Investigating the association between sugar-sweetened beverages intake and risk of metabolic syndrome among Ellisras rural youth : Ellisras longitudinal study

Abstract

Background: Metabolic syndrome (MetS) is amongst the underlying causes of mortality and morbidity globally. However, lifestyle habits such as frequent consumption of sugar-sweetened beverages (SSBs) contributes to its onset. The study was aimed at investigating the association between MetS and SSBs intake among Ellisras rural youth. Additionally, to find the best obesity indices to predict MetS. Methods: The current study included a total of 593 Ellisras rural youth, aged 22 to 30 years (289 males and 304 females). Anthropometric measurements, blood pressure (BP), and biochemical assessment were taken using standards procedures. A validated 24hrs recall questionnaire and food manuals were used to collect SSBs data. Binary logistic regression was applied to determine the association between SSBs intake and MetS components for the adjusted model. Confirmatory factor analysis was used to test the best single-factor models to predict MetS on commonly selected obesity indices. Results: The SSBs quartile 4 was associated with a high risk of high fasting blood glucose (FBG) for adjusted (OR=2.32; CI=1.15-4.70; p<0.05) and unadjusted (OR=2.34; CI=1.16-4.73; p<0.05) models were a significant linear trend (p for trend=0.049) in males was found. Low risk of reduced high density lipoprotein cholesterol (HDL-C) was associated with the second and fourth SSBs quartiles for unadjusted ((OR=0.40; CI=0.18-0.85; p<0.05; OR=0.37; CI=0.13-0.80; p<0.05) respectively and adjusted model (OR=0.40; CI=0.18-0.85; p<0.05; OR=0.37; CI=0.17-0.80; p<0.05) respectively in females. Moreover, the fourth SSBs quartile was likely to decrease the risk of high triglycerides (TG) for unadjusted (OR=0.12; CI=0.01-0.87; p<0.05) and adjusted (OR=0.10; CI=0.01-0.83; p<0.05) models were the significant linear trend (p= trend 0.006) was observed also in females. There was a significant linear trend association between SSBs quartiles consumption and high TG in males and high waist circumference (WC) in females, but logistic regression analysis didn’t depict any significant association (p>0.05). In males, single model fit built based on WC (comparative fit index (CFI)=1.00; turker lewis index (TLI)=1.05; RMSEA=0.00; akaike information criterion (AIC)=-2680) and waist to height ratio v (WHtR) (RMSEA=0.00, CFI=1.00; AIC=-2662, TLI=1.05;) suggested a better fit index as compared to body mass index (BMI) and neck circumference (NC). Among females, a single model fit built on NC obtained a better fit index (RMSEA=0.05, CFI=0.90, and AIC= -429.21, TLI=0.71). Conclusion: In this study, there was an association between SSBs consumption and some MetS components (high TG, reduced HDL-C, and high FBG). Obesity indices including WHtR, NC, and WC were the best predictors of MetS. Future studies are recommended to further investigate the association of the risk of MetS and the consumption SSBs and the best obesity indices to predict MetS to assist in efforts to help curb MetS and related risk factors in rural areas of South Africa.