Abstract：
OBJECTIVE: The abrupt change of climate has led to an increasing trend of hospitalised patients in recent years. This study aimed to analyse the temperature variability (TV) associated with respiratory disease (RD) hospitalisations, hospital stays and hospital expenses.
METHODS: The generalized linear model combined with distributed lag non-linear model was used to investigate the association between TV and RD hospitalisations.
METHODS: TV was determined by measuring the standard deviation of maximum and minimum temperatures for the current day and the previous 7 days. RD hospitalisations data were obtained from three major tertiary hospitals in Huaibei City, namely, the Huaibei People\'s Hospital, the Huaibei Hospital Of Traditional Chinese Medicine and the Huaibei Maternal and Child Health Care Hospital. First, using a time series decomposition model, the seasonality and long-term trend of hospitalisations, hospital stays and hospital expenses for RD were explored in this warm temperate sub-humid monsoon climate. Second, robust models were used to analyse the association between TV and RD hospitalisations, hospital stays and hospital expenses. In addition, this study stratified results by sex, age and season. Third, using the attributable fraction (AF) and attributable number (AN), hospitalisations, hospital stays and hospital expenses for RD attributed to TV were quantified.
RESULTS: Overall, 0.013% of hospitalisations were attributed to TV0-1 (i.e. TV at the current day and previous 1 day), corresponding to 220 cases, 1603 days of hospital stays and 1,308,000 RMB of hospital expenses. Females were more susceptible to TV than males, and the risk increased with longer exposure (the highest risk was seen at TV0-7 [i.e. TV at the current day and previous 7 days] exposure). Higher AF and AN were observed at ages 0-5 years and ≥65 years. In addition, it was also found that TV was more strongly linked to RD in the cool season. The hot season was positively associated with hospital stays and hospital expenses at TV0-3 to TV0-7 exposure.
CONCLUSIONS: Exposure to TV increased the risk of hospitalisations, longer hospital stays and higher hospital expenses for RD. The findings suggested that more attention should be paid to unstable weather conditions in the future to protect the health of vulnerable populations.
METHODS: The generalized linear model combined with distributed lag non-linear model was used to investigate the association between TV and RD hospitalisations.
METHODS: TV was determined by measuring the standard deviation of maximum and minimum temperatures for the current day and the previous 7 days. RD hospitalisations data were obtained from three major tertiary hospitals in Huaibei City, namely, the Huaibei People\'s Hospital, the Huaibei Hospital Of Traditional Chinese Medicine and the Huaibei Maternal and Child Health Care Hospital. First, using a time series decomposition model, the seasonality and long-term trend of hospitalisations, hospital stays and hospital expenses for RD were explored in this warm temperate sub-humid monsoon climate. Second, robust models were used to analyse the association between TV and RD hospitalisations, hospital stays and hospital expenses. In addition, this study stratified results by sex, age and season. Third, using the attributable fraction (AF) and attributable number (AN), hospitalisations, hospital stays and hospital expenses for RD attributed to TV were quantified.
RESULTS: Overall, 0.013% of hospitalisations were attributed to TV0-1 (i.e. TV at the current day and previous 1 day), corresponding to 220 cases, 1603 days of hospital stays and 1,308,000 RMB of hospital expenses. Females were more susceptible to TV than males, and the risk increased with longer exposure (the highest risk was seen at TV0-7 [i.e. TV at the current day and previous 7 days] exposure). Higher AF and AN were observed at ages 0-5 years and ≥65 years. In addition, it was also found that TV was more strongly linked to RD in the cool season. The hot season was positively associated with hospital stays and hospital expenses at TV0-3 to TV0-7 exposure.
CONCLUSIONS: Exposure to TV increased the risk of hospitalisations, longer hospital stays and higher hospital expenses for RD. The findings suggested that more attention should be paid to unstable weather conditions in the future to protect the health of vulnerable populations.
摘要：
目的：近年来，气候的突变导致住院患者呈上升趋势。本研究旨在分析与呼吸系统疾病（RD）住院相关的温度变异性（TV），住院时间和住院费用。
方法：采用广义线性模型和分布滞后非线性模型相结合的方法研究TV与RD住院的关系。
方法：TV是通过测量当天和前7天的最高和最低温度的标准偏差来确定的。RD住院数据来自淮北市三大三甲医院，即,淮北市人民医院,淮北市中医院和淮北市妇幼保健院。首先,使用时间序列分解模型，住院的季节性和长期趋势，在这种温暖的温带半湿润季风气候下，探索了RD的住院时间和住院费用。第二,使用稳健模型分析TV和RD住院之间的关联，住院时间和住院费用。此外,这项研究按性别分层结果，年龄和季节。第三，使用归因分数(AF)和归因数(AN)，住院治疗,对归因于电视的RD的住院时间和住院费用进行了量化。
结果：总体而言，0.013％的住院归因于TV0-1（即当天和前1天的电视），对应220例，1603天的住院天数和1,308,000元的住院费用。女性比男性更容易看电视，风险随着暴露时间的延长而增加(最高风险出现在TV0-7[即当天和前7天的电视]暴露)。在0-5岁和≥65岁时观察到较高的AF和AN。此外,还发现，在凉爽的季节，电视与RD的联系更加紧密。在TV0-3至TV0-7暴露时，炎热季节与住院时间和住院费用呈正相关。
结论：接触电视会增加住院风险，RD的住院时间更长，住院费用更高。研究结果表明，未来应更加关注不稳定的天气条件，以保护弱势群体的健康。
方法：采用广义线性模型和分布滞后非线性模型相结合的方法研究TV与RD住院的关系。
方法：TV是通过测量当天和前7天的最高和最低温度的标准偏差来确定的。RD住院数据来自淮北市三大三甲医院，即,淮北市人民医院,淮北市中医院和淮北市妇幼保健院。首先,使用时间序列分解模型，住院的季节性和长期趋势，在这种温暖的温带半湿润季风气候下，探索了RD的住院时间和住院费用。第二,使用稳健模型分析TV和RD住院之间的关联，住院时间和住院费用。此外,这项研究按性别分层结果，年龄和季节。第三，使用归因分数(AF)和归因数(AN)，住院治疗,对归因于电视的RD的住院时间和住院费用进行了量化。
结果：总体而言，0.013％的住院归因于TV0-1（即当天和前1天的电视），对应220例，1603天的住院天数和1,308,000元的住院费用。女性比男性更容易看电视，风险随着暴露时间的延长而增加(最高风险出现在TV0-7[即当天和前7天的电视]暴露)。在0-5岁和≥65岁时观察到较高的AF和AN。此外,还发现，在凉爽的季节，电视与RD的联系更加紧密。在TV0-3至TV0-7暴露时，炎热季节与住院时间和住院费用呈正相关。
结论：接触电视会增加住院风险，RD的住院时间更长，住院费用更高。研究结果表明，未来应更加关注不稳定的天气条件，以保护弱势群体的健康。
