Evidence map›Paper›PMID 30585192›Full record

ReviewNutrients2018

Tea Polyphenols in Promotion of Human Health.

Naghma Khan, Hasan Mukhtar

Abstract readReview
In one paragraph

Review in Nutrients, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 314 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
314citing papers in PubMed, 6 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

314 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
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  18. Production of Instant Linden Tea (Food science & nutrition · 2026
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254 more citing papers are in PubMed but not listed here.

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

2 authors.

Naghma Khan4385 Medical Sciences Center, 1300 University Ave, Dept. of Dermatology, University of Wisconsin-Madison, Madison, WI 53706, USA. nkhan@dermatology.wisc.edu.
Hasan Mukhtar4385 Medical Sciences Center, 1300 University Ave, Dept. of Dermatology, University of Wisconsin-Madison, Madison, WI 53706, USA. hmukhtar@dermatology.wisc.edu.

Funding

American Cancer Society RSG-15-013-01-CNEUniversity of Wisconsin Carbone Cancer Center P30 CA014520
6 · The paper itself

Abstract

Tea is the most widely used beverage worldwide. Japanese and Chinese people have been drinking tea for centuries and in Asia, it is the most consumed beverage besides water. It is a rich source of pharmacologically active molecules which have been implicated to provide diverse health benefits. The three major forms of tea are green, black and oolong tea based on the degree of fermentation. The composition of tea differs with the species, season, leaves, climate, and horticultural practices. Polyphenols are the major active compounds present in teas. The catechins are the major polyphenolic compounds in green tea, which include epigallocatechin-3-gallate (EGCG), epigallocatechin, epicatechin-3-gallate and epicatechin, gallocatechins and gallocatechin gallate. EGCG is the predominant and most studied catechin in green tea. There are numerous evidences from cell culture and animal studies that tea polyphenols have beneficial effects against several pathological diseases including cancer, diabetes and cardiovascular diseases. The polyphenolic compounds present in black tea include theaflavins and thearubigins. In this review article, we will summarize recent studies documenting the role of tea polyphenols in the prevention of cancer, diabetes, cardiovascular and neurological diseases.

Indexed as

Cardiovascular DiseasesCentral Nervous System DiseasesDiabetes MellitusHumansNeoplasmsPolyphenolsTeaPolyphenolsTeacancerdiseasesEGCGgreen teatea polyphenols

Identifiers

PMID30585192
PMCPMC6356332

What OpenQuestion holds

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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.