Increasing either protein or fiber at mealtimes has relatively modest effects on ingestive behavior. Whether protein and fiber have additive or interactive effects on ingestive behavior is not known. ...Fifteen overweight adults (5 female, 10 male; BMI: 27.1 ± 0.2 kg/m²; aged 26 ± 1 year) consumed four breakfast meals in a randomized crossover manner (normal protein (12 g) + normal fiber (2 g), normal protein (12 g) + high fiber (8 g), high protein (25 g) + normal fiber (2 g), high protein (25 g) + high fiber (8 g)). The amount of protein and fiber consumed at breakfast did not influence postprandial appetite or ad libitum energy intake at lunch. In the fasting-state, visual food stimuli elicited significant responses in the bilateral insula and amygdala and left orbitofrontal cortex. Contrary to our hypotheses, postprandial right insula responses were lower after consuming normal protein vs. high protein breakfasts. Postprandial responses in other a priori brain regions were not significantly influenced by protein or fiber intake at breakfast. In conclusion, these data do not support increasing dietary protein and fiber at breakfast as effective strategies for modulating neural reward processing and acute ingestive behavior in overweight adults.
Dietary protein and fiber independently influence insulin-mediated glucose control. However, potential additive effects are not well-known. Men and women (
= 20; age: 26 ± 5 years; body mass index: ...26.1 ± 0.2 kg/m²; mean ± standard deviation) consumed normal protein and fiber (NPNF; NP = 12.5 g, NF = 2 g), normal protein and high fiber (NPHF; NP = 12.5 g, HF = 8 g), high protein and normal fiber (HPNF; HP = 25 g, NF = 2 g), or high protein and fiber (HPHF; HP = 25 g, HF = 8 g) breakfast treatments during four 2-week interventions in a randomized crossover fashion. On the last day of each intervention, meal tolerance tests were completed to assess postprandial (every 60 min for 240 min) serum glucose and insulin concentrations. Continuous glucose monitoring was used to measure 24-h interstitial glucose during five days of the second week of each intervention. Repeated-measures ANOVA was applied for data analyses. The HPHF treatment did not affect postprandial glucose and insulin responses or 24-h glucose total area under the curve (AUC). Higher fiber intake reduced 240-min insulin AUC. Doubling the amount of protein from 12.5 g to 25 g/meal and quadrupling fiber from 2 to 8 g/meal at breakfast was not an effective strategy for modulating insulin-mediated glucose responses in these young, overweight adults.
Introduction
Many barriers prevent individuals from regularly engaging in physical activity (PA), including lack of time and access to facilities. Providing free gym membership close to one's work ...may alleviate both time and financial barriers, increase PA, and result in greater weight loss. The purpose of this secondary analysis was to determine if gym usage, self‐reported leisure PA, and weight loss differed between participants working on the University of Colorado Anschutz Medical Campus (ON) versus working off‐campus (OFF) during a 6‐month weight loss trial.
Methods
117 adults (ON, n = 62; OFF, n = 55) with overweight or obesity received free gym memberships for the duration of trial. Average gym check ins/week, self‐report leisure PA, weight, and fat and lean mass were compared between groups.
Results
ON reported more check‐ins than OFF (ON, 0.93 ± 0.16 times/week; OFF, 0.55 ± 0.10 times/week p = 0.038). Both groups reported increased leisure PA, with ON reporting more leisure PA than OFF at month 4. Both groups had reductions in weight and fat mass, which were similar between groups.
Conclusion
Gym usage in both groups was low, suggesting that convenient and free gym access only marginally promoted use of provided facilities, likely having little additional impact on PA and weight change.
CLINICAL TRIAL REGISTRATION
The parent trial was registered at clinicaltrials.gov: NCT02627105.
Adherence to healthy eating patterns (HEPs) is often short-lived and can lead to repetitive attempts of adopting-but not maintaining-HEPs. We assessed effects of adopting, abandoning, and readopting ...HEPs (HEP cycling) on cardiovascular disease risk factors (CVD-RF). We hypothesized that HEP cycling would improve, worsen, and again improve CVD-RF. Data were retrospectively pooled for secondary analyses from two randomized, crossover, controlled feeding trials (n = 60, 52 ± 2 years, 30.6 ± 0.6 kg/m²) which included two 5⁻6 week HEP interventions (Dietary Approaches to Stop Hypertension-style or Mediterranean-style) separated by a four-week unrestricted eating period. Ambulatory and fasting blood pressures (BP), fasting serum lipids, lipoproteins, glucose, and insulin were measured before and during the last week of HEP interventions. Fasting systolic BP and total cholesterol decreased (-6 ± 1 mm Hg and -19 ± 3 mg/dL, respectively, p < 0.05), returned to baseline, then decreased again (-5 ± 1 mm Hg and -13 ± 3 mg/dL, respectively, p < 0.05) when adopting, abandoning, and readopting a HEP; magnitude of changes did not differ. Ambulatory and fasting diastolic BP and high-density lipoprotein cholesterol concentrations followed similar patterns; glucose and insulin remained unchanged. Low-density lipoprotein cholesterol concentrations decreased with initial adoption but not readoption (-13 ± 3 and -6 ± 3, respectively, interaction p = 0.020). Healthcare professionals should encourage individuals to consistently consume a HEP for cardiovascular health but also encourage them to try again if a first attempt is unsuccessful or short-lived.
Background
There are well‐established regional differences in obesity prevalence in the United States but relatively little is known about why or whether success in weight loss differs regionally.
...Objective
The objective of this study was to determine whether changes in body weight, engagement in physical activity (PA), and psychosocial factors differed in Alabama (AL) versus Colorado (CO) in response to a 16‐week behavioral weight loss program.
Design
This is an ancillary study to a weight loss intervention being conducted simultaneously in AL and CO with identical intervention content and delivery in 70 participants (n = 31 AL and n = 39 CO). Body weight, objective (accelerometry) PA, and responses to psychosocial questionnaires (reward‐based eating, stress, social support) were collected at baseline and at Week 16.
Results
There were no differences in percent weight loss between states (AL: 10.98%; CO: 11.675%, p = 0.70), and weights at Week 16 were not different for participants in AL and CO (AL: 101.54 ± 4.39 kg, CO: 100.42 ± 3.67 kg, p = 0.84). Accelerometry‐derived step count, stepping time, and activity score were all greater at Week 16 for participants in AL compared to participants in CO. Hedonic eating scores were more favorable for participants in AL at baseline (AL: 24.08 ± 2.42; CO: 34.99 ± 2.12, p = 0.0023) and at Week 16 (AL: 18.62 ± 2.70; CO: 29.11 ± 2.19, p = 0.0023). Finally, participants in AL presented more favorable social support scores at Week 16 compared to participants in CO.
Conclusions
Weight loss did not differ between states, suggesting that factors contributing to higher obesity rates in some regions of the United States may not be barriers to weight loss. Further, participants in AL experienced greater improvements in some factors associated with weight maintenance, indicating the need to study regional differences in weight loss maintenance. National Clinical Trial 03832933.
There are well-established regional differences in obesity prevalence in the U.S., but relatively little is known about whether these differences impact efforts for weight loss. The objective of the ...study was to determine whether changes in body weight, engagement in physical activity (PA), and psychosocial factors differed in Colorado (CO) vs Alabama (AL) in response to a 16-week standardized behavioral weight management program. We hypothesized that weight loss would be greater in Colorado due to a more favorable physical and social environment.
This is an ancillary study to a weight loss intervention being conducted simultaneously in AL and CO with identical intervention content and delivery. Study participants (n = 70, 39 CO, 31 AL) were randomized to either a high protein (HP) or normal protein (NP) diet for 16 weeks and attended weekly group classes led by a trained coach targeting diet, mindset, and physical activity. Body weight, objective (accelerometry) and self-reported (International Physical Activity Questionnaire) PA, and responses to psychosocial questionnaires were collected at baseline and week 16. Psychosocial constructs included executive function, hedonic eating, stress, and social support.
Both states lost a significant amount of weight (CO 13.2 ± 4.9 kg P = 0.0067; AL 12.5 ± 5.6 kg P = 0.0262) with no differences between states (P = 0.9315). Both states improved in all PA outcomes over time, with AL increasing significantly more in objective PA measures when compared to CO. AL had more favorable scores for hedonic eating at baseline (23.2 ± 2.4 vs 32.5 ± 1.8, P = 0.0017), which persisted to week 16 (19.0 ± 2.7 vs 29.7 ± 2.2, P = 0.0021). Finally, AL improved in several social support factors while CO did not.
While weight loss did not differ between states, AL experienced greater improvements in some factors known to improve long-term weight loss maintenance. Results from this study provide a strong rationale for investigating potential regional differences in the maintenance of lost weight that may not be apparent during the active weight loss phase of interventions. Future research in this area will require effective methods for tracking participants beyond the conclusion of most clinical trials.
The parent clinical trial is supported by The Beef Checkoff.
Socioeconomically disadvantaged populations are more likely to have both low nutrition literacy and low cooking efficacy. This combination often results in a high consumption of convenience foods ...that are typically energy-dense, nutrient poor, and promote the development or exacerbation of chronic disease. The objective of this study is to examine the effect of nutrition education, hands-on cooking practices, and financial incentives on grocery purchasing behaviors and diet quality in a low-income community.
Forty participants will receive nutrition education and hands-on cooking experiences through a 10-week nutrition education program via Zoom. An instructor will teach participants a nutrition topic and then prepare and cook a related meal with them. Participants will be notified of the recipe prior to class, and required foods will be provided for those participants who are unable to afford them. Participants will also receive discounts on food items labeled as “Live HealthSmart Foods” (LHS) at the Village Market grocery store in the East Lake neighborhood of Birmingham, Alabama. LHS foods include fresh, frozen or canned fruits and vegetables, whole grains, lean proteins, and low-fat or fat-free dairy products. Participants will use a unique pin code to receive the discount and their account will be examined for trends in their shopping behaviors. Main outcomes of interest include proportion of LHS foods purchased, dietary intake measured by a food frequency questionnaire and changes in nutrition literacy and cooking efficacy.
Study results will indicate 1) if there is a synergistic effect of nutrition education, hands-on cooking practices, and financial incentives on grocery purchasing behaviors and 2) how the intervention influences diet quality.
Results will also inform our endeavor of expanding the territory of the Live HealthSmart food model in a randomized community-based trial investigating the intervention’s potential for translation and implementation in a wider and more diverse community setting.
This work was supported by the Live HealthSmart Alabama initiative, the Cooking Well nutrition program, Village Market, Albert Schweitzer Fellowship and the University of Alabama at Birmingham.
Abstract only
Background
Dietary protein and fiber independently influence insulin‐mediated glucose control. However, the potential additive or synergistic effects of higher protein and fiber intake ...on postprandial insulin and glucose responses are not known.
Purpose
This study assessed the effects of protein and fiber intakes at breakfast on postprandial insulin and glucose responses.
Methods
Men and women n = 20; age: 26 ± 5 y; body mass index: 26.1 ± 0.2 kg/m
2
; means ± SEM consumed provided breakfast meals with varying protein (high = 25 g vs. normal =12.5 g) and fiber (high= 8 g vs. normal = 3 g) amounts during 4, 2‐week interventions (randomized crossover experimental design). Each 2‐week period was separated by a 2‐week washout period. The breakfast variations included: normal protein and fiber (NPNF), normal protein and high fiber (NPHF), high protein and normal fiber (HPNF), or high protein and fiber (HPHF). Breakfast was provided with fixed energy (400 kcal) and digestible carbohydrate (50 g) on each day, and the remainder of daily energy intake was self‐selected. On the last day of each intervention period, a meal tolerance test was completed to assess serum glucose and insulin concentrations at fasting and hourly for 4 hours (240 min). Repeated measures ANOVA was applied for data analyses.
Results
There were no differential responses among breakfast meals on composite postprandial insulin and glucose (240‐min total areas under the curve (AUC)) after adjusting for fasting values, sex, and breakfast treatment order. Analysis of the 0–120 min and 120–240 min AUCs supported that higher protein and/or fiber did not influence glucose responses. Further, differential responses were not observed for insulin AUC at 0–120 min but were for 120–240 min. The 120–240 min insulin AUC was numerically lowest after NPHF (880 ± 103 μU/mL) and was statistically different from HPNF (1228 ± 104 μU/mL) but not HPHF (1004 ± 104 μU/mL) or NPNF (1049 ± 108 μU/mL).
Conclusion
Doubling the amount of protein from 12.5 g to 25 g/meal and increasing fiber from 3 to 8 g/meal did not additively or synergistically affect postprandial insulin and glucose responses. These results do not support increasing dietary protein and fiber at breakfast as an effective strategy for modulating insulin‐mediated glucose responses in young, overweight adults.
Support or Funding Information
Support: American Egg Board‐ Egg Nutrition Center; NIH UL1TR0001108; USDA‐NIFA 2011‐38420‐20038
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