A Nutrition-Focused Approach During Continuous Glucose Monitoring Initiation in People With Type 2 Diabetes: Using a Theoretical Framework to Unite Continuous Glucose Monitoring and Food Choices.

Continuous glucose monitoring (CGM) has transformed diabetes care, yet opportunities for further innovations still exist. Some research suggests CGM could be an ideal tool to guide food choices and other healthy lifestyle behaviors, especially for people with type 2 diabetes (T2D). Behavior change theories can be used to understand and describe how CGM users make food-related decisions, which could ultimately lead to the design of more tailored and effective interventions. In this commentary, we describe what it looks like to use the behavior change wheel-a theory-based intervention development framework-to design an intervention for people with T2D who will use CGM data to guide food choices aligned with evidence-based nutrition recommendations. Such frameworks may be beneficial when designing or evaluating future technology-focused behavior change interventions.

The Use of Rescue Insulin in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).

OBJECTIVE: To describe rescue insulin use and associated factors in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE). RESEARCH DESIGN AND METHODS: GRADE participants (type 2 diabetes duration <10 years, baseline A1C 6.8%-8.5% on metformin monotherapy, N = 5,047) were randomly assigned to insulin glargine U-100, glimepiride, liraglutide, or sitagliptin and followed quarterly for a mean of 5 years. Rescue insulin (glargine or aspart) was to be started within 6 weeks of A1C >7.5%, confirmed. Reasons for delaying rescue insulin were reported by staff-completed survey. RESULTS: Nearly one-half of GRADE participants (N = 2,387 [47.3%]) met the threshold for rescue insulin. Among participants assigned to glimepiride, liraglutide, or sitagliptin, rescue glargine was added by 69% (39% within 6 weeks). Rescue aspart was added by 44% of glargine-assigned participants (19% within 6 weeks) and by 30% of non-glargine-assigned participants (14% within 6 weeks). Higher A1C values were associated with adding rescue insulin. Intention to change health behaviors (diet/lifestyle, adherence to current treatment) and not wanting to take insulin were among the most common reasons reported for not adding rescue insulin within 6 weeks. CONCLUSIONS: Proportionately, rescue glargine, when required, was more often used than rescue aspart, and higher A1C values were associated with greater rescue insulin use. Wanting to use noninsulin strategies to improve glycemia was commonly reported, although multiple factors likely contributed to not using rescue insulin. These findings highlight the persistent challenge of intensifying type 2 diabetes treatment with insulin, even in a clinical trial.

Acacia Gum Is Well Tolerated While Increasing Satiety and Lowering Peak Blood Glucose Response in Healthy Human Subjects.

Acacia gum (AG) is a non-viscous soluble fiber that is easily incorporated into beverages and foods. To determine its physiological effects in healthy human subjects, we fed 0, 20, and 40 g of acacia gum in orange juice along with a bagel and cream cheese after a 12 h fast and compared satiety, glycemic response, gastrointestinal tolerance, and food intake among treatments. Subjects (n = 48) reported less hunger and greater fullness at 15 min (p = 0.019 and 0.003, respectively) and 240 min (p = 0.036 and 0.05, respectively) after breakfast with the 40 g fiber treatment. They also reported being more satisfied at 15 min (p = 0.011) and less hungry with the 40 g fiber treatment at 30 min (p = 0.012). Subjects reported more bloating, flatulence, and GI rumbling on the 40 g fiber treatment compared to control, although values for GI tolerance were all low with AG treatment. No significant differences were found in area under the curve (AUC) or change from baseline for blood glucose response, although actual blood glucose with 20 g fiber at 30 min was significantly less than control. Individuals varied greatly in their postprandial glucose response to all treatments. AG improves satiety response and may lower peak glucose response at certain timepoints, and it is well tolerated in healthy human subjects. AG can be added to beverages and foods in doses that can help meet fiber recommendations.

The Influence of Diet Interventions Using Whole, Plant Food on the Gut Microbiome: A Narrative Review.

Dietary intake is a key determinant of gastrointestinal microbiota composition. Studies have considered the relationship between gut microbiota and dietary patterns. It is likely that certain plant foods that contain fiber and other bioactive matter may be more likely to drive microbial changes than others; however, study design and other factors can make interpretation of the literature difficult. Fifteen well-controlled, well-defined diet interventions published between 2008 and 2018 using whole, plant foods were evaluated for their influence on gut microbiota. There was limited effect on microbial diversity across studies and modest microbial changes were noted in 10 of 15 studies. More research is needed before specific plant foods can be recommended to improve gut microbiota and ultimately health. Methodologic considerations for future diet and microbiome studies are discussed. Additional research to better understand how specific whole, plant foods influence microbe composition, functionality, and metabolite production is needed, as are mechanistic studies linking diet-induced gut microbe changes to health.

Inulin-type fructans and whey protein both modulate appetite but only fructans alter gut microbiota in adults with overweight/obesity: A randomized controlled trial.

SCOPE: Independently, prebiotics and dietary protein have been shown to improve weight loss and/or alter appetite. Our objective was to determine the effect of combined prebiotic and whey protein on appetite, body composition and gut microbiota in adults with overweight/obesity. METHODS AND RESULTS: In a 12 week, placebo-controlled, double-blind study, 125 adults with overweight/obesity were randomly assigned to receive isocaloric snack bars of: (1) Control; (2) Inulin-type fructans (ITF); (3) Whey protein; (4) ITF + Whey protein. Appetite, body composition and gut microbiota composition/genetic potential were assessed. Compared to Control, body fat was significantly reduced in the Whey protein group at 12 wks. Hunger, desire to eat and prospective food consumption were all lower with ITF, Whey protein and ITF + Whey protein compared to Control at 12 wks. Microbial community structure differed from 0 to 12 wks in the ITF and ITF +Whey Protein groups (i.e. increased Bifidobacterium) but not Whey Protein or Control. Changes in microbial genetic potential were seen between Control and ITF-containing treatments. CONCLUSION: Adding ITF, whey protein or both to snack bars improved several aspects of appetite control. Changes in gut microbiota may explain in part the effects of ITF but likely not whey protein.

Consuming foods with added oligofructose improves stool frequency: a randomised trial in healthy young adults.

The impact of oligofructose (OF) intake on stool frequency has not been clearly substantiated, while significant gastrointestinal (GI) symptoms have been reported in some individuals. The aim of the present study was to determine the effects of OF on stool frequency and GI symptoms in healthy adults. In an 8-week, randomised, double-blind, parallel-arm study, ninety-eight participants were provided with 16 g OF in yogurt and snack bars (twenty male and thirty female) or matching control foods (seventeen male and thirty-one female), to incorporate, by replacement, into their usual diets. Participants completed a daily online questionnaire recording stool frequency and rating four symptoms: bloating, flatulence, abdominal cramping and noise, each on a Likert scale from '0' for none (no symptoms) to '6' for very severe, with a maximum symptom intensity score of 24 (sum of severities from all four symptoms). Online 24 h dietary recalls were completed during pre-baseline and weeks 4, 6 and 8 to determine fibre intake. When provided with OF foods, fibre intake increased to 24·3 (sem 0·5) g/d from pre-baseline (12·1 (sem 0·5) g/d; P < 0·001). Stool frequency increased with OF from 1·3 (sem 0·2) to 1·8 (sem 0·2) stools per d in males and 1·0 (sem 0·1) to 1·4 (sem 0·1) stools per d in females during intervention weeks compared with pre-baseline (P < 0·05),but did not change for control participants (males: 1·6 (sem 0·2) to 1·8 (sem 0·2); females: 1·3 (sem 0·1) to 1·4 (sem 0·1)). Flatulence was the most commonly reported symptom. Mean GI symptom intensity score was higher for the OF group (3·2 (sem 0·3)) v. control (1·7 (sem 0·1)) (P < 0·01), with few participants reporting above moderate symptoms. No change in symptom intensity occurred over time. Consuming yogurt and snack bars with 16 g OF improves regularity in young healthy adults. However, GI symptoms, resulting from an increase in oligofructose intake, may not diminish with time.

Feasibility of measuring gastric emptying time, with a wireless motility device, after subjects consume fiber-matched liquid and solid breakfasts.

To explore the feasibility and sensitivity of a new technology for measuring gastric emptying time (GET) in appetite research, and also to compare appetite after subjects consumed macronutrient- and fiber-matched liquid and solid meals. Fourteen women (BMI of 21.2 ± 0.3) participated in this randomized, crossover study. On two separate days, fasted subjects consumed liquid (fruit juices and skim milk) and solid (oatmeal, blueberries, and apples) breakfasts. Both meals had 10 g of fiber and 410 kcal. GET was assessed with the SmartPill GI Motility System®, appetite was assessed with visual analog scales, and food intake was measured at lunch. Despite the same amount of fiber, GET was about 1h longer after the oatmeal than after the liquids. Subjects were less hungry after the oatmeal than after the liquids. Satisfaction and fullness were marginally improved with the oatmeal compared to the liquids. There was a negative association between GET and hunger. Lunchtime food and beverage intake did not differ between treatments. The SmartPill appears feasible and sensitive in appetite research, but has limitations. A solid meal with naturally occurring fiber from oatmeal and whole fruits increased GET and decreased hunger more than a liquid meal with added fiber.

Glucose and insulin do not decrease in a dose-dependent manner after increasing doses of mixed fibers that are consumed in muffins for breakfast.

Conventional wisdom suggests that fiber consumption leads to lower postprandial glucose and insulin response. We hypothesized that increasing doses of mixed, viscous fiber would lower glucose and insulin levels in a dose-dependent manner. Healthy men (n = 10) and women (n = 10) with a body mass index of 24 ± 2 (mean ± SEM) participated in this double-blind, crossover study. On 4 separate visits, fasting subjects consumed an approximately 2093 kJ (500 calorie) muffin with 0, 4, 8, or 12 g of mixed fibers. Blood was drawn to measure glucose and insulin at regular intervals throughout a 3-hour test period. Area under the curve (AUC) glucose was significantly lower after 0 g of fiber than after 4, 8, or 12 g of fiber (arbitrary AUC units ± SEM: 25.3 ± 5.2 vs 44.6 ± 7.7, 49.7 ± 7.9, 51.5 ± 6.6, respectively; P < .006). Area under the curve glucose increased with increasing fiber doses (P for trend = .0003). Area under the curve insulin was higher after the 4-g dose than after the 0-, 8-, and 12-g doses (arbitrary AUC units ± SEM: 84.4 ± 8.0 vs 60.1 ± 6.5, 69.4 ± 8.7, 69.7 ± 8.5, respectively; P < .05); it did not change in a dose-dependent manner. Area under the curve glucose and AUC insulin did not correlate with each other. Glucose and insulin did not decrease in a dose-dependent manner after 0, 4, 8, and 12 g of mixed fibers were consumed in muffins for breakfast. The lack of differences was largely based on the individual variation in glucose response. Caution should be used when making general claims about the expected impact of fiber on glucose and insulin levels.

The use of a wireless motility device (SmartPill®) for the measurement of gastrointestinal transit time after a dietary fibre intervention.

Historically, measurement of gastrointestinal transit time has required collection and X-raying of faecal samples for up to 7 d after swallowing radio-opaque markers; a tedious, labour-intensive technique for both subjects and investigators. Recently, a wireless motility capsule (SmartPill®), which uses gut pH, pressure and temperature to measure transit time, has been developed. This device, however, has not been validated with dietary interventions. Therefore, we conducted a controlled cross-over trial to determine whether the device could detect a significant difference in transit time after ten healthy subjects (five men and five women) consumed 9 g of wheat bran (WB) or an equal volume, low-fibre control for 3 d. A paired t test was used to determine differences in transit times. Colonic transit time decreased by 10·8 (sd 6·6) h (P = 0·006) on the WB treatment. Whole-gut transit time also decreased by 8·9 (sd 5·4) h (P = 0·02) after the consumption of WB. Gastric emptying time and small-bowel transit time did not differ between treatments. Despite encouraging results, the present study had several limitations including short duration, lack of randomisation and unusable data due to delayed gastric emptying of the capsule. With minimal participant burden, the SmartPill technology appears to be a potentially useful tool for assessing transit time after a dietary intervention. This technology could be considered for digestive studies with novel fibres and other ingredients that are promoted for gut health.

Increasing doses of fiber do not influence short-term satiety or food intake and are inconsistently linked to gut hormone levels.

BACKGROUND: People who eat more fiber often have a lower body weight than people who eat less fiber. The mechanism for this relationship has been explained, in part, by increased satiety, which may occur as a result of changes in appetite-suppressing gut hormone levels, and decreases in food intake at subsequent meals. OBJECTIVE: We hypothesized that increasing doses of mixed fiber, consumed in muffins for breakfast, would proportionally influence satiety, gut hormone levels, and subsequent food intake. DESIGN: This was a randomized, double-blind, crossover study. Healthy men (n=10) and women (n=10) with a BMI of 24+/-2 (mean+/-SEM) participated in this study. Fasting subjects consumed a muffin with 0, 4, 8, or 12 g of mixed fibers and approximately 500 kcal. Visual analog scales rated hunger and satiety for 3 h; blood was drawn to measure ghrelin, glucagon-like peptide-1 (GLP-1), and peptide YY(3-36) (PYY(3-36)) at various intervals; and food intake was measured at an ad libitum lunch. RESULTS: Responses to satiety-related questions did not differ among treatments. However, despite lack of differences in satiety, gut hormone levels differed among treatments. Ghrelin was higher after the 12 g fiber dose than after the 4 and 8 g fiber doses. GLP-1 was higher after the 0 g fiber dose than after the 12 and 4 g fiber doses, and PYY(3-36) did not differ among fiber doses. Food intake was also indistinguishable among doses. CONCLUSION: Satiety, gut hormone response, and food intake did not change in a dose-dependent manner after subjects consumed 0, 4, 8, and 12 g of mixed fiber in muffins for breakfast.

Greater satiety response with resistant starch and corn bran in human subjects.

Some studies suggest high-fiber foods are more satiating than foods with little or no fiber. However, we hypothesized that certain types of dietary fiber may enhance satiety more than others. Healthy men and women (N = 20) participated in this acute, randomized double-blind, crossover study comparing the effects of 4 fibers and a low-fiber (LF) treatment on satiety. On 5 separate visits, fasting subjects consumed either a LF muffin (1.6 g fiber) or 1 of 4 high-fiber muffins (8.0-9.6 g fiber) for breakfast. The subjects used 4 questions on 100 mm visual analogue scales to rate satiety at baseline and at regular intervals for 180 minutes after muffin consumption. Responses were analyzed as area under the curve and significant differences from baseline. Satiety differed among treatments. Resistant starch and corn bran had the most impact on satiety, whereas polydextrose had little effect and behaved like the LF treatment. Results from this study indicate that not all fibers influence satiety equally.

Long-term enteral nutrition facilitates optimization of body weight.

BACKGROUND: Optimization of body mass index (BMI) among cancer survivors is a priority. Long-term enteral nutrition is required by many head and neck cancer survivors and may be utilized to affect changes in BMI. METHODS: We used a retrospective review of head and neck cancer survivors dependent on enteral nutrition. Patients were grouped according to their BMI at initiation of enteral feeding. Patients with normal, low, or elevated BMI were assigned a goal of weight maintenance, weight gain, or weight reduction, respectively. Changes in BMI over time were recorded. RESULTS: We identified 39 head and neck cancer survivors requiring enteral nutrition. Median time on enteral nutrition was 32 +/- 39.6 months. At the initiation of enteral feeding, 51% of patients had a normal BMI and were assigned to the weight maintenance group, 84% successfully maintained a normal BMI (mean 22.4 +/- 1.7 kg/m(2)), and 18% had a low BMI and were assigned to the weight gain group. In all, 85% achieved or trended toward a normal BMI (from 16.5 +/- 1.9 to 19.2 +/- 1.6 kg/m(2); p = .02). When enteral feedings began, 31% of patients had an elevated BMI and were assigned a goal of weight reduction; all were able to reduce their BMI (from 30.2 +/- 5 to 27.3 +/- 6 kg/m(2); p < .001). CONCLUSIONS: Long-term enteral feeding facilitates body weight optimization among ambulatory head and neck cancer survivors. These findings may potentially be generalized to all ambulatory patients who are dependent on enteral nutrition.