3.1. Descriptive statistics of the number of ER visits, air pollution levels, and meteorological measures
Table 1 shows the total number of ED visits due to acute asthma in each month from 2005-2013. There were a total 3287 days during this period. The baseline daily ER visits for asthma attack rate was 7.7 ± 4.0 per 1 million persons for the whole observation period. The 24-hr PM2.5 average levels ranged from 8.1 to 97.1 μg/m3 (mean 29.8 ± 12.6 μg/m3). The lowest and highest value for 24-hr PM10 average level was 17.9 μg/m3 and 370.7 μg/m3, respectively (mean 53.1 ± 22.2 μg/m3). The timeframes for 24-h average of pollutants and meteorological factors were shown in Figure 2. There were obvious downward trends for SO2, CO and PM2.5 except for O3 during this period.
Of the 998625 persons enrolled from January 1, 2005, there were 72649 asthmatic patients with a prevalence rate 7.27% (7.63% for male and 6.92% for female) (Supplementary Table 1). The prevalence rate of asthma for pediatric group, younger adult group and older age group was 13.51%, 3.94%, and 15.56%, respectively. The study population was randomly selected from 2005 and traced to 2013 without join of new case. As these children grew up, the young adult group showed the most accumulative number of asthmatic patients since 2010 (Supplementary Table 1). For ER visit for asthma acute exacerbation, the pediatric group had the highest ER visit rate (40.1%) in 2005 among different age groups (Supplementary Table 2). As these children grew up, the young adult group showed the most accumulative number of ER visits for asthma attack since 2010.
3.2. Highly correlation between the level of each outdoor air pollutant and meteorological factors
Table 2. demonstrates the correlation for daily values over the entire period among the air pollutants and weather variables. PM2.5, PM10, SO2, CO and NO2 had a strong positive correlation with each other and were negatively correlated with temperature, rainfall and relative humidity. It is reasonable for the high degree of correlation of PM10 and PM2.5 (Figure 3A). However, outdoor air NO2 and CO were also highly correlated (r = 0.9) (Figure 3B). Our results showed a decrease in outdoor air pollution with rainfall (Figure 3C) and more severe air pollution during the cold season (Figure 3D).
3.3. Great differences of outdoor air pollutants among different geographic areas
In further study, we tried to compare the air pollution in different geographic areas. Taiwan was grouped into six geographic areas. ANONA analysis revealed great differences for each air pollutant among different geographic areas in Taiwan (Supplementary Table 3). After plotted the outdoor air pollutant and meteorological factors by geographic area into heatmaps (Supplementary Figure 1), CO and NO2 levels were higher in area 1, 2, and 3 than other areas (Supplementary Figure 1A, 1B), while PM2.5 and PM10 levels were higher in area 4 and 5 than others (Supplementary Figure 1C, 1D). Area 5 had the highest level of O3 and SO2 (Supplementary Figure 1E, 1F). Since there was great variations in outdoor air pollutants among different geographic areas, data from a nation-wide study cannot provide information for how outdoor air pollutants/meteorological factors will necessarily influence every asthma ER visit.
When we combined the monthly mean values of PM2.5, monthly mean temperature, and ER visit for asthma attack, we found the number of ER visits for asthma AE to be positively correlated with the PM2.5 value (Figure 4). However, there were more ED visits due to asthma in the winter and spring and fewer during summer and early autumn. Thus, there will be oversight if only a single air pollutant is considered during asthma ER visits. As shown in Table 2, there was close interplay among each air pollutant and meteorological factor. Therefore, the contribution of each air pollutant and meteorological factor for asthma ER visit is needed to be further clarified.
3.4. The relationship of air pollution/ meteorologic factor to ED visits for asthma by case cross-over study
In further study, the case-crossover design was applied to evaluate the relationship between air pollution/ meteorological factors and daily ER visits for asthma acute attack. Individuals with a verified date of ER visit for asthma attack between January 1, 2005, and December 31, 2013, were included. During the study period, there were 25 167 case days and 149 442 control days. For case-crossover analysis, a total of 25 167 ER visits (7.7±4.0 per day in 3287 days) for asthma AE and 149 442 control days were included. The gender ratio for male to female was 56.7 to 43.3 with dominant in age 18 to 64-year-old (37.6%). Here meteorological factor was considered to be a variable rather than adjusted factor, because meteorologic factor was also an important risk factor for asthma AE in the real world. Using six reference periods (7, 14 and 21 d before and after the case period), a 1 mg/m3 increase in the 48-h averages of PM2.5 and 1 ℃ decrease in temperature were associated with asthma ER visit [odds ratio (OR) = 1.004 (95% CI 1.001–1.007) and 0.986 (95% CI 0.980–0.991) respectively] (Table 3-1). As the study cases were divided by male and female, a 1 mg/m3 increase in the 48-h averages of PM2.5 and 1 ℃ increase in temperature were associated with asthma ER visit [OR = 1.004 (95% CI, 1.000–1.008) and 0.986 (95% CI, 0.979–0.994) respectively] for male patients. A 1 ppb increase in the 48-h averages of O3 and a 1 ℃ increase in temperature were associated with asthma ER visit [OR = 1.003 (95% CI, 1.000–1.007) and 0.985 (95% CI, 0.976–0.993) respectively] for female patients. As the study cases were divided according to age, temperature increase was a protective factor for asthma ER visit, with a 1 ℃ increase in temperature associated with OR = 0.981 (95% CI 0.971–0.991) and 0.985 (95% CI, 0.975–0.994) for the pediatric age group and young adult group, respectively (Table 3-2). Each 1 mg/m3 increase in the 48-h averages of PM2.5 was associated with asthma ER visit for patients older than 65 years of age (OR = 1.008 (95% CI, 1.003–1.014). We also analyzed the effect of air pollutants on asthma AE without meteorologic factor considered (Supplementary Table 4). If temperature, humidity, and rainfall were not considered, more air pollutants showed significant impacts on asthma AE. For example, O3 and NO2 will show harmful effects for asthma AE in the group of 0-17 years old boy and girl, respectively. Thus, meteorologic factor is important and should be considered simultaneously with air pollution.
Since younger children may suffer higher rates of respiratory illness. We further stratified the pediatric group and determined the effect of air pollution and meteorologic factor on asthma AE (Table 3-3). The major impact of outdoor air pollution and meteorologic factor on pediatric asthma AE was for age 6 to 11-year-old. A 1 mm/day increase in the 24-h averages of rainfall and 1℃ increase in temperature were associated with asthma ER visit [odds ratio (OR) = 0.897 (95% CI 0.816–0.986) and 0.972 (95% CI 0.949–0.995) respectively] for age 6 to 11-year-old boy. A 1 ppb increase in the 48-h averages of NO2 were associated with asthma ER visit [odds ratio (OR) = 1.054 (95% CI 1.007–1.102)] for age 6 to 11-year-old girl.