Evidence map›Paper›PMID 28708077›Full record

ArticleInternational journal of environmental research and public health2017

Environmental Drivers and Predicted Risk of Bacillary Dysentery in Southwest China.

Han Zhang, Yali Si, Xiaofeng Wang, Peng Gong

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Green Space and Health in Mainland China: A Systematic Review.International journal of environmental research and public health · 2021
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Brain diseases in changing climate.Environmental research · 2019
    Review
  8. Exploring the Relevance of Green Space and Epidemic Diseases Based on Panel Data in China from 2007 to 2016.International journal of environmental research and public health · 2019
    Article
  9. Spatiotemporal Characteristics of Bacillary Dysentery from 2005 to 2017 in Zhejiang Province, China.International journal of environmental research and public health · 2018
    Article
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

4 authors at 2 institutions in 1 country.

Han ZhangMinistry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China. zhanghan11@mails.tsinghua.edu.cn.
Yali SiMinistry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China. yalisi@mail.tsinghua.edu.cn.
Xiaofeng WangCenter for Public Health Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China. wangxf2002abc@163.com.
Peng GongMinistry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China. penggong@tsinghua.edu.cn.
Tsinghua University · CNChinese Center For Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacillary dysentery has long been a considerable health problem in southwest China, however, the quantitative relationship between anthropogenic and physical environmental factors and the disease is not fully understand. It is also not clear where exactly the bacillary dysentery risk is potentially high. Based on the result of hotspot analysis, we generated training samples to build a spatial distribution model. Univariate analyses, autocorrelation and multi-collinearity examinations and stepwise selection were then applied to screen the potential causative factors. Multiple logistic regressions were finally applied to quantify the effects of key factors. A bootstrapping strategy was adopted while fitting models. The model was evaluated by area under the receiver operating characteristic curve (AUC), Kappa and independent validation samples. Hotspot counties were mainly mountainous lands in southwest China. Higher risk of bacillary dysentery was found associated with underdeveloped socio-economy, proximity to farmland or water bodies, higher environmental temperature, medium relative humidity and the distribution of the Tibeto-Burman ethnicity. A predictive risk map with high accuracy (88.19%) was generated. The high-risk areas are mainly located in the mountainous lands where the Tibeto-Burman people live, especially in the basins, river valleys or other flat places in the mountains with relatively lower elevation and a warmer climate. In the high-risk areas predicted by this study, improving the economic development, investment in health care and the construction of infrastructures for safe water supply, waste treatment and sewage disposal, and improving health related education could reduce the disease risk.

Indexed as

EnvironmentSocioeconomic FactorsChinaDysentery, BacillaryHumansIncidenceRisk Factorsanthropogenic environmentbacillary dysenterylogistic regression modelphysical environmentprevention and interventionrisk mapping

Identifiers

PMID28708077
PMCPMC5551220
OpenAlexW2734539583

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.