Background:
Effects of dietary factors on cardiometabolic risk are often studied in isolation. Yet, multiple dietary components are often consumed together, which may alter effects of individual dietary factors.
Objective:
To quantify effects of 7 diet components (fruits, vegetables, nuts/seeds, whole grains, fish, dietary fiber) when consumed within the context of overall dietary patterns on major metabolic risks.
Methods:
Using MOOSE and PRISMA guidelines, we systematically searched multiple databases to identify randomized controlled feeding studies evaluating effects of diet patterns on cardiometabolic risk factors. We focused on trials evaluating major diet patterns that included fruits, vegetables, nuts/seeds, whole grains, fish, and dietary fiber as major components and tested effects on BP, lipids, BMI or waist circumference, or glucose-insulin homeostasis (fasting glucose, HbA1c, oral glucose tolerance test, postprandial glucose, fasting insulin). Studies were excluded if <4 weeks, utilized diet advice rather than feeding, involved other major interventions, relied on self-reported outcomes, or included only patients with cachectic or end-stage disease. Multivariate inverse-variance weighted meta-regression estimated the pooled effects of individual diet components, when consumed together, on cardiometabolic risks.
Results:
Meta-regression analyses of 6 intervention arms in 3 large dietary pattern trials demonstrated significant effects of several individual components (Table) Pooled results including additional dietary pattern trials and results for adiposity and glucose/insulin homeostasis are to be shown.
Conclusions:
This systematic assessment quantifies the impact of individual dietary factors on cardiometabolic risks within the context of overall diet patterns, more accurately reflecting complementary effects of multiple components and informing magnitudes of benefits for preventive policies and interventions.
Associations between Dietary Patterns and Cardiometabolic Risks in Japan: A Cross-Sectional Study from the Fukushima Health Management Survey, 2011–2015