Ya-Shu Liu1, Qi-Jun Wu1, Yang Xia1, Jia-Yu Zhang1, Yu-Ting Jiang1, Qing Chang1, Yu-Hong Zhao2. 1. Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China. 2. Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China. Electronic address: zhaoyuhong@sj-hospital.org.
Abstract
BACKGROUND AND AIMS: Epidemiological association studies have reported inconsistent findings on the relationship between carbohydrate intake and risk of metabolic syndrome (MetS). Therefore, we aimed to conduct the first dose-response meta-analysis to investigate this effect. METHODS AND RESULTS: A systematic search in PubMed and Web of Science databases from their inception to June 01, 2019, together with relevant literature scrutiny, was performed to identify related studies for inclusion into the meta-analysis. We calculated the odds ratios (ORs) with 95% confidence intervals (CIs) using a random effects model. Furthermore, subgroup, sensitivity, heterogeneity, and publication bias analyses were performed. This meta-analysis included 14 cross-sectional and four cohort studies, totaling 284,638 participants and 69,554 MetS cases. The highest versus the lowest carbohydrate intake values were associated with an increased risk of MetS (OR: 1.253, 95% CI: 1.147-1.368), with moderate heterogeneity (I2 = 54.5%). Using dose-response analysis, we found a linear association between carbohydrate consumption and MetS risk with a corresponding OR of 1.026 (95% CI, 1.004-1.048) and with significant heterogeneity (I2 = 82.0%) at 5% energy intake from carbohydrates. We have found similar results using subgroup analyses for major study characteristics and adjustment for confounders. Sensitivity analysis further enhanced the robustness of the results, and no publication bias was detected. CONCLUSION: Carbohydrate intake is associated with an increased risk of developing MetS. Therefore, additional large prospective cohort studies are warranted to confirm our findings.
BACKGROUND AND AIMS: Epidemiological association studies have reported inconsistent findings on the relationship between carbohydrate intake and risk of metabolic syndrome (MetS). Therefore, we aimed to conduct the first dose-response meta-analysis to investigate this effect. METHODS AND RESULTS: A systematic search in PubMed and Web of Science databases from their inception to June 01, 2019, together with relevant literature scrutiny, was performed to identify related studies for inclusion into the meta-analysis. We calculated the odds ratios (ORs) with 95% confidence intervals (CIs) using a random effects model. Furthermore, subgroup, sensitivity, heterogeneity, and publication bias analyses were performed. This meta-analysis included 14 cross-sectional and four cohort studies, totaling 284,638 participants and 69,554 MetS cases. The highest versus the lowest carbohydrate intake values were associated with an increased risk of MetS (OR: 1.253, 95% CI: 1.147-1.368), with moderate heterogeneity (I2 = 54.5%). Using dose-response analysis, we found a linear association between carbohydrate consumption and MetS risk with a corresponding OR of 1.026 (95% CI, 1.004-1.048) and with significant heterogeneity (I2 = 82.0%) at 5% energy intake from carbohydrates. We have found similar results using subgroup analyses for major study characteristics and adjustment for confounders. Sensitivity analysis further enhanced the robustness of the results, and no publication bias was detected. CONCLUSION:Carbohydrate intake is associated with an increased risk of developing MetS. Therefore, additional large prospective cohort studies are warranted to confirm our findings.
Authors: Leen Oyoun Alsoud; Nelson C Soares; Hamza M Al-Hroub; Muath Mousa; Violet Kasabri; Nailya Bulatova; Maysa Suyagh; Karem H Alzoubi; Waseem El-Huneidi; Bashaer Abu-Irmaileh; Yasser Bustanji; Mohammad H Semreen Journal: Metabolites Date: 2022-06-01
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