Risk factors for allergic diseases: a cross-sectional survey of 9,501 Chinese preschool-aged children

Associations between long-term exposure to PM2.5 chemical constituents and allergic diseases: evidence from a large cohort study in China

BACKGROUND

Exposure to air pollutants may cause immune responses and further allergic diseases, but existing studies have mostly, if not all, focused on effects of short-term exposure to PM2.5 on allergic diseases.

OBJECTIVES

We estimated associations of long-term exposure to PM2.5 chemical constituents with allergic disease risks and effect modification.

METHODS

We used the baseline of a newly established, provincially representative cohort of 51,480 participants in southwest China. The presence of allergic rhinitis, allergic asthma, urticaria, and allergic conjunctivitis was self-reported by following a formed questionnaire in face-to-face interviews. The average concentrations of PM2.5 chemical constituents (NO3-, SO42-, NH4+, organic matter [OM], and black carbon [BC]) over participants' residence were estimated using machine learning models. Logistic regression with double robust estimator and weighted quantile sum regression were used to estimate the effects of PM2.5 chemical constituents on allergic disease risks, as well as relative importance of each PM2.5 chemical constituent.

RESULTS

Per interquartile range increase in the concentration of all PM2.5 chemical constituents was associated with the elevated risks for allergic asthma (OR = 1.79 [1.41-2.26]), allergic conjunctivitis (1.54 [1.19-2.00]), urticaria (1.36 [1.25-1.48]), and allergic rhinitis (1.18 [1.11-1.26]). NO3- contributed more to risks for allergic asthma (weight = 46.05 %), urticaria (72.29 %), and allergic conjunctivitis (47.65 %), while NH4+ contributed more to allergic rhinitis (78.07 %). OM contributed most to the risks for allergic asthma (30.81 %) and allergic conjunctivitis (31.40 %). BC was also associated with allergic rhinitis, urticaria, and allergic conjunctivitis, only with a considerable weight for urticaria (24.59 %). Joint effects of PM2.5 chemical constituents on risks for allergic rhinitis and urticaria were stronger in minorities and farmers than their counterparts.

CONCLUSION

Long-term exposure to PM2.5 chemical constituents was associated with the increased allergic disease risks, with NO3- and NH4+ accounting for the largest variance of the associations. Our findings would serve as scientific evidence for developing more explicit strategies of air pollution control.

Predicting risk of overweight or obesity in Chinese preschool-aged children using artificial intelligence techniques

OBJECTIVES

We adopted the machine-learning algorithms and deep-learning sequential model to determine and optimize most important factors for overweight and obesity in Chinese preschool-aged children.

METHODS

This is a cross-sectional survey conducted in 2020 at Beijing and Tangshan. Using a stratified cluster random sampling strategy, children aged 3-6 years were enrolled. Data were analyzed using the PyCharm and Python.

RESULTS

A total of 9478 children were eligible for inclusion, including 1250 children with overweight or obesity. All children were randomly divided into the training group and testing group at a 6:4 ratio. After comparison, support vector machine (SVM) outperformed the other algorithms (accuracy: 0.9457), followed by gradient boosting machine (GBM) (accuracy: 0.9454). As reflected by other 4 performance indexes, GBM had the highest F1 score (0.7748), followed by SVM with F1 score at 0.7731. After importance ranking, the top 5 factors seemed sufficient to obtain descent performance under GBM algorithm, including age, eating speed, number of relatives with obesity, sweet drinking, and paternal education. The performance of the top 5 factors was reinforced by the deep-learning sequential model.

CONCLUSIONS

We have identified 5 important factors that can be fed to GBM algorithm to better differentiate children with overweight or obesity from the general children, with decent prediction performance.