Evidence map›Paper›PMID 35309840›Full record

ArticleComputational and mathematical methods in medicine2022

Analysis of Influencing Factors for Chronic Diseases: A Large Sample Epidemiological Survey from Liaoyang.

Cuiqin Jiang, Qian Wang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Cuiqin JiangNeurology Department, Liaoyang Central Hospital, Liaoyang, 111000 Liaoning, China.ORCID https://orcid.org/0000-0003-3363-4651
Qian WangNeurology Department, Liaoyang Central Hospital, Liaoyang, 111000 Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Northeast China is a region with a serious aging population. There are fewer articles on epidemiological surveys on the prevalence of chronic diseases in aging areas of China. The study is aimed at understanding the prevalence of chronic noncommunicable diseases such as hypertension and diabetes mellitus (DM) in Liaoning Province, northeast China, and analyzing the risk factors for these chronic diseases. Methods: A questionnaire survey and physical examination were conducted in 5008 permanent residents in 2 streets (Henan Street and Hebei Street) covered by Liuerbao Central Health Center in Liaoyang and 4 villages (Miaogou Village, Wangjia Village, Heyan Village, and Shuiquan Village) covered by Shuiquan Health Center in Tianshui Town of Liaoyang from January 2020 to December 2020. Results: A total of 4990 patients were included. The prevalence rates of hypertension, DM, dyslipidemia, and obesity in residents in Liaoyang were 54.13%, 12.30%, 43.31%, and 20.52%, respectively. The prevalence of hypertension and DM was highest in both male and female patients aged 40-60 years, which was higher than that in the other age groups ( Conclusion: In Liaoyang, northeast China, the prevalence of noninfectious chronic diseases was high, and the prevalence rate in people over 40 years old was significantly higher than that in people under 40 years old. The prevalence and progression of chronic diseases were obviously related to local living and eating habits; thus, health education needs to be improved.

Indexed as

AdolescentAdultAgedChinaChronic DiseaseComputational BiologyDiabetes MellitusDyslipidemiasEpidemiologic StudiesFemaleHumansHypertensionMaleMiddle AgedNoncommunicable DiseasesObesity

Identifiers

PMID35309840
PMCPMC8926533
OpenAlexW4220860521

What OpenQuestion holds

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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.