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AbstractBackground:Lifestyle changes that emphasis on plant-based diets (PBD) are typically recommended for those at risk for type 2 diabetes mellitus (T2DM) to mitigate their cardo-metabolic risk. We examined the impact of the inclusion of eggs compared with their exclusion from PBD on diet quality among adults at risk for T2DM.Methods:This was a randomized, controlled, single-blind, crossover trial of 35 adults (mean age 60.7 years; 25 women, 10 men; 34 Caucasians, 1 African-American) at risk for T2DM (i.e., pre- diabetes or metabolic syndrome) assigned to one of two possible sequence permutations of two treatments (PBD with eggs and exclusively PBD), with a 4-week washout period. Participants received dietary counseling from a dietitian to exclude or to include 2 eggs daily in the context of PBD for a 6-week period. Diet quality was assessed using the Healthy Eating Index 2015 (HEI-2015) at baseline and 6 weeks.Results:Compared with the exclusion of eggs, the inclusion of eggs in the context of PBD improved the diet quality score for intake of total protein foods (1.0 ± 1.1 vs. −0.4 ± 1.0; p<.0001); seafood and plant proteins (0.2 ± 1.2 vs. −0.4 ± 1.1; p = 0.0338); and fatty acids (0.8 ± 2.5 vs. −0.7 ± 2.7; p = 0.0260). Overall diet quality score depreciated with the adoption of exclusively PBD without eggs (−3.1 ± 8.3; p = 0.0411), while it was unaffected with the adoption of a PBD with the inclusion of eggs (−0.6 ± 7.9; p = 0.6892).Conclusions:Eggs could be used as an adjuvant to enhance the diet quality among those at risk for T2DM who adopt plant-based dietary patterns.

Purpose: We previously demonstrated that including walnuts in the diets of adults at risk for type 2 diabetes mellitus (T2DM) led to improved overall diet quality. This report examines the specific changes in their nutrient intake.Design: This was a randomized, controlled, modified Latin square parallel design trial with 2 treatment arms. Participants were randomized to walnut intake with, or without, dietary advice to regulate caloric intake. Within each treatment arm, they were further randomized to one of 2 sequence permutations (walnut-included/walnut-excluded or walnut-excluded/walnut-included diet), with a 3-month washout between treatment phases.Setting: Community hospital in Lower Naugatuck Valley in Connecticut.Participants: Cohort of 112 participants (31 men and 81 women) at risk for T2DM.Intervention: Participants included 56 g (366 kcal) of walnuts in their daily diets for 6 months.Measures: Nutrient intake was assessed using web-based Automated Self-Administered 24-Hour Dietary Assessment.Analysis: Data were analyzed using generalized linear models.Results: Walnut inclusion led to increased intake of total fat, calcium, magnesium, thiamin, total saturated fatty acids, and monounsaturated and polyunsaturated fatty acids (379.0 ± 90.3 g vs −136.5 ± 92.7 g, P< .01; 230.7 ± 114.2 mg vs −95.2 ± 117.4 mg, P= .05; 111.0 ± 33.9 mg vs −32.3 ± 34.9 mg, P< .01; 0.28 ± 0.2 mg vs −0.47 ± 0.2 mg, P= .02; 8.6 ± 3.4 g vs −1.1 ± 3.5 g, P=.05; 6.3 ± 3.9 g vs −6.3 ± 4.0 g, P= .03; and 25.4 ± 4.0 vs −6.6 ± 4.2 g, P< .01, respectively). Vitamin C intake decreased (−65.3 ± 55.3 mg vs 98.9 ± 56.8 mg, P= .04). Protein intake increased from baseline with the inclusion of walnuts (20.0 ± 8.8 g, P< .05). Walnut inclusion led to an increase in total calories consumed when caloric intake is not regulated.Conclusion: Including walnuts in the diets of these adults led to increased dietary intake of some nutrients associated with lower risk of developing T2DM and other cardiometabolic risk factors.

Purpose. To compare two intensity levels (standard vs. enhanced) of a nutrition and physical activity intervention vs. a control (usual programs) on nutrition knowledge, body mass index, fitness, academic performance, behavior, and medication use among elementary school students.Design. Quasi-experimental with three arms.Setting. Elementary schools, students’ homes, and a supermarket.Subjects. A total of 1487 third-grade students.Intervention. The standard intervention (SI) provided daily physical activity in classrooms and a program on making healthful foods, using food labels. The enhanced intervention (EI) provided these plus additional components for students and their families.Measures. Body mass index (zBMI), food label literacy, physical fitness, academic performance, behavior, and medication use for asthma or attention-deficit hyperactivity disorder (ADHD).Analysis. Multivariable generalized linear model and logistic regression to assess change in outcome measures.Results. Both the SI and EI groups gained less weight than the control (p < .001), but zBMI did not differ between groups (p = 1.00). There were no apparent effects on physical fitness or academic performance. Both intervention groups improved significantly but similarly in food label literacy (p = .36). Asthma medication use was reduced significantly in the SI group, and nonsignificantly (p = .10) in the EI group. Use of ADHD medication remained unchanged (p = .34).Conclusion. The standard intervention may improve food label literacy and reduce asthma medication use in elementary school children, but an enhanced version provides no further benefit.

To examine the association of the Supplemental Nutrition Assistance Program (SNAP) and diet quality among low-income adults.

Purpose. Consumer understanding of nutrition information is key to making dietary choices consistent with guidelines. The development of an objective, science-based, and universally applicable system of nutrition guidance would be of considerable potential value to the public health.Design. A multidisciplinary expert panel was convened to develop the Overall Nutritional Quality Index (ONQI). Dietary guidelines, existing nutritional scoring systems, and other pertinent scientific literature were reviewed. An algorithm based on the overall nutritional quality of food was developed and subjected to consumer research and validation testing.Results. The ONQI algorithm incorporates over 30 entries representing both micronutrient and macronutrient properties of foods, as well as weighting coefficients representing epidemiologic associations between nutrients and health outcomes. The basic entry in the algorithm is a weighted trajectory score, which compares nutrient concentration in a food to the recommended concentration of a given nutrient in a healthful diet. In content validity testing, ONQI rankings and expert panel rankings correlated highly (R = .92; p < .001). In regression analysis, aggregated ONQI scores for total diet corresponded well with the Healthy Eating Index (p < .001) in the National Health and Nutrient Examination Survey 2003–2006 cohort (n = 15,900). Consumer research indicated strong appeal to consumers of the ONQI system in general, and the scores on a 1 to 100 scale specifically. A system for acquiring nutrient data, meeting U.S. Food and Drug Administration and U.S. Department of Agriculture standards, has been established so that virtually any food, beverage, meal, or recipe can be scored.Conclusions. The ONQI is a sophisticated nutrition guidance system developed by a multidisciplinary group independently of all food industry interests with excellent initial performance in both consumer research and validation testing. Combined with a consumer education program, the ONQI has considerable potential to improve dietary patterns, and consequently the public health. Prospective study of effects on dietary patterns and health outcomes is warranted.