Binary logistic regression was carried out by applying inverse probability of treatment weighting (IPTW) using the propensity score. To calculate the propensity score, we used a multivariable logistic regression model to estimate the probability of each patient, including confounders. After applying the propensity score weights, the evaluation of the disturbance factors in the two groups was made with the variance ratio. The closer the variance ratio is to 1.0, the similar the characteristics of the two groups. The disturbing factor characteristics in the two groups were evaluated as statistically similar when the variance ratio ranged from 0.5 to 2.0.26 Odds ratio (OR) with 95% confidence interval (CI) were reported for the association between anemia and asthma severity. Subgroup analysis was performed according to age group (children: under 13 years old, adolescents: 13 years or older and under 18 years old), gender, and types of health insurance. All statistical analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC, USA). This study was approved by the Institutional Review Board of Dongduk Women’s University (IRB No. DDWU2008-01).

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