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Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis

BACKGROUND: Xinxiang, a city in Henan Province, suffered from frequent floods due to persistent and heavy precipitation from 2004 to 2010. In the same period, dysentery was a common public health problem in Xinxiang, with the proportion of reported cases being the third highest among all the notifie...

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Autores principales: Ni, Wei, Ding, Guoyong, Li, Yifei, Li, Hongkai, Jiang, Baofa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Co-Action Publishing 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4124174/
https://www.ncbi.nlm.nih.gov/pubmed/25098726
http://dx.doi.org/10.3402/gha.v7.23904
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author Ni, Wei
Ding, Guoyong
Li, Yifei
Li, Hongkai
Jiang, Baofa
author_facet Ni, Wei
Ding, Guoyong
Li, Yifei
Li, Hongkai
Jiang, Baofa
author_sort Ni, Wei
collection PubMed
description BACKGROUND: Xinxiang, a city in Henan Province, suffered from frequent floods due to persistent and heavy precipitation from 2004 to 2010. In the same period, dysentery was a common public health problem in Xinxiang, with the proportion of reported cases being the third highest among all the notified infectious diseases. OBJECTIVES: We focused on dysentery disease consequences of different degrees of floods and examined the association between floods and the morbidity of dysentery on the basis of longitudinal data during the study period. DESIGN: A time-series Poisson regression model was conducted to examine the relationship between 10 times different degrees of floods and the monthly morbidity of dysentery from 2004 to 2010 in Xinxiang. Relative risks (RRs) of moderate and severe floods on the morbidity of dysentery were calculated in this paper. In addition, we estimated the attributable contributions of moderate and severe floods to the morbidity of dysentery. RESULTS: A total of 7591 cases of dysentery were notified in Xinxiang during the study period. The effect of floods on dysentery was shown with a 0-month lag. Regression analysis showed that the risk of moderate and severe floods on the morbidity of dysentery was 1.55 (95% CI: 1.42–1.670) and 1.74 (95% CI: 1.56–1.94), respectively. The attributable risk proportions (ARPs) of moderate and severe floods to the morbidity of dysentery were 35.53 and 42.48%, respectively. CONCLUSIONS: This study confirms that floods have significantly increased the risk of dysentery in the study area. In addition, severe floods have a higher proportional contribution to the morbidity of dysentery than moderate floods. Public health action should be taken to avoid and control a potential risk of dysentery epidemics after floods.
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spelling pubmed-41241742014-08-20 Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis Ni, Wei Ding, Guoyong Li, Yifei Li, Hongkai Jiang, Baofa Glob Health Action Original Article BACKGROUND: Xinxiang, a city in Henan Province, suffered from frequent floods due to persistent and heavy precipitation from 2004 to 2010. In the same period, dysentery was a common public health problem in Xinxiang, with the proportion of reported cases being the third highest among all the notified infectious diseases. OBJECTIVES: We focused on dysentery disease consequences of different degrees of floods and examined the association between floods and the morbidity of dysentery on the basis of longitudinal data during the study period. DESIGN: A time-series Poisson regression model was conducted to examine the relationship between 10 times different degrees of floods and the monthly morbidity of dysentery from 2004 to 2010 in Xinxiang. Relative risks (RRs) of moderate and severe floods on the morbidity of dysentery were calculated in this paper. In addition, we estimated the attributable contributions of moderate and severe floods to the morbidity of dysentery. RESULTS: A total of 7591 cases of dysentery were notified in Xinxiang during the study period. The effect of floods on dysentery was shown with a 0-month lag. Regression analysis showed that the risk of moderate and severe floods on the morbidity of dysentery was 1.55 (95% CI: 1.42–1.670) and 1.74 (95% CI: 1.56–1.94), respectively. The attributable risk proportions (ARPs) of moderate and severe floods to the morbidity of dysentery were 35.53 and 42.48%, respectively. CONCLUSIONS: This study confirms that floods have significantly increased the risk of dysentery in the study area. In addition, severe floods have a higher proportional contribution to the morbidity of dysentery than moderate floods. Public health action should be taken to avoid and control a potential risk of dysentery epidemics after floods. Co-Action Publishing 2014-08-05 /pmc/articles/PMC4124174/ /pubmed/25098726 http://dx.doi.org/10.3402/gha.v7.23904 Text en © 2014 Wei Ni et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Ni, Wei
Ding, Guoyong
Li, Yifei
Li, Hongkai
Jiang, Baofa
Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis
title Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis
title_full Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis
title_fullStr Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis
title_full_unstemmed Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis
title_short Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis
title_sort impacts of floods on dysentery in xinxiang city, china, during 2004–2010: a time-series poisson analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4124174/
https://www.ncbi.nlm.nih.gov/pubmed/25098726
http://dx.doi.org/10.3402/gha.v7.23904
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