Cross-Sectional Associations between Dietary Fat-Related Behaviors and Continuous Metabolic Syndrome Score among Young Australian Adults

Full-fat dairy products and cardiometabolic health outcomes: Does the dairy-fat matrix matter?

Reducing dairy fat intake is a common dietary guideline to limit energy and saturated fatty acid intake for the promotion of cardiometabolic health. However, research utilizing a holistic, food-based approach to assess the consumption of the fat found in dairy, a broad and diverse food group, may provide new insight into these guidelines. Dairy fat is comprised of a diverse assembly of fatty acids, triacylglycerols, sterols, and phospholipids, all uniquely packaged in a milk fat globule. The physical structure of this milk fat globule and its membrane is modified through different processing methods, resulting in distinctive dairy-fat matrices across each dairy product. The objectives of this narrative review were to first define and compare the dairy-fat matrix in terms of its unique composition, physical structure, and fat content across common dairy products (cow's milk, yogurt, cheese, and butter). With this information, we examined observational studies and randomized controlled trials published within the last 10 years (2013-2023) to assess the individual effects of the dairy-fat matrix in milk, yogurt, cheese, and butter on cardiometabolic health and evaluate the implications for nutrition guidance. Searches conducted on Ovid MEDLINE and PubMed® utilizing search terms for cardiometabolic health, both broadly and regarding specific disease outcomes and risk factors, yielded 59 studies that were analyzed and included in this review. Importantly, this review stratifies by both dairy product and fat content. Though the results were heterogeneous, most studies reported no association between intake of these individual regular-fat dairy products and cardiometabolic outcome measures, thus, the current body of evidence suggests that regular-fat dairy product consumption may be incorporated within overall healthy eating patterns. Research suggests that there may be a beneficial effect of regular-fat milk and yogurt intake on outcome measures related to body weight and composition, and an effect of regular-fat cheese intake on outcome measures related to blood lipids, but more research is necessary to define the directionality of this relationship. Lastly, we identify methodological research gaps and propose future research directions to bolster the current evidence base available for ascertaining the role of dairy fat in a healthy diet.

Eating behavior and metabolic syndrome over time

PURPOSE

We evaluated the longitudinal associations between eating behaviors (EB) and risk of metabolic syndrome (MetS).

METHODS

We obtained complete data on EB, assessed using the Dutch Eating Behavior Questionnaire, and MetS components at baseline and follow-up. Participants included 1876 individuals (704 men, 1172 women; mean age, 45.0 ± 12.8 years) from those participating in the Korean Healthy Twin study. A generalized estimating equation model was applied, with sociodemographic factors, health-related factors, follow-up interval, and EB (baseline and changes over time) as independent factors.

RESULTS

MetS at baseline was 21.5%, while incident MetS and persistent MetS were 12.0% and 66.6%, respectively, at the 3.13 ± 1.38 years follow-up period. In men, baseline restrained EB had positive associations with concurrent MetS (odds ratio [95% confidence interval] per 1 point increase in the score, 1.55 [1.33-1.81]) and persistent MetS (1.53 [1.16-2.01]); baseline external EB and change in external EB had positive associations with persistent MetS (1.56 [1.04-2.33], 1.37 [1.01-2.22], respectively). In women, baseline restrained EB had a positive association with concurrent MetS (1.14 [1.01-1.30]); baseline external EB had an inverse association with persistent MetS (0.71[0.52-0.98]); baseline emotional EB had positive associations with concurrent, incident, and persistent MetS (1.23 [1.01-1.50], 2.14 [1.50-3.06], and 1.92 [1.40-2.64], respectively); and change in emotional EB had positive associations with incident and persistent MetS (1.50 [1.05-2.15], 1.62 [1.14-2.29], respectively).

CONCLUSION

Higher restrained and external EB, and an increase in external EB in men; and higher restrained and emotional EB, and an increase in emotional EB in women may be associated with increased risk of concurrent, incident, or persistent MetS.

LEVEL OF EVIDENCE

III, cohort study.

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults

The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Indexes of diet quality can be derived theoretically from evidence-based recommendations, empirically from existing datasets, or a combination of the two. We used these methods to derive diet quality indexes (DQI), generated from a novel dietary assessment, and to evaluate relationships with cardiometabolic risk factors in young adults with (n = 106) or without (n = 106) diagnosed depression (62% female, mean age = 21). Participants completed a liking survey (proxy for usual dietary consumption). Principle component analysis of plasma (insulin, glucose, lipids) and adiposity (BMI, Waist-to-Hip ratio) measures formed a continuous cardiometabolic risk factor score (CRFS). DQIs were created: theoretically (food/beverages grouped, weighted conceptually), empirically (grouping by factor analysis, weights empirically-derived by ridge regression analysis of CRFS), and hybrid (food/beverages conceptually-grouped, weights empirically-derived). The out-of-sample CRFS predictability for the DQI was assessed by two-fold and five-fold cross validations. While moderate consistencies between theoretically- and empirically-generated weights existed, the hybrid outperformed theoretical and empirical DQIs in cross validations (five-fold showed DQI explained 2.6% theoretical, 2.7% empirical, and 6.5% hybrid of CRFS variance). These pilot data support a liking survey that can generate reliable/valid DQIs that are significantly associated with cardiometabolic risk factors, especially theoretically- plus empirically-derived DQI.