Evidence map›Paper›PMID 27940632›Full record

ArticleBMJ open2016

Association between meteorological factors and bacillary dysentery incidence in Chaoyang city, China: an ecological study.

Yang Zhao, Yaxin Zhu, Zhiwei Zhu, Bo Qu

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  7. Observational
  8. 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 1 institution in 1 country.

Yang ZhaoFaculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China.
Yaxin ZhuFaculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China.
Zhiwei ZhuFaculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China.
Bo QuFaculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo quantify the relationship between meteorological factors and bacillary dysentery incidence.

designEcological study.

settingWe collected bacillary dysentery incidences and meteorological data of Chaoyang city from the year 1981 to 2010. The climate in this city was a typical northern temperate continental monsoon. All meteorological factors in this study were divided into 4 latent factors: temperature, humidity, sunshine and airflow. Structural equation modelling was used to analyse the relationship between meteorological factors and the incidence of bacillary dysentery. MATERIAL: Incidences of bacillary dysentery were obtained from the Center for Disease Control and Prevention of Chaoyang city, and meteorological data were collected from the Bureau of Meteorology in Chaoyang city. PRIMARY OUTCOME MEASURES: The indexes including χ

resultsThe goodness-of-fit results of the model showing that RMSEA=0.08, GFI=0.84, CFI=0.88, SRMR=0.06 and the χ

conclusionsHumidity and temperature should be given greater consideration in bacillary dysentery prevention measures for northern temperate continental monsoon climates, such as that of Chaoyang.

Indexed as

WeatherChinaCross-Sectional StudiesDysentery, BacillaryHumansIncidenceRisk FactorsBacillary dysenteryMeteorological factorsStructural equation modeling

Identifiers

PMID27940632
PMCPMC5168663
OpenAlexW2559992817

What OpenQuestion holds

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LicenceCC BY-NC
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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.