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作者

Zhidong Liu Guoyong Ding Ying Zhang Jiahui Lao Yanyu Liu Jing Zhang Liang Lu Qiyong Liu Baofa Jiang

作者单位

Shandong University Climate Change and Health Center, Jinan, Shandong Province 250012, People's Republic of China. Department of epidemiology, School of Public Health, Taishan Medical College, Taian, Shandong Province 271016, People's Republic of China. School of Public Health, China Studies Centre, The University of Sydney, New South Wales, Australia. State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, Beijing 102206, People's Republic of China. Department of Epidemiology, School of Public Health, Shandong University, Jinan, Shandong Province 250012, People's Republic of China Shandong University Climate Change and Health Center, Jinan, Shandong Province 250012, People's Republic of China. Electronic address: bjiang@sdu.edu.cn. Department of Epidemiology, School of Public Health, Shandong University, Jinan, Shandong Province 250012, People's Republic of China

刊名

Environmental research

年份

2019

卷号

Vol.170

页码

359-365

ISSN

1096-0953

关键词

Diarrheal diseases Floods Lag and cumulative effects Matched analysis

摘要

Floods may influence different types of diarrheal diseases and epidemiological studies of pathogen-specific diarrhea due to floods in China are still needed. In addition, few studies have been conducted to quantify the lag and cumulative risk of diarrheal disease due to floods in Guangxi, China. Our study aimed to identify different types of diarrheal diseases that were sensitive to floods and to quantify their lag and cumulative impact. A matched analysis based on time series data of floods and...更多

Floods may influence different types of diarrheal diseases and epidemiological studies of pathogen-specific diarrhea due to floods in China are still needed. In addition, few studies have been conducted to quantify the lag and cumulative risk of diarrheal disease due to floods in Guangxi, China. Our study aimed to identify different types of diarrheal diseases that were sensitive to floods and to quantify their lag and cumulative impact. A matched analysis based on time series data of floods and infectious disease from 2006 to 2010 was conducted in Guangxi, China. Each flood day was treated as an independent unit in our study. A simplified assumption that each day of the flood confers the same risk was adopted before analysis. Each flood day was matched to a non-flood day by city and time. Log-linear mixed-effects regression models were used to quantify the association between different types of diarrheal diseases and floods. Lag and cumulative effects were also calculated to get delayed and overall effects. A total of 45,131 diarrhea cases were notified in the study area over the study period. After controlling for the long-term trend, seasonality, and meteorological factors, floods caused a significantly increased risk of total diarrheal diseases. The RR was highest at lag 2 days . Floods caused a significantly increased risk in bacillary dysentery and in other infectious diarrhea, but not in typhoid fever and paratyphoid fever. Floods were significantly associated with total diarrheal diseases and other infectious diarrhea for both cumulative lag 0-7 and 0-14 days. Our study provides strong evidence of a positive association between floods and diarrheal diseases including bacillary dysentery and other infectious diarrhea in study area. Public health interventions should be taken to prevent a potential risk of these flood-sensitive diarrheal diseases according to the different lag period after floods.收起

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