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Effects of EPA and DHA on blood pressure and inflammatory factors: a meta-analysis of randomized controlled trials

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Critical Reviews in Food Science and Nutrition
DOI:
10.1080/10408398.2018.1492901
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July, 2018
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Critical Reviews in Food Science and Nutrition

ISSN: 1040-8398 (Print) 1549-7852 (Online) Journal homepage: http://www.tandfonline.com/loi/bfsn20

Effects of EPA and DHA on blood pressure
and inflammatory factors: a meta-analysis of
randomized controlled trials
Xiao-fei Guo, Ke-lei Li, Jiao-mei Li & Duo Li
To cite this article: Xiao-fei Guo, Ke-lei Li, Jiao-mei Li & Duo Li (2018): Effects of EPA and DHA
on blood pressure and inflammatory factors: a meta-analysis of randomized controlled trials, Critical
Reviews in Food Science and Nutrition, DOI: 10.1080/10408398.2018.1492901
To link to this article: https://doi.org/10.1080/10408398.2018.1492901

Accepted author version posted online: 11
Jul 2018.

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Effects of EPA and DHA on blood pressure and inflammatory factors: a meta-analysis
of randomized controlled trials
Xiao-fei Guo1,2, Ke-lei Li1, Jiao-mei Li2 and Duo Li1,2
1

Institute of Nutrition and Health, Qingdao University, Qingdao, China

2

Department of Food Science and Nutrition, Zhejiang University, Hangzhou, China

Author affiliations:
Institute of Nutrition and Health, Qingdao University, Qingdao, China

2

Department of Food Science and Nutrition, Zhejiang University, Hangzhou, China

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1

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(X-F G1,2, K-L L1, J-M L2 and D L1,2)

Duo Li

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308 Ningxia Road, Qingdao 266071, China,

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E-mail: duoli@qdu.edu.cn

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Phone: 86-532-82991018
Fax: 86-532-82991018

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Institute of Nutrition & Health, Qingdao University,

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Corresponding author:

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Sources of support: This work is supported by the National Basic Research Program
of China (973 Program: 2015CB553604); by National Natural Science Foundation of

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China (NSFC: 81773433); and by the Ph.D. Programs Foundation of Ministry of
Education of China (20120101110107). The funders have no role in study design, data
collection and analysis; , decision to publish, or preparation of the manuscript.

Running title: Effects of EPA and DHA on blood pressure and inflammatory factors

Abstract:
The present study aimed to clarify whether eicosapentaenoic acid (EPA) and
docosahexaenoic acid (DHA) have differential effects on blood pressure and
inflammatory mediators. A systematic literature search was conducted in PubMed and
Scopus updated to Apr. 2018. The mean changes in risk factors of chronic diseases
were calculated as weighted mean difference (WMD) by using a random-effects
model. Twenty randomized controlled trials (RCTs) were included. The summary
estimate showed that EPA intervention significantly reduced systolic blood pressure

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(SBP) (-2.6 mmHg; 95%confident interval (CI): -4.6, -0.5 mmHg), especially in
subjects with dyslipidemia (-3.8 mmHg; 95%CI: -6.7, -0.8 mmHg). The pooled effect

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indicated that supplemental DHA exerted a significant reduction in diastolic blood

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pressure (DBP) in subjects with dyslipidemia (-3.1 mmHg; 95%CI: -5.9, -0.2 mmHg).
Both EPA (-0.56 mg/L; 95%CI: -1.13, 0.00) and DHA (-0.5 mg/L; 95%CI: -1.0, -0.03)

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significantly reduced the concentrations of C-reactive protein (CRP), respectively,
especially in subjects with dyslipidemia and higher baseline CRP concentrations.

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Given that limited trials have focused on EPA or DHA intervention on concentrations
of interleukin (IL)-6 and tumor necrosis factor (TNF)-α, further RCTs should be

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explored on these inflammatory factors. The present meta-analysis provides
substantial evidence that EPA and DHA have independent (blood pressure) and shared

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(CRP concentration) effects on risk factors of chronic diseases, and high-quality RCTs

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findings.

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with multi-center and large simple-size should be performed to confirm the present

Keywords: Eicosapentaenoic acid; Docosahexaenoic acid; Randomized controlled
trial; Blood pressure; Inflammatory factors

Introduction
Elevated blood pressure is the leading global risk factor for cardiovascular diseases
(CVD) and chronic kidney disease, affecting more than one billion individuals and
causing an estimated 9·4 million deaths every year (Danaei, et al., 2014; World Health
Organization., 2013). Accumulating evidence suggests that specific recommendations
of nature-origin nutrients have shown to reduce blood pressure, which then inhibit the
risk of hypertension and CVD (Campbell, Dickinson, Critchley, Ford, & Bradburn,
2013; Guo, Li, Tang, & Li, 2017; Miller, Mary, & Alexander, 2014). Inflammation is

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part of normal host to infection or injury in the body, and these immunologic
processes must be ordered and controlled. Once these responses present in a

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disordered and inappropriate manner, inflammatory response can occur and are

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characterized by overexpression of inflammatory mediators, including tumor necrosis
factor (TNF)-α, interleukin (IL)-1β, and IL-6 (Calder, 2006). Convincing evidence has

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suggested that chronic low-grade inflammation plays a pivotal role in the initiation,
propagation and development of non-communicable diseases, including obesity,

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allergy, asthma, diabetes mellitus, CVD and cancers (Baker, Hayden, & Ghosh, 2011).
C-reactive protein (CRP) is a kind of acute phase reactant protein, which plays a

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pivotal role in innate immune response (Du, 2000). It is mainly synthesized and
secreted by hepatocytes and smooth muscle response, and participated in multiple

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aspects of atherogenesis and thrombogenesis (Calabró, Willerson, & Yeh, 2003).

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Sufficient evidence supported that elevated CRP is an independent predictor of risk
for future diabetes mellitus and CVD events (Freeman, et al., 2002; Paul M. Ridker,

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Buring, Shih, Matias, & Hennekens, 1998).

There is abundant evidence supporting the beneficial effects of n-3 polyunsaturated
fatty acids (PUFA) on blood pressure and inflammatory factors (Allaire, et al., 2016;
Campbell, et al., 2013; Li, Huang, Zheng, Wu, & Li, 2014; Miller, et al., 2014). Two
principal n-3 PUFA of marine-origin have been separated, identified and characterized,
namely eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). A large
proportion of scientific research has reported the beneficial effects of fish oil (a

mixture of EPA and DHA) on blood pressure and inflammatory factors, but does not
discriminate their independent effects. The isolated roles of each have been received
limited study due to the greater availability of combined EPA and DHA products than
purified EPA and DHA. With the development of separation and purification
technologies, several randomized controlled trials (RCTs) have explored the
biological effects of EPA and DHA administrated as monotherapy (Allaire, et al.,
2016; Azizi-Soleiman, et al., 2013; Kohashi, et al., 2014; Sagara, et al., 2011; Tani,
Nagao, Yagi, Atsumi, & Hirayama, 2017; Tsunoda, et al., 2015); however, their effects

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on blood pressure and inflammatory markers are controversial. Therefore, this
meta-analysis aimed to address the question of whether EPA and DHA monotherapy

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have differential effects on blood pressure (systolic blood pressure (SBP) and diastolic

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blood pressure (DBP)) and inflammatory factors (CRP, IL-6 and TNF-α).

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Methods

The present study was performed on the basis of the recommendations of the

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Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)

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statement (Moher, Liberati, Tetzlaff, & Altman, 2009).

Literature search

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A systematic literature search was conducted up to Apr. 2018, using the databases of

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PubMed and Scopus. Eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA)
was paired with blood pressure (BP), systolic blood pressure (SBP) and diastolic

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blood pressure (DBP), C-reactive protein (CRP), interleukin 6 (IL-6), tumor necrosis
factor alpha (TNF-α), interleukin or inflammation as search terms. Besides, the
reference lists of original studies, reviews and meta-analyses were also scrutinized by
using Google and Baidu Scholar.

Inclusion criteria
An RCT that was included must meet the following criteria: (1) RCTs of either
cross-over or parallel design; (2) using EPA or DHA as only intervention; (3) The

RCTs provided available data to calculate mean differences between baseline and
endpoint regarding SBP, DBP, CRP, TNF-α or IL-6.

Data extraction and quality assessment
Data extraction was independently conducted by two investigators, and any
controversy was solved via discussion reaching a consensus. The basic information of
identified articles was extracted, including surname of first author, publication year,
country, gender, sample-size, age, period of intervention, and types of intervention.

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For the included studies, the means and standard deviations (SDs) of blood pressure
and inflammatory factors at baseline and endpoint in both the control and intervention

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groups were extracted, respectively. The final outcome was extracted if the outcomes

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of the trial had provided multiple times at different stages. If the SD was not provided
in the trial, we calculated it from interquartile or standard error of the mean (SEM) on

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the basis of the equation listed in the Cochrane handbook (Higgins, 2011). The Jadad
score criteria, which included five items, were used for quality assessment, namely

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random sequence generation, randomization, allocation concealment, double blinding
and reason of dropout (Moher, et al., 1998). The trial scored one point for each area

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Statistical analysis

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reported, and a trial with Jadad score ≥ 4 was classified as high quality.

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Using random-effects model developed by DerSimonian and Laird, the summary
estimate was pooled as weighted mean difference (WMD) (DerSimonian & Laird,

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1986). Heterogeneity between the studies was assessed by I2 statics, with values of
25%, 50% and 75% regarded as low, moderate and high degree of heterogeneity,
respectively (Higgins, 2011). The fixed-effects model was used for data synthesis
when there was no obvious heterogeneity. To identify the source of heterogeneity,
subgroup and meta-regression analyses were conducted to focus on the information of
the trials: region, mean age, dose of EPA or DHA supplementation, study duration,
and baseline SBP, DBP and CRP levels. To evaluate whether the overall effect was
steady, sensitivity analysis was performed with deleting one trail at a time, and the

effect size was re-calculated. Publication bias was conducted by using Begg’s rank
correlation test (Significant level at P < 0.1) (Egger, Davey Smith, Schneider, &
Minder, 1997). The trim-and-fill method was conducted to correct the potential
publication bias, if the Begg’s test was significant. Statistical analysis was conducted
with STATA 11.0 for windows (Stata CORP, College station, TX). A P value of ≤ 0.05
was regarded as statistically significant.

Results

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Study selection
The process of literature search is presented in Figure 1. After deleting 392 duplicates,

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2782 unique articles were retrieved from PubMed, Scopus and hand searching. Of

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these, 2734 articles were removed by screening titles and abstracts, and 48 articles
were left for full-text examination. After checking full-text, 28 articles were excluded

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because they did not meet the inclusion criteria (e.g., study design, unpurified EPA or
DHA, multi-component intervention or without providing sufficient data for

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Study characteristics

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quantitative analysis).

A total of 20 RCTs were included (Table 1). Of these, five studies were performed in

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North America (Allaire, et al., 2016; Kelley, Siegel, Fedor, Adkins, & Mackey, 2009;

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Kelley, Siegel, Vemuri, & Mackey, 2007; Stark & Holub, 2004; Tsunoda, et al., 2015),
six in Asia (Azizi-Soleiman, et al., 2013; Kohashi, et al., 2014; Satoh, et al., 2009;

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Satoh, et al., 2007; Shimizu, et al., 1995; Tomiyama, et al., 2005), six in Europe
(Grimsgaard, Bonaa, Hansen, & Myhre, 1998; Nestel, et al., 2002; Sagara, et al., 2011;
Sanders, Gleason, Griffin, & Miller, 2006; Tani, et al., 2017; Theobald, et al., 2007),
and three in Oceania (Mori, Bao, Burke, Puddey, & Beilin, 1999; Mori, et al., 2003;
Woodman, et al., 2002). Four studies were performed in healthy subjects (Grimsgaard,
et al., 1998; Sanders, et al., 2006; Stark & Holub, 2004; Theobald, et al., 2007;
Tsunoda, et al., 2015), while the rest of the studies were conducted in subjects with
dyslipidemia (Allaire, et al., 2016; Kelley, et al., 2009; Kelley, et al., 2007; Kohashi,

et al., 2014; Mori, et al., 1999; Nestel, et al., 2002; Sagara, et al., 2011; Satoh, et al.,
2009; Satoh, et al., 2007; Tani, et al., 2017; Tomiyama, et al., 2005) or diabetes
mellitus (Azizi-Soleiman, et al., 2013; Mori, et al., 2003; Shimizu, et al., 1995;
Woodman, et al., 2002).

Effects of EPA/DHA supplementation on blood pressure and inflammatory
factors
Eight trials reported EPA supplementation on SBP (Grimsgaard, et al., 1998; Kohashi,

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et al., 2014; Mori, et al., 1999; Nestel, et al., 2002; Satoh, et al., 2009; Shimizu, et al.,
1995; Tomiyama, et al., 2005; Woodman, et al., 2002), and the pooled effect showed a

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significant reduction in SBP (-2.6 mmHg; 95% CI:-4.6, -0.5 mmHg; I2 = 0.0%, P =

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0.814), especially in subjects with dyslipidemia (-3.8 mmHg; 95%CI: -6.7, -0.8
mmHg) (Figure 2). Seven studies provided available data to investigate EPA

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supplementation on DBP (Grimsgaard, et al., 1998; Mori, et al., 1999; Nestel, et al.,
2002; Satoh, et al., 2009; Shimizu, et al., 1995; Tomiyama, et al., 2005; Woodman, et

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al., 2002), and the summary effect was not significant (-1.1 mmHg; 95%CI: -2.8, 0.6
mmHg) (Figure 2). Nine trials reported DHA supplementation on SBP (Grimsgaard,

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et al., 1998; Kelley, et al., 2007; Mori, et al., 1999; Nestel, et al., 2002; Sagara, et al.,
2011; Sanders, et al., 2006; Stark & Holub, 2004; Theobald, et al., 2007; Woodman, et

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al., 2002), and the summary estimate was not significant (-1.3 mmHg; 95%CI: -3.2,

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0.7 mmHg) (Figure 3). Eight trials reported DHA supplementation on DBP (Kelley, et
al., 2007; Mori, et al., 1999; Nestel, et al., 2002; Sagara, et al., 2011; Sanders, et al.,

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2006; Stark & Holub, 2004; Theobald, et al., 2007; Woodman, et al., 2002), and the
pooled effect was not significant (-1.0 mmHg; 95%CI: -2.6, 0.6) (Figure 3). However,
the pooled effect was significant in subjects with dyslipidemia (-3.1 mmHg; 95%CI:
-5.9, -0.2 mmHg), with no significant between heterogeneity (I2 = 0.0%, P = 0.730)
(Figure 3). Six trials reported EPA supplementation on CRP concentration (Allaire, et
al., 2016; Azizi-Soleiman, et al., 2013; Mori, et al., 2003; Satoh, et al., 2009; Satoh, et
al., 2007; Tani, et al., 2017), and the pooled effect showed a borderline reduction in
CRP concentrations (-0.56 mg/L; 95%CI: -1.13, 0.00 mg/L), with a significant

between study heterogeneity (I2 = 89.3%, P < 0.001) (Figure 4). The mean change in
CRP concentration was pooled in seven trials (Allaire, et al., 2016; Azizi-Soleiman, et
al., 2013; Kelley, et al., 2009; Mori, et al., 2003; Sanders, et al., 2006; Stark & Holub,
2004; Tsunoda, et al., 2015), and DHA supplementation exerted a significant
reduction in CRP concentration (-0.5 mg/L; 95%CI: -1.0, -0.03 mg/L), with no
significant between study heterogeneity (I2 = 0.0%, P = 0.734) (Figure 4). Two trials
reported EPA supplementation on IL-6 concentration (Allaire, et al., 2016; Mori, et al.,
2003), and the summary estimate was not significant (-17.38 ng/L; 95%CI: -51.86,

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17.10 ng/L) (Supplementary Figure 1). Three trials reported EPA supplementation on

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TNF-α concentration (Allaire, et al., 2016; Kohashi, et al., 2014; Mori, et al., 2003),

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and the pooled effect was not significant (-1.93 ng/L; 95%CI: -5.52, 1.67 ng/L)

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(Supplementary Figure 2). Four trials reported DHA supplementation on IL-6
concentration (Allaire, et al., 2016; Kelley, et al., 2009; Mori, et al., 2003; Theobald,

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et al., 2007), and DHA supplementation did not show a significant reduction in IL-6
concentration (-0.28 ng/L; 95%CI: -1.02, 0.46 ng/L) (Supplementary Figure 3). Two

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trials reported DHA supplementation on TNF-α concentration (Allaire, et al., 2016;
Mori, et al., 2003), and the pooled estimated mean difference was -6.44 ng/L (95%CI;

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-11.76, -1.12 ng/L; I2 = 0.0%, P = 0.763) (Supplementary Figure 4).

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Subgroup and meta-regression analyses

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The pooled effect showed that supplementation with EPA significantly reduced SBP
(-4.15 mmHg; 95%CI:-7.31, -0.98 mmHg) in subjects from Asia (Table 2).

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Supplemental EPA showed a significant reduction in SBP in subjects whose mean age
was ≥ 60 years (-3.50 mmHg; 95%CI: -6.59, -0.40 mmHg), but not in subjects whose
mean age was < 60 years. In addition, supplemental EPA significantly reduced SBP in
subjects whose baseline SBP was ≥ 130 mmHg (-5.30 mmHg; 95%CI: -10.50, -0.09
mmHg). The studies stratified by health status indicated that the pooled effect showed
a significant reduction in SBP in subjects with dyslipidemia (-3.79 mmHg; 95%CI:
-6.74, -0.83 mmHg). Besides, the pooled estimated effects significantly reduced SBP
in subjects with EPA supplementation < 2 g/day (-4.15 mmHg; 95%CI: -7.31, -0.98

mmHg) and the duration of EPA supplementation ≥ 3 months (-4.15 mmHg; 95%CI:
-7.31,

-0.98

mmHg),

respectively.

Regarding

CRP

concentration,

EPA

supplementation exerted a marginal reduction in CRP concentration in subjects from
Asia (-0.15 ng/L; 95%CI: -0.30, 0.00 ng/L). Besides, supplemental EPA significantly
reduced CRP concentration in subjects with dyslipidemia (-0.65 mg/L; 95%CI: -1.29,
-0.02 mg/L). Additionally, EPA supplementation exerted a significant reduction in
CRP concentration in subjects whose baseline CRP concentration was ≥ 2 mg/L (-1.77
mg/L; 95%CI: -2.32, -1.22 mg/L). Supplemental EPA indicated that significant

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differences were discerned on CRP concentrations of the trials stratified by dose (P for
meta-regression = 0.017) and duration (P for meta-regression = 0.017) with

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meta-regression analysis, respectively (Table 2).

The pooled estimated effect showed that DHA supplementation significantly reduced

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DBP in subjects with dyslipidemia (-3.05 mmHg; 95%CI: -5.94, -0.16 mmHg) (Table
3). Supplemental DHA significantly reduced CRP concentration in subjects form

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North America (-0.57 ng/L; 95%CI: -1.11, -0.04), and exerted a significant reduction
in CRP concentration in subjects whose mean age was ≥ 50 years (-0.60 mg/L; 95%CI:

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-1.11. -0.08 mg/L), but not in subjects whose mean age was < 50 years. The trials
stratified by health status indicated that DHA supplementation significantly reduced

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the CRP concentration in subjects with dyslipidemia (-0.74 mg/L; 95%CI: -1.31, -0.18

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mg/L), but not in healthy subjects. Besides, the pooled effect showed a significant
reduction in CRP concentration in subjects with DHA supplementation ≥ 2 g per day

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(-0.67 mg/L; 95%CI: -1.21, -0.12 mg/L). Additionally, the pooled effect indicated that
supplemental DHA imposed a significant reduction in CRP concentration in subjects
whose baseline CRP concentration was ≥ 3 mg/L (-0.74 mg/L; 95%CI: -1.35, -0.14
mg/L) (Table 3).

Quality assessment and publication bias
According Jadad score criteria, four trials were regarded as high-quality studies
(Allaire, et al., 2016; Grimsgaard, et al., 1998; Nestel, et al., 2002; Sanders, et al.,

2006) (Table 1). The remaining 14 trials were classified as low-quality studies,
because they did not report information, including randomization, generation of
random sequence, binding, allocation concealment or reasons for dropout
(Azizi-Soleiman, et al., 2013; Kelley, et al., 2009; Kelley, et al., 2007; Kohashi, et al.,
2014; Mori, et al., 1999; Mori, et al., 2003; Sagara, et al., 2011; Satoh, et al., 2009;
Satoh, et al., 2007; Shimizu, et al., 1995; Stark & Holub, 2004; Tani, et al., 2017;
Theobald, et al., 2007; Tomiyama, et al., 2005; Tsunoda, et al., 2015; Woodman, et al.,
2002). Begg's rank correlation test indicated that no significant publication bias was

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found with EPA supplementation on SBP (P = 0.386), DBP (P = 0.764), CRP (P =

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0.851), TNF-α (P = 0.117) and IL-6 (P = 0.317), and no significant publication bias

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was discerned with DHA supplementation on SBP (P = 0.677), DBP (P = 0.805), CBP

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(P = 0.652), TNF-α (P = 0.317) and IL-6 (P = 0.497). In a sensitivity analysis, the
pooled estimates of EPA and DHA supplementation on SBP, DBP, CRP, IL-6 and

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TNF-α levels were not substantially driven with deleting one trial at a time

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(Supplementary Figure 5-14).

Discussion

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To the best of our knowledge, the present study was the first meta-analysis evaluating
the effects of EPA/DHA as monotherapy on blood pressure and inflammatory markers.

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Supplemental EPA exerted a significant reduction in SBP, especially in subjects with

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dyslipidemia. Supplementation with DHA significantly reduced DBP in subjects with
dyslipidemia. Both EPA and DHA showed a significant reduction in CRP

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concentration, especially in subjects with dyslipidemia.

It is now widely appreciated that EPA and DHA are metabolized to different
mediators and are equally important with respect to cardiovascular protection (De,
2011; Guo, Sinclair, Kaur, & Li, 2017; Mori & Woodman, 2006). Even recently, it
was unclear as to whether EPA or DHA have differential effects on blood pressure and
inflammatory markers. With the development of separation and purification
technologies, several RCTs have used EPA and/or DHA as intervention to explore

their independent effects, however, the results have been inconsistent. Therefore, we
carried out the present quantitative meta-analysis to investigate whether EPA and
DHA have independent effects on blood pressure and inflammatory markers. The
pooled effects showed that EPA and DHA have differential effect on SBP and DBP.
EPA supplementation significantly reduced SBP, especially in subjects with
dyslipidemia. In addition, supplemental EPA exerted a significant reduction in SBP in
subjects who consumed EPA < 2 g per day (Kohashi, et al., 2014; Satoh, et al., 2009;
Shimizu, et al., 1995; Tomiyama, et al., 2005), but not in subjects who consumed EPA

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≥ 2 g per day (Grimsgaard, et al., 1998; Mori, et al., 1999; Nestel, et al., 2002;
Woodman, et al., 2002). The reason was that the duration of EPA intervention also

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played a pivotal role to reduce SBP. For the four trials, only in one trial the duration of

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EPA intervention was more than 3 months (Mori, et al., 1999), so the pooled effect of
supplemental EPA ≥ 2 g per day did not exert significant reduction in SBP

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(Grimsgaard, et al., 1998; Mori, et al., 1999; Nestel, et al., 2002; Woodman, et al.,
2002). Although DHA supplementation did not significantly reduce SBP, the summary

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estimate showed a significant reduction in DBP in subjects with dyslipidemia (Kelley,

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et al., 2007; Mori, et al., 1999; Nestel, et al., 2002; Sagara, et al., 2011).

The underlying mechanisms through which n-3 PUFA have favourable effect on blood

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pressure have been summarized as follows. First, the predominant hypotensive effect

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of n-3 PUFA attributes to stimulate the synthesis of prostacyclin (a vasodilator) and
inhibit thromboxane (a vasoconstrictor and a potent hypertensive agent) (Knapp,

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1991). Second, changes in endothelial function by n-3 PUFA is also regarded as a key
factor responsible for lowering systemic vascular resistance (Mozaffarian, 2007),
improving in endothelial vasodilator function (Goodfellow, Bellamy, Ramsey, Jones,
& Lewis, 2000) and arterial compliance (Chu, Yin, & Beilin, 1992). Besides, the
incorporation of n-3 PUFA into cardiomyocyte membranes has shown to positively
influence on β-adrenergic signaling transduction and that might be associated with
anti-arrhythmic and lowing-blood pressure effects (Grynberg, Fournier, Sergiel, &
Athias, 1995). What puzzled us was why EPA and DHA have differential effects on

SBP and DBP. To confirm the above findings, additional long-term RCTs should be
conducted to explore their independent effects.

Inappropriate and excessive inflammation contributes to the initiation and
development of acute and chronic diseases, and produces a variety of inflammatory
cytokines (Calder, 2006). Of these, CRP has received widely attention and is regarded
as an independent predictor of metabolic syndrome, diabetes mellitus, incident
peripheral arterial disease, myocardial infraction, stroke and cardiovascular death

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(Pradhan, Manson, Rifai, Buring, & Ridker, 2001; Ridker, Stampfer, & Rifai, 2001;
Paul M Ridker, 2003; Paul M Ridker, Wilson, & Grundy, 2004). Although the pooled

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effect of RCTs has shown that fish oil significantly reduced the CRP concentration (Li,

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et al., 2014), influences of supplemental DHA or EPA on CRP level are still
controversial. The findings of the present study indicated that EPA as well as DHA

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significantly reduced CRP concentration, respectively, especially in subjects with
dyslipidemia and higher baseline CRP levels. Besides, the pooled effect showed that

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DHA supplementation significantly reduced the concentration of TNF-α. Considering
that only two trials reported supplemental DHA on TNF-α concentration (Allaire, et

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al., 2016; Mori, et al., 2003), the result should be explained with caution. Meanwhile,
few trials have explored supplementation with EPA or DHA on concentrations of

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TNF-α and IL-6, and further RCT should be carried out to investigate their

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independent effect on inflammatory factors.

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There were several strengths in this study. First, the study was the first to
quantitatively evaluate the independent effect of EPA and DHA on blood pressure and
inflammatory factors. Twenty trials were included with a large sample-size and strong
statistical power, thus the summary effects provide substantial evidence that EPA and
DHA have differential and shared effects on blood pressure and CRP concentration.
Second, sensitivity analysis indicated that the pooled effects were not significantly
driven after deleting any one of the trial, indicating the stability of the results.
Meanwhile, there was no indication of publication bias, suggesting that the missing

data or unpublished studies would not exert the summary estimate. Simultaneously,
this study still had several inevitable limitations. Although a total of 20 trials were
included, few trials provided available date with respect to individual risk factors. Due
to limited data, we could not conduct dose-response analyses to obtain the optimal
dose and duration of EPA and DHA supplementation on blood pressure and
inflammatory factors. Additionally, given that limited trials reported supplementation
with EPA and DHA on concentrations of TNF-α and IL-6, the results should be
explained with caution. Third, only four studies were classified as high-quality

ip

t

according to Jadad score criteria. Most of the trials did not report the generation of
random sequence and randomization, thus inapposite study design may result in

cr

biased results through carryover of treatment effects in imbalanced characteristics in

us

baseline (Morris, Sacks, & Rosner, 1993). Besides, the control groups used different
types of placebos, including canola oil, corn oil and olive oil, and several trials did not

an

describe or even did not use the placebos. Therefore, the placebos may bias the results,

M

even if the evidence was unconvincing (Sacks, 1989).

Conclusion

ed

This meta-analysis indicates that supplemental EPA significantly reduced the SBP,
especially in subjects with dyslipidemia, and supplementation with DHA exerts a

pt

significant reduction in DBP in subjects with dyslipidemia. EPA as well as DHA have

ce

shared effects to reduce the concentration of CRP, especially in subjects with
dyslipidemia and higher baseline CRP concentrations. This study provides substantial

Ac

evidence that EPA and DHA have independent and shared effects on risk factors of
chronic diseases.

Funding
This work is supported by the National Basic Research Program of China (973
Program:
2015CB553604); by National Natural Science Foundation of China (NSFC:
81773433); and by the Ph.D. Programs Foundation of Ministry of Education of China

(20120101110107). The funders have no role in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.

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Figure 1. PRISMA flow diagram of the study selection.
Figure 2. Effect of EPA intervention on SBP and DBP values. The summary estimate
was calculated as weighted mean differences (WMD) by using a random-effects
model. The diamond denotes summary risk estimate, and horizontal line represents 95%
CI. Abbreviations: CI, confidential interval; DBP, diastolic blood pressure; EPA,
eicosapentaenoic acid; SBP, systolic blood pressure.
Figure 3. Effect of DHA intervention on SBP and DBP values. The summary estimate
was calculated as weighted mean differences (WMD) by using a random-effects
model. The diamond denotes summary risk estimate, and horizontal line represents 95%
CI. Abbreviations: CI, confidential interval; DBP, diastolic blood pressure; DHA,
docosahexaenoic acid; SBP, systolic blood pressure.
Figure 4. Effect of EPA or DHA intervention on CRP concentration. The summary
estimate was calculated as weighted mean differences (WMD) by using a
random-effects model. The diamond denotes summary risk estimate, and horizontal
line represents 95% CI. Abbreviations: CI, confidential interval; CRP, C-reactive
protein; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid.

pt

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t

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pt

ce

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ed
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us

an

M
t

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Table 1. Characteristics of the 20 eligible RCTs
Gender
Author,
year

Country

(F/M);
mean age,

Health status

Duration

Study

Treatment dose,

Diet

design

No. of participants

change

Jada
Medication

d
score

year
Placebo: Corn oil,
3g/day; n = 125
EPA, 3 g/day
Allaire,
2016

Female/male,
Canada

106/48;
52.2±15.2

(>90% 2.7 g/day); n

Metabolic

10

syndrome

weeks

Cross-over

= 121

NR

None

5

DHA, 3 g/day

t

(>90% 2.7 g/day); n

eiman,

n = 17

Female/Male,
Iran

2012

23/22;

T2DM

54.9±8.2

12
weeks

Parallel

EPA, 980 mg/day; n

us

Azizi‑Sol

cr

Placebo: Canola oil,

ip

= 123

= 14

usual

Hypoglycemic

diet

agents

NR

None

Usual

Anti-inflammator

diet

y medications

Usual

Anti-inflammator

diet

y medications

3

DHA, 964 mg/day;

an

n = 14

Placebo: Corn oil, 4

Female;
44.2±5.3

Healthy

7 weeks

Parallel

ce

2009

U.S

Male; 39-66

Ac

Kelly,

EPA, 4 g/d (95%
pure ethyl ester), n
= 75

4

DHA 4 g/d (90%
pure ethyl ester), n
= 72

pt

rd,1998

Norway

ed

Grimsgaa

M

g/d; n = 77

Placebo: OO, 7.5
g/day; n = 17

Hypertriglyce

3

ridemia

Months

DHA, 7.5 g/d
Parallel

(containing DHA
3.0 g and no EPA);

1

n = 17

Placebo: OO, 7.5
g/day; n = 17
Kelley,
2007

U.S

Male;

Hyperlipidem

3

54.1±1.8

ia

Months

DHA, 7.5
Parallel

g/d(containing
DHA 3.0 g and no
EPA); n = 17

3

Kohashi,2
014

Female/Male,
Japan

20/119;
70.2±9.0

Chronic heart

Placebo: none, n =

failure (CHF)

12

patients with

Months

Parallel

dyslipidemia

68
EPA, 1.8 g/day, n =

NR

Standard medical
treatment for CHF

0

71
Placebo: OO, 4
g/day; n = 20
EPA ethyl ester

Mori,
1999

Australia

Male;

Hyperlipidem

48.8±2.0

ia

6 weeks

Parallel

(96%), 4 g/day; n =
19

Usual

None

diet

3

DHA ethyl ester
(92%), 4 g/day; n =
17
Placebo: OO; n =

t

Anti-inflammator

16

12/39;

T2DM

6 weeks

Parallel

61.2±2.0

17

ip

Australia

(96%), 4 g/day; n =

usual
diets

DHA ethyl ester

us

2003

Female/Male,

y

cr

Mori,

EPA ethyl ester

(92%), 4 g/day; n =

d

Dyslipidemia

7 weeks

57.8±7.8
hypertension

11

Scotland

Male, 38;

and/or

52.5±3.9

hypercholeste

Parallel

5 weeks

Parallel

ed

Sagara,20

an

2002

17/21;

Sanders,

40/39;
32.5±13.4

2007

Ac

Satoh,

Female/male,

Japan

28/16;

51.6±13.9

drugs, aspirin, or
antioxidant

Healthy

g/day; n = 14
EPA, 3 g/d; n = 12

None

4

None

3

None

5

NR

None

2

NR

None

2

NR

NR

1

DHA 3 g/d; n = 12
Placebo: OO, 1
g/day; n = 23
DHA, 2 g/day; n =

Usual
diet

Placebo: OO, 4
g/day; n = 39

4 weeks

NR

15

Parallel

DHA-rich TAG, 4
g/day (containing

ce

2006

U.K

pt

rolemia

Female/Male,

3

Placebo: OO, 3

Female/male,

M

Switzerlan

lipid-lowering

vitamins

18

Nestel,

drugs,

usual
diet

1.5 g DHA); n = 40
Placebo: None; n =

Metabolic

3

syndrome

months

22
Parallel

EPA, (98% ethyl
ester) 1.8g/day; n =
22
Placebo: None; n =

Satoh,
2009

Female/male,
Japan

53/39;

Dyslipidemia

51.7±1.5

3
months

46
Parallel

EPA, (98% ethyl
ester) 1.8g/day; n =
46

Shimizu,1

Japan

Female/male,

Diabetic

12

Parallel

Placebo: None; n =

995

63.6±12.1;

nephropathy

months

16

23/22;

EPA, (90% ethyl
ester) 0.9 g/day; n =
29
Placebo: Corn and

Stark,
2004

Canada

Female;
56.7±1.9

soy oil, 6 g/day; n =
Healthy

4 weeks

Cross-over

32

NR

None

3

Statins

2

DHA, 6 g/day(2.8
g/day DHA); n = 32
Placebo: None; n =

Switzerlan

2017

d

Female/male,
13/93; 67 ±
11

53

Coronary

6

artery disease

months

Parallel

EPA, 1.8 g/day
(ethyl ester 98 %), n

usual
diet

t

Tani,

Tomiyam
a, 2005

Healthy

48.7±6.7

3
months

43/41;

38
DHA, 0.7 g/day; n
= 38

NR

None

3

NR

NR

0

NR

None

2

usual

Anti-hypertensive

diet

drug

Placebo: None; n =

Female/male,
Japan

Cross-over

cr

19/19;

us

2007

UK

Dyslipidemia

64.5±12.9

13
months

Parallel

44

EPA, 1.8 g/day; n =

an

Theobald,

Placebo: OO; n =

Female/male,

ip

= 53

40

Tsunoda,

Female/Male,
U.S

12/38;

Healthy

6 weeks

Parallel

51.6±9.7

Australia

12/39;

61.2±8.4

T2DM

6 weeks

EPA, 1.8 g/dag; n =
16

= 18
Placebo: OO,4

pt

ce

, 2002

Female/Male,

Ac

Woodman

g/day; n = 16

DHA, 1.8 g/day; n

ed

2015

M

Placebo: OO, 6.0

g/day; 16
EPA, (96% ethyl
ester), 4 g/day; n =
Parallel

17
DHA, (92% ethyl
ester), 4 g/day; n =
17

Abbreviations: DHA, docosahexaenoic acid; EPA, eicosapentaenoic acid; NR, not reported; OO,
olive oil; T2DM, type 2 diabetes mellitus.

3

Table 2. Subgroup and meta-regression analyses of EPA supplementation on SBP,
DBP and CRP levels
SBP mmHg

DBP mmHg

Factors

Pooled

Pooled

stratified

effect

effect

No.

(95%

Heterogeneity

Pb

No.

CI)

(95%

CRP mg/L
Pooled
Pb

Heterogeneity

No.

CI)
2

I (%)

P

a

effect

Heterogeneity

(95%
CI)

I

2

P

a

I2

(%)
0.347

2

-4.15

0.0

0.838

3

3.11)

0.00)

-1.25

0.0

0.654

2

-2.20

-0.73

0.0

0.587

2

-1.84

(-8.30,

(-4.78,

3.90)

1.10)

-1.84

0.0

0.688

1

an
4

-3.50

-1.27

ed

4

0.661

3

pt

-0.40)

0.0

0.821

-3.79

0.0

2

1

0.896

(-2.87,

0.475

3

-0.64

-0.77

0.0

0.982

2

0.04

(-3.99,

(-0.21,

2.72)

0.28)

4

-2.01

0.0

0.951

4

-0.65

-0.83)

0.67)

-0.02)

0.288

2

-0.43

0.0

0.919

2

-0.13

(-12.03,

(-4.65,

(-1.31,

5.33)

3.78)

1.04)

-1.20

0.0

1.0

1

0.585

95.3

<0.001

0.0

0.614

-0.60

(-4.20,

(3.05,

1.80)

1.85)

Dose of EPA

0.0

0.586

(-1.29,

11.3

<0.001

0.839

(-4.70,

-3.35

92.9

0.34)

(-6.74,

Ac

5

-2.24

(-1.87,

0.331

ce

Health status

1.12)

-1.61)

0.64)

0.0

-0.37

(-1.86,

(-3.18,

(-6.59,

Healthy

0.442

0.762

(-4.54,
0.86)

0.383

0.30)

0.0

M

0.460

0.05

0.0

(-0.20,

1.60)
0.0

year

T2DM

1

(-3.06,

Mean age,

Dyslipidemia

0.732

1

4

-0.15

-0.98)

America

≥ 60

3

(-0.30,

North

< 60

0.999

(-4.92,

1.70)
2

0.0

(-7.31,

(-4.21,

Oceania

-0.91

0.076

ip

4

0.664

cr

Europe

(%)

us

Asia

Pa

t

Region

0.245

0.915

0.017

intake
< 2 g/day

4

-4.15
(-7.31,

0.0

0.814

3

Pb

-0.91
(-4.92,

0.0

0.999

4

-0.10
(-0.27,

20.4

0.287

-0.98)
≥ 2 g/day

4

-1.43

3.11)
0.0

0.938

≥ 3 mon

-1.16

(-4.09,

(-2.98,

1.23)

0.67)

Duration
< 3 mon

4

0.08)
0.0

0.7
91

4

-1.43

0.0

0.938

-1.43

0.915
4

-1.16

0.0

0.791

0.017
2

-1.43

(-2.98,

(-3.25,

1.23)

0.67)

0.38)

0.0

0.654

3

-0.91

0.0

0.999

4

-0.10

(-7.31,

(-4.92,

(-0.27,

-0.98)

0.55)

0.08)

Baseline

0.023

(-3.25,

(-4.09,

-4.15

80.6

0.38)

0.245
4

2

80.6

0.023

20.4

0.287

0.306

4

-2.06

0.0

0.871

0.0

0.630

ip

< 130 mmHg

t

SBP

(-4.27,
≥ 130 mmHg

4

-5.30

cr

0.15)

us

(-10.50,
-0.09)

0.533

DBP
< 76 mmHg

3

-1.86
(-4.60,

≥ 76 mmHg

4

0.0

M

0.08)

an

Baseline

-0.68

0.0

0.744

0.999

(-2.77,

ed

1.41)

Baseline

pt

CRP

Ac

≥ 2 mg/L

ce

< 2 mg/L

0.220

3

-0.10

45.1

0.162

79.7

0.007

(-0.23,
0.03)
3

-1.77
(-2.32,
-1.22)

Abbreviations: CI, confidential interval; CRP, C-reactive protein; DBP, diastolic
blood pressure; EPA, eicosapentaenoic acid; No., number of included studies; SBP,
systolic blood pressure; T2DM, type 2 diabetes mellitus; Pa for heterogeneity; Pb for
meta-regression analysis.

Table 3. Subgroup and meta-regression analyses of DHA supplementation on SBP,
DBP and CRP levels
SBP mmHg

DBP mmHg

Factors

Pooled

Pooled

stratified

effect

effect

No.

Heterogeneity

(95%

Pb

No.

CI)

(95%

CRP mg/L
Pooled
Pb

Heterogeneity

effect

No.

CI)
I

2

P

I

2

P

a

I2

(%)

Region

Pb

CI)

a

(%)

Heterogeneity

(95%

Pa

(%)

0.964

0.961

0.803

Asia

1

-0.94
(-2.92,

0.0

0.775

4

(-3.51,

2

America

0.706

2

(-7.60,

4.17)

3.55)
73.7

0.051

2

(-4.13,

14.21)

3.50)

-1.41

0.0

0.446

2

-0.51

ed

-0.67

0.0

0.558

6

pt

3.51)

-1.02

0.0

4

1

0.713

0.03

0.0

0.536

4

1.77)
-0.57

53.3

0.389

0.143

2

-1.48

3

0.01

0.0

0.538

5

-0.60

(-3.71,

(-1.11.

0.74)

-0.08)

-0.21

12.3

0.320

3

0.07

-3.05

0.0

0.730

3

-0.74

(-8.93,

(-5.94,

(-1.31,

0.79)

-0.16)

-0.18)

1

1.00

1

(-4.06,

(-1.71,

18.60)

6.06)

1.77)

0.769

0.0

0.628

0.0

0.870

0.03

(-3.40,

Dose of

0.612

0.500

1.06)

7.60

0.0

0.778

2.09)
4

0.980

1.18)

1.18)

0.905

0.0

(-1.15,

(-0.91,

0.0

0.463

-0.04)

(-2.52,

-4.07

0.0

(-1.11,

(-3.22,

Ac

4

1

(-1.71,

0.840

ce

Health status

T2DM

0.091

3.01)

(-4.84,

Dyslipidemia

1.56)

65.0

(-4.03,

0.83)
5

(-1.56,

0.652

(-3.65,

Healthy

-0.31

(-13.99,

year

≥ 50

-2.02

(-6.72,

0.11

0.00

cr

0.0

0.766

4

1

1.57)

-1.28

Mean age,

< 50

0.478

us

North

2

0.0

(-2.76,

0.92)
Oceania

-0.60

ip

-1.29

an

5

M

Europe

t

1.05)

0.811

0.293

DHA intake
< 2 g/day

2

-1.96
(-6.94,

0.0

0.547

3

-0.73
(-3.31,

18.8

0.292

3

-0.02
(-0.94,

0.0

0.558

3.02)
≥ 2 g/day

7

1.84)

-1.11

0.0

0.506

≥ 3 mon

-1.36

(-3.26,

(-3.73,

1.03)

1.00)

Duration
< 3 mon

5

0.90)
0.0

0.4
07

2

-1.19

0.0

0.461

-0.67

0.457
6

-0.56

12.5

0.335

0.956
6

-0.50

(-2.65,

(-1.02,

0.98)

1.53)

0.03)

0.0

0.782

2

-2.28

0.0

0.893

1

0.0

0.612

-0.50

(-6.23,

(-5.40,

(-1.58,

3.24)

0.84)

0.58)

Baseline

0.794

-0.12)

(-3.36,

-1.49

0.0

(-1.21,

0.914
7

4

0.757

5

-1.12

0.0

0.831

28.2

0.243

ip

< 125 mmHg

t

SBP

(-3.24,
≥ 125 mmHg

4

-2.06

cr

1.00)

us

(-7.41,
3.29)

0.405

< 73 mmHg

3

0.0

0.449

M

DBP
-0.33

0.402

(-2.38,
1.71)

≥ 73 mmHg

5

an

Baseline

-2.11

0.0

(-4.80,

ed

0.58)

Baseline

pt

CRP

Ac

≥ 3 mg/L

ce

< 3 mg/L

0.263

3

-0.12

0.0

0.594

0.0

0.814

(-0.87,
0.62)
4

-0.74
(-1.35,
-0.14)

Abbreviations: CI, confidential interval; CRP, C-reactive protein; DBP, diastolic
blood pressure; DHA, docosahexaenoic acid; No., number of included studies; SBP,
systolic blood pressure; T2DM, type 2 diabetes mellitus; Pa for heterogeneity; Pb for
meta-regression analysis.