Evidence map›Paper›PMID 27023599›Full record

ArticleNutrients2016

Gender Differences in Dietary Patterns and Their Association with the Prevalence of Metabolic Syndrome among Chinese: A Cross-Sectional Study.

Shu-Hong Xu, Nan Qiao, Jian-Jun Huang, Chen-Ming Sun, Yan Cui, Shuang-Shuang Tian, Cong Wang, Xiao-Meng Liu, Hai-Xia Zhang, Hui Wang and 3 more

Abstract read
In one paragraph

Article in Nutrients, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 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

38 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

13 authors.

Shu-Hong XuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. xushuh_sxmu@sina.com.
Nan QiaoDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. qiaonan_sxmu@sina.com.
Jian-Jun HuangDepartment of Neurosurgery, General Hospital of Datong Coal Mining Group, Datong 037000, China. hjj1958@126.com.
Chen-Ming SunDepartment of Urology, General Hospital of Datong Coal Mining Group, Datong 037000, China. bun005@126.com.
Yan CuiDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. cuiyan_sxmu@sina.com.
Shuang-Shuang TianDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. tianshuang_sxmu@sina.com.
Cong WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. wangcong_sxmu@sina.com.
Xiao-Meng LiuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. liuxiaomengsy@163.com.
Hai-Xia ZhangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. zhx.196@163.com.
Hui WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. annieyuner@163.com.
Jie LiangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. liangjie_sxmu@sina.com.
Qing LuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. qlu@epi.msu.edu.
Tong WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjiannanlu Street, Taiyuan 030001, China. tongwang@sxmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Few studies have investigated gender differences in dietary intake. The objective of this cross-sectional study was to examine gender differences in dietary patterns and their association with the prevalence of metabolic syndrome. The food intakes of 3794 subjects enrolled by a two-stage cluster stratified sampling method were collected using a valid semi-quantitative food frequency questionnaire (FFQ). Metabolic syndrome (MetS) was defined according to the International Diabetes Federation (IDF) and its prevalence was 35.70% in the sample (37.67% in men and 24.67% in women). Dietary patterns were identified using factor analysis combined with cluster analysis and multiple group confirmatory factor analysis was used to assess the factorial invariance between gender groups. The dominating dietary pattern for men was the "balanced" dietary pattern (32.65%) and that for women was the "high-salt and energy" dietary pattern (34.42%). For men, the "animal and fried food" dietary pattern was related to higher risk of MetS (odds ratio: 1.27; 95% CI: 1.01-1.60), after adjustment for age, marital status, socioeconomic status and lifestyle factors. For women, the "high-salt and energy" dietary pattern was related to higher risk of MetS (odds ratio: 2.27; 95% CI: 1.24-4.14). We observed gender differences in dietary patterns and their association with the prevalence of MetS. For men, the "animal and fried food" dietary pattern was associated with enhancive likelihood of MetS. For women, it was the "high-salt and energy" dietary pattern.

Indexed as

Feeding BehaviorAdultAsian PeopleChinaCross-Sectional StudiesDietFemaleFood AnalysisHumansMaleMetabolic SyndromeMiddle AgedOdds RatioPrevalenceRisk Factorscluster analysisdietary patternsfactor analysisinvariancemetabolic syndrome

Identifiers

PMID27023599
PMCPMC4848649

What OpenQuestion holds

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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.