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Predicting risk for childhood asthma by pre-pregnancy, perinatal, and postnatal factors
Hui-Ju Wen1,2, Tung-Liang Chiang3, Shio-Jean Lin4
1Division of Environmental Health and Occupational Medicine, National Health Research Institutes, Miaoli, Taiwan.
Insights
This study identified early-life risk factors for childhood asthma. The findings enable prediction of asthma risk, aiding in developing preventive strategies for children.
Area of Science:
- Pediatrics
- Epidemiology
- Environmental Health
Background:
- Atopic diseases manifest early in life, necessitating early risk prediction for conditions like childhood asthma.
- Identifying early-life exposures can significantly contribute to the prevention of childhood asthma.
Purpose of the Study:
- To investigate early-life risk factors associated with childhood asthma.
- To develop a predictive model for childhood asthma development.
Main Methods:
- A national birth cohort study utilized multistage stratified systematic sampling from the 2005 Taiwan Birth Registry.
- Data on risk factors and child health were collected via home interviews at 6 months and 5 years.
- Backward stepwise regression analysis identified risk factors for predictive asthma models.
Main Results:
- 19,192 children completed the study; 6.6% were diagnosed with asthma by age 5.
- Key predictors included pre-pregnancy (parental atopy, SES), perinatal (residence, indoor mold, renovations), and postnatal factors (maternal depression, infant atopic dermatitis).
- Predicted asthma probabilities ranged from 3.2-4.1% (lowest) to 68.1-78.1% (highest) for boys and girls.
Conclusions:
- The study developed a technique for predicting childhood asthma risk.
- This predictive capability supports the development of targeted asthma prevention strategies.
Background:
Symptoms of atopic disease start early in human life. Predicting risk for childhood asthma by early-life exposure would contribute to disease prevention. A birth cohort study was conducted to investigate early-life risk factors for childhood asthma and to develop a predictive model for the development of asthma.
Methods:
National representative samples of newborn babies were obtained by multistage stratified systematic sampling from the 2005 Taiwan Birth Registry. Information on potential risk factors and children's health was collected by home interview when babies were 6 months old and 5 yr old, respectively. Backward stepwise regression analysis was used to identify the risk factors of childhood asthma for predictive models that were used to calculate the probability of childhood asthma.
Results:
A total of 19,192 children completed the study satisfactorily. Physician-diagnosed asthma was reported in 6.6% of 5-yr-old children. Pre-pregnancy factors (parental atopy and socioeconomic status), perinatal factors (place of residence, exposure to indoor mold and painting/renovations during pregnancy), and postnatal factors (maternal postpartum depression and the presence of atopic dermatitis before 6 months of age) were chosen for the predictive models, and the highest predicted probability of asthma in 5-yr-old children was 68.1% in boys and 78.1% in girls; the lowest probability in boys and girls was 4.1% and 3.2%, respectively.
Conclusions:
This investigation provides a technique for predicting risk of childhood asthma that can be used to developing a preventive strategy against asthma.
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