Krefis Anne Caroline, Fischereit Jana, Hoffmann Peter, Pinnschmidt Hans, Sorbe Christina, Augustin Matthias, Augustin Jobst
Institute for Health Services Research in Dermatology and Nursing (IVDP), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
Meteorological Institute, University of Hamburg, Hamburg, Germany.
BMJ Open Respir Res. 2018 Nov 1;5(1):e000338. doi: 10.1136/bmjresp-2018-000338. eCollection 2018.
Associations between air pollutants, meteorological conditions and respiratory diseases have been extensively shown. The aim of this study was to investigate associations between daily meteorological data, data on air pollution and emergency department (ED) visits depending on the day of the week, season and year (study period from 2013 to 2015).
Highly correlated environmental data entered a categorical principal components analysis (CATPCA). We analysed cross-correlation functions between the time series of the respective daily environmental factors and daily ED visits. Time lags with peak correlations of environmental variables obtained by the CATPCA on ED visits together with day of the week, year, running day (linear, quadratic and cubic), season and interaction terms entered the univariate analysis of variance (UNIANOVA) model.
The analyses demonstrated main effects on ED visits for the day of the week with highest admission rates on Mondays (B=10.69; ƞ=0.333; p<0.001). A significant time trend could be observed showing increasing numbers of ED visits per each year (p<0.001). The variable 'running day' (linear, quadratic and cubic) indicated a significant non-linear effect over time. The variable season showed significant results with winter, spring and summer recording fewer ED visits compared with the reference season autumn. Environmental variables showed no direct associations with respiratory ED visits.
ED visits were significantly associated with temporal variables. Our data did not show direct associations between environmental variables and ED visits.In times of rapid urbanisation, increases in respiratory diseases, temperature and air pollution, our analyses can help focus future studies and enhance strategies to reduce increasing numbers of respiratory diseases and ED visits. Because the potential costs of medical care in hospitals can be high compared with physicians, public health recommendations for reducing the increasing ED visits should be promoted and evaluated.
空气污染物、气象条件与呼吸道疾病之间的关联已得到广泛证实。本研究旨在调查每日气象数据、空气污染数据与急诊科（ED）就诊之间的关联，具体取决于一周中的日期、季节和年份（研究期为2013年至2015年）。
高度相关的环境数据进行了分类主成分分析（CATPCA）。我们分析了各每日环境因素的时间序列与每日ED就诊之间的交叉相关函数。通过CATPCA获得的环境变量与ED就诊的峰值相关性的时间滞后，连同一周中的日期、年份、连续天数（线性、二次和三次）、季节和交互项进入单变量方差分析（UNIANOVA）模型。
分析表明，一周中的日期对ED就诊有主要影响，周一的入院率最高（B = 10.69；ƞ = 0.333；p < 0.001）。可以观察到显著的时间趋势，即每年ED就诊人数增加（p < 0.001）。变量“连续天数”（线性、二次和三次）表明随时间有显著的非线性影响。季节变量显示出显著结果，与参考季节秋季相比，冬季、春季和夏季的ED就诊次数较少。环境变量与呼吸道ED就诊无直接关联。
ED就诊与时间变量显著相关。我们的数据未显示环境变量与ED就诊之间的直接关联。在快速城市化、呼吸道疾病、温度和空气污染增加的时期，我们的分析有助于聚焦未来研究并加强减少呼吸道疾病和ED就诊人数增加的策略。由于与医生相比，医院医疗护理的潜在成本可能很高，应推广并评估减少ED就诊人数增加的公共卫生建议。
