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Meta-Analysis
. 2016 Mar 23:6:23625.
doi: 10.1038/srep23625.

Effects of Berries Consumption on Cardiovascular Risk Factors: A Meta-analysis with Trial Sequential Analysis of Randomized Controlled Trials

Affiliations
Meta-Analysis

Effects of Berries Consumption on Cardiovascular Risk Factors: A Meta-analysis with Trial Sequential Analysis of Randomized Controlled Trials

Haohai Huang et al. Sci Rep. .

Abstract

The effects of berries consumption on cardiovascular disease (CVD) risk factors have not been systematically examined. Here, we aimed to conduct a meta-analysis with trial sequential analysis to estimate the effect of berries consumption on CVD risk factors. PubMed, Embase, and CENTRAL were searched for randomized controlled trials (RCTs) that regarding the effects of berries consumption in either healthy participants or patients with CVD. Twenty-two eligible RCTs representing 1,251 subjects were enrolled. The pooled result showed that berries consumption significantly lowered the low density lipoprotein (LDL)-cholesterol [weighted mean difference (WMD), -0.21 mmol/L; 95% confidence interval (CI), -0.34 to -0.07; P = 0.003], systolic blood pressure (SBP) (WMD, -2.72 mmHg; 95% CI, -5.32 to -0.12; P = 0.04), fasting glucose (WMD, -0.10 mmol/L; 95% CI, -0.17 to -0.03; P = 0.004), body mass index (BMI) (WMD, -0.36 kg/m(2); 95% CI, -0.54 to -0.18, P < 0.00001), Hemoglobin A1c (HbA1c) (WMD, -0.20%; 95% CI, -0.39 to -0.01; P = 0.04) and tumor necrosis factor-α (TNF-α) (WMD, -0.99 ρg/mL; 95% CI, -1.96 to -0.02; P = 0.04). However, no significant changes were seen in other markers. The current evidence suggests that berries consumption might be utilized as a possible new effective and safe supplementary option to better prevent and control CVD in humans.

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Figures

Figure 1
Figure 1. Meta-analysis of effects of berries products consumption on lipid parameters (A, TC; B, LDL; C, HDL; D, TG) compared with control arms.
Sizes of data markers indicate the weight of each study in the analysis. WMD, weighted mean difference (the results were obtained from a random-effects model).
Figure 2
Figure 2. TSA on pooled result of effects of berries consumption on lipid profiles.
(A) TSA on pooled result of TC: the cumulative sample size over the RIS of 1,606 and the cumulative Z-curve did not cross both the conventional boundary and the trial sequential monitoring boundary. (B) TSA on pooled result of LDL cholesterol: the cumulative sample size over the RIS of 1,082 and the cumulative Z-curve crossed both the conventional boundary and the trial sequential monitoring boundary for benefit. (C) TSA on pooled result of HDL cholesterol: the cumulative sample size over the RIS of 1,792 and the cumulative Z-curve did not cross both the conventional boundary and the trial sequential monitoring boundary. (D) TSA on pooled result of TG: the cumulative sample size over the RIS of 1,192 and the cumulative Z-curve did not cross both the conventional boundary and the trial sequential monitoring boundary. RIS, required information size.
Figure 3
Figure 3. Meta-analysis of effects of berries consumption on BP (A, SBP; B, DBP) compared with control arms.
Sizes of data markers indicate the weight of each study in the analysis. WMD, weighted mean difference (the results were obtained from a random-effects model).
Figure 4
Figure 4. Tests for publication bias of effects of berries consumption on lipid profiles (A, TC; B, LDL; C, HDL, D, TG) and BP (E, SBP; F, DBP).

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