Evidence map›Paper›PMID 33232966›Full record

ArticleObesity facts2020

Prevalence and Related Factors of Metabolic Syndrome in Beijing, China (Year 2017).

Aijuan Ma, Kai Fang, Jing Dong, Zhong Dong

Abstract read
In one paragraph

Article in Obesity facts, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  5. Cluster of factors related to metabolic changes in older individuals: a cross-sectional study.Sao Paulo medical journal = Revista paulista de medicina · 2025
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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

4 authors.

Aijuan MaBeijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China.
Kai FangBeijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China.
Jing DongBeijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China.
Zhong DongBeijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China, dongzhbjcdcmb@yeah.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMetabolic syndrome (MetS) is one of the major public health problems worldwide. The aim of this study was to investigate the prevalence and associated risk factors of MetS in Beijing to formulate targeted policies.

methodsData from the 2017 Beijing Chronic Disease and Risk Factors Surveillance were used in this study, in which multistage stratified cluster sampling was adopted to collect a representative sample of 12,597 Beijing residents aged from 18 to 79 years. According to the definition of the International Diabetes Federation, the weighted prevalence of MetS and clustering of MetS components were estimated. The Rao-Scott adjusted χ2 test was used to test differences in MetS and components rates, and complex sampling unconditional logistic regression was used to explore influencing factors of MetS.

resultsThe prevalence of MetS was 25.59% (95% CI 23.77-27.41), and the proportion of men and women was 30.53% (95% CI 28.32-32.75) and 20.44% (95% CI 18.29-22.58), respectively. The proportion of central obesity, high fasting plasma glucose, high triglyceride, low high-density lipoprotein cholesterol, and high blood pressure (BP) was 42.02, 27.96, 32.87, 27.25, and 43.06%, respectively. A total of 29.60% (95% CI 27.55-31.74) participants presented at least three components of MetS. The results from complex sampling unconditional logistic regression revealed that the risk factors for having MetS included being 45-59 years old, being 60-79 years old, being male, living in a rural area, education with junior middle school level, education with primary school or below level, harmful use of alcohol, inappropriate sleep time, and having an unhealthy waist-to-height ratio (WHtR); the OR values were 1.55 (95% CI 1.32-1.81), 1.94 (95% CI 1.62-2.31), 1.51 (95% CI 1.34-1.70), 1.27 (95% CI 1.06-1.52), 1.38 (95% CI 1.13-1.68), 1.44 (95% CI 1.13-1.84), 1.50 (95% CI 1.14-1.99), 1.23 (95% CI 1.10-1.37), and 238.20 (95% CI 92.54-613.12), respectively.

conclusionsThe prevalence of MetS is still in a rising trend in Beijing. Strategies aimed at prevention and control of high BP should be prioritized to reduce the occurrence of MetS. WHtR is more important to evaluate MetS. Health education and personalized lifestyle intervention should be promoted to keep a healthy WHtR and waist circumference. An appropriate sleep time should be kept, and harmful alcohol drinkers should limit or abstain from alcohol.

Indexed as

AdolescentAdultAgedBeijingFemaleHumansHypertensionLogistic ModelsMaleMetabolic SyndromeMiddle AgedObesityPrevalenceRisk FactorsWaist-Height RatioYoung AdultBeijingMetabolic syndromeObesityRisk factorsWaist circumference

Identifiers

PMID33232966
PMCPMC7802480

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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.