The hypocholesterolemic effect of soy is well-documented and this has led to the regulatory approval of a health claim relating soy protein to a reduced risk of cardiovascular disease (CVD). However, soybeans contain additional components, such as isoflavones, lecithins, saponins and fiber that may improve cardiovascular health through independent mechanisms. This review summarizes the evidence on the cardiovascular benefits of non-protein soy components in relation to known CVD risk factors such as hypertension, hyperglycemia, inflammation, and obesity beyond cholesterol lowering. Overall, the available evidence suggests non-protein soy constituents improve markers of cardiovascular health; however, additional carefully designed studies are required to independently elucidate these effects. Further, work is also needed to clarify the role of isoflavone-metabolizing phenotype and gut microbiota composition on biological effect.

Current evidence suggests a link between red and processed meat consumption and the risk of various cancers and other health outcomes. Using national survey data from the Canadian Community Health Survey (CCHS)-Nutrition 2015, we aimed to model a dietary scenario to assess the potential effects of increasing the intake of currently consumed plant-based meat alternatives by 100% and decreasing the consumption of red and processed meat by 50% on the diet quality and nutrient intakes of Canadians (≥1 year). This dietary scenario had no significant impact on dietary energy intake (p > 0.05), but resulted in a significant increase in the dietary intakes of fibre, polyunsaturated fatty acids, magnesium, and dietary folate equivalents (p < 0.05). On the other hand, this dietary scenario was accompanied by a significant decrease in protein (from 77.8 ± 0.6 g to 73.4 ± 0.6 g), cholesterol, zinc, and vitamin B12 intake (p < 0.05). Further, based on Nutrient Rich Food (NRF) scores, the overall nutritional value of the simulated diet was higher than the baseline diet. Our modeling showed that the partial replacement of red and processed meat with plant-based alternatives improves overall diet quality but may adversely affect the intake of some micronutrients, especially zinc and vitamin B12.

Polyphenol extracts from coloured fruits and vegetables inhibit α-glucosidase in vitro, however it is not known whether this translates into an attenuation of blood glucose response in vivo. We examined this relationship in a GI study by feeding coloured potatoes to 9 healthy volunteers. We also examined the in vitro inhibitory activity of potato anthocyanin extracts on rat intestinal α-glucosidase. Potatoes (Purple Majesty; Red-Y38; Yukon Gold and Snowden) were fed with skin after cooking in a convection oven, using a random block design and 50 g available carbohydrate. Glucose was used as the standard and venous blood collected at 0, 15, 30, 45, 60, 90, 120 min. Areas under the curve (AUC) for glucose and insulin were calculated, and GI and Insulin Index derived. Neither AUC for blood glucose response nor insulin was significantly different among the various potatoes studied. Although the mean GI (±SE) values for the potato types varied (purple = 77.0 ± 9.0; red = 78.0 ± 14.0; yellow = 81.0 ± 16.0; and white = 93.0 ± 17.0), these differences were not significantly different. The mean (±SE) polyphenol content (mg GAE/100 g DW) was 234 ± 28; 190 ± 15; 108 ± 39; 82 ± 1 for purple, red, yellow and white potatoes, respectively. There was a significant inverse correlation between polyphenol content and GI of the potatoes (r = −0.825; p < 0.05; n = 4). In vitro, polyphenol extracts of red and purple potatoes inhibited α-glucosidase by 37.4 ± 2.2% and 28.7 ± 3.2%, respectively. The GI of coloured potatoes is significantly related to their polyphenol content, possibly mediated through an inhibitory effect of anthocyanins on intestinal α-glucosidase.

Proximate composition and starch nutritional properties of twenty cooked lentils were assessed to identify unique varieties that could be used in value added foods. Significant variations exist among the lentil varieties (p < 0.05) with respect to their energy, fat, protein, carbohydrate, and dietary fiber content, and these are related to lentil type and seed size. Dazil and Greenstar were unique for their high resistant starch content (RS) and lower area under the starch hydrolysis curve (SHAUC) while Proclaim was opposite. SHAUC was positively correlated (p < 0.001) with rapidly digestible starch (RDS) content (r = 0.626) but negatively correlated with RS content (r = −0.635). Principal component analysis showed that the first three principal components accounted for 62.8% of the total variance and the contribution of SHAUC was 33.2%. These results confirm that in vitro SHAUC and a combination of RDS and RS may be predictive of the digestibility profile of cooked lentils.

Consumption of pulses is associated with many health benefits by mechanisms that are not fully understood. This study sought to identify the starch component(s) in cooked lentils responsible for lowering postprandial glycemic response (PPGR). Rapidly digestible (RDS), slowly digestible (SDS) and resistant starch (RS) content of 20 varieties of cooked lentil were determined by in vitro methods and 8 varieties, representing a linear range of SDS, were chosen for a human trial with 10 participants to determine PPGR and glycemic index (GI). Among the 20 lentil varieties, RS accounted for 35% of the variation of in vitro area under the starch hydrolysis curve (SHAUC) (r = −0.587; p < 0.01), but RDS (r = 0.401; p = 0.080) and SDS (r = −0.022; p = 0.927) were not significantly related to SHAUC. Multiple linear regression of in vitro data resulted in an equation [SHAUCest = 30.9RDS − 63.6RS + 9680] that accounted for 70% of the variance in SHAUC, with SDS excluded due to collinearity. In the human trial all 8 lentils had low GI values (10 to 23). Neither GI nor area under the glucose response curve (AUC) was significantly related to RDS, SDS or RS (minimum p = 0.24). However, SHAUC and SHAUCest, respectively, were related to both GI (r = 0.704, p = 0.051; r = 0.773, p = 0.024) and AUC (r = 0.765, p = 0.027; r = 0.822, p = 0.012). These results confirm that lentils have low GI values, which is not reliably predicted by their RDS, SDS and RS contents when considered individually. However, in vitro SHAUC and a combination of RDS and RS may be predictive of the PPGR of lentils.