在未来的几十年中,整个欧洲,特别是地中海周围的极端天气事件可能会变得更加强烈和频繁。一些微生物的繁殖率,包括引起食源性疾病的细菌,也会受到这些事件的影响。因此,这项研究的目的是确定由于主要的细菌性食源性疾病(BFDs)和各种气象变量而导致的急诊入院之间是否存在统计学上的显着关系。包括热浪。我们进行了时间序列研究,在2013-2018年期间,马德里地区(西班牙)每天观察因变量(BFD导致的急诊住院)和自变量(化学空气污染的气象变量和控制变量),使用带有泊松回归的广义线性模型,其中包括控制变量和滞后变量以拟合模型。我们计算了每日最高温度的阈值,高于该阈值时,此类入院人数在统计学上显着增加,分析了全年和夏季的数据,并估计了相对风险和可归因于风险。全年最高日气温超过12°C每上升一度,估计可归因风险为3.6%,夏季温度高于阈值热浪定义温度(34°C)每升高一度,则为12.21%。此外,不同的气象变量显示出统计上显著的关联。尽管在全年和夏季的分析中,日照时数和平均风速都很重要,变量“雨”和“相对湿度”,仅在全年的分析中显示出显著的关系。高环境温度是一个风险因素,有利于增加由于主要BFDs引起的急诊住院治疗,在与热浪时期一致的日子里观察到更大的影响。这项研究产生的结果可以作为实施BFD预防策略的基础,尤其是在热浪的日子.
The coming decades are likely to see of extreme weather events becoming more intense and frequent across Europe as a whole and around the Mediterranean in particular. The reproduction rate of some microorganisms, including the bacteria that cause foodborne diseases, will also be affected by these events. The aim of this study was thus to ascertain whether there might be a statistically significant relationship between emergency hospital admissions due to the principal bacterial foodborne diseases (BFDs) and the various meteorological variables, including heatwaves. We conducted a time-series study, with daily observations of both the dependent variable (emergency hospital admissions due to BFDs) and the independent variables (meteorological variables and control variables of chemical air pollution) across the period 2013-2018 in the Madrid Region (Spain), using Generalised Linear Models with Poisson regression, in which control and lag variables were included for the purpose of fitting the models. We calculated the threshold value of the maximum daily temperature above which such admissions increased statistically significantly, analysed data for the whole year and for the summer months alone, and estimated the relative and attributable risks. The estimated attributable risk was 3.6 % for every one-degree rise in the maximum daily temperature above 12 °C throughout the year, and 12.21 % for every one degree rise in temperature above the threshold heatwave definition temperature (34 °C) in summer. Furthermore, different meteorological variables displayed a statistically significant association. Whereas hours of sunlight and mean wind speed proved significant in the analyses of both the whole year and summer, the variables \"rain\" and \"relative humidity\", only showed a significant relationship in the analysis for the whole year. High ambient temperature is a risk factor that favours the increase in emergency hospitalisations attributable to the principal BFDs, with a greater impact being observed on days coinciding with heatwave periods. The results yielded by this study could serve as a basis for implementing BFD prevention strategies, especially on heatwave days.