As a staple food and dense source of nutrients, milk and alternatives play an important role in nutrient adequacy. The aims of this study were to quantify the consumption of milk and alternatives within Canadian self-selected diets and determine their contribution to intakes of nutrients and energy. First, 24-h dietary recalls from the 2015 Canadian Community Health Survey—Nutrition were used to assess 1-d food and nutrient intakes among Canadian adults ≥19 y (n = 13,616). Foods were classified as milk and alternatives according to the 2007 Canada’s Food Guide. Descriptive statistics were used to calculate daily servings of milk and alternatives by different age groups and demographic characteristics. Population ratios were used to discern their contribution to total intakes of nutrients and energy. Mean daily servings (±SE) were highest for milk (0.60 ± 0.02) and cheese (0.42 ± 0.01), intermediate for frozen dairy (0.16 ± 0.01) and yoghurt (0.14 ± 0.01), and lowest for soy and other dairy (20% to total intakes of calcium (52.62 ± 0.46%), vitamin D (38.53 ± 0.78%), saturated fat (28.84 ± 0.51%), vitamin B12 (27.73 ± 0.57%), vitamin A (26.16 ± 0.58%), phosphorus (24.76 ± 0.35%), and riboflavin (24.43 ± 0.37%), of which milk was the top source. Milk and alternatives contribute substantially to nutrient intakes and thus warrant further attention in terms of mitigating nutrient inadequacy among the Canadian population.

The role of the retail food environment in obesity risk is unclear, which may be due in part to the lack of consideration of individual differences in the responsivity to food cues. This cross-sectional investigation geo-temporally linked the CARTaGENE biobank (including genetic, dietary, lifestyle, and anthropometric data) with in-store retail food environment data to examine interactions between a polygenic risk score (PRS) for obesity and (1) diet quality (n = 6807) and (2) in-store retail food measures (n = 3718). The outcomes included adiposity-related measures and diet quality assessed using the 2010 Canadian-adapted Healthy Eating Index. A vegetable:soft drink ratio was constructed for each retail measure to assess the relative healthfulness of exposures. Generalized linear models adjusted for individual and neighborhood socio-demographic factors were used to evaluate main and interactive effects. Diet quality significantly modified the association between polygenic risk of obesity and body mass index, waist circumference, and body fat percent. A significant interaction was also observed between PRS and regular price of vegetables in relation to soft drinks on waist circumference. These results replicate previous reports of diet moderating polygenic risk of obesity and suggest that prices of low vs. high-energy density foods are an intervention target to address population obesity rates.

Background: Diet is an important determinant of body weight and may modulate genetic susceptibility to obesity.Objective: This systematic review and meta‐analysis aimed to synthesize evidence related to interactions between polygenic risk and nutrient intakes on obesity outcomes.Methods: MEDLINE, EMBASE, Web of Science, and Cochrane Library were systematically searched to identify observational studies that assessed interactions between polygenic risk and nutrient intakes on obesity‐related outcomes. Random effects meta‐analyses were performed for pooled polygenic risk score (PRS)–total fat intake and PRS–protein intake interaction coefficients on body mass index (BMI).Results: Twenty‐six publications were retrieved with studies conducted among European, Asian, and African samples. Dietary fats (saturated fat, omega‐3, and trans fat) and energy intake were most frequently reported to interact with PRS on obesity outcomes, but the total number of studies available was low. No significant interactions were identified in meta‐analyses of PRS interactions with total fat intake and protein intake on BMI. Several studies were rated as low quality, heterogeneity was high, and although study samples were racially diverse, PRSs tended to be based on samples of European ancestry.Conclusion: Evidence of interactions between polygenic risk and nutrient intakes on obesity outcomes is limited and inconsistent. Further research addressing limitations related to study quality and polygenic risk characterization is needed.