Evaluation of Various Starchy Foods: A Systematic Review and Meta-Analysis on Chemical Properties Affecting the Glycemic Index Values Based on In Vitro and In Vivo Experiments

Abstract

The chemical properties that serve as major determinants for the glycemic index (GI) of starchy food and recommended low-GI, carbohydrate-based foods have remained enigmatic. This present work performed a systematic assessment of linkages between chemical properties of foods and GI, and selected low-GI starchy foods. The data were sourced from literature published in various scientific journals. In total, 57 relevant studies and 936 data points were integrated into a database. Both in vitro and in vivo studies on GI values were included. The database was subsequently subjected to a meta-analysis. Meta-analysis from in vitro studies revealed that the two significant factors responsible for the GI of starchy foods were resistant starch and phenolic content (respectively, standardized mean difference (SMD): −2.52, 95% confidence interval (95%CI): −3.29 to −1.75, p (p-value) < 0.001; SMD: −0.72, 95%CI: −1.26 to −0.17, p = 0.005), while the lowest-GI crop type was legumes. Subgroup analysis restricted to the crop species with significant low GI found two crops, i.e., sorghum (SMD: −0.69, 95%CI: −2.33 to 0.96, p < 0.001) and red kidney bean (SMD: −0.39, 95%CI: −2.37 to 1.59, p = 0.001). Meta-analysis from in vivo studies revealed that the two significant factors responsible for the GI of starchy foods were flavonoid and phenolic content (respectively, SMD: −0.67, 95%CI: −0.87 to −0.47, p < 0.001; SMD: −0.63, 95%CI: −1.15 to −0.11, p = 0.009), while the lowest-GI crop type was fruit (banana). In conclusion, resistant starch and phenolic content may have a desirable impact on the GI of starchy food, while sorghum and red kidney bean are found to have low GI.

Oat-Based Foods: Chemical Constituents, Glycemic Index, and the Effect of Processing

“…Growing evidence indicates that naturally occurred phenolics have the potential to modulate carbohydrate digestion and glucose absorption through the inhibition of starch digestive enzymes and potential regulation of intestinal glucose transporters [58,59]. More recently, a systematic review and meta-analysis revealed that phenol levels in foods were negatively correlated with GI, and the mechanism was the inhibition of α-amylase and α-glucosidase [13]. Intake of 1 mg/mL of oat phenolics (either caffeic acid, chlorogenic acid, or ferulic acid) significantly suppressed (35-85%) glucose transport in rat intestinal brush boarder membrane vesicles [60].…”

“…With regard to their effects on GI, current evidence mainly attributes them to oat phenolics. These bioactive components can reduce the absorption of glucose by inhibiting digestive enzymes, which is a potential therapeutic way to manage Type 2 diabetes [13]. However, more clinical trials are still needed to confirm the efficiency of this processing technique on oat GI.…”

“…Moreover, the chemical composition of food fundamentally determines the GI value. A recent review of the GI of starchy foods from the perspective of chemical composition concluded that resistant starch and phenolics contributed greatly to GI [13]. Plenty of plant-derived polysaccharides have been proved to play a significant role in managing glucose and insulin metabolism.…”

Microbiota and Metabolite Modifications after Dietary Exclusion of Dairy Products and Reduced Consumption of Fermented Food in Young and Older Men

“…These effects were maintained after adjustment for BMI change suggesting that dietary change was the cause of their modulation. The amounts and composition of many foods and nutrients in the diet can influence glucose homeostasis, as reported for fruits, vegetables, fibre, protein, fats, and minerals [77]. However, there is now considerable evidence to suggest that dietary effects on glycemia are highly individualised, particularly during the postprandial phase after eating, challenging the notion of single glucose lowering diet [78].…”

Kadar Pati Resisten Pangan Tinggi Karbohidrat Hasil Autoclaving-Cooling 2 Siklus: Studi Meta-Analisis

“…Data dianalisis menggunakan nilai ukuran efek Hedges'd (Standardized Mean Difference/SMD) dengan nilai selang kepercayaan (Confidence interval/CI) 95% dan dikumpulkan dalam suatu model efek acak (random effects model) (Afandi, Wijaya, Faridah, Suyatma, & Jayanegara, 2021;Palupi, Jayanegara, Ploeger, & Kahl, 2012). Data-data yang sudah diinput ke dalam Microsoft Excel kemudian dihitung nilai S, J, d, Vd, Sd, Wd, Wd*d, D+, Vd+, Sd+ dan CI+ menggunakan lembar kerja yang pernah dikembangkan oleh Afandi (2020) berdasarkan rumus-rumus berikut :…”