Table 11. continued
Average time spent
extracurricular per day Average time spent in-door area except home or school (ex. hospital, library, department store, mart, theater, restaurant) per day during weekdays
N/A
Average time spent in public area (ex. theater) per day Average time spent in PC- room or karaoke per day
N/A
Average time spent at home per day during weekends, sleeping hour included
N/A
Average time spent at school per day during weekends
N/A
Average time spent using public transportation (bus or subways) per day during weekends
N/A
Average time spent outside (field, playground or park. Not in a building, car or subways) per day during weekends
N/A
Average time spent in-door area except home or school (ex. hospital, library, department store, mart, theater, restaurant) per day during weekends
1차 조사의 설문지에서 평일/주말의 구분이 명확하지 않았던 문제와, 집이나 학교 외의 실내공간에서 보내는 시간이 지나치게 세분화되어 있던 것을 반영하 여 설문지를 수정하여 이후부터 사용하였으나, 추적 검사 자료를 분석하려는 이 연구에 있어서는 변수가 통일되지 않는 문제가 있어 주말과 관련한 응답은 제외 하고 집, 학교, 차량, 실외 활동의 네 가지로 단순화시켜 변수를 통일하는 것이 가능할지 여부를 확인하였다.
1회차의 응답과 나머지 회차의 응답을 두 개의 그룹으로 나누고, 각 설문에서 유효값과 결측값을 가진 케이스 수를 각각 분석한 후 다시 응답값의 평균, 표준 편차, 평균의 95% 신뢰구간을 분석하였다(Table 12, Table 13).
Table 12. Distribution of missing values of integrated variables
integrated valuables
1stsurvey (4,680 case)
2nd~ 5thsurveys (11,381 case) effective
value
missing value
effective value
missing value Hour of
home activity per 1 day
3,124 1,556 (33.2 %) 10,915 466 (4.1 %)
Hour of school activity per 1 day
4,342 338 (7.2 %) 10,946 435 (3.8 %)
Hour of in-car activity per 1 day
1,812 2,868 (61.3 %) 7,037 4344 (38.2 %)
Hour of outdoor activity per 1 day
2,983 1,697 (36.3 %) 10,242 1139 (10.0 %)
Table 13. Comparison of two groups in integrated variables
Integrated valuables
1stsurvey (4,680 case) mean ± S.D.
(95% confidence interval)
2ndsurvey (11,381 case) mean ± S.D.
(95% confidence interval) Hour of
home activity per 1 day
14.03 ±1.99 (13.96 ~ 14.10 )
13.43 ±2.49 (13.38 ~ 13.47 )
Hour of school activity per 1 day
5.67 ±1.19 (5.63 ~ 5.70 )
6.25 ±1.33 (6.23 ~ 6.28 )
Hour of in-car activity per 1 day
0.65 ±0.89 (0.61 ~ 0.69 )
0.36 ±0.59 (0.35 ~ 0.38 )
Hour of outdoor activity per 1 day
1.40 ±0.90 (1.37 ~ 1.43 )
1.53 ±1.49 (1.51 ~ 1.56 )
Table 13 에서와 같이 4 개의 모든 변수에 있어, 평균의 95% 신뢰구간이 겹치는 부분이 없어(p<0.000) 같은 의미의 변수라고 생각할 수 없었다. 이 연구에서 각 학생들 개인 수준에서 실내 활동과 실외 활동을 정량하기 위한 변수였기에 조작적 정의를 통해 변수를 다소 수정하여 사용하더라도 분석에 포함시키기 위해 노력하였지만 해당 변수는 분석에 사용하기에 적합치 않은 것으로 나타나 연구의 제한점으로 남는다.
Analysis of factors related to allergic rhinitis focused on air pollution factors using follow-up
data of elementary school students in Ulsan
Suk Hwan Kim
POSCO health center, POSCO, Pohang, South Korea.
Objectives
The purpose of this study is to identify the effects of environmental factors, particularly representative air pollutants, among the factors affecting allergic rhinitis of elementary school children.
Methods
All panelists of four elementary schools in Ulsan were constructed and surveyed at two-year intervals. The survey used data collected five times over a nine-year period from June 2009 to April 15, 2018. The questionnaire used in the survey was a modified version of the ISAAC (International society of asthma and allergy of children). As an indicator to ensure allergic responsiveness objectively, skin prick test (SPT) was performed with 24 standard antigens.
To estimate outdoor air pollution exposure levels, sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and particulate matter 10 µmor less in diameter(PM10) concentration data were collected.
Three target variables were used.
1. prevalence of allergic rhinitis by last-1-year diagnosis 2. occurrence of allergic rhinitis by last-1-year diagnosis
3. among children who had allergic rhinitis at the first survey, the increase of number of co-morbid other allergic diseases during last-1-year
Each analysis was repeated again within a limited subject group who had positive SPT.
Logistic regression analysis was used to select variables suitable for the statistical model. And then selected variables were used to assess the association with target variables by the generalized estimation equation.
Results
About factors influencing prevalence of allergic rhinitis, among environmental factors, PM10 concentrations were associated with low risk.
In the analysis within positive SPT students, CO concentrations also were associated with low risk. The risk of living in a house built within last year was high, and the risk of living in a multi-family house or apartment was higher than in a detached house. History of allergic diseases of the family showed high risk. There was a relationship between history of bronchiolitis under 2 years of age and higher risk. Boys showed higher risk than girls.
About factors influencing the occurrence of allergic rhinitis, NO2, SO2and CO concentrations showed high risk. In particular, odds ratio of SO2
concentrations was 1.196. PM10 concentrations were associated with low risk. Family history of allergic diseases were also significant.