Evidence map›Paper›PMID 41402546›Full record

ArticleScientific reports2025

Gender disparities in complex association of metabolic syndrome with dietary habits and lifestyle risk factors in Chinese population.

Yan Huang, Zongkai Li, Hui Jing, Samuel Chacha, Xiaoyan Lin, Baibing Mi, Yezhou Liu, Qiang Li, Yuan Shen, Jiaomei Yang and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

13 authors.

Yan HuangDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Zongkai LiDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Hui JingDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Samuel ChachaDepartment of Molecular Diagnostics, Sumbawanga Regional Referral Hospital, Rukwa, 413, Tanzania.
Xiaoyan LinDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Baibing MiDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Yezhou LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Qiang LiDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Yuan ShenDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Jiaomei YangDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Duolao WangDepartment of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, L7 8XZ, UK.
Hong YanDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Shaonong DangDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China. tjdshn@mail.xjtu.edu.cn.

Funding

the National Key Research and Development Program of China 2017YFC0907200the Natural Science Basic Research Program of Shaanxi Province 2021JM-034the Scientific Research Project Xi'an Municipal Health Commission 20221223
6 · The paper itself

Abstract

The purpose of this study is to explore individual and joint effect of comprehensive dietary habits and lifestyle on Metabolic syndrome(MetS), and its gender disparities. Data were derived from the baseline survey in the Regional Ethnic Cohort Study in northwest China. Unhealthy lifestyle index(ULI) and unhealthy dietary habits score(UDHS) were established. The association of MetS and its components with ULI or UDHS was analyzed by logistic model. The joint impact of UDHS and ULI on MetS was investigated. Potential masking effect of lifestyle was evaluated on the association between dietary habits and MetS. All analyses were conducted separately by gender. ULI was associated with a higher risk of MetS and its components, irrespective of gender. In males, higher UDHS was linked to a higher risk of MetS while in females it appeared to be associated with a lower risk of MetS. Participants with unhealthy dietary habits and an unhealthy lifestyle were found to have a higher risk of developing MetS compared to those maintaining healthy dietary habits and lifestyle, with 3.18 times(95% CI: 2.48 ~ 4.08) higher risk in males and 3.36 times(95%CI: 2.27 ~ 4.97) higher risk in females. However, females with healthy dietary habits but unhealthy lifestyle showed a higher OR of 5.52. ULI masked a 41.7% effect between UDHS and MetS in females. Unhealthy lifestyle was significantly associated with increased risk of MetS regardless of gender. Unhealthy dietary habits appear to increase the risk of MetS in males but not females. The unhealthy lifestyle may interfere with effect of unhealthy dietary habits on MetS in females. Adherence to healthy lifestyle and dietary habits would benefit prevention and control of MetS.

Indexed as

Feeding BehaviorLife StyleMetabolic SyndromeAdultAgedChinaEast Asian PeopleFemaleHumansMaleMiddle AgedRisk FactorsSex FactorsDietary habitsGenderLifestyleMetabolic syndrome

Identifiers

PMID41402546
PMCPMC12827463

What OpenQuestion holds

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Registered trials

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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.