Dietary fibre and whole grains in diabetes management: Systematic review and meta-analyses

Andrew N Reynolds; Ashley P Akerman; Jim Mann

doi:10.1371/journal.pmed.1003053

. 2020 Mar 6;17(3):e1003053. doi: 10.1371/journal.pmed.1003053

Dietary fibre and whole grains in diabetes management: Systematic review and meta-analyses

Andrew N Reynolds ^1,^2,^*, Ashley P Akerman ^1,³, Jim Mann ^1,²

Editor: Ronald Ching Wan Ma⁴

PMCID: PMC7059907 PMID: 32142510

Abstract

Background

Fibre is promoted as part of a healthy dietary pattern and in diabetes management. We have considered the role of high-fibre diets on mortality and increasing fibre intake on glycaemic control and other cardiometabolic risk factors of adults with prediabetes or diabetes.

Methods and findings

We conducted a systematic review of published literature to identify prospective studies or controlled trials that have examined the effects of a higher fibre intake without additional dietary or other lifestyle modification in adults with prediabetes, gestational diabetes, type 1 diabetes, and type 2 diabetes. Meta-analyses were undertaken to determine the effects of higher fibre intake on all-cause and cardiovascular mortality and increasing fibre intake on glycaemic control and a range of cardiometabolic risk factors. For trials, meta regression analyses identified further variables that influenced the pooled findings. Dose response testing was undertaken; Grading of Recommendations Assessment, Development and Evaluation (GRADE) protocols were followed to assess the quality of evidence. Two multicountry cohorts of 8,300 adults with type 1 or type 2 diabetes followed on average for 8.8 years and 42 trials including 1,789 adults with prediabetes, type 1, or type 2 diabetes were identified. Prospective cohort data indicate an absolute reduction of 14 fewer deaths (95% confidence interval (CI) 4–19) per 1,000 participants over the study duration, when comparing a daily dietary fibre intake of 35 g with the average intake of 19 g, with a clear dose response relationship apparent. Increased fibre intakes reduced glycated haemoglobin (HbA1c; mean difference [MD] −2.00 mmol/mol, 95% CI −3.30 to −0.71 from 33 trials), fasting plasma glucose (MD −0.56 mmol/L, 95% CI −0.73 to −0.38 from 34 trials), insulin (standardised mean difference [SMD] −2.03, 95% CI −2.92 to −1.13 from 19 trials), homeostatic model assessment of insulin resistance (HOMA IR; MD −1.24 mg/dL, 95% CI −1.72 to −0.76 from 9 trials), total cholesterol (MD −0.34 mmol/L, 95% CI −0.46 to −0.22 from 27 trials), low-density lipoprotein (LDL) cholesterol (MD −0.17 mmol/L, 95% CI −0.27 to −0.08 from 21 trials), triglycerides (MD −0.16 mmol/L, 95% CI −0.23 to −0.09 from 28 trials), body weight (MD −0.56 kg, 95% CI −0.98 to −0.13 from 18 trials), Body Mass Index (BMI; MD −0.36, 95% CI −0·55 to −0·16 from 14 trials), and C-reactive protein (SMD −2.80, 95% CI −4.52 to −1.09 from 7 trials) when compared with lower fibre diets. All trial analyses were subject to high heterogeneity. Key variables beyond increasing fibre intake were the fibre intake at baseline, the global region where the trials were conducted, and participant inclusion criteria other than diabetes type. Potential limitations were the lack of prospective cohort data in non-European countries and the lack of long-term (12 months or greater) controlled trials of increasing fibre intakes in adults with diabetes.

Conclusions

Higher-fibre diets are an important component of diabetes management, resulting in improvements in measures of glycaemic control, blood lipids, body weight, and inflammation, as well as a reduction in premature mortality. These benefits were not confined to any fibre type or to any type of diabetes and were apparent across the range of intakes, although greater improvements in glycaemic control were observed for those moving from low to moderate or high intakes. Based on these findings, increasing daily fibre intake by 15 g or to 35 g might be a reasonable target that would be expected to reduce risk of premature mortality in adults with diabetes.

Andrew Nathan Reynolds et al conduct a meta-analysis to show that high dietary fibre is an important aspect of diabetes management.

Author summary

Why was the study done?

Higher intakes of dietary fibre are associated with a reduction in premature mortality and incidence of a wide range of noncommunicable diseases and their risk factors in the population at large. We have considered the role of high-fibre diets on mortality and increasing fibre intake on cardiometabolic risk factors of adults with prediabetes or diabetes.
We conducted a systematic review and meta-analyses to inform an update of European nutrition guidelines for diabetes management.

What did the researchers do and find?

We examined prospective cohort studies of dietary fibre intake and mortality as well as controlled trials, which considered the effects of increasing fibre intakes on glycaemic control and risk factors for cardiovascular disease. We explored dose response relationships between dietary fibre and these outcomes to determine a more reliable estimate for recommended intakes.
We found that participants in prospective cohort studies consuming higher intakes of dietary fibre had a reduced risk of premature mortality when compared with those with lower fibre intakes.
We also found that the results from controlled trials were complementary, with increasing intake of fibre improving glycaemic control and other risk factors for cardiovascular disease, such as cholesterol levels and body weight.

What do the findings mean?

Those with prediabetes, type 1, or type 2 diabetes should increase their dietary fibre intakes by 15 g per day or to 35 g per day.
One practical way to increase fibre intakes is to replace refined grain products with whole grain foods.

Introduction

The observation derived from uncontrolled studies in the 1970s [1–3] that amongst people with diabetes glycaemic control improved when dietary carbohydrate was increased, led to the resurrection of an earlier suggestion [4] that a relatively high carbohydrate intake might be preferable to what was then the cornerstone of dietary advice for diabetes, a low (typically around 40% of total energy) carbohydrate diet [5]. Connor and Connor reached a similar conclusion based on the increased risk of coronary heart disease in people with diabetes and the adverse effects on blood lipids of a low carbohydrate diet, which was typically high in saturated fat [6].

Subsequent controlled trials confirmed the potential of relatively high- compared with low-carbohydrate intake to reduce levels of glycated haemoglobin, improve diurnal blood glucose profiles and levels of total and low-density lipoprotein (LDL) cholesterol in people with diabetes [7–10]. However, these benefits were only apparent when the carbohydrate-containing foods were rich in dietary fibre [11,12]. Other randomised trials and a 2013 systematic review and meta-analysis of trials demonstrated in people with type 2 diabetes the benefit of dietary fibre on glycaemic control when total carbohydrate intake remained constant [13,14]. There have been 2 more recent reviews, one related to the effects of viscous fibre [15], and the other was an umbrella review that did not provide any new analyses [16].

We have undertaken a systematic review and meta-analysis of dietary fibre in diabetes management. The inclusion of more trials and consideration of prospective cohort studies with additional information obtained from the authors has enabled us to extend earlier observations and examine several additional issues relevant to nutrition recommendations for adults with diabetes. We have explored whether dietary fibre also has the potential to improve glycaemic control in type 1 diabetes and prediabetes and favourably influence a range of cardiometabolic risk factors in addition to glycaemic control (cholesterol [total, LDL, high-density lipoprotein (HDL)], triglycerides, body weight, body mass index, waist circumference, fasting insulin, homeostatic model assessment of insulin resistance [HOMA IR], blood pressure, and C-reactive protein [CRP]). Examination of prospective data has enabled us to examine whether these benefits translate into a reduction in morbidity and mortality. Our expanded exploration of existing trials as well as cohort studies has permitted us to also examine, for the first time to our knowledge, whether dose response relationships exist between dietary fibre and a range of clinically relevant outcome measures and to provide a justification for a quantitative recommendation for fibre intakes in diabetes management.

Methods

We followed PRISMA reporting standards for systematic reviews and meta-analyses [17]. The protocol for this systematic review was prospectively registered CRD42018089162.

PICO tables and eligibility criteria

The overall objectives of this systematic review and meta analysis were to determine whether higher fibre intake has the potential to reduce risk of premature mortality, or whether increasing fibre intake, regardless of source, improve glycaemic control or cardiometabolic risk factors in all types of diabetes regardless of treatment regimen. The PICO (Population, Intervention, Control, and Outcomes) tables (S1 Appendix), agreed by a subcommittee of the Diabetes and Nutrition Study Group of the European Association for the Study of Diabetes (DNSG), were developed to address the research question ‘what is the role of high fibre diets in diabetes management’. Prospective cohorts or studies nested in cohorts of adults with prediabetes or impaired glucose tolerance, gestational diabetes, or type 1 or type 2 diabetes that reported all-cause or cardiovascular mortality were considered eligible. Controlled trials were required to report on glycaemic control, insulin measures, blood lipids, adiposity, blood pressure, or CRP. Parallel and crossover trials of at least 6 weeks duration in which the intervention was an increase in whole grains or dietary fibre [18] were included. Six weeks was considered by the DNSG subcommittee to be the minimum trial duration in which HbA1c (the primary outcome) may be expected to change. Adults identified as having prediabetes or impaired glucose tolerance, gestational diabetes, or type 1 or type 2 diabetes, regardless of type of medication and presence of comorbidities were eligible. Eligible trials included studies in which foods were provided or those in which dietary advice regarding fibre and whole grain was given with no further instruction to change intake of macronutrients or energy. Trials comparing equivalent amounts of one fibre type with another were not included.

Literature search

Eligible controlled trials and prospective cohort studies were identified in the same search, using Cochrane search strategies [19]. OVID Medline, Embase, PubMed, and the Cochrane Central Register of Controlled Trials were searched up to 18 January 2019. These searches included a range of terms for diabetes or impaired glucose metabolism, dietary carbohydrate and fibre, and trial design (available in full in S2 Appendix). This online strategy was augmented by hand searches of reference lists to identify other potentially eligible publications. Commercially available software was used to remove duplicates and aid screening [20]. No date or language restrictions were applied.

Study selection, data extraction, and risk of bias assessment

Literature searches, identification of eligible studies, data extraction, and bias assessment were undertaken independently by at least 2 researchers, with any discrepancies resolved with an additional reviewer. Data were extracted using pretested forms [21]. For prospective cohort studies, the most adjusted values for effect size were extracted. For controlled trials, we used baseline data and those from the last time point except for in sensitivity analyses of trial duration in which we included data from any time point from 6-weeks trial duration. We used the Newcastle-Ottawa Scale [22] to assess risk of bias of prospective cohort studies and the Cochrane Collaboration’s tool for assessing risk of bias in randomised trials [23].

Data analysis

For prospective cohort studies, we received additional data from the authors, such as country-specific effect size estimates. We considered the relationship between fibre intake and all-cause or cardiovascular disease related mortality by comparing the highest intake quantile with the lowest intake quantile [24]. Dose response relationships were considered with restricted cubic splines in a two-stage, random effects model [25] after testing for linearity. We measured the risk reduction in all-cause and cardiovascular mortality on the plotted line between an average intake of 19 g per day [26] and the highest intake for which data were available.

For controlled trials, we analysed the mean difference between intervention and control groups with generic inverse variance models and random effects. We used the mean difference between change from baseline values when reported or calculated them with the reported data. For trials with more than one eligible intervention, we have avoided a unit of analysis error by splitting the size of the control group accordingly [19]. For outcomes reported in unique units, we report the standardised mean difference. Correlation coefficients were obtained from publications when reported or imputed from the average of available correlation coefficients per outcome.

The initial calculations for each trial outcome involved pooled data from all eligible studies. However, given the broad nature of the research question, additional factors influencing the initial findings could not be discounted. We considered these factors with a series of univariate meta regression analyses to identify variables beyond the increase in fibre intakes. Variables considered for each outcome were specified in the PICO table as potential sources of bias, trial characteristics, participant characteristics such as diabetes type, or intervention parameters such as the type of fibre prescribed. We ran additional meta regression analyses beyond those stated in the PICO table to consider the generalisability of our results for patients with comorbidities. For trials, we used meta regression analyses with restricted cubic splines of the measured (preferred) or prescribed fibre increase, when available, as dose response testing. When we identified an interaction with baseline fibre intake, we tested the fibre increase as a percentage of the baseline fibre intake.

For both prospective cohort studies and controlled trials, heterogeneity was assessed with the I² statistic [27] and the Cochrane Q test [28]. Sensitivity analyses were conducted when an I² statistic was found to be more than 50% or a p for heterogeneity of <0.10. The effect of each individual study on the pooled result was considered with an influence analysis. This involved the removal of intervention data from the pooled estimate one at a time. Small study effects, as might be seen with publication bias, were assessed with Egger’s test [29] and the trim and fill method [30]. Analyses were performed in Stata statistical software [31] or the ‘metafor’ package of R [32]. The most relevant analyses are presented in the results section and the full analyses in the supplementary material (S3–S17 Appendices). We used Grading of Recommendations Assessment, Development and Evaluation (GRADE) protocols [33] to calculate absolute risk reductions and evaluate the quality of the body of evidence as either high, moderate, low, or very low. Quality of the evidence was assessed by the research team and revised if required after discussion with the DNSG.

Results

A flow chart of identified studies is shown in Fig 1. Data from 2 multicountry prospective cohort studies including 8,300 adults with type 1 or type 2 diabetes residing in 22 countries followed for a mean duration of 8.8 years [34,35] and 42 controlled trials with 1,789 participants were included in the meta-analyses [36–76]. Trial size ranged from 8 to 185 participants, with interventions increasing fibre intakes by 1 to 45 g per day. The vast majority of interventions were 6 to 12 weeks long (93%), with only 1 trial undertaken for a full year. No eligible trials of women with gestational diabetes were identified. A description of identified prospective cohort studies and controlled trials are available in the supplementary materials (S2 Appendix).

Mortality from prospective cohort studies

All-cause mortality was appreciably reduced when comparing the highest fibre intakes with the lowest (relative risk (RR) 0.55, 95% CI 0.35–0.86, I² 0%) over a weighted mean duration of 8.8 years. The estimated cardiovascular mortality risk reduction (RR 0.61, 95% CI 0.26–1.42, I² 10%) was comparable (p = 0.811), however confidence intervals were wide because of the limited number of outcome events available. Influence analysis did not identify any study or country specific data that significantly differed from the pooled result, and Egger’s tests did not suggest publication bias. The relationship between fibre intake and all-cause and cardiovascular mortality in adults with type 1 and type 2 diabetes using country level data when possible is shown in Fig 2. There was a 35% (95% CI 10%–48%) risk reduction in all-cause mortality associated with an intake of 35 g per day compared with 19 g per day. This resulted in an absolute risk reduction of 14 (95% CI 4–19) fewer deaths per 1,000 participants over the duration of the studies included. The plotted relationship was not linear (p = 0.005). Further details are shown in the supplementary material (S3 Appendix).

Fig 2 — **Dietary fibre intake and all-cause (left) and CVD mortality (right) in cohorts with type 1 or type 2 diabetes.** The 95% CIs are shown as dashed lines. Cohort data are presented as country specific estimates when possible. Circle size indicates the weighting of each data point, with bigger circles indicating greater influence. CVD, cardiovascular disease.

Glycaemic control

Thirty-three controlled trials of increasing fibre intakes on glycated haemoglobin (HbA1c) are shown in Fig 3. When considering all eligible trials, regardless of the amount of fibre prescribed, HbA1c improved with the interventions when compared with the controls (MD −2.00 mmol/mol, 95% CI −3.30 to −0.71) as shown in Table 1. Fasting glucose levels also improved with increased fibre intake (MD −0.56, 95% CI −0.73 to −0.38 from 34 trials). Influence analysis did not identify any trials that significantly influenced the pooled result for HbA1c or fasting blood glucose. There was no evidence of publication bias in the results for HbA1c and fasting blood glucose. Meta regression did not identify differences in the pooled results for HbA1c or for fasting plasma glucose because of diabetes type, diabetes medication, trial risk of bias, fibre type, trial size, or trial duration. Meta regression did indicate the reduction in HbA1c was greater in trials that did not control the weight of participants during the trials (MD −2.67 mmol/mol, 95% CI −4.18 to −1.16 from 28 trials) when compared with trials that did (MD 1.26 mmol/mol, 95% CI −0.15 to 2.68 from 5 trials). Meta regression also indicate the reduction in fasting plasma glucose was greater in trials that included participants with comorbidities (MD −0.91 mmol/L, 95% CI −1.46 to −0.36 from 15 trials) than trials that excluded participants with comorbidities (MD −0.26, 95% CI −0.46 to −0.05 from 19 trials). The results for fasting plasma glucose varied by the global region that the trial was conducted in. Further analyses for HbA1c and fasting blood glucose are shown in the supplementary material (S4 and S5 Appendices). Dose response testing for HbA1c and fasting glucose are shown in Fig 4. Both HbA1c and fasting glucose curves are plotted as a percentage of the baseline fibre intake because there was an interaction with baseline fibre intake when reported, indicating greater benefits were observed for those moving from low to moderate or high intakes.

Table 1. Summary differences in glycaemic control and cardiometabolic risk factors between intervention and control groups from trials of increasing fibre intakes.

Outcome	Trials	Participants (I/C)	Initial I²	MD (95% CI)
HbA1c (mmol/mol)	33	815/738	98.7%	−2.00 (−3.30 to −0.71)
Fasting plasma glucose (mmol/L)	34	936/871	99.1%	−0.56 (−0.73 to −0.38)
Total cholesterol (mmol/L)	27	662/605	98.0%	−0.34 (−0.46 to −0.22)
LDL cholesterol (mmol/L)	21	559/512	96.2%	−0.17 (−0.27 to −0.08)
HDL cholesterol (mmol/L)	25	722/666	96.7%	0.04 (0.01–0.07)
Triglycerides (mmol/L)	28	760/708	97.7%	−0.16 (−0.23 to −0.09)
Body weight (kg)	18	455/422	98.2%	−0.56 (−0.98 to −0.13)
BMI (kg/m²)	14	382/381	97.4%	−0.36 (−0.55 to −0.16)
Waist circumference (cm)	8	178/171	97.4%	−1.42 (−2.63 to −0.21)
Systolic blood pressure (mmHg)	12	325/295	98.6%	−1.86 (−4.85 to 1.12)
Diastolic blood pressure (mmHg)	12	325/295	97.1%	−1.19 (−2.87 to 0.49)
C-reactive protein (SMD)	7	216/217	96.9%	−2.80 (−4.52 to −1.09)
Fasting plasma insulin (SMD)	19	489/458	96.4%	−2.03 (−2.92 to −1.13)
HOMA IR (mg/dL)	9	292/289	99.7%	−1.24 (−1.72 to −0.76)

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Abbreviations: BMI, Body Mass Index; HDL, high-density lipoprotein; HOMA IR, homeostatic model assessment of insulin resistance; I/C, intervention/control; LDL, low-density lipoprotein; SMD, standardised mean difference

Fig 4 — HbA1c (top left, data from 16 trials of 758 participants), fasting glucose (top right, data from 18 trials of 979 participants), total cholesterol (bottom left, data from 25 trials of 1,178 participants), and body weight (bottom right, data from 18 trials of 877 participants) from trials of increasing fibre intakes. The 95% CIs are shown as dashed lines. FPG, fasting plasma glucose.

Blood lipids

Twenty-seven controlled trials of increasing fibre intakes on total cholesterol are shown in Fig 5. The summary effects of increasing fibre intake on the reported markers of cholesterol and triglycerides are shown in Table 1. Total cholesterol, LDL cholesterol, and triglycerides all reduced with increased fibre intakes. Influence analysis did not identify any trials that significantly influenced the pooled result for total cholesterol, LDL cholesterol, HDL cholesterol, and triglycerides. No publication bias was observed for these outcomes. Meta regression analyses identified the pooled results for the increasing fibre intakes, and the reduction in total cholesterol, LDL cholesterol, and triglycerides were robust with no differences due to diabetes type, diabetes medication, trial risk of bias, fibre type, trial size, or trial duration. Meta regression indicated that the results for HDL cholesterol varied by global region where the trials were conducted and were higher in trials of nonviscous fibres (MD 0.11 mmol/L, 95% CI 0.03–0.18 from 6 trials) than in trials of viscous fibres (MD 0.02 mmol/L, 95% CI −0.01 to 0.04 from 11 trials). Dose response testing for total cholesterol indicated the improvement is dose dependent, with higher intakes leading to greater improvements (shown in Fig 4). Further analyses for fibre intakes and blood lipids are shown in the supplementary material (S6–S9 Appendices).

Body weight and additional cardiometabolic risk factors

Pooled estimates for the relationship between increasing dietary fibre and markers of adiposity and additional cardiometabolic risk factors are shown in Table 1. Increasing fibre intake reduced body weight (MD −0.56 kg, 95% CI −0.98 to −0.13 from 18 trials), BMI (MD −0.36 kg/m², 95% CI −0.55 to −0.16 from 14 trials), and waist circumference (MD −1.42 cm, 95% CI −2.63 to −0.21 from 8 trials), despite no advice to reduce energy intake. For waist circumference, removal of 2 trials [47, 74] in influence analysis did not remove the significance of the pooled effect (MD −1.59, 95% CI −3.07 to 0.10 cm). No publication bias was observed for these outcomes. Meta regression indicated the results for body weight and waist circumference were robust, with no differences due to diabetes type, diabetes medication, trial risk of bias, fibre type, trial size, or trial duration. BMI results differed by baseline fibre intake. Dose response testing for body weight is shown in Fig 4. There was no evidence of dose response associations between increasing fibre intake and measures of body weight. Further analyses for these outcomes are shown in the supplementary materials (S10–S12 Appendices). Fasting plasma insulin, C-reactive protein levels, and HOMA IR improved with higher fibre diets; however, blood pressure did not (as shown in Table 1). Influence analysis did not identify any trial that significantly influenced the pooled results. There was a probable publication bias for the evidence relating to fasting plasma insulin, although trim and fill analyses did not appreciably change the observed effect size (SMD −2.48, 95% CI −3.56 to −1.42). Meta regression indicated the results for systolic and blood pressure were robust, with no differences due to diabetes type, diabetes medication, trial risk of bias, fibre type, trial size, or trial duration. Results indicated that for the outcome insulin, dietary fibre trials conducted in the Middle East produced a greater reduction (SMD −6.22, 95% CI −10.84 to −1.61) than trials in Asia (SMD −2.14, 95% CI −3.48 to −0.80) or Europe (SMD −0.65, 95% CI −1.71 to 0.41). Further analyses and information on these outcomes are available in the supplementary material (S13–S17 Appendices).

Heterogeneity

Pooled data from the 2 multicountry prospective cohort studies were largely homogenous, with an I² ≤ 10%. Conversely, pooled controlled trial data had high heterogeneity for each outcome assessed (I² ≥ 90%). Potential sources of bias or markers of trial quality were not identified by meta regression analyses as contributors to heterogeneity nor was the type of diabetes. All subgroups of variables identified as relevant by meta regression analyses are shown in the GRADE tables of the supplementary materials (S18 Appendix). Small study effects, influence analysis, and meta regression analyses each failed to identify a single or consistent cause for the high heterogeneity within the pooled data from trials; however, they did exclude multiple sources of bias or systematic error as determinants of the presented results.

Risk of bias assessment and GRADE tables

Risk of bias was low in the prospective cohort studies, which both achieved 8 out of a possible 9 on the Newcastle-Ottawa Score. The trials provided sufficient reporting for the assessment of data completeness and selective reporting, but overall assessment of bias was limited by insufficient reporting of sequence generation, allocation concealment, and blinding of participants and outcomes. Further information is contained in the supplementary materials (S2 Appendix).

When following GRADE protocols, evidence relating to all-cause mortality from prospective cohort studies was graded as moderate quality, having been upgraded because of a clear dose response. Evidence regarding fasting plasma glucose, total cholesterol, and LDL cholesterol were graded as high because of the dose response. Evidence from trials relating to most cardiometabolic risk factors was graded as being of moderate quality, having been downgraded for high heterogeneity. Full GRADE tables are shown in the supplementary material (S18 Appendix). The PRISMA checklist is shown in S19 Appendix.

Discussion

Summary of findings

The findings from our systematic review and meta-analyses have demonstrated the likely benefits of increasing dietary fibre in people with diabetes. Prospective cohort study data indicate a reduced risk of total mortality in adults with diabetes. Given that in many relatively affluent societies most adults consume around 20 g of dietary fibre per day [26], our data suggest that a 15 g increase to 35 g per day might be a reasonable target that would be expected to reduce risk of premature mortality by 10% to 48%. A similar finding to that observed for total mortality is apparent when considering cardiovascular mortality in relation to dietary fibre intakes, although confidence intervals were wide as a result of few events. Findings from controlled trials indicate that increasing intakes can improve glycaemic control, body weight, total and LDL cholesterol, and CRP, providing evidence to support the findings relating to total and cardiovascular mortality. Our analysis indicates these findings apply to those with type 1 and type 2 diabetes, whether treated on diet alone, oral agents, insulin, or a combination of treatments, as well as those with prediabetes.

What the study adds to the existing literature

Our study extends the findings of a previous systematic review and meta-analysis of controlled trials that examined the effects of dietary fibre, regardless of source, in the management of diabetes [13]. That review considered only the effects on glycaemic control in people with type 2 diabetes. We were able to include 34 more trials that involved an additional 600 participants in both intervention and control groups, included people with type 1 or type 2 diabetes and prediabetes, and examined a range of additional outcomes. We excluded a number of trials included in the 2013 review, which involved changes in other nutrients in addition to an increase in dietary fibre [77,78], comparisons of one type of fibre with another [79–81], or compared a fibre-rich diet with another dietary intervention [82]. Two more recent reviews have been published; one considered the effects of viscous fibre [15], and the other was an umbrella review which provided no new analyses [16].

A substantial body of data derived from well-conducted controlled trials that have compared the effects on glycaemic control and cardiometabolic risk factors of relatively low (around 40%) and relatively high (around 60%) carbohydrate intakes in both type 1 and type 2 diabetes [7,8,10,11] support our findings and their clinical relevance. These studies were not included in our meta-analysis because our principal objective was to examine the effect of increasing dietary fibre intake without advice to change the overall carbohydrate load of the diet. Benefits, particularly in terms of glycaemic control and lipid profiles, were observed with higher carbohydrate intakes, but only when a high proportion of total carbohydrate was derived from foods rich in dietary fibre [11,12]. A high-carbohydrate–low-fibre diet was associated with similar or worse overall glycaemic control, lower HDL, and higher triglyceride levels when compared with lower carbohydrate intakes [83]. These findings were apparent even when energy balance was rigorously controlled. This appears to contradict our findings, which indicated that the effect of fibre on glycated haemoglobin was apparent only in trials that did not attempt to achieve energy balance, suggesting that weight loss may have been responsible for this effect of dietary fibre. However, we identified only 5 trials that measured glycated haemoglobin that involved weight control, so this observation may also have been because of the small number of trials.

Strengths and limitations

The present study has a number of strengths. Arguably, the most important of these is the parallel consideration of the effects of higher fibre intakes in controlled trials and prospective cohort studies. The former approach involved the examination of the effects on glycaemic control and cardiometabolic risk factors and the latter the extent to which these may translate into clinical outcomes. Although the analysis of only 2 cohort studies of participants with type 1 or type 2 diabetes may be seen as a limitation, participants were drawn from 22 countries. Additional information provided to us by the investigators of these studies enabled us to use country-specific effect size estimates. We were also able to demonstrate the dose response effect in terms of the relationship between dietary fibre and total mortality and that the relationship was not linear as had been previously been believed to be the case. Although the dose response effect between dietary fibre and cardiovascular mortality appeared similar to that observed for total mortality, the number of events was smaller and the upper confidence interval remained above 1. Nevertheless, these observations together with the relationship between dietary fibre and the cardiovascular risk factors observed in trials suggest that a dose response effect is indeed likely. So, although it is never possible to fully discount residual confounding in observational studies, the consistency of findings in the trials and cohort studies together with the dose response relationships suggest a causal association.

The meta-analysis of the intervention trials has potential limitations. All pooled analyses from controlled trials were subject to high heterogeneity, and therefore the strength of the evidence was, as required by GRADE, downgraded accordingly. However, such heterogeneity is to be expected given that trials included a variety of interventions and a range of dietary fibre intakes and were undertaken in a variety of populations consuming different diets and with different background lifestyle patterns. Our consideration of dietary fibre from supplements as well as from food sources, such as whole grains, may have contributed to the observed heterogeneity, however, not to the extent that it was detected by meta regression analyses for any outcome. Although there were only 2 controlled trials that were conducted in people with type 1 diabetes, meta regression analyses did not identify type of diabetes as a determining variable for any outcome, such as HbA1c. Furthermore Balk and colleagues [84] demonstrated a clear relationship between dietary fibre and HbA1c in the EURODIAB cohort of people with type 1 diabetes, in addition to the relationship between dietary fibre and total mortality shown by Schoenaker and colleagues [85]. Meta regression analyses also did not identify that potential sources of bias were determining variables of the pooled results, and sensitivity analyses did not identify data integrity issues for the majority of cardiometabolic outcomes. Instead, key variables beyond increasing fibre intake were the amount of fibre provided or consumed by participants at baseline, the global region where the trials were conducted, and participant inclusion criteria other than diabetes type. A further potential limitation to this work was the lack of prospective cohort data in non-European countries. However, the association between higher intakes of fibre and lower HbA1c has been observed in China [86] and Japan [87, 88]. The lack of long-term (12 months or greater) randomised controlled trials of increasing fibre intake in adults with diabetes is somewhat mitigated by the findings of the cohort studies. Thus, we believe that despite the observed heterogeneity the conduct of a meta-analysis was appropriate and our conclusions valid.

Implications of our findings

Previous meta-analyses of clinical trials have demonstrated the potential of fibre supplements derived from psyllium [89] or viscous sources [15] to improve glycaemic control and cardiometabolic risk factors. European guidelines for the management of type 1 and type 2 diabetes have emphasised the benefits of soluble forms of dietary fibre from legumes [90]. However, our systematic review and meta-analyses that included trials in which fibre was increased either by the addition of supplements of extracted or synthetic fibres, or by the inclusion of fibre rich foods, found that the source and type of dietary fibre did not influence the extent of improvements in glycaemic control or the various cardiometabolic measurements. When considering the findings of this research in relation to nutrition recommendations for the management of diabetes, it is noteworthy that the reduction in risk of premature mortality observed in the prospective cohort studies for both type 1 and type 2 diabetes was with fibre principally derived from food sources, rather than from manufactured foods to which extracted or synthetic fibre have been added. So, although the chemistry, physical properties, physiology, and metabolic effects of dietary fibre suggest that the observed benefits in terms of improvement in cardiometabolic risk factors should signal reduced morbidity and greater life expectancy in association with all types and sources of dietary fibre, the only direct evidence for such benefit derives from fibre as it occurs naturally in food. Thus, although a role for fibre supplements should not be excluded, the dose response data from the prospective cohorts studies supports the consumption of high fibre foods, which will most likely contain additional nutrients [91].

Despite not directly addressing the issue, these findings also have implications for recommendations relating to the total amount of carbohydrates in the diabetic dietary prescription. The case has been made for reductions in total carbohydrates, with suggestions that intake should be reduced to below 26% total energy (a ‘low carbohydrate’ diet) or to an even greater extent for a ketogenic diet [92]. Such suggestions have typically been based on relatively short-term studies (of up to 6 months duration), which have shown an improvement in glycaemic control and lipid profiles, especially in those with type 2 diabetes in which total carbohydrates has been reduced [93]. Such studies do not often consider whether the improvements observed are due to the lower carbohydrate load or the reduced energy intake. Longer term follow up indicates no lasting benefit in terms of cardiometabolic risk factors when low carbohydrate diets have been compared with more conventional dietary approaches [93–95].

Conclusion

Aggregated data from intervention trials and cohort studies provide strong support for current nutrition recommendations [90,96], which advise that those with all types of diabetes should be encouraged to have adequate intake of dietary fibre. Vegetables, pulses, whole fruits, and whole grains are excellent sources. There is no suggestion from cohort studies or controlled trials that relatively high intake of these carbohydrate-rich foods are associated with deterioration of glycaemic control or weight gain. These findings do not detract from the widely accepted recommendation to reduce intakes of sugars and rapidly digested starches [97]. Our findings indicate that for those who choose a reduced intake of total carbohydrates, the inclusion of fibre supplements may provide the means of ensuring recommended intake. However, further long-term adequately powered studies will be required to establish whether fibre supplements will confer longer term clinical benefit that is comparable with fibre that occurs naturally in foods.

Supporting information

S1 Appendix. PICO tables: Fibre and whole grains in diabetes management.

PICO, Population, Intervention, Control, and Outcomes.

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S2 Appendix. Identified studies.

Table A: Description of identified prospective studies. Table B: Description of identified intervention trials. Fig A: Cochrane risk of bias tool summary for the trials identified as eligible for this review.

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S3 Appendix. Analyses for fibre and mortality.

Fig A: Higher versus lower analysis for all-cause mortality. Data from 6 European countries in EPIC and EURODIAB cohort with random effects model. Fig B: Higher versus lower analysis for cardiovascular mortality. Data from 6 European countries in EPIC and EURODIAB cohort with random effects model.

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S4 Appendix. Analyses for fibre and HbA1c (mmol/mol).

Fig A: Mean difference in HbA1c (mmol/mol) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses to test for interaction. Fig B: Dose response curve for HbA1c (mmol/mol) when increasing fibre intakes accounting for baseline value when the data were available.

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S5 Appendix. Analyses for fibre and fasting plasma glucose (mmol/L).

Fig A: Mean difference in fasting glucose (mmol/L) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for fasting plasma glucose (mmol/mol) when increasing fibre intakes accounting for baseline value when known.

(DOCX)

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S6 Appendix. Analyses for fibre and total cholesterol (mmol/L).

Fig A: Mean difference in total cholesterol (mmol/L) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for total cholesterol (mmol/L) when increasing fibre intakes.

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S7 Appendix. Analyses for fibre and LDL cholesterol (mmol/L).

Fig A: Mean difference in LDL cholesterol (mmol/L) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for LDL cholesterol (mmol/L) when increasing fibre intakes. LDL, low-density lipoprotein.

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S8 Appendix. Analyses for fibre and HDL cholesterol (mmol/L).

Fig A: Mean difference in HDL cholesterol (mmol/L) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for HDL cholesterol (mmol/L) when increasing fibre intakes. HDL, high-density lipoprotein.

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S9 Appendix. Analyses for fibre and triglycerides (mmol/L).

Fig A: Mean difference in triglycerides (mmol/L) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for triglycerides (mmol/L) when increasing fibre intakes.

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S10 Appendix. Analyses for fibre and body weight (kg).

Fig A: Mean difference in body weight (kg) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for body weight (kg) when increasing fibre intakes.

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S11 Appendix. Analyses for fibre and BMI (kg/m²).

Fig A: Mean difference in BMI (kg/m²) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. BMI, Body Mass Index.

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S12 Appendix. Analyses for fibre and waist circumference (cm).

Fig A: Mean difference in waist circumference (cm) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction.

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S13 Appendix. Analyses for fibre and systolic blood pressure (mmHg).

Fig A: Mean difference in systolic blood pressure (mmHg) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for systolic blood pressure (mmHg) when increasing fibre intakes.

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S14 Appendix. Analyses for fibre and diastolic blood pressure (mmHg).

Fig A: Mean difference in diastolic blood pressure (mmHg) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for diastolic blood pressure (mmHg) when increasing fibre intakes.

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S15 Appendix. Analyses for fibre and C-reactive protein (SMD).

Fig A: Standardised mean difference in CRP between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. CRP, C-reactive protein; SMD, standardised mean difference.

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S16 Appendix. Analyses for fibre and fasting plasma insulin (SMD).

Fig A: Standardised mean difference in fasting insulin between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. SMD, standardised mean difference.

(DOCX)

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S17 Appendix. Analyses for fibre and HOMA IR (mg/dL).

Fig A: Mean difference in HOMA IR (mg/dL) between intervention and control groups from trials of increasing fibre intakes. Table A: Univariate meta regression analyses as tests for interaction. Fig B: Dose response curve for HOMA IR (mg/dL) when increasing fibre intakes. HOMA IR, homeostatic model assessment of insulin resistance.

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S18 Appendix. GRADE tables.

Table A: Do greater intakes of total dietary fibre reduce the risk of all-cause and CVD mortality for adults with type1 or type 2 diabetes? Table B: What is the effect of increasing dietary fibre intakes on HbA1c (mmol/mol) in diabetes management? Table C: What is the effect of increasing dietary fibre intakes on fasting plasma glucose (mmol/L) in diabetes management? Table D: What is the effect of increasing dietary fibre intakes on total cholesterol (mmol/L) in diabetes management? Table E: What is the effect of increasing dietary fibre intakes on LDL cholesterol (mmol/L) in diabetes management? Table F: What is the effect of increasing dietary fibre intakes on HDL cholesterol (mmol/L) in diabetes management? Table G: What is the effect of increasing dietary fibre intakes on triglycerides (mmol/L) in diabetes management? Table H: What is the effect of increasing dietary fibre intakes on body weight (kg) in diabetes management? Table I: What is the effect of increasing dietary fibre intakes on BMI in diabetes management? Table J: What is the effect of increasing dietary fibre intakes on waist circumference (cm) in diabetes management? Table K: What is the effect of increasing dietary fibre intakes on fasting plasma insulin (standardised mean difference) in diabetes management? Table L: What is the effect of increasing dietary fibre intakes on HOMA IR (mg/dL) in diabetes management? Table M: What is the effect of increasing dietary fibre intakes on systolic blood pressure (mmHg) in diabetes management? Table N: What is the effect of increasing dietary fibre intakes on diastolic blood pressure (mmHg) in diabetes management? Table O: What is the effect of increasing dietary fibre intakes on C-reactive protein in diabetes management? BMI, Body Mass Index; CVD, Cardiovascular disease; GRADE, Grading of Recommendations Assessment, Development and Evaluation; HDL, high-denisty lipoprotein; HOMA IR, homeostatic model assessment of insulin resistance; LDL, low-density lipoprotein.

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S19 Appendix. PRISMA Checklist for reporting of systematic reviews.

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Acknowledgments

We warmly acknowledge the authors who responded to our requests for further clarification or additional analyses, in particular, Associate Professor Joline Beulens, Associate Professor Sabita Soedamah-Muthu, Dr. Danielle Schoenaker, and Professor Monika Toeller. We also thank our translators for their work on publications in languages other than English: Dr. Alexandra Chisholm, Ms. Willemijn de Bruin, Dr. Zheng Feei Ma, Ms. Minako Kataoka, Dr. Luciano Rigano, Dr. Santiago Rodríguez-Jiménez, Dr. Pouya Saeedi, and Dr. Olya Shatova.

Abbreviations

BMI: body mass index
CI: confidence interval
CRP: C-reactive protein
CVD: cardiovascular disease
DNSG: Diabetes and Nutrition Study Group of the European Association for the Study of Diabetes
FPG: fasting plasma glucose
GRADE: grading of recommendations assessment, development and evaluation
HbA1c: glycated haemoglobin
HDL: high-density lipoprotein
HOMA IR: homeostatic model assessment of insulin resistance
LDL: low-density lipoprotein
MD: mean difference
PICO: Population, Intervention, Control, and Outcomes
RR: relative risk
SMD: standardised mean difference

Data Availability

All relevant data may be obtained within the manuscript, the supporting information file, or from the original articles.

Funding Statement

This work was funded by the Department of Medicine at the University of Otago, New Zealand (ANR, APA), the Healthier Lives National Science Challenge, New Zealand (JM), and the Edgar Diabetes and Obesity Research Centre, New Zealand (ANR, JM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS Med. doi: 10.1371/journal.pmed.1003053.r001

Decision Letter 0

Adya Misra

25 Sep 2019

Dear Dr. Reynolds,

Thank you very much for submitting your manuscript "Dietary fibre in diabetes management: systematic review and meta analyses" (PMEDICINE-D-19-01995) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Oct 09 2019 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

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We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/plosmedicine/s/submission-guidelines#loc-methods.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Adya Misra, PhD

Senior Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

Abstract please combine methods and findings into one section

Abstract-last sentence of the methods and findings section should include the limitations of your methodology

Abstract- last sentence “… reduce risk of premature mortality”. Should this be followed by…” in diabetic patients?”

At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

Please include an “Introduction” heading at the start of the introduction

Line 70- please remove reference to “new” or clarify if this is an update to a previously published systematic review. Please provide a citation for the same.

Line 72- “has” not “have”

Line 77-78 please avoid assertions of primacy

Page 7- please move the role of the funding source to the “Financial disclosure” section

Please provide p values along with 95% confidence intervals where appropriate

Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.

Line 277- a systematic review cannot demonstrate any health benefit, please revise as necessary

Line 280-281-please clarify if the reduced risk of mortality is for the general population or for patients with diabetes

Please remove page numbers from the PRISMA checklist as these are likely to change

Comments from the reviewers:

Reviewer #1: This manuscript presents results of a systematic review and meta-analysis of dietary fiber in diabetes management. The rationale for conducting the study is well-developed. The authors included 2 prospective studies and 41 intervention trials, and demonstrated the benefits of increasing dietary fiber for reducing mortality and a series of cardiometabolic risk factors in prediabetes, type 1 and 2 diabetes. The statistical analysis is adequate and the potential sources of bias are well considered for each outcome. Here are some major concerns about the study:

1. The number of prospective studies may be too small for a meta-analysis. Therefore, the authors may want to focus on clinical trials (I found one previous publication in Plos Medicine might be informative. PMID: 27434027), and provide some comments two prospective studies, In addition, causal inferences (such as "Cardiovascular mortality risk reduction" in line 169) can rarely be made from observational studies, and more conservative description would be preferred. If the authors want to keep meta-analysis of prospective studies, then influence tests are strongly discouraged as there are only two studies.

2. Some believes that a meta-analysis should not be performed when between-study heterogeneities are large(as in this study), because it shows that findings from these studies are essentially different and cannot be solely explained by random errors. The authors may want to defense their decision to perform a meta.

3. The generalization of conclusion to type 1 diabetes has been listed as a strength of while only two studies have been conduced among T1D patients. The authors may want to comment on if dietary advices for T1D and T2D management are interchangeable, and why an analysis stratified by diabetes type was not performed.

4. Except for mortality and glycemic control, 11 additional cardiometabolic risk factors were discussed in this study. The results of dose response analysis for each outcome in the manuscript text were so brief that need to be further discussed.

Minor concerns:

Line 75, might be useful to mention which CVD risk factors have been considered.

Line 76, "and whether these benefits translate into a reduction in morbidity and mortality" How has this question been addressed ? Does this imply the inclusion of prospective cohort studies ?

Line 175, "This resulted in an absolute risk reduction of 14 (95%CI 4 to" how was this data derived ?

Line 185, it might be useful to describe some study characteristics briefly, such as sample size, doses, % men/women, disease status(T1D/T2D), and duration of intervention.

The flow chart (Figure 1) is confusing-- out of 8,050 records retrieved from initial search, however, the sum of the records from different databases below is 8,086; 42 studies were included according to the flow chart while there are 43 identified studies in Table S1 and Table S2.

Reviewer #2: See attachment

Michael Dewey

Reviewer #3: The systematic review and meta-analysis from Reynolds et al titled: "Dietary fibre in diabetes management: systematic review and meta analysis" provides relevant and comprehensive update on previous literature in this area on a wide scope of outcomes. However, there are several concerns that need to be addressed, outlined below:

- In the introduction, the authors rationalize the need for the systematic review and meta analysis through dietary CHO focus, citing that (lines 63-65) controlled trials confirm potential of relatively high to low CHO intakes in diabetes. The latest SRMA however, does not fully support this stance. Moreover, the SRMA cited from 2013 refer mostly to the benefit of fiber addition/supplementation rather than as part of a high CHO diet. The authors should provide some rationale for the trial in the context of more recent research/meta analysis on whole grain/dietary fibre in DM management (McRae MP. J Chirop Med. 2018; Wang Y et al. Int J Mol Epid Genet. 2019; Jovanovski E et al, Diabetes Care, 2019,e tc ).

- With regards to analysis of mean difference (MD) between intervention and control groups (line 131), please indicate whether MD between end values or MD between change-from-baseline values were used and whether there was an order of preference. I.e. order of preference could be use of change values provided by article if available, followed by calculation of change values where appropriate, followed by end values provided by article and lastly calculation of end values.

- Please provide detail on how the trials with multiple comparison arms were treated? If compared to a single control arm, were the comparisons combined to create a single pair-wise comparison or were they included as separate comparisons? If the latter, were there any adjustments made (ie. was the SE(MD) adjusted) to take this duplicate comparison into account? I.e. In the forest plot for HbA1c (figure 3) it appears that multiple intervention arms from the same trial were listed separately.

- In line 144, please elaborate on the influence analysis, i.e. what determined whether a study was influential?

- Concern that the search is not comprehensive. The authors have used only "dietary fiber/re" or whole grain terms to try to 'comprehensively' capture all research on dietary fiber. It is likely that many possibly eligible trials were missed by not including explicit food search terms or specific known fibers/whole grains or their sources (ie for beans (legumes), oats, cereal etc)... It appears that trials fitting selection criteria have been missed (ie McGeoch et al., 2013 etc). The review here included many cardiometabolic outcomes, such as blood lipids, blood pressure, etc. However, the presented online search term only included glycemia-related search for outcomes (Search#2 Supplementary, pg 3). Again, it is possible that some trials relating to these outcomes may have been missed.

- Within the dose response analysis, how did the authors collectively assess doses of whole grain sources ie 50g of barley, containing ~8% b-glucan fiber, relative to more isolated sources of dietary fiber? Did the authors extrapolate/estimate the amount of fiber from whole food sources? The dose response analysis would otherwise not have much merit. In S1 under a priori subgroup analysis: Amount: is the volume of fibre or whole grain used?

- A priori subgroup analysis included "fibre type: all fibre or just one type (i.e inulin) viscosity, solubility". Please clarify in more detail what fibre types were considered, which 'viscosity' and 'solubility. Is this an inclusive list of all the subanalysis that were performed?

- In the GRADE assessment authors report on categorical analysis of study participant health status (ie presence/absence of renal issues etc). This was not included in the PICO table of a priori subgroup analysis? Please indicate exactly which variables were tested, and whether these variables were determined apriori.

- In table S3 authors exclude based on HbA1c, aged over 65 etc. Is this categorically assessed (ie over vs uder 65?). What does exclusion based on HbA1c or BMI mean? Please be more concise in provision of explanations.

- What singular fibre types were assessed as a dicotomous variables (is Table S1)?

- Were there any restrictions on study duration? It is questionable whether short term trials (ie <3-4wks) are relevant on certain outcomes, especially on your primary outcome.

- The dose response curve for HbA1c is presented as % intake from baseline. How much data was available? The authors do not report on the dose response relationship per amount of fibre intake per se. Does the relationship still hold?

- We need to be very careful in conclusions that the study results cannot be generalized to whole grain as only very few studies evaluated a whole grain. Perhaps that identifies future areas of research. Most of the data is on dietary fiber supplements and concentrates and this perhaps should be acknowledged.

- Please add a section on study limitations. Some limitations are already mentioned in discussion.

- Discussion: Lines 283-284. Was this statement based on subanalysis of background treatment type (ie diet alone vs oral agents, vs insulin vs combination) for each of the 5 outcomes?

- Discussion: Line 324-325. Please provide data on MD according to each category (T1DM, T2DM, pre-diabetes). There are very few studies in the non-T2DM categories.

- Discussion: Line 346: The authors mention previous meta analysis of RCTs demonstrating potential of psyllium and viscous fibers to affect glycemic control. These SRMAs report on significantly larger magnitudes of change (ie the latter SRMA, the effect of viscous fiber is approx. 3 fold higher, including both extracted fibers and whole foods -ie oats). It would be useful to comment on the difference observed and potential of different fiber types to improve magnitude of effect of fiber, rather than focus on all fiber that is highly heterogeneous (as demonstrated here).

- Lines 356-360. Similarly, we need to be careful when extrapolating conclusions on cardiometabolic risk (as the 'only direct evidence for such benefit") based on 2 cohorts that have inherent risk of confounding and in this instance, have not shown a cardiovascular benefit. While the authors rightly conclude that the consumption of high fibre foods should be encouraged (line 361), the conclusions should be in the context of the current evidence from RCTs and fiber sources they studied.

- The authors comment in the discussion on reduced risk of total mortality, but not on results of CV mortality which is the focus of the assessed RF in this review.

- Discussion: Lines 293-304 and 363-372 further discuss comparison of low/high carbohydrate diets which are not considered or explored in this SRMA (as sub-analysis of background diet) and thus may not be very relevant in this context. The fiber in majority of trials is supplemented to the diet. These sections should be less elaborate.

- Lines 305-305: The authors suggest that the weight-loss may be 'principally responsible' for the observed effect on HbA1c. However, the MD in weight-loss reported here and in other SRMAs of dietary fibre is minimal (MD of <1kg) and likely not sufficient to generate the HbA1c reduction observed in this and other SRMAs.

- Minor: Figure 3 describing mean difference in HbA1c contains random descriptors of study (ie either dose, type of fiber, diet in brackets or no descriptor, without apparent systematical order. Please revise.

- Minor: Line 138: Prescribed or measured fibre increase was used in dose response testing. Which was taken when both are reported?

Any attachments provided with reviews can be seen via the following link:

[LINK]

Attachment

Submitted filename: reynolds.pdf

Click here for additional data file.^{(70.7KB, pdf)}

PLoS Med. 2020 Mar 6;17(3):e1003053. doi: 10.1371/journal.pmed.1003053.r002

Author response to Decision Letter 0

15 Oct 2019

Attachment

Submitted filename: PlosMedicine Reviewers comments.docx

Click here for additional data file.^{(46.4KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003053.r003

Decision Letter 1

Adya Misra

26 Nov 2019

Dear Dr. Reynolds,

Thank you very much for submitting your manuscript "Dietary fibre in diabetes management: systematic review and meta analyses" (PMEDICINE-D-19-01995R1) for consideration at PLOS Medicine.

[LINK]

We expect to receive your revised manuscript by Dec 17 2019 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

We look forward to receiving your revised manuscript.

Sincerely,

Adya Misra, PhD

Senior Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

Title- in accordance with comments from Ref 2- please amend title to “Whole grain fibre and management of diabetes: a systematic review and meta-analysis”

Please include a space between text and reference brackets

Page 6-please avoid assertions of primacy

Discussion- a systematic review cannot demonstrate any health benefit, please revise as necessary. Please also tone down conclusions to avoid overreaching.

Please update your literature search, in accordance with comments from Reviewer 3

Comments from the reviewers:

Reviewer #2: The authors have addressed my points.

I still feel that prediction intervals are helpful in the presence of heterogeneity because they tell us about what might be the result from a future study. By contrast the confidence intervals tell us about the precision of the overall mean. If on reflection the authors still feel they are not informative I would not want to push the issue.

Michael Dewey

Reviewer #3: The authors have addressed some of the raised issues in sufficient manner. However, there are several concerns that remain which are very relevant and should be carefully considered before proceeding:

A concern remains that the search is not systematic and comprehensive. The authors state that food sources other than whole grain were not included as search terms. This limits the review to comprehensively searching only whole grain types of fiber. The authors should make this more prominent in their conclusions. The reader should not be misguided to infer all dietary fiber was included.

Similarly, there are a number of cardiometabolic outcomes reported from trials in addition to glycemic measures. The search terms do not include these. While the authors suggest hand search was employed and they believe they would detect most through the glycemic search terms, this is not a systematic review. This is an important limitation.

The last search was done in Jan 2019. This approaches one year (from publication time). A search update is strongly recommended.

The authors state that all dose response testing used the fiber dose. In many trials, the fiber dose is not reported (ie when oats/whole grain is administered). If not available (ie directly from authors), how was the fiber dose estimated (ie of b-glucan in whole oats or barley, psyllium fiber)?

A priori subgroup analysis included type of fiber, viscosity and solubility. The authors did not report on which fibers were categorized in these groups in order to run sub-analysis. Please clarify.

The overall tone and discussion of paper puts emphasis on whole grain. However, majority of trials appear to be supplementation of fiber from various sources to diet (and 2 cohorts). While the authors argue that meta regression did not identify differences between 2 sources (p=0.057), we must be careful how we interpret the available evidence. Evidence, based on the present search for whole grain, is still scarce (only n=4 trials for HbA1c), and most of the data refers to supplemented type. The conclusions therefore need to be cautionary.

Similarly, the concern remains that strong recommendations and conclusions in discussion are based on only 2 European cohorts (ie "the only direct evidence for benefit derives from fibre as it occurs naturally in food), whereas most of the evidence from controlled trials on cardiometabolic risk is on fibre supplement (if discussing natural fiber from foods, ideally all food sources including legumes should have been included in this review).

Despite that meta regression did not identify differences in effect size based on diabetes type, etc. for transparency purposes, information on MD + CIs for each subgroup estimate is warranted, especially in light of multiple comments in this regard.

The authors continue to suggest that the weight-loss observed here may be 'principally responsible' for the observed effect on HbA1c. The MD in body weight was -0.6kg. Guidelines generally cite that sustained weight loss of ≥5kg may improve glycemic control. If deciding to keep, please provide references for the statement in the response referring to <1kg change in weight.

The authors recommend that in those with prediabetes, type 1, or type 2 diabetes - should increase their dietary fibre intakes by 15 grams per day or to 35 grams per day. Does this hold for each diabetes category? What is the basis for 15g? The recommendations should be more cautionary (very little data for type1 DM exists).

Minor note: Sartore 2009 is not randomized trial. Please modify the Table of Characteristics.

Minor note: It would be useful to provide the data for HbA1c in % (NGSP), perhaps in brackets for ease of reader.

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2020 Mar 6;17(3):e1003053. doi: 10.1371/journal.pmed.1003053.r004

Author response to Decision Letter 1

9 Dec 2019

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Submitted filename: PlosMed response to reviewers.docx

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PLoS Med. doi: 10.1371/journal.pmed.1003053.r005

Decision Letter 2

Adya Misra

22 Jan 2020

Dear Dr. Reynolds,

Thank you very much for re-submitting your manuscript "Dietary fibre in diabetes management: systematic review and meta analyses" (PMEDICINE-D-19-01995R2) for review by PLOS Medicine.

I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

Our publications team (plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

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We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by %Jan 29 2020 11:59PM.

Sincerely,

Adya Misra, PhD

Senior Editor

PLOS Medicine

plosmedicine.org

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Requests from Editors:

Author summary- could you provide a sentence in “why was the study done” to outline the importance of fibre in the diet

Author summary- I believe Line 63 has an additional “at”

Title- Please alter the title to include grains in line with comments from Ref 3 in the last round

Methods- please specify, if that’s the case that PRISMA reporting guidelines were used. In addition please provide a reference to the completed checklist

Methods- you have not mentioned a search update as previously discussed. Please note that we are coming up to a year since the last search date and it is standard practice to update the search to ensure no new articles are missed

Methods- please provide information about quality assessment as done in the abstract

Throughout- please ensure all p values are “p” rather than P. Please also revise “HbA1c” to include c in lower case and not subscript

Figure 2 requires clarification. For instance- does this include Type 1 or 2 diabetes patients

Figure 4 requires clarification. For instance please provide a key to the graphs and explain which cardiovascular factors were included

Discussion- In line with the comments from Ref 3 in the last round, in the limitations section please provide a brief explanation regarding the inclusion of grains/legumes in the current meta-analysis and what impact this has on the conclusions (if any).

Methods- please indicate that a full search strategy has been provided as SI

PRISMA checklist- please remove page numbers as these are likely to change and use paragraphs or sections instead

Comments from Reviewers:

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. doi: 10.1371/journal.pmed.1003053.r006

Decision Letter 3

Adya Misra

3 Feb 2020

Dear Dr. Reynolds,

On behalf of my colleagues and the academic editor, Dr. Ronald Ma, I am delighted to inform you that your manuscript entitled "Dietary fibre and whole grains in diabetes management: systematic review and meta analyses" (PMEDICINE-D-19-01995R3) has been accepted for publication in PLOS Medicine.

PRODUCTION PROCESS

Before publication you will see the copyedited word document (in around 1-2 weeks from now) and a PDF galley proof shortly after that. The copyeditor will be in touch shortly before sending you the copyedited Word document. We will make some revisions at the copyediting stage to conform to our general style, and for clarification. When you receive this version you should check and revise it very carefully, including figures, tables, references, and supporting information, because corrections at the next stage (proofs) will be strictly limited to (1) errors in author names or affiliations, (2) errors of scientific fact that would cause misunderstandings to readers, and (3) printer's (introduced) errors.

If you are likely to be away when either this document or the proof is sent, please ensure we have contact information of a second person, as we will need you to respond quickly at each point.

PRESS

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PROFILE INFORMATION

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Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it.

Best wishes,

Adya Misra, PhD

Senior Editor

PLOS Medicine

plosmedicine.org

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Appendix. PICO tables: Fibre and whole grains in diabetes management.

PICO, Population, Intervention, Control, and Outcomes.

(DOCX)

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S2 Appendix. Identified studies.

(DOCX)

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S3 Appendix. Analyses for fibre and mortality.

(DOCX)

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S4 Appendix. Analyses for fibre and HbA1c (mmol/mol).

(DOCX)

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S5 Appendix. Analyses for fibre and fasting plasma glucose (mmol/L).

(DOCX)

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S6 Appendix. Analyses for fibre and total cholesterol (mmol/L).

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S7 Appendix. Analyses for fibre and LDL cholesterol (mmol/L).

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S8 Appendix. Analyses for fibre and HDL cholesterol (mmol/L).

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S9 Appendix. Analyses for fibre and triglycerides (mmol/L).

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S10 Appendix. Analyses for fibre and body weight (kg).

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S11 Appendix. Analyses for fibre and BMI (kg/m²).

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S12 Appendix. Analyses for fibre and waist circumference (cm).

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S13 Appendix. Analyses for fibre and systolic blood pressure (mmHg).

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S14 Appendix. Analyses for fibre and diastolic blood pressure (mmHg).

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S15 Appendix. Analyses for fibre and C-reactive protein (SMD).

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S16 Appendix. Analyses for fibre and fasting plasma insulin (SMD).

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S17 Appendix. Analyses for fibre and HOMA IR (mg/dL).

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S18 Appendix. GRADE tables.

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S19 Appendix. PRISMA Checklist for reporting of systematic reviews.

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Attachment

Submitted filename: reynolds.pdf

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Attachment

Submitted filename: PlosMedicine Reviewers comments.docx

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Submitted filename: PlosMed response to reviewers.docx

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Data Availability Statement

All relevant data may be obtained within the manuscript, the supporting information file, or from the original articles.

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PERMALINK

Dietary fibre and whole grains in diabetes management: Systematic review and meta-analyses

Andrew N Reynolds

Ashley P Akerman

Jim Mann

Roles

Abstract

Background

Methods and findings

Conclusions

Author summary

Why was the study done?

What did the researchers do and find?

What do the findings mean?

Introduction

Methods

PICO tables and eligibility criteria

Literature search

Study selection, data extraction, and risk of bias assessment

Data analysis

Results

Fig 1. Flow chart indicating the process by which eligible prospective cohort studies and controlled trials were identified.

Mortality from prospective cohort studies

Fig 2.

Glycaemic control

Fig 3. Mean difference in glycated haemoglobin (mmol/mol) between intervention and control groups from trials of increasing fibre intakes.

Table 1. Summary differences in glycaemic control and cardiometabolic risk factors between intervention and control groups from trials of increasing fibre intakes.

Fig 4. Dose response curves of increasing fibre intakes and key cardiometabolic risk factors.

Blood lipids

Fig 5. Mean difference in total cholesterol (mmol/L) between intervention and control groups from trials of increasing fibre intakes.

Body weight and additional cardiometabolic risk factors

Heterogeneity

Risk of bias assessment and GRADE tables

Discussion

Summary of findings

What the study adds to the existing literature

Strengths and limitations

Implications of our findings

Conclusion

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Adya Misra

Roles

Author response to Decision Letter 0

Decision Letter 1

Adya Misra

Roles

Author response to Decision Letter 1

Decision Letter 2

Adya Misra

Roles

Decision Letter 3

Adya Misra

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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