ABSTRACT
Numerous observational studies have investigated the role of the Dietary Inflammatory Index (DII®) in chronic disease risk. The aims of this umbrella review and integrated meta-analyses were to systematically synthesize the observational evidence reporting on the associations between the DII and health outcomes based on meta-analyses, and to assess the quality and strength of the evidence for each associated outcome. This umbrella review with integrated meta-analyses investigated the association between the DII and a range of health outcomes based on meta-analyses of observational data. A credibility assessment was conducted for each outcome using the following criteria: statistical heterogeneity, 95% prediction intervals, evidence for small-study effect and/or excess significance bias, as well as effect sizes and P values using calculated random effects meta-analyses. In total, 15 meta-analyses reporting on 38 chronic disease-related outcomes were included, incorporating a total population of 4,360,111 subjects. Outcomes (n = 38) were examined through various study designs including case-control (n = 8), cross-sectional (n = 5), prospective (n = 5), and combination (n = 20) study designs. Adherence to a pro-inflammatory dietary pattern had a significant positive association with 27 (71%) of the included health outcomes (P value < 0.05). Using the credibility assessment, Class I (Convincing) evidence was identified for myocardial infarction only, Class II (Highly suggestive) evidence was identified for increased risk of all-cause mortality, overall risk of incident cancer, and risk of incident site-specific cancers (colorectal, pancreatic, respiratory, and oral cancers) with increasing (more pro-inflammatory) DII score. Most outcomes (n = 31) presented Class III (Suggestive) or lower evidence (Weak or No association). Pro-inflammatory dietary patterns were nominally associated with an increased risk of many chronic disease outcomes. However, the strength of evidence for most outcomes was limited. Further prospective studies are required to improve the precision of the effect size.
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