Evidence map›Paper›PMID 38933184›Full record

ArticleFundamental research2024

The mediatory role of water quality on the association between extreme precipitation events and infectious diarrhea in the Yangtze River Basin, China.

Junfeng Yu, Liang Zhao, Xin-Zhong Liang, Hung Chak Ho, Masahiro Hashizume, Cunrui Huang

Abstract read
In one paragraph

Article in Fundamental research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Junfeng YuSchool of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
Liang ZhaoThe State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
Xin-Zhong LiangDepartment of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20740, USA.
Hung Chak HoDepartment of Public and International Affairs, City University of Hong Kong, Hong Kong 999077, China.
Masahiro HashizumeDepartment of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
Cunrui HuangVanke School of Public Health, Tsinghua University, Beijing 100084, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extreme precipitation is exacerbating the burden of infectious diarrhea in the context of climate change, it is necessary to identify the critical and easy-to-intervene intermediate factors for public health strategies. Water quality may be the most important mediator, while relevant empirical evidence is limited. This study aimed to examine the role of water quality in the process of infectious diarrhea caused by extreme precipitation. Weekly infectious diarrhea cases, meteorological factors and water quality data in Yangtze River Basin in China between October 29, 2007 to February 19, 2017 were obtained. Two-stage statistical models were used to estimate city-specific extreme precipitation, water quality and infectious diarrhea relationships that were pooled to derive regional estimates. A causal mediation analysis was used to assess the mediation effect of water quality. In Yangtze River Basin, extreme precipitation events had a significant impact on infectious diarrhea (Incidence Rate Ratios [IRR]: 1.027, 95% Confidence Interval [CI]: 1.013∼1.041). After extreme precipitation events, the dissolved oxygen (DO) in surface water decreased (-0.123 mg/L, 95%CI: -0.159 mg/L∼-0.086 mg/L), while the un-ionized ammonia (NH(3)-N) increased (0.004 mg/L, 95%CI: 0.001 mg/L∼0.006 mg/L). The combined overall effect of DO and NH(3)-N on infectious diarrhea showed that both low and high concentrations were associated with an increased risk of infectious diarrhea. The causal mediation analysis showed that the mediation proportion of the two water quality indexes (DO and NH(3)-N) is 70.54% (

Indexed as

Dissolved oxygenExtreme precipitationInfectious diarrheaMediation analysisUn-ionized ammoniaWater quality

Identifiers

PMID38933184
PMCPMC11197735

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.