Evidence map›Paper›PMID 35811941›Full record

ArticleFrontiers in nutrition2022

Effects of Different Green Teas on Obesity and Non-Alcoholic Fatty Liver Disease Induced by a High-Fat Diet in Mice.

Dan-Dan Zhou, Qian-Qian Mao, Bang-Yan Li, Adila Saimaiti, Si-Yu Huang, Ruo-Gu Xiong, Ao Shang, Min Luo, Hang-Yu Li, Ren-You Gan and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

8 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Antiobesity effects of onion (Food science & nutrition · 2023
    Review
  6. Review
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  8. Frontiers in nutrition · 2022
    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

12 authors at 2 institutions in 1 country.

Dan-Dan ZhouGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Qian-Qian MaoGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Bang-Yan LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Adila SaimaitiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Si-Yu HuangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Ruo-Gu XiongGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Ao ShangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Min LuoGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Hang-Yu LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Ren-You GanResearch Center for Plants and Human Health, Institute of Urban Agriculture, Chinese Academy of Agricultural Sciences, Chengdu, China.
Hua-Bin LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Sha LiSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Sun Yat-sen University · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-alcoholic fatty liver disease (NAFLD) and obesity are serious public health problems. Green tea is widely consumed in the world and different green teas could possess different bioactivities. In this study, the effects of 10 selected green teas on obesity and NAFLD were evaluated and compared. The mice fed with a high-fat diet were intervened with green tea extract (200 mg/kg body weight) for 15 weeks. Most of these teas were first evaluated for their effects on obesity and NAFLD. The results showed that Selenium-Enriched Chaoqing Green Tea and Jieyang Chaoqing Tea showed the most prominent inhibition of obesity and body weight gains of mice in these two tea intervention groups and model groups were 5.3, 5.5, and 13.7 g, respectively. In addition, Jieyang Chaoqing Tea, Taiping Houkui Tea, and Selenium-Enriched Chaoqing Green Tea exerted the most notable effect on NAFLD, which was attributed to decreasing body weight, and lipid content and ameliorating oxidative stress. Furthermore, 13 phytochemicals were determined in these teas by high-performance liquid chromatography and the correlation analysis found that epigallocatechin gallate, gallocatechin, and epigallocatechin might contribute to the decrease of hepatic weight, while epicatechin might reduce oxidative stress. In general, several green teas could prevent the development of obesity and NAFLD and could be developed into functional foods. This study was also helpful for the public to select appropriate tea to prevent obesity and NAFLD.

Indexed as

antioxidant activitygreen teanon-alcoholic fatty liver diseaseobesityprevention

Identifiers

PMID35811941
PMCPMC9263825
OpenAlexW4283396529

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.