Evidence map›Paper›PMID 28281057›Full record

ArticleEnvironmental science and pollution research international2017

The death of the circulatory system diseases in China: provincial socioeconomic and environmental perspective.

Haixia Pu, Jiatian Li, Pin Wang, Linlin Cui, Huaxin Wang

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 26 citations in OpenAlex.

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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

5 authors at 4 institutions in 1 country.

Haixia PuInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Jiatian LiFaculty of Land Resource Engineering, Kunming University of Science and Technology, Wenchang Road, 121 street, Kunming, 650093, China. lijiatian2017@sohu.com.
Pin WangDesign and Research Institute of the Yellow River Water Conservancy Committee, Zhengzhou, 450003, China.
Linlin CuiInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Huaxin WangInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
University of Chinese Academy of Sciences · CNChinese Academy of Sciences · CNKunming University of Science and Technology · CNYellow River Institute of Hydraulic Research · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Few studies have explored the association between circulatory system diseases (CSDs) and provincial socioeconomic and environmental factors from spatial perspective, although large literature have focused on CSD. The numbers of death of hypertension disease (HD), ischemic heart disease (IHD), and cerebrovascular disease (CVD) are investigated, and 14 representative socioeconomic and environmental factors are collected. Stepwise regression model (SRM) and geographically weighted regression model (GWRM) are applied to determine the spatial correlation between the number of death of those diseases and selected factors. The results are the following: (1) diseases exhibit a pattern of zonal distribution. Higher HD is mostly distributed in south district, whereas higher IHD and CVD are observed in the north area. (2) SO

Indexed as

Cardiovascular DiseasesCerebrovascular DisordersCardiovascular SystemChinaHumansMyocardial IschemiaCerebrovascular diseaseCoal consumptionHypertension diseaseIschemic heart diseasePM2.5SO2 emission amount

Identifiers

PMID28281057
OpenAlexW2592311634

What OpenQuestion holds

Textmetadata
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.