Evidence map›Paper›PMID 27251154›Full record

ArticleInfectious diseases of poverty2016

Spatial transmission and meteorological determinants of tuberculosis incidence in Qinghai Province, China: a spatial clustering panel analysis.

Hua-Xiang Rao, Xi Zhang, Lei Zhao, Juan Yu, Wen Ren, Xue-Lei Zhang, Yong-Cheng Ma, Yan Shi, Bin-Zhong Ma, Xiang Wang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Infectious diseases of poverty, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 3 pooled it
6.0field-weighted citation impact, top 3% 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

51 citing papers in PubMed, 3 syntheses or guidelines pooled it, 113 citations in OpenAlex.

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  20. The Recent Transmission and Associated Risk Factor ofInfection and drug resistance · 2024
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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

13 authors at 2 institutions in 2 countries.

Hua-Xiang RaoDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China.
Xi ZhangDepartment of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, 46202, USA.
Lei ZhaoDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China.
Juan YuDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, Shanxi, 030001, China.
Wen RenDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China.
Xue-Lei ZhangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China.
Yong-Cheng MaInstitute for Communicable Disease Control and Prevention, Qinghai Center for Disease Control and Prevention, Xining, Qinghai, 810007, China.
Yan ShiInstitute for Communicable Disease Control and Prevention, Qinghai Center for Disease Control and Prevention, Xining, Qinghai, 810007, China.
Bin-Zhong MaInstitute for Communicable Disease Control and Prevention, Qinghai Center for Disease Control and Prevention, Xining, Qinghai, 810007, China.
Xiang WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China.
Zhen WeiDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China.
Hua-Fang WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China.
Li-Xia QiuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, Shanxi, 030001, China. qlx_1126@yeah.net.
Shanxi Medical University · CNIndiana University – Purdue University Indianapolis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis (TB) is the notifiable infectious disease with the second highest incidence in the Qinghai province, a province with poor primary health care infrastructure. Understanding the spatial distribution of TB and related environmental factors is necessary for developing effective strategies to control and further eliminate TB.

methodsOur TB incidence data and meteorological data were extracted from the China Information System of Disease Control and Prevention and statistical yearbooks, respectively. We calculated the global and local Moran's I by using spatial autocorrelation analysis to detect the spatial clustering of TB incidence each year. A spatial panel data model was applied to examine the associations of meteorological factors with TB incidence after adjustment of spatial individual effects and spatial autocorrelation.

resultsThe Local Moran's I method detected 11 counties with a significantly high-high spatial clustering (average annual incidence: 294/100 000) and 17 counties with a significantly low-low spatial clustering (average annual incidence: 68/100 000) of TB annual incidence within the examined five-year period; the global Moran's I values ranged from 0.40 to 0.58 (all P-values < 0.05). The TB incidence was positively associated with the temperature, precipitation, and wind speed (all P-values < 0.05), which were confirmed by the spatial panel data model. Each 10 °C, 2 cm, and 1 m/s increase in temperature, precipitation, and wind speed associated with 9 % and 3 % decrements and a 7 % increment in the TB incidence, respectively.

conclusionsHigh TB incidence areas were mainly concentrated in south-western Qinghai, while low TB incidence areas clustered in eastern and north-western Qinghai. Areas with low temperature and precipitation and with strong wind speeds tended to have higher TB incidences.

Indexed as

ClimateAdolescentAdultAgedAged, 80 and overChildChild, PreschoolChinaFemaleHumansIncidenceInfantInfant, NewbornMaleMiddle AgedSpatial AnalysisMeteorological factorsSpatial clusteringSpatial panel data modelTuberculosis incidence

Identifiers

PMID27251154
PMCPMC4890510
OpenAlexW2345883982

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.