Evidence map›Paper›PMID 27708414›Full record

ArticleScientific reports2016

Association between dietary patterns and metabolic syndrome in Chinese adults: a propensity score-matched case-control study.

Yang Xia, Yeqing Gu, Fei Yu, Qing Zhang, Li Liu, Ge Meng, Hongmei Wu, Huanmin Du, Hongbin Shi, Xiaoyan Guo and 23 more

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

  1. 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

33 authors.

Yang XiaNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Yeqing GuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Fei YuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Qing ZhangHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Li LiuHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Ge MengNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Hongmei WuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Huanmin DuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Hongbin ShiHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Xiaoyan GuoNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Xing LiuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Chunlei LiNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Peipei HanDepartment of Rehabilitation and Sports Medicine, Tianjin Medical University, Tianjin, China.
Renwei DongDepartment of Rehabilitation and Sports Medicine, Tianjin Medical University, Tianjin, China.
Xiuyang WangDepartment of Rehabilitation and Sports Medicine, Tianjin Medical University, Tianjin, China.
Xue BaoNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Qian SuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Liyun FangNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Fangfang LiuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Huijun YangNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Li KangDepartment of Rehabilitation and Sports Medicine, Tianjin Medical University, Tianjin, China.
Yixuan MaDepartment of Rehabilitation and Sports Medicine, Tianjin Medical University, Tianjin, China.
Bin YuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Shaomei SunHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Xing WangHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Ming ZhouHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Qiyu JiaHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Qi GuoDepartment of Rehabilitation and Sports Medicine, Tianjin Medical University, Tianjin, China.
Yuntang WuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Kun SongHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Guowei HuangNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Guolin WangHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Kaijun NiuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies indicated that dietary patterns were associated with metabolic syndrome (MS), but little is known in Chinese. We design this case-control study to evaluate the associations between dietary patterns and MS in Chinese adults. In this study, 1492 participants with MS were matched with 1492 controls using the 1:1 ratio propensity score matching methods. Dietary intake was assessed using a valid self-administered food frequency questionnaire, and MS was defined in accordance with the criteria of the American Heart Association scientific statement of 2009. Higher scores for the high-protein/cholesterol pattern were associated with higher prevalence of MS. Compared with the participants in the lowest quartile, the odds ratio (OR) for the extreme quartile was 1.36 (95% confidence interval (CI), 1.10-1.68) and the P for trend <0.01 after adjusted for the other two dietary pattern scores. We also found a moderate consumption of the balanced pattern was associated with the lowest prevalence of MS. The ORs across quartiles of the balanced pattern were 1 (reference), 0.83 (95% CI, 0.68-1.02), 0.69 (95% CI, 0.56-0.85), and 0.84 (95% CI, 0.68-1.04) after adjustment. Our study demonstrates that there is a strong association between a diet rich in animal offal, animal blood, meat, and sausage and a higher prevalence of MS.

Indexed as

AdultBody Mass IndexCase-Control StudiesChinaCross-Sectional StudiesDiet, High-FatDiet, High-ProteinFemaleHumansMaleMetabolic SyndromeMiddle AgedNutrition SurveysOdds RatioPrevalencePropensity Score

Identifiers

PMID27708414
PMCPMC5052517

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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.