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Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China

BACKGROUND: Although studies have provided the estimates of floods-diarrhoea associations, little is known about the lag effect, effect modification, and attributable risk. Based on Sichuan, China, an uneven socio-economic development province with plateau, basin, and mountain terrains spanning diff...

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Autores principales: Lan, Tianjiao, Hu, Yifan, Cheng, Liangliang, Chen, Lingwei, Guan, Xujing, Yang, Yili, Guo, Yuming, Pan, Jay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Society of Global Health 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308977/
https://www.ncbi.nlm.nih.gov/pubmed/35871400
http://dx.doi.org/10.7189/jogh.12.11007
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author Lan, Tianjiao
Hu, Yifan
Cheng, Liangliang
Chen, Lingwei
Guan, Xujing
Yang, Yili
Guo, Yuming
Pan, Jay
author_facet Lan, Tianjiao
Hu, Yifan
Cheng, Liangliang
Chen, Lingwei
Guan, Xujing
Yang, Yili
Guo, Yuming
Pan, Jay
author_sort Lan, Tianjiao
collection PubMed
description BACKGROUND: Although studies have provided the estimates of floods-diarrhoea associations, little is known about the lag effect, effect modification, and attributable risk. Based on Sichuan, China, an uneven socio-economic development province with plateau, basin, and mountain terrains spanning different climatic zones, we aimed to systematically examine the impacts of floods on diarrheal morbidity. METHODS: We retrieved information on daily diarrheal cases, floods, meteorological variables, and annual socio-economic characteristics for 21 cities in Sichuan from January 1, 2017 to December 31, 2019. We fitted time-series Poisson models to estimate the city-specific floods-diarrhoea relation over the lags of 0-14 days, and then pooled them using meta-analysis for cumulative and lag effects. We further employed meta-regression to explore potential effect modifiers and identify effect modification. We calculated the attributable diarrheal cases and fraction of attributable morbidity within the framework of the distributed lag model. RESULTS: Floods had a significant cumulative association with diarrhoea at the provincial level, but varied by regions and cities. The effects of the floods appeared on the second day after the floods and lasted for 5 days. Floods-diarrhoea relations were modified by three effect modifiers, with stronger flood effects on diarrhoea found in areas with higher air pressure, lower diurnal temperature range, or warmer temperature. Floods were responsible for advancing a fraction of diarrhoea, corresponding to 0.25% within the study period and 0.48% within the flood season. CONCLUSIONS: The impacts imposed by floods were mainly distributed within the first week. The floods-diarrhoea relations varied by geographic and climatic conditions. The diarrheal burden attributable to floods is currently low in Sichuan, but this figure could increase with the exposure more intensive and the effect modifiers more detrimental in the future. Our findings are expected to provide evidence for the formulation of temporal- and spatial-specific strategies to reduce potential risks of flood-related diarrhoea.
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spelling pubmed-93089772022-08-04 Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China Lan, Tianjiao Hu, Yifan Cheng, Liangliang Chen, Lingwei Guan, Xujing Yang, Yili Guo, Yuming Pan, Jay J Glob Health Research Theme 7: Health Transitions in China BACKGROUND: Although studies have provided the estimates of floods-diarrhoea associations, little is known about the lag effect, effect modification, and attributable risk. Based on Sichuan, China, an uneven socio-economic development province with plateau, basin, and mountain terrains spanning different climatic zones, we aimed to systematically examine the impacts of floods on diarrheal morbidity. METHODS: We retrieved information on daily diarrheal cases, floods, meteorological variables, and annual socio-economic characteristics for 21 cities in Sichuan from January 1, 2017 to December 31, 2019. We fitted time-series Poisson models to estimate the city-specific floods-diarrhoea relation over the lags of 0-14 days, and then pooled them using meta-analysis for cumulative and lag effects. We further employed meta-regression to explore potential effect modifiers and identify effect modification. We calculated the attributable diarrheal cases and fraction of attributable morbidity within the framework of the distributed lag model. RESULTS: Floods had a significant cumulative association with diarrhoea at the provincial level, but varied by regions and cities. The effects of the floods appeared on the second day after the floods and lasted for 5 days. Floods-diarrhoea relations were modified by three effect modifiers, with stronger flood effects on diarrhoea found in areas with higher air pressure, lower diurnal temperature range, or warmer temperature. Floods were responsible for advancing a fraction of diarrhoea, corresponding to 0.25% within the study period and 0.48% within the flood season. CONCLUSIONS: The impacts imposed by floods were mainly distributed within the first week. The floods-diarrhoea relations varied by geographic and climatic conditions. The diarrheal burden attributable to floods is currently low in Sichuan, but this figure could increase with the exposure more intensive and the effect modifiers more detrimental in the future. Our findings are expected to provide evidence for the formulation of temporal- and spatial-specific strategies to reduce potential risks of flood-related diarrhoea. International Society of Global Health 2022-07-25 /pmc/articles/PMC9308977/ /pubmed/35871400 http://dx.doi.org/10.7189/jogh.12.11007 Text en Copyright © 2022 by the Journal of Global Health. All rights reserved. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Research Theme 7: Health Transitions in China
Lan, Tianjiao
Hu, Yifan
Cheng, Liangliang
Chen, Lingwei
Guan, Xujing
Yang, Yili
Guo, Yuming
Pan, Jay
Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China
title Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China
title_full Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China
title_fullStr Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China
title_full_unstemmed Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China
title_short Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China
title_sort floods and diarrheal morbidity: evidence on the relationship, effect modifiers, and attributable risk from sichuan province, china
topic Research Theme 7: Health Transitions in China
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308977/
https://www.ncbi.nlm.nih.gov/pubmed/35871400
http://dx.doi.org/10.7189/jogh.12.11007
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