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Meta-Analysis
. 2021 Oct;75(10):e14295.
doi: 10.1111/ijcp.14295. Epub 2021 Jun 25.

Glycemic index, but not glycemic load, is associated with an increased risk of metabolic syndrome: Meta-analysis of observational studies

Affiliations
Meta-Analysis

Glycemic index, but not glycemic load, is associated with an increased risk of metabolic syndrome: Meta-analysis of observational studies

Mohammadreza Askari et al. Int J Clin Pract. 2021 Oct.

Abstract

Background: Diets with high glycemic index (GI) or high glycemic load (GL) have been linked to important risk factors associated with the development of metabolic syndrome (MetS), such as dyslipidemia, higher blood glucose, and insulin concentrations. However, the role of GI and GL in relation to Mets is still understudied and controversial. This review, therefore, assessed whether high GI or GL contribute to development of Mets.

Methods: A systematic search of four bibliographic databases was conducted (MEDLINE/PubMed, EMBASE, Web of Sciences, and Scopus) from inception to January 2020 for observational studies assessing GI/GL in relation to MetS. Risk estimates were pooled using random-effect models for the highest versus lowest intake categories, and assessed for heterogeneity using subgroup analysis. The dose-response nature of the relationship was also investigated. Sensitivity analysis and Egger test were used to check the robustness of findings and the possibility of publication bias, respectively.

Results: Data from 12 publications (one cohort study and eleven cross-sectional studies) with a total sample size of 36,295 subjects are included. The pooled effect sizes from the nine studies indicated high versus low dietary GI was associated with increased risk of MetS (OR = 1.05, 95% CI: 1.01 to 1.09) (I2 = 58.1, P = .004). This finding was supported by all subgroup analyses except where studies used 24-h recalls for dietary assessment. Additionally, a linear dose-response investigation revealed that each 5-point increment in GI was associated with 2% increase in the risk of MetS (OR = 1.02, 95% CI: 1.01 to 1.02); non-linear pattern was insignificant, however (p-nonlinearity = 0.63). Moreover, pooled effect sizes from ten studies suggested that no association was found between the GL and MetS with results remaining consistent in all subgroup analyses.

Conclusion: A diet with lower GI may protect against MetS. Nutrition policy and clinical practices should encourage a diet with low GI. Future studies should include both GI and GL and different criteria of MetS to provide a better comparison.

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References

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