Abstract
Aims/hypothesis
Nordic dietary patterns that are high in healthy traditional Nordic foods may have a role in the prevention and management of diabetes. To inform the update of the EASD clinical practice guidelines for nutrition therapy, we conducted a systematic review and meta-analysis of Nordic dietary patterns and cardiometabolic outcomes.
Methods
We searched MEDLINE, EMBASE and The Cochrane Library from inception to 9 March 2021. We included prospective cohort studies and RCTs with a follow-up of ≥1 year and ≥3 weeks, respectively. Two independent reviewers extracted relevant data and assessed the risk of bias (Newcastle–Ottawa Scale and Cochrane risk of bias tool). The primary outcome was total CVD incidence in the prospective cohort studies and LDL-cholesterol in the RCTs. Secondary outcomes in the prospective cohort studies were CVD mortality, CHD incidence and mortality, stroke incidence and mortality, and type 2 diabetes incidence; in the RCTs, secondary outcomes were other established lipid targets (non-HDL-cholesterol, apolipoprotein B, HDL-cholesterol, triglycerides), markers of glycaemic control (HbA1c, fasting glucose, fasting insulin), adiposity (body weight, BMI, waist circumference) and inflammation (C-reactive protein), and blood pressure (systolic and diastolic blood pressure). The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach was used to assess the certainty of the evidence.
Results
We included 15 unique prospective cohort studies (n=1,057,176, with 41,708 cardiovascular events and 13,121 diabetes cases) of people with diabetes for the assessment of cardiovascular outcomes or people without diabetes for the assessment of diabetes incidence, and six RCTs (n=717) in people with one or more risk factor for diabetes. In the prospective cohort studies, higher adherence to Nordic dietary patterns was associated with ‘small important’ reductions in the primary outcome, total CVD incidence (RR for highest vs lowest adherence: 0.93 [95% CI 0.88, 0.99], p=0.01; substantial heterogeneity: I2=88%, pQ<0.001), and similar or greater reductions in the secondary outcomes of CVD mortality and incidence of CHD, stroke and type 2 diabetes (p<0.05). Inverse dose–response gradients were seen for total CVD incidence, CVD mortality and incidence of CHD, stroke and type 2 diabetes (p<0.05). No studies assessed CHD or stroke mortality. In the RCTs, there were small important reductions in LDL-cholesterol (mean difference [MD] −0.26 mmol/l [95% CI −0.52, −0.00], pMD=0.05; substantial heterogeneity: I2=89%, pQ<0.01), and ‘small important’ or greater reductions in the secondary outcomes of non-HDL-cholesterol, apolipoprotein B, insulin, body weight, BMI and systolic blood pressure (p<0.05). For the other outcomes there were ‘trivial’ reductions or no effect. The certainty of the evidence was low for total CVD incidence and LDL-cholesterol; moderate to high for CVD mortality, established lipid targets, adiposity markers, glycaemic control, blood pressure and inflammation; and low for all other outcomes, with evidence being downgraded mainly because of imprecision and inconsistency.
Conclusions/interpretation
Adherence to Nordic dietary patterns is associated with generally small important reductions in the risk of major CVD outcomes and diabetes, which are supported by similar reductions in LDL-cholesterol and other intermediate cardiometabolic risk factors. The available evidence provides a generally good indication of the likely benefits of Nordic dietary patterns in people with or at risk for diabetes.
Registration
ClinicalTrials.gov NCT04094194.
Funding
Diabetes and Nutrition Study Group of the EASD Clinical Practice.
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Introduction
Several dietary patterns high in plant foods have shown advantages for managing cardiometabolic risk. Evidence from prospective cohort studies and RCTs has shown that adherence to the Mediterranean [1,2,3,4,5,6,7,8,9], Dietary Approaches to Stopping Hypertension (DASH) [10], Portfolio [11,12,13,14,15,16,17,18,19] and healthy vegetarian [20, 21] dietary patterns is associated with a lower risk of CVD and a reduction in intermediate cardiometabolic risk factors in adults with and without diabetes. The applicability of these dietary patterns to northern European countries is limited by cultural values and preferences and the availability/costs of specific foods [22,23,24]. Nordic dietary patterns, known variably as the Nordic diet [25], New Nordic Diet [26], healthy Nordic diet [27, 28] and Baltic Sea diet [29], include foods that are typically consumed as part of traditional Nordic diets and that are consistent with Nordic dietary guidelines [26, 30]. These foods include whole-grain cereals (especially rye, oats and barley), berries, other temperate fruits (especially apples and pears), vegetables (especially root and cruciferous vegetables), legumes, fish/shellfish, nuts and canola oil/rapeseed oil (as primary fat sources) and low-fat dairy foods [26, 27, 29, 31].
The benefits of Nordic dietary patterns have been recognised in major clinical practice guidelines on obesity [32], and diabetes [33,34,35,36]. The EASD has not reviewed the evidence or made specific recommendations on Nordic dietary patterns. Although existing systematic reviews and meta-analyses of RCTs support the benefits of Nordic dietary patterns [37,38,39,40], these syntheses did not include prospective cohort studies or assess the certainty of the evidence. To update the EASD clinical practice guidelines for nutrition therapy, the Diabetes Nutrition Study Group commissioned a systematic review and meta-analysis of prospective cohort studies and randomised trials of Nordic dietary patterns and cardiometabolic outcomes, including an assessment of the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach.
Methods
Design
We followed the Cochrane handbook for systematic reviews of interventions [41], with results reported according to Meta-analyses of Observational Studies in Epidemiology (MOOSE) [42] and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) [43] guidelines (see electronic supplementary material [ESM] Table 1). The protocol was registered at ClinicalTrials.gov (NCT04094194).
Data sources and searches
We searched MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials from inception to 9 March 2021 (ESM Table 2). Manual searches supplemented these database searches.
Eligibility criteria
We included prospective cohort studies of Nordic dietary patterns and CVD and diabetes outcomes with a duration of ≥1 year, and RCTs of Nordic dietary patterns and intermediate cardiometabolic outcomes with a duration of ≥3 weeks. Populations had to have diabetes but be free of CVD for assessment of CVD outcomes, be free of diabetes for assessment of diabetes outcomes, and have diabetes or risk factors for diabetes for assessment of intermediate outcomes. Prospective cohort studies were excluded if they did not report outcome data by level of exposure using an index or scale. RCTs were excluded if they lacked a suitable comparator diet (non-isocaloric). If more than one report was available for the same study, then the report with the longest follow-up was used. There were no language restrictions (ESM Tables 3 and 4).
Data extraction
Two reviewers (PM and EV, AJG, LC or AZ) independently extracted the data. The reviewers extracted RRs and 95% CIs for the most adjusted model from prospective cohort studies and mean differences (MDs) and SEMs from RCTs. MDs for change were preferred over end values. Missing SEMs were derived from available data using published formulae [44]. Ritz et al [45] were contacted for missing data. All disagreements were reconciled by consensus or arbitration by a senior reviewer (TAK, JLS)
Outcomes
The primary outcome was total CVD incidence in prospective cohort studies and LDL-cholesterol in RCTs. Secondary outcomes were CVD mortality, CHD incidence and mortality, stroke incidence and mortality and type 2 diabetes incidence in prospective cohort studies, and other established lipid targets (non-HDL-cholesterol, HDL-cholesterol, triglycerides [TG], apolipoprotein B [ApoB]), markers of glycaemic control (HbA1c, fasting blood glucose, fasting insulin), adiposity (body weight, BMI, waist circumference [WC]) and inflammation (C-reactive protein [CRP]) and blood pressure in RCTs.
Risk of bias
Two reviewers independently assessed risk of bias. The Newcastle–Ottawa Scale (NOS) [46] was used to assess the risk of bias in prospective cohort studies. Studies with a score of ≥6 out of 9 were considered to be of high quality. The Cochrane risk of bias tool was used to assess the risk of bias in RCTs [47] across five domains (sequence generation, allocation concealment, blinding, incomplete outcome data and selective reporting).
Statistical analysis
Pairwise meta-analyses were conducted using Review Manager (RevMan) version 5.3 (The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark). All other analyses were performed using Stata 16.1 (StataCorp LP, College Station, TX, USA).
Data were pooled using DerSimonian and Laird random-effects models. RR estimates were obtained from natural log-transformed RRs and their SEMs comparing the highest with the lowest diet scores in the most adjusted models; MDs were obtained by pooling MDs and SEMs. Hazard ratios and odds ratios were treated as RRs [48]. Paired analyses were conducted for crossover trials (correlation coefficient=0.5) [49]. Fixed-effects models were used when fewer than five comparisons were available [50].
Interstudy heterogeneity was estimated using the Cochran Q test and quantified by the I2 statistic. An I2≥50% and pQ<0.1 were considered evidence of substantial heterogeneity. Sources of heterogeneity were explored in sensitivity and subgroup analyses. Sensitivity analyses were conducted by the systematic removal of each study and recalculation of the pooled estimate. Sensitivity analyses by energy control were conducted by restricting analyses to ad libitum (free intake without strict energy control) trials for adiposity outcomes. If ten or more comparisons were available, subgroup analyses were performed by meta-regression. A priori subgroup analyses were conducted by follow-up, sex, risk of bias and funding source for prospective cohort studies, and by study design, follow-up, comparator, baseline values, risk of bias, diabetes duration and funding source for RCTs.
We performed dose–response meta-analyses (DRMs) using one-stage random effects [51,52,53]. Nordic dietary pattern scores were scaled or standardised to the Nordic diet score, with a range between 0 and 6 [54]. Linear DRM was expressed per 1-point score, and global DRM was assessed using the non-linear association at the highest global population adherence. DRMs were planned for RCTs when adherence scores were available for six or more study comparisons.
If ten or more comparisons were available, publication bias was assessed by visual inspection of funnel plots and formal testing with the Begg and Egger tests [55, 56], with significance set at p<0.1. The Duval and Tweedie trim-and-fill method was used to adjust for funnel plot asymmetry [57].
GRADE assessment
The GRADE approach [58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73] was used to assess the certainty of the evidence. The evidence from prospective cohort studies was classified initially as being of low certainty and that from RCTs was classified initially as being of high certainty, with the evidence downgraded or upgraded based on prespecified criteria. Criteria for downgrading included study limitations (high risk of bias), inconsistency (substantial unexplained interstudy heterogeneity: I2>50% and pQ<0.10), indirectness (presence of factors that limit generalisability), imprecision (95% CIs cross prespecified minimally important differences [MIDs]) and publication bias (detection of small-study effects). Criteria for upgrading included a dose–response gradient, large magnitude of effect (RR≥2 or RR≤0.5; prospective cohort studies only) and attenuation by plausible confounding. We interpreted the magnitude of the effect/association [74] based on prespecified criteria using MIDs and adapted GRADE thresholds using the following language: ‘trivial’, ‘small important’, ‘moderate’, ‘large’ and ‘very large’. At the request of the referees, we also performed a post hoc assessment of the certainty of the evidence using NutriGrade [75].
Results
Figure 1 shows the results of the literature search. We identified 1959 reports, of which 21 met the eligibility criteria: 15 prospective cohort studies (n=1,057,176, with 41,708 cardiovascular events and 13,121 diabetes cases) [76,77,78,79,80,81,82,83,84,85,86,87,88,89,90] and six RCTs (n=717) [28, 91,92,93,94,95].
Prospective cohort studies
Study characteristics
Table 1 and ESM Tables 5 and 6 show the characteristics of the prospective cohort studies included. All studies were conducted in European adult populations. The median age of participants was 49–57 years. All of the prospective cohort studies included individuals with diabetes except for the four studies (six comparisons) assessing the association of Nordic dietary patterns with type 2 diabetes incidence [82, 87,88,89]. The median follow-up was 13.5–17.65 years. Adherence to Nordic dietary patterns was assessed using six scores: Healthy Nordic Food Index (eight studies [76, 77, 79,80,81, 83, 85, 88]), diet quality index (DQI) that assesses adherence to the 2005 Swedish Nutrition Recommendations (SNR) (DQI-SNR; three studies [78, 84, 89]), Nordic diet score (one study [82]), Baltic Sea Diet Score (one study [87]), modified Baltic Sea Diet Score (one study [90]) and Danish food-based dietary guidelines (one study [86]). All studies were funded by government, university or not-for-profit sources (agency funding) except one [87], which received agency and industry funding.
ESM Table 7 shows the confounding variables included in the most adjusted model for each of the cohorts included. The median (range) number of variables in the most adjusted model was 12 (7–17).
Risk of bias
ESM Table 8 shows the NOS scores for the cohorts included. All studies were of high quality (NOS≥6).
Primary outcome
Figures 2, 3a and ESM Fig. 1 show the extreme quantiles and DRMs for the association between Nordic dietary patterns and the primary outcome, total CVD incidence. Nordic dietary patterns were associated with a lower incidence of CVD (RR, 0.93 [95% CI 0.88, 0.99], p=0.01; substantial heterogeneity: I2=88%, pQ<0.001) comparing participants with the highest adherence with those with the lowest adherence. There was an inverse linear dose–response gradient for adherence to Nordic dietary patterns and a decrease in total CVD incidence of 2% per increase in unit of the Nordic diet score (RR 0.98 [95% CI 0.97, 0.99], p<0.001), with global DRM showing that adherence to Nordic dietary patterns over the global range of scores was associated with a reduction in incidence of CVD of 7% (RR 0.93 [95% CI 0.88, 0.99]).
Secondary outcomes
Figures 2, 3b–e and ESM Figs 2–5 show the extreme quantiles and DRMs for the association between Nordic dietary patterns and the secondary cardiometabolic outcomes. Nordic dietary patterns were associated with lower CVD mortality (RR 0.81 [95% CI 0.73, 0.90], p<0.001; no substantial heterogeneity: I2=33%; pQ=0.16) and stroke incidence (RR 0.88 [95% CI 0.70, 0.98], p=0.02; no substantial heterogeneity: I2=2%; pQ=0.36) comparing participants with the highest adherence with those with the lowest adherence. There was an inverse linear dose–response relationship for adherence to Nordic dietary patterns (pdeparture-from-linearity≥0.05) for all secondary outcomes, with global DRM showing that adherence to Nordic dietary patterns over the global range of scores was associated with reductions of 26% in CVD mortality (RR 0.74 [95% CI 0.69, 0.80]) and reductions of 12%, 13% and 9% in the incidence of CHD (RR 0.88 [0.79, 0.98]), stroke (RR 0.87 [0.78, 0.97]) and type 2 diabetes (RR 0.91 [0.84, 0.99]), respectively. No studies reported CHD or stroke mortality outcomes.
Sensitivity analyses
ESM Table 9 shows the results of the influence analyses. The systematic removal of seven individual cohort comparisons altered several findings: the significance of the summary estimate changed from non-significant to significant for CHD incidence; the evidence of substantial heterogeneity was partially or fully explained for incidence of CVD, CHD and type 2 diabetes; and the significance of the summary estimate was lost for incidence of CVD and stroke.
Subgroup analyses
No subgroup analyses were undertaken as fewer than ten cohort comparisons were available per outcome.
Publication bias
No publication bias analyses were undertaken as fewer than ten cohort comparisons were available per outcome.
Randomised controlled trials
Study characteristics
Table 2 and ESM Table 10 show the characteristics of the six RCTs included [28, 91,92,93,94,95]. All of the trials were conducted in Europe and had a parallel design. Participants had a median age of 47.65–53.7 years and one or more risk factor for diabetes (overweight or obese [three trials], the metabolic syndrome [one trial], dyslipidaemia [one trial] or high cardiovascular risk [one trial]). Median follow-up was 12–48 weeks. Nordic dietary pattern interventions varied and comprised the New Nordic Diet (one trial [94]), new Nordic recommendations (two trials [91, 93]), Danish official dietary guidelines (one trial [92]) and healthy Nordic diet (two trials [28, 95]). The control diets also varied and comprised general healthy eating recommendation (one trial [93]), usual Western diet (one trial [28]) and usual/habitual Nordic diet (four trials [91, 92, 94, 95]). Feeding control ranged from the provision of dietary advice to the provision of some meals. Three trials received agency funding and three received agency and industry funding.
Risk of bias
ESM Fig. 6 shows the summary and individual Cochrane risk of bias assessments for the included RCTs. Most RCTs were judged as having a low or unclear risk of bias across the five domains. Although three trials were rated as having a high risk of bias in one of the five domains, overall there was no evidence of serious risk of bias.
Primary outcome
Figure 4 and ESM Fig. 7 show the effects of Nordic dietary patterns on the intermediate primary outcome LDL-cholesterol. Adherence to Nordic dietary patterns was associated with a reduction in LDL-cholesterol compared with control diets (MD −0.26 mmol/l [95% CI −0.52, −0.00], pMD=0.05; substantial heterogeneity: I2=89%, pQ<0.001). Linear or non-linear dose–responses could not be assessed.
Secondary outcomes
Figure 4 and ESM Figs 8–20 show the effects of Nordic dietary patterns on the intermediate secondary outcomes. Compared with control diets, Nordic dietary patterns were associated with reductions in non-HDL-cholesterol (−0.69 mmol/l [95% CI −0.9, −0.48], pMD <0.01; substantial heterogeneity: I2=81%, pQ<0.01), ApoB (−0.15 g/l [95% CI −0.19, −0.11], pMD<0.01; substantial heterogeneity: I2=96%, pQ<0.01), body weight (−2.00 kg [95% CI −3.24, −0.75], pMD=0.002; substantial heterogeneity: I2=88%, pQ<0.01), BMI (−0.98 kg/m2 [95% CI −1.19, −0.77], pMD<0.01; no substantial heterogeneity: I2=19%, pQ=0.3); WC (−1.32 cm [95% CI −2.20, −0.43], pMD=0.003; substantial heterogeneity: I2=71%, pQ=0.02); insulin (−7.83 pmol/l [95% CI −12.26, −3.39], pMD<0.01; no substantial heterogeneity: I2=0%, pQ=0.57), systolic blood pressure (SBP; −3.35 mmHg [−5.12, −1.59], pMD<0.01; substantial heterogeneity: I2=50%, pQ=0.11) and diastolic blood pressure (DBP; −1.50 mmHg [−2.62, −0.37], pMD=0.009; no substantial heterogeneity: I2=34%, pQ=0.21). There were no effects on the other intermediate cardiometabolic outcomes. Linear or non-linear dose–responses could not be assessed.
Sensitivity analyses
ESM Table 11 shows selected sensitivity analyses in which systematic removal of individual trials altered the results. Systematic removal of individual trials resulted in the following: loss of significance for LDL-cholesterol, ApoB and WC, although the pooled effect estimates still favoured Nordic diets; change in the pooled effect estimate from non-significant to a significant decrease for TG; and explanation of the substantial heterogeneity for LDL-cholesterol, non-HDL-cholesterol, TG, HDL-cholesterol, BMI, WC, DBP and CRP.
ESM Fig. 21 shows the results of the sensitivity analysis including only ad libitum trials. Removal of two trials (those by Uusitupa et al [95] [isocaloric trial] and Huseinovic et al [93] [negative energy balance trial]) resulted in reductions in body weight (MD −2.16 kg [95% CI −3.51 to −0.82 mmol/l], pMD=0.002; substantial heterogeneity: I2=82%, pQ=0.001), BMI (MD −0.85 kg/m2 [95% CI −1.31 to −0.40 mmol/l], pMD<0.01; no substantial heterogeneity: I2=37%, pQ=0.20) and WC (−1.32 cm [95% CI −3.49, 0.84], pMD=0.23; substantial heterogeneity: I2=78%, pQ=0.01) without changing the significance or the magnitude of the effect, except for BMI, for which the magnitude of the reduction was decreased.
Subgroup analyses
No subgroup analyses were undertaken as fewer than ten trial comparisons were available for any outcome.
Publication bias
No publication bias analyses were undertaken as fewer than ten trial comparisons were available for any outcome.
Medication use
Of the six trials, only two reported medication use [94, 95]. In one trial, one participant in the New Nordic Diet group and one in the average Danish diet group began antihypertensive medication during the study [94], while in the other trial no changes in dosage of antihypertensive and lipid-lowering medication were allowed during the study [95].
Adverse events
Two trials assessed adverse events [28, 92]. No adverse events were reported.
Acceptability
No trials assessed the acceptability of Nordic dietary patterns. Four trials assessed adherence to the Nordic dietary pattern, which was reported as satisfactory or high [28, 91, 94, 95].
GRADE assessments
ESM Table 12 summarises the GRADE assessments of the associations between Nordic dietary patterns and CVD outcomes in prospective cohorts. The certainty of evidence for the primary outcome, total CVD incidence (small important reduction), was graded as low owing to downgrades for imprecision and inconsistency and an upgrade for dose–response gradient. For the secondary outcomes, the certainty of evidence was graded as moderate for CVD mortality (moderate reduction) owing to an upgrade for dose–response gradient and no downgrades, and low for CHD (small important reduction), stroke (small important reduction) and type 2 diabetes (small important reduction) owing to downgrades for imprecision and upgrades for dose–response gradient in all cases. NutriGrade assessments gave the same ratings as the GRADE approach for four out of five (80%) outcomes, and a lower rating for the remaining outcome (20%) (ESM Table 13).
ESM Table 14 shows the GRADE assessments conducted for the effect of Nordic dietary patterns on cardiometabolic risk factors in RCTs. The certainty of evidence for the primary outcome, LDL-cholesterol (small important reduction), was graded as low owing to downgrades for inconsistency and imprecision. The certainty of evidence for the secondary outcomes was graded as high for HDL-cholesterol (no effect), BMI (moderate reduction) and blood glucose (no effect) in the absence of downgrades, moderate for non-HDL-cholesterol (large reduction), ApoB (moderate reduction) and body weight (moderate reduction) owing to downgrades for inconsistency, and moderate for TG (no effect), insulin (small important reduction), WC (trivial reduction), SBP (small important reduction), DBP (trivial reduction) and CRP (no effect) owing to downgrades for imprecision. Compared with the GRADE approach, NutriGrade assessments gave the same ratings for one of the 14 (7%) outcomes and lower ratings for 13 of 14 (93%) outcomes (ESM Table 15).
Discussion
We conducted a comprehensive systematic review and meta-analysis of Nordic dietary patterns and cardiometabolic outcomes, including 15 prospective cohort studies (n=1,057,176 with 41,708 cardiovascular events and 13,121 diabetes cases) and six RCTs (n=717). We observed that Nordic dietary patterns were associated with a small important reduction in the primary clinical outcome of CVD incidence (7% by global DRM), with similar or greater reductions in the secondary clinical outcomes of CVD mortality (26% by global DRM), CHD incidence (12% by global DRM) and stroke incidence (13% by global DRM) in adults with diabetes, and type 2 diabetes incidence (9% by global DRM) in adults without diabetes. These reductions were supported by reductions in intermediate cardiometabolic outcomes in adults with one or more risk factor for diabetes. Nordic dietary patterns resulted in small important reductions in the primary intermediate outcome LDL-cholesterol (−0.26 mmol/l) and similar or greater reductions in the secondary intermediate outcomes of non-HDL-cholesterol (−0.69 mmol/l), ApoB (−0.15 g/l), body weight (−2 kg), insulin (−7.83 pmol/l) and SBP (−3.35 mmHg). Other secondary outcomes showed trivial reductions or no effect.
Findings in the context of the literature
We are not aware of any previous systematic reviews and meta-analyses of prospective cohort studies of Nordic dietary patterns; however, our findings agree with those of previous systematic reviews and meta-analyses of key foods that are emphasised as being part of Nordic dietary patterns. Systematic reviews and meta-analyses of prospective cohort studies have demonstrated that total fruit and vegetable intake is associated with reductions in CVD, CHD and stroke incidence and/or mortality, with the greatest benefits found for certain root vegetables (i.e. carrots) and cruciferous vegetables (including cabbage) [96]. Other key components of Nordic dietary patterns, including whole grains (oats and rye) [97, 98], fish [99] and legumes [100], have been associated with reductions in CVD, stroke and cardiovascular mortality and/or incidence of type 2 diabetes.
Our findings also agree with and expand on those of several previous systematic reviews and meta-analyses of RCTs of Nordic dietary patterns and intermediate cardiometabolic outcomes. Three systematic reviews and meta-analyses of RCTs found reductions in SBP associated with Nordic dietary patterns [37, 101, 102]. One systematic review and meta-analysis of RCTs showed similar reductions in blood insulin levels but not blood glucose levels [38]. A second showed similar reductions in body weight but not BMI and WC [39, 103]. A third showed no effect of Nordic dietary patterns on inflammation, which agrees with our finding of no effect on CRP [40], although a single RCT did report interleukin-1 receptor antagonism [95].
There are several possible explanations for the observed benefits of Nordic dietary patterns. One is the concordance of Nordic dietary patterns with Mediterranean, DASH, Portfolio, healthy vegetarian and low glycaemic index/load dietary patterns, which are associated with improvements in clinical cardiometabolic outcomes and intermediate cardiometabolic outcomes [3, 10,11,12, 104,105,106,107]. Key foods shared with these other dietary patterns [27, 30] have also been shown to improve intermediate cardiometabolic outcomes. These foods include viscous fibres [108, 109] from oats and barley [110, 111], temperate fruit and berries [112, 113], nuts [103, 114,115,116] and legumes [117,118,119,120,121,122,123,124,125]. Another possible explanation for the observed benefits of Nordic dietary patterns is because of weight loss induced by the interventions. Most of the included RCTs, however, adjusted for weight [28, 94] or BMI [91, 93], indicating that effects were largely independent of weight loss.
Strengths and limitations
The present systematic review and meta-analysis has several strengths. It provides a comprehensive synthesis of the currently available evidence on the potential role of Nordic dietary patterns in both patient-important and surrogate CVD outcomes. We used a systematic search strategy to capture all pertinent prospective cohort studies and RCTs. We explored dose–responses in prospective cohorts, which highlighted a significant linear protective association of Nordic dietary patterns with CVD outcomes. We assessed the certainty of the evidence using the GRADE approach and performed a post hoc analysis using NutriGrade (although the latter was not used to inform our assessment of the certainty of the evidence as it was not prespecified or endorsed by the guidelines committee).
Several limitations were identified in the available evidence. First, there was evidence of serious inconsistencies. We observed substantial unexplained heterogeneity in the primary outcomes, total CVD incidence in the prospective cohort studies and LDL-cholesterol in the RCTs, and in several of the secondary outcomes in the RCTs. Second, there was evidence of serious imprecision. We observed imprecision in the primary outcomes, total CVD incidence in the prospective cohort studies and LDL-cholesterol in the RCTs, and in several of the secondary outcomes. Finally, there was some evidence of indirectness. Different criteria were used to define Nordic dietary patterns, which may have contributed to the heterogeneity observed. We downgraded the evidence for HbA1c because of serious indirectness, as data were available from only a single RCT of a single Nordic dietary pattern (Danish official dietary guidelines), limiting generalisability to other Nordic dietary patterns. We did not, however, downgrade the evidence for other outcomes because of the use of different definitions of Nordic dietary patterns, as the evidence appeared robust to the different definitions. Another potential source of indirectness was the inability to isolate the effects/associations in diabetes. Prospective cohort studies did not provide subgroup data by diabetes status, and none of the RCTs included individuals with diabetes. We did not downgrade for indirectness here, as the prospective cohort studies did include a representative proportion of individuals with diabetes and the RCTs included individuals at risk for diabetes. The key components of Nordic dietary patterns have also been shown individually to lower cardiometabolic risk factors reliably in people with diabetes [108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126].
Implications
Dietary interventions remain the cornerstone of type 2 diabetes and CVD prevention and management [127,128,129]. Clinical practice guidelines for obesity, type 2 diabetes and CVD have shifted from focusing on single nutrients to focusing on dietary patterns [127,128,129]. Nordic dietary patterns ( ≥25% energy as whole grains, ≥175g/day of temperate fruits, ≥150–200g/day of berries, ≥175g/day of vegetables, legumes and canola oil, three or more servings/week of fatty fish, two or more servings/day of low-fat dairy products) [95] have important similarities (with some differences [130, 131]) to other established dietary patterns that are high in plant foods such as the Mediterranean, DASH, Portfolio and vegetarian dietary patterns. Population intakes of Nordic countries, as well as other European countries, Canada and the USA, do not meet the targets for these other dietary patterns [125, 132,133,134,135]. Nordic dietary patterns may provide a promising alternative to help individuals in Nordic countries and elsewhere achieve the cardiometabolic benefits of dietary interventions. This approach may have impacts beyond health [136, 137]. As pointed out by the WHO Regional Office for Europe, the Nordic nutrition recommendations will be the first nutrition recommendations integrating environmental health with personal health [137].
Conclusions
Adherence to Nordic dietary patterns is associated with generally small important reductions in major CVD outcomes and incidence of diabetes and similar or greater reductions in LDL-cholesterol and other intermediate cardiometabolic outcomes. Our confidence in the evidence is generally low to moderate, with the evidence for reductions in clinical outcomes from prospective cohort studies supported by reductions in intermediate cardiometabolic outcomes from RCTs. Although there is a need for more long-term RCTs using standard definitions of Nordic dietary patterns that assess the effects on clinical outcomes and intermediate cardiometabolic outcomes (especially HbA1c) in diabetes, the available evidence provides a generally good indication of the likely benefit of Nordic dietary patterns in adults with or at risk for diabetes.
Data availability
All data generated or analysed during this study are included in this published article (and its ESM information files).
Abbreviations
- ApoB:
-
Apolipoprotein B
- CRP:
-
C-reactive protein
- DASH:
-
Dietary Approaches to Stopping Hypertension
- DBP:
-
Diastolic blood pressure
- DQI-SNR:
-
Diet quality index (DQI) that assesses adherence to the 2005 Swedish Nutrition Recommendations (SNR)
- DRM:
-
Dose–response meta-analysis
- GRADE:
-
Grading of Recommendations, Assessment, Development and Evaluation
- MD:
-
Mean difference
- MID:
-
Minimally important difference
- NOS:
-
Newcastle–Ottawa Scale
- PRISMA:
-
Preferred Reporting Items for Systematic Reviews and Meta-analyses
- SBP:
-
Systolic blood pressure
- TG:
-
Triglycerides
- WC:
-
Waist circumference
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Acknowledgements
Aspects of this work were presented at the 36th International Symposium on Diabetes and Nutrition, Opatija, Croatia, 27–29 June 2018, and at Nutrition 2020 Live Online, 1–4 June 2020. With the exception of the Diabetes and Nutrition Study Group of the Clinical Practice Guidelines Expert Committee for Nutrition Therapy, none of the sponsors had a role in any aspect of the study, including design and conduct of the study; collection, management, analysis and interpretation of the data; and preparation, review and approval of the manuscript or decision to publish.
Authors’ relationships and activities
AZ is a part-time research associate at INQUIS Clinical Research (formerly Glycemic Index Laboratories), a contract research organisation, and a consultant for the Glycemic Index Foundation. AJG has received consulting fees from Solo GI Nutrition and an honorarium from the Soy Nutrition Institute. LC was a Mitacs Elevate postdoctoral 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. TAK has received research support from the CIHR, the International Life Science Institute (ILSI) and the National Honey Board. He has been an invited speaker at the Calorie Control Council Annual Meeting for which he received an honorarium. EMC reports grants from the Natural Sciences and Engineering Research Council of Canada and the CIHR while this study was being conducted, has received research support from Lallemand Health Solutions and Ocean Spray, and has received consultant fees and speaker and travel support from Danone and Lallemand Health Solutions (all are outside this study). DR is director of Vuk Vrhovac University Clinic for Diabetes, Endocrinology and Metabolic Diseases at Merkur University Hospital, Zagreb, Croatia. He is the president of the Croatian Society for Diabetes and Metabolic Disorders of the Croatian Medical Association. He serves as an Executive Committee member of the Croatian Endocrine Society, Croatian Society of Obesity and Croatian Society for Endocrine Oncology. He was a board member and secretary of IDF Europe and is currently the chair of the IDF Young Leaders in Diabetes (YLD) Programme. He has served as an Executive Committee member of the Diabetes and Nutrition Study Group of the EASD and currently serves as an Executive Committee member of the Diabetes and Cardiovascular Disease Study Group of the EASD. He has served as principal investigator or co-investigator in clinical trials for AstraZeneca, Eli Lilly, MSD, Novo Nordisk, Sanofi Aventis, Solvay and Trophos. He has received travel support, speaker fees and honoraria for advisory board engagements and/or consulting fees from Abbott, Amgen, AstraZeneca, Bayer, Belupo, Boehringer Ingelheim, Eli Lilly, LifeScan – Johnson & Johnson, the International Sweeteners Association, Krka, Medtronic, Mediligo, Mylan, Novartis, Novo Nordisk, MSD, Pfizer, Pliva, Roche, Salvus, Sandoz, Solvay, Sanofi Aventis and Takeda. HK is Director of Clinical Research at the Physicians Committee for Responsible Medicine, a non-profit organisation that provides nutrition education and research. JS-S reports serving on the board of and receiving grant support through his institution from the International Nut and Dried Fruit Council (INC) and the Eroski Foundation. He reports serving on the Executive Committee of the Instituto Danone Spain. He reports receiving research support from the Instituto de Salud Carlos III, Spain; Ministerio de Educación y Ciencia, Spain; the Departament de Salut Pública de la Generalitat de Catalunya, Catalonia, Spain; the European Commission; the California Walnut Commission, USA; Patrimonio Comunal Olivarero, Spain; La Morella Nuts, Spain; and Borges, Spain. He reports receiving consulting fees or travel expenses from Danone, the California Walnut Commission, the Eroski Foundation, the Instituto Danone Spain, Nuts for Life, the Australian Nut Industry Council, Nestlé, Abbot and Font Vella y Lanjarón. He is on the Clinical Practice Guidelines Expert Committee of the EASD and served on the Scientific Committee of the Spanish Agency for Food Safety and Nutrition and the Spanish Federation of the Scientific Societies of Food, Nutrition and Dietetics. He is a member of the International Carbohydrate Quality Consortium (ICQC) and an Executive Board Member of the Diabetes and Nutrition Study Group of the EASD. CWCK has received grants or research support from the Advanced Food and Materials Network, Agriculture and Agri-Food Canada (AAFC), the Almond Board of California, Barilla, the CIHR, the Canola Council of Canada, the International Nut and Dried Fruit Council, the International Tree Nut Council Nutrition Research and Education Foundation, Loblaw Brands, the Peanut Institute, Pulse Canada and Unilever. He has received in-kind research support from the Almond Board of California, Barilla, the California Walnut Commission, Kellogg Canada, Loblaw Brands, Nutrartis, Quaker (PepsiCo), the Peanut Institute, Primo, Unico, Unilever, WhiteWave Foods/Danone. He has received travel support and/or honoraria from Barilla, the California Walnut Commission, the Canola Council of Canada, General Mills, the International Nut and Dried Fruit Council, the International Pasta Organization, Lantmannen, Loblaw Brands, the Nutrition Foundation of Italy, the Oldways Preservation Trust, Paramount Farms, the Peanut Institute, Pulse Canada, Sun-Maid, Tate & Lyle, Unilever and White Wave Foods/Danone. He has served on the scientific advisory board for the International Tree Nut Council, International Pasta Organisation, McCormick Science Institute and Oldways Preservation Trust. He is a founding member of the ICQC and an Executive Board Member of the Diabetes and Nutrition Study Group of the EASD, is on the Clinical Practice Guidelines Expert Committee for Nutrition Therapy of the EASD and is a Director of the Toronto 3D Knowledge Synthesis and Clinical Trials foundation. JLS has received research support from the Canadian Foundation for Innovation, the Ontario Research Fund, the Province of Ontario Ministry of Research, Innovation and Science, the CIHR, Diabetes Canada, the American Society for Nutrition (ASN), the International Nut and Dried Fruit Council Foundation, the National Honey Board (US Department of Agriculture [USDA] honey ‘Checkoff’ programme), the Institute for the Advancement of Food and Nutrition Sciences (IAFNS; formerly ILSI North America), Pulse Canada, the Quaker Oats Center of Excellence, the United Soybean Board (USDA soy ‘Checkoff’ programme), 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 (established by the Alberta Pulse Growers), the Plant Protein Fund at the University of Toronto (which has received contributions from IFF) and the Nutrition Trialists Fund at the University of Toronto (established by an inaugural donation from the Calorie Control Council). He has received food donations to support RCTs from the Almond Board of California, the California Walnut Commission, the Peanut Institute, Barilla, Unilever/Upfield, Unico/Primo, Loblaw Companies, Quaker, Kellogg Canada, WhiteWave Foods/Danone, Nutrartis and Dairy Farmers of Canada. He has received travel support, speaker fees and/or honoraria from the ASN, Danone, Dairy Farmers of Canada, FoodMinds, Nestlé, Abbott, General Mills, the Comité Européen des Fabricants de Sucre (CEFS), Nutrition Communications, the International Food Information Council (IFIC), the Calorie Control Council and the International Glutamate Technical Committee. He has or has had ad hoc consulting arrangements with Perkins Coie, Tate & Lyle, Phynova 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 Scientific Advisory Committee. He is on the Clinical Practice Guidelines Expert Committees of Diabetes Canada, the EASD, the Canadian Cardiovascular Society and Obesity Canada/Canadian Association of Bariatric Physicians and Surgeons. He serves or has served as an unpaid member of the Board of Trustees and an unpaid scientific advisor for the Food, Nutrition, and Safety Program (FNSP) and the Carbohydrates Committee of the IAFNS. He is a member of the ICQC, an Executive Board Member of the Diabetes and Nutrition Study Group of the EASD, and Director of the Toronto 3D Knowledge Synthesis and Clinical Trials foundation. His spouse is an employee of AB InBev. PM, EV, SBM, VC, US, UR, MU, A-MA, KH and IT declare that there are no relationships or activities that might bias, or be perceived to bias, their work.
Contribution statement
US, UR, MU, A-MA, KH, IT, DR, HK, JSS, CWCK, SBM and JLS were responsible for the conception and design of the study. PM, EV, AJG, LC and AZ acquired the data. PM, AZ and TAK performed the statistical analyses. PM, AZ, AJG, TAK, LC, SBM, VC and JLS drafted the article. All authors had access to the data and participated in the analysis and interpretation of the data, provided critical revision of the article for important intellectual content and approved the final version for publication. JLS is the guarantor. He accepts full responsibility for the conduct of the study, integrity of the data, accuracy of the data analyses and decision to publish.
Funding
Open access funding provided by University of Eastern Finland (UEF) including Kuopio University Hospital. The Diabetes and Nutrition Study Group of the EASD commissioned this systematic review and meta-analysis and provided funding and logistical support for meetings as part of the development of the EASD clinical practice guidelines for nutrition therapy. This work was also supported by the Canadian Institutes of Health Research (CIHR; reference no. 129920) through the Canada-wide Human Nutrition Trialists’ Network (NTN). The Diet, Digestive tract, and Disease (3D) Centre, funded through the Canada Foundation for Innovation and the Ministry of Research and Innovation’s Ontario Research Fund, provided the infrastructure for the conduct of this work. PM was funded by a Connaught Fellowship, an Onassis Foundation Fellowship and a Peterborough KM Hunter Charitable Foundation Scholarship. AZ was funded by a Toronto3D Postdoctoral Fellowship Award and a Banting and Best Diabetes Centre (BBDC) Fellowship in Diabetes Care. AJG was funded by a Nora Martin Fellowship in Nutritional Sciences, the Banting & Best Diabetes Centre Tamarack Graduate Award in Diabetes Research, the Peterborough K. M. Hunter Charitable Foundation Graduate Award and an Ontario Graduate Scholarship. LC was funded by a Mitacs Elevate Postdoctoral Fellowship Award. TAK was funded by a Toronto 3D Postdoctoral Fellowship Award. EMC held the Lawson Family Chair in Microbiome Nutrition Research at the Lawson Centre for Child Nutrition, Temerty Faculty of Medicine, University of Toronto. JS-S is partially supported by the Catalan Institution for Research and Advanced Studies (ICREA) under the ICREA Acadèmia programme. JLS was funded by a PSI Graham Farquharson Knowledge Translation Fellowship, Canadian Diabetes Association Clinician Scientist Award, CIHR Institute of Nutrition, Metabolism and Diabetes (INMD)/Canadian Nutrition Society (CNS) New Investigator Partnership Prize and BBDC Sun Life Financial New Investigator Award.
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Massara, P., Zurbau, A., Glenn, A.J. et al. Nordic dietary patterns and cardiometabolic outcomes: a systematic review and meta-analysis of prospective cohort studies and randomised controlled trials. Diabetologia 65, 2011–2031 (2022). https://doi.org/10.1007/s00125-022-05760-z
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DOI: https://doi.org/10.1007/s00125-022-05760-z