| Literature DB >> 33172016 |
Karolina Jakubczyk1, Aleksandra Drużga1, Janda Katarzyna1, Karolina Skonieczna-Żydecka1.
Abstract
BACKGROUND: Antioxidant potential is defined as the ability to neutralize oxygen free radicals that are generated in excess due to environmental influences. The body's defense mechanisms often require support in preventing the effects of oxidative stress. The literature data suggest that curcumin has antioxidant activity that can significantly reduce oxidative stress levels. The aim was to assess the impact of curcumin on oxidative stress markers.Entities:
Keywords: Indian saffron; antioxidant; curcumin; meta-analysis; oxidative stress; polyphenol; turmeric
Year: 2020 PMID: 33172016 PMCID: PMC7694612 DOI: 10.3390/antiox9111092
Source DB: PubMed Journal: Antioxidants (Basel) ISSN: 2076-3921
Figure 1Study flow chart.
Study characteristics.
| Study Description | Intervention | Persons Analyzed | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Reference/Year/Country/Sponsorship | Blinding/Crossover (Y/N)/Multi-Arm > 2 | Focus on | ROB | The Form of Supplement | Curcumin Dose/(mg/day) | Duration of Administration (days)/Comparator | N Total Randomized/Analyzed | Age Years (Mean ± SD) | Males ( |
| Saraf-Bank/2019/Iran/Academia | SB/N/N | MDA, TCA | 5 | Pills | 500 | 70/placebo | 60/60 | 16.001 ± 1.64 | 0/0 |
| Alizadeh/2017/Iran/Academia | DB/N/N | MDA, TCA | 5 | Nanomicelle | 80 | 70/placebo | 60/56 | 30.27 ± 4.00 | 60/100 |
| Ghazimoradi/2017/Iran/Academia | DB/N/N | PAB | 4 | Pills | 1000 | 42/placebo | 120/109 | 38.05 ± 2.89 | 19/17.43 |
| Nasseri/2017/Iran/Academia | DB/N/N | MDA, TAC, Catalase | 2 | Pills | 1000 | 84/placebo | 68/61 | 26.80 ± 6.64 | 26/42.62 |
DB—double blind; SB—single blind; N—no; Y—yes; NA—not applicable; ROB—risk of bias; SD—standard deviation; MDA—malondialdehyde; TAC—total antioxidant capacity; PAB—pro-oxidant–antioxidant balance.
Figure 2An effect size standardized mean difference, for MDA at endpoint in persons taking curcumin vs. controls (endpoint data). Q = 53.330, df(Q) = 2, p = 0.000, I-squared = 96.250.
Figure 3An effect size standardized mean difference, for TAC at endpoint in persons taking curcumin vs. controls (endpoint data). Q = 90.804, df(Q) = 2, p = 0.000, I-squared = 97.797.
Risk of bias (ROB).
| No. | Reference/Year/Country/Sponsorship | Random Sequence Generation (Selection Bias) | Allocation Concealment (Selection Bias) | Blinding of Participants and Personnel (Performance Bias) | Blinding of Outcome Assessment (Detection Bias) | Incomplete Outcome Data Addressed (Attrition Bias) | Selective Reporting (Reporting Bias) | Other Bias | No. of Low ROB Assessments |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Saraf- Bank/2019/Iran/Academia | L | L | L | ? | L | L | ? | 5 |
| 2 | Alizadeh/2017/Iran/Academia | L | L | L | ? | L | L | ? | 5 |
| 3 | Ghazimoradi/2017/Iran/Academia | L | L | ? | ? | L | L | ? | 4 |
| 4 | Nasseri/2017/Iran/Academia | H | H | ? | ? | L | L | ? | 2 |
L—low risk of bias; H—high risk of bias; ?—unclear risk of bias.
Figure 4Funnel plot for endpoint MDA (SMD) in present meta-analysis.
Figure 5Funnel plot for endpoint TCA (SMD) in present meta-analysis.