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Comparing the effects of docosahexaenoic and eicosapentaenoic acids on cardiovascular risk factors: Pairwise and network meta-analyses of randomized controlled trials

  • Author Footnotes
    1 Mohammad Hassan Sohouli and Somaye Fatahi contributed equally to this work.
    Somaye Fatahi
    Footnotes
    1 Mohammad Hassan Sohouli and Somaye Fatahi contributed equally to this work.
    Affiliations
    Student Research Committee, Faculty of Public Health Branch, Iran University of Medical Sciences, Tehran, Iran

    Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
    Search for articles by this author
  • Author Footnotes
    1 Mohammad Hassan Sohouli and Somaye Fatahi contributed equally to this work.
    Mohammad Hassan Sohouli
    Footnotes
    1 Mohammad Hassan Sohouli and Somaye Fatahi contributed equally to this work.
    Affiliations
    Student Research Committee, Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
    Search for articles by this author
  • Elma Izze da Silva Magalhães
    Affiliations
    Postgraduate Programme in Collective Health, Federal University of Maranhão, Rua Barão de Itapary, 155, Centro, São Luís, MA, Brazil
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  • Victor Nogueira da Cruz Silveira
    Affiliations
    Postgraduate Programme in Collective Health, Federal University of Maranhão, Rua Barão de Itapary, 155, Centro, São Luís, MA, Brazil
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  • Fernando Zanghelini
    Affiliations
    Postgraduate Program in Therapeutic Innovation, Federal University of Pernambuco, Pernambuco, Brazil
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  • Parisa Rahmani
    Affiliations
    Pediatric Gastroenterology and Hepatology Research Center, Pediatrics Centre of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
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  • Hamed Kord-Varkaneh
    Affiliations
    Student Research Committee, Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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  • Elham Sharifi-Zahabi
    Affiliations
    Student Research Committee, Faculty of Public Health Branch, Iran University of Medical Sciences, Tehran, Iran
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  • Farzad Shidfar
    Correspondence
    Corresponding author. Department of Nutrition, School of Public Health, Iran University of Medical Sciences, No 7, West Arghavan St, Farahzadi Blvd, PO Box 19395-4741, Tehran 1981619573, Iran.
    Affiliations
    Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
    Search for articles by this author
  • Author Footnotes
    1 Mohammad Hassan Sohouli and Somaye Fatahi contributed equally to this work.
Published:September 27, 2022DOI:https://doi.org/10.1016/j.numecd.2022.09.013

      Highlights

      • Evidence studies suggests that DHA may have greater potential effects on improving CVD risk factors than EPA.
      • Network meta-analysis of comparisons of DHA and EPA suggested significant comparable effects only on LDL.
      • Pairwise meta-analysis of DHA and EPA showed significant difference in their effects on glucose and Insulin.
      • Findings suggest that both EPA and DHA act similarly on the markers with slight changes in glucose, insulin, and LDL.

      Abstract

      Background

      Evidence from clinical trial studies suggests that docosahexaenoic acids (DHA) may have greater potential effects on improving cardiovascular risk factors than eicosapentaenoic acid (EPA). However, this evidence has not yet been meta-analyzed and quantified. The aim of this study was to evaluate and compare the effect of DHA and EPA monotherapy on cardiovascular risk factors based on paired and network meta-analysis.

      Methods

      Relevant articles published up to January 2022 were systematically retrieved from relevant databases. We included all Randomized Controlled Trials (RCTs) on adults that directly compared the effects of DHA with EPA and RCTs of indirect comparisons (DHA and EPA monotherapy compared to control groups). Data were pooled by pairwise and network meta-analysis and expressed as mean differences (MDs) with 95% CIs. The study protocol was registered with PROSPERO (Registration ID: CRD42022328630).

      Results

      Network meta-analysis of comparisons of DHA and EPA suggested significant comparable effects only on LDL-C (MD EPA versus DHA = −8.51 mg/L; 95% CI: −16.67; −0.35). However, the Network meta-analysis not show a significant effect for other risk factors. Furthermore, pairwise meta-analysis of direct comparisons of DHA and EPA showed significant difference in their effects on plasma glucose (MD EPA versus DHA = −0.31 mg/L; 95% CI: −0.60, −0.02), Insulin (MD EPA versus DHA = −2.14 mg/L; 95% CI: −3.26, −1.02), but the results were not significant for risk factors.

      Conclusion

      Our findings suggest that both EPA and DHA act similarly on the markers under study, with slight changes in plasma glucose, insulin, and LDL-C.

      Keywords

      1. Introduction

      Cardiovascular diseases as well-established predictor of chronic disease, represent the leading causes of mortality worldwide [
      • Joshi R.
      • Agrawal T.
      • Fathima F.
      • Usha T.
      • Thomas T.
      • Misquith D.
      • et al.
      Cardiovascular risk factor reduction by community health workers in rural India: a cluster randomized trial.
      ]. According to reports, more than 18.6 million deaths in 2019 were attributed to cardiovascular risk factors [
      • Roth G.A.
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      • Johnson C.O.
      • Addolorato G.
      • Ammirati E.
      • Baddour L.M.
      • et al.
      Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study.
      ]. Hypertension, dyslipidemia, insulin resistance, smoking, obesity, sedentary lifestyle, and family history of cardiovascular disease, are the underlying factors for most cardiovascular events [
      • Jardim T.V.
      • Gaziano T.A.
      • Nascente F.M.
      • Carneiro CdS.
      • Morais P.
      • Roriz V.
      • et al.
      Multiple cardiovascular risk factors in adolescents from a middle-income country: prevalence and associated factors.
      ]. Moreover, the cluster of these risk factors is associated with a significant increase in medical expenditures and lost productivity [
      • McQueen R.B.
      • Ghushchyan V.
      • Olufade T.
      • Sheehan J.J.
      • Nair K.V.
      • Saseen J.J.
      Incremental increases in economic burden parallels cardiometabolic risk factors in the US.
      ].
      Recently, the use of herbal or medicinal supplements or the intake of certain nutrients to manage and control cardiovascular risk factors has increased among people around the world. Among these, long-chain ω-3 PUFAs (LCn-3PUFAs), mainly eicosapentaenoic acid (EPA) and docosahexaenoic acids (DHA), have received much attention for their beneficial effects on cardiovascular risk factors. Seafood, especially fatty fish, are potential sources of DHA and EPA. However their potential effects on these risk factors are mainly when taken as a supplement and in large quantities [
      • Calder P.C.
      Very long-chain n-3 fatty acids and human health: fact, fiction and the future.
      ,
      • Casula M.
      • Olmastroni E.
      • Gazzotti M.
      • Galimberti F.
      • Zambon A.
      • Catapano A.L.
      Omega-3 polyunsaturated fatty acids supplementation and cardiovascular outcomes: do formulation, dosage, and baseline cardiovascular risk matter? An updated meta-analysis of randomized controlled trials.
      ]. To date, in most clinical trials, DHA and EPA have been used in combination and in various forms and ratios because DHA and EPA are usually present naturally and in combination in foods and supplements. A recent meta-analysis has shown that omega-3 supplementation has potentially beneficial effects on major cardiovascular outcomes [
      • Casula M.
      • Olmastroni E.
      • Gazzotti M.
      • Galimberti F.
      • Zambon A.
      • Catapano A.L.
      Omega-3 polyunsaturated fatty acids supplementation and cardiovascular outcomes: do formulation, dosage, and baseline cardiovascular risk matter? An updated meta-analysis of randomized controlled trials.
      ]. However, some meta-analysis studies did not report a significant effect of this supplement on CVD outcomes [
      • Rizos E.C.
      • Markozannes G.
      • Tsapas A.
      • Mantzoros C.S.
      • Ntzani E.E.
      Omega-3 supplementation and cardiovascular disease: formulation-based systematic review and meta-analysis with trial sequential analysis.
      ,
      • Yu F.
      • Qi S.
      • Ji Y.
      • Wang X.
      • Fang S.
      • Cao R.
      Effects of omega-3 fatty acid on major cardiovascular outcomes: a systematic review and meta-analysis.
      ]. But the highlight of this study was the different results of the study when using the various forms of this supplement. In addition, in several clinical trial studies, DHA and EPA were not equally effective in improving cardiovascular risk factors. Thus, some studies show a greater effect of DHA and some other studies show a greater effect of EPA [
      • de Luis D.
      • Domingo J.C.
      • Izaola O.
      • Casanueva F.F.
      • Bellido D.
      • Sajoux I.
      Effect of DHA supplementation in a very low-calorie ketogenic diet in the treatment of obesity: a randomized clinical trial.
      ,
      • Golzari M.H.
      • Hosseini S.
      • Koohdani F.
      • Yaraghi A.-A.S.
      • Javanbakht M.H.
      • Mohammadzadeh-Honarvar N.
      • et al.
      The effect of eicosapentaenoic acid on the serum levels and enzymatic activity of paraoxonase 1 in the patients with type 2 diabetes mellitus.
      ,
      • Huerta A.E.
      • Navas-Carretero S.
      • Prieto-Hontoria P.L.
      • Martínez J.A.
      • Moreno-Aliaga M.J.
      Effects of α-lipoic acid and eicosapentaenoic acid in overweight and obese women during weight loss.
      ,
      • Kelley D.S.
      • Siegel D.
      • Vemuri M.
      • Mackey B.E.
      Docosahexaenoic acid supplementation improves fasting and postprandial lipid profiles in hypertriglyceridemic men.
      ,
      • Lavie C.J.
      • Bernasconi A.
      Impressive results with EPA, but EPA/DHA combinations also reduce cardiovascular outcomes.
      ,
      • Raghu B.
      • Venkatesan P.
      Effect of n-3 fatty acid supplementation on blood glucose, lipid profile and cytokines in humans: a pilot study.
      ].
      However, so far no systematic study and meta-analysis has been performed as the gold standard of evidence to compare the effects of DHA and EPA monotherapy and difference between these two forms on cardiovascular factors including blood pressure, lipid profile and glycemic index. Therefore, we have examined this issue in this study. In addition, in this study, we used the network and paired meta-analysis approach to better compare and contrast DHA and EPA.

      2. Methods

      2.1 Search strategy

      The current systematic review was executed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement criteria [
      • Moher D.
      • Shamseer L.
      • Clarke M.
      • Ghersi D.
      • Liberati A.
      • Petticrew M.
      • et al.
      Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.
      ]. The study protocol was registered with PROSPERO (Registration ID: CRD42022328630). To find related articles search was carried out from the time of selection until January 2022 through international electronic databases including: PubMed/MEDLINE, SCOPUS, Web of Science and EMBASE. The Randomized controlled trials (RCTs) that showed the impact of omega 3 on cardiovascular risk factor (weight, total cholesterol, LDL- and HDL cholesterol and triglyceride, HbA1c, glucose, insulin, systolic blood pressure, diastolic blood pressure) were considered. The following keywords of Medical Sub Headings (MeSH) were used as search terms: (“Omega-3 Fatty Acids” OR “Eicosapentaenoic Acid” OR “Docosahexaenoic Acid” OR DHA OR EPA) AND (“Glycated Hemoglobin A” OR HbA1c OR “Insulin Resistance” OR Glucose OR “Glucose Intolerance” OR Triglycerides OR “HDL Cholesterol” OR “LDL Cholesterol” OR “total cholesterol” OR “Blood Pressure” OR “Arterial Pressure” OR Hypertension OR SBP OR DBP) AND (“Clinical Trials” OR “Cross-Over Studies” OR “Double-Blind Method” OR “Single-Blind Method” OR “Random Allocation” OR RCT OR “Clinical Trial” OR “Controlled Clinical Trials” OR “Intervention Studies” OR assignment). There were no time or language restrictions in the literature search. Moreover, we have identified the sources of review articles to find more potential articles.

      2.2 Study selection

      We screened the articles. In the first screening, the related articles were identified by the titles and abstracts of the articles and the relevant articles were retrieved in full text and validated for inclusion in the systematic review. RCTs with the following criteria were selected to be included in this meta-analysis: 1) published randomized controlled trial; 2) RCTs that directly compared the effects of DHA to those of EPA, or assessed the effects of DHA or EPA individually compared with a suitable control (i.e., fatty acids other than EPA and DHA as control); 3) adult participants over 18 years of age and 4) Trials reporting cardiovascular risk factor at baseline and after intervention (total cholesterol, LDL and HDL cholesterol and triglyceride, HbA1c, glucose, insulin, systolic blood pressure (SBP), diastolic blood pressure (DBP)). Also, the following exclusion criteria were considered: lack of outcome measures, trials that included data that could not be used in this meta-analysis (such as examining hazard or odds ratios, did not report mean or SD), non-control group studies, duplicated studies, in vitro studies, observational studies, animal studies, review articles and studies that administered omega 3 in combination with other compounds were excluded from our study.

      2.3 Data extraction

      Two independent investigators screened the titles and abstracts of articles initially retrieved on online search of databases, and extracted essential data from eligible full-text articles included the following: first author's name, study location, publication year, RCT design (crossover or parallel), sample size (intervention and control groups), participant characteristics (gender, age, and health status), duration of intervention, the amount of DHA and EPA consumption, and the means and standard deviations (SDs) of intended outcomes at baseline, post intervention and/or changes between baseline and post intervention.

      2.4 Quality assessment

      The quality of the selected studies was assessed using the Cochrane risk of bias tool [
      • Higgins J.
      Cochrane handbook for systematic reviews of interventions. Version 5.1. 0.
      ] and considering the following parameters including: Adequate random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other biases. Based on the recommendations of the Cochrane Handbook, the judgment of each item was recorded as “unclear,” “low,” or “high” risk of bias. Discrepant results were resolved through discussing with a third author. According to the aforementioned domains, the overall quality of each individual study was considered as good (low risk for >2 items), fair (low risk for 2 items), or weak (low risk for <2 items).

      2.5 Data synthesis and statistical analysis

      Meta-analysis was performed for cardiovascular risk factor using RevMan V.5.3 software and STATA version 12.0 (Stata Corp, College Station, TX, USA). Standard formulas were applied to convert different formats of data to the mean and standard deviations [
      • Higgins J.
      Cochrane handbook for systematic reviews of interventions. Version 5.1. 0.
      ,
      • Hozo S.P.
      • Djulbegovic B.
      • Hozo I.
      Estimating the mean and variance from the median, range, and the size of a sample.
      ]. For instance, If the SDs of the change were unavailable, we obtained it through the following formula: SD changes = square root [(SD baseline 2 + SD final 2) - (2 × R × SD baseline × SD final)]. Also, for trials that only reported standard error of the mean (SEM), we convert (SEM) to the SD using the following formula: SD = SEM × √n, where “n” is the number of subjects in each group. Statistical heterogeneity between trials was detected by the I-square (I2) statistic [
      • Higgins J.P.
      • Thompson S.G.
      • Deeks J.J.
      • Altman D.G.
      Measuring inconsistency in meta-analyses.
      ]. Sensitivity analysis was also done to assess the impact of every individual study on the pooled effect size. Publication bias was evaluated based on Egger's test [
      • Egger M.
      • Smith G.D.
      • Schneider M.
      • Minder C.
      Bias in meta-analysis detected by a simple, graphical test.
      ]. We used standard Cochrane methods for pairwise meta-analysis and augmented this evidence using network meta-analysis methods.

      2.6 Pairwise meta-analysis

      Data were managed and analyzed with the use of Review Manager (RevMan) version 5.3.2 (The Nordic Cochrane Centre, The Cochrane Collaboration) for the pairwise meta-analysis. The generic inverse variance method with random effects models was used to synthesize the overall effect estimate of DHA and EPA on cardiovascular risk factors. Der Simonian and Laird random-effects models were used even in the absence of statistically significant between-study heterogeneity, as they yield more conservative summary effect estimates in the presence of residual heterogeneity [
      • Moher D.
      • Shamseer L.
      • Clarke M.
      • Ghersi D.
      • Liberati A.
      • Petticrew M.
      • et al.
      Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.
      ,
      • DerSimonian R.
      • Laird N.
      Meta-analysis in clinical trials.
      ]. For each outcome, mean differences (MDs) between DHA and EPA were extracted for each pairwise comparison when provided in the publications. If not provided, post intervention values after each treatment (DHA and EPA) in each study were used to calculate MDs between the 2 treatments. MDs were calculated by subtracting means of post intervention values and SEs were calculated from the available data and statistics using published formulas [
      • Moher D.
      • Shamseer L.
      • Clarke M.
      • Ghersi D.
      • Liberati A.
      • Petticrew M.
      • et al.
      Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.
      ]. When only medians and IQRs were available, means were estimated from median values using the new method of Luo et al. [
      • Luo D.
      • Wan X.
      • Liu J.
      • Tong T.
      Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range.
      ] and SDs were estimated from IQR using the method described by Wan et al. [
      • Wan X.
      • Wang W.
      • Liu J.
      • Tong T.
      Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.
      ]. The SEs were then calculated from SD values using Cochrane Formulas [
      • Moher D.
      • Shamseer L.
      • Clarke M.
      • Ghersi D.
      • Liberati A.
      • Petticrew M.
      • et al.
      Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.
      ]. Paired analyses were applied to all crossover trials with the use of a conservative correlation coefficient of 0.5 in determining the missing variance data of crossover trials [
      • Elbourne D.R.
      • Altman D.G.
      • Higgins J.P.
      • Curtin F.
      • Worthington H.V.
      • Vail A.
      Meta-analyses involving cross-over trials: methodological issues.
      ]. For studies with multiple interventions (e.g., different doses of DHA or EPA) or controls, we did not combine groups but split the “shared” group into 2 or more groups with sample size divided between groups, and included 2 or more comparisons as proposed in the Cochrane Handbook to overcome unit-of-analysis error [
      • Higgins J.
      Cochrane handbook for systematic reviews of interventions. Version 5.1. 0.
      ]. The pooled estimates are expressed and presented as MDs with 95% CIs. Inter study heterogeneity was assessed with the Cochran Q statistic and quantified by the I2 statistic, where I2 ≥50% at P < 0.10 was considered as substantial heterogeneity. Sources of heterogeneity were explored through sensitivity analyses. To determine the particular influence of any single study on the results, each trial comparison was individually removed from the pairwise meta-analysis and the overall effect size and heterogeneity were recalculated. We did not perform a priori subgroup analyses nor investigated publication bias, as there were fewer than 10 direct comparisons available for the analyses of each outcome in the pairwise meta-analysis.

      2.7 Network meta-analysis

      Data for the network meta-analysis were managed and analyzed with the use of STATA/SE version 13 (StataCorp). We performed a frequentist network meta-analysis using a multivariate meta-analysis model and the “network” suite of commands available in STATA [
      • Chaimani A.
      • Higgins J.P.
      • Mavridis D.
      • Spyridonos P.
      • Salanti G.
      Graphical tools for network meta-analysis in STATA.
      ]. For each outcome, post intervention values after each treatment in each study (DHA versus control and EPA versus control) were extracted and used to calculate MDs between DHA and EPA directly in STATA. Random-effects network meta-analysis was used for cardiovascular risk factors. We used the fixed option for omega 3 data, as there was no source of heterogeneity. Network diagrams were performed for each outcome to show the interactions among the studies included in the network meta-analysis and to illustrate the available direct comparisons between treatments [
      • Chaimani A.
      • Higgins J.P.
      • Mavridis D.
      • Spyridonos P.
      • Salanti G.
      Graphical tools for network meta-analysis in STATA.
      ]. We checked the consistency in the data using both local and global approaches in STATA. We applied the loop-specific and the side-splitting approaches as local methods to evaluate the presence of statistical inconsistency. The loop-specific approach looks at the inconsistency in each closed loop in the network [
      • Bucher H.C.
      • Guyatt G.H.
      • Griffith L.E.
      • Walter S.D.
      The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials.
      ] whereas the side-splitting approach detects comparisons for which direct estimates disagree with indirect evidence from the entire network [
      • Dias S.
      • Welton N.J.
      • Caldwell D.
      • Ades A.E.
      Checking consistency in mixed treatment comparison meta-analysis.
      ]. The global approach tests for overall inconsistency from all possible sources in the whole network simultaneously using a design-by-treatment interaction model [
      • Jackson D.
      • Barrett J.K.
      • Rice S.
      • White I.R.
      • Higgins J.P.
      A design-by-treatment interaction model for network meta-analysis with random inconsistency effects.
      ]. If inconsistency was suggested, sensitivity analyses were performed to explore the sources of heterogeneity. The sensitivity analysis was also done to assess the impact of every individual study on the pooled effect size. Publication bias was assessed in the network meta-analysis through generation of comparison-adjusted funnel plots that were visually inspected for asymmetry, but only when 10 trial comparisons or more were available for a specific outcome.

      3. Results

      The details of step by step RCTs identification and selection process are presented in Fig. 1. An overall of 3564 studies were retrieved through initial online database search. After removing duplicate records, totally, 1985 publications remained. Then after screening the title and abstracts of related RCTs according to the inclusion criteria, 1950 trials were deleted. Finally, 18 [
      • de Luis D.
      • Domingo J.C.
      • Izaola O.
      • Casanueva F.F.
      • Bellido D.
      • Sajoux I.
      Effect of DHA supplementation in a very low-calorie ketogenic diet in the treatment of obesity: a randomized clinical trial.
      ,
      • Golzari M.H.
      • Hosseini S.
      • Koohdani F.
      • Yaraghi A.-A.S.
      • Javanbakht M.H.
      • Mohammadzadeh-Honarvar N.
      • et al.
      The effect of eicosapentaenoic acid on the serum levels and enzymatic activity of paraoxonase 1 in the patients with type 2 diabetes mellitus.
      ,
      • Huerta A.E.
      • Navas-Carretero S.
      • Prieto-Hontoria P.L.
      • Martínez J.A.
      • Moreno-Aliaga M.J.
      Effects of α-lipoic acid and eicosapentaenoic acid in overweight and obese women during weight loss.
      ,
      • Kelley D.S.
      • Siegel D.
      • Vemuri M.
      • Mackey B.E.
      Docosahexaenoic acid supplementation improves fasting and postprandial lipid profiles in hypertriglyceridemic men.
      ,
      • Buckley R.
      • Shewring B.
      • Turner R.
      • Yaqoob P.
      • Minihane A.M.
      Circulating triacylglycerol and apoE levels in response to EPA and docosahexaenoic acid supplementation in adult human subjects.
      ,
      • Egert S.
      • Kannenberg F.
      • Somoza V.
      • Erbersdobler H.F.
      • Wahrburg U.
      Dietary α-linolenic acid, EPA, and DHA have differential effects on LDL fatty acid composition but similar effects on serum lipid profiles in normolipidemic humans.
      ,
      • Mocking R.J.
      • Assies J.
      • Bot M.
      • Jansen E.H.
      • Schene A.H.
      • Pouwer F.
      Biological effects of add-on eicosapentaenoic acid supplementation in diabetes mellitus and co-morbid depression: a randomized controlled trial.
      ,
      • Neff L.M.
      • Culiner J.
      • Cunningham-Rundles S.
      • Seidman C.
      • Meehan D.
      • Maturi J.
      • et al.
      Algal docosahexaenoic acid affects plasma lipoprotein particle size distribution in overweight and obese adults.
      ,
      • Sasaki J.
      • Miwa T.
      • Odawara M.
      Administration of highly purified eicosapentaenoic acid to statin-treated diabetic patients further improves vascular function.
      ,
      • Singhal A.
      • Lanigan J.
      • Storry C.
      • Low S.
      • Birbara T.
      • Lucas A.
      • et al.
      Docosahexaenoic acid supplementation, vascular function and risk factors for cardiovascular disease: a randomized controlled trial in young adults.
      ,
      • Stark K.D.
      • Holub B.J.
      Differential eicosapentaenoic acid elevations and altered cardiovascular disease risk factor responses after supplementation with docosahexaenoic acid in postmenopausal women receiving and not receiving hormone replacement therapy.
      ,
      • Tani S.
      • Yagi T.
      • Matsuo R.
      • Kawauchi K.
      • Atsumi W.
      • Matsumoto N.
      • et al.
      Administration of eicosapentaenoic acid may alter lipoprotein particle heterogeneity in statin-treated patients with stable coronary artery disease: a pilot 6-month randomized study.
      ,
      • Tomiyama H.
      • Takazawa K.
      • Osa S-i
      • Hirose K-i
      • Hirai A.
      • Iketani T.
      • et al.
      Do eicosapentaenoic acid supplements attenuate age-related increases in arterial stiffness in patients with dyslipidemia?: a preliminary study.
      ,
      • Sawada T.
      • Tsubata H.
      • Hashimoto N.
      • Takabe M.
      • Miyata T.
      • Aoki K.
      • et al.
      Effects of 6-month eicosapentaenoic acid treatment on postprandial hyperglycemia, hyperlipidemia, insulin secretion ability, and concomitant endothelial dysfunction among newly-diagnosed impaired glucose metabolism patients with coronary artery disease. An open label, single blinded, prospective randomized controlled trial.
      ,
      • Woodman R.J.
      • Mori T.A.
      • Burke V.
      • Puddey I.B.
      • Watts G.F.
      • Beilin L.J.
      Effects of purified eicosapentaenoic and docosahexaenoic acids on glycemic control, blood pressure, and serum lipids in type 2 diabetic patients with treated hypertension.
      ,
      • Nomura S.
      • Inami N.
      • Shouzu A.
      • Omoto S.
      • Kimura Y.
      • Takahashi N.
      • et al.
      The effects of pitavastatin, eicosapentaenoic acid and combined therapy on platelet-derived microparticles and adiponectin in hyperlipidemic, diabetic patients.
      ,
      • Allaire J.
      • Vors C.
      • Harris W.S.
      • Jackson K.H.
      • Tchernof A.
      • Couture P.
      • et al.
      Comparing the serum TAG response to high-dose supplementation of either DHA or EPA among individuals with increased cardiovascular risk: the ComparED study.
      ,
      • Mahmoudabadi M.M.S.
      • Rahbar A.R.
      Effect of EPA and vitamin C on superoxide dismutase, glutathione peroxidase, total antioxidant capacity and malondialdehyde in type 2 diabetic patients.
      ] trials were found to be eligible to be included in the present meta-analysis after reviewing the full text of the articles.
      Figure 1
      Figure 1Flow chart of the included studies, including identification, screening, eligibility and the final sample included.

      3.1 Study characteristics

      The summary of the main features of the included studies is shown in Table 1. According to the studies included in this meta-analysis, 7 studies have been conducted in Asia, 6 studies in Europe, 4 studies in the United States and one study in Australia. These studies were published between the years 2002–2020. Sixteen RCTs had a parallel design, whereas the remaining were crossover in design. The duration of intervention ranged from 4 to 24 weeks. The age range of the participants in the study ranged from 25 to 67.8 and except for one study that was done only on men, in all other studies, both sexes were used as participants. DHA was used in 8 articles and EPA was used as an intervention group in 13 articles. Also, the amount used for both DHA and EPA varied from 0.5 to 4.9 g. From the selected studies, 6 studies were performed on individuals with diabetes or glucose disorders, 6 studies were performed on subjects with cardiovascular problems, 3 studies were performed on overweight or obese subjects and 2 studies were performed on healthy individuals.
      Table 1Characteristics of eligible studies.
      Author (year)CountryClinical Trial DesignPopulationMean Age yearsexSample Size

      Active/Placebo
      Period (week)OutcomeIntervention GroupControl Group
      Buckley et al. 2004UKParallelNormolipidaemic Humans46F/M15/164Cholesterol, LDL-C, HDL-C, TG.4·9 g DHA/4·8 g EPAOlive oil
      De luis et al. 2016SpainParallelObese patient47/4F/M14/1524Cholesterol, LDL-C, HDL-C, TG, glucose, insulin, HOMA-IR.Very Low Calorie Ketogenic Diet +0.5 g DHAVery Low Calorie Ketogenic Diet
      Egert et al. 2009GermanyParallelNormolipidemic Humans25/3F/M25/246Cholesterol, LDL-C, HDL-C, TG.2.3 g DHA, 2.2 g/d EPA4.4 g ALA
      Kelley et al. 2007USAParallelHypertriglyceridemic men55M17/1712Cholesterol, LDL-C, HDL-C, TG, SBP, DBP, glucose, insulin.3 g DHA7.5 g olive
      Mocking et al. 2012NetherlandsParallelDiabetes Mellitus patients54F/M11/1212Cholesterol, LDL-C, HDL-C, TG.1 g EPARapeseed oil and medium chain triglycerides
      Neff et al. 2010USAParallelOverweight or obese adults43F/M19/1720Cholesterol, LDL-C, HDL-C, TG.2 g of algal DHACorn- soy bean
      Sasaki et al. 2012JapanParallelN/A67F/M15/1324Cholesterol, LDL-C, HDL-C, TG, SBP, DBP, glucose, HbA1c.1.8 g EPAStatin
      Singhal et al. 2013UKParallelType 2 diabetes28/2F/M136/13816Cholesterol, LDL-C, HDL-C, TG, SBP, DBP, glucose, insulin, HOMA-IR.1.6 g DHA4 g olive oil
      Stark et al. 2004CanadacrossoverHealthy volunteers56/7F/M32/324Cholesterol, LDL-C, HDL-C, TG, SBP, DBP, glucose, insulin.2.8 g DHAplacebo
      Tani et al. 2020japanParallelWomen receiving and not receiving Hormone Replacement Therapy63/9F/M30/3024Cholesterol, HDL-C,TG, LDL-C1.8 g EPAN/A
      Tomiyama et al. 2005japanParallelCoronary artery disease patients receiving statin therapy65F/M40/4412Cholesterol, HDL-C, TG, LDL-C, SBP, DBP, glucose.1.8 g EPADiet therapy in consultation with a nutritionist
      Golzari et al. 2017IranParallelPatients with dyslipidemia44/44N/A18/188Cholesterol, HDL-C, TG, LDL-C, SBP, DBP, glucose, HbA1c.2 g EPAplacebo
      Sawada et al. 2016japanParallelType 2 diabetic patients67/8F/M54/5324Cholesterol, HDL-C, TG, LDL-C, SBP, DBP, glucose, HbA1c, HOMA-IR.1.8 g EPAN/A
      Woodman et al. 2002AustraliaParallelPatients with impaired glucose metabolism61/2F/M18/166Cholesterol, HDL-C, TG, LDL-C, glucose, insulin, HbA1c.4 g DHA/4 g EPAOlive oil
      Nomura et al. 2009JapanParallelType 2 diabetic patients with treated hypertension65F/M72/6424Cholesterol, HDL-C, TG, LDL-C, HbA1c.Pitavastatin+ 1.8 g EPAPitavastatin
      Allaire et al. 2019CanadacrossoverHyperlipidemic,55F/M54/5710Cholesterol, HDL-C, TG, LDL-C, SBP, DBP, glucose, insulin.2.7 g EPACorn oil
      Shakouri Mahmoudabadi et al. 2014IranParallelType 2 diabetic patients52F/M20/208Glucose, HbA1c.200 mg vitC +0.5 g EPA200 mg vitC + placebo
      Huerta et al. 2015SpainParallelOverweight and Obese Women38F/M18/2210Glucose, insulin, HOMA-IR.1.3 g EPAplacebo
      TC: total cholesterol, LDL: low density lipoprotein, HDL: high density lipoprotein, TG: triglyceride, SBP: systole blood pressure, DBP: diastolic blood pressure, F: Female, M: Male.
      The quality assessment results of the studies are shown in Supplementary Table 2. The overall evaluation of the risk of bias indicated an unclear risk of bias for 8 articles and a low risk of bias was reported for the rest of the articles.

      3.2 Meta-analysis (network and pair meta-analysis)

      3.2.1 Glucose, Insulin, HbA1c and HOMA-IR

      Pairwise meta-analysis of direct comparisons of DHA and EPA showed significant difference in their effects on plasma glucose (MD EPA versus DHA = −0.31 mg/L; 95% CI: −0.60, −0.02), Insulin (MD EPA versus DHA = −2.14 mg/L; 95% CI: −3.26, −1.02), but the result was not significant for HbA1c (MD EPA versus DHA = −0.12; 95% CI: −0.27, 0.03) (Table 2, Supplementary Fig. 2). Network meta-analysis of all direct and indirect comparisons of DHA and EPA also suggested no significant comparable effects on plasma glucose (MD EPA versus DHA = −0.47 mg/L; 95% CI: −1.33; 0.39), Insulin (MD EPA versus DHA = −1.78 mg/L; 95% CI: −6.73; 3.18), HbA1c (MD EPA versus DHA = −0.34; 95% CI: −1.17; 0.50) and HOMA-IR (MD EPA versus DHA = −0.20; 95% CI: −0.91; 0.51) (Table 2, Fig. 2 and Supplementary Fig. 5).
      Table 2Network estimated the effect of EPA and DHA on cardiovascular risk factors.
      EPADHAControl
      SBP
      EPA−2.46 [−6.90; 1.98]
      −2.48 [−7.47; 2.52]DHA0.02 [−2.28; 2.32]
      −2.46 [−6.90; 1.98]0.02 [−2.28; 2.32]Control
      DBP
      EPA−2.46 [−6.90; 1.98]
      −2.48 [−7.47; 2.52]DHA0.02 [−2.28; 2.32]
      −2.46 [−6.90; 1.98]0.02 [−2.28; 2.32]Control
      Glucose
      EPA−0.31 [−1.33; 0.71]−0.08 [−0.91; 0.74]
      −0.47 [−1.33; 0.39]DHA−0.55 [1.10;0.01]
      −0.23 [−1.11; 0.66]−0.65 [1.20; -0.10]Control
      Insulin
      EPA−2.14 [−7.63; 3.35]0.22 [−4.74; 5.18]
      −1.78 [−6.73; 3.18]DHA−1.55 [−4.33; 1.22]
      −0.15 [−5.66; 5.36]−1.55 [−4.33; 1.22]Control
      HbA1c
      EPA−0.12 [−1.05; 0.81]−0.26 [−0.69; 0.17]
      −0.34 [−1.17; 0.50]DHA−0.08 [−0.91; 0.75]
      −0.26 [−0.69; 0.17]−0.29 [−1.21; 0.63]Control
      HOMA-IR
      EPA0.00 [−0.61; 0.61]
      −0.20 [−0.91; 0.51]DHA−0.20 [−0.57; 0.17]
      0.00 [−0.61; 0.61]−0.20 [−0.57; 0.17]Control
      LDL-C
      EPA1.61 [−10.84; 14.06]−8.92 [15.01;2.83]
      −8.51 [16.67;0.35]DHA−1.04 [−7.68; 5.60]
      −7.47 [13.42;1.52]−2.52 [ −9.40; 4.36]Control
      HDL-C
      EPA2.67 [−3.97; 9.31]−2.45 [−5.65; 0.74]
      −0.80 [−5.06; 3.46]DHA−3.26 [−6.63; 0.11]
      −2.23 [−5.50; 1.03]−3.78 [7.27;0.28]Control
      TC
      EPA4.56 [ −8.81; 17.93]−8.43 [-14.80; -2.06]
      −6.70 [−15.30; 1.89]DHA1.66 [ −5.74; 9.06]
      −6.74 [12.94;0.53]−0.03 [ −7.12; 7.05]Control
      TG
      EPA−6.96 [−24.22; 10.29]−12.56 [−26.20; 1.08]
      0.56 [−24.34; 25.47]DHA−22.31 [37.10;7.53]
      −12.71 [−25.90; 0.47]−19.68 [33.83;5.53]Control
      Data are expressed as mean differences represented by a square and 95% CIs.
      Significance is considered as the absence of zero in the range of the confidence interval (CI).
      Figure 2
      Figure 2Network diagrams from network meta-analysis comparing the effect of DHA and EPA in adults on A) SBP, B) DBP, C)Glucose, D)Insulin, E)HbA1c, F)HOMA-IR, G) LDL-C, H) HDL-C, I)TC, J)TG. The size of the nodes is proportional to the number of participants and the thickness of the lines is proportional to the number of studies available for a particular comparison.

      3.2.1 LDL, HDL, TC and TG

      Pairwise meta-analysis of direct comparisons of the effects of DHA and EPA revealed no significant difference on LDL-C (MD EPA versus DHA = 1.61 mg/L; 95% CI: −10.84; 14.06), HDL-C (MD EPA versus DHA = 2.67 mg/L; 95% CI: −3.97; 9.31), TC (MD EPA versus DHA = 4.56 mg/L; 95% CI: −8.81; 17.93), and TG (MD EPA versus DHA = −6.96 mg/L; 95% CI: −24.22; 10.29) (Supplementary Fig. 3 and Table 2). Network meta-analysis of all direct and indirect comparisons of DHA and EPA also suggested significant comparable effects only on LDL-C (MD EPA versus DHA = -8.51 mg/L; 95% CI: −16.67; −0.35). Other lipid profile markers revealed no significant results, HDL-C (MD EPA versus DHA = −0.80 mg/L; 95% CI: −5.06; 3.46), TC (MD EPA versus DHA = −6.70 mg/L; 95% CI: −15.30; 1.89) and TG (MD EPA versus DHA = 0.56 mg/L; 95% CI: −24.34; 25.47) (Table 2, Fig. 2 and Supplementary Fig. 6).

      3.3 Blood pressure outcomes

      The main results of the pairwise meta-analysis are presented as forest plots for SBP and DBP in Supplementary Fig. 1 and Table 2. The main results of the network meta-analysis are presented as interval plots for SBP, and DBP in Table 2, Fig. 2 and Supplementary Fig. 4. Network meta-analysis of all direct and indirect comparisons of DHA and EPA suggested no significant comparable effects of the two modalities on SBP and DBP) MD EPA versus DHA = −2.48 mmHg; 95% CI: −7.47, 2.52 mmHg).

      3.4 Network inconsistency

      To determine the particular influence of any single study on the results, each trial comparison was individually removed from the pairwise meta-analysis and the results are shown in Supplementary Fig. 7. For comparisons in the network meta-analysis, the sidesplitting approach suggested a significant inconsistency for LDL and TC. To assess the presence of inconsistency, we also fit an NMA model similar to leverage plots. The model showed no significant inconsistency for LDL-C and TC (Supplementary Fig. 8).

      3.5 Publication bias

      Publication bias assessment with funnel plot for the primary outcomes did not indicate publication bias in the meta-analysis and was roughly symmetrical.

      4. Discussion

      To our knowledge, the present meta-analysis is the first to quantitatively assess the distinct effects of EPA and DHA on cardiovascular risk factors. Our findings suggest that both EPA and DHA act similarly on the markers under study, with slight changes in plasma glucose, insulin, and LDL-C. The evaluation of inconsistencies in the meta-analysis proved that there were no limitations or biases in the studies evaluated.
      Previous reviews have already demonstrated the protective power of EPA and DHA polyunsaturated fatty acids on cardiovascular events [
      • Lavie C.J.
      • Bernasconi A.
      Impressive results with EPA, but EPA/DHA combinations also reduce cardiovascular outcomes.
      ,
      • Vors C.
      • Allaire J.
      • Mejia S.B.
      • Khan T.A.
      • Sievenpiper J.L.
      • Lamarche B.
      Comparing the effects of docosahexaenoic and eicosapentaenoic acids on inflammation markers using pairwise and network meta-analyses of randomized controlled trials.
      ,
      • Shahidi F.
      • Ambigaipalan P.
      Omega-3 polyunsaturated fatty acids and their health benefits.
      ,
      • Lopez-Huertas E.
      The effect of EPA and DHA on metabolic syndrome patients: a systematic review of randomised controlled trials.
      ,
      • Ghasemi Fard S.
      • Wang F.
      • Sinclair A.J.
      • Elliott G.
      • Turchini G.M.
      How does high DHA fish oil affect health? A systematic review of evidence.
      ,
      • Saini R.K.
      • Keum Y.-S.
      Omega-3 and omega-6 polyunsaturated fatty acids: dietary sources, metabolism, and significance—a review.
      ]. Randomized clinical trials, as well as reviews of these studies, reinforce that supplementation alone or both was effective in reducing CVD [
      • Lavie C.J.
      • Bernasconi A.
      Impressive results with EPA, but EPA/DHA combinations also reduce cardiovascular outcomes.
      ]. However, while the combined results of the RCTs reinforce the cardioprotective power, results of some individual studies do not follow this behaviour [
      • Lavie C.J.
      • Bernasconi A.
      Impressive results with EPA, but EPA/DHA combinations also reduce cardiovascular outcomes.
      ,
      • Vors C.
      • Allaire J.
      • Mejia S.B.
      • Khan T.A.
      • Sievenpiper J.L.
      • Lamarche B.
      Comparing the effects of docosahexaenoic and eicosapentaenoic acids on inflammation markers using pairwise and network meta-analyses of randomized controlled trials.
      ,
      • Shahidi F.
      • Ambigaipalan P.
      Omega-3 polyunsaturated fatty acids and their health benefits.
      ,
      • Lopez-Huertas E.
      The effect of EPA and DHA on metabolic syndrome patients: a systematic review of randomised controlled trials.
      ,
      • Ghasemi Fard S.
      • Wang F.
      • Sinclair A.J.
      • Elliott G.
      • Turchini G.M.
      How does high DHA fish oil affect health? A systematic review of evidence.
      ,
      • Saini R.K.
      • Keum Y.-S.
      Omega-3 and omega-6 polyunsaturated fatty acids: dietary sources, metabolism, and significance—a review.
      ,
      • Cottin S.
      • Sanders T.
      • Hall W.
      The differential effects of EPA and DHA on cardiovascular risk factors.
      ]. It is suggested that these different results can be caused by the different conditions and design of the studies.
      Also, some other studies with a different design compared to our study in order to investigate and evaluate the effects of omega-3 supplementation in the prevention of CVD, show a reduction in the risk of outcomes related to CVD, including myocardial infarction (MI), coronary heart disease (CHD) events, CVD events, and CHD mortality [
      • Bernasconi A.A.
      • Wiest M.M.
      • Lavie C.J.
      • Milani R.V.
      • Laukkanen J.A.
      Effect of omega-3 dosage on cardiovascular outcomes: an updated meta-analysis and meta-regression of interventional trials.
      ,
      • Hu Y.
      • Hu F.B.
      • Manson J.E.
      Marine omega-3 supplementation and cardiovascular disease: an updated meta-analysis of 13 randomized controlled trials involving 127 477 participants.
      ]. In another study with the aim of determining the effectiveness of omega-3 fatty acids on fatal and non-fatal CVD outcomes and investigating the potential difference in the therapeutic effects of EPA monotherapy versus EPA + DHA, the results showed the effect of omega-3 fatty acids on reducing CVD mortality, non-fatal MI, CHD events, and major cardiovascular adverse events. This meta-analysis also reported a higher rate ratios with EPA monotherapy than EPA + DHA for cardiovascular mortality, nonfatal MI, and CHD events. Overall, in this meta-analysis, omega-3 fatty acids were reported to reduce cardiovascular mortality and improve cardiovascular outcomes. Also, cardiovascular risk reduction was greater with EPA monotherapy than EPA + DHA [
      • Khan S.U.
      • Lone A.N.
      • Khan M.S.
      • Virani S.S.
      • Blumenthal R.S.
      • Nasir K.
      • et al.
      Effect of omega-3 fatty acids on cardiovascular outcomes: a systematic review and meta-analysis.
      ]. However, some meta-analysis studies did not report a significant effect of this supplement on CVD outcomes [
      • Rizos E.C.
      • Markozannes G.
      • Tsapas A.
      • Mantzoros C.S.
      • Ntzani E.E.
      Omega-3 supplementation and cardiovascular disease: formulation-based systematic review and meta-analysis with trial sequential analysis.
      ,
      • Yu F.
      • Qi S.
      • Ji Y.
      • Wang X.
      • Fang S.
      • Cao R.
      Effects of omega-3 fatty acid on major cardiovascular outcomes: a systematic review and meta-analysis.
      ].
      There is evidence on the cardioprotective effect of these fatty acids, especially on their combined effects on the reduction of triglyceride and lipoprotein levels, consistent with the findings of this work [
      • Raghu B.
      • Venkatesan P.
      Effect of n-3 fatty acid supplementation on blood glucose, lipid profile and cytokines in humans: a pilot study.
      ,
      • Cottin S.
      • Sanders T.
      • Hall W.
      The differential effects of EPA and DHA on cardiovascular risk factors.
      ,
      • Geovanini G.R.
      • Libby P.
      Atherosclerosis and inflammation: overview and updates.
      ,
      • Marchio P.
      • Guerra-Ojeda S.
      • Vila J.M.
      • Aldasoro M.
      • Victor V.M.
      • Mauricio M.D.
      Targeting early atherosclerosis: a focus on oxidative stress and inflammation. Oxidative medicine and cellular longevity.
      ,
      • Wooten J.S.
      • Biggerstaff K.D.
      • Ben-Ezra V.
      Responses of LDL and HDL particle size and distribution to omega-3 fatty acid supplementation and aerobic exercise.
      ,
      • Zatterale F.
      • Longo M.
      • Naderi J.
      • Raciti G.A.
      • Desiderio A.
      • Miele C.
      • et al.
      Chronic adipose tissue inflammation linking obesity to insulin resistance and type 2 diabetes.
      ]. Some studies reinforce that both fatty acids have similar effects on the reduction of blood lipoproteins [
      • Zatterale F.
      • Longo M.
      • Naderi J.
      • Raciti G.A.
      • Desiderio A.
      • Miele C.
      • et al.
      Chronic adipose tissue inflammation linking obesity to insulin resistance and type 2 diabetes.
      ], however other evidence shows that there are uncertainties due to results skewed towards one or the other fatty acid [
      • Mori T.A.
      • Burke V.
      • Puddey I.B.
      • Watts G.F.
      • O'Neal D.N.
      • Best J.D.
      • et al.
      Purified eicosapentaenoic and docosahexaenoic acids have differential effects on serum lipids and lipoproteins, LDL particle size, glucose, and insulin in mildly hyperlipidemic men.
      ].
      About this, in this work, we found that the administration of EPA caused higher reductions in LDL-C levels when compared to DHA, which this greater reduction in LDL-C by EPA can be caused by the potential anti-inflammatory effect of this form of omega-3 compared to DHA [
      • Cottin S.
      • Sanders T.
      • Hall W.
      The differential effects of EPA and DHA on cardiovascular risk factors.
      ]. Other scientific investigations have reinforced the protective potential of EPA and DHA on inflammatory markers and some studies suggest a causal relationship between inflammation and dysregulation of lipoproteins, especially LDL-C [
      • Wooten J.S.
      • Biggerstaff K.D.
      • Ben-Ezra V.
      Responses of LDL and HDL particle size and distribution to omega-3 fatty acid supplementation and aerobic exercise.
      ]. Given the similarity between the protective mechanisms of EPA and DHA, the reasons that distinguish them are unclear, but we can assume that differences in supplementation time, dose or the existence of previous comorbidities may alter the effectiveness of both.
      Furthermore, reductions in serum insulin and plasma glucose were also observed, consistent with findings from epidemiological studies that reported lower prevalence's of glucose intolerance and type 2 diabetes in populations with high fish consumption [
      • Saini R.K.
      • Keum Y.-S.
      Omega-3 and omega-6 polyunsaturated fatty acids: dietary sources, metabolism, and significance—a review.
      ]. Hyperglycaemia and hyperinsulinemia are conditions that can be caused by inflammation in adipose tissue, as well as confer a state of low-grade chronic inflammation and elevations in cardiovascular risk, making them cyclic [
      • Piya M.K.
      • McTernan P.G.
      • Kumar S.
      Adipokine inflammation and insulin resistance: the role of glucose, lipids and endotoxin.
      ]. Like lipoproteins, studies that proposed to investigate the effects of EPA and DHA on plasma glucose and insulin obtained ambiguous and inconclusive results, possibly caused using high doses of fish oil [
      • Lavie C.J.
      • Bernasconi A.
      Impressive results with EPA, but EPA/DHA combinations also reduce cardiovascular outcomes.
      ,
      • Vors C.
      • Allaire J.
      • Mejia S.B.
      • Khan T.A.
      • Sievenpiper J.L.
      • Lamarche B.
      Comparing the effects of docosahexaenoic and eicosapentaenoic acids on inflammation markers using pairwise and network meta-analyses of randomized controlled trials.
      ,
      • Lopez-Huertas E.
      The effect of EPA and DHA on metabolic syndrome patients: a systematic review of randomised controlled trials.
      ,
      • Kelley D.S.
      • Adkins Y.
      Similarities and differences between the effects of EPA and DHA on markers of atherosclerosis in human subjects.
      ,
      • Morishita M.
      • Tanaka T.
      • Shida T.
      • Takayama K.
      Usefulness of colon targeted DHA and EPA as novel diabetes medications that promote intrinsic GLP-1 secretion.
      ,
      • Sarbolouki S.
      • Javanbakht M.H.
      • Derakhshanian H.
      • Hosseinzadeh P.
      • Zareei M.
      • Hashemi S.B.
      • et al.
      Eicosapentaenoic acid improves insulin sensitivity and blood sugar in overweight type 2 diabetes mellitus patients: a double-blind randomised clinical trial.
      ]. However, in a study that aimed to investigate the effects of EPA alone on glycaemia and insulinemia, its protective effect on the reduction of such rates was observed, consistent with the findings of this work [
      • Sarbolouki S.
      • Javanbakht M.H.
      • Derakhshanian H.
      • Hosseinzadeh P.
      • Zareei M.
      • Hashemi S.B.
      • et al.
      Eicosapentaenoic acid improves insulin sensitivity and blood sugar in overweight type 2 diabetes mellitus patients: a double-blind randomised clinical trial.
      ].
      Despite the large number of studies whose findings reinforce ambiguity or inconsistencies in the effects of EPA or DHA alone on cardiovascular risk markers, this review makes use of two robust statistical methods that make it possible to assess these fatty acids directly and indirectly. In this way, the risk of bias or inconsistencies between studies was minimized or even avoided.
      The combined use of two statistically robust methods such as network and paired meta-analyses strengthens the consistency of the findings of this work. Its applications in this study allow the assessment of the risk of bias, as well as the identification of the nature of the association between the outcomes under study and related methods used in the studies included in this review. Furthermore, the application of the network allows an increase in the number of studies and quality of evidence.
      In addition, we acknowledge limitations of the statistical methods of this study include the following: (1) the increased risk of making a type I error that results from testing several exploratory outcomes at an unadjusted significance level of 0.05; (2) the method of splitting shared groups when a study tested multiple interventions or controls only partially overcomes unit-of-analysis error since the multiple interventions included in the analysis remain correlated, and (3) depending on whether transitivity holds for every pairwise comparison, indirect comparisons may suffer from the same potential for bias and confounding as is the case for observational studies.

      5. Conclusion

      Our findings suggest that both EPA and DHA act similarly on the markers under study, with slight changes in plasma glucose, insulin, and LDL-C. The benefits conferred on the EPA mentioned here in this work may result from the number of studies used in the meta-analysis, suggesting that future studies that assess its effects on cardiovascular risk can be carried out for further compilation of the literature.

      Authors' contributions

      F. SH, and Mh. S contributed in conception, design, and statistical analysis. Mh. S, F. Z., E. SH., V. S., P.R., H. KV., and S. F contributed in data collection and manuscript drafting. Mh. S and F. SH supervised the study. All authors approved the final version of the manuscript.

      Funding

      No funding.

      Availability of data and materials

      Data available on request due to privacy/ethical restrictions.

      Ethics approval and consent to participate

      This study was approved by the research council and ethics committee Iran University of Medical Sciences, Tehran, Iran.

      Consent for publication

      Not applicable.

      Declaration of competing interest

      We, the authors, declare that we had no competing interests.

      Appendix A. Supplementary data

      The following is the Supplementary data to this article:

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