School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Environ Int. 2018 Nov;120:223-230. doi: 10.1016/j.envint.2018.08.014. Epub 2018 Aug 10.
Little is known about the relationship between Salmonella infection and meteorological parameters other than air temperature. This study aimed to explore associations of Salmonella hospitalizations with temperature, relative humidity (RH) and rainfall.
With negative binomial distribution assumed, time-series regression model adjusting for season and time trend were constructed employing distributed lag non-linear models and generalized additive models. Meteorological variables including mean temperature, RH, and daily total rainfall as well as indicator variables including day of the week and public holiday were incorporated in the models.
Higher temperature was strongly associated with more hospitalizations over the entire range of temperatures observed. There was a net 6.13 (95%Confidence Interval (CI) 3.52-10.67) relative risk of hospitalization at a temperature of 30.5 °C, relative to 13 °C, lag 0-16 days. Positive associations were found for RH above 60% and rainfall between 0 and 0.14 mm. Extreme high humidity (96%) and trace rainfall (0.02 mm) were associated with 2.06 (95%CI 1.35-3.14), lag 0-17 day, and 1.30 (95%CI 1.01-1.67), lag 0-26 days, relative risks of hospitalizations, relative to 60% and no rain, respectively.
High temperatures, high RH and light rainfall are positively associated with Salmonella hospitalizations. The very strong association with temperatures implies that hotter days will lead to increases in Salmonella morbidity in the absence of other changes, and the public health implications of this could be exacerbated by global climate change.
除了气温之外,人们对沙门氏菌感染与气象参数之间的关系知之甚少。本研究旨在探讨沙门氏菌住院与温度、相对湿度(RH)和降雨量之间的关系。
假设采用负二项分布,采用分布滞后非线性模型和广义加性模型构建时间序列回归模型,调整季节和时间趋势。模型中纳入了气象变量,包括平均气温、RH 和日总降雨量,以及包括星期几和公共假日在内的指示变量。
在观察到的整个温度范围内,较高的温度与更多的住院人数密切相关。与 13°C 相比,温度为 30.5°C 时住院的相对风险为 6.13(95%置信区间(CI)为 3.52-10.67),滞后 0-16 天。RH 高于 60%和降雨量在 0 至 0.14mm 之间时,呈正相关。极高湿度(96%)和微量降雨(0.02mm)分别与 0-17 天和 0-26 天的住院相对风险 2.06(95%CI 1.35-3.14)和 1.30(95%CI 1.01-1.67)相关。
高温、高 RH 和小雨与沙门氏菌住院呈正相关。与温度的强烈关联意味着,在没有其他变化的情况下,天气炎热将导致沙门氏菌发病率增加,而全球气候变化可能会使这种情况对公共健康的影响更加严重。