Keywords: Green tea, Inflammation, Meta-analysis, Oxidative stress
Abbreviations: CRP, C-reactive protein; TNF-α, tumour necrosis factor-α; IL-6, interleukin-6; IL-1β, interleukin-1 beta; TAC, total antioxidant capacity; MDA, malondialdehyde; SOD, superoxide dismutase; GPX, glutathione peroxidase; WMD, weighted mean difference
Abstract
Green tea, a plant rich in bioactive compounds, has been highlighted for its beneficial effects. In the present systematic review and meta-analysis of randomised controlled trials (RCTs), the impact of green tea on inflammatory and oxidative markers is investigated. Using pre-defined keywords, online databases (PubMed, Scopus, Web of Science Core Collection, and Google Scholar) were searched for relevant articles, published from inception up to February 2024. The outcomes included C-reactive protein (CRP), tumour necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β), total antioxidant capacity (TAC), malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPX). Analyses of subgroups, linear, and non-linear associations were also carried out. Out of 1264 records initially retrieved, 38 RCTs were included. Supplementation with green tea improved the following indicators: IL-1β (weighted mean difference (WMD): −0.10 pg/mL; 95% CI: −0.15, -0.06), MDA (WMD: −0.40 mcmol/L; 95 % CI: −0.63, −0.18), TAC (WMD: 0.09 mmol/L; 95% CI: 0.05, 0.13), SOD (WMD: 17.21 u/L; 95% CI: 3.24, 31.19), and GPX (WMD: 3.90 u/L; 95% CI: 1.85, 5.95); but failed to improve others, including CRP (WMD: 0.01 mg/L; 95% CI: −0.14, 0.15), IL-6 (WMD: −0.34 pg/mL; 95% CI:−0.94, 0.26), and TNF-α (WMD: −0.07 pg/mL; 95% CI: −0.42, 0.28). Supplementation with green tea can improve the body’s oxidative status. However, the results showed no significant effect of green tea on inflammatory markers, except for IL-1β. Further studies are needed to determine the effectiveness of green tea, particularly on inflammatory status.
Introduction
Inflammation is known as the underlying factor contributing to the pathology of multiple diseases.(1) Specifically, the footsteps of inflammatory processes are apparent in the pathophysiology of most metabolic disorders.(2) By nature, inflammatory pathways are designed to take part in the human defence system, against potential foreign dangers. However, owing to various reasons, sometimes these secreted agents (interleukin (IL)-1, IL-6, tumour necrosis factor-α (TNF-α) are among the most studied) involuntarily cause harm to the individual; hence, many disorders are followed as the inevitable ramifications(3); including autoimmune diseases (such as rheumatoid arthritis, systematic lupus erythematosus), cardiovascular diseases, diabetes, and so forth.(4–6) Oxidative processes are among the most significant triggers in deriving an inflammatory response from the body(7); they are also the means used by immune cells to eradicate unwanted cells/microbes.(8) Reactive oxygen species (ROSs) and reactive nitrogen species, mainly by-products of vital oxidative processes, have been highlighted in their role of provoking inflammatory cascades.(9,10)
Nonetheless, there exist built-in mechanisms to keep the imperative oxidative/inflammatory response and the indiscriminate response causing chronic diseases in consonance.(11) These include antioxidant proteins, such as glutathione peroxidase (GPX) and superoxide dismutase (SOD); as well as anti-inflammatory eicosanoids.(12–14) Dietary factors have been found integral in the aforementioned balance; these encompass a range from wholistic dietary patterns to individual foodstuff.(15) Green tea, by the scientific name of Camellia sinensis, is amongst the most studied for its beneficial health effects.(16) Abundant in chemicals with antioxidant properties (mostly polyphenols, such as flavonoids and phenolic acids), green tea is hypothetically capable of repressing destructive oxidative/inflammatory environment in the body.(17) Nevertheless, these claims are still controversial, both in matters of long-term effectiveness and dosages needed to evoke them.
Therefore, the present systematic review, meta-analysis, and dose-response analysis of the existing literature in the form of randomised controlled trials (RCTs) were designed to conclusively answer the question of whether green tea supplementation/consumption could ameliorate the oxidative/inflammatory environment (indicated by clinically relevant factors, including C-reactive protein (CRP), IL-6, IL-1β, TNF-α, total antioxidant capacity (TAC), malondialdehyde (MDA), GPX, and SOD).
Methods
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement was used to perform the present systematic review and meta-analysis.(18) The protocol is registered in the international prospective register of systematic reviews (PROSPERO) under the number CRD42024506734. It is worthy to note that additional analyses, such as sensitivity and non-linear dose-response, were conducted beyond the predefined analyses in PROSPERO registration, due to their significance in strengthening the findings.
Search strategy
The inclusion criteria of eligible studies were determined using the population, intervention, comparison, outcome, study design (PICOS) model, which stands for participants (aged ≥ 18 years old), intervention (green tea supplementation), comparison (studies with control group), outcome (C-reactive protein (CRP), tumour necrosis factor α (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β), total antioxidant capacity (TAC), malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GPX)), and study (randomised controlled trials). We conducted a thorough search of the online databases of PubMed, Scopus, Web of Science Core Collection, and Google Scholar from inception up to February 2024, regardless of language or time limitations. Search terms are listed in Supplementary Table 1. To ensure that all qualified publications were identified, we manually searched the reference lists of all relevant studies and previous reviews.
Table 1.
Results of risk of bias assessment for randomised clinical trials included in the current meta-analysis by the revised Cochrane risk-of-bias tool (RoB-2)
| Author, year of publication (country) | Bias arising from the randomisation process |
Bias due to deviations from intended interventions |
Bias due to missing outcome data | Bias in measurement of the outcome |
Bias in selection of the reported result | Overall risk of bias |
|---|---|---|---|---|---|---|
| Van het Hof et al., 1997 (Netherlands) |
S | S | L | L | L | S |
| De Maat et al., 2000 (Netherlands) |
S | S | L | L | L | S |
| Erba et al., 2007 (Italy) |
L | L | L | L | L | L |
| Fukino et al., 2008 (Japan) |
S | L | L | L | S | S |
| Mohammadi et al., 2010 (Iran) |
L | L | L | L | L | L |
| Li et al., 2010 (USA) |
L | S | L | L | L | L |
| Basu et al., 2011 (USA) |
L | L | L | L | L | L |
| Sone et al., 2011 (Japan) |
L | L | L | L | L | L |
| Bogdanski et al., 2012 (Poland) |
L | L | L | L | L | L |
| Suliburska et al., 2012 (Poland) |
L | L | L | L | L | L |
| Mousavi et al., 2013 (Iran) |
L | S | L | L | L | L |
| Basu et al., 2013 (USA) |
L | L | L | L | L | L |
| Lasaite et al., 2014 (Lithuania) |
L | L | L | L | L | L |
| Spadiene et al., 2014 (Lithuania) |
L | L | L | L | L | L |
| Liu et al., 2014 (Taiwan) |
L | L | L | L | L | L |
| Mielgo-Ayuso et al., 2014 (Spain) |
L | L | L | L | L | L |
| Kuo et al., 2015 (Taiwan) |
L | L | L | L | L | L |
| Borges et al., 2016 (Brazil) |
L | L | L | L | L | L |
| Lee et al., 2016 (Taiwan) |
L | L | L | L | L | L |
| Hussain et al., 2017 (Pakistan) |
L | L | L | L | L | L |
| Hadi et al., 2017 (Iran) |
L | L | L | L | L | L |
| Soeizi et al., 2017 (Iran) |
L | S | L | L | S | S |
| Tabatabaee et al., 2017 (Iran) |
L | L | L | L | L | L |
| Mombaini et al., 2017 (Iran) |
L | L | L | L | L | L |
| Nogueira et al., 2017 (Brazil) |
L | L | L | L | L | L |
| Venkatakrishnanet al., 2018 (Taiwan) |
L | L | L | L | L | L |
| Shin et al., 2018 (South Korea) |
S | S | L | L | L | S |
| Maeda-Yamamoto et al., 2018 (Japan) |
L | L | L | L | L | L |
| Azizbeigi et al., 2019 (Iran) |
L | L | L | L | L | L |
| Bagheri et al., 2020 (Iran) |
L | S | L | L | L | L |
| Benlloch et al., 2020 (Spain) |
L | L | L | L | L | L |
| Hadi et al., 2020 (Iran) |
L | L | L | L | L | L |
| Kondori et al., 2021 (Iran) |
L | S | L | L | L | L |
| Bazyar et al., 2021 (Iran) |
L | L | L | L | L | L |
| El-Elimat et al., 2022 (Jordan) |
L | L | L | L | L | L |
| Naderifard al., 2022 (Iran) |
L | L | L | L | L | L |
| Rondanelli al., 2023 (Italy) |
L | L | L | L | L | L |
| Ahmed Merza Mohammadet al., 2023 (Iraq) |
L | L | L | L | L | L |
H: high risk, L: low risk, S: some concerns.
Study selection and eligibility criteria
We included eligible studies in the current meta-analysis if they met the following criteria: randomised controlled trials; adult population (aged more than 18 years); reported CRP, IL-6, TNF-α, IL-1β, TAC, MDA, SOD, or GPX in both the intervention and placebo groups; and had an intervention period of more than 2 weeks. We excluded the studies that had the following conditions: had duplicated data, lacked the placebo group, had a non-RCT design, and were carried out on animals, children, pregnant or breastfeeding women, and those with inadequate information for the outcomes of interest.
Data extraction
Two independent reviewers performed the data extraction and study selection. The following data were extracted from the included studies: the first author’s last name, the duration and location of the study, the year of publication, the age and gender of participants, the research design, the type and dose of green tea, the number of participants in each group, and results (means and standard deviations (SDs) for the outcomes of interest before and after the intervention).
Risk of bias assessment
A comprehensive evaluation of the bias risk in the included studies is presented in Table 1. The risk of bias in the included studies was assessed using the updated version of the Cochrane risk-of-bias instrument (RoB-2).(19) This tool assesses potential sources of bias with regard to the following methodological domains: the randomisation procedure; deviations from intended interventions; missing outcome data; selective reporting of results; outcome measurement; and the final assessment. The included studies were assessed as low risk (L), some concerns (S), or high risk (H) of bias with regard to each potential source of bias, based on the recommendations for risk of bias assessment published in the Cochrane Handbook.
Certainty assessment
To assess certainty of evidence across the included studies, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group guidelines were used. This tool includes five domains to examine the quality of evidence including risk of bias, inconsistency, imprecision, indirectness, and publication bias. With respect to the quality of evidence, studies were categorised into four groups: high, moderate, low, and very low.(20)
Statistical analysis
The mean changes and standard deviations (SDs) of the outcome of interest for the intervention and placebo groups were used to estimate the effect sizes. The results of effect sizes were displayed as weighted mean differences (WMDs) and 95% confidence intervals (CIs).(21) Mean changes were estimated by calculating changes in the outcomes during the trial, if mean changes were not reported. The Hozo et al. method was also applied to convert standard errors, 95% CIs, and interquartile ranges to SDs.(22) Using the following formula, missing SDs for changes were estimated: SDchange=square root [(SDbaseline 2 + SDfinal 2) − (2×R×SDbaseline×SDfinal)]. The R-value of the mentioned formula was considered to be 0.9.(23) We calculated the overall effect size using a random effect model that takes into account study differences (the DerSimonian-Laird method).(24) Furthermore, between-study heterogeneity was measured using the I2 statistic and Cochrane’s Q test. Significant between-study heterogeneity was identified with an I2 value >50% or a p-value <0.05 for the Q-test.(25,26) We conducted subgroup analyses, to identify potential sources of heterogeneity considering some important variables including baseline body mass index (BMI (kg/m2)), health condition of participants, type of green tea, study location, green tea dosage (mg/ day), duration of intervention (weeks), and gender. Sensitivity analysis was used to show how each study affected the overall effect size using the leave-one-out method.(27) We used the Elbourne et al. method to handle the cross-over design study.(28) Publication bias was assessed using visual inspection of the funnel plots and a Begg rank correlation test. The study utilised the trim-and-fill method to examine the impact of publication bias on the study’s outcomes and adjust the overall effect size.(29) Meta-regression and non-linear dose-response (using fractional polynomial modelling) were performed to observe the association between the green tea dosage (mg/day) and the intervention duration (weeks) with the outcomes of interest.(30) The meta-analysis was done using the Stata Software, version 14 (StataCorp). p-values <0.05 were considered as statistically significant.
Results
Study selection
We obtained 1264 records from the initial search. Following that, we eliminated 35 duplicate papers. After evaluating the remaining 1229 records, we excluded 820 irrelevant articles based on title and abstract assessment. Among the 409 papers retained for more comprehensive full-text evaluation, 253 RCTs were excluded due to reporting irrelevant outcomes. Furthermore, additional 34 articles were excluded due to their intervention duration being insufficient (specifically, less than two weeks). Additionally, 72 RCTs were removed from the analysis due to administering green tea in combination with other compounds exclusively within the intervention group. Twelve RCTs were also excluded because they were conducted on children. Finally, 38 eligible RCTs were used in the current systematic review and meta-analysis,(31–68) among which 19 articles assessed the impact of green tea on CRP,(32,37–40,42,46–48,50,51,54,55,60–63,65,67) 13 articles on TAC,(36,40,41,44,45,49,52,53,56,57,59,60,68) 11 articles on MDA,(33,40,44,45,49,52,53,57,64,66,68) 10 articles on IL-6,(31,34–36,39,40,46,47,62,67) 8 articles on TNFα,(31,35,39,40,46,47,60,67) 7 articles on GPX,(33,34,41,53,58,66,68) 5 articles on SOD,(34,41,43,53,68) and two articles on IL-1β.(62,67) Figure 1 illustrates the flow diagram representing the process of study selection.
Fig. 1.
Flow diagram of study selection.
Characteristics of the included studies
Table 2 provides an overview of the characteristics of the 38 RCTs included in the present systematic review and meta-analysis. These RCTs were conducted in Iran,(33,35–37,39,40,44,45,47,49,57,63) Taiwan,(41,50,52,55) the United States,(58,62,64) Japan,(43,61,65) Poland,(59,60) Lithuania,(53,56) Netherlands,(67,68) Spain,(38,54) Italy,(32,66) South Korea,(42) Jordan,(34) and Iraq,(31) and were published between years 1997 and 2023. Six studies were exclusively performed on male subjects,(35,38–40,44,52) 4 studies on female subjects,(33,46,47,54) and others on both genders. The number of participants in the included RCT samples ranged from 20 to 143, yielding a total sample size of 1985 individuals. The mean age of participants was between 19 and 63 years. The dosage of green tea supplementation varied between 200 mg/day (green tea extract) and 9 g/day (green tea leaves), and the duration of intervention ranged from 4 to 48 weeks across selected RCTs. Except for three studies that had cross-over design,(46,61,65) the majority of studies took advantage of a parallel design. Regarding the vectors of green tea supplements used in the intervention, 12 studies used green tea extract,(32,35,42,48,49,52,53,55,56,60,63,64) 9 studies used epigallocatechin-3-gallate (EGCG),(36–38,43,51,54,58,59,62) 5 studies used green tea catechins,(31,41,61,65,66) and other studies used green tea leaves. Also, four RCTs examined post-exercise impact of green tea.(33,35,39,40) It should be noted that we made sure that in case of combined intervention, the control group received the same accompanied treatment. The included studies were conducted on healthy individuals,(33,41,43,52,61,66–68) patients with type 2 diabetes (T2D) and prediabetes,(36,37,53,55–57,63,65) obese and overweight individuals,(32,34,39,40,46,59,60) athletes,(35,49) patients with metabolic syndrome,(58,62) non-alcoholic fatty liver disease (NAFLD),(44,48) diabetic nephropathy,(51) chronic stable angina,(50) β–thalassaemia major,(45) polycystic ovary syndrome,(47) multiple sclerosis,(38) COVID-19,(31) and older adults.(64)
Table 2.
Characteristics of included studies
| Author, Year (Location) | Study design | Population | Gender | Number (Case/control) | Intervention Mean (range) age (years) | Intervention Mean BMI (kg/m2) | Duration (Weeks) | Intervention Intervention group Control group |
Outcome |
|---|---|---|---|---|---|---|---|---|---|
| Van het Hof et al., 1997 (Netherlands) |
RCT, Parallel | Healthy | M/F | 14/16 | 37 | 23.72 | 4 | Green Tea (3 g/day) Placebo |
TAC MDA GPx SOD |
| De Maat et al., 2000 (Netherlands) (a) |
RCT, Parallel | Smoking healthy individuals | M/F | 15/15 | 32 | 22 | 4 | Green Tea (3 g/day) Placebo |
CRP TNFα IL-1β IL-6 |
| De Maat et al., 2000 (Netherlands) (b) |
RCT, Parallel | Smoking healthy individuals | M/F | 13/15 | 33 | 22 | 4 | Green Tea (9 g/day) Placebo |
CRP TNFα IL-1β IL-6 |
| Erba et al., 2007 (Italy) |
RCT, Parallel | Healthy | M/F | 12-Dec | 19.1 | NR | 6 | Green Tea Catechins (250 mg/day) Placebo |
MDA GPx |
| Fukino et al., 2008 (Japan) (a) |
RCT, Crossover | T2DM and prediabetes | M/F | 29/31 | 53.9 | 25.4 | 8 | Green Tea Catechins (456 mg/day) Placebo |
CRP |
| Fukino et al., 2008 (Japan) (b) |
RCT, Crossover | T2DM and prediabetes | M/F | 31/29 | 53.5 | 26 | 8 | Green Tea Catechins (456 mg/day) Placebo |
CRP |
| Mohammadi et al., 2010 (Iran) |
RCT, Parallel | T2DM | M/F | 29/29 | 55.14 | 28.64 | 8 | Green Tea Extract (1500 mg/day) Placebo |
CRP |
| Li et al., 2010 (USA) |
RCT, Parallel | Older Adults | M/F | 20/20 | 59 | 24.2 | 16 | Green Tea Extract (200 mg/day) + Lutein Placebo + Lutein |
MDA |
| Basu et al., 2011 (USA) (a) |
RCT, Parallel | MetS | M/F | 13-Dec | 42.8 | 36.1 | 8 | EGCG (440 mg/day – Brewed Green Tea) Placebo |
CRP IL-1β IL-6 |
| Basu et al., 2011 (USA) (b) |
RCT, Parallel | MetS | M/F | 10-Dec | 39.5 | 36.1 | 8 | EGCG (500 mg/day - Capsule) Placebo |
CRP IL-1β IL-6 |
| Sone et al., 2011 (Japan) |
RCT, Crossover | Healthy | M/F | 25/26 | 43.2 | 24.6 | 9 | Green Tea Catechins (400 mg/day) Placebo |
CRP |
| Bogdanski et al., 2012 (Poland) |
RCT, DB, Parallel | Obese, Hypertensive patients | M/F | 28/28 | 49.2 | 32.5 | 12 | Green Tea Extract (379 mg/day) = 208 mg EGCG Placebo |
CRP TNFα TAC |
| Suliburska et al., 2012 (Poland) |
RCT, DB, Parallel | Obese | M/F | 23/23 | 48.56 | 32.07 | 12 | EGCG (208 mg/day) Placebo (Microcrystalline Cellulose) |
TAC |
| Mousavi et al., 2013 (Iran) (a) |
RCT, Parallel | T2DM | M/F | 24/14 | 54.6 | 27.4 | 8 | Green Tea (10 g/day) = 800 ml Green Tea Drink Placebo |
TAC |
| MDA | |||||||||
| Mousavi et al., 2013 (Iran) (b) |
RCT, Parallel | T2DM | M/F | 25/14 | 54.6 | 27.4 | 8 | Green Tea (5 g/day) = 400 ml Green Tea Drink Placebo |
TAC MDA |
| Basu et al., 2013 (USA) (a) |
RCT, Parallel | MetS | M/F | 13-Dec | 42.8 | 34.6 | 8 | EGCG (440 mg/day – Brewed Green Tea) Placebo |
GPx |
| Basu et al., 2013 (USA) (b) |
RCT, Parallel | MetS | M/F | 10-Dec | 39.5 | 38 | 8 | EGCG (460 mg/day - Capsule) Placebo |
GPx |
| Lasaite et al., 2014 (Lithuania) |
RCT, DB, Parallel | T2DM | M/F | 17/14 | 57.2 | NR | 36 | Green Tea Extract (400 mg/day) Placebo (Microcrystalline cellulose) |
TAC |
| Spadiene et al., 2014 (Lithuania) (a) |
RCT, DB, Parallel | T2DM | M/F | 20/25 | 62.18 | NR | 36 | Green Tea Extract (400 mg/day) Placebo (Microcrystalline cellulose) |
TAC MDA GPx SOD |
| Spadiene et al., 2014 (Lithuania) (b) |
RCT, DB, Parallel | T2DM | M/F | 20/25 | 62.18 | NR | 36 | Green Tea Extract (400 mg/day) Placebo (Microcrystalline cellulose) |
TAC MDA GPx SOD |
| Liu et al., 2014 (Taiwan) |
RCT, DB, Parallel | T2DM | M/F | 39/38 | 55 | 26.2 | 16 | Decaffeinated Green Tea Extract (1500 mg/day) Placebo |
CRP |
| Mielgo-Ayuso et al., 2014 (Spain) |
RCT, DB, Parallel | Obese | F | 43/30 | 19-49 | NR | 12 | EGCG (300 mg/day) Placebo (Lactose) |
CRP |
| Kuo et al., 2015 (Taiwan) |
RCT, DB, Parallel | Healthy | M | 10-Oct | 20 | 21.95 | 4 | Green Tea Extract (250 mg/day) Placebo (Starch) | TAC MDA CRP |
| Borges et al., 2016 (Brazil) |
RCT, DB, Parallel | Diabetic Nephropathy | M/F | 21/21 | 43.2 | 24.6 | 12 | EGCG (800 mg/day) Placebo |
|
| Lee et al., 2016 (Taiwan) |
RCT, Parallel | Chronic Stable Angina | M/F | 35/36 | 62.6 | 25.3 | 6 | Green Tea Polyphenols (600 mg/day) Placebo |
CRP |
| Hussain et al., 2017 (Pakistan) |
RCT, Parallel | NAFLD | M/F | 40/40 | 25 | 29.5 | 12 | Green Tea Extract (1000 mg/day) Placebo |
CRP |
| Hadi et al., 2017 (Iran) |
RCT, DB, Parallel | Soccer Athletes | M | 16/16 | 20.94 | 22.6 | 6 | Green Tea Extract (450 mg/day) Placebo (Maltodextrin) |
TAC |
| Soeizi et al., 2017 (Iran) |
RCT, Parallel | β–thalassaemia major | M/F | 26/26 | 23.1 | 20.9 | 8 | Green Tea (7.5 g/day) Placebo |
TAC MDA |
| Tabatabaee et al., 2017 (Iran) |
RCT, DB, Parallel | NAFLD | M | 21/24 | 41 | 43.06 | 12 | Green Tea (550 mg/day) Placebo |
TAC MDA |
| Mombaini et al., 2017 (Iran) |
RCT, Parallel | PCOS | F | 22/23 | 23.22 | 28.96 | 6 | Green Tea (2000 mg/day) Placebo |
CRP TNFα IL-6 |
| Nogueira et al., 2017 (Brazil) |
RCT, Crossover | Obese prehypertensive women | F | 20/20 | 41.1 | 33.56 | 4 | Green Tea (1500 mg/day) Placebo (Cellulose) |
CRP TNFα IL-6 |
| Venkatakrishnanet al., 2018 (Taiwan) |
RCT, DB, Parallel | Healthy | M/F | 20/19 | 35-55 | 31.39 | 12 | Green Tea Catechins (780 mg/day) Placebo |
TAC GPx SOD |
| Shin et al., 2018 (South Korea) |
RCT, Parallel | Complete removal of colorectal adenomas by endoscopic polypectomy | M/F | 72/71 | 59.6 | 24.1 | 48 | Green Tea Extract (900 mg/day) Placebo |
CRP |
| Maeda-Yamamoto et al., 2018 (Japan) |
RCT, DB, Parallel | Healthy | M/F | 38/37 | 49.8 | 23.9 | 12 | EGCG (322 mg/day) Placebo |
SOD |
| Azizbeigi et al., 2019 (Iran) |
RCT, Parallel | Obese | M | 10-Oct | 23.9 | 31.8 | 8 | Green Tea (500 mg/day) + Training Placebo (Sucrose) + Training |
CRP TNFα IL-6 TAC MDA |
| Bagheri et al., 2020 (Iran) |
RCT, Parallel | Overweight | M | 15/15 | 43.8 | 27.3 | 8 | Green Tea (500 mg/day) + Training Placebo + Training |
CRP TNFα IL-6 |
| Benlloch et al., 2020 (Spain) |
RCT, Parallel | MS | M | 25/21 | 44.56 | 25.92 | 16 | EGCG (800 mg/day) Placebo |
CRP |
| Hadi et al., 2020 (Iran) |
RCT, DB, Parallel | T2DM | M/F | 22/22 | 51.47 | 29.44 | 8 | EGCG (300 mg/day) Placebo |
CRP TAC MDA |
| Kondori et al., 2021 (Iran) |
RCT, Parallel | Athletes | M | 12-Dec | 24.5 | 23.2 | 10 | Green Tea Extract (500 mg/day) + Exercise Placebo (Maltodextrin) + Exercise |
CRP TAC MDA |
| Bazyar et al., 2021 (Iran) |
RCT, DB, Parallel | T2DM | M/F | 22/22 | 51.75 | 29.46 | 8 | EGCG (300 mg/day) Placebo (White Flour) |
IL-6 TAC |
| El-Elimat et al., 2022 (Jordan) |
non-randomised open-label comparative study | Overweight and obese | M/F | 16/18 | 28 | 35.7 | 12 | Matcha Green Tea (2000 mg/day) Placebo |
IL-6 GPx |
| Naderifard al., 2022 (Iran) (a) |
RCT, Parallel | Untrained Women | F | 14/14 | 32.4 | 26.22 | 6 | Matcha Green Tea (1000 mg/day) Placebo (Dextrin) |
MDA GPx |
| Naderifard al., 2022 (Iran) (b) |
RCT, Parallel | Untrained Women | F | 14/14 | 32.4 | 26.22 | 6 | Matcha Green Tea (1000 mg/day) + Training Placebo (Dextrin) + Training |
MDA GPx |
| Rondanelli al., 2023 (Italy) |
RCT, DB, Parallel | Overweight or obese post-menopausal women | M/F | 14/14 | 60.57 | 31.1 | 8 | Green Tea Extract (300 mg/day) Placebo |
CRP |
| Ahmed Merza Mohammadet al., 2023 (Iraq) |
RCT, DB, Parallel | COVID | M/F | 26/24 | 50.1 | 27.11 | 4 | Green Tea Catechins (360 mg/day) Placebo |
TNFα IL-6 |
DB: Double-blind/NR: Not reported/T2DM: Type 2 diabetes mellitus/MetS: Metabolic syndrome/ PCOS: Polycystic ovary syndrome/NAFLD: Non-alcoholic fatty liver disease/MS: Multiple Sclerosis/M: male/F: female/CRP: C-reactive protein/TNF-a: Tumour necrosis factor-a/IL: Interleukin/TAC: Total antioxidant capacity/MDA: Malondialdehyde/GPx: Glutathione peroxidase/SOD: Superoxide dismutase.
Data presented in order of year.
Results from quality assessment
Risk of bias was assessed using the Cochrane Risk of Bias Tool version 2 (RoB2) for the following domains: randomisation process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. All but five studies were considered at overall low risk for bias.(42,45,65,67,68) Two assessors conducted the assessment independently. Any disagreements were resolved either through discussion or with the involvement of a third reviewer. None of the studies demonstrated a high risk of bias in any areas (Table 1).
Meta-analysis
The pooled effect size of the included studies indicated that green tea supplementation could decrease levels of IL-1β (WMD: −0.10 pg/mL; 95% CI: −0.15, −0.06; I2 = 39.3 %; Fig. 2), and MDA (WMD: −0.40 mcmol/L; 95 % CI: −0.63, −0.18; I2 = 99.2 %; Fig. 3). Also, the supplementation increased levels of TAC (WMD: 0.09 mmol/L; 95% CI: 0.05, 0.13; I2 = 84.9 %; Fig. 3), SOD (WMD: 17.21 u/L; 95% CI: 3.24, 31.19; I2 = 92.1 %; Fig. 3), and GPX (WMD: 3.90 u/L; 95% CI: 1.85, 5.95; I2 = 93.1 %; Fig. 3). However, green tea intake did not show a beneficial impact on CRP (WMD: 0.01 mg/L; 95% CI: −0.14, 0.15; I2 = 94.0%; Fig. 2), IL-6 (WMD: −0.34 pg/mL; 95% CI: −0.94, 0.26; I2 = 84.2 %; Fig. 2), or TNF-α (WMD: −0.07 pg/mL; 95% CI: −0.42, 0.28; I2 = 90.3 %; Fig. 2).
Fig. 2.
Forest plots for the effect of green tea supplementation on inflammatory markers. Horizontal lines represent 95% CIs. Diamonds represent pooled estimates from random-effects analysis. WMD: weighted mean difference, CI: confidence interval.
Fig. 3.
Forest plots for the effect of green tea supplementation on antioxidant status. Horizontal lines represent 95% CIs. Diamonds represent pooled estimates from random-effects analysis. WMD: weighted mean difference, CI: confidence interval.
Subgroup analysis
The findings of subgroup analyses are shown in Table 3. To find sources of heterogeneity and explore the effect sizes, we carried out subgroup analyses based on some confounding factors. The results showed that green tea consumption is unable to improve CRP levels in any of the subgroups. The supplementation decreased IL-6 levels in participants who consumed less than 500 mg of green tea per day. The green tea intake could improve TNF-α in those studies which included participants with a BMI equal to or more than 30 kg/m2, carried out in non-Asian countries, and lasted more than 8 weeks.
Table 3.
Subgroup analysis to assess the effect of green tea supplementation on inflammatory markers and antioxidant status
| Variable | Number of effect sizes | WMD (95% CI) | p-Valuea | I2 (%)b | p for heterogeneityc |
p for between subgroup heterogeneityd |
|---|---|---|---|---|---|---|
| CRP | ||||||
| Overall | 22 | 0.01 (−0.14, 0.15) | 0.914 | 94.0 | < 0.001 | – |
| BMI (kg/m2) | < 0.001 | |||||
| <30 | 14 | −0.12 (−0.37, 0.12) | 0.332 | 94.1 | < 0.001 | |
| ≥30 | 7 | 0.19 (−0.04, 0.43) | 0.108 | 92.8 | < 0.001 | |
| Dosage (mg/day) | 0.036 | |||||
| <500 | 8 | 0.30 (−0.02, 0.64) | 0.069 | 92.9 | < 0.001 | |
| ≥500 | 14 | −0.12 (−0.31, 0.06) | 0.199 | 94.7 | < 0.001 | |
| Duration (weeks) | 0.010 | |||||
| ≤8 | 15 | 0.08 (−0.09, 0.27) | 0.353 | 90.4 | < 0.001 | |
| >8 | 7 | −0.11 (−0.46, 0.23) | 0.523 | 96.9 | < 0.001 | |
| Health status | < 0.001 | |||||
| Healthy | 4 | −0.13 (−0.68, 0.40) | 0.622 | 88.4 | < 0.001 | |
| Unhealthy | 18 | 0.05 (−0.10, 0.21) | 0.496 | 94.3 | < 0.001 | |
| Type of intervention | 0.151 | |||||
| Green tea extract | 17 | −0.13 (−0.28, 0.02) | 0.090 | 94.2 | < 0.001 | |
| Brewed green tea | 5 | 1.00 (−0.12, 2.13) | 0.081 | 94.1 | < 0.001 | |
| Location of study | < 0.001 | |||||
| Asia | 12 | −0.17 (−0.42, 0.06) | 0.154 | 94.9 | < 0.001 | |
| Non-Asia | 10 | −0.005 (−0.02, 0.01) | 0.688 | 91.5 | < 0.001 | |
| Gender | < 0.001 | |||||
| Both | 16 | 0.12 (−0.12, 0.37) | 0.323 | 94.3 | < 0.001 | |
| Male | 2 | −0.36 (−1.05, 0.31) | 0.291 | 90.4 | 0.001 | |
| Female | 4 | 0.07 (−0.11, 0.27) | 0.442 | 89.6 | < 0.001 | |
| IL-6 | ||||||
| Overall | 12 | −0.34 (−0.94, 0.26) | 0.271 | 84.2 | < 0.001 | – |
| BMI (kg/m2) | 0.001 | |||||
| <30 | 7 | 0.09 (−0.44, 0.64) | 0.731 | 76.8 | < 0.001 | |
| ≥30 | 5 | −0.97 (−3.53, 1.40) | 0.421 | 87.5 | < 0.001 | |
| Dosage (mg/day) | 0.037 | |||||
| <500 | 3 | −0.41 (−0.79, −0.03) | 0.032 | 0.0 | 0.734 | |
| ≥500 | 9 | −0.28 (−1.13, 0.56) | 0.513 | 87.6 | < 0.001 | |
| Duration (weeks) | < 0.001 | |||||
| ≤8 | 10 | −0.55 (−1.11, 0.007) | 0.053 | 80.9 | < 0.001 | |
| >8 | 1 | −1.90 (−3.86, 0.06) | 0.058 | – | – | |
| Health status | < 0.001 | |||||
| Healthy | 4 | 0.70 (−0.63, 2.04) | 0.299 | 84.7 | < 0.001 | |
| Unhealthy | 8 | −1.05 (−2.03, −0.07) | 0.036 | 80.1 | < 0.001 | |
| Type of intervention | 0.755 | |||||
| Green tea extract | 10 | −0.38 (−1.03, 0.25) | 0.238 | 87.0 | < 0.001 | |
| Brewed green tea | 2 | 0.22 (−1.22, 1.67) | 0.765 | 0.0 | 0.683 | |
| Location of study | 0.001 | |||||
| Asia | 7 | −0.06 (−0.58, 0.45) | 0.801 | 79.9 | < 0.001 | |
| Non-Asia | 5 | −0.37 (−2.93, 2.16) | 0.770 | 86.3 | < 0.001 | |
| Gender | < 0.001 | |||||
| Both | 7 | −0.36 (−1.25, 0.52) | 0.423 | 41.2 | 0.116 | |
| Male | 3 | 0.63 (−0.43, 1.70) | 0.243 | 90.0 | < 0.001 | |
| Female | 2 | −2.21 (−5.63, 1.20) | 0.204 | 94.5 | < 0.001 | |
| TNF-α | ||||||
| Overall | 9 | −0.07 (−0.42, 0.28) | 0.696 | 90.3 | < 0.001 | – |
| BMI (kg/m2) | < 0.001 | |||||
| <30 | 6 | 0.28 (−0.15, 0.72) | 0.199 | 84.4 | < 0.001 | |
| ≥30 | 3 | −0.60 (−0.91, −0.29) | < 0.001 | 67.9 | < 0.001 | |
| Dosage (mg/day) | < 0.001 | |||||
| <500 | 2 | −0.44 (−1.13, 0.25) | 0.212 | 55.5 | 0.134 | |
| ≥500 | 7 | 0.02 (−0.41, 0.28) | 0.909 | 89.5 | < 0.001 | |
| Duration (weeks) | < 0.001 | |||||
| ≤8 | 7 | −0.16 (−0.42, 0.08) | 0.199 | 74.6 | 0.001 | |
| >8 | 1 | −0.67 (−0.89, −0.44) | < 0.001 | – | – | |
| Health status | 0.019 | |||||
| Healthy | 4 | 0.60 (−0.31, 1.52) | 0.196 | 90.6 | < 0.001 | |
| Unhealthy | 5 | −0.39 (−0.80, 0.01) | 0.057 | 91.2 | < 0.001 | |
| Type of intervention | 0.999 | |||||
| Green tea extract | 8 | −0.05 (−0.43, 0.32) | 0.772 | 91.6 | < 0.001 | |
| Brewed green tea | 1 | −0.14 (−0.69, 0.41) | 0.618 | – | – | |
| Location of study | < 0.001 | |||||
| Asia | 5 | 0.28 (−0.32, 0.89) | 0.358 | 89.8 | < 0.001 | |
| Non-Asia | 4 | −0.43 (−0.66, −0.20) | < 0.001 | 50.3 | 0.110 | |
| Gender | < 0.001 | |||||
| Both | 4 | −0.33 (−0.72, 0.04) | 0.087 | 53.6 | 0.091 | |
| Male | 3 | 0.63 (−1.41, 2.67) | 0.544 | 94.9 | < 0.001 | |
| Female | 2 | −0.16 (−0.61, 0.28) | 0.477 | 93.7 | < 0.001 | |
| TAC | ||||||
| Overall | 15 | 0.09 (0.05, 0.13) | < 0.001 | 84.9 | < 0.001 | – |
| BMI (kg/m2) | < 0.001 | |||||
| <30 | 7 | 0.09 (0.06, 0.11) | < 0.001 | 58.1 | 0.026 | |
| ≥30 | 5 | 0.16 (0.12, 0.19) | < 0.001 | 0.0 | 0.592 | |
| Dosage (mg/day) | < 0.001 | |||||
| <500 | 7 | 0.08 (−0.003, 0.17) | 0.058 | 91.9 | < 0.001 | |
| ≥500 | 8 | 0.09 (0.07, 0.11) | < 0.001 | 0.0 | 0.581 | |
| Duration (weeks) | 0.238 | |||||
| ≤8 | 8 | 0.08 (0.06, 0.11) | < 0.001 | 52.4 | 0.040 | |
| >8 | 7 | 0.06 (−0.03, 0.17) | 0.209 | 92.2 | < 0.001 | |
| Health status | 0.648 | |||||
| Healthy | 3 | 0.07 (0.03, 0.11) | < 0.001 | 77.5 | 0.012 | |
| Unhealthy | 12 | 0.08 (0.02, 0.15) | 0.008 | 86.8 | < 0.001 | |
| Type of intervention | < 0.001 | |||||
| Green tea extract | 10 | 0.07 (0.006, 0.14) | 0.033 | 87.9 | < 0.001 | |
| Brewed green tea | 5 | 0.09 (0.08, 0.11) | < 0.001 | 0.0 | 0.601 | |
| Location of study | 0.860 | |||||
| Asia | 9 | 0.10 (0.06, 0.14) | < 0.001 | 55.9 | 0.020 | |
| Non-Asia | 6 | 0.06 (−0.02, 0.14) | 0.146 | 93.3 | < 0.001 | |
| Gender | 0.009 | |||||
| Both | 11 | 0.08 (0.03, 0.14) | 0.003 | 87.5 | < 0.001 | |
| Male | 3 | 0.07 (−0.01, 0.16) | 0.085 | 38.5 | 0.197 | |
| Female | 1 | 0.14 (0.08, 0.19) | < 0.001 | – | – | |
| MDA | ||||||
| Overall | 14 | −0.40 (−0.63,−0.18) | < 0.001 | 99.2 | < 0.001 | – |
| BMI (kg/m2) | < 0.001 | |||||
| <30 | 9 | −0.43 (−0.71, −0.15) | 0.002 | 99.5 | < 0.001 | |
| ≥30 | 2 | −0.60 (−1.58, 0.37) | 0.227 | 92.0 | < 0.001 | |
| Dosage (mg/day) | < 0.001 | |||||
| <500 | 5 | −0.03 (−0.07, 0.01) | 0.130 | 61.5 | < 0.001 | |
| ≥500 | 9 | −0.52 (−0.95, −0.10) | 0.015 | 98.8 | 0.034 | |
| Duration (weeks) | 0.113 | |||||
| ≤8 | 10 | −0.42 (−0.82, −0.03) | 0.033 | 99.5 | < 0.001 | |
| >8 | 4 | −0.32 (−0.76, 0.10) | 0.135 | 90.3 | < 0.001 | |
| Health status | < 0.001 | |||||
| Healthy | 7 | −0.43 (−0.83, −0.04) | 0.013 | 99.6 | < 0.001 | |
| Unhealthy | 7 | −0.37 (−0.67, −0.07) | 0.030 | 84.2 | < 0.001 | |
| Type of intervention | < 0.001 | |||||
| Green tea extract | 10 | −0.43 (−0.69, −0.16) | 0.001 | 99.4 | < 0.001 | |
| Brewed green tea | 4 | −0.32 (−1.10, 0.44) | 0.410 | 95.5 | < 0.001 | |
| Location of study | < 0.001 | |||||
| Asia | 9 | −0.58 (−1.05, −0.11) | 0.015 | 99.5 | < 0.001 | |
| Non-Asia | 5 | −0.02 (−0.17, 0.13) | 0.794 | 84.3 | < 0.001 | |
| Gender | < 0.001 | |||||
| Both | 9 | −0.31 (−0.53, −0.10) | 0.004 | 92.6 | < 0.001 | |
| Male | 3 | −0.13 (−0.38, 0.11) | 0.297 | 60.8 | 0.078 | |
| Female | 2 | −1.001 (−1.17, −0.82) | < 0.001 | 92.6 | < 0.001 | |
| GPX | ||||||
| Overall | 10 | 3.90 (1.85, 5.95) | < 0.001 | 93.1 | < 0.001 | – |
| BMI (kg/m2) | < 0.001 | |||||
| <30 | 3 | 9.53 (0.21, 18.86) | 0.045 | 94.3 | < 0.001 | |
| ≥30 | 4 | 4.29 (−0.01, 8.60) | 0.051 | 92.0 | < 0.001 | |
| Dosage (mg/day) | 0.584 | |||||
| <500 | 4 | 3.16 (−1.62, 7.94) | 0.195 | 93.6 | < 0.001 | |
| ≥500 | 6 | 4.58 (1.49, 7.67) | 0.004 | 94.0 | < 0.001 | |
| Duration (weeks) | < 0.001 | |||||
| ≤8 | 6 | 6.95 (3.12, 10.78) | < 0.001 | 89.2 | < 0.001 | |
| >8 | 4 | 0.53 (−1.17, 2.23) | 0.540 | 87.9 | < 0.001 | |
| Health status | < 0.001 | |||||
| Healthy | 5 | 7.12 (2.00, 12.24) | 0.006 | 90.4 | < 0.001 | |
| Unhealthy | 5 | 1.71 (−0.36, 3.79) | 0.106 | 92.4 | < 0.001 | |
| Type of intervention | < 0.001 | |||||
| Green tea extract | 7 | 3.55 (1.04, 6.07) | 0.006 | 93.0 | < 0.001 | |
| Brewed green tea | 3 | 4.48 (1.43, 7.52) | 0.004 | 84.7 | 0.001 | |
| Location of study | < 0.001 | |||||
| Asia | 4 | 7.75 (0.41, 15.11) | 0.039 | 94.8 | < 0.001 | |
| Non-Asia | 6 | 2.21 (0.27, 4.15) | 0.025 | 91.5 | < 0.001 | |
| Gender | < 0.001 | |||||
| Both | 8 | 2.21 (0.41, 4.02) | 0.016 | 91.4 | < 0.001 | |
| Male | – | – | – | – | – | |
| Female | 2 | 13.72 (10.36, 17.40) | < 0.001 | 0.0 | 0.809 | |
| SOD | ||||||
| Overall | 6 | 17.21 (3.24, 31.19) | 0.016 | 92.1 | < 0.001 | – |
| BMI (kg/m2) | 0.500 | |||||
| <30 | 2 | 23.14 (−23.86, 70.15) | 0.335 | 96.4 | < 0.001 | |
| ≥30 | 2 | 98.54 (−96.67, 293.75) | 0.322 | 97.0 | < 0.001 | |
| Dosage (mg/day) | 0.015 | |||||
| <500 | 2 | 0.001 (−0.37, 0.38) | 0.997 | 0.0 | 0.693 | |
| ≥500 | 4 | 47.06 (0.34, 93.78) | 0.048 | 94.8 | < 0.001 | |
| Duration (weeks) | < 0.001 | |||||
| ≤8 | 1 | 48.00 (30.26, 65.73) | < 0.001 | – | – | |
| >8 | 5 | 6.56 (−5.95, 19.09) | 0.304 | 88.6 | < 0.001 | |
| Health status | 0.499 | |||||
| Healthy | 3 | 68.17 (10.11, 126.24) | 0.021 | 96.8 | < 0.001 | |
| Unhealthy | 3 | 1.71 (−3.16, 6.59) | 0.490 | 0.0 | 0.673 | |
| Type of intervention | 0.499 | |||||
| Green tea extract | 3 | 1.71 (−3.16, 6.59) | 0.490 | 0.0 | 0.673 | |
| Brewed green tea | 3 | 68.17 (10.11, 126.24) | 0.021 | 96.8 | < 0.001 | |
| Location of study | < 0.001 | |||||
| Asia | 3 | 8.83 (−5.19, 22.87) | 0.217 | 94.2 | < 0.001 | |
| Non-Asia | 3 | 16.84 (−24.45, 58.13) | 0.424 | 78.8 | 0.009 | |
| Gender | – | |||||
| Both | 6 | 17.21 (3.24, 31.19) | 0.016 | 92.1 | < 0.001 | |
| Male | – | – | – | – | – | |
| Female | – | – | – | – | – | |
Abbreviation: WMD: Weighted Mean Difference, CI: Confidence Interval, CRP: C-reactive protein, IL-6: Interleukin-6, TNF-a: Tumour Necrosis Factor Alpha, TAC: Total Antioxidant Capacity, MDA: Malondialdehyde, GPX: Glutathione Peroxidase, SOD: Superoxide Dismutase, BMI; Body Mass Index.
aRefers to the mean (95% CI).
bInconsistency, percentage of variation across studies due to heterogeneity.
cObtained from the Q-test.
dObtained from the fixed-effects model.
The beneficial effect of the green tea on TAC was not observed in some subgroups (male participants, non-Asian countries, duration greater than 8 weeks, and supplementation dosage less than 500 mg/day). In addition, we observed that green tea intake could not decrease MDA levels in studies enrolling participants with BMIs equal to or more than 30 kg/m2, participants who had a daily intake of green tea less than 500 mg, studies carried out in non-Asian countries, studies with a duration more than 8 weeks, and studies that included only male participants. Moreover, the beneficial impact of the supplementation on GPX was not found in studies that included unhealthy individuals, lasted more than 8 weeks, administered a daily dose of less than 500 mg, and had participants with a BMIs equal to or more than 30 kg/m2. Furthermore, green tea consumption increased SOD in those studies performed on healthy individuals, studies that administered brewed green tea to the subjects, studies with a period of intervention equal to or less than 8 weeks, and studies with a supplementation dosage equal to or more than 500 mg/day. Subgroup analysis with regard to IL-1β was rendered impossible due to lack of sufficient arms in each subgroup.
Sensitivity analysis and publication bias
The sensitivity analyses indicated that the elimination of none of the studies could alter the overall effect sizes of CRP (95% CI: -0.22, 0.27), TNF-α (95% CI: -0.55, 0.44), IL-1β (95% CI: −0.22, −0.02), TAC (95% CI: 0.04, 0.14), MDA (95% CI: −0.77, −0.09), and GPX (95% CI: 1.09, 7.46). However, the results showed that the overall effect size depended on some studies with respect to IL-6(35) and SOD(34,41,43,68); such that by removing the studies, the non-significant effect for IL-6 converted to a decreasing statistically significant effect, and the significant impact of SOD became non-significant.
We utilised Begg’s weighted regression test and examined funnel plots to detect publication bias in the papers that were included. Based on visual assessment, the funnel plots showed asymmetries regarding all the outcomes of interest (Supplementary Fig. 1). However, the findings of Begg’s test showed no publication bias for TAC (p = 0.692), MDA (p = 0.956), IL-6 (p = 0.945), or SOD (p = 0.462). The Begg’s test showed that there was publication bias for both CRP (p = 0.021) and GPX (p = 0.032). To further investigate the results, we used the trim-and-fill method. The overall effect size for CRP changed from not significant to significant (WMD: −0.22 mg/l; 95% CI: −0.38, −0.07), but there was no significant change for GPX after the trim-and-fill analysis. The Begg’s test was not conducted for TNF-α and IL-1β due to the lack of robustness of the Begg’s test in studies with less than 10 effect sizes.
Non-linear dose-response between duration and dose of green tea supplementation and the outcomes of interest
Non-linear dose-response analysis showed that supplementation dosage had no association with the outcomes of interest, except for IL-1β (P-non-linearity = 0.016) (Fig. 4). Moreover, we did not find any non-linear associations between the duration of the studies and the outcomes of interest (Fig. 5).
Fig. 4.
Dose-response relations between green tea dosage (mg/day) and absolute (unstandardised) mean differences of the outcomes in non-linear fashion.
Fig. 5.
Dose-response relationships between duration of intervention (week) and absolute (unstandardised) mean differences of the outcomes in non-linear fashion.
Meta-regression analysis
We performed a meta-regression analysis to assess the linear effect of dose and duration on the outcomes of interest. The results showed that the effect of green tea intake was not related to the dose of supplementation. In addition, the impact of green tea consumption on the outcomes of interest was independent of study duration, except for TAC (coefficient = − 0.004, p = 0.019).
Grading of evidence
At the outcome level, the GRADE guidelines were utilised to evaluate the quality of evidence across all included studies. As presented in Supplementary Table 2, the evidence quality was moderate for IL-1β, low for TAC and TNF-a, and very low for CRP, IL-6, MDA, GPX, and SOD.
Discussion
The findings of the present investigation can be summed up in the following statements: (1) supplementation with green tea seems to be unable to ameliorate pro-inflammatory indicators/agents of CRP, IL-6, and TNF-α; contrary to IL-1β which appears to be improved by the intervention; (2) supplementation with green tea improves measurements/indices of oxidative stress, including TAC, MDA, GPX, and SOD; (3) analyses of the subgroups show factors such as dosage, duration, and vectors of intervention; health status and biological gender of participants; and the location of the study all might contribute to the heterogeneity of the findings; and (4) linear regression and the examination of possible non-linear associations revealed that study duration influences the impact of green tea supplementation on TAC and that there is a non-linear association between the dosage of intervention and changes in IL-1β.
The impact of green tea on indicators of oxidative balance, owing to its abundance of antioxidant agents, could be considered self-explanatory. As aforementioned, green tea contains multiple compounds with antioxidant properties, the most important of which are catechins, or tea flavonoids; these include (−)-epigallocatechin (EGC), (−)-epicatechin (EC), (−)-epigallocatechin-3-gallate (EGCG), and (−)-epicatechin-3-gallate (ECG).(16) In fact, the impact of Camellia sinensis on scavenging free radicals and enhancing the performance of antioxidant enzymes (such as GPX and SOD) have been previously examined.(69) The tea flavonoids are hypothesised to also suppress oxidative stress through induction of several pathways, such as protein kinase Cδ/acidic sphingomyelinase (PKCδ/ASM) and protein kinase B/endothelial nitric oxide synthase (Akt/eNOS).(70) Furthermore, down-regulation of other enzymes, such as matrix metalloproteinase-12 (MMP-12), extracellular signal-regulated kinase, nuclear factor-kappa B (NF-κB), phosphoinositide-3 kinase (PI3K), and haem oxygenase-1 (OH-1), have been hypothesised as possible mechanisms through which green tea polyphenols might equilibrise the production of ROSs and their eradication.(71)
The findings of the present study support the potent antioxidant influences of acute consumption of green tea. Nonetheless, there are some notes that need to be accounted. For instance, the effect of intervention, on direct measurements of indices of antioxidant balance (i.e., TAC, MDA, GPX, and SOD), seem to be diluted when the duration of intake exceeds eight weeks, which undermines the effectiveness of such a dietary intervention in the long-term. However, these observations are in sharp contrast to what Rojano-Ortega(72) concluded in a systematic review of its impact on exercise-induced oxidative stress. The author suggests that ‘regular’ intake of green tea, rather than an acute portion, might be more relevant in reducing the exercise-induced oxidative stress. Nevertheless, in a clinical setting which dictates a comprehensive outlook regarding the preventive potency of green tea (in the context of various oxidative-related pathologies, such as cancer), the findings of the present study seem more pertinent. In spite of that, comprehensive reviews of observational studies still suggest that green tea consumption might be associated with lower risk of diseases with long periods of latency, such as cancer.(73) With respect to this discrepancy, we suggest that mechanisms, other than that of long-term modification of detoxification enzymes, should be further investigated.
With respect to inflammatory markers (including IL-6, TNF-α, and CRP), our analyses suggest no beneficial impact of green tea supplementation. The only marker which seemed to be affected by the intervention was IL-1β. Not too much merit can, and should be given to the latter, since it is backed by merely two studies; further investigations are needed to clarify whether the observed discrepancy is meaningful or not. Nonetheless, there seems to be a sharp disparity between the findings of the present study and what the existing literature demonstrates, since most studies suggest that consumption/supplementation with green tea ameliorates the inflammatory flare caused by various conditions. For instance, in a review of clinical and epidemiological studies, Ohisi et al(74) concluded that green tea/EGCG consumption is capable of improving the inflammatory balance. They even proposed that green tea catechins do so by their ROS-scavenging properties, repressing the expression of NF-κB which is responsible for production of various pro-inflammatory cytokines/enzymes, such as IL-1β, TNF-α, MMP-9, and cyclooxygenase-2 (COX-2) (which mediates the production of some pro-inflammatory eicosanoids). Likewise, Oz(75) investigated the role of green tea/its polyphenols in chronic inflammatory diseases. The author suggested that green tea polyphenols can be indeed regarded as potential therapeutic agents to treat diseases with chronic inflammation at their epicentre, such as inflammatory bowel diseases, gastrointestinal malignancies, and neurodegenerative disorders. Nonetheless, two important interwoven deductions can be made regarding the findings of the present study: (1) even though supplementation with green tea is potent in modifying the oxidative environment, this does not necessarily conclude in a reduced inflammation (in spite of most of the proposed mechanisms); and (2) this might be due to the fact that, as observed in our subgroup analyses, the impact of green tea supplementation seems to be disputable in the long-term; thus, partially explaining the lack of effectiveness in altering the inflammatory equilibrium which evidently must go through delayed processes of signalling pathways and transcription.
The present systematic review is unprecedented in its comprehensiveness and findings which contravene the previous presumptions. However, these findings must be interpreted in light of some limitations. Firstly, significant heterogeneities were observed with regard to most of the, accepted only for the sake of inclusion of more studies. We attempted to investigate these heterogeneities via extensive subgroup analyses. Secondly, the assessment of the evidence showed us that the quality of the included studies with regard to most of the outcomes was low and very low. Therefore, it can be recommended that the following investigations be conducted whenever fresh/high-quality evidence emerges on the same issue.
Conclusion
Our findings suggest that supplementation with green tea can ameliorate indices of oxidative stress. However, there is no solid evidence that inflammatory markers are influenced by green tea consumption/supplementation. Therefore, supplementation should only be aimed at reduced oxidative stress. The answer to whether the intervention would lead to a long-term modification of inflammatory status warrants further uniform investigations.
Supporting information
Dehzad et al. supplementary material
Dehzad et al. supplementary material
Dehzad et al. supplementary material
Acknowledgements
Not applicable.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/jns.2025.13
Author contributions
The authors’ contribution was as follows: MA contributed to the design and statistical analysis. HG and MJD conducted the systematic search, screening and data extraction. MA, MM, MN, and HG interpreted data and wrote the manuscript. All authors read and approved the final manuscript.
Financial support
None.
Competing interests
The authors declared no conflicts of interest.
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