Evidence map›Paper›PMID 38443462›Full record

ArticleScientific reports2024

Causal association study of the dynamic development of the metabolic syndrome based on longitudinal data.

Jaina Razbek, Liangliang Bao, Yan Zhang, Mayisha Daken, Mingqin Cao

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 1 institution in 1 country.

Jaina RazbekDepartment of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, China.
Liangliang BaoDepartment of Postgraduate Management Section, The Fourth Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Yan ZhangDepartment of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, China.
Mayisha DakenDepartment of Epidemic Prevention, Karamay Centre for Disease Control and Prevention, Karamay, China.
Mingqin CaoDepartment of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, China. cmq66@126.com.
Xinjiang Medical University · CN

Funding

National Natural Science Foundation of China 71663053
6 · The paper itself

Abstract

The dynamic progression of metabolic syndrome (MetS) includes developmental deterioration and reverse recovery; however, the key factors in this bidirectional progression have not been identified. Our study aimed to use the data obtained from the China Health and Retirement Longitudinal Study (CHARLS) and construct a Bayesian network to explore the causal relationship between influential factor and the development and recovery of MetS. Followed up at 4 years, forward progression of MetS occurred in 1543 and reverse recovery of MetS occurred in 1319 of 5581 subjects. Bayesian Networks showed that hyperuricemia and body mass index (BMI) levels directly influenced progression of MetS, and gender, exercise and age play an indirect role through hyperuricemia and BMI levels; high hemoglobin A1c (HbA1c) and BMI levels directly influenced recovery of MetS, and gender and exercise play an indirect role through BMI levels. Bayesian Network inference found that the rate of progression of MetS in subjects with hyperuricemia increases from 36 to 60%, the rate of progression of MetS in subjects with overweight or obese increases from 36 to 41% and the rate of reverse recovery rate of MetS in subjects with high HbA1c decreased from 33 to 20%. Therefore, attention to individuals at high risk of hyperuricemia, high HbA1c levels, and overweight/obesity should be enhanced, with early detection and following healthy behavioral interventions to prevent, control and delay the progression of MetS and its components.

Indexed as

HyperuricemiaMetabolic SyndromeBayes TheoremGlycated HemoglobinHumansLongitudinal StudiesObesityOverweightGlycated Hemoglobin

Identifiers

PMID38443462
PMCPMC10914715
OpenAlexW4392457929

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.