背景:由昆虫和螨虫引起的皮炎,被诊断为丘疹性荨麻疹或sc疮,是一种常见的皮肤病。然而,关于天气和空气污染对这种疾病门诊就诊的影响的研究仍然缺乏。本研究旨在探讨气象和环境因素对皮炎门诊患者每日就诊的影响。
方法:对广州最大的皮肤科专科医院2015-2020年共43,101份门诊就诊记录进行分析,中国。基于风险因素之间的Pearson相关性的分层聚类模型用于选择回归变量。拟合线性回归模型以确定风险因素与每日就诊之间的统计显着关联,考虑到温度的短期影响。采用排列重要性来评估这些因素的预测能力。
结果:短期气温与每日就诊呈正相关,并表现出很强的预测能力。就门诊病人总数而言,一天的滞后温度不仅对日常访问有重大影响,但也具有排列重要性的最高中值。这个结论在大多数亚组中都是可靠的,除了夏季和summer疮的亚组,其中滞后三天的温度有负面影响。相比之下,空气污染与日常访问无关,预测能力较弱。此外,工作日,假期和趋势对日常访问有重大影响,但预测能力较弱。
结论:我们的研究表明,短期气温与每日就诊呈正相关,并表现出较强的预测能力。然而,空气污染与日常访问无关,预测能力较弱。本研究结果为地方政府制定干预措施和建立基于环境的疾病预警系统提供了参考。
BACKGROUND: Dermatitis caused by insects and mites, diagnosed as papular urticaria or
scabies, is a common skin disease. However, there is still a lack of studies about the effects of weather and air pollution on outpatient visits for this disease. This study aims to explore the impacts of meteorological and environmental factors on daily visits of dermatitis outpatients.
METHODS: Analyses are conducted on a total of 43,101 outpatient visiting records during the years 2015-2020 from the largest dermatology specialist hospital in Guangzhou,
China. Hierarchical cluster models based on Pearson correlation between risk factors are utilized to select regression variables. Linear regression models are fitted to identify the statistically significant associations between the risk factors and daily visits, taking into account the short-term effects of temperatures. Permutation importance is adopted to evaluate the predictive ability of these factors.
RESULTS: Short-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. In terms of total outpatients, the one-day lagged temperature not only has a significant impact on daily visits, but also has the highest median value of permutation importance. This conclusion is robust across most subgroups except for subgroups of summer and
scabies, wherein the three-day lagged temperature has a negative effect. By contrast, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. Moreover, weekdays, holidays and trends have significant impacts on daily visits, but with weak predictive abilities.
CONCLUSIONS: Our study suggests that short-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. Nevertheless, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. The results of this study provide a reference for local authorities to formulate intervention measures and establish an environment-based disease early warning system.