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Effects of strawberry intervention on cardiovascular risk factors: a meta-analysis of randomised controlled trials

Published online by Cambridge University Press:  02 April 2020

Qi Gao
Affiliation:
Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
Li-Qiang Qin
Affiliation:
Department of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, People’s Republic of China
Ahmed Arafa
Affiliation:
Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Osaka, Japan Department of Public Health, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt
Ehab S. Eshak
Affiliation:
Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Osaka, Japan Department of Public Health, Faculty of Medicine, Minia University, El-Minya, Egypt
Jia-Yi Dong*
Affiliation:
Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
*
*Corresponding author: Jia-Yi Dong, email [email protected]
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Abstract

We conducted a meta-analysis of randomised controlled trials (RCT) to examine the effects of strawberry interventions on cardiovascular risk factors. We searched multiple databases including PubMed, Web of Science and Scopus to identify eligible studies published before 19 May 2019. The endpoints were blood pressure, total cholesterol (TC), HDL-cholesterol, LDL-cholesterol, TAG, fasting blood glucose, endothelial function and inflammatory factors. Pooled analyses were performed using random- or fixed-effects models according to a heterogeneity test. We also conducted sub-group analyses by baseline endpoint levels. We included eleven RCT in this meta-analysis (six for blood pressure, seven for lipid profile, seven for fasting blood glucose and six for C-reactive protein (CRP)). Overall, the strawberry interventions significantly reduced CRP levels by 0·63 (95 % CI −1·04, −0·22) mg/l but did not affect blood pressure, lipid profile or fasting blood glucose in the main analyses. Our analysis stratified by baseline endpoint levels showed the strawberry interventions significantly reduced TC among people with baseline levels >5 mmol/l (−0·52 (95 % CI −0·88, −0·15) mmol/l) and reduced LDL-cholesterol among people with baseline levels >3 mmol/l (−0·31 (95 % CI −0·60, −0·02) mmol/l). There was little evidence of heterogeneity in the analysis and no evidence of publication bias. In summary, strawberry interventions significantly reduced CRP levels and may improve TC and LDL-cholesterol in individuals with high baseline levels.

Type
Full Papers
Copyright
© The Authors 2020

CVD is the leading cause of morbidity and mortality worldwide(Reference Wang, Naghavi and Allen1). Annually, more than 17 million deaths are attributable to CVD, with these deaths anticipated to increase by 30 % over the next decade(Reference Smith, Collins and Ferrari2). Most CVD are potentially preventable, and it is important to design and implement effective strategies to prevent CVD.

Observational studies have shown fruit consumption was associated with a lower risk for developing total CVD, CHD and stroke(Reference Aune, Giovannucci and Boffetta3). Among kinds of fruits, strawberries are well known for being rich in polyphenol, vitamins and minerals(Reference Giampieri, Forbes-Hernandez and Gasparrini4,Reference Giampieri, Alvarez-Suarez and Battino5) . In fact, strawberries have been ranked as a top source of polyphenol and antioxidant capacity among foods consumed in the USA(Reference Halvorsen, Carlsen and Phillips6). Strawberry polyphenols have been shown to have direct and indirect antimicrobial, anti-allergy and antihypertensive properties, inhibit the activities of some physiological enzymes and receptors and protect from oxidative stress-related diseases(Reference Giampieri, Forbes-Hernandez and Gasparrini4).

The biological and functional properties of strawberries have been studied in animal models(Reference Giampieri, Forbes-Hernandez and Gasparrini4) and extended to humans in a few epidemiological studies(Reference Gaziano, Manson and Branch7Reference Sesso, Gaziano and Jenkins9). In the past decade, emerging interventional trials have been conducted to examine the health effects of strawberries in humans(Reference Zunino, Parelman and Freytag10Reference Amani, Moazen and Shahbazian20). However, most of these trials had small sample sizes, which might have resulted in insufficient statistical power. Additionally, the results varied across studies, with some showing strawberries had a beneficial effect on cardiovascular risk factors whereas others did not. Therefore, we aimed to evaluate the treatment effects of strawberry interventions on cardiovascular risk factors by conducting a meta-analysis of randomised controlled trials (RCT).

Methods

Literature search

This meta-analysis was conducted and reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline for reporting meta-analyses of RCT(Reference Moher, Liberati and Tetzlaff21). Two authors (Q. G. and J.-Y. D.) independently searched PubMed, Web of Science and Scopus for relevant studies published before 19 May 2019. The search was updated on 20 February 2020. The endpoints of interest were blood pressure, total cholesterol (TC), LDL-cholesterol, HDL-cholesterol, TAG, fasting blood glucose, endothelial function and inflammatory factors. The keywords used for the literature search were ‘strawberry’, ‘hypertension’, ‘blood pressure’, ‘lipid’, ‘cholesterol’, ‘LDL’, ‘HDL’, ‘triglyceride’, ‘blood glucose’, ‘endothelial function’, ‘inflammation’ and ‘trial’. The search strategy is shown in the online Supplementary material. We also conducted a manual review of reference lists of the identified studies. No effort was made to retrieve unpublished studies, and there was no restriction to publication date.

Study selection

Studies were selected for analysis if they (1) were RCT (either parallel or crossover); (2) used strawberries as the intervention and had a control group; (3) measured blood pressure, lipid profiles, blood glucose, endothelial function or inflammatory factors at baseline and follow-up and (4) had an intervention longer than 1 week. Studies were excluded if they examined the acute effects of a strawberry intervention within several hours, or when the intervention included fruits other than strawberries.

Data extraction

We extracted the characteristics of each trial included in this meta-analysis. The extracted data included: name of first author, study area, publication year, intervention duration, study design, dose of intervention and control group, sample size, mean age or age range, sex, as well as the mean and standard deviation values for each endpoint at baseline and post-intervention. For studies with more than two follow-up measurements, data from the last follow-up were used. Similarly, for studies with more than two intervention groups, data from the highest dose group were used.

Quality assessment

The quality of the included trials was evaluated using the revised tool for assessing risk of bias in randomised trials(Reference Higgins, Sterne and Savovic22). Each included trial was judged as ‘low risk’, ‘high risk’ or ‘some concerns’ for six aspects: randomisation process, deviations from the intended interventions, missing outcomes, outcome measurement and selection of reported results. An overall risk of bias judgement was then made. Disagreements during study selection, data extraction and quality assessment were resolved by discussion among the authors.

Statistical analysis

For each endpoint, mean net changes between the baseline and follow-up values in the intervention and control groups/periods were calculated. The standard deviations for the net changes were obtained from the original studies or computed using a standard formula(Reference Higgins, Eldridge and Li23). The effect size of the intervention was calculated as the mean difference in the net changes in the intervention and control groups/periods. Heterogeneity between studies was assessed using Cochran’s Q test (P < 0·10 as statistically significant) and the I 2 statistic, which is considered a measure of the inconsistency between studies(Reference Higgins, Thompson and Deeks24). A random-effects model(Reference DerSimonian and Laird25) was used to perform the pooled analysis when P for heterogeneity <0·10; otherwise, a fixed-effects model was selected. We conducted pre-specified stratified analyses and meta-regression analyses by baseline endpoint values to examine whether baseline levels could modify the effects of the intervention. Sensitivity analyses were also performed to test whether individual studies had a considerable impact on the overall results. The risk for publication bias was assessed using Egger’s test(Reference Egger, Davey Smith and Schneider26). A ‘trim and fill’ method(Reference Duval and Tweedie27) was used to correct results when such bias was detected. All analyses were performed using Stata version 12.0.

Results

The flow of the literature search is shown in Fig. 1. The initial search of the electronic databases identified 129 records, but most of these were excluded after scanning the title and abstract. This left twenty-two articles for full-text review. Eleven articles were further excluded because they examined acute effects of a strawberry intervention (n 6), had no outcome of interest (n 2), used cranberries or mixed berries as the intervention (n 2) or had no control group (n 1). Finally, eleven RCT were included in our analysis (blood pressure n 6, lipid profile n 7, blood glucose n 7, C-reactive protein (CRP) n 6). The RCT that used oat bran bread as a control(Reference Jenkins, Nguyen and Kendall13) was not included in the analysis for lipid profile because there is a body of evidence supporting a lipid-lowering effect of oat bran(Reference Hui, Liu and Lang28), and using oat bran as a control may mask the true effect of a strawberry intervention on participants’ lipid profile.

Fig. 1. Flow chart of study selection.

Table 1 shows the characteristics of each included RCT. These eleven trials were published between 2008 and 2017. Seven studies were double-blind RCT, two were single-blind RCT and two were open-label RCT. Six trials used cross-over designs, whereas the others used parallel designs. The interventions included freeze-dried strawberry beverage or powder (n 10) or fresh strawberries (n 1). RCT with a single- or double-blind design used a placebo similar in colour and flavour to strawberries as the control, and the two open-label RCT used oat bran bread or water as a control. The sample size of each RCT was 17–60 participants, with a total of 357 participants in the eleven trials. The intervention duration ranged from 1 to 12 weeks, with a median of 6 weeks. All RCT enrolled middle-aged individuals, except for one trial that enrolled adolescents aged 14–18 years(Reference Djurica, Holt and Ren16). The results of quality assessment of the included RCT are shown in online Supplementary Table S1. In general, most RCT had low risk for overall bias.

Table 1. Characteristics of included randomised controlled trials examining the effects of strawberry intervention on cardiovascular risk factors in men and women

(Mean values and standard deviations; ranges)

X, crossover; SB, single-blind; FDS, freeze-dried strawberries; DB, double-blind.

The results of the pooled analysis examining the effects of the strawberry interventions on blood pressure, lipid profile, blood glucose and CRP levels are shown in Table 2. The main analyses showed that the strawberry interventions significantly reduced CRP levels by 0·63 (95 % CI −1·04, −0·22) mg/l but did not affect blood pressure, lipid profile or fasting blood glucose. There was little evidence of heterogeneity throughout the analyses. The analysis stratified by baseline endpoint levels showed the strawberry interventions led to a significant decrease in TC levels among those with baseline TC levels >5 mmol/l (weighted mean difference −0·52 (95 % CI −0·88, −0·15) mmol/l) (Fig. 2). Similarly, the strawberry interventions significantly reduced LDL-cholesterol among those with baseline LDL-cholesterol levels >3 mmol/l (weighted mean difference −0·31 (95 % CI −0·60, −0·02) mmol/l) (Fig. 3). Tests for publication bias using Egger’s regression showed no evidence of such bias in all endpoints, though the test for TC was borderline significant (Table 2). Correcting the potential bias by the ‘trim and fill’ method obtained the same results for TC.

Table 2. Meta-analysis of randomised controlled trials examining the effects of strawberry intervention on cardiovascular risk factors

(Weighed mean differences and 95 % confidence intervals)

Fig. 2. Meta-analysis on the effects of strawberry intervention on total cholesterol (TC) by the baseline levels. WMD, weighted mean difference.

Fig. 3. Meta-analysis on the effects of strawberry intervention on LDL-cholesterol by the baseline levels. WMD, weighted mean difference.

The results of the meta-regression showed that the baseline values of TC and LDL-cholesterol were associated with the magnitude of the treatment effects (online Supplementary Figs. S1 and S2). In the sensitivity analyses, no single RCT showed a substantial impact on the overall pooled results for each endpoint.

Discussion

This meta-analysis of RCT indicated that the strawberry interventions significantly reduced CRP levels but did not affect blood pressure, lipid profile or fasting blood glucose compared with placebo. However, in the sub-group analysis, the strawberry interventions significantly lowered TC and LDL-cholesterol levels in those with high baseline levels. The results of meta-regression indicated that baseline levels of TC and LDL-cholesterol were associated with the treatment effect of strawberry interventions.

The potential cardio-protective effects of strawberry consumption may be attributed to its richness in polyphenols, folate, vitamin C and minerals(Reference Giampieri, Alvarez-Suarez and Battino5,Reference Giampieri, Tulipani and Alvarez-Suarez29) . Anthocyanins are the best-known polyphenolic compounds in strawberries, which have been shown to have antioxidant, anti-inflammation and cardio-protective properties(Reference Afrin, Gasparrini and Forbes-Hernandez30). Studies in animal and cell models showed that gastric lipase(Reference McDougall and Stewart31) and cholesteryl ester transfer protein(Reference Qin, Xia and Ma32) are necessary for lipid generation. One clinical trial involving 120 patients with dyslipidaemia aged 40–65 years showed that anthocyanins could increase cellular cholesterol efflux to serum and decrease the mass and activity of plasma cholesteryl ester transfer protein(Reference Qin, Xia and Ma32). There was also evidence that anthocyanins may enhance ATP-binding cassette transporter A1 (ABCA1)-mediated cholesterol efflux in macrophages, which in turn can improve lipid profiles(Reference Xia, Hou and Zhu33). Furthermore, a recent meta-analysis of seventeen RCT showed that anthocyanin supplementation led to significant reductions in TAG (−0·10 (95 % CI −0·16, −0·05) mmol/l), LDL-cholesterol (−0·23 (95 % CI −0·29, −0·52) mmol/l) and apoB (−0·14 (95 % CI −0·17, −0·11) μmol/l)(Reference Shah and Shah34).

It was uncertain why baseline levels of TC and LDL-cholesterol were associated with the treatment effects of strawberry interventions. One explanation may be that individuals with higher baseline levels of these lipids could have more room for improvement compared with those with lower baseline levels. However, the results of the sub-group analyses should be interpreted with caution because they were based on a limited number of RCT.

Several prospective cohort studies have examined the association of anthocyanin intakes with risk for CVD. Cassidy et al. reported that a high intake of anthocyanins was associated with a decreased risk for myocardial infarction among 93 600 women (aged 25–42 years) in the Nurses’ Health Study II (hazard ratio (HR) 0·68; 95 % CI 0·49, 0·96)(Reference Cassidy, Mukamal and Liu35). In addition, those authors detected an 8 % decrease in risk for hypertension (HR 0·92; 95 % CI 0·86, 0·98) in the highest quintile of anthocyanin intake compared with the lowest quintile based on three cohorts: Nurses’ Health Study I with 121 700 female nurses aged 30–55 years, Nurses’ Health Study II with 116 430 women aged 25–42 years and Health Professionals Follow-Up Study with 51 529 men aged 40–75 years(Reference Cassidy, O’Reilly and Kay36). The inconsistent results of RCT and cohort studies on blood pressure may be due to biases involved in cohort studies, in particular confounding bias and measurement errors. Mink et al. showed that dietary intake of anthocyanidins was associated with a reduced risk for mortality from CHD, CVD and all-cause death (for any v. no intake: HR 0·88 (95 % CI 0·78, 0·99); HR 0·91 (95 % CI 0·83, 0·99) and HR 0·90 (95 % CI 0·86, 0·95), respectively) in the Iowa Women’s Health Study(Reference Mink, Scrafford and Barraj8). A recent meta-analysis by Kimble et al. showed that intake of dietary anthocyanins reduced the risk for incident CHD (HR 0·91; 95 % CI 0·83, 0·99) and CVD mortality (HR 0·92; 95 % CI 0·87, 0·97)(Reference Kimble, Keane and Lodge37). However, no associations were observed between anthocyanin intake and risk for incident stroke, myocardial infarction or total CVD(Reference Kimble, Keane and Lodge37).

Conversely, evidence from observational studies directly examining the association between strawberry consumption and risk for CVD is limited. The Women’s Health Study that involved 38 176 middle-aged women showed consuming ≥2 servings/week of strawberries compared with no consumption had a non-significant association with a higher risk for CVD throughout a 10 year follow-up (HR 1·27; 95 % CI 0·94, 1·72)(Reference Sesso, Gaziano and Jenkins9). In addition, a cross-sectional analysis of baseline variables in that study showed a slightly reduced likelihood (14 % lower) of having elevated CRP levels among high strawberry consumers(Reference Sesso, Gaziano and Jenkins9). In the Iowa Women’s Health Study (34 489 postmenopausal women aged 55–69 years), higher strawberry consumption was not associated with CHD mortality (HR 0·95; 95 % CI 0·83, 1·08) compared with lower consumption(Reference Mink, Scrafford and Barraj8). Among 1299 older adults that participated in the Massachusetts Health Care Panel study, the consumption of ≥1 serving of fresh strawberries or melons per d v. an intake of <1 serving per d was not associated with risk for CVD mortality (HR 0·70; 95 % CI 0·10, 4·79); however, it is worth mentioning that only 1·2 % of the participants in that study consumed ≥1 serving of fresh strawberries/melons per d(Reference Gaziano, Manson and Branch7). Given the limited evidence regarding strawberry consumption and risk for CVD, large-scale prospective cohort studies are still warranted.

The main strength of our meta-analysis was that all included studies were RCT, which minimised the risk for confounding and recall biases involved in observational studies. However, limitations of our meta-analysis should also be noted. First, the number of included RCT and the sample size of individual trials were limited. Despite the RCT design, there might have been considerable differences in baseline characteristics between the treatment and control groups in cases with a small sample size. For example, in the study by Amani et al. (Reference Amani, Moazen and Shahbazian20), the baseline LDL-cholesterol levels were 2·46 and 3·00 mg/l in the treatment (n 19) and control (n 17) groups, respectively, although the difference was not significant (P = 0·13). Second, the individual trials used various forms of strawberries and different doses as interventions. It remains uncertain whether such differences could result in different treatment effects. However, there was little evidence of heterogeneity across studies for all endpoints. Third, the treatment durations were relatively short (all ≤12 weeks). The long-term effects of the strawberry interventions were therefore not determined. Fourth, publication bias could be a threat to the validity of our findings. Test for such bias in TC was borderline significant, but correcting the bias changed the results little.

In conclusion, the findings of the present meta-analysis of RCT indicated that strawberry interventions significantly reduced CRP levels and may lower TC and LDL-cholesterol in those with higher baseline levels. Because of the limited number of included RCT and small sample sizes, it is premature to recommend strawberries as a dietary therapy for dyslipidaemia. Large-scale RCT are needed to verify our findings.

Acknowledgements

We thank Jennifer Carr for language editing.

This study was supported by Japan Society for the Promotion of Science KAKENHI grant number A18H063910 and T19K214700 to J.-Y. D.

The funders had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; or the decision to submit the manuscript for publication.

Q. G. collected the data, analysed the data and wrote the manuscript. L.-Q. Q., A. A. and E. S. E. conducted the technique review and edited the manuscript. J.-Y. D. designed the study, collected the data, analysed the data and edited the manuscript.

The authors declare that there are no conflicts of interest.

Supplementary material

For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S000711452000121X

References

Wang, H, Naghavi, M, Allen, C, et al. (2016) Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 388, 14591544.CrossRefGoogle Scholar
Smith, SC Jr, Collins, A, Ferrari, R, et al. (2012) Our time: a call to save preventable death from cardiovascular disease (heart disease and stroke). Eur Heart J 33, 29102916.Google Scholar
Aune, D, Giovannucci, E, Boffetta, P, et al. (2017) Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality – a systematic review and dose–response meta-analysis of prospective studies. Int J Epidemiol 46, 10291056.CrossRefGoogle ScholarPubMed
Giampieri, F, Forbes-Hernandez, TY, Gasparrini, M, et al. (2015) Strawberry as a health promoter: an evidence based review. Food Funct 6, 13861398.CrossRefGoogle ScholarPubMed
Giampieri, F, Alvarez-Suarez, JM & Battino, M (2014) Strawberry and human health: effects beyond antioxidant activity. J Agr Food Chem 62, 38673876.CrossRefGoogle ScholarPubMed
Halvorsen, BL, Carlsen, MH, Phillips, KM, et al. (2006) Content of redox-active compounds (ie, antioxidants) in foods consumed in the United States. Am J Clin Nutr 84, 95135.CrossRefGoogle ScholarPubMed
Gaziano, JM, Manson, JE, Branch, LG, et al. (1995) A prospective study of consumption of carotenoids in fruits and vegetables and decreased cardiovascular mortality in the elderly. Ann Epidemiol 5, 255260.CrossRefGoogle ScholarPubMed
Mink, PJ, Scrafford, CG, Barraj, LM, et al. (2007) Flavonoid intake and cardiovascular disease mortality: a prospective study in postmenopausal women. Am J Clin Nutr 85, 895909.CrossRefGoogle ScholarPubMed
Sesso, HD, Gaziano, JM, Jenkins, DJ, et al. (2007) Strawberry intake, lipids, C-reactive protein, and the risk of cardiovascular disease in women. J Am Coll Nutr 26, 303310.CrossRefGoogle ScholarPubMed
Zunino, SJ, Parelman, MA, Freytag, TL, et al. (2012) Effects of dietary strawberry powder on blood lipids and inflammatory markers in obese human subjects. Br J Nutr 108, 900909.CrossRefGoogle ScholarPubMed
Schell, J, Scofield, RH, Barrett, JR, et al. (2017) Strawberries improve pain and inflammation in obese adults with radiographic evidence of knee osteoarthritis. Nutrients 9, 949.CrossRefGoogle ScholarPubMed
Moazen, S, Amani, R, Homayouni Rad, A, et al. (2013) Effects of freeze-dried strawberry supplementation on metabolic biomarkers of atherosclerosis in subjects with type 2 diabetes: a randomized double-blind controlled trial. Ann Nutr Metab 63, 256264.CrossRefGoogle ScholarPubMed
Jenkins, DJ, Nguyen, TH, Kendall, CW, et al. (2008) The effect of strawberries in a cholesterol-lowering dietary portfolio. Metabolism 57, 16361644.CrossRefGoogle Scholar
Feresin, RG, Johnson, SA, Pourafshar, S, et al. (2017) Impact of daily strawberry consumption on blood pressure and arterial stiffness in pre- and stage 1-hypertensive postmenopausal women: a randomized controlled trial. Food Funct 8, 41394149.CrossRefGoogle ScholarPubMed
Ellis, CL, Edirisinghe, I, Kappagoda, T, et al. (2011) Attenuation of meal-induced inflammatory and thrombotic responses in overweight men and women after 6-week daily strawberry (Fragaria) intake. A randomized placebo-controlled trial. J Atheroscler Thromb 18, 318327.CrossRefGoogle ScholarPubMed
Djurica, D, Holt, RR, Ren, J, et al. (2016) Effects of a dietary strawberry powder on parameters of vascular health in adolescent males. Br J Nutr 116, 639647.CrossRefGoogle ScholarPubMed
Burton-Freeman, B, Linares, A, Hyson, D, et al. (2010) Strawberry modulates LDL oxidation and postprandial lipemia in response to high-fat meal in overweight hyperlipidemic men and women. J Am Coll Nutr 29, 4654.CrossRefGoogle ScholarPubMed
Basu, A, Fu, DX, Wilkinson, M, et al. (2010) Strawberries decrease atherosclerotic markers in subjects with metabolic syndrome. Nutrition Res 30, 462469.CrossRefGoogle ScholarPubMed
Basu, A, Betts, NM, Nguyen, A, et al. (2014) Freeze-dried strawberries lower serum cholesterol and lipid peroxidation in adults with abdominal adiposity and elevated serum lipids. J Nutr 144, 830837.CrossRefGoogle ScholarPubMed
Amani, R, Moazen, S, Shahbazian, H, et al. (2014) Flavonoid-rich beverage effects on lipid profile and blood pressure in diabetic patients. World J Diabetes 5, 962968.CrossRefGoogle ScholarPubMed
Moher, D, Liberati, A, Tetzlaff, J, et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339, b2535.CrossRefGoogle ScholarPubMed
Higgins, JPT, Sterne, JAC, Savovic, J, et al. (2016) A revised tool for assessing risk of bias in randomized trials. Cochrane Database Syst Rev, issue 10, 2931.Google Scholar
Higgins, J, Eldridge, S & Li, T (2019) Cochrane Handbook for Systematic Reviews of Interventions. The Cochrane Collaboration. https://training.cochrane.org/handbook/current/chapter-23 (accessed June 2019).Google Scholar
Higgins, JP, Thompson, SG, Deeks, JJ, et al. (2003) Measuring inconsistency in meta-analyses. BMJ 327, 557560.CrossRefGoogle ScholarPubMed
DerSimonian, R & Laird, N (1986) Meta-analysis in clinical trials. Control Clin Trials 7, 177188.CrossRefGoogle ScholarPubMed
Egger, M, Davey Smith, G, Schneider, M, et al. (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315, 629634.CrossRefGoogle ScholarPubMed
Duval, S & Tweedie, R (2000) Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 56, 455463.CrossRefGoogle ScholarPubMed
Hui, S, Liu, K, Lang, H, et al. (2019) Comparative effects of different whole grains and brans on blood lipid: a network meta-analysis. Eur J Nutr 58, 27792787.CrossRefGoogle ScholarPubMed
Giampieri, F, Tulipani, S, Alvarez-Suarez, JM, et al. (2012) The strawberry: composition, nutritional quality, and impact on human health. Nutrition 28, 919.CrossRefGoogle ScholarPubMed
Afrin, S, Gasparrini, M, Forbes-Hernandez, TY, et al. (2016) Promising health benefits of the strawberry: a focus on clinical studies. J Agr Food Chem 64, 44354449.CrossRefGoogle ScholarPubMed
McDougall, GJ & Stewart, D (2005) The inhibitory effects of berry polyphenols on digestive enzymes. Biofactors 23, 189195.CrossRefGoogle ScholarPubMed
Qin, Y, Xia, M, Ma, J, et al. (2009) Anthocyanin supplementation improves serum LDL- and HDL-cholesterol concentrations associated with the inhibition of cholesteryl ester transfer protein in dyslipidemic subjects. Am J Clin Nutr 90, 485492.CrossRefGoogle ScholarPubMed
Xia, M, Hou, M, Zhu, H, et al. (2005) Anthocyanins induce cholesterol efflux from mouse peritoneal macrophages: the role of the peroxisome proliferator-activated receptor {gamma}-liver X receptor {alpha}-ABCA1 pathway. J Biol Chem 280, 3679236801.CrossRefGoogle ScholarPubMed
Shah, K & Shah, P (2018) Effect of anthocyanin supplementations on lipid profile and inflammatory markers: a systematic review and meta-analysis of randomized controlled trials. Cholesterol 2018, 8450793.CrossRefGoogle ScholarPubMed
Cassidy, A, Mukamal, KJ, Liu, L, et al. (2013) High anthocyanin intake is associated with a reduced risk of myocardial infarction in young and middle-aged women. Circulation 127, 188196.CrossRefGoogle Scholar
Cassidy, A, O’Reilly, EJ, Kay, C, et al. (2011) Habitual intake of flavonoid subclasses and incident hypertension in adults. Am J Clin Nutr 93, 338347.CrossRefGoogle ScholarPubMed
Kimble, R, Keane, KM, Lodge, JK, et al. (2019) Dietary intake of anthocyanins and risk of cardiovascular disease: a systematic review and meta-analysis of prospective cohort studies. Crit Rev Food Sci Nutr 59, 30323043.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Flow chart of study selection.

Figure 1

Table 1. Characteristics of included randomised controlled trials examining the effects of strawberry intervention on cardiovascular risk factors in men and women(Mean values and standard deviations; ranges)

Figure 2

Table 2. Meta-analysis of randomised controlled trials examining the effects of strawberry intervention on cardiovascular risk factors(Weighed mean differences and 95 % confidence intervals)

Figure 3

Fig. 2. Meta-analysis on the effects of strawberry intervention on total cholesterol (TC) by the baseline levels. WMD, weighted mean difference.

Figure 4

Fig. 3. Meta-analysis on the effects of strawberry intervention on LDL-cholesterol by the baseline levels. WMD, weighted mean difference.

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