Does ginger supplementation lower blood pressure? A systematic review and meta-analysis of clinical trials.
Hossein HasaniArman ArabAmir HadiMakan PourmasoumiAbed GhavamiMaryam MiraghajaniPublished in: Phytotherapy research : PTR (2019)
The aim of the present systematic review and meta-analysis was to determine the efficacy of ginger supplementation on blood pressure (BP). PubMed, Scopus, ISI Web of Science, Cochrane Library, and Google Scholar were comprehensively searched until September 2018. Human clinical trials, which reported the effect of ginger supplementation on aortic and/or brachial BP, were included. Mean differences were pooled using a random effects model. Standard methods were used for assessment of heterogeneity, sensitivity analysis, and publication bias. Total of six randomized clinical trials (345 participants) were included in the meta-analysis. Pooled analysis suggested that ginger supplementation can reduced systolic BP (MD: -6.36 mmHg, 95% confidence interval [-11.27, -1.46]; I2 = 89.8%; P = .011) and diastolic BP (MD: -2.12 mmHg, 95% confidence interval [-3.92, -0.31]; I2 = 73.4%; P = .002). When studies were categorized based on participants' mean age, ginger dosage and duration of intervention, systolic BP and diastolic BP were significantly decreased only in the subset of studies with mean age ≤ 50 years, follow-up duration of ≤8 weeks and ginger doses ≥3 g/d. Our findings revealed that ginger supplementation has favorable effects on BP. Nonetheless, further studies are warranted before definitive conclusions may be reached.
Keyphrases
- blood pressure
- left ventricular
- clinical trial
- hypertensive patients
- systematic review
- case control
- heart rate
- randomized controlled trial
- heart failure
- endothelial cells
- single cell
- public health
- pulmonary artery
- molecular dynamics
- atrial fibrillation
- ejection fraction
- adipose tissue
- blood glucose
- phase ii
- coronary artery
- pulmonary arterial hypertension
- skeletal muscle
- meta analyses
- study protocol
- data analysis
- neural network