Background: Greater adherence to the Mediterranean diet, a traditional dietary pattern of the wider region of the Mediterranean sea, has been associated with favourable cardiometabolic outcomes, including the prevention of type 2 diabetes and cardiovascular diseases (CVD). However, limited local food availability, increased cost or unfamiliar culture and tradition render the Mediterranean diet difficult to follow in the northern European environment. The Nordic Diet or those of other traditional diets of the Nordic countries (Sweden, Norway, Finland, Denmark, Iceland, Faeroe islands) are dietary patterns rich in traditional Nordic foods, including berries, grains, and fatty fish common in northern Europe. The Nordic Diet has been associated with favorable cardiometabolic outcomes including improved lipid profile and insulin sensitivity. These benefits have been recognized in the most recent updates of the clinical practice guidelines for diabetes in Canada. The European Association for the Study of Diabetes (EASD) has not included the Nordic dietary pattern in their guidelines.
Need for proposed research: High quality systematic reviews and meta-analyses of randomized controlled trials and prospective cohorts represent high-quality evidence to support dietary guidelines and public health policy. As dietary guidelines and public health policy have shifted towards food and dietary-pattern based recommendations, there is a need for systematic reviews and meta-analyses comparing the role of the Nordic diet in the prevention and management of cardiometabolic outcomes and cardiovascular diseases.
Objectives: To support the update of the European Association for the Study of Diabetes (EASD) clinical practice guidelines for nutrition therapy, the investigators will conduct a systematic review and meta-analysis of randomized controlled trials and prospective cohorts using the GRADE approach on the Nordic dietary pattern on cardiometabolic risk factors and cardiovascular disease outcomes.
Design: The systematic review and meta-analysis of clinical trials and prospective cohort studies will be conducted according to the Cochrane Handbook for Systematic Reviews of interventions and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines.
Data sources: MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials (Clinical Trials; CENTRAL) will be searched using appropriate search terms supplemented by hand searches of references of included studies.
Study selection: Randomized controlled trials conducted in humans with a follow-duration ≥ 3 week investigating the effect of a Nordic diet on cardiometabolic outcomes will be included. Studies that are not conducted in humans, not randomized, have an acute feeding design (\<3 weeks), lack a suitable control (non-isocaloric) and/or do not report viable endpoint data will not be included. Prospective cohort studies with greater than 1-year of follow-up will be included.
Data extraction: Two or more investigators will independently extract relevant data and assess risk of bias using the Cochrane Risk of Bias Tool for randomized clinical trials and the Newcastle Ottawa Scale for prospective cohorts. All disagreements will be resolved by consensus. Standard computations and imputations will be used to derive missing variance data for the randomized clinical. Risk ratios, odds ratios and hazard ratios for clinical outcomes in the prospective cohort studies will be extracted or derived from clinical event data across exposure to a Nordic diet.
Outcomes: For the randomized clinical trials, the primary outcome will be LDL-cholesterol. Secondary outcomes will include markers of glycemic control (HbA1c, fasting glucose, fasting insulin); other blood lipids (non-HDL-C, apo B, HDL-C, triglycerides); adiposity (body weight, BMI, waist circumference), blood pressure (systolic and diastolic blood pressure) and inflammation (C-reactive protein \[CRP\]).
For prospective cohorts, the primary outcome will be incident CVD Secondary outcomes include incident coronary heart disease (CHD) and incident stroke.
Data synthesis:
Trials: Data will be pooled by the generic inverse-variance method with DerSimonian and Laird random-effects models and expressed as mean differences (MDs) with 95% confidence intervals (95% CIs). Random-effects models were used as they account for residual heterogeneity and yield more conservative estimates. Fixed-effects models will be used for \<5 trials. Paired analyses will be applied to all crossover trials. Heterogeneity will be tested by Cochran's Q statistic and quantified by the I2 statistic. To explore sources of heterogeneity, we will conduct sensitivity analyses, in which each study is systematically removed. If there are ≥10 trials, we will explore sources of heterogeneity by a priori subgroup analyses by study design (parallel or crossover), follow-up duration (\<12 weeks or ≥12 weeks), comparator diet, baseline measurements, risk of bias, disease duration, and funding source. Significant unexplained heterogeneity will be investigated by additional post hoc subgroup analyses (e.g. age, sex, diet quality index, composition of the background diet \[total % energy from fat, carbohydrate, protein\]). Meta-regression analyses will assess the significance of categorical and continuous subgroups analyses. When ≥10 studies are available, publication bias will be investigated by inspection of funnel plots and formal testing using the Egger and Begg tests. If publication bias is suspected, we will attempt to adjust for funnel plot asymmetry by imputing the missing study data using the Duval and Tweedie trim and fill method.
Prospective cohort studies: Natural log-transformed relative risks (RRs) or hazard ratios (HRs) of clinical outcomes, comparing extreme quantiles (the highest exposure versus the lowest exposure or reference group), will be pooled separately using the generic inverse variance method with random effects models and expressed as RRs with 95% confidence intervals (CIs). Heterogeneity will be tested by Cochran's Q statistic and quantified by the I2 statistic. To explore sources of heterogeneity, we will conduct sensitivity analyses, in which each study is systematically removed. If ≥10 cohort comparisons were available, then we will perform an a-priori subgroup analyses by meta-regression for follow-up (\<10 years vs. ≥10 years), sex (males vs. females, males vs. mixed, females vs. mixed), study quality (NOS \<6 vs. ≥6) and funding source. Significant unexplained heterogeneity will be investigated by additional post hoc subgroup analyses. Linear and non-linear dose-response relations will be explored with the use of random-effects generalised least-squares trend estimation (GLST) models and spline curve modeling (MKSPLINE procedure), respectively. When ≥10 studies are available, publication bias will be investigated by inspection of funnel plots and formal testing using the Egger and Begg tests. If publication bias is suspected, we will attempt to adjust for funnel plot asymmetry by imputing the missing study data using the Duval and Tweedie trim and fill method.
Evidence assessment: The certainty of the evidence for each outcome will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE).
Knowledge translation plan: The results will be disseminated through interactive presentations at local, national, and international scientific meetings and publication in high impact factor journals. Target audiences will include the public health and scientific communities with interest in nutrition, diabetes, obesity, and cardiovascular disease. Feedback will be incorporated and used to improve the public health message and key areas for future research will be defined. Applicant/Co-applicant Decision Makers will network among opinion leaders to increase awareness and participate directly as committee members in the development of future guidelines.
Significance: The proposed project will aid in knowledge translation to the role of the Nordic Diet in cardiovascular disease prevention and management, strengthening the evidence-base for guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.
