Low-Carbohydrate Diet Patterns That Favor High-Quality Carbohydrates Are Associated with Beneficial Long-Term Changes in Biomarkers of Inflammation and Oxidative Stress in the Framingham Offspring Cohort
Résumé fourni par la source
Background: Low-carbohydrate diet (LCD) patterns have been studied as a potential strategy to reduce chronic inflammation. Evidence remains equivocal, likely because of differences in the quality of carbohydrate sources among LCD patterns. Objectives: To prospectively examine the associations between LCD patterns varying in carbohydrate quality, and changes of inflammation and oxidative stress biomarkers. Methods: = 2225; median 6.7-y follow-up, mean baseline age: 60.1 y), we used food frequency questionnaires to create 2 LCD scores (LCDS) accounting for quality of carbohydrates sources. These reflected higher intake of total fat and protein, and lower intake of either low-quality carbohydrates [high-quality LCDS (HQ-LCDS)] or high-quality carbohydrates [low-quality LCDS (LQ-LCDS)]. We calculated an inflammation and oxidative stress score by summing the standardized values of 9 inflammatory and oxidative stress biomarkers. Least-square mean change in the inflammation and oxidative stress score across quintile categories of LCDS was estimated using multivariable linear regression models, adjusted for potential confounders. Results: = 0.003). No significant associations were observed for LQ-LCDS. Conclusions: LCD patterns that preserved high-quality carbohydrates while replacing low-quality carbohydrates sources, such as refined grains and added sugars, with fat and protein were inversely associated with inflammation and oxidative stress score, potentially lowering chronic disease risk.
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Contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Low-Carbohydrate Diet Patterns That Favor High-Quality Carbohydrates Are Associated with Beneficial Long-Term Changes in Biomarkers of Inflammation and Oxidative Stress in the Framingham Offspring Cohort
- Date Crossref
- 01/07/2025
- Éditeur
- Elsevier BV
- Type
- journal-article
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