Objective To evaluate the agreement between diet-disease effect estimates of bodies of evidence from randomised controlled trials and those from cohort studies in nutrition research, and to investigate potential factors for disagreement. Design Meta-epidemiological study. Data sources Cochrane Database of Systematic Reviews, and Medline. Review methods Population, intervention or exposure, comparator, outcome (PI/ECO) elements from a body of evidence from cohort studies (BoE(CS)) were matched with corresponding elements of a body of evidence from randomised controlled trials (BoE(RCT)). Pooled ratio of risk ratios or difference of mean differences across all diet-disease outcome pairs were calculated. Subgroup analyses were conducted to explore factors for disagreement. Heterogeneity was assessed through I 2 and τ 2 . Prediction intervals were calculated to assess the range of possible values for the difference in the results between evidence from randomised controlled trials and evidence from cohort studies in future comparisons. Results 97 diet-disease outcome pairs (that is, matched BoE(RCT) and BoE(CS)) were identified overall. For binary outcomes, the pooled ratio of risk ratios comparing estimates from BoE(RCT) with BoE(CS) was 1.09 (95% confidence interval 1.04 to 1.14; I 2 =68%; τ 2 =0.021; 95% prediction interval 0.81 to 1.46). The prediction interval indicated that the difference could be much more substantial, in either direction. We further explored heterogeneity and found that PI/ECO dissimilarities, especially for the comparisons of dietary supplements in randomised controlled trials and nutrient status in cohort studies, explained most of the differences. When the type of intake or exposure between both types of evidence was identical, the estimates were similar. For continuous outcomes, small differences were observed between randomised controlled trials and cohort studies. Conclusion On average, the difference in pooled results between estimates from BoE(RCT) and BoE(CS) was small. But wide prediction intervals and some substantial statistical heterogeneity in cohort studies indicate that important differences or potential bias in individual comparisons or studies cannot be excluded. Observed differences were mainly driven by dissimilarities in population, intervention or exposure, comparator, and outcome. These findings could help researchers further understand the integration of such evidence into prospective nutrition evidence syntheses and improve evidence based dietary guidelines.

<b><i>Introduction:</i></b> We conducted a scoping review of systematic reviews (SRs) on dietary fat intake and health outcomes in human adults within the context of a position paper by the “International Union of Nutritional Sciences Task force on Dietary Fat Quality” tasked to summarize the available evidence and provide dietary recommendations. <b><i>Methods:</i></b> We systematically searched several databases for relevant SRs of randomized controlled trials (RCTs) and/or prospective cohort studies published between 2015 and 2019 assessing the association between dietary fat and health outcomes. <b><i>Results:</i></b> Fifty-nine SRs were included. The findings from SRs of prospective cohort studies, which frequently compare the highest versus lowest intake categories, found mainly no association of total fat, monounsaturated fatty acid (MUFA), polyunsaturated fatty acid (PUFA), and saturated fatty acid (SFA) with risk of chronic diseases. SRs of RCTs applying substitution analyses indicate that SFA replacement with PUFA and/or MUFA improves blood lipids and glycemic control, with the effect of PUFA being more pronounced. A higher intake of total trans-fatty acid (TFA), but not ruminant TFA, was probably associated with an increased risk of mortality and cardiovascular disease based on existing SRs. <b><i>Conclusion:</i></b> Overall, the available published evidence deems it reasonable to recommend replacement of SFA with MUFA and PUFA and avoidance of consumption of industrial TFA.

Background Randomized controlled trials (RCTs) and cohort studies are the most common study design types used to assess the treatment effects of medical interventions. To evaluate the agreement of effect estimates between bodies of evidence (BoE) from randomized controlled trials (RCTs) and cohort studies and to identify factors associated with disagreement. Methods Systematic reviews were published in the 13 medical journals with the highest impact factor identified through a MEDLINE search. BoE-pairs from RCTs and cohort studies with the same medical research question were included. We rated the similarity of PI/ECO (Population, Intervention/Exposure, Comparison, Outcome) between BoE from RCTs and cohort studies. The agreement of effect estimates across BoE was analyzed by pooling ratio of ratios (RoR) for binary outcomes and difference of mean differences for continuous outcomes. We performed subgroup analyses to explore factors associated with disagreements. Results One hundred twenty-nine BoE pairs from 64 systematic reviews were included. PI/ECO-similarity degree was moderate: two BoE pairs were rated as “more or less identical”; 90 were rated as “similar but not identical” and 37 as only “broadly similar”. For binary outcomes, the pooled RoR was 1.04 (95% CI 0.97–1.11) with considerable statistical heterogeneity. For continuous outcomes, differences were small. In subgroup analyses, degree of PI/ECO-similarity, type of intervention, and type of outcome, the pooled RoR indicated that on average, differences between both BoE were small. Subgroup analysis by degree of PI/ECO-similarity revealed high statistical heterogeneity and wide prediction intervals across PI/ECO-dissimilar BoE pairs. Conclusions On average, the pooled effect estimates between RCTs and cohort studies did not differ. Statistical heterogeneity and wide prediction intervals were mainly driven by PI/ECO-dissimilarities (i.e., clinical heterogeneity) and cohort studies. The potential influence of risk of bias and certainty of the evidence on differences of effect estimates between RCTs and cohort studies needs to be explored in upcoming meta-epidemiological studies.

<b><i>Introduction:</i></b> We conducted a scoping review of dietary guidelines with the intent of developing a position paper by the “IUNS Task force on Dietary Fat Quality” tasked to summarize the available evidence and provide the basis for dietary recommendations. <b><i>Methods:</i></b> We systematically searched several databases and Web sites for relevant documents published between 2015 and 2019. <b><i>Results:</i></b> Twenty documents were included. Quantitative range intake recommendations for daily total fat intake included boundaries from 20 to 35% of total energy intake (TEI), for monounsaturated fat (MUFA) 10–25%, for polyunsaturated fat (PUFA) 6–11%, for saturated-fat (SFA) ≤11–≤7%, for industrial trans-fat (TFA) ≤2–0%, and &#x3c;300–&#x3c;200 mg/d for dietary cholesterol. The methodological approaches to grade the strength of recommendations were heterogeneous, and varied highly between the included guidelines. Only the World Health Organization applied the GRADE approach and graded the following recommendation as “strong”: to reduce SFA to below 10%, and TFA to below 1% and replace both with PUFA if SFA intake is greater than 10% of TEI. <b><i>Conclusion:</i></b> Although the methodological approaches of the dietary guidelines were heterogeneous, most of them recommend total fat intakes of 30–≤35% of TEI, replacement of SFA with PUFA and MUFA, and avoidance of industrial TFA.

We aimed to identify and compare empirical data to determine the concordance of diet-disease effect estimates of bodies of evidence (BoE) from randomized controlled trials (RCTs), dietary intake and biomarkers of dietary intake in cohort studies (CSs). The Cochrane Database of Systematic Reviews and MEDLINE were searched for systematic reviews (SRs) of RCTs, and SRs of CSs that investigated both dietary intake and biomarkers of intake published between 01.01.2010 and 31.12.2019. For matched diet-disease associations, the concordance between results from the three different BoE was analyzed using two definitions: qualitative (e.g., 95% CI within a pre-defined range), and quantitative (test hypothesis on the z score). Moreover, the differences in the results coming from BoERCTs, BoECSs dietary-intake, and BoECSs biomarkers were synthesized to get a pooled ratio of risk ratio (RRR) across all eligible diet-disease associations, so to compare the three BoE. Overall 49 diet-disease associations derived from 41 SRs were identified and included in the analysis. 24%, 10%, 39% of the diet-disease associations were qualitatively concordant comparing BoERCTs vs. BoECSs dietary-intake, BoERCTs vs. BoECSs biomarkers and comparing both BoE from CSs, respectively. 88%, 69%, 90% of the diet-disease associations were quantitatively concordant comparing BoERCTs vs. BoECSs dietary-intake, BoERCTs vs. BoECSs biomarkers and comparing both BoE from CSs, respectively. The pooled RRR comparing effects from BoERCTs with effects from BoECSs dietary-intake was 1.09 (95% CI 1.06, 1.13), and RRR: 1.18 (95% CI 1.10, 1.25) compared to BoECSs biomarkers. Comparing both BoE from CSs, the difference in the results was also small (RRR: 0.92; 95% CI: 0.88, 0.96). Our findings suggest that BoE from RCTs and CSs are often quantitatively concordant. Prospective SRs in nutrition research should include whenever possible BoE from RCTs, and CSs on dietary intake and biomarkers of intake to provide the whole picture for an investigated diet-disease association. Statement of significance: Our findings suggest that bodies of evidence from randomized controlled trials and cohort studies are often concordant.