119. Dockery, D.W., Schwartz, J., Spengler, J.D., 1992. Air pollution and daily mortality: associations with particulates and acid aerosols. Environ. Res. 59, 362–373. Gent, J.F., Triche, E.W., Holford, T.R., Belanger, K., Bracken, M.B., Beckett, W.S., Leaderer, B.P., 2003. Association of low-level ozone and fine particles with respiratory symptoms in children with asthma. J. Am. Med. Assoc. 290, 1859–1867. Gold, D.R., Litonjua, A., Schwartz, J., Lovett, E., Larson, A., Nearing, B., Allen, G., Verrier, M., Cherry, R., Verrier, R., 2000. Ambient pollution and heart rate variability. Circulation 101, 1267–1273.
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Keatinge, W.R., Coleshaw, S.R., Easton, J.C., Cotter, F., Mattock, M.B., Chelliah, R., 1986. Increased platelet and red cell counts, blood viscosity, and plasma cholesterol levels during heat stress, and mortality from coronary and cerebral thrombosis. Am. J. Med. 81, 795–800. Koken, P.J., Piver, W.T., Ye, F., Elixhauser, A., Olsen, L.M., Portier, C., 2003. Temperature, air pollution, and hospitalization for cardiovascular diseases among elderly people in Denver. Environ. Health Perspect. 111, 1312–1317. Kunst, A.E., Looman, C.W., Mackenbach, J.P., 1993. Outdoor air temperature and mortality in The Netherlands: a time-series analysis. Am. J. Epidemiol. 137, 331–341. Littell, R.C., Milliken, G.A., Stroup, W.W., Wolfinger, R.D., 1996. SAS System for Mixed Models. SAS Institute Inc., Cary, NC, 633pp. Maheswaran, R., Haining, R.P., Brindley, P., Law, J., Pearson, T., Fryers, P.R., Wise, S., Campbell, M.J., 2005. Small-area level ecological study. Outdoor air pollution, mortality, and hospital admissions from coronary heart disease in Sheffield, UK: a small-area level ecological study. Eur. Heart J. 26, 2543–2549. Medina-Ramon, M., Zanobetti, A., Schwartz, J., 2006. The effect of ozone and PM10 on hospital admissions for pneumonia and chronic obstructive pulmonary disease: a national multicity study. Am. J. Epidemiol. 163, 579–588. Pekkanen, J., Brunner, E.J., Anderson, H.R., Tiittanen, P., Atkinson, R.W., 2000. Daily concentrations of air pollution and plasma fibrinogen in London. Occup. Environ. Med. 57, 818–822. Peters, A., Skorkovsky, J., Kotesvec, F., Brynda, J., Spix, C., Wichmann, H.E., Heinrich, J., 2000. Associations between mortality and air pollution in central Europe. Environ. Health Perspect. 108, 283–287.
Pinkerton, K.E., Joad, J.P., 2006. Influence of air pollution on respiratory health during perinatal development. Clin. Exp. Pharmacol. Physiol. 33, 269–272. Pope III, C.A., Schwartz, J., Ransom, M.R., 1992. Daily mortality and PM10 pollution in Utah Valley. Arch. Environ. Health 47, 211–217. Schwartz, J., Dockery, D.W., 1992. Particulate air pollution and daily mortality in Steubenville, Ohio. Am. J. Epidemiol. 135, 12–19. Seaton, A., MacNee, W., Donaldson, K., Godden, D., 1995. Particulate air pollution and acute health effects. Lancet 345, 176–178. Wellenius, G.A., Schwartz, J., Mittleman, M.A., 2006. Particulate air pollution and hospital admissions for congestive heart failure in seven United States cities. Am. J. Cardiol. 97, 404–408. Wong, T.W., Lau, T.S., Yu, T.S., Neller, A., Wong, S.L., Tam, W., Pang, S.W., 1999. Air pollution and hospital admissions for respiratory and cardiovascular diseases in Hong Kong. Occup. Environ. Med. 56, 679–683. Wong, C.M., Ma, S., Hedley, A.J., Lam, T.H., 2001. Effect of air pollution on daily mortality in Hong Kong. Environ. Health Perspect. 109, 335–340. Wong, T.W., Tam, W.S., Yu, T.S., Wong, A.H.S., 2002. Associations between daily mortalities from respiratory and cardiovascular diseases and air pollution in Hong Kong, China. Occup. Environ. Med. 59, 30–35. Zanobetti, A., Schwartz, J., Samoli, E., Gryparis, A., Touloumi, G., Peacock, J., Anderson, R.H., Le Tertre, A., Bobros, J., Celko, M., Goren, A., Forsberg, B., Michelozzi, P., Rabczenko, D., Hoyos, S.P., Wichmann, H.E., Katsouyanni, K., 2003. The temporal pattern of respiratory and heart disease mortality in response to air pollution. Environ. Health Perspect. 111, 1188–1193.
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Environmental Research journal homepage: www.elsevier.com/locate/envres
Association between daily mortality from respiratory and cardiovascular diseases and air pollution in Taiwan Wen-Miin Liang a,b, Hsing-Yu Wei a, Hsien-Wen Kuo a,c, a b c
Institute of Environmental Health, Department of Public Health, School of Public Health, China Medical University, Taichung, Taiwan, ROC Biostatistics Center, China Medical University, Taichung, Taiwan, ROC Institute of Environmental and Occupational Health Sciences, National Yang-Ming University, No. 155, Sec. 2, Linong Street, Taipei, 112 Taiwan, ROC
a r t i c l e in fo
abstract
Article history: Received 17 April 2007 Received in revised form 24 September 2008 Accepted 1 October 2008 Available online 21 November 2008
Background: Many studies have investigated the effects of air pollutants on disease and mortality. However, the results remain inconsistent and inconclusive. We thought that the impact of different seasons or ages of people may explain these differences. Methods: Measurement of the five pollutants (particulate matter o10 mm in aerodynamic diameter (PM10), SO2, NO2, O3, and CO) was monitored by automated measuring units at five different stations. Monitoring stations were provided by the Taiwan Environmental Protection Agency (EPA) from 1997 to 1999. The subjects in the study were classified in two groups: those 65 years of age and older, and those of all ages (including the subjects in the X65 group). Data on daily mortality caused by respiratory disease, cardiovascular disease, and all other causes including the two aforementioned was collected by the Taiwan Department of Health (DOH). A time-series regression model was used to analyze the relative risk of respiratory and cardiovascular diseases due to air pollution in the summer and winter seasons. Results: Risk of death from all causes and mortality from cardiovascular diseases during winter was significantly positively correlated with levels of SO2, CO, and NO2 for both groups of subjects and additionally with PM10 for the elderly (X65 years old) group. There were significant positive correlations with respiratory diseases and levels of O3 for both groups. However, the only significant positive correlation was with O3 (RR ¼ 1.283) for the elderly group during summer. No other parameters showed significance for either group. Conclusion: Our findings contribute to the evidence of an association between SO2, CO, NO2, and PM10 and mortality from respiratory and cardiovascular diseases, especially among elderly people during the winter season. Crown Copyright & 2008 Published by Elsevier Inc. All rights reserved.
Keywords: Daily mortality Respiratory and cardiovascular disease Air pollution
1. Introduction Previous epidemiological research (Maheswaran et al., 2005; Pinkerton and Joad, 2006; Medina-Ramon et al., 2006) has consistently demonstrated an association between levels of ambient air pollutants and daily mortality, hospital admissions, and emergency room visits from respiratory and cardiovascular disease (CVD). With the exception of particulate matter, the relationship between gaseous air pollutants (ozone, nitrogen dioxide, sulphur dioxide, and carbon monoxide) and mortality has been inconsistently reported in Asia. Studies from Asian
Corresponding author at: Institute of Environmental and Occupational Health Sciences, National Yang-Ming University, No. 155, Sec. 2, Linong Street, Taipei, 112 Taiwan, ROC. Fax: +886 2 28278254. E-mail address: [email protected] (H.-W. Kuo).
countries are scarce, possibly due to incomparable study methods and air quality monitoring equipment, and there has been a lack of assessment of individual exposure to air pollutants and their relationship to mortality. However, recent improvements in economic conditions and environmental awareness in Taiwan have led to the allocation of resources to perform widespread air monitoring on the island. The APHEA-2 project was conducted and tested to determine whether deaths from respiratory and CVDs are advanced by just a few days or possibly many weeks using a multi-city hierarchical modeling approach for all ages and stratified by age groups. This study confirms that most of the effects of air pollution persist for more than a month after exposure and prolonged exposure to air pollution is associated with premature mortality in people suffering from respiratory and CVDs (Zanobetti et al., 2003). In Taiwan, summers are hot with high and humid, whereas winters are typically mild and dry. Urbanization is widespread and a large
0013-9351/$ - see front matter Crown Copyright & 2008 Published by Elsevier Inc. All rights reserved. doi:10.1016/j.envres.2008.10.002
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proportion of the population resides in high-rise buildings in close proximity to road traffic. Diesel vehicles are a major source of air pollution in urban areas and contribute a substantial proportion of inhalable particles. Levels of PM10, NOx, and CO in Taiwan are higher than cities of comparable population size in the United States and Europe. In Ohio, USA, a study by Schwartz and Dockery (1992) showed, after controlling for season, temperature and SO2 using Poisson regression, there was a strong positive correlation between total suspended particles (TSP) and daily death rates. When concentrations of TSP increased by 100 mg/m3, the death rate increased by 4% (RR ¼ 1.04). After adjusting for season and meteorological conditions, a 100 mg/m3 increase in PM10 concentration was found to cause a 16% and 17% increase in the daily death rates in St. Louis and East Tennessee, respectively (Dockery et al., 1992). There was a strong positive correlation between PM10 concentrations (5 days prior to recorded death) and nonaccidental death rates. An increase of 100 mg/m3 resulted in a 43% and 20% increase in the daily mortality from respiratory diseases and CVD, respectively. A longitudinal study by Pope et al. (1992) in Philadelphia (1974–1988) shows that after adjusting for season and temperature using Poisson regression, mortality is related to air pollutant concentrations. When TSP, SO2, and O3 increased by 34.7 mg/m3, 12.9 ppb, and 20.2 ppb, respectively, the mortality rate, increased by 1%, 1%, and 2%, respectively. Many studies show a correlation between air pollutants and mortality, yet the relationship remains unclear due to a complex interaction of multiple factors including those temporal and spatial. Moreover, since different populations are exposed to a complex mixture of air pollutants that vary in composition with geography and climatic conditions, much of the recent work in air pollution study has focused on individual components of human health. Unfortunately conclusions based on previous studies are unclear due to heterogeneric study areas that provide inconsistent findings. Few studies have considered the effects of age on deaths caused by air pollution. Since elderly people are more sensitive to their environment, our study considered air pollution-related deaths from respiratory and, CVD and all causes of death in elderly people as well as separately in addition to the all-ages group. Furthermore, by categorizing data into seasons, we were able to more accurately determine the effects of air pollution.
2. Materials and methods 2.1. Settings Our study population comprised of residents from Central Taiwan during 1997–1999. Population density in the study area was high and the area considered a metropolis, geographically situated in a basin. 2.2. Outcomes Daily mortality data was collected by the Taiwan Department of Health (DOH). Cause of death was classified according to the International Classification of Diseases Revision 9 (ICD-9): all causes of death excluding accidents ICD9 code 4800, respiratory disease ICD9 codes 460–519, CVD codes 390–459. Death certificates, the accuracy of which has recently improved, were obtained from the DOH. Nevertheless, our study was a longitudinal study and therefore errors in the raw data are assumed random. 2.3. Air pollutants/exposure assignment Hourly concentration data for particulate matter o10 mm in aerodynamic diameter (PM10), SO2, NO2, O3, and CO were monitored by automated measuring units at five different stations. Monitoring stations were provided by the Taiwan Environmental Protection Agency (EPA). Temperature and dew point were obtained similarly. With the exception of O3 (taken as a maximum 8-h average from 9:00 am to 17:00 pm) and CO (taken as a maximum 8-h average), every 24-h
an arithmetic average reading was determined for each station and an arithmetic average was calculated over all stations. Analysis of air pollution included 24-h concentration averages of SO2 (UV fluorescence), CO (non-dispersive infrared photometry), NO2 (chemiluminescen), PM10 (B-ray attenuation method), and maximum 8-h average O3 (Ultraviolet photometry).
2.3.1. Analysis Analyses of relative risk of respiratory and cardiovascular and all causes of death due to air pollution for both all-ages and X65 groups were determined using a time-series regression model separately for each season, in which the error term is regressed by parameters accounted for autoregressive and moving average effects (Bowerman and O’Connell, 1993). First, a base model was determined by finding appropriate lag and accumulated effects of each single pollutant in assessing its effect on mortality after adjusted for year effect, month effect, week effect, holiday effect, and temperature effect. To observe the influence of the lag effect and accumulative effects for each air pollutant on mortality, under different conditions, such as a 1-day lag with 2 accumulative days, which means we take the average of the values from yesterday and the day before yesterday. In our analysis, we tried each of combinations of ‘‘lag effect (0–5 days)’’ and ‘‘accumulated effect (1–5 days)’’. In a model using lag i accumulated over j days, the covariate is averaged over lags i to i+j1. Among those models for each analysis, the final model was determined according to the minimized value of the AIC (Littell et al., 1996). For example, for mortality of all causes in the summer term, the final base model for PM10 was with 1 day lag and 1 day accumulated for all-ages group, while for SO2, the final base model was with 2 days lag and 3 days accumulated. Secondly, to avoid too many parameters in model which would reduce the prediction power, backward selection method were used to determine the final model according to the p-value removal criteria. The risk ratio (RR) and its 95% confidence interval (CI) for an interquartile range (IQR, between the 25th and 75th percentile) increase of each pollutant from the final model were shown. Since air pollutants vary by season in Taiwan, ‘‘spring season’’ (March–May), ‘‘summer season’’ (June–August), ‘‘autumn season’’ (September–November) and ‘‘winter season’’ (December–February) were categorized and assessed. Based on these seasons, there may be different patterns of relationships between ambient air pollutants and the three causes of mortality. We only show the results from summer and winter since no results from spring and autumn was significant in our analysis. All statistical tests were two-sided. Values of po0.05 were considered statistically significant.
3. Results Mean levels of air pollutants and meteorological variables are presented in Table 1. Values were lowest during summer months with the exception of ozone (O3). Particulate matter and O3 were highest during the fall. Temperatures and dew points were highest in summer, followed by fall, spring, and winter. Figs. 1a–c illustrate mean daily deaths from all causes of death, respiratory disease, and CVD, respectively, according to season. Data on all-ages and elderly participants (X65 years old) are also presented. Death rates were lowest in summer and highest in winter for both the all-ages and elderly groups. Death rates from CVDs and respiratory diseases showed similar trends. Meanwhile, the all-ages group showed little difference in death by respiratory disease between the summer and fall. Correlation values between air pollution parameters are provided in Table 2. PM10 levels were significantly positively correlated with all other air parameters. Other significant positive correlations include SO2 with NO2 (r ¼ 0.70) and CO (r ¼ 0.56) as well as NO2 with CO (r ¼ 0.78). All pollutants with the exception of O3 were found to have a significant negative correlation with temperature and dew point at po0.001. Figs. 2a and b indicate, according to summer and winter weather, the risk of death from all causes associated with each air pollutant when pollutant levels increase per IQR. The values of IQR in each air pollutant were shown in Table 3. With the exception of the ozone pollutants, IQR levels of air pollutants in winter were consistently higher than in the summer. The risk of death during winter was significantly positively correlated with all air pollutants, with the exception of O3, for the all-ages (a) and elderly (X65) (b) groups, and PM10 for the all-ages group. During summer, only two significant positive correlations were evident in
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Table 1 Air pollutants and meteorological variables by season Pollutanta
Season
Number
Meanb
SD
Min
Max
PM10 (mg/m3)
Springc Summer Fall Winter
276 276 272 269
68.70 39.39 69.62 66.70
29.21 17.26 30.45 33.73
18.95 17.64 18.14 17.61
190.44 108.26 184.44 186.69
SO2 (ppb)
Spring Summer Fall Winter
276 276 272 270
4.82 2.84 4.56 4.81
2.31 1.72 2.58 3.09
0.93 0.54 0.60 0.28
14.19 10.42 13.80 19.62
NO2 (ppb)
Spring Summer Fall Winter
276 276 272 270
28.04 17.76 26.89 28.30
7.40 4.54 7.68 7.83
13.53 8.19 9.67 11.68
57.50 37.19 55.26 55.92
CO (ppm)
Spring Summer Fall Winter
276 276 272 270
1.10 0.85 1.12 1.13
0.33 0.28 0.39 0.49
0.48 0.42 0.35 0.37
2.46 2.14 2.51 2.76
O3 (ppb)
Spring Summer Fall Winter
276 276 272 270
40.71 31.20 45.57 28.62
16.39 14.95 17.10 11.50
5.28 5.16 4.22 3.52
96.58 90.03 90.61 64.44
Temperature (1c)
Spring Summer Fall Winter
276 276 272 270
23.51 28.30 25.03 17.47
3.34 1.71 2.62 3.06
14.09 21.94 16.09 7.43
29.28 31.36 30.07 24.67
Dew point (1c)
Spring Summer Fall Winter
276 276 272 270
18.41 23.07 20.19 13.59
2.96 1.61 3.26 3.71
8.22 17.89 6.06 -2.78
23.44 26.61 25.19 20.42
N ¼ 1095 days. a PM10, SO2, NO2: daily mean; CO: 8-h maximum; O3: 8-h mean (9 am–5 pm). b The daily average of air pollutant is from five air monitoring stations. c spring: March–May; Summer: June–Aug.; Fall: September–November; Winter: December–February 12, 1–2 months.
the elderly group between the risk of death with NO2 (RR ¼ 1.058) and CO (RR ¼ 1.054). No other pollutants showed significance for either group. Figs. 3a and b illustrate, according to summer and winter weather, the risk of death from respiratory diseases associated with each air pollutant when pollutant levels increase from 25% to 75%. The risk of death during winter was significantly positively correlated with O3 for both groups and additionally SO2 for the elderly (X65) (b) group. During summer, the only significant positive correlation was with O3 (RR ¼ 1.283) per IQR increase for the elderly group. No other pollutants showed significance for either group. Figs. 4a and b show, according to summer and winter, the risk of death from CVD associated with each air pollutant when pollutant levels increase per IQR. The risk of death during winter was significantly positively correlated with SO2 (RR ¼ 1.087 and RR ¼ 1.150), NO2 (RR ¼ 1.15 and RR ¼ 1.27), and CO (RR ¼ 1.238 and RR ¼ 1.416) per IQR increase for both the all-ages and elderly groups. The elderly group (X65) (b) had an additional correlation with PM10 (RR ¼ 1.194) during winter. During summer, the only significantly positive correlation was with NO2 (RR ¼ 1.188) per IQR increase for the elderly group.
Fig. 1. (a–c) Daily mortality from all causes of death, all respiratory causes and all cardiovascular causes by season and age (scale for all ages shown on the left axis; for X65 ages shown on the right axis) (1997–1999, N ¼ 1095 days).
Table 2 Correlation matrix between air pollutants and meteorological variables, in Taichung (1997–1999) PM10
SO2
NO2
CO
O3
Temperature Dew point
1.00 PM10 SO2 0.69a 1.00 NO2 0.78a 0.70a 1.00 CO 0.64a 0.56a 0.78a 1.00 O3 0.57a 0.42a 0.36a 0.21a 1.00 Temperature 0.12a 0.12a 0.35a 0.15a 0.27a 1.00 Dew point 0.16a 0.15a 0.35a 0.10a 0.12a 0.93a a
1.00
po0.001.
Table 4 shows the best lag effect and cumulative effect using the single pollutant model in summer and winter. We noticed a difference in the lag effect and cumulative effect between summer
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Fig. 2. (a and b) Summer and winter risk estimates of all causes of death (all ages shown on top; X65 ages shown on the bottom) for five pollutants (triangle represents summer; diamond represents winter).
Table 3 Inter-quartile range (IQR) of air pollutants for summer and winter seasons Pollutants Unit Summer Winter
PM10 mg/m3 15.55 39.98
SO2 ppb 1.76 2.70
NO2 ppb 6.09 10.22
CO ppm 0.31 0.70
O3 ppb 14.73 14.87
and winter. Different pollutants showed a difference in the lag effect and cumulative effect in summer and winter. Different causes of death also showed a difference in the lag effect and cumulative effect in summer and winter. The results using multi-pollutant models in summer were not significantly different. Table 5 shows only results using both single and multi-pollutant models in winter. Table 5 shows selected relative risk estimates (75th vs. 25th percentile) for pollutants having significant effects using both the single and multipollutant models. CO and O3 significantly affected all causes of death in winter using multi-pollutant models. In addition, CO also significantly affected all causes of death in winter using the single
pollutant model. Furthermore, O3 significantly affected deaths due to respiratory diseases in winter using both single and multipollutant models. Likewise, CO significantly affected deaths due to CVD in winter using both single and multi-pollutant models. CO also significantly affected deaths due to CVD in winter in people aged 65 and older using both single and multi-pollutant models.
4. Discussion In this study, lag patterns of air pollutants with cause-specific mortality were assessed for each single pollutant model adjusted for year effect, month effect, week effect, holiday effect, and temperature effect separately by season. The patterns were different among cause-specific mortality, age group, pollutant, and season. For respiratory disease in the all-age group, there were no lag effects for PM10, SO2, and NO2, while CO and O3 had a lag effect of 2 days. For CVD in the elderly group, PM10 and O3 showed no lag effects. Generally speaking, our study found that optimal lags ranged from 0 (concurrent) to 2 single lag days and
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Fig. 3. (a and b) Summer and winter risk estimates of all respiratory causes (all ages shown on top; X65 ages shown on the bottom) for five pollutants (triangle represents summer season; diamond represents winter season).
1–3 cumulative lag days. Although our findings are similar to a previous study presented by Wong et al. (2001), we found a significant effect by PM10 on all causes of death and CVD for the elderly group in winter, which was not found in Wong’s study. However, Wong’s study failed to classify different age groups or seasons. Risk estimates for mortality due to CVD for the all-age group and the elderly group were 4.0% and 5.6%, respectively in summer, and 12% and 19.4%, respectively in winter, per IQR increase of PM10. These results are high compared to previous studies by Zanobetti et al. (2003) and Wong et al. (2001) which found values for cardiovascular death of 1.97% and 1.70% per 10 mg/m3, respectively. A 10 mg/m3 increase in PM10 was associated with a 0.72% (95% confidence interval 0.35–1.10%) increase in the rate of admissions for people suffering from congestive heart failure on the same day. Wellenius et al. (2006) found associations between exposure to particles and certain markers of CVD, including decreased heart rate variability. The effects of PM10 appeared to be less severe in patients with secondary diagnoses of hypertension. These different results may be explained by the use of a different basis for measuring PM10 across studies. For example
our study used IQR PM10 values of 15 and 40 mg/m3 in summer and winter, respectively. Therefore, the results of our study indicate that both the negative health effects of PM10 and the fluctuation in its concentration is greater in winter. Our study found that elderly people were at a significantly higher risk of death from all causes and CVDs associated with PM10. Although risk ratios of respiratory deaths per IQR PM10 were greater than one, high fluctuations prevented significant findings in winter. PM10 may invoke alveolar inflammation, release inflammatory mediators, exacerbate lung conditions, and increases the blood’s ability to coagulate, thereby leading to acute episodes of CVDs (Seaton et al., 1995). Mechanisms controlling the effects of air pollutants on cardiovascular mortality and morbidity may be illustrated by changes in the blood’s ability to coagulate and changes in the nervous system’s control of the heart, possibly leading to arrhythmias (Seaton et al., 1995; Peters et al., 2000). Our study findings indicate that increased daily mortality from all causes of death and CVD are associated with SO2, NO2, and CO levels during winter. This result is in agreement with previous studies conducted in Asia (Wong et al., 2002; Chang et al., 2005).
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Fig. 4. (a and b) Summer and winter risk estimates of all cardiovascular causes (all ages shown on top; X65 ages shown on the bottom) for five pollutants (triangle represents summer; diamond represents winter).
Table 4 The best lag effect and cumulative effect in the single pollutant model PM10
SO2
NO2
CO
O3
The best lag effect and cumulative effect in the single pollutant model, in summer All causes of death 1–1 2–4 2–2 2–2 2–2 All deaths X65 age 1–2 2–4 2–2 2–2 2–2 Deaths due to respiratory diseases 0–0 0–0 0–0 2–2 2–3 Deaths due to respiratory diseases X65 age 0–0 2–4 2–4 2–2 2–3 Deaths due to cardiovascular disease 0–0 2–2 2–4 1–3 1–1 Deaths due to cardiovascular disease X65 age 0–0 2–2 2–2 2–2 0–1
The best lag effect and cumulative effect in the single pollutant model, in winter All causes of death 0–1 1–1 0–2 0–2 1–1 All causes of death X65 age 0–1 1–1 0–2 0–2 1–1 Deaths due to respiratory diseases 1–3 1–3 1–1 1–1 2–3 Deaths due to respiratory diseases X65 age 0–0 1–1 1–1 1–1 1–1 Deaths due to cardiovascular disease 0–2 0–2 0–2 0–2 1–1 Deaths due to cardiovascular disease X65 age 0–2 1–2 0–2 0–2 0–0
NO2 is correlated with plasma fibrinogen and augments the incidence of ventricular arrhythmia and ventricular tachycardia in patients with implanted cardiovascular defibrillators (Peters et al., 2000). Mortality increases in patients with angina when they are exposed to moderate levels of CO. CO has been reported to impair myoglobin’s oxygen transport and storage capacity, and even low levels of carboxyhemoglobin exacerbate myocardial ischemia in patients with coronary artery diseases (Allred et al., 1989). In a study conducted on London office workers, increased fibrinogen concentrations were associated with the previous day’s NO2 and CO levels (Pekkanen et al., 2000). However, CO and NO2 have not been associated with increased heart rate or decreased heart rate variability (Gold et al., 2000). SO2 has also been associated with cardiovascular effects and its relationship with increased CVD hospital admissions in Hong Kong (Wong et al., 1999). Alternatively, exposure to extreme temperatures is associated with an increase in daily mortality in different regions (Kunst et al., 1993; Braga et al., 2001). High temperatures have been related to an
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Table 5 Selected relative risk estimates (75th vs. 25th percentile) for pollutant having significant effects in both single and multiple pollutant models in winter PM10
SO2
NO2
CO
O3
0.898 (0.807–0.998) 1.059 (0.999–1.122)
1.026 (0.989–1.064) 1.043a (1.018–1.098)
1.034 (0.9222–1.159) 1.090a (1.027–1.157)
1.148a (1.014–1.300) 1.127a (1.052–1.208)
1.061a (1.005–1.120) 1.045 (0.998–1.095)
1.087 (0.661–1.787) 1.347 (0.990–1.833)
1.095 (0.921–1.301) 1.176 (0.998–1.384)
0.785 (0.550–1.120) 1.101 (0.906–1.351)
1.403 (0.975–2.019) 1.237 (0.993–1.541)
1.395a (1.068–1.823) 1.428a (1.126–1.811)
Cardiovascular death (in winter) Multi-pollutants 0.923 (0.743–1.146) One pollutant 1.12 (0.998–1.258)
1.046 (0.980–1.117) 1.087a (1.025–1.151)
1.021 (0.848–1.228) 1.15a (1.043–1.267)
1.246a (1.017–1.527) 1.238a (1.109–1.381)
0.933 (0.845–1.029) 0.943 (0.862–1.031)
Cardiovascular death X65 age (in winter) Multi-pollutants 0.736 (0.545–0.995) One pollutant 1.194a (1.002–1.425)
1.088 (0.985–1.202) 1.150a (1.053–1.255)
1.098 (0.828–1.455) 1.270a (1.096–1.471)
1.492a (1.101–2.022) 1.416a (1.199–1.672)
1.039 (0.912–1.183) 1.039 (0.910–1.187)
All cause death (in winter) Multi-pollutants One pollutant
Respiratory death (in winter) Multi-pollutants One pollutant
a
po0.05.
increase in the frequency of hospitalization for acute myocardial infarction and congestive heart failure. However, it is also associated with a decrease in the frequency of visits for coronary atherosclosis and pulmonary heart disease among elderly residents (Koken et al., 2003). It has been postulated that the relationship between temperature and cardiovascular mortality and morbidity can be predicted from blood viscosity and cholesterol levels. An increase is related to high temperature, whereas blood pressure and fibrinogen levels increase during winter (Keatinge et al., 1986). Our study used single air pollutant on the daily mortality due to all causes, respiratory and CVDs. Risk of death from all causes and CVD during winter was significantly positively correlated with levels of SO2, CO, and NO2 for both groups of subjects and additionally with PM10 for the elderly (X65 years old) group. There were significant positive correlations with respiratory disease and levels of O3 for both groups during winter. However, the only significantly positive correlations were respiratory disease with O3 (RR ¼ 1.283) and all causes of death with NO2 (RR ¼ 1.058) and CO (RR ¼ 1.054) for the elderly group during summer. No other pollutants showed significance for either group. Because five pollutants had a high correlation with each other, the results from multi-pollutant model had a problem of multicollinearity which was hard to determine the effects of each pollutant on the CVD and respiratory tract (data not shown). Generally speaking, both single and multi-pollutant models consistently showed the daily mortality caused by CVD was significantly affected by CO pollutants, and the daily mortality of respiratory disease was greatly affected by ozone pollutants. These results support our finding that the risk of death was significantly positively correlated with SO2, NO2, and CO for both groups of subjects and additionally with PM10 for the elderly (X65 years old) group, but no significance was found for any pollutant for either group during winter from all causes of death and CVD. Our study provides insight into the adverse effects of air pollution including short-term or long-term exposure for total morality as well as specifically for mortality from respiratory and CVD.
There have not been a lot of reports about cardiovascular effects of O3, and O3 shows a lack of statistical significance. On the other hand, O3 shows a significant difference to respiratory diseases during winter. This finding is similar with a previous study (Gent et al., 2003), which indicated that a 50 ppb increase in 1-h O3 was associated with increased likelihood of wheeze (by 35%) and chest tightness (by 47%). The highest levels of O3 (1- or 8-h averages) were associated with increased shortness of breath and rescue medication use in children with asthma. However, it is likely that the long-term health effects of respiratory and CVD that we observed in this study were due to the mixture of air pollutants rather than just one component. In conclusion, our findings contribute to the evidence of an association between SO2, CO, NO2, and PM10 and mortality from respiratory and CVDs, especially among elderly people during the winter. Development of longitudinal and panel studies is needed to further elucidate the mechanisms of air pollution as they are related to mortality from respiratory diseases and CVD. References Allred, E.N., Bleecker, E.R., Chaitman, B.R., Dahms, T.E., Gottlieb, S.O., Hackney, J.D., Pagano, M., Selvester, R.H., Walden, S.M., Warren, J., 1989. Short-term effects of carbon monoxide exposure on the exercise performance of subjects with coronary artery disease. N. Engl. J. Med. 321, 1426–1432. Bowerman, B.L., O’Connell, R.T., 1993. Forecasting and Time Series: An Applied Approach, third ed. Duxbury, Pacific Grove, CA. Braga, A.L., Zanobetti, A., Schwartz, J., 2001. The lag structure between particulate air pollution and respiratory and cardiovascular deaths in 10 US cities. J. Occup. Environ. Med. 43, 927–933. Chang, C.C., Tsai, S.S., Ho, S.C., Yang, C.Y., 2005. Air pollution and hospital admissions for cardiovascular disease in Taipei, Taiwan. Environ. Res. 98, 114–119. Dockery, D.W., Schwartz, J., Spengler, J.D., 1992. Air pollution and daily mortality: associations with particulates and acid aerosols. Environ. Res. 59, 362–373. Gent, J.F., Triche, E.W., Holford, T.R., Belanger, K., Bracken, M.B., Beckett, W.S., Leaderer, B.P., 2003. Association of low-level ozone and fine particles with respiratory symptoms in children with asthma. J. Am. Med. Assoc. 290, 1859–1867. Gold, D.R., Litonjua, A., Schwartz, J., Lovett, E., Larson, A., Nearing, B., Allen, G., Verrier, M., Cherry, R., Verrier, R., 2000. Ambient pollution and heart rate variability. Circulation 101, 1267–1273.
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