Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease that affects 20% of children worldwide. Although environmental factors including weather and air pollutants have been shown to be associated with AD symptoms, the time-dependent nature of such a relationship has not been adequately investigated. Objective: This paper aims to assess the short-term impact of weather and air pollutants on AD severity scores. Methods: Using longitudinal data from a published panel study of 177 paediatric patients followed up for 17 months, we developed statistical machine learning models to predict daily AD severity scores for individual study participants. Exposures consisted of daily meteorological variables and concentrations of air pollutants and outcomes were daily recordings of scores for six AD signs. We developed a mixed effect autoregressive ordinal logistic regression model, validated it in a forward-chaining setting, and evaluated the effects of the environmental factors on the predictive performance. Results: Our model outperformed benchmark models for daily prediction of the AD severity scores. The predictive performance of AD severity scores was not improved by the addition of measured environmental factors. Any potential short-term influence of environmental exposures on AD severity scores was outweighed by the underlying persistence of preceding scores. Conclusions: Our data does not offer enough evidence to support a claim that AD symptoms are associated with weather or air pollutants on a short-term basis. Inferences about the magnitude of the effect of environmental factors require consideration of the time-dependence of the AD severity scores.

中文翻译：

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环境因素对预测特应性皮炎的每日严重程度评分的影响

背景：特应性皮炎（AD）是一种慢性炎症性皮肤病，影响了全球近20％的儿科人口。尽管已经证明环境因素（例如天气和空气污染物）与AD症状有关，但是尚未充分研究环境因素与后续AD症状之间关系的时间依赖性。在这里，我们旨在评估天气和空气污染物对AD严重性评分的短期影响。方法：使用来自177个小儿患者的随访17个月的公开小组研究的纵向数据，我们开发了统计机器学习模型来预测单个研究参与者的每日AD严重程度评分。暴露包括每日气象变量和空气污染物的浓度，结局是AD严重程度评分的每日记录。我们开发了一种混合效应自回归序数逻辑回归模型，在前向链接环境中对其进行了验证，并评估了环境因素对预测性能的影响。结果：对于AD严重程度评分的每日预测，我们的模型优于基准（历史或统一）模型。添加严重程度的环境因素并不能改善AD严重程度评分的预测性能。潜在的持久性超过了环境暴露对AD严重性评分的任何潜在短期影响。结论：该数据没有提供足够的证据来支持AD症状在短期内与天气或空气污染物有关的说法。关于环境因素影响大小的推论需要考虑AD严重性评分的时间依赖性。