Seasonal Cycle and Relationship of Seasonal Rhino- and Influenza Virus Epidemics With Episodes of Asthma Exacerbation in Different Age Groups

Study population

We conducted a retrospective population-based cohort study using the Health Insurance Review and Assessment Service (HIRA) database. Korea has a national healthcare system that covers all physician and hospital services. These data consist of the complete electronic medical records of approximately 98% of the Korean population, and include primary, secondary, and tertiary care.11 We obtained the claims data of the number of ED visits for AE (International Classification of Disease [ICD], 10th version, coded as J45-J46) from January 1, 2008 to December 31, 2012 for patients of all ages. The information extracted included age, sex, area code, date of ED visit, and results of treatment.

Variable description

Individuals with AEs were identified as those who visited an ED for this condition during the study period. This definition of AE, using ICD code data, has 36.4% sensitivity and 94.4% specificity in children aged 2-17 years.12 Subjects were classified into 5 age groups (<2 years, 3-5 years, 6-19 years, 20-59 years, and >60 years). To determine the incidence rate of AE for the different age groups, we used census data obtained from the website of the Ministry of the Interior (rcps.egov.go.kr:8081). This population distribution was retrieved from data from December 31, 2012, which are categorized by age and location. Severe AE is defined by hospitalization, transfer, or death, and other visits as minor exacerbations. The cities classified as metropolitan are Seoul (latitude: 37.57), Busan (latitude: 35.18), Daegu (latitude: 35.87), Gwangju (latitude: 35.16), Incheon (latitude: 37.46), Ulsan (latitude: 35.54), and Daejeon (latitude: 36.35).

Respiratory virus epidemic

Rhino and influenza virus results were obtained from the Korea Centers for Disease Control and Prevention (KCDC), along with weekly virus epidemic data. Briefly, respiratory specimens (throat nasal swab) were collected from patients with acute respiratory infections (ARIs) from 91 primary hospitals nationwide, including pediatric, otolaryngology, and internal medicine facilities. Virus testing was performed using conventional reverse transcription (RT)-polymerase chain reaction (PCR) from 2008 to 2010, and real-time RT-PCR from 2011 to 2012. These data were also used to compare different age groups, because they included patient age, sex, and residential region. We used the rhino- and influenza virus PCR results, and integrated them into the AE database for analysis.

Statistical analysis

The crude number of visits for AE per 1,000 people in this study was determined for individuals of different ages, sexes, and residential regions, and calculated using the census population. Census data in Korea (December 31, 2012) were obtained from the website of the Ministry of the Interior (rcps.egov.go.kr:8081).

The statistical analysis employed Fourier regression to determine the period of seasonal cycles in 5 age groups. Previous studies have used models of this form in numerous applications to describe periodic cycles. Briefly, the data for each age group was fitted to the first 8 consecutive sinusoidal functions by Fourier regression. This can be represented as follows13:

where Y(t) is the number of patients at day t, a₀ is the Midline Estimating Statistic Of Rhythm (MESOR), a_i and b_i are the i-th amplitude and acrophase, ω(=2πT/8) is related to the shortest period (T), and ε(t) is the error term. Fourier regression produces ω(=2πT/8), and thus shortest period (T). Using Fourier regression, we searched the count and month of the peak in the seasonal pattern of each age group.

We used the Cosinor regression method to determine the amplitudes and phases of data collected at different times. This method is particularly suitable for the detection of rhythmicity in cross-sectional studies, and for comparison of parameters in different cycles.14 We analyzed 4 parameters—MESOR, amplitude, period, and phase—to characterize seasonal rhythmicity:

where M is the MESOR, A is the amplitude, τ is the period, ϕ is the acrophase, and e(t) is the error term.13 Two peaks during the same year had differences in amplitude and phase. We compared the amplitudes of series with 2 peaks, such as spring and fall. The 5-year of data were divided into 2 parts: March 1 to August 31 (spring) and September 1 to February 28 (fall). Applying the Cosinor method with the 2 divided subsets of data allowed us to obtain the amplitude, phase, and MESOR of each part. Phase (the date of a peak) was compared for groups with different ages and of residential regions.

Calculation of the moving average for each week was utilized to determine the number of visits for each age group. To analyze the correlations of the different age groups (infant, preschool, school, adults, and elderly) with regional ED visits among 7 metropolitan areas, we used the cross-correlation function (CCF). When analyzing the CCF between virus infections and AE events of each age group, a week was considered a unit, because data on respiratory virus infection was reported on a weekly basis.

Study subjects

There were 157,559 ED visits (daily mean: 86.2±40.2) for AE in Korea between January 1, 2008 and December 31, 2012, corresponding to a crude ED visitation rate of 0.62 events/1,000 people/year. Overall, the rate was less than 0.1 events/1,000 people/year (n=101) in aged 0-11 months, and highest in those aged 12-23 months (7.8 events/1,000 people/year, n=18,419). The rate quickly declined until it reached 0.4 events/1,000 people/year (n=1,150) in those 13 years. After age 13, the rate did not change until age 61. In the 13 to 61 years' age group, the average ED visit was 0.27±0.06 events/1,000 people/year. The rate again started to increase, which became 0.5 events/1,000 people/year in aged 62 years, and 1.24±0.44 events/1,000 people/year in those aged ≥62 years (Fig. 1). The age-related number of emergency room visits was similar to the age-related prevalence of asthma reported previously.15

The male-to-female ratios in the incidence of AE varied among the 5 age groups. There were more males than females in the 3 groups of children aged <18 years, but more females than males for 18- to 59-years and the oldest age group (Table 1). Among the 157,559 ED visits, 18,250 (11.6%) occurred in subjects aged <2 years, 29,716 (18.9%) in those 2-5 years, 24,399 (15.5%) in those 6-17 years-old, 43,515 (27.6%) by those 18-59 years-old, and 41,679 (26.5%) in those aged >60 years.

Periodicity of the AE cycle in different age groups

Fig. 2 shows the number of daily ED visits for AE in Korea over 5 years (January 2008 to December 2012) for the 5 age groups. The results of Fourier regression analysis (solid lines) help visualize the patterns of AE cycles in each age group. Notably, there was only 1 maximum per year in subjects aged >60 years (T=365.3 days; which means length of each sinusoidal cycle, 95% CI, 357.0-374.0; P<0.010), but 2 maxima per year in the other 4 age groups (infants: T=182.4 days; 95% CI, 180.9-184.0; P<0.010; preschool children: T=179.2 days; 95% CI, 178.0-180.4; P<0.010; school children: T=181.8 days; 95% CI, 180.5-183.1; P<0.010; and adults: T=180.8 days; 95% CI, 178.4-183.2; P<0.010).

Amplitude and concordance of the AE cycle in different age groups

We confirmed that the proportion of ED visits for AE was highest in September for subjects aged 6-17 years (3,959/24,399, 16.2%), and in October (11.8%) for those aged 2-5 years. The maximum was larger in February for those aged >60 years (10.7%), and in May for infants (12.7%). The amplitude of the AE cycle, defined as the difference between the minimum and maximum AE rates, was higher in fall than spring for subjects aged ≥2 years (all age groups: P<0.001) (Table 2). For subjects aged <2 years, the spring amplitude was greater than the fall amplitude (9.16, 95% CI, 8.75-9.75 vs 3.04; 95% CI, 2.46-3.62; P<0.010) (Table 2). In addition, the fall amplitude was greater in those aged 6-17 years (9.09, 95% CI, 7.73-10.44; P<0.010) than in those 18-59 years (4.07, 95% CI, 3.08-5.06; P<0.010) and in preschoolers (6.73, 95% CI, 5.77-7.70; P<0.010).

AE cycles and peaks showed similar patterns throughout all <60 years age groups (Fig. 2). In Table 3, we calculated cross-correlation coefficients between age groups. Using the school aged group as an indicator, the cross-correlation coefficient was highest for preschoolers (rho=0.794; P<0.010), followed by adults (rho=0.692; P<0.010), and infants (rho=0.518; P<0.01). The similarity was not significant in the elderly (rho=0.115; P=0.140) (Table 3).

Phase and lag time of the AE cycle in different age groups

While the eldest group only showed single peak per year, all the other groups showed dual peaks, which can be divided into spring and fall cycles. Those 4 groups had different phases of the AE cycle. The Cosinor regression model of those 4 groups results phase value, which means the date of the highest prevalence. The phases of the 4 groups were statistically different from each other (Table 4). The spring and fall AE peaks were earliest for subjects aged 6-17 years, followed by preschoolers, adults, and infants for the spring peaks, and followed by adults, preschoolers, and infants for the fall peaks (Table 4). More specifically, the AE peak for school children preceded those of preschool children by 10 days and infants by almost 1 month.

Incidence and peak of AE in different geographic areas

The rate of ED visits for AE was highest in Gwangju (1.16/1,000/year), followed by Jeju-do (1.15/1,000/year), Jeollabuk-do (0.99/1,000/year), and Jeollanam-do (0.90/1,000/year) (Fig. 3). Busan and Daegu had the lowest rates (0.41 and 0.34/1,000/year). Comparing the rate of ED visits for AE showed that some regions (i.e., Gwangju) had nearly 3-times higher ED visit rates than others regions (i.e., Daegu). To determine whether this phenomenon is related to the age structure of the populations in the different regions, we compared ED visits for AE of all 7 metropolitan cities in each age group. The results showed that the ED visits for AE was always 3-5-fold higher in metropolitan areas (data not shown).

To compare the time of the AE peak with region, we compared peak dates of those aged 6-17 years. The result indicated that an approximately one week later peak occurred in coastal cities of lower latitude, such as Busan and Ulsan. The cross-correlation coefficient between locations ranged from 0.423 to 0.724 (Fig. 4, Supplementary Table).

Cross-correlation between AE cycle and rhino- and influenza virus epidemics in different age groups

There were 57,228 viral PCR samples available, with 22.4% being positive for influenza virus and 14.9% positive for rhinovirus. The cross-correlation between AE and rhinovirus prevalence was highest in school children (rho=0.331; P<0.010), but there were no statistically significant correlations for preschoolers and infants (Fig. 5A). The cross-correlation coefficient between AE and influenza virus prevalence was higher for the elderly (rho=0.682; P<0.010) than the other age groups (rho=0.458-0.545; P<0.010) (Fig. 5B).