https://orcid.org/0000-0003-4187-7514
Figures
Abstract
Whether food source or energy mediates the effect of fructose-containing sugars on blood pressure (BP) is unclear. We conducted a systematic review and meta-analysis of the effect of different food sources of fructose-containing sugars at different levels of energy control on BP. We searched MEDLINE, Embase and the Cochrane Library through June 2021 for controlled trials ≥7-days. We prespecified 4 trial designs: substitution (energy matched substitution of sugars); addition (excess energy from sugars added); subtraction (excess energy from sugars subtracted); and ad libitum (energy from sugars freely replaced). Outcomes were systolic and diastolic BP. Independent reviewers extracted data. GRADE assessed the certainty of evidence. We included 93 reports (147 trial comparisons, N = 5,213) assessing 12 different food sources across 4 energy control levels in adults with and without hypertension or at risk for hypertension. Total fructose-containing sugars had no effect in substitution, subtraction, or ad libitum trials but decreased systolic and diastolic BP in addition trials (P<0.05). There was evidence of interaction/influence by food source: fruit and 100% fruit juice decreased and mixed sources (with sugar-sweetened beverages [SSBs]) increased BP in addition trials and the removal of SSBs (linear dose response gradient) and mixed sources (with SSBs) decreased BP in subtraction trials. The certainty of evidence was generally moderate. Food source and energy control appear to mediate the effect of fructose-containing sugars on BP. The evidence provides a good indication that fruit and 100% fruit juice at low doses (up to or less than the public health threshold of ~10% E) lead to small, but important reductions in BP, while the addition of excess energy of mixed sources (with SSBs) at high doses (up to 23%) leads to moderate increases and their removal or the removal of SSBs alone (up to ~20% E) leads to small, but important decreases in BP in adults with and without hypertension or at risk for hypertension.
Trial registration: Clinicaltrials.gov: NCT02716870.
Citation: Liu Q, Chiavaroli L, Ayoub-Charette S, Ahmed A, Khan TA, Au-Yeung F, et al. (2023) Fructose-containing food sources and blood pressure: A systematic review and meta-analysis of controlled feeding trials. PLoS ONE 18(8): e0264802. https://doi.org/10.1371/journal.pone.0264802
Editor: Heming Wang, Brigham and Women’s Hospital and Harvard Medical School, UNITED STATES
Received: February 15, 2022; Accepted: June 30, 2023; Published: August 15, 2023
Copyright: © 2023 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This work was supported by Diabetes Canada (CS-5-15-4771-JS) and the Canadian Institutes of Health Research (funding reference number, 129920). The Diet, Digestive tract, and Disease (3-D) Centre, funded through the Canada Foundation for Innovation (CFI) and the Ministry of Research, and Innovation’s Ontario Research Fund (ORF), provided the infrastructure for the conduct of this project. LC was funded by a Mitacs-Elevate Postdoctoral Fellowship Award. SA-C was funded by a CIHR Canadian Graduate Scholarships Master’s Award, the Loblaw Food as Medicine Graduate Award, the Ontario Graduate Scholarship (OGS), and the CIHR Canadian Graduate Scholarship Doctoral Award (funding reference number 476251).TAK was funded by a Toronto 3D Foundation Postdoctoral Fellowship Award. DL was funded by a St. Michael’s Hospital Research Training Centre Scholarship. AZ was funded by a BBDC Postdoctoral Fellowship. AC and AA were funded by Toronto 3D Foundation MSc Scholarship Awards. DJAJ was funded by the Government of Canada through the Canada Research Chair Endowment. JLS was funded by a PSI Graham Farquharson Knowledge Translation Fellowship, Diabetes Canada Clinician Scientist award, CIHR INMD/CNS New Investigator Partnership Prize, and Banting & Best Diabetes Centre Sun Life Financial New Investigator Award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: LC is a Mitacs-Elevate post-doctoral fellow jointly funded by the Government of Canada and the Canadian Sugar Institute. She was previously employed as a casual clinical coordinator at INQUIS Clinical Research, Ltd. (formerly Glycemic Index Laboratories, Inc.), a contract research organization. SA-C has received funding from CIHR Canadian Graduate Scholarship-Master’s, the Loblaw Food as Medicine Award, and the Ontario Graduate Scholarship. AA and AC have received funding from a Toronto 3D MSc Scholarship award. TAK has received research support from the Canadian Institutes of Health Research (CIHR), the International Life Science Institute (ILSI), and National Honey Board. He has been an invited speaker at the Calorie Control Council Annual meeting for which he has received an honorarium. He was funded by a Toronto 3D Postdoctoral Fellowship Award. FA-Y is a part-time Research Assistant at INQUIS Clinical Research, Ltd., a contract research organization. DL reports receiving a stipend from University of Toronto Department of Nutritional Sciences Graduate Student Fellowship, University of Toronto Fellowship in Nutritional Sciences, University of Toronto Supervisor’s Research Grant - Early Researcher Awards, and Dairy Farmers of Canada Graduate Student Fellowships; a scholarship from St. Michael’s Hospital Research Training Centre, and a University of Toronto School of Graduate Studies Conference Grant. AZ is a part-time Research Associate at INQUIS Clinical Research, Ltd., a contract research organization, and has received funding from a BBDC Postdoctoral Fellowship. RJdS has served as an external resource person to the World Health Organization’s Nutrition Guidelines Advisory Group on trans fats, saturated fats, and polyunsaturated fats. The WHO paid for his travel and accommodation to attend meetings from 2012-2017 to present and discuss this work. He has also done contract research for the Canadian Institutes of Health Research’s Institute of Nutrition, Metabolism, and Diabetes, Health Canada, and the World Health Organization for which he received remuneration. He has received speaker’s fees from the University of Toronto, and McMaster Children’s Hospital. He has held grants from the Canadian Foundation for Dietetic Research, Population Health Research Institute, and Hamilton Health Sciences Corporation as a principal investigator, and is a co-investigator on several funded team grants from Canadian Institutes of Health Research. He has served as an independent director of the Helderleigh Foundation (Canada). He serves as a member of the Nutrition Science Advisory Committee to Health Canada (Government of Canada), and is a co-opted member of the Scientific Advisory Committee on Nutrition (SACN) Subgroup on the Framework for the Evaluation of Evidence (Public Health England). TMSW is an employee of INQUIS Clinical Research, Toronto, Canada, and has authored several diet books on the glycaemic index for which he has received royalties from Phillipa Sandall Publishing Services and CABI Publishers; and has received consultant fees, honorariums, travel funding, or research support from or served on the scientific advisory board for Canadian Institutes of Health Research, Canadian Diabetes Association, Dairy Farmers of Canada, McCain Foods, Temasek Polytechnic, Northwestern University, Royal Society of London, Glycemic Index Symbol programme, CreaNutrition AG, McMaster University, Canadian Society for Nutritional Sciences, National Sports and Conditioning Association, Faculty of Public Health and Nutrition—Autonomous University of Nuevo Leon, and Diabetes and Nutrition Study Group of the European Association for the Study of Diabetes. CWCK has received grants or research support from the Advanced Food Materials Network, Agriculture and Agri-Foods Canada, Almond Board of California, American Pistachio Growers, Barilla, Calorie Control Council, Canadian Institutes of Health Research, Canola Council of Canada, International Nut and Dried Fruit Council, International Tree Nut Council Research and Education Foundation, Loblaw Brands, Pulse Canada, Saskatchewan Pulse Growers and Unilever; has received in-kind research support from the Almond Board of California, American Peanut Council, Barilla, California Walnut Commission, Kellogg Canada, Loblaw Companies, Quaker (PepsiCo), Primo, Unico, Unilever, WhiteWave Foods; has received travel support or honorariums from the American Peanut Council, American Pistachio Growers, Barilla, California Walnut Commission, Canola Council of Canada, General Mills, International Nut and Dried Fruit Council, International Pasta Organization, Loblaw Brands Ltd, Nutrition Foundation of Italy, Oldways Preservation Trust, Paramount Farms, Peanut Institute, Pulse Canada, Sabra Dipping, Saskatchewan Pulse Growers, Sun-Maid, Tate & Lyle, Unilever and White Wave Foods; has served on the scientific advisory board for the International Tree Nut Council, International Pasta Organization, Lantmannen, McCormick Science Institute, Oldways Preservation Trust, Paramount Farms and Pulse Canada; is a member of the International Carbohydrate Quality Consortium, executive board member of the Diabetes and Nutrition Study Group of the European Association for the Study of Diabetes; is on the Clinical Practice Guidelines Expert Committee for Nutrition Therapy of the European Association for the Study of Diabetes; and is a director of the Toronto 3D Knowledge Synthesis and Clinical Trials Foundation. DJAJ has received research grants from Saskatchewan & Alberta Pulse Growers Associations, the Agricultural Bioproducts Innovation Program through the Pulse Research Network, the Advanced Foods and Material Network, Loblaw Companies Ltd., Unilever Canada and Netherlands, Barilla, the Almond Board of California, Agriculture and Agri-food Canada, Pulse Canada, Kellogg’s Company, Canada, Quaker Oats, Canada, Procter & Gamble Technical Centre Ltd., Bayer Consumer Care, Springfield, NJ, Pepsi/Quaker, International Nut & Dried Fruit Council (INC), Soy Foods Association of North America, the Coca-Cola Company (investigator initiated, unrestricted grant), Solae, Haine Celestial, the Sanitarium Company, Orafti, the International Tree Nut Council Nutrition Research and Education Foundation, the Peanut Institute, Soy Nutrition Institute (SNI), the Canola and Flax Councils of Canada, the Calorie Control Council, the Canadian Institutes of Health Research (CIHR), the Canada Foundation for Innovation (CFI)and the Ontario Research Fund (ORF). He has received in-kind supplies for trials as a research support from the Almond board of California, Walnut Council of California, American Peanut Council, Barilla, Unilever, Unico, Primo, Loblaw Companies, Quaker (Pepsico), Pristine Gourmet, Bunge Limited, Kellogg Canada, WhiteWave Foods. He has been on the speaker’s panel, served on the scientific advisory board and/or received travel support and/or honoraria from 2020 China Glycemic Index (GI) International Conference, Atlantic Pain Conference, Academy of Life Long Learning, the Almond Board of California, Canadian Agriculture Policy Institute, Loblaw Companies Ltd, the Griffin Hospital (for the development of the NuVal scoring system), the Coca-Cola Company, Epicure, Danone, Diet Quality Photo Navigation (DQPN), Better Therapeutics (FareWell), Verywell, True Health Initiative (THI), Heali AI Corp, Institute of Food Technologists (IFT), Soy Nutrition Institute (SNI), Herbalife Nutrition Institute (HNI), Saskatchewan & Alberta Pulse Growers Associations, Sanitarium Company, Orafti, the American Peanut Council, the International Tree Nut Council Nutrition Research and Education Foundation, the Peanut Institute, Herbalife International, Pacific Health Laboratories, Nutritional Fundamentals for Health (NFH), Barilla, Metagenics, Bayer Consumer Care, Unilever Canada and Netherlands, Solae, Kellogg, Quaker Oats, Procter & Gamble, Abbott Laboratories, Dean Foods, the California Strawberry Commission, Haine Celestial, PepsiCo, the Alpro Foundation, Pioneer Hi-Bred International, DuPont Nutrition and Health, Spherix Consulting and WhiteWave Foods, the Advanced Foods and Material Network, the Canola and Flax Councils of Canada, Agri-Culture and Agri-Food Canada, the Canadian Agri-Food Policy Institute, Pulse Canada, the Soy Foods Association of North America, the Nutrition Foundation of Italy (NFI), Nutra-Source Diagnostics, the McDougall Program, the Toronto Knowledge Translation Group (St. Michael’s Hospital), the Canadian College of Naturopathic Medicine, The Hospital for Sick Children, the Canadian Nutrition Society (CNS), the American Society of Nutrition (ASN), Arizona State University, Paolo Sorbini Foundation and the Institute of Nutrition, Metabolism and Diabetes. He received an honorarium from the United States Department of Agriculture to present the 2013 W.O. Atwater Memorial Lecture. He received the 2013 Award for Excellence in Research from the International Nut and Dried Fruit Council. He received funding and travel support from the Canadian Society of Endocrinology and Metabolism to produce mini cases for the Canadian Diabetes Association (CDA). He is a member of the International Carbohydrate Quality Consortium (ICQC). His wife, Alexandra L Jenkins, is a director and partner of INQUIS Clinical Research for the Food Industry, his 2 daughters, Wendy Jenkins and Amy Jenkins, have published a vegetarian book that promotes the use of the foods described here, The Portfolio Diet for Cardiovascular Risk Reduction (Academic Press/Elsevier 2020 ISBN:978-0-12-810510-8)and his sister, Caroline Brydson, received funding through a grant from the St. Michael’s Hospital Foundation to develop a cookbook for one of his studies. JLS has received research support from the Canadian Foundation for Innovation, Ontario Research Fund, Province of Ontario Ministry of Research and Innovation and Science, Canadian Institutes of health Research (CIHR), Diabetes Canada, PSI Foundation, Banting and Best Diabetes Centre (BBDC), American Society for Nutrition (ASN), INC International Nut and Dried Fruit Council Foundation, National Dried Fruit Trade Association, National Honey Board (the U.S. Department of Agriculture [USDA] honey “Checkoff” program), International Life Sciences Institute (ILSI), Pulse Canada, Quaker Oats Center of Excellence, The United Soybean Board (the USDA soy “Checkoff” program), The Tate and Lyle Nutritional Research Fund at the University of Toronto, The Glycemic Control and Cardiovascular Disease in Type 2 Diabetes Fund at the University of Toronto (a fund established by the Alberta Pulse Growers), and The Nutrition Trialists Fund at the University of Toronto (a fund established by an inaugural donation from the Calorie Control Council). He has received in-kind food donations to support a randomized controlled trial from the Almond Board of California, California Walnut Commission, Peanut Institute, Barilla, Unilever/Upfield, Unico/Primo, Loblaw Companies, Quaker, Kellogg Canada, WhiteWave Foods/Danone, and Nutrartis. He has received travel support, speaker fees and/or honoraria from Diabetes Canada, Dairy Farmers of Canada, FoodMinds LLC, International Sweeteners Association, Nestlé, Pulse Canada, Canadian Society for Endocrinology and Metabolism (CSEM), GI Foundation, Abbott, General Mills, Biofortis, ASN, Northern Ontario School of Medicine, INC Nutrition Research & Education Foundation, European Food Safety Authority (EFSA), Comité Européen des Fabricants de Sucre (CEFS), Nutrition Communications, International Food Information Council (IFIC), Calorie Control Council, and Physicians Committee for Responsible Medicine. He has or has had ad hoc consulting arrangements with Perkins Coie LLP, Tate & Lyle, Wirtschaftliche Vereinigung Zucker e.V., Danone, and Inquis Clinical Research. He is a member of the European Fruit Juice Association Scientific Expert Panel and former member of the Soy Nutrition Institute (SNI) Scientific Advisory Committee. He is on the Clinical Practice Guidelines Expert Committees of Diabetes Canada, European Association for the study of Diabetes (EASD), Canadian Cardiovascular Society (CCS), and Obesity Canada/Canadian Association of Bariatric Physicians and Surgeons. He serves or has served as an unpaid scientific advisor for the Food, Nutrition, and Safety Program (FNSP) and the Technical Committee on Carbohydrates of ILSI North America. He is a member of the International Carbohydrate Quality Consortium (ICQC), Executive Board Member of the Diabetes and Nutrition Study Group (DNSG) of the EASD, and Director of the Toronto 3D Knowledge Synthesis and Clinical Trials foundation. His wife is an employee of AB InBev. QL, AC, SBM, VLC, and LAL declare no competing interests. There are no products in development or marketed products to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Abbreviations: BP, blood pressure; CI, confidence interval; GRADE, grading of recommendations assessment, development, and evaluation; MD, mean difference; MID, minimally important difference; PICOTS, population, intervention, comparator, outcome, time and study design; PRISMA, Reporting Items for Systematic Reviews and Meta-Analysis; SD, standard deviation; SE, standard error; SSB, sugar-sweetened beverages
Introduction
Cardiovascular diseases are the leading cause of death globally, claiming the lives of 17.9 million people each year, or 32% of deaths worldwide [1]. Chronically elevated blood pressure (BP), also known as hypertension, is a leading modifiable risk factor for these diseases [2]. The global prevalence of hypertension has been increasing in the past decades [3]. A purported contributor to this increase in hypertension is the intake of sugars with a particular focus on fructose since it is thought to act as an unregulated substrate for de novo lipogenesis, bypassing negative feedback control, unlike its glucose counterpart [4–10]. Fructose has been implicated as a driver of hypertension as well as the development of obesity and diabetes [9, 11, 12], both of which further contribute to hypertension and its downstream complications [13]. The proposed mechanisms are supported by animal models, ecological studies, and some fructose over-feeding trials using levels of exposure well beyond population intakes, which have limited application to human health [14].
Emerging evidence indicates that the effect of fructose-containing sugars (sucrose, high-fructose corn syrup, fructose) is mediated by the food source in which they are consumed and the level of energy control. Systematic reviews and meta-analyses have shown that fructose-containing sugars providing excess energy, especially as sugar-sweetened beverages (SSBs), are associated with increased risk of obesity [15, 16], metabolic syndrome [17], diabetes [18], gout [19], and cardiovascular disease [20] in prospective cohort studies and increases in related intermediate cardiometabolic risk factors in controlled feeding trials [21–25]; whereas these adverse signals are not seen for other important food sources or total fructose in energy-matched substitution for other carbohydrates which would replace them as part of food reformulation strategies to reduce these sugars.
We have conducted a series of systematic reviews and meta-analyses to address these questions in relation to hypertension. We recently showed that in prospective cohort studies, SSBs are associated with increased risk of hypertension [26, 27], whereas total fructose intake at moderate doses [28] or other important foods sources [26] do not show the same relationship with higher intakes of fruit and yogurt, and moderate intake of 100% fruit juice even associated with lower risk of hypertension [26]. We also showed that in controlled feeding trials, total fructose (independent of food sources) in energy-matched substitution for other carbohydrates does not increase blood pressure (BP) and even decreases diastolic blood pressure and mean arterial pressure [29]. To complete this series, we aim to clarify the extent to which food source mediates the effect of fructose-containing sugars on blood pressure in controlled clinical trials. Therefore, we conducted a systematic review and meta-analysis of controlled trials of the effect of different food sources of fructose-containing sugars at different levels of energy control on blood pressure and assessed the certainty of evidence using GRADE.
Methods
We followed the Cochrane Handbook for Systematic Reviews of Interventions (version 6.3) [30] for the conduct of our systematic review and meta-analysis and reported our results following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [31] (S1 Table in S1 File). The study protocol is registered at ClinicalTrials.gov (NCT02716870). All relevant data are within the manuscript and its S1 File.
Data sources and search strategy
We conducted a systematic search in MEDLINE, Embase, and the Cochrane Central Register of Controlled Studies databases through June 28th, 2021. S2, S3 Tables in S1 File present the search strategy based on the PICOTS framework; there were no language restrictions. Validated filters from the McMaster University Health Information Research Unit were applied to limit the database search to controlled studies only [32]. Manual searches of the reference lists of included studies complemented the systematic search.
Study selection
We included randomized and non-randomized controlled feeding trials in humans of all health backgrounds and ages, with intervention periods ≥7 days investigating the effect of orally consumed fructose-containing sugars from various food sources compared with control diets free of or lower in fructose-containing sugars on systolic or diastolic blood pressure. We excluded studies of liquid meal replacement interventions and studies of interventions or comparators of rare sugars that contain fructose (e.g., isomaltulose, melezitose, or turanose) or were low calorie epimers of fructose (e.g., allulose, tagatose, sorbose). Reports were initially excluded based on review of their titles and abstracts by a single reviewer. Those reports that remained were then excluded based on review of the full text reports by at least 2 reviewers (QL, SA-C, DL, LC, FAY, AC, XQ, AA), leaving the final set of reports to be included in our syntheses. We prespecified four study design levels based on energy control: 1) ’substitution’ or isocaloric trials, in which energy from the food sources of fructose-containing sugars was substituted for other non-fructose-containing macronutrients under energy matched conditions; 2) ’addition’ trials, in which excess energy from the food sources of fructose-containing sugars was added to the background diet compared to the same diet alone without the excess energy (with or without the use of non-nutritive/low-calorie sweeteners to match sweetness); 3) ’subtraction’ trials, in which energy from the food sources of fructose-containing sugars was subtracted from background diets compared with the original background diets through displacement by water or low-calorie sweeteners or elimination altogether; and 4) ’ad libitum’ trials, in which energy from the food sources of fructose-containing sugars was freely replaced (that is, the participants could eat as much or as little as they like within reasonable limits e.g. intake required to be between 75 and 125% of predicted daily energy requirements) with other non-fructose-containing macronutrients without any strict control of either the study foods or the background diets, allowing for free replacement of energy. In reports containing more than one eligible trial comparison (a unique comparison between an intervention and control group in a trial), we included each available trial comparison.
Data extraction
At least two reviewers (QL, SA-C, LC, AA) independently extracted data from eligible studies. Relevant information included food source of fructose-containing sugars, number of participants, setting, participant health status, study design, level of feeding control, randomization, comparator, fructose-containing sugars type, macronutrient profile of the diets, follow-up duration, energy balance, funding source and outcome data. S4 Table in S1 File shows the definitions for the different food sources of fructose-containing sugars. Authors were contacted for missing outcome data when it was indicated that blood pressure was measured but not reported. In the absence of outcome data and inability to obtain the original data from authors, values were extracted from figures using Plot Digitizer [33] where available.
Risk of bias assessment
Included studies were assessed for risk of bias independently and in duplicate by ≥2 reviewers (QL, SA-C, LC, AA) using the Cochrane Risk of Bias Tool [30]. Assessment was done across six domains of bias (sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting and other). Risk of bias for each domain was assessed as either “low” (proper methods taken to reduce bias), “high” (improper methods creating bias) or “unclear” (insufficient information provided). The “other” domain applied only to crossover trials; “high” risk of bias was given when there was no washout between interventions, otherwise the trial was rated as “low”. Reviewer discrepancies were resolved by consensus or arbitration by the senior author (JLS).
Outcomes
The outcomes were systolic and diastolic blood pressure. Mean differences (MDs) between the intervention and control arm and their standard errors (SEs) were extracted for each eligible trial comparison (each unique comparison between an intervention and control group in a trial). If unavailable, they were derived from available data using published formulas [30]. Mean pairwise difference in change-from-baseline values were preferred over end values. When median data was provided, they were converted to mean data with corresponding variances using methods developed by Luo et al. (2018) [34] and Wan et al. (2014) [35]. When no variance data was available, the standard deviation (SD) was borrowed from a trial similar in size, participants and nature of intervention [36].
Data syntheses and analyses
We used Stata software, version 16.1 (StataCorp, College Station, TX, USA) for all analyses. As our primary research question was to assess the effect of different food sources of fructose-containing sugars at different energy control levels, we performed separate pairwise meta-analyses for each of the four prespecified designs by energy control level (substitution, addition, subtraction and ad libitum trials) and assessed the interaction between food sources of fructose-containing sugars within each energy control level using the Cochrane Handbook’s recommended standard Q-test for subgroup differences (significance at P<0.10) [37–39].
The principal effect measures were the mean pair-wise differences in change-from-baseline (or alternatively, end differences) between the food sources of fructose-containing sugars arm and the comparator arm (significance at P<0.05). Data were analyzed using the generic inverse variance method with DerSimonian and Laird random-effects model [30, 40]. A fixed effects model was used when <5 trial comparisons were available [41]. Paired analyses were applied to all crossover trials with the use of a within-individual correlation coefficient between treatment of 0.5 as described by Elbourne et al. to calculate SEs [42–44]. Data were expressed as MDs with 95% confidence intervals (CIs). To mitigate a unit-of-analysis error, when arms of trials with multiple intervention or control arms were used more than once, the corresponding sample size was divided by the number of times it was used for calculation of the standard error [30].
Heterogeneity was assessed by visual inspection of the forest plots and using the Cochrane Q statistic and quantified using the I2 statistic [30]. We considered an I2≥50% and PQ<0.10 as evidence of substantial heterogeneity [30]. Sources of heterogeneity were explored by sensitivity analyses, including individual trial influence, altering pairwise comparison correlation coefficient and subgroup analyses. The influence analysis systematically removed each trial comparison from the meta-analysis with recalculation of the summary effect estimate. A trial whose removal explained the heterogeneity or changed the significance, direction, or magnitude (by more than the minimally important difference (MID) for systolic/diastolic BP, 2mmHg [45]) of the effect was considered an influential trial. To determine whether the overall results were robust to the use of different correlation coefficients in crossover trials, we also conducted sensitivity analyses using correlation coefficients of 0.25 and 0.75. If ≥10 trials were available [38, 46] we conduced subgroup analyses to explore sources of heterogeneity using meta-regression (significance at P<0.05). A priori subgroup analyses were conducted by participant health status, age, anti-hypertensive medication use, randomization, energy balance, baseline outcome levels, fructose sugars type, comparator type, study design, follow-up, feeding control, fructose-containing sugars dose, and funding. Post-hoc subgroup analyses were conducted by sugars regulatory designation and type of imputation done for deriving variances. Meta-regression analyses were used to assess the significance of each subgroup categorically and, when applicable, continuously.
If ≥6 trial comparisons were available [47], we assessed the effect modification by dose using meta-regression with linear and non-linear (using restricted cubic splines) dose-response gradients (significance at P<0.05). Non-linear dose-response gradients were estimated using restricted cubic splines with default knots set at the 15th, 50th and 85th percentiles of the exposure variable as recommended by Harrell [48] and assessed for departure from linearity. We also assessed non-linear dose-response threshold effects with three prespecified spline knots at public health thresholds of 5% [49, 50], 10% [50, 51], and 25% [52] total energy (%E).
If ≥10 trials were available, we assessed for small-study effects (publication bias) by visual inspection of contour-enhanced funnel plots and formal testing with Egger’s [53] and Begg’s [54] tests (significance at P<0.10) [55]. If there was evidence of publication bias, we adjusted for funnel plot asymmetry and assessed for small-study effects by imputing the missing trial data using the Duval and Tweedie trim-and-fill method [56].
Certainty of the evidence
The certainty of the evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach and software (GRADEpro GDT, McMaster University and Evidence Prime Inc., Hamilton, Canada) [57]. The assessments were conducted by at least two independent reviewers (QL, SA-C, LC, AA) and discrepancies were resolved by consensus or arbitration by the senior author (JLS). The evidence was rated as high, moderate, low, or very low certainty. The included controlled trials were initially rated as high certainty by default and then downgraded or upgraded based on pre-specified criteria. Reasons for downgrading the evidence included risk of bias (assessed by the Cochrane Risk of Bias Tool [58]), inconsistency (substantial unexplained inter-study heterogeneity, I2>50% and P<0.10), indirectness (presence of factors that limit the generalizability of the results), imprecision (the 95% CI for effect estimates overlap the MID [2mmHg for systolic BP and diastolic BP] for benefit or harm), and publication bias (significant evidence of small study effects). The reason for upgrading the evidence was presence of a significant dose-response gradient [59–64]. We then used the MIDs to assess the importance of the magnitude of our point estimates using the effect size categories according to GRADE guidance [57, 65–67] as follows: large effect (≥5x MID); moderate effect (≥2x MID); small important effect (≥1x MID); and trivial/unimportant effect (< 1 MID).
Results
Search results
Fig 1 shows the flow of the literature. We retrieved 10,505 reports from databases and manual searches, 10,156 of which were excluded based on the title or abstract. Of the 327 reports reviewed in full text, 93 reports of controlled feeding trials (147 trial comparisons, N = 5,213) met the eligibility criteria [68–160]. These trials included twelve different food sources of fructose-containing sugars (SSBs; sweetened dairy; sweetened dairy alternative [soy]; 100% fruit juice; fruit; dried fruit; mixed fruit forms; sweetened cereal grains and bars; sweets and desserts; added nutritive [caloric] sweetener; and mixed sources [with SSBs], and mixed sources [without SSBs]) across four energy control levels: substitution (72 trial comparisons); addition (64 trial comparisons); subtraction (10 trial comparisons); and ad libitum (6 trial comparisons). The mixed sources (without SSBs) food category includes those trials in which the intervention included more than one of the food sources, excluding SSBs (e.g., sweets and desserts and fruits). Out of the fifteen authors who were contacted for missing blood pressure outcome data, nine responded and provided unpublished data [71, 85, 86, 106, 117, 124, 136, 141, 156].
Trial characteristics
Table 1 and S5 Table in S1 File show the trial characteristics. Trial sizes ranged from a median of 11 participants (range 9–50) in ad libitum trials to 109 participants (range 12–240) in subtraction trials. Participants were a mix of adults with and without hypertension or at risk for hypertension (overweight/obesity or diabetes). There were approximately equal ratios of both sexes for substitution and addition trials with slightly more women than men, but there were proportionally more females for subtraction and ad libitum trials. Most participants were young adults with ages ranging from a median of 28 (range: 22–42) years in subtraction trials to 40 (range: 8–63) years in substitution trials. Most trials were conducted in an outpatient setting (80–100%), performed in American and European countries, and were parallel in design (53% in substitution, 64% in addition, 90% in subtraction, and 17% in ad libitum trials). Feeding control was mostly supplemented for substitution (65%), addition (84%), and subtraction (50%) trials, and metabolic for most ad libitum (67%) trials. Most studies were randomized (75%-100%), except ad libitum trials (33%). The dose of fructose-containing sugars ranged from a median of 6.7% (1–26%) in addition trials to 23% (23–23%) of total energy intake in ad libitum trials. The follow-up duration ranged from a median of two weeks (range 2–6.5 weeks) in ad libitum trials to 26.1 weeks (15.5–35.8 weeks) in subtraction trials. Most trials were funded by industry sources for substitution trials (65%), agency sources for addition trials (government, not-for-profit health agency, or university sources) (63%), agency and industry sources for ad libitum trials (83%), and subtraction trials were mostly funded by agency and industry (30%) or failed to reported funding sources (30%). The comparators for substitution trials were mostly mixed comparator (23/72, 32%) followed by starch (19/72, 26%) and glucose (17/72, 24%), diet alone for addition trials (43/64, 67%), non-nutritive sweetener for subtraction (6/10, 60%) and starch for ad libitum trials (3/6, 50%). The main food sources for substitution trials were SSBs (16/72, 22%) and mixed sources (with SSBs) (13/72, 18%). The main food sources for addition trials were SSBs (17/64, 27%) followed by 100% fruit juice (16/64, 25%) and fruit (16/64, 25%). SSBs were also the main food source for subtraction (8/10, 80%) and mixed sources (with SSBs) in ad libitum trials (6/6, 100%).
Risk of bias
S1-S4 Figs in S1 File show a summary of the risk of bias (ROB) assessments of the included trials. Most trials were assessed as having unclear ROB in random sequence generation (75/147, 51%), allocation concealment (94/147, 64%), and incomplete outcome data domains (91/147, 62%) due to poor reporting, while most were low ROB in blinding (88/147, 60%) and selective outcome reporting (84/147, 57%) domains. Most cross-over trials were assessed as having high ROB in the “other” (carry-over effects) domain (32/62, 52%). Few studies were assessed as having high ROB, for random sequence generation (39/147, 27%), allocation concealment (24/147, 16%), blinding of participants and personnel (6/147, 4%), incomplete outcome data (1/147, 0.6%), selective outcome reporting (5/147, 3%), and other (carry-over effects) (32/147, 22%) ROB domains, respectively. Thus, there was no overall serious ROB in any trial comparisons except for in ad libitum trials for diastolic BP where 4 of the 6 trials had high ROB for sequence generation and allocation concealment (due to not being randomized).
Systolic blood pressure
Fig 2 presents an overall summary of the effects of different food sources of fructose-containing sugars on systolic BP at four levels of energy control. S5-S8 Figs in S1 File present the individual forest plots for each level of energy control. Total fructose-containing sugars resulted in a reduction in systolic BP for addition trials (64 trials; MD: -2.23mmHg; 95% CI: -3.40, -1.06mmHg, PMD<0.001; substantial heterogeneity, I2 = 69.3%, PQ<0.001), whereas there was no effect in substitution trials (72 trials; MD: -0.33mmHg; 95% CI: -1.16, 0.51mmHg; PMD = 0.445; no substantial heterogeneity, I2 = 39.4%, PQ = 0.001), subtraction trials (10 trials; MD: -1.16mmHg; 95% CI: -2.90, 0.57mmHg; PMD = 0.188; substantial heterogeneity, I2 = 82.2%, PQ<0.001), or ad libitum trials (6 trials; MD: 0.98mmHg; 95% CI: -0.43, 2.39mmHg; PMD = 0.173; no heterogeneity, I2 = 0.0%, PQ = 0.902).
Data are weighted mean differences (95% confidence intervals). The bolded lines present the effect estimates for total fructose-containing sugars on SBP at each of the 4 levels of energy control. Where there was significant interaction or influence by food source, effect estimates for each individual food source are presented. Analyses were conducted by generic, inverse variance random effects models (at least five trials available) or fixed effects models (fewer than five trials available). Between-study heterogeneity was assessed by the Cochran Q statistic, where PQ<0.100 is considered statistically significant, and quantified by the I2 statistic, where I2≥50% is considered evidence of substantial heterogeneity. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) of randomized controlled trials are rated as "High" certainty of evidence and can be downgraded by five domains and upgraded by one domain. The white squares represent no downgrades, while filled black squares indicate a single downgrade or upgrades for each outcome, and the black square with a white “2” indicates a double downgrade for each outcome. CI = confidence interval; DRM, dose response model; GRADE = Grading of Recommendations, Assessment, Development and Evaluation; MD = mean difference; N = number; SSB = sugar-sweetened beverage; SBP = systolic blood pressure. a For the interpretation of the magnitude, we used the MIDs to assess the importance of magnitude of our point estimate using the effect size categories according to new GRADE guidance. * Where there was a significant interaction by food source (in substitution and addition trials), or influence by food source (in subtraction and ad libitum trials where SSBs and/or Mixed sources (with SSBs) were the sole food sources), we performed the GRADE analysis for each individual food source. †Not upgraded for dose-response (see S8 Table in S1 File for details). ‡The interpretation of the magnitude of the effect was based on the inverse linear dose-response gradient (see S8 Table in S1 File for details).
An interaction by food source was detected in the substitution trials (P = 0.089), although none of the food sources showed an effect on systolic BP. An interaction by food source was also detected in addition trials (P<0.001): mixed sources (with SSBs) resulted in an increase in systolic BP (1 trial; MD: 6.90mmHg; 95% CI: 2.22, 11.58; PMD = 0.004), while 100% fruit juice resulted in a reduction in systolic BP (16 trials; MD: -3.74mmHg; 95% CI: -5.28, -2.20mmHg; PMD<0.001; substantial heterogeneity, I2 = 53.5%, PQ = 0.006) and fruit resulted in a reduction in systolic BP (16 trials; MD: -6.37mmHg; 95% CI: -9.21, -3.52mmHg; PMD<0.001; substantial heterogeneity, I2 = 68.7%, PQ<0.001), whereas no other food sources showed an effect on systolic BP with variable directions of effect. Although we were unable to assess interaction by food source for systolic BP in subtraction and ad libitum trials, there was evidence of influence by food source on systolic BP. In subtraction trials, the removal of mixed sources (with SSBs) resulted in a reduction in systolic BP (2 trials; MD: -2.26mmHg; 95% CI: -2.79, -1.76mmHg; PMD<0.001; substantial heterogeneity, I2 = 96.7%, PQ<0.001). The lack of effect on systolic BP was specific to a single food source (SSBs) in ad libitum trials.
Diastolic blood pressure
Fig 3 presents an overall summary of the effects of different food sources of fructose-containing sugars on diastolic BP at four levels of energy control. S9-S12 Figs in S1 File present the individual forest plots for each level of energy control. Total fructose-containing sugars resulted in a reduction in diastolic BP in addition trials (64 trials; MD: -1.15mmHg; 95% CI: -1.98, -0.32mmHg, PMD = 0.007; substantial heterogeneity, I2 = 58.4%, PQ<0.001), whereas there was no effect in substitution trials (72 trials; MD: 0.12mmHg; 95% CI: -0.53, 0.78mmHg; PMD = 0.714; substantial heterogeneity, I2 = 59.1%, PQ<0.001), subtraction trials (10 trials; MD: -0.09mmHg; 95% CI: -0.74, 0.57mmHg; PMD = 0.796; substantial heterogeneity, I2 = 61.7%, PQ = 0.005), or ad libitum trials (6 trials; MD: 1.14mmHg; 95% CI: -0.66, 2.93mmHg; PMD = 0.214; no heterogeneity, I2 = 0.0%, PQ = 0.619).
Data are weighted mean differences (95% confidence intervals). The bolded lines present the effect estimates for total fructose-containing sugars on DBP at each of the 4 levels of energy control. Where there was significant interaction or influence by food source, effect estimates for each individual food source are presented. Analyses conducted by generic, inverse variance random effects models (at least five trials available) or fixed effects models (fewer than five trials available). Between-study heterogeneity was assessed by the Cochran Q statistic, where PQ<0.100 is considered statistically significant, and quantified by the I2 statistic, where I2≥50% is considered evidence of substantial heterogeneity. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) of randomized controlled trials are rated as "High" certainty of evidence and can be downgraded by five domains and upgraded by one domain. The white squares represent no downgrades, while filled black squares indicate a single downgrade or upgrades for each outcome, and the black square with a white “2” indicates a double downgrade for each outcome. CI = confidence interval; DBP = diastolic blood pressure; GRADE = Grading of Recommendations, Assessment, Development and Evaluation; MD = mean difference; N = number; SSB = sugar-sweetened beverage. a For the interpretation of the magnitude, we used the MIDs to assess the importance of magnitude of our point estimate using the effect size categories according to new GRADE guidance. *Where there was a significant interaction by food source (in substitution and addition trials) or influence by food source (in subtraction and ad libitum trials where SSBs and/or Mixed sources (with SSBs) were the sole food sources), we performed the GRADE analysis for each individual food source. †Not upgraded for dose-response (see S8 Table in S1 File for details).
An interaction by food source was detected in addition trials (P<0.001) for diastolic BP: mixed sources (with SSBs) resulted in an increase in diastolic BP (1 trial; MD: 5.30mmHg; 95% CI: 1.11, 9.49mmHg; PMD = 0.013), while 100% fruit juice resulted in a reduction in diastolic BP (16 trials; MD: -2.06mmHg; 95% CI: -3.47, -0.66mmHg; PMD = 0.004; no substantial heterogeneity, I2 = 47.2%, PQ = 0.019) and fruit resulted in a reduction in diastolic BP (16 trials; MD: -3.88mmHg; 95% CI: -5.72, -2.04mmHg; PMD<0.001; substantial heterogeneity, I2 = 55.1%, PQ = 0.004), whereas no other food sources showed an effect on diastolic BP with variable directions of effect. There was no evidence of an interaction by food source in substitution trials or subtraction trials, and we were unable to assess an interaction by food source in ad libitum trials for diastolic BP. There was, however, evidence of influence by food source on diastolic BP in subtraction and ad libitum trials. The lack of effect on diastolic BP was specific to a single food source (mixed sources [with SSBs]) in ad libitum trials and 2 food sources (SSBs and mixed sources [with SSBs]) in subtraction trials.
Sensitivity analyses
S13-S20 Figs in S1 File present the influence analyses for total fructose-containing sugars at the 4 levels of energy control. Removal of single trial comparisons resulted in a gain of significance for the reduction in systolic BP in subtraction trials [119] and increase in diastolic BP in ad libitum trials [145] and provided a partial explanation of the evidence of substantial heterogeneity for systolic BP in subtraction trials (Vazquez-Duran et al. 2016 water arm [114]) and diastolic BP in substitution trials [110].
S21-S46 Figs in S1 File present the influence analyses for individual food sources for those analyses that showed evidence of an interaction or influence by food source. Removal of single trial comparisons resulted in a gain of significance for the reduction in systolic BP for fruit [142] and dried fruit [137] in substitution trials and for the reduction in systolic BP for the removal of SSBs [119] and resulted in a change in the direction of effect (Vazquez-Duran et al. 2016 NSBs arm [114]) for diastolic BP in subtraction trials. Removal of single trial comparisons also provided a partial explanation of the evidence of substantial heterogeneity for the effect of fruit on systolic BP in substitution trials [110], 100% fruit juice on systolic BP in addition trials [118, 140] and sweets and desserts on diastolic BP in addition trials [101].
S6 Table in S1 File shows sensitivity analyses for the different correlation coefficients (0.25 and 0.75) used in paired analyses of crossover trials. The use of these different correlation coefficients did not alter the direction, magnitude, or significance of the effect or evidence for heterogeneity for any outcomes across food sources and levels of energy control. The exceptions were the use of a correlation of 0.75 which led to a significant reduction for the effect of added nutritive (caloric) sweetener on systolic BP in substitution trials (7 trials; MD: -1.85mmHg; 95% CI: -3.56, -0.13mmHg; PMD = 0.035, I2 = 0.00%, PQ = 0.587) and a significant increase for the effect of mixed sources (without SSBs) on systolic BP in substitution trials (3 trials; MD: 2.63mmHg; 95% CI: 0.87, 4.40mmHg; PMD = 0.004, I2 = 0.00%, PQ = 0.889) and of 0.25 which led to a partial explanation of heterogeneity for the effect of fruit on diastolic BP in addition trials (16 trials; MD: -4.14mmHg; 95% CI: -5.97, -2.31; PMD<0.001, I2 = 47.45%, PQ = 0.018).
Subgroup analyses
S47-S58 Figs in S1 File present the subgroup analyses for the effect of important food sources of fructose-containing sugars, where there were at least 10 trial comparisons, on blood pressure. In the 4 analyses for systolic BP and diastolic BP in either substitution or addition trials, there was significant effect modification of the following in 3 of the 4 analyses: fructose-containing sugars type (fruit decreased BP while others generally showed no effect or harmful effect), regulatory designation (naturally occurring decreased BP while others generally showed no effect or harmful effect) and dose (<10%E decreased blood pressure, while other generally showed no effect); the following in 2 of 4 analyses: baseline blood pressure, medication use (mixed decrease, others no effect) and follow up (≤8wks decrease, >8wks no effect); the following in 1 of the 4 analyses: age, funding, type of mean difference, risk of bias categories, feeding control, and comparator. For subtraction trials, there was significant effect modification on systolic BP and diastolic BP in at least one of the following: design, follow-up, and risk of bias (selective outcome reporting).
S59-S76 Figs in S1 File present the subgroup analyses for the effect of individual food sources, where there was a significant interaction or influence by food source and at least 10 trial comparisons, on blood pressure. For systolic BP in substitution trials, SSBs, fruit and mixed sources (with SSBs), and in addition analyses for both systolic BP and diastolic BP, SSBs, 100% fruit juice and fruit were analyzed. In all analyses except for SSBs on systolic BP in addition trials, there was significant effect modification in at least one of the following: funding, age, health status, baseline systolic BP or diastolic BP, follow-up, risk of bias categories, antihypertensive medication use, design, and dose.
S77-S83 Figs in S1 File present the continuous meta regression analyses for the effect of important food sources of fructose-containing sugars on blood pressure. In both substitution and addition trials, baseline systolic BP or diastolic BP were significant. Where baseline blood pressure level increased, important food sources of fructose-containing sugars had a greater reduction in blood pressure. There was also a significant continuous meta regression for age in substitution trials on diastolic BP, and in addition trials on systolic BP where with increasing age, important food sources of fructose-containing sugars had a greater reduction in blood pressure.
S83-S91 Figs in S1 File present the continuous meta regression analyses for the effect of individual food sources including SSBs, fruit, mixed sources (with SSBs) for systolic BP in substitution trials, and SSBs, 100% fruit juice and fruit in addition analyses for both systolic and diastolic BP. In substitution trials for systolic BP, there was a negative association for baseline SBP for both fruit and mixed sources (with SSBs), for follow-up for fruit and for dose for mixed sources (with SSBs). In addition trials for systolic and diastolic BP, there was a positive association for dose for fruit, while there was a negative association for follow-up for 100% fruit juice for systolic BP only.
Dose response analyses
S92-S128 Figs in S1 File present linear and non-linear dose-response analyses. For substitution trials, although there was no dose response of total fructose-containing sugars, when assessed by food sources, there was an inverse linear dose response for the effect of mixed sources (with SSBs) on systolic BP (P = 0.009, S100 Fig, panel F in S1 File) where greater reductions were seen with larger doses, however this was no longer significant with the removal of one trial with a dose of nearly 60%E (P = 0.204) [111]. For addition trials, there was a significant positive linear dose response gradient for the effect of total fructose-containing sugars on systolic BP and diastolic BP (coeflinear:0.34; 95% CI, 0.21 to 0.47, Plinear<0.001, S93 Fig in S1 File; coeflinear: 0.24; 95% CI, 0.13 to 0.34, Plinear<0.001, S97 Fig in S1 File, respectively), and when assessed by food source, there was a positive linear dose response for the effect of fruit on systolic BP and diastolic BP in addition trials (16 trials, coeflinear: 4.8mmHg; 95% CI: 1.2 to 8.5, Plinear = 0.009, S101 Fig panel D in S1 File, and coeflinear: 3.4mmHg; 95% CI: 0.8 to 6.1, Plinear = 0.012, per serving (5%E) of fruit, S103 Fig, panel D in S1 File, respectively) where greater reductions were seen with smaller doses; however reductions were seen in systolic and diastolic BP across the entire dose response range. There was a dose response at the public health threshold of 25% E for the effect of SSBs sugars dose on systolic BP in addition trials (17 trials, P = 0.038, S119 Fig in S1 File); however, there was only 1 trial with a dose >25% E. For subtraction trials, there was a significant linear dose response for the effect of removal of SSBs on systolic BP (8 trials, coeflinear: -2.66mmHg; 95% CI: -4.28 to -1.03, Plinear = 0.001, per serving (355ml, 8%E) of SSB, S102 Fig in S1 File) where greater reductions were seen with greater removal of SSBs. There was also a non-linear u-shaped dose response for the effect of the removal of SSBs on diastolic BP in subtraction trials (8 trials, P = 0.003, S104 Fig in S1 File) and at the public threshold of 5% and 10% of energy (8 trials, P = 0.031, for each, S128 Fig in S1 File).
Publication bias
S129-S144 Figs in S1 File present the publication bias assessments for all outcomes.
There was evidence of funnel plot asymmetry for the effect of SSBs on diastolic BP in addition trials (Egger’s test P = 0.036). Adjustment for funnel plot asymmetry with the imputation of 13 missing trials by The Duval and Tweedie trim-and-fill method, however, did not alter the magnitude or significance of the effect, suggesting that there was no meaningful influence of publication bias on the results. Publication bias could not be assessed in ad libitum comparisons, or for certain food sources where there was significant interaction by food source, as there were <10 trials available for these analyses.
GRADE assessment
Figs 2, 3 and S7, S8 Tables in S1 File present the GRADE assessments. To support GRADE assessments, additional post-hoc subgroup analyses to further explore indirectness (S145-S159 Figs in S1 File) on blood pressure methodology, fasted state, and outcome consideration were conducted and did not show any evidence of effect modifications either in analyses for total fructose containing sugars or across food sources (where applicable). The certainty of evidence for the effect of total fructose-containing sugars on systolic BP was low in substitution trials (no effect) and very low in addition (moderate reduction), subtraction (no effect), and ad libitum (no effect) trials, owing to double downgrades for indirectness across the 4 levels of energy control and single downgrades for inconsistency in addition trials and imprecision in addition, subtraction and ad libitum trials. The certainty of evidence for the effect of total fructose-containing sugars on diastolic BP was high for substitution trials (no effect), low for subtraction (no effect) and very low for addition (trivial reduction) and ad libitum trials (no effect), owing to double downgrades for indirectness in addition, subtraction and ad libitum trials and single downgrades for risk of bias (ad libitum), inconsistency (addition) or imprecision (ad libitum).
Because there was a significant interaction by food source in substitution trials for systolic BP and addition trials for systolic BP and diastolic BP and influence of individual food sources in subtraction trials and ad libitum trials, we assessed the certainty of evidence for individual food sources in these analyses. The certainty of evidence was moderate for the effect of mixed sources (with SSBs) on systolic BP in addition trials (moderate increase), owing to a single downgrade for indirectness, high for the effect of 100% fruit juice in addition trials (small important reduction) and moderate for the effect of fruit in addition trials (moderate reduction), owing to a single downgrade for inconsistency. The certainty of evidence was low for the effect of mixed sources (with SSBs) on diastolic BP in addition trials (moderate increase), owing to downgrades for indirectness and imprecision, and moderate for the effects of 100% fruit juice in addition trials (small important reduction) and fruit in addition trials (small important reduction), owing to single downgrades for imprecision and inconsistency, respectively. The certainty of the evidence was high for the effect of removing SSBs on systolic BP in subtraction trials (small important reduction) owing to a downgrade for imprecision and an upgrade for linear dose response, and very low for the effects of removing mixed sources (with SSBs) on systolic BP in subtraction trials (small important reduction). The certainty of evidence varied from high to low for all other food sources owing to downgrades for risk of bias, inconsistency, indirectness, and/or imprecision.
Discussion
Our systematic review and meta-analysis of 93 reports (147 trial comparisons) in 5,213 in participants with and without hypertension or at risk for hypertension assessed the effects of 12 different food sources (SSBs; sweetened dairy; sweetened dairy alternative [soy]; 100% fruit juice; fruit; dried fruit; mixed fruit forms; sweetened cereal grains and bars; sweets and desserts; added nutritive [caloric] sweetener; mixed sources [with SSBs] and mixed sources [without SSBs]) with a median dose of 7% (1–26%) to 23% (23–23%) of total energy across four different levels of energy control over median follow-up of 2–26 weeks. Total fructose-containing sugars led to small important reductions of 2.2mmHg in systolic BP and trivial reductions of 1.15mmHg in diastolic BP in addition trials. There was no effect at the other levels of energy control in substitution, addition, subtraction, or ad libitum trials. There was an interaction or influence by food source. 100% fruit juice and fruit at lower doses that did not exceed the public health threshold of ~10% E led to small important reductions (-3.7mmHg in systolic and -2.06mmHg in diastolic BP) and moderate reductions (-6.37mmHg in systolic and -3.88mmHg in diastolic BP), respectively, in addition trials. On the other hand, mixed sources (with SSBs) at high doses providing 23% excess energy led to moderate increases of 6.9 mmHg in systolic BP and 5.3 mmHg in diastolic BP in addition trials and the removal of a median 5% of excess energy from mixed sources (with SSBs) led to small important reductions (-2.2mmHg) in systolic BP in subtraction trials. The removal of a median of 15% excess energy from SSBs also led to small important reductions in systolic BP with evidence of a linear dose response gradient (removal of one serving (355ml, 8%E) of SSBs was associated with a systolic BP reduction of 2.2 mmHg) in subtraction trials. Other important food sources of fructose-containing sugars showed no effect on BP.
Findings in relation to the literature
Our findings are in agreement with a previous systematic review and meta-analysis by Ha et al. [29] in that they did not demonstrate an adverse effect of total fructose-containing sugars on blood pressure. However, Ha et al. [29] demonstrated beneficial reductions on diastolic BP and mean arterial pressure when fructose-containing sugars were substituted for other carbohydrates in energy-matched conditions and no effects on systolic BP or diastolic BP in addition trials, whereas our findings showed no effect on either systolic BP or diastolic BP in energy-matched conditions, but a benefit when consumed as excess calories, which was driven by the effects of fruit and fruit juice. The discrepancy in findings may be the result of the much large number of trials included in the present analysis (72 substitution and 64 addition trials compared to 13 and 2, respectively). Further, another systematic review and meta-analysis found that substitutions of free sugars, as defined by the WHO [49], for complex carbohydrates had no significant effects on blood pressure [161], agreeing with our findings.
Although the moderate harmful effects of mixed sources (with SSBs) on systolic BP and diastolic BP in addition trials were based on only one trial, we also found significant beneficial dose response effects of removing SSBs from the diet in subtraction trials on systolic BP (based on 8 trials). However, we did not find a significant effect of SSBs alone on either systolic BP or diastolic BP in addition trials. The lack of effect of SSBs in addition trials compared to the observed linear dose response effect in subtraction trials of SSBs may be due to the shorter duration (median 3-wk, range 2-26wk vs median 26-wk, range 1-52wk, respectively) and more normal body weight of the study participants (14/17 trials in normal mixed weight adults, 3/17 overweight or obese vs 3/8 in normal mixed weight adults, 3/8 overweight or obese and 2/8 overweight/obese with either high or low liver fat, respectively). The findings of the potential harmful effect of SSBs are supported by previous literature connecting SSB intake and hypertension and high blood pressure. Our previous systematic review and meta-analysis of prospective cohorts found a significant 10% dose response increase in risk of incident hypertension per 1-serving (355 mL)/day SSB intake, with a wide coverage of cohorts [26]. Other recent systematic reviews and meta-analyses have identified similar associations between SSBs intake and incident hypertension [162–164]. Most proposed mechanisms from analyses of both observational and clinical trials link SSBs consumed as excess calories directly to other adverse health conditions like type 2 diabetes [165, 166] and weight gain [15], which secondarily raise blood pressure. However, SSBs consumed as excess energy has been shown to increase blood uric acid [22], which is a commonly proposed pathway by which fructose intake may lead to hypertension [4–6, 8–10].
We found that fructose-containing sugar doses of up to 10% daily energy intake consumed in the form of fruit demonstrated beneficial linear dose response effects on blood pressure across the dose response range, with greater reductions seen with smaller doses and diminishing as doses increase. This dose relationship has been seen with cohort studies examining fruit and vegetable intake and incident hypertension [167–169]. The evidence of beneficial effects of fruit concur with recent systematic reviews and meta-analyses, including our previous one that showed a significant dose response of a 6% decrease in risk of incident hypertension per 240g serving /day of fruit intake [26]. One popular hypothesis of the beneficial effects of fruit consumption pertains to their high flavonoid contents [170]. These flavonoids have been shown to decrease endothelial dysfunction, inflammation and oxidative stress—important factors in the development of hypertension–as well as decrease blood pressure [171–175]. Various fruits are also rich in potassium with small amounts of magnesium and calcium, the combination of which has been shown to decrease blood pressure [176]. Ensuring adequate potassium intake, via the inclusion of fruits in the diet, can help individuals achieve a lower blood pressure, particularly in individuals with hypertension [177].
The beneficial effect of 100% fruit juice we found on blood pressure is likely due to the same nutrients and bio-compounds as found in fruit though the lack of fiber, the intake of which is also linked to lower blood pressure [178, 179], may explain our findings of 100% fruit juice’s smaller reductions on blood pressure compared to fruit. However, it is worth noting that our prior systematic review and meta-analysis found a U-shaped dose-dependent relationship between incident hypertension and 100% fruit juice intake, with maximum protection shown around 0.5–1 serving (50–150 mL)/day intake and suggestion of harmful associations over 200 mL/day intake. A recent systematic review and meta-analysis found a similar dose-dependent relationship of 100% fruit juice intake in prospective cohorts with cardiovascular event risk with the benefit-harm threshold at 170 mL/day [180]. The authors attributed the benefit of 100% fruit juice to the significant decrease in both systolic BP and diastolic BP they also identified in randomized controlled trials [180]. Thus, there may be potential for harmful effects on blood pressure at higher doses of 100% fruit juice intake that is not captured in our current analysis.
Furthermore, the predominant subgroup effects we identified (i.e., significant effect modification by: fructose-containing sugar type, regulatory designation, and dose) in substitution and addition trials seem to support the food sources interactions observed, as they capture the significant effects of fruit and 100% fruit juice as natural sources of sugars where the source is fruit, and these studies generally were lower doses compared to studies of other food sources.
Historically, the link between fructose and hypertension comes from animal models where animals were fed high fructose diets (>60%E), mainly as free fructose, to induce hypertension and insulin resistance [6]. In addition to the evidence from animal models, there are some human trials demonstrating that acute ingestion of very high doses of fructose or fructose-containing sugars (~12–15%E as a single bolus) increases blood pressure postprandially [181, 182]. The present study only included trials with >1-week intervention, thus was not designed to explore the acute postprandial effects of different food sources of fructose-containing sugars. However, the present study did not demonstrate evidence of harm in the range of 1–52 weeks (median 6-weeks) follow-up period. Evidence from one study provided an exception where mixed sources (with SSBs) consumed at high doses providing 23% excess energy in addition to the habitual diet, led to an increase in blood pressure. The results of this study highlight that the effect of energy and not fructose per se should be considered to be of importance for longer term effect. Furthermore, there is a lack of evidence that fructose consumption is associated with an elevated risk of developing hypertension over the long term (median 18-years), particularly if consumed at less than 10%E [28]. In exploring potential effect modification by follow-up duration in our subgroup analyses, follow-up duration was only significant in the subgroup analysis of the effect of fruit in substitution trials of SBP (trials with >8-weeks follow-up duration showed a significant reduction in SBP, whereas trials with ≤8-weeks showed no statistically significant effect). In continuous analyses, we found a significant negative association for fruit on SBP in substitution trials and 100% fruit juice on SBP in addition trials (where greater follow-up was associated with greater reduction in SBP). Although it appears there is some benefit with longer follow-up, this was not consistent across the food sources analyzed and we were unable to conduct these analyses for most food sources owing to inadequate trial comparisons (<10 trial comparisons).
Since there are metabolic differences between free fructose and glucose, and possibly when bound as the disaccharide sucrose, in our subgroup analyses, we did include an assessment of effect modification by fructose type where we compared trials of sucrose, HFCS and free fructose. In our trials of SSBs, neither in substitution nor addition analyses, did we see significant effect modification by fructose type. This is supported by reviews showing no harmful effects (including on blood pressure and other cardiovascular risk factors) of HFCS, sucrose or fructose alone, when consumed isocalorically (energy matched conditions) [14, 21, 23, 24, 29]. When it comes to food sources, the dose, food matrix, and other aspects within the foods (e.g. bioactives) influence the effect, as we observed reductions in BP for fruit and 100% fruit juice.
Altogether, our results highlight the importance of considering whole foods or dietary patterns, rather than just nutrients (i.e. fructose or fructose-containing sugars), and the energy conditions under which these foods are consumed. There is limited evidence to suggest intakes of food sources of fructose-containing sugars are harmful on blood pressure. The exception where we see a harmful increase in blood pressure is when mixed sources (with SSBs) are consumed as excess calories in addition to the participants habitual diet, in comparison to the control group where participants are consuming only their habitual diet. Conversely, the removal of mixed sources (with SSBs), or of SSBs alone, from the habitual diet, as a reduction in calories, compared to participants still consuming these foods, resulted in a reduction in BP. Therefore, when it comes to mixed sources (with SSBs), the effects on blood pressure are likely mediated by energy and not fructose itself. Most other food sources of fructose-containing sugars showed no effect, except fruit and 100% fruit juice which showed reductions in BP, likely due to the dose of fructose-containing sugars (<10%E), the food matrix, and the contribution of bioactive compounds.
Strengths and limitations
Our systematic review and meta-analysis has several strengths. First, we conducted a comprehensive and reproducible search and selection process of the literature examining the effect of food sources of fructose-containing sugars on blood pressure. Second, we collated and synthesized the totality of available evidence from a large body (93 studies, 147 trial comparisons, N = 5,213) of controlled intervention studies, which give the greatest protection against bias. Third, we had comprehensive exploration of possible sources of heterogeneity. Fourth, we evaluated the shape and strength of the dose-response relationships. Fifth, we assessed the overall quality of evidence using the GRADE assessment approach.
Our analyses also presented limitations. First, our diastolic BP ad libitum analysis was downgraded for serious ROB due to 4 of the 6 trials not being randomized and sensitivity analyses revealing a difference in effect where those 4 trials with high ROB increased diastolic BP whereas the overall pooled effect showed no effect. Second, there was evidence of very serious indirectness resulting in double downgrades in all overall pooled analyses of total fructose-containing sugars for substitution and addition trials, except for diastolic BP in substitution trials, due to significant interaction or influence of food source. Another source of very serious indirectness was the limited number of food sources of fructose-containing sugars available for some analyses. Subtraction and ad libitum trials were double downgraded due to having only one or two food sources available (SSBs and/or mixed sources (with SSBs)), limiting the ability to assess differences in food sources, and thus it is unclear whether these effects hold for other important food sources of fructose-containing sugars. The differences in methodologies used to measure blood pressure, whether measurements were taken in the fasted state, and whether blood pressure was considered a primary or secondary outcome are additional potential sources of indirectness. We performed post-hoc subgroup analyses (S145-S159 Figs in S1 File) on blood pressure methodology, fasted state, and outcome consideration and did not find any evidence of effect modifications either in analyses for total fructose containing sugars or across food sources (where applicable), so we did not downgrade for serious indirectness in any of these cases. Third, some analyses (e.g., fruit in addition analyses) were downgraded for serious inconsistency due to substantial unexplained heterogeneity. Lastly, some analyses were downgraded for imprecision due to crossing the prespecified minimally importance difference for harm or benefit as we cannot rule out clinically important benefit and/or harm.
Weighing the strengths and limitations, the certainty of evidence was generally moderate (moderate to low) for the increasing effect of mixed sources (with SSBs) and moderate (moderate to high) for the decreasing effect of 100% fruit juice and fruit in addition trials, high for the decreasing effect of the removal of SSBs in subtraction trials, very low for the decreasing effect of the removal of mixed sources (with SSBs), and moderate (low to high) for the effect of all other comparisons on systolic and diastolic BP.
Implications
As dietary guidelines shift toward a more food-based approach, our findings may have implications for guiding recommendations on the prevention and management of high blood pressure. Although not all individuals meet the hypertension cut-offs at ≥140 mmHg systolic BP and/or ≥90 mmHg diastolic BP, even prehypertensive individuals (systolic BP of 120–139 mmHg or diastolic BP of 80–90 mmHg) are at significantly higher risk for cardiovascular risks and complications [183–189]. Therefore, there is a need to develop preventative and treatment strategies for hypertension, as well as prehypertension. Our findings demonstrate the importance of focusing on specific foods and the energy conditions under which they are consumed, rather than prescribing limits on total fructose-containing sugars. Currently, guidelines generally recommend adhering to a DASH or Mediterranean diet abundant in fruits, vegetables, whole grains, and plant proteins, and limited in sweets and sugar-sweetened beverages [190–194]. We found that the effect of consuming fruit on systolic BP in addition conditions was beyond the -2 mmHg minimally important benefit for blood pressure, which translates to a 10% lower risk of stroke mortality and 7% lower risk of mortality from other vascular causes [45]. Thus, an emphasis on fresh fruit alongside a limitation on SSBs should be a centerpiece in current dietary guidelines for the prevention and management of high blood pressure. Our research also supports the differentiation between added and natural sugars in dietary guidelines, given that our research indicates benefit on blood pressure from moderate intakes of 100% fruit juice which contains only natural sugars.
Conclusion
In conclusion, the effect of fructose-containing sugars on blood pressure appears to be mediated by both energy control and food source. The addition of excess energy from mixed sources (with SSBs) at high doses (up to 23%) increases, while the removal of excess energy (up to ~20% E) from SSBs and mixed sources (with SSBs) reduces systolic and diastolic BP, whereas fruit and 100% fruit juice at low doses (up to or less than the public health threshold of ~10% E) reduce systolic and diastolic BP. These effects were not seen for other important food sources of fructose-containing sugars at any level of energy control. Our confidence in the estimates is generally moderate. The available evidence provides a good indication that fruit and 100% fruit juice at low doses lead to small important reductions in BP, while the addition of mixed sources (with SSBs) at high doses leads to moderate increases and their removal or the removal of SSBs alone, leads to small important decreases in this population. The main sources of uncertainty across the analyses were indirectness and imprecision. There remains a need for more high-quality randomized trials assessing a broader variety of food sources of fructose-containing sugars to provide more precise estimates. In the meantime, these findings suggest policy and guideline makers should consider the role of energy and food source for the prevention and management of hypertension and continue to encourage SSBs reduction strategies.
Acknowledgments
Aspects of this work were presented at The Canadian Nutrition Society’s Thematic 2021 Online Conference (22–23 January 2021); American Society for Nutrition’s Nutrition 2021 Live Online (7–10 June 2021); and The Diabetes and Nutrition Study Group’s 38th International Symposium on Diabetes and Nutrition, (21–24 June 2021).
We would like to acknowledge the following authors for sending unpublished data to be included in this research: Dr. Panu K. Luukkonen; Dr. Richard Mattes; Fredrik H. Nystrom, MD, PhD; and Desiree M. Sigala, PhD.
References
- 1.
WHO. Cardiovascular disease (CVDs) 2021 [Available from: https://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds).
- 2. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020;396(10258):1223–49. pmid:33069327
- 3.
WHO. Hypertension 2021 [Available from: https://www.who.int/news-room/fact-sheets/detail/hypertension.
- 4. Johnson RJ, Segal MS, Sautin Y, Nakagawa T, Feig DI, Kang D-H, et al. Potential role of sugar (fructose) in the epidemic of hypertension, obesity and the metabolic syndrome, diabetes, kidney disease, and cardiovascular disease. The American journal of clinical nutrition. 2007;86(4):899–906. pmid:17921363
- 5. Caliceti C, Calabria D, Roda A, Cicero AFG. Fructose Intake, Serum Uric Acid, and Cardiometabolic Disorders: A Critical Review. Nutrients. 2017;9(4):395. pmid:28420204
- 6. Klein AV, Kiat H. The mechanisms underlying fructose-induced hypertension: a review. J Hypertens. 2015;33(5):912–20. pmid:25715094
- 7. Komnenov D, Levanovich PE, Rossi NF. Hypertension Associated with Fructose and High Salt: Renal and Sympathetic Mechanisms. Nutrients. 2019;11(3):569. pmid:30866441
- 8. Khitan Z, Kim DH. Fructose: A Key Factor in the Development of Metabolic Syndrome and Hypertension. Journal of Nutrition and Metabolism. 2013;2013:682673. pmid:23762544
- 9. Johnson RJS-L, L. G. Nakagawa T. The effect of fructose on renal biology and disease. J Am Soc Nephrol. 2010;21(12):2036–9. pmid:21115612
- 10. Madero M, Perez-Pozo SE, Jalal D, Johnson RJ, Sánchez-Lozada LG. Dietary fructose and hypertension. Current hypertension reports. 2011;13(1):29–35. pmid:20957458
- 11. Lustig RH, Schmidt LA, Brindis CD. Public health: The toxic truth about sugar. Nature. 2012;482(7383):27–9. pmid:22297952
- 12. Johnson RJ, Nakagawa T, Sanchez-Lozada LG, Shafiu M, Sundaram S, Le M, et al. Sugar, Uric Acid, and the Etiology of Diabetes and Obesity. Diabetes. 2013;62(10):3307–15. pmid:24065788
- 13. Organization WH. A global brief on hypertension: silent killer, global public health crisis: World Health Day 2013. World Health Organization; 2013.
- 14. Rippe JM, Angelopoulos TJ. Sucrose, high-fructose corn syrup, and fructose, their metabolism and potential health effects: what do we really know? Adv Nutr. 2013;4(2):236–45. pmid:23493540
- 15. Malik VS, Pan A, Willett WC, Hu FB. Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. The American journal of clinical nutrition. 2013;98(4):1084–102. pmid:23966427
- 16. Te Morenga L, Mallard S, Mann J. Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. Bmj. 2013;346.
- 17. Semnani-Azad Z, Khan TA, Mejia SB, de Souza RJ, Leiter LA, Kendall CW, et al. Association of major food sources of fructose-containing sugars with incident metabolic syndrome: a systematic review and meta-analysis. JAMA network open. 2020;3(7):e209993–e. pmid:32644139
- 18. Tsilas CS, de Souza RJ, Mejia SB, Mirrahimi A, Cozma AI, Jayalath VH, et al. Relation of total sugars, fructose and sucrose with incident type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies. Cmaj. 2017;189(20):E711–E20. pmid:28536126
- 19. Ayoub-Charette S, Liu Q, Khan TA, Au-Yeung F, Mejia SB, de Souza RJ, et al. Important food sources of fructose-containing sugars and incident gout: a systematic review and meta-analysis of prospective cohort studies. BMJ open. 2019;9(5):e024171. pmid:31061018
- 20. Khan TA, Tayyiba M, Agarwal A, Mejia SB, de Souza RJ, Wolever TM, et al., editors. Relation of total sugars, sucrose, fructose, and added sugars with the risk of cardiovascular disease: a systematic review and dose-response meta-analysis of prospective cohort studies. Mayo Clinic Proceedings; 2019: Elsevier.
- 21. Sievenpiper J, de Souza R, Mirrahimi A, Yu M, Carleton A, Chiavaroli L, et al. Effect of fructose feeding on body weight: systematic review and meta-analyses of controlled feeding trials. Ann Intern Med. 2012;156:291–304.
- 22. Ayoub-Charette S, Chiavaroli L, Liu Q, Khan TA, Zurbau A, Au-Yeung F, et al. Different Food Sources of Fructose-Containing Sugars and Fasting Blood Uric Acid Levels: A Systematic Review and Meta-Analysis of Controlled Feeding Trials. The Journal of Nutrition. 2021. pmid:34087940
- 23. Chiu S, Sievenpiper J, De Souza R, Cozma A, Mirrahimi A, Carleton A, et al. Effect of fructose on markers of non-alcoholic fatty liver disease (NAFLD): a systematic review and meta-analysis of controlled feeding trials. European journal of clinical nutrition. 2014;68(4):416–23. pmid:24569542
- 24. Chiavaroli L, de Souza RJ, Ha V, Cozma AI, Mirrahimi A, Wang DD, et al. Effect of fructose on established lipid targets: a systematic review and meta‐analysis of controlled feeding trials. Journal of the American Heart Association. 2015;4(9):e001700. pmid:26358358
- 25. Choo VL, Viguiliouk E, Mejia SB, Cozma AI, Khan TA, Ha V, et al. Food sources of fructose-containing sugars and glycaemic control: systematic review and meta-analysis of controlled intervention studies. bmj. 2018;363. pmid:30463844
- 26. Liu Q, Ayoub‐Charette S, Khan TA, Au‐Yeung F, Blanco Mejia S, De Souza RJ, et al. Important food sources of fructose‐containing sugars and incident hypertension: a systematic review and dose‐response meta‐analysis of prospective cohort studies. Journal of the American Heart Association. 2019;8(24):e010977. pmid:31826724
- 27. Jayalath VH, de Souza RJ, Ha V, Mirrahimi A, Blanco-Mejia S, Di Buono M, et al. Sugar-sweetened beverage consumption and incident hypertension: a systematic review and meta-analysis of prospective cohorts. The American journal of clinical nutrition. 2015;102(4):914–21. pmid:26269365
- 28. Jayalath VH, Sievenpiper JL, de Souza RJ, Ha V, Mirrahimi A, Santaren ID, et al. Total Fructose Intake and Risk of Hypertension: A Systematic Review and Meta-Analysis of Prospective Cohorts. Journal of the American College of Nutrition. 2014;33(4):328–39. pmid:25144126
- 29. Ha V, Sievenpiper JL, de Souza RJ, Chiavaroli L, Wang DD, Cozma AI, et al. Effect of fructose on blood pressure a systematic review and meta-analysis of controlled feeding trials. Hypertension. 2012;59(4):787–95. pmid:22331380
- 30. Higgins JPT TJ, Chandler J, Cumpston M, Li T, Page MJ, Welch VA Cochrane Handbook for Systematic Reviews of Interventions version 6.1 [Internet]. Cochrane; 2020 [Available from: https://training.cochrane.org/cochrane-handbook-systematic-reviews-interventions#how-to-cite.
- 31. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. pmid:33782057
- 32. Wilczynski NL, Morgan D, Haynes RB, Hedges T. An overview of the design and methods for retrieving high-quality studies for clinical care. BMC Med Inform Decis Mak. 2005;5:20–. pmid:15969765
- 33.
SourceForge. Plot Digitizer 2001 [updated 24-Oct-2015. Available from: http://plotdigitizer.sourceforge.net/.
- 34. 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. Stat Methods Med Res. 2018;27(6):1785–805. pmid:27683581
- 35. 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. BMC Medical Research Methodology. 2014;14(1):135. pmid:25524443
- 36. Furukawa TA, Barbui C, Cipriani A, Brambilla P, Watanabe N. Imputing missing standard deviations in meta-analyses can provide accurate results. Journal of Clinical Epidemiology. 2006;59(1):7–10. pmid:16360555
- 37. Borenstein M, Higgins JP. Meta-analysis and subgroups. Prev Sci. 2013;14(2):134–43. pmid:23479191
- 38.
Borenstein MHL HJ. Introduction to Meta-Analysis. UK: John Wiley & Sons; 2009.
- 39. Deeks JJ, Higgins JP, Altman DG, Group obotCSM. Analysing data and undertaking meta-analyses. Cochrane Handbook for Systematic Reviews of Interventions2019. p. 241–84.
- 40. DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled Clinical Trials. 1986;7(3):177–88. pmid:3802833
- 41. Tufanaru C, Munn Z, Stephenson M, Aromataris E. Fixed or random effects meta-analysis? Common methodological issues in systematic reviews of effectiveness. Int J Evid Based Healthc. 2015;13(3):196–207. pmid:26355603
- 42. Elbourne DR, Altman DG, Higgins JPT, Curtin F, Worthington HV, Vail A. Meta-analyses involving cross-over trials: methodological issues. International Journal of Epidemiology. 2002;31(1):140–9. pmid:11914310
- 43. Follmann D, Elliott P, Suh I, Cutler J. Variance imputation for overviews of clinical trials with continuous response. J Clin Epidemiol. 1992;45(7):769–73. pmid:1619456
- 44.
Balk EM, Earley A, Patel K, Trikalinos TA, Dahabreh IJ. AHRQ Methods for Effective Health Care. Empirical Assessment of Within-Arm Correlation Imputation in Trials of Continuous Outcomes. Rockville (MD): Agency for Healthcare Research and Quality (US); 2012.
- 45. Collaboration PS. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. The Lancet. 2002;360(9349):1903–13. pmid:12493255
- 46. Thompson SG, Higgins JP. How should meta-regression analyses be undertaken and interpreted? Stat Med. 2002;21(11):1559–73. pmid:12111920
- 47. Fu R, Gartlehner G, Grant M, Shamliyan T, Sedrakyan A, Wilt TJ, et al. Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program. Journal of Clinical Epidemiology. 2011;64(11):1187–97. pmid:21477993
- 48.
Harrell FE Jr., Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York: Springer; 2001.
- 49.
Guideline: sugars intake for adults and children [Internet]. Geneva (Switzerland): World Health Organization; 2015 [cited 2018 Nov 10]. Available from: http://apps.who.int/iris/bitstream/handle/10665/149782/9789241549028_eng.pdf;jsessionid=F9FAD19E165BB45830BA1A484FC6FD93?sequence=1.
- 50.
Carbohydrates and health: Scientific Advisory Committee on Nutrition; 2015 [Available from: https://www.gov.uk/government/publications/sacn-carbohydrates-and-health-report#:~:text=The%20Scientific%20Advisory%20Committee%20on%20Nutrition%20(%20SACN%20)%20was%20asked%20by,2%20diabetes%2C%20bowel%20health%20and.
- 51.
Agriculture. USDoHaHSaUSDo. 2015–2020 Dietary Guidelines for Americans. 8th Edition 2015 National Academies Press; 2015 [Available from: https://health.gov/dietaryguidelines/2015/guidelines/.
- 52.
Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington, DC: Institute of Medicine, The National Academies Press; 2005. 1358 p.
- 53. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34. pmid:9310563
- 54. Begg CB, Mazumdar M. Operating Characteristics of a Rank Correlation Test for Publication Bias. Biometrics. 1994;50(4):1088–101. pmid:7786990
- 55. Sterne JA, Gavaghan D, Egger M. Publication and related bias in meta-analysis: power of statistical tests and prevalence in the literature. J Clin Epidemiol. 2000;53(11):1119–29. pmid:11106885
- 56. Duval S, Tweedie R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56(2):455–63. pmid:10877304
- 57. Schünemann H BJ, Guyatt GOA. GRADE Handbook [Internet]. 2013 [cited 2018 Nov 10]. Available from: https://handbook-5-1.cochrane.org.
- 58. Higgins JP, Altman DG, Gotzsche PC, Juni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928. pmid:22008217
- 59. Andrews J, Guyatt G, Oxman AD, Alderson P, Dahm P, Falck-Ytter Y, et al. GRADE guidelines: 14. Going from evidence to recommendations: the significance and presentation of recommendations. J Clin Epidemiol. 2013;66(7):719–25. pmid:23312392
- 60. Brunetti M, Shemilt I, Pregno S, Vale L, Oxman AD, Lord J, et al. GRADE guidelines: 10. Considering resource use and rating the quality of economic evidence. J Clin Epidemiol. 2013;66(2):140–50. pmid:22863410
- 61. Guyatt GH, Oxman AD, Schünemann HJ. GRADE guidelines-an introduction to the 10th-13th articles in the series. J Clin Epidemiol. 2013;66(2):121–3. pmid:22968177
- 62. Guyatt GH, Thorlund K, Oxman AD, Walter SD, Patrick D, Furukawa TA, et al. GRADE guidelines: 13. Preparing summary of findings tables and evidence profiles-continuous outcomes. J Clin Epidemiol. 2013;66(2):173–83. pmid:23116689
- 63. Guyatt G, Oxman AD, Sultan S, Brozek J, Glasziou P, Alonso-Coello P, et al. GRADE guidelines: 11. Making an overall rating of confidence in effect estimates for a single outcome and for all outcomes. J Clin Epidemiol. 2013;66(2):151–7. pmid:22542023
- 64. Guyatt GH, Oxman AD, Santesso N, Helfand M, Vist G, Kunz R, et al. GRADE guidelines: 12. Preparing summary of findings tables-binary outcomes. J Clin Epidemiol. 2013;66(2):158–72. pmid:22609141
- 65. Balshem H, Helfand M, Schünemann HJ, Oxman AD, Kunz R, Brozek J, et al. GRADE guidelines: 3. Rating the quality of evidence. Journal of clinical epidemiology. 2011;64(4):401–6. pmid:21208779
- 66. Schünemann HH JPT; Vist GE; Glasziou P; Akl EA; Skoetz N; Guyatt GH. Completing ‘Summary of findings’ tables and grading the certainty of the evidence. Cochrane Handbook for Systematic Reviews of Interventions 62 (updated February 2021)2021.
- 67. Santesso N, Glenton C, Dahm P, Garner P, Akl EA, Alper B, et al. GRADE guidelines 26: informative statements to communicate the findings of systematic reviews of interventions. Journal of clinical epidemiology. 2020;119:126–35. pmid:31711912
- 68. Silbernagel G, Machann J, Unmuth S, Schick F, Stefan N, Häring HU, et al. Effects of 4-week very-high-fructose/glucose diets on insulin sensitivity, visceral fat and intrahepatic lipids: an exploratory trial. British Journal of Nutrition. 2011;106(1):79–86. pmid:21396140
- 69. Stanhope KL, Havel PJ. Fructose consumption: Considerations for future research on its effects on adipose distribution, lipid metabolism, and insulin sensitivity in humans. Journal of Nutrition. 2009;139(6):1236S–41S. pmid:19403712
- 70. Aeberli I, Gerber PA, Hochuli M, Kohler S, Haile SR, Gouni-Berthold I, et al. Low to moderate sugar-sweetened beverage consumption impairs glucose and lipid metabolism and promotes inflammation in healthy young men: a randomized controlled trial–. The American journal of clinical nutrition. 2011;94(2):479–85.
- 71. Aeberli I, Hochuli M, Gerber PA, Sze L, Murer SB, Tappy L, et al. Moderate amounts of fructose consumption impair insulin sensitivity in healthy young men: a randomized controlled trial. Diabetes care. 2013;36(1):150–6. pmid:22933433
- 72. Agebratt C, Ström E, Romu T, Dahlqvist-Leinhard O, Borga M, Leandersson P, et al. A randomized study of the effects of additional fruit and nuts consumption on hepatic fat content, cardiovascular risk factors and basal metabolic rate. PloS one. 2016;11(1):e0147149. pmid:26788923
- 73. Aghababaee SK, Vafa M, Shidfar F, Tahavorgar A, Gohari M, Katebi D, et al. Effects of blackberry (Morus nigra L.) consumption on serum concentration of lipoproteins, apo A-I, apo B, and high-sensitivity-C-reactive protein and blood pressure in dyslipidemic patients. Journal of Research in Medical Sciences. 2015;20(7):685–91.
- 74. Ahmed T, Sadia H, Batool S, Janjua A, Shuja F. Use of prunes as a control of hypertension. Journal of Ayub Medical College, Abbottabad: JAMC. 2010;22(1):28–31. pmid:21409897
- 75. Amagase H, Sun B, Nance DM. Immunomodulatory effects of a standardized lycium barbarum fruit juice in chinese older healthy human subjects. Journal of Medicinal Food. 2009;12(5):1159–65. pmid:19857084
- 76. Anderson JW, Weiter KM, Christian AL, Ritchey MB, Bays HE. Raisins compared with other snack effects on glycemia and blood pressure: A randomized, controlled trial. Postgraduate Medicine. 2014;126(1):37–43. pmid:24393750
- 77. Bays H, Weiter K, Anderson J. A randomized study of raisins versus alternative snacks on glycemic control and other cardiovascular risk factors in patients with type 2 diabetes mellitus. Physician and Sportsmedicine. 2015;43(1):37–43. pmid:25609549
- 78. Angelopoulos TJ, Lowndes J, Sinnett S, Rippe JM. Fructose containing sugars do not raise blood pressure or uric acid at normal levels of human consumption. J Clin Hypertens (Greenwich). 2015;17(2):87–94. pmid:25496265
- 79. Banini AE, Boyd LC, Allen JC, Allen HG, Sauls DL. Muscadine grape products intake, diet and blood constituents of non-diabetic and type 2 diabetic subjects. Nutrition. 2006;22(11):1137–45. pmid:17030113
- 80. Basu A, Du M, Leyva MJ, Sanchez K, Betts NM, Wu M, et al. Blueberries decrease cardiovascular risk factors in obese men and women with metabolic syndrome. Journal of Nutrition. 2010;140(9):1582–7. pmid:20660279
- 81. Basu A, Fu DX, Wilkinson M, Simmons B, Wu M, Betts NM, et al. Strawberries decrease atherosclerotic markers in subjects with metabolic syndrome. Nutrition Research. 2010;30(7):462–9. pmid:20797478
- 82. Black RNA, Spence M, McMahon RO, Cuskelly GJ, Ennis CN, McCance DR, et al. Effect of eucaloric high-and low-sucrose diets with identical macronutrient profile on insulin resistance and vascular risk: a randomized controlled trial. Diabetes. 2006;55(12):3566–72. pmid:17130505
- 83. Brymora A, Flisinski M, Johnson RJ, Goszka G, Stefanska A, Manitius J. Low-fructose diet lowers blood pressure and inflammation in patients with chronic kidney disease. Nephrology Dialysis Transplantation. 2012;27(2):608–12. pmid:21613382
- 84. Campos V, Despland C, Brandejsky V, Kreis R, Schneiter P, Chiolero A, et al. Sugar‐and artificially sweetened beverages and intrahepatic fat: A randomized controlled trial. Obesity. 2015;23(12):2335–9. pmid:26727115
- 85. Despland C, Walther B, Kast C, Campos V, Rey V, Stefanoni N, et al. A randomized-controlled clinical trial of high fructose diets from either Robinia honey or free fructose and glucose in healthy normal weight males. Clinical Nutrition ESPEN. 2017;19:16–22.
- 86. Claesson A-L, Holm G, Ernersson Å, Lindström T, Nystrom FH. Two weeks of overfeeding with candy, but not peanuts, increases insulin levels and body weight. Scandinavian journal of clinical and laboratory investigation. 2009;69(5):598–605. pmid:19396658
- 87. Cooper PL, Wahlqvist ML, Simpson RW. Sucrose versus saccharin as an added sweetener in non-insulin-dependent diabetes: short- and medium-term metabolic effects. Diabet Med. 1988;5(7):676–80. pmid:2975554
- 88. Cressey R, Kumsaiyai W, Mangklabruks A. Daily consumption of banana marginally improves blood glucose and lipid profile in hypercholesterolemic subjects and increases serum adiponectin in type 2 diabetic patients. 2014. pmid:25651610
- 89. Davidi A, Reynolds J, Njike VY, Ma Y, Doughty K, Katz DL. The effect of the addition of daily fruit and nut bars to diet on weight, and cardiac risk profile, in overweight adults. Journal of human nutrition and dietetics: the official journal of the British Dietetic Association. 2011;24(6):543–51. pmid:21883530
- 90. Dow CAG, Chow S. B., Patil H. H. S., Thomson B. S., C. A. The effects of daily consumption of grapefruit on body weight, lipids, and blood pressure in healthy, overweight adults. Metabolism: Clinical and Experimental. 2012;61(7):1026–35. pmid:22304836
- 91. Hegde SV, Adhikari P, M N, D’Souza V. Effect of daily supplementation of fruits on oxidative stress indices and glycaemic status in type 2 diabetes mellitus. Complement Ther Clin Pract. 2013;19(2):97–100. pmid:23561067
- 92. Hernandez-Cordero S, Barquera S, Rodriguez-Ramirez S, Villanueva-Borbolla MA, de Cossio TG, Dommarco JR, et al. Substituting water for sugar-sweetened beverages reduces circulating triglycerides and the prevalence of metabolic syndrome in obese but not in overweight mexican women in a randomized controlled trial. Journal of Nutrition. 2014;144(11):1742–52. pmid:25332472
- 93. Israel KD, Michaelis OEt, Reiser S, Keeney M. Serum uric acid, inorganic phosphorus, and glutamic-oxalacetic transaminase and blood pressure in carbohydrate-sensitive adults consuming three different levels of sucrose. Ann Nutr Metab. 1983;27(5):425–35.
- 94. Kanellos PT, Kaliora AC, Tentolouris NK, Argiana V, Perrea D, Kalogeropoulos N, et al. A pilot, randomized controlled trial to examine the health outcomes of raisin consumption in patients with diabetes. Nutrition. 2014;30(3):358–64. pmid:24262513
- 95. Karlsen A, Svendsen M, Seljeflot I, Laake P, Duttaroy AK, Drevon CA, et al. Kiwifruit decreases blood pressure and whole-blood platelet aggregation in male smokers. Journal of Human Hypertension. 2013;27(2):126–30. pmid:22258209
- 96. Koh E, Ard N, Mendoza F. Effects of fructose feeding on blood parameters and blood pressure in impaired glucose-tolerant subjects. Journal of the American Dietetic Association. 1988;88(8):932–8. pmid:3294273
- 97. Koivisto V, Yki‐Järvinen H. Fructose and insulin sensitivity in patients with type 2 diabetes. Journal of internal medicine. 1993;233(2):145–53. pmid:8433075
- 98. Kumari S, Devi R, Mangaraj M. Effect of Guava in blood glucose and lipid profile in healthy human subjects: A randomized controlled study. Journal of Clinical and Diagnostic Research. 2016;10(9):BC04–BC7. pmid:27790420
- 99. Lehtonen HM, Suomela JP, Tahvonen R, Vaarno J, Venojarvi M, Viikari J, et al. Berry meals and risk factors associated with metabolic syndrome. European Journal of Clinical Nutrition. 2010;64(6):614–21. pmid:20197789
- 100. Lehtonen H-M, Suomela J, Tahvonen R, Yang B, Venojärvi M, Viikari J, et al. Different berries and berry fractions have various but slightly positive effects on the associated variables of metabolic diseases on overweight and obese women. European journal of clinical nutrition. 2011;65(3):394. pmid:21224867
- 101. Leskinen MH, Hautaniemi EJ, Tahvanainen AM, Koskela JK, Päällysaho M, Tikkakoski AJ, et al. Daily liquorice consumption for two weeks increases augmentation index and central systolic and diastolic blood pressure. PloS one. 2014;9(8):e105607. pmid:25153328
- 102. Lewis AS, McCourt HJ, Ennis CN, Bell PM, Courtney CH, McKinley MC, et al. Comparison of 5% versus 15% sucrose intakes as part of a eucaloric diet in overweight and obese subjects: Effects on insulin sensitivity, glucose metabolism, vascular compliance, body composition and lipid profile. A Randomised Controlled Trial. Metabolism: Clinical and Experimental. 2013;62(5):694–702. pmid:23363580
- 103. Madero M, Rodriguez Castellanos FE, Jalal D, Villalobos-Martin M, Salazar J, Vazquez-Rangel A, et al. A pilot study on the impact of a low fructose diet and allopurinol on clinic blood pressure among overweight and prehypertensive subjects: A randomized placebo controlled trial. Journal of the American Society of Hypertension. 2015;9(11):837–44. pmid:26329473
- 104. Poppitt SD, Keogh GF, Prentice AM, Williams DEM, Sonnemans HMW, Valk EEJ, et al. Long-term effects of ad libitum low-fat, high-carbohydrate diets on body weight and serum lipids in overweight subjects with metabolic syndrome. American Journal of Clinical Nutrition. 2002;75(1):11–20. pmid:11756055
- 105. Puglisi MJ, Vaishnav U, Shrestha S, Torres-Gonzalez M, Wood RJ, Volek JS, et al. Raisins and additional walking have distinct effects on plasma lipids and inflammatory cytokines. Lipids in Health and Disease. 2008;7 (no pagination)(14). pmid:18416823
- 106. Raben A, Macdonald I, Astrup A. Replacement of dietary fat by sucrose or starch: effects on 14 d ad libitum energy intake, energy expenditure and body weight in formerly obese and never-obese subjects. Int J Obes Relat Metab Disord. 1997;21(10):846–59. pmid:9347402
- 107. Raben A, Vasilaras TH, Moller AC, Astrup A. Sucrose compared with artificial sweeteners: different effects on ad libitum food intake and body weight after 10 wk of supplementation in overweight subjects. American Journal of Clinical Nutrition. 2002;76(4):721–9. pmid:12324283
- 108. Ravn-Haren G, Dragsted LO, Buch-Andersen T, Jensen EN, Jensen RI, Nemeth-Balogh M, et al. Intake of whole apples or clear apple juice has contrasting effects on plasma lipids in healthy volunteers. Eur J Nutr. 2013;52(8):1875–89. pmid:23271615
- 109. Shema-Didi L, Kristal B, Sela S, Geron R, Ore L. Does Pomegranate intake attenuate cardiovascular risk factors in hemodialysis patients? Nutrition Journal. 2014;13 (1) (no pagination)(18). pmid:24593225
- 110. Singh RBR S. S. Singh R. Niaz M. A. Singh N. K. Madhu S. V. Effects on plasma ascorbic acid and coronary risk factors of adding guava fruit to the usual diet in hypertensives with mild to moderate hypercholesterolaemia. Journal of Nutritional and Environmental Medicine. 1997;7(1):5–14.
- 111. Surwit RS, Feinglos MN, McCaskill CC, Clay SL, Babyak MA, Brownlow BS, et al. Metabolic and behavioral effects of a high-sucrose diet during weight loss. American Journal of Clinical Nutrition. 1997;65(4):908–15. pmid:9094871
- 112. Tate DF, Turner-McGrievy G, Lyons E, Stevens J, Erickson K, Polzien K, et al. Replacing caloric beverages with water or diet beverages for weight loss in adults: main results of the C hoose H ealthy O pt i ons C onsciously E veryday (CHOICE) randomized clinical trial–. The American journal of clinical nutrition. 2012;95(3):555–63.
- 113. van Meijl LE, Mensink RP. Low-fat dairy consumption reduces systolic blood pressure, but does not improve other metabolic risk parameters in overweight and obese subjects. Nutr Metab Cardiovasc Dis. 2011;21(5):355–61. pmid:20153619
- 114. Vazquez-Duran M, Orea-Tejeda A, Castillo-Martinez L, Cano-Garcia A, Tellez-Olvera L, Keirns-Davis C. A randomized control trial for reduction of caloric and non-caloric sweetened beverages in young adults: effects in weight, body composition and blood pressure. Nutr Hosp. 2016;33(6):1372–8. pmid:28000468
- 115. Amani R, Moazen S, Shahbazian H, Ahmadi K, Jalali MT. Flavonoid-rich beverage effects on lipid profile and blood pressure in diabetic patients. World journal of diabetes. 2014;5(6):962. pmid:25512803
- 116. Engel S, Tholstrup T, Bruun JM, Astrup A, Richelsen B, Raben A. Effect of high milk and sugar-sweetened and non-caloric soft drink intake on insulin sensitivity after 6 months in overweight and obese adults: a randomized controlled trial. European journal of clinical nutrition. 2018;72(3):358–66. pmid:29235560
- 117. Sigala DM, Widaman AM, Hieronimus B, Nunez MV, Lee V, Benyam Y, et al. Effects of Consuming Sugar-Sweetened Beverages for 2 Weeks on 24-h Circulating Leptin Profiles, Ad Libitum Food Intake and Body Weight in Young Adults. Nutrients. 2020;12(12):3893. pmid:33352724
- 118. Abedini M, Ghasemi‐Tehrani H, Tarrahi MJ, Amani R. The effect of concentrated pomegranate juice consumption on risk factors of cardiovascular diseases in women with polycystic ovary syndrome: A randomized controlled trial. Phytotherapy Research. 2021;35(1):442–51. pmid:32767710
- 119. Al-Dujaili E, Twaij H, Bataineh Y, Arshad U, Amjid F. Effect of stevia consumption on blood pressure, stress hormone levels and anthropometrical parameters in healthy persons. American Journal of Pharmacology and Toxicology. 2017;12:7–17.
- 120. Al-Dashti YA, Holt RR, Carson JG, Keen CL, Hackman RM. Effects of Short-term dried plum (prune) intake on markers of bone resorption and vascular function in healthy postmenopausal women: A randomized crossover trial. Journal of medicinal food. 2019;22(10):982–92. pmid:31194598
- 121. Alatas H, Sja’bani M, Mustofa M, Mukti AG, Bawazier LA, Irijanto F, et al. The effects of soursop supplementation on blood pressure, serum uric acid, and kidney function in a prehypertensive population in accordance with the 2017 ACC/AHA guideline. Journal of human hypertension. 2020;34(3):223–32. pmid:31462727
- 122. Asgary S, Sahebkar A, Afshani MR, Keshvari M, Haghjooyjavanmard S, Rafieian‐Kopaei M. Clinical evaluation of blood pressure lowering, endothelial function improving, hypolipidemic and anti‐inflammatory effects of pomegranate juice in hypertensive subjects. Phytotherapy Research. 2014;28(2):193–9. pmid:23519910
- 123. Ayoobi N, Jafarirad S, Haghighizadeh MH, Jahanshahi A. Protective Effect of Dark Chocolate on Cardiovascular Disease Factors and Body Composition in Type 2 Diabetes: A Parallel, Randomized, Clinical Trial. Iranian Red Crescent Medical Journal. 2017;19(8).
- 124. Beisner J, Gonzalez-Granda A, Basrai M, Damms-Machado A, Bischoff SC. Fructose-induced intestinal microbiota shift following two types of short-term high-fructose dietary phases. Nutrients. 2020;12(11):3444. pmid:33182700
- 125. Chiu S, Siri-Tarino P, Bergeron N, Suh JH, Krauss RM. A randomized study of the effect of replacing sugar-sweetened soda by reduced fat milk on cardiometabolic health in male adolescent soda drinkers. Nutrients. 2020;12(2):405. pmid:32033078
- 126. Dikariyanto V, Smith L, Francis L, Robertson M, Kusaslan E, O’Callaghan-Latham M, et al. Snacking on whole almonds for 6 weeks improves endothelial function and lowers LDL cholesterol but does not affect liver fat and other cardiometabolic risk factors in healthy adults: The ATTIS study, a randomized controlled trial. The American journal of clinical nutrition. 2020;111(6):1178–89. pmid:32412597
- 127. Domínguez-Coello S, Carrillo-Fernández L, Gobierno-Hernández J, Méndez-Abad M, Borges-Álamo C, García-Dopico JA, et al. Decreased Consumption of Added Fructose Reduces Waist Circumference and Blood Glucose Concentration in Patients with Overweight and Obesity. The DISFRUTE Study: A Randomised Trial in Primary Care. Nutrients. 2020;12(4):1149. pmid:32325919
- 128. Du C, Smith A, Avalos M, South S, Crabtree K, Wang W, et al. Blueberries improve pain, gait performance, and inflammation in individuals with symptomatic knee osteoarthritis. Nutrients. 2019;11(2):290. pmid:30699971
- 129. Ebbeling CB, Feldman HA, Steltz SK, Quinn NL, Robinson LM, Ludwig DS. Effects of Sugar‐Sweetened, Artificially Sweetened, and Unsweetened Beverages on Cardiometabolic Risk Factors, Body Composition, and Sweet Taste Preference: A Randomized Controlled Trial. Journal of the American Heart Association. 2020;9(15):e015668. pmid:32696704
- 130. Esmaeilinezhad Z, Barati-Boldaji R, Brett N, De Zepetnek J, Bellissimo N, Babajafari S, et al. The effect of synbiotics pomegranate juice on cardiovascular risk factors in PCOS patients: a randomized, triple-blinded, controlled trial. Journal of endocrinological investigation. 2020;43(4):539–48. pmid:31713129
- 131. Franck M, de Toro-Martín J, Garneau V, Guay V, Kearney M, Pilon G, et al. Effects of Daily Raspberry Consumption on Immune-Metabolic Health in Subjects at Risk of Metabolic Syndrome: A Randomized Controlled Trial. Nutrients. 2020;12(12):3858. pmid:33348685
- 132. Hallfrisch J, Reiser S, Prather ES. Blood lipid distribution of hyperinsulinemic men consuming three levels of fructose. The American journal of clinical nutrition. 1983;37(5):740–8. pmid:6846212
- 133. Hieronimus B, Medici V, Bremer AA, Lee V, Nunez MV, Sigala DM, et al. Synergistic effects of fructose and glucose on lipoprotein risk factors for cardiovascular disease in young adults. Metabolism. 2020;112:154356. pmid:32916151
- 134. Irannejad niri Z, Shidfar F, Jabbari M, Zarrati M, Hosseini A, Malek M, et al. The effect of dried Ziziphus vulgaris on glycemic control, lipid profile, Apo‐proteins and hs‐CRP in patients with type 2 diabetes mellitus: A randomized controlled clinical trial. Journal of food biochemistry. 2021;45(3):e13193. pmid:32227501
- 135. Jalilvand A, Behrouz V, Nikpayam O, Sohrab G, Hekmatdoost A. Effects of low fructose diet on glycemic control, lipid profile and systemic inflammation in patients with type 2 diabetes: A single-blind randomized controlled trial. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2020;14(5):849–55. pmid:32559734
- 136. Jones JB, Provost M, Keaver L, Breen C, Ludy M-J, Mattes RD. A randomized trial on the effects of flavorings on the health benefits of daily peanut consumption. The American journal of clinical nutrition. 2014;99(3):490–6. pmid:24351876
- 137. Kaliora AC, Kokkinos A, Diolintzi A, Stoupaki M, Gioxari A, Kanellos PT, et al. The effect of minimal dietary changes with raisins in NAFLD patients with non-significant fibrosis: a randomized controlled intervention. Food & function. 2016;7(11):4533–44. pmid:27714002
- 138. Kanellos PT, Kaliora AC, Protogerou AD, Tentolouris N, Perrea DN, Karathanos VT. The effect of raisins on biomarkers of endothelial function and oxidant damage; an open-label and randomized controlled intervention. Food Research International. 2017;102:674–80. pmid:29195999
- 139. Kojadinovic MI, Arsic AC, Debeljak‐Martacic JD, Konic‐Ristic AI, Kardum ND, Popovic TB, et al. Consumption of pomegranate juice decreases blood lipid peroxidation and levels of arachidonic acid in women with metabolic syndrome. Journal of the Science of Food and Agriculture. 2017;97(6):1798–804. pmid:27476699
- 140. Lazavi F, Mirmiran P, Sohrab G, Nikpayam O, Angoorani P, Hedayati M. The barberry juice effects on metabolic factors and oxidative stress in patients with type 2 diabetes: a randomized clinical trial. Complement Ther Clin Pract. 2018;31:170–4. pmid:29705451
- 141. Luukkonen PK, Sädevirta S, Zhou Y, Kayser B, Ali A, Ahonen L, et al. Saturated fat is more metabolically harmful for the human liver than unsaturated fat or simple sugars. Diabetes care. 2018;41(8):1732–9. pmid:29844096
- 142. Madero M, Arriaga JC, Jalal D, Rivard C, McFann K, Perez-Mendez O, et al. The effect of two energy-restricted diets, a low-fructose diet versus a moderate natural fructose diet, on weight loss and metabolic syndrome parameters: a randomized controlled trial. Metabolism: Clinical & Experimental. 2011;60(11):1551–9.
- 143. Maki KC, Palacios OM, Kramer MW, Trivedi R, Dicklin MR, Wilcox ML, et al. Effects of substituting eggs for high-carbohydrate breakfast foods on the cardiometabolic risk-factor profile in adults at risk for type 2 diabetes mellitus. European journal of clinical nutrition. 2020;74(5):784–95. pmid:32152513
- 144. Maleki Z, Jazayeri S, Eslami O, Shidfar F, Hosseini AF, Agah S, et al. Effect of soy milk consumption on glycemic status, blood pressure, fibrinogen and malondialdehyde in patients with non-alcoholic fatty liver disease: a randomized controlled trial. Complementary therapies in medicine. 2019;44:44–50. pmid:31126574
- 145. Markey O, Le Jeune J, Lovegrove JA. Energy compensation following consumption of sugar-reduced products: a randomized controlled trial. Eur J Nutr. 2016;55(6):2137–49. pmid:26349919
- 146. Martini D, Rosi A, Tassotti M, Antonini M, Dall’Asta M, Bresciani L, et al. Effect of coffee and cocoa-based confectionery containing coffee on markers of cardiometabolic health: Results from the pocket-4-life project. Eur J Nutr. 2021;60(3):1453–63. pmid:32728879
- 147. Mietus‐Snyder ML, Shigenaga MK, Suh JH, Shenvi SV, Lal A, McHugh T, et al. A nutrient‐dense, high‐fiber, fruit‐based supplement bar increases HDL cholesterol, particularly large HDL, lowers homocysteine, and raises glutathione in a 2‐wk trial. The FASEB Journal. 2012;26(8):3515–27. pmid:22549511
- 148. Navaei N, Pourafshar S, Akhavan NS, Litwin NS, Foley EM, George KS, et al. Influence of daily fresh pear consumption on biomarkers of cardiometabolic health in middle-aged/older adults with metabolic syndrome: a randomized controlled trial. Food & function. 2019;10(2):1062–72. pmid:30720034
- 149. Neto MM, da Silva TF, de Lima FF, Siqueira TM, Toscano LT, de Moura SK, et al. Whole red grape juice reduces blood pressure at rest and increases post-exercise hypotension. Journal of the American College of Nutrition. 2017;36(7):533–40. pmid:28853994
- 150. Nier A, Brandt A, Conzelmann IB, Özel Y, Bergheim I. Non-alcoholic fatty liver disease in overweight children: Role of fructose intake and dietary pattern. Nutrients. 2018;10(9):1329. pmid:30235828
- 151. Njike VY, Faridi Z, Shuval K, Dutta S, Kay CD, West SG, et al. Effects of sugar-sweetened and sugar-free cocoa on endothelial function in overweight adults. International journal of cardiology. 2011;149(1):83–8. pmid:20036019
- 152. Palacios OM, Maki KC, Xiao D, Wilcox ML, Dicklin MR, Kramer M, et al. Effects of consuming almonds on insulin sensitivity and other cardiometabolic health markers in adults with prediabetes. Journal of the American College of Nutrition. 2020;39(5):397–406. pmid:31525129
- 153. Puupponen‐Pimiä R, Seppänen‐Laakso T, Kankainen M, Maukonen J, Törrönen R, Kolehmainen M, et al. Effects of ellagitannin‐rich berries on blood lipids, gut microbiota, and urolithin production in human subjects with symptoms of metabolic syndrome. Molecular nutrition & food research. 2013;57(12):2258–63. pmid:23934737
- 154. Schell J, Betts NM, Lyons TJ, Basu A. Raspberries improve postprandial glucose and acute and chronic inflammation in adults with type 2 diabetes. Annals of Nutrition and Metabolism. 2019;74(2):165–74. pmid:30763939
- 155. Schwimmer JB, Ugalde-Nicalo P, Welsh JA, Angeles JE, Cordero M, Harlow KE, et al. Effect of a low free sugar diet vs usual diet on nonalcoholic fatty liver disease in adolescent boys: a randomized clinical trial. Jama. 2019;321(3):256–65. pmid:30667502
- 156. Stanhope KL, Medici V, Bremer AA, Lee V, Lam HD, Nunez MV, et al. A dose-response study of consuming high-fructose corn syrup–sweetened beverages on lipid/lipoprotein risk factors for cardiovascular disease in young adults. The American journal of clinical nutrition. 2015;101(6):1144–54. pmid:25904601
- 157. Swarbrick MM, Stanhope KL, Elliott SS, Graham JL, Krauss RM, Christiansen MP, et al. Consumption of fructose-sweetened beverages for 10 weeks increases postprandial triacylglycerol and apolipoprotein-B concentrations in overweight and obese women. British Journal of Nutrition. 2008;100(5):947–52. pmid:18384705
- 158. Tang SP, Wan Yusuf W, Abd Aziz CB, Mustafa M, Mohamed M. Effects of six-month tualang honey supplementation on physiological and biochemical profiles in asymptomatic, treatment-naïve HIV-infected patients. Tropical Journal of Natural Product Research. 2020.
- 159. Vos MB, Weber MB, Welsh J, Khatoon F, Jones DP, Whitington PF, et al. Fructose and oxidized low-density lipoprotein in pediatric nonalcoholic fatty liver disease: a pilot study. Archives of pediatrics & adolescent medicine. 2009;163(7):674–5. pmid:19581556
- 160. Geidl-Flueck B, Hochuli M, Németh Á, Eberl A, Derron N, Köfeler HC, et al. Fructose-and sucrose-but not glucose-sweetened beverages promote hepatic de novo lipogenesis: A randomized controlled trial. Journal of hepatology. 2021;75(1):46–54. pmid:33684506
- 161. Fattore E, Botta F, Agostoni C, Bosetti C. Effects of free sugars on blood pressure and lipids: a systematic review and meta-analysis of nutritional isoenergetic intervention trials. The American Journal of Clinical Nutrition. 2016;105(1):42–56. pmid:28003201
- 162. Kim YJ Y. Prospective association of sugar-sweetened and artificially sweetened beverage intake with risk of hypertension. Arch Cardiovasc Dis. 2016;109(4):242–53. pmid:26869455
- 163. Xi B, Huang Y, Reilly KH, Li S, Zheng R, Barrio-Lopez MT, et al. Sugar-sweetened beverages and risk of hypertension and CVD: a dose–response meta-analysis. British Journal of Nutrition. 2015;113(05):709–17. pmid:25735740
- 164. Cheungpasitporn W, Thongprayoon C, Edmonds PJ, Srivali N, Ungprasert P, Kittanamongkolchai W, et al. Sugar and artificially sweetened soda consumption linked to hypertension: a systematic review and meta-analysis. Clinical and Experimental Hypertension. 2015;37(7):587–93. pmid:26114357
- 165. Malik VS, Popkin BM, Bray GA, Despres JP, Willett WC, Hu FB. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care. 2010;33(11):2477–83. pmid:20693348
- 166. Schwingshackl L, Hoffmann G, Lampousi AM, Knuppel S, Iqbal K, Schwedhelm C, et al. Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. Eur J Epidemiol. 2017;32(5):363–75. pmid:28397016
- 167. Wu LS D. He, Y. Fruit and vegetables consumption and incident hypertension: Dose-response meta-analysis of prospective cohort studies. Journal of Human Hypertension. 2016;30(10):573–80.
- 168. Li BL F. Wang L. Zhang D. Fruit and Vegetables Consumption and Risk of Hypertension: A Meta-Analysis. J Clin Hypertens (Greenwich). 2016;18(5):468–76. pmid:26826021
- 169. Schwingshackl L, Schwedhelm C, Hoffmann G, Knüppel S, Iqbal K, Andriolo V, et al. Food groups and risk of hypertension: a systematic review and dose-response meta-analysis of prospective studies. Advances in nutrition. 2017;8(6):793–803. pmid:29141965
- 170.
Rice-Evans CA, Packer L. Flavonoids in health and disease: CRC Press; 2003.
- 171. Barona J, Aristizabal JC, Blesso CN, Volek JS, Fernandez ML. Grape polyphenols reduce blood pressure and increase flow-mediated vasodilation in men with metabolic syndrome. The Journal of nutrition. 2012;142(9):1626–32. pmid:22810991
- 172. Landmesser U, Drexler H. Endothelial function and hypertension. Current opinion in cardiology. 2007;22(4):316–20. pmid:17556884
- 173. Paravicini TM, Touyz RM. NADPH oxidases, reactive oxygen species, and hypertension. Diabetes care. 2008;31(Supplement 2):S170–S80.
- 174. Rodríguez-Iturbe B, Pons H, Quiroz Y, Johnson RJ. The immunological basis of hypertension. American journal of hypertension. 2014;27(11):1327–37. pmid:25150828
- 175. Egert S, Bosy-Westphal A, Seiberl J, Kürbitz C, Settler U, Plachta-Danielzik S, et al. Quercetin reduces systolic blood pressure and plasma oxidised low-density lipoprotein concentrations in overweight subjects with a high-cardiovascular disease risk phenotype: a double-blinded, placebo-controlled cross-over study. British Journal of Nutrition. 2009;102(07):1065–74. pmid:19402938
- 176. Tsubota-Utsugi MO, Kikuya T., Metoki M., Kurimoto H., Suzuki A., Fukushima K., et al. High fruit intake is associated with a lower risk of future hypertension determined by home blood pressure measurement: the OHASAMA study. Journal of Human Hypertension. 2011;25(3):164–71. pmid:20445569
- 177. Filippini T, Naska A, Kasdagli MI, Torres D, Lopes C, Carvalho C, et al. Potassium Intake and Blood Pressure: A Dose‐Response Meta‐Analysis of Randomized Controlled Trials. Journal of the American Heart Association. 2020;9(12):e015719. pmid:32500831
- 178. Streppel MT, Arends LR, van ‘t Veer P, Grobbee DE, Geleijnse JM. Dietary Fiber and Blood Pressure: A Meta-analysis of Randomized Placebo-Controlled Trials. Archives of Internal Medicine. 2005;165(2):150–6. pmid:15668359
- 179. Khan K, Jovanovski E, Ho HVT, Marques ACR, Zurbau A, Mejia SB, et al. The effect of viscous soluble fiber on blood pressure: A systematic review and meta-analysis of randomized controlled trials. Nutrition, Metabolism and Cardiovascular Diseases. 2018;28(1):3–13. pmid:29153856
- 180. D’Elia L, Dinu M, Sofi F, Volpe M, Strazzullo P, Bordoni A, et al. 100% Fruit juice intake and cardiovascular risk: a systematic review and meta-analysis of prospective and randomised controlled studies. Eur J Nutr. 2021;60(5):2449–67. pmid:33150530
- 181. Brown CM, Dulloo AG, Yepuri G, Montani JP. Fructose ingestion acutely elevates blood pressure in healthy young humans. Am J Physiol Regul Integr Comp Physiol. 2008;294(3):R730–7. pmid:18199590
- 182. Le MT, Frye RF, Rivard CJ, Cheng J, McFann KK, Segal MS, et al. Effects of high-fructose corn syrup and sucrose on the pharmacokinetics of fructose and acute metabolic and hemodynamic responses in healthy subjects. Metabolism. 2012;61(5):641–51. pmid:22152650
- 183. Qureshi AI, Suri MFK, Kirmani JF, Divani AA, Mohammad Y. Is Prehypertension a Risk Factor for Cardiovascular Diseases? Stroke. 2005;36(9):1859–63. pmid:16081866
- 184. Zhang Y, Lee ET, Devereux RB, Yeh J, Best LG, Fabsitz RR, et al. Prehypertension, Diabetes, and Cardiovascular Disease Risk in a Population-Based Sample. The Strong Heart Study. 2006;47(3):410–4.
- 185. Hsia J, Margolis KL, Eaton CB, Wenger NK, Allison M, Wu L, et al. Prehypertension and Cardiovascular Disease Risk in the Women’s Health Initiative. Circulation. 2007;115(7):855–60. pmid:17309936
- 186. Vasan RS, Larson MG, Leip EP, Evans JC, O’Donnell CJ, Kannel WB, et al. Impact of High-Normal Blood Pressure on the Risk of Cardiovascular Disease. New England Journal of Medicine. 2001;345(18):1291–7. pmid:11794147
- 187. Greenlund KJ, Croft JB, Mensah GA. Prevalence of heart disease and stroke risk factors in persons with prehypertension in the united states, 1999–2000. Archives of Internal Medicine. 2004;164(19):2113–8. pmid:15505124
- 188. Yadav S, Boddula R, Genitta G, Bhatia V, Bansal B, Kongara S, et al. Prevalence & risk factors of pre-hypertension & hypertension in an affluent north Indian population. Indian Journal of Medical Research. 2008;128(6):712.
- 189. Grotto I, Grossman E, Huerta M, Sharabi Y. Prevalence of Prehypertension and Associated Cardiovascular Risk Profiles Among Young Israeli Adults. Hypertension. 2006;48(2):254–9. pmid:16754794
- 190. Buelt A, Richards A, Jones AL. Hypertension: New Guidelines from the International Society of Hypertension. American Family Physician. 2021;103(12):763–5. pmid:34128614
- 191. Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Himmelfarb CD, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults. Journal of the American College of Cardiology. 2018;71(19):e127–e248.
- 192. Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH). European Heart Journal. 2018;39(33):3021–104.
- 193. Rabi DM, McBrien KA, Sapir-Pichhadze R, Nakhla M, Ahmed SB, Dumanski SM, et al. Hypertension Canada’s 2020 comprehensive guidelines for the prevention, diagnosis, risk assessment, and treatment of hypertension in adults and children. Canadian Journal of Cardiology. 2020;36(5):596–624. pmid:32389335
- 194. Hall ME, Cohen JB, Ard JD, Egan BM, Hall JE, Lavie CJ, et al. Weight-Loss Strategies for Prevention and Treatment of Hypertension: A Scientific Statement From the American Heart Association. Hypertension.HYP. 0000000000000202. pmid:34538096