Background and aims: Diet plays a central role in regulating inflammation and is closely related to the development of chronic diseases. We aimed to develop an inflammatory food index (IFI) based on the relationship of food items with biomarkers of inflammation and to evaluate its association with weight gain and type 2 diabetes.
Methods and results: A sample of 9909 participants of the ELSA-Brasil study was analyzed. Standardized measurements including interviews, anthropometry, and laboratory exams were performed at baseline and follow-up. A baseline food frequency questionnaire was used to derive IFI scores using reduced rank regression (RRR). The inflammatory pattern derived included 11 pro-inflammatory food groups: processed meat, red meat, pork, sugary soda, and hot dogs. The anti-inflammatory pattern included seven food groups: fruits, nuts, and wine. The IFI score, adjusted through logistic regression for multiple sociodemographic, behavioral, and clinical covariates, including body mass index, predicted the development of a large weight gain (tertile 3 vs. 1: OR = 1.30; 95%CI 1.08-1.55). The score, adjusted for sociodemographic factors through proportional hazard models, predicted incident diabetes (tertile 3 vs. 1: HR = 1.26; 95%CI 1.04-1.52).
Conclusion: These findings support the hypothesis that subclinical inflammation caused by a pro-inflammatory food pattern, characterized mainly by greater ultra-processed food consumption, underlies weight gain and the development of type 2 diabetes. This study was registered at clinicaltrials.com as NCT02320461.
Keywords: Diabetes mellitus; Diet; Inflammation; Obesity; Weight gain.
Copyright © 2022 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.