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A Randomized, Crossover Trial Assessing Appetite, Energy Metabolism, Blood Biomarkers, and Ad Libitum Food Intake Responses to a Mid-Morning Pecan Snack vs. an Equicaloric High-Carbohydrate Snack in Healthy Volunteers with Overweight/Obesity

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Anschutz Health and Wellness Center, 12348 E. Montview Blvd., MailStop C263, Aurora, CO 80045, USA
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Division of Endocrinology, Diabetes and Metabolism, University of Colorado Denver, Anschutz Medical Campus, 12801 E. 17th Ave., RC1 South Rm 7103, Aurora, CO 80045, USA
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Department of Pediatrics, University of Colorado Denver, Anschutz Medical Campus, 13123 E. 16th Ave., B065, Aurora, CO 80045, USA
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Division of General Internal Medicine, University of Colorado Denver, Anschutz Medical Campus, 12801 E. 17th Ave., RC1 South Rm 7103, Aurora, CO 80045, USA
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Department of Medicine, Medical University of South Carolina, 96 Jonathan Lucas St., CSB 822, Charleston, SC 29425, USA
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Author to whom correspondence should be addressed.
Nutrients 2024, 16(13), 2084; https://doi.org/10.3390/nu16132084
Submission received: 7 June 2024 / Revised: 27 June 2024 / Accepted: 28 June 2024 / Published: 29 June 2024
(This article belongs to the Section Carbohydrates)

Abstract

:
Background: The differential effects of pecans versus other popular snack foods on appetite and blood markers of metabolism and satiety have not been well studied. This study investigated the effects of a single mid-morning snack of pecans or tortilla chips on subjective appetite, food intake, blood measures of hormones and metabolites, and resting energy expenditure. Methods: Twenty participants with overweight and obesity were enrolled in a within-participants, randomized crossover trial. Participants had indwelling catheters placed for blood sampling and were fed a standardized breakfast, followed two hours later by a 250 kcal snack of either pecans or tortilla chips, and then by a self-selected lunch. Visual analog scale (VAS) appetite measures, blood markers, and energy expenditure were taken at intervals after food consumption. Results: VAS ratings, energy, food intake and macronutrient composition did not differ between treatment conditions, but glucose and insulin were significantly more elevated after tortilla chips. Free fatty acids (FFA), triglycerides (TG), peptide YY (PYY), and glucagon-like peptide-1 (GLP-1) were higher after consuming pecans compared to tortilla chips. Conclusions: Pecan consumption improves postprandial glucose and insulin profiles which would be beneficial to individuals at risk of developing type 2 diabetes. Further studies are needed to investigate whether increased relative secretion of PYY and GLP-1 after eating pecans versus tortilla chips may affect subjective appetite and energy intake if consumed chronically.

1. Introduction

Pecans are one of several tree nuts for which there is a growing body of evidence describing positive health benefits, including cardiovascular health [1,2,3], appetite [4,5], and body weight management [6,7,8]. While pecans are often included in general statements about the effects of tree nuts on human physiology and health, they are less well-studied than some other tree nuts, such as almonds and walnuts. All tree nuts are relatively high in fat and energy, but there are differences in the composition of the fats present as well as their protein, carbohydrate, fiber, micronutrient, and phytochemical profiles [9,10,11], any of which may affect the physiological and behavioral responses to their consumption. Pecans are high in monounsaturated and polyunsaturated fats, low in saturated fat, protein, and carbohydrate, and high in tocopherols (particularly gamma-tocopherol), flavonoids and phytosterols [11,12,13]. As might be expected, pecans are often associated with studies reporting beneficial effects of tree nut consumption on blood lipids and lipoproteins, inflammatory markers, vascular function, and cardiovascular disease risk [3,14,15,16,17,18,19], although not all findings are consistent [20]. A smaller number of studies have directly examined the effects of pecans on cardiovascular health markers and have reported benefits largely consistent with those of almonds and walnuts [12,21,22]. The beneficial effect nuts have on blood lipids and other cardio-metabolic health markers is generally attributed to their high unsaturated to saturated fat ratio as well as their relatively high antioxidant content (e.g., from various polyphenolic compounds) [11].
Some nuts have been examined for their potential effects on body weight management. Almonds and walnuts have a reduced energy value compared to the Atwater factor estimate due to their reduced digestibility [23,24]. There are reports of enhanced satiety following nut consumption [25], although this finding is not consistent when compared to iso-caloric ingestion of other food [26]. Other studies have observed an increased thermic effect following nut consumption [27,28]. Increased satiety may be related to the high polyunsaturated fat content of nuts [29,30], while increased energy expenditure may be related either to the high content of polyunsaturated fats in nuts [31,32,33] or to their high content of flavonoids [34]. Studies have shown that when nuts are included in weight loss diets in comparison to diets without nuts, dietary compliance is improved and weight (and even weight loss) is not adversely affected [28,35,36,37,38]. Overall, despite their high fat and calorie content, nuts can be incorporated into the diet in moderation without interfering with weight loss and maintenance, while at the same time delivering benefits for cardiovascular health and diet quality [12,27,35,36,38,39,40].
To our knowledge, no studies have compared the postprandial effects of pecan snacks to other typical savory snacks of dramatically different macronutrient composition (e.g., tortilla chips) on measures of energy intake, appetite regulation (subjective evaluations of appetite, blood biomarkers of appetite), energy expenditure and substrate utilization. This may be important as diets high in carbohydrates and highly processed food have been implicated in the risk for obesity and metabolic dysregulation [41,42]. Pecans are high fat (21 g/ounce), low carbohydrate (3 g/ounce), relatively low protein (3 g/ounce) and low fiber snacks (3 g/ounce), while tortilla chips are much lower in fat (7 g/ounce), much higher in carbohydrate (19 g/ounce), with similar protein (2 g/ounce) and low fiber (1 g/ounce) contents. Both snacks are low or devoid of sugar (0–1 g/ounce). Given that snacking is a high-frequency behavior in the population and savory snacks are a large market, we conducted this study to directly compare a high-fat pecan snack to a typical high-carbohydrate savory snack. The reason we chose to compare pecans to tortilla chips instead of to other nuts is that people who are trying to lose or actively manage weight may avoid nuts because of their high fat and calorie content (for a standard weight-based serving) and choose a lower fat snack, like tortilla chips instead. Thus, it would help to better understand the effects of pecans on satiety and ad libitum food consumption in comparison to a different kind of snack that may attract weight-conscious individuals. Recent attention focused on “ultra-processed” foods and their potential contribution to weight gain and obesity [41] adds additional interest for comparing a natural, unprocessed snack like pecans, to a more highly processed snack like tortilla chips.
The major aim of this study was to characterize the metabolic, blood biomarker, subjective appetite, energy expenditure, and subsequent energy intake response to pecans when consumed as snacks compared to tortilla chips, which are comparatively much lower in fat, and much higher in carbohydrate.

2. Materials and Methods

2.1. Study Design

In this study, a randomized, two-period, crossover design was used to measure the effect of different snacks on appetite, blood biomarkers, energy expenditure, and self-selected energy intake. Participants were given a standardized breakfast of 250 kcal and then either roasted and lightly salted pecans (250 kcal, 1.25 ounces, 45 mg sodium/ounce) or lightly salted tortilla chips (250 kcal, 1.79 ounces, 55 mg sodium/ounce) as a mid-morning snack. See Appendix A, Figure A1 and Figure A2 for the pecan and tortilla chip nutrition facts panels. We used two different tortilla chips of nearly identical composition for this study because one of the products became unavailable during this study, forcing us to use a different, but comparable product. The snacks were given on two separate occasions, with at least one week between them. After the snack, participants were allowed to have an ad libitum lunch, during which their food and energy intake were assessed. Blood measures of appetite hormones and metabolic markers were assessed at baseline (before breakfast), before snack, and at regular intervals after snack and lunch. Subjective appetite was assessed by visual analog scales (VAS) before breakfast, and at 15, 40, 60, 90, and 120 min intervals thereafter including post-breakfast, post-snack, and post-lunch. Metabolic rate was assessed by ventilated gas exchange before breakfast and after the snack.

2.2. Participants

One hundred ninety-one adult male and female volunteers aged 20–50 with a body mass index (BMI, kg/m2) of 27 ≤ 40 were screened for eligibility (Figure 1). Participants had to habitually eat breakfast, be willing to eat the test snacks and other foods offered, be weight stable for the last 6 months (no loss or gain of more than 3 kg in last 6 months) and be willing to consent and adhere to test procedures and schedule. People with nut allergies, uncontrolled thyroid disorders, diabetes mellitus, eating disorders, who were pregnant, or planning to become pregnant during this study, who were lactating, had uncontrolled hypertension, were actively dieting, or were participating in an intensive physical activity training regimen (>300 min/wk exercise), or with any medical history or current medication affecting appetite were excluded. Pre-menopausal women were tested in the follicular phase of their menstrual cycle if cycling regularly. Also, individuals who consumed pecans regularly (>3× per week) were excluded to avoid any potential outcome effects due to habituation. People unable to lie still with a clear hood over their head for the measurement of energy expenditure (2× at 20 min/test) were also excluded. We chose to study individuals with overweight and obesity as they are likely to be seeking dietary strategies to help manage body weight.
Of the 191 applicants, 164 did not meet the eligibility criteria and 27 were enrolled in this study. Six of those enrolled did not participate in this study. Twenty-one participants completed both treatment visits. The data for one subject were not included in the analysis as they reported starting a weight loss medication during the trial which could have affected their appetite, blood, and energy expenditure measurements.
Participants were recruited from the Anschutz Medical Campus (over 25,000 employees) and surrounding community via flyers placed on campus and in the community, study information placed on our Center website, emails sent to members of our large recruiting database accumulated from previous studies, and to the campus community and social media ads if needed. Preliminary screening was performed by telephone interview and eligible participants came to the Anschutz Health and Wellness Center (AHWC) to complete screening. Objective measurement of height, weight, BP, pulse, review of medical history, and completion of a food screening questionnaire (to document that nuts are included in their usual diet, that they are regular breakfast eaters, and to confirm that they are not habitual pecan eaters) were collected from each participant. Participants were also shown the two test snacks (bag of pecans and bag of tortilla chips) and asked to try each snack to confirm that they would be able to consume the snacks as provided on test days. Informed consent was obtained from all eligible participants.

2.3. Protocol

2.3.1. Screening Visit

Baseline measures and washout week: Participants were asked to refrain from exercise and alcohol consumption the day before each test day and until after discharge on test days and were asked to not consume/use any food, caffeine, or marijuana for 12 h before testing (i.e., from 7 p.m. the night before test days). Further, participants were asked to abstain from any nut consumption during the one week before each test day.

2.3.2. Testing Visits

Test day visits and preparation: Participants were given food items to prepare and consume a standard dinner between 5 and 7 p.m. the night before each test day. The meal contained approximately 35% of the estimated total daily energy intake, 15% protein, 30% fat, and 55% carbohydrate. Participants were asked to fast after 7 p.m. the evening before each test day. On test days, participants reported to the clinic early in the morning after an overnight fast and underwent an assessment of resting metabolic rate (RMR; 20 min. assessment following a 30 min rest). An indwelling intravenous catheter was then placed in one arm for blood sampling throughout the test day. A baseline blood sample was drawn, and subjective measures of appetite were obtained using visual analog scales (VAS). They then received a standardized breakfast providing approximately 266 total kcal, consisting of 18% protein, 30% fat, and 52% carbohydrate (as % of calories). The content of the breakfast was Eggbeater scrambled eggs, whole wheat bread with butter, orange juice, and 12 ounces of water. They were asked to consume the entire breakfast in 15 min. VAS measures of hunger, fullness, and prospective consumption [43] were completed at time zero and 15, 40, 60, 90, and 120 min following breakfast until the test snacks were provided mid-morning. A pre-snack blood sample was drawn, a VAS scale was completed, and the test snacks (250 kcal; 1.25 ounces of pecans, and 1.79 ounces of tortilla chips) were consumed in their entirety (15 min to consume; 8 ounces of water provided). REE (20 min measure) was assessed immediately after snack consumption. VAS appetite scales and blood were completed/drawn at 15, 40, 60, 90, and 120 min following snack consumption, with the last recording/sample occurring just before consumption of an ad libitum lunch meal.
The ad libitum lunch meal consisted of a variety of different foods offering approximately 1843 kcal of energy with an overall composition of approximately 15% protein, 55% carbohydrate, and 30% fat. Twelve ounces of water and one can each of regular Pepsi and Diet Pepsi were provided as the beverages. Participants were given 30 min for lunch and instructed to eat what they wanted. They could request more of any food. This design neither restricted intake nor encouraged overconsumption. Blood samples and VAS appetite ratings were taken/completed at 15, 40, 60, 90, and 120 min from the start of lunch. Participants were then discharged.

2.4. Outcome Measures

Energy and macronutrient intake at lunch: Ad libitum energy intake and macronutrient composition consumed at lunch were assessed by weighing all food served to participants and weighing any remaining food after the meal and calculating energy and nutrient intake based using the ProNutra™ (version 3.6.0.1) nutrition software.
Blood measures: The following analytes were determined using the Olympus Chemistry Analyzer, Beckman AU 480, Beckman Coulter, Brea, CA, USA. Plasma glucose was determined by the hexokinase method. Serum insulin was determined by a chemiluminescence immunoassay using the Access®, Ultrasensitive Insulin Reagent. Serum free fatty acids (FFA) and plasma triglycerides (TG) were measured spectrophotometrically using Fisher Scientific reagents (Thermo Fisher Scientific, Waltham, MA, USA). Plasma total glucagon-like peptide-1 (GLP-1) was measured by ELISA kit, Mercodia, Uppsala, Sweden. Plasma peptide YY (PYY), leptin, and ghrelin were measured by radio-immunoassay kit, Millipore Sigma, Burlington, MA, USA.
All serum and plasma samples were stored at −70 °C until analysis. Homeostatic model assessment of insulin resistance (HOMA-IR) was calculated from fasting glucose and insulin (HOMA-IR = Glucose (mg/dL) × Insulin (μU/L)/405) [44].
Energy expenditure: Resting (RMR) and post-meal resting energy expenditure (REE) were measured by standard indirect calorimetry using the ventilated hood technique (Parvo Medics Truemax 2400, Salt Lake City, UT, USA). This was performed at baseline (before breakfast) and after the mid-morning snack. The baseline measure (RMR) was taken after 30 min of supine quiet rest. Post-snack measures of energy expenditure (REE) were taken when participants were at rest (sitting, before laying down for the measure) during their stay in the test facility. Data from 3 min to 18 min (out of the 20 min measure) were used in the analysis as this time yielded the most stable readings (eliminating effects of movement as participants were getting comfortable).
Appetite: During the study day, participants marked visual analog scales (hunger, fullness, desire to eat, prospective consumption) administered at baseline, and at 15, 40, 60, 90, and 120 min after breakfast, snack, and lunch. Subjective feelings were rated on a 100 mm horizontal line preceded by the questions: “How hungry are you right now?” and anchored on the left by “not at all hungry” and by “extremely hungry” on the right; Fullness was queried by “How full do you feel right now?” anchored by “not at all…” and “extremely…”; Desire to eat was queried by, “How strong is your desire to eat right now?” anchored by “not at all…” and “extreme…; and prospective consumption was queried by, “how much food do you think you can eat right now?” with anchors of “not (much) at all” to “extremely/an extreme amount”. Participants marked a vertical line on the 100 mm horizontal line to indicate their feelings in response to the questions.
The snack, meal, and sampling schedules are shown in Table 1.

2.5. Statistical Analysis

Randomization and sample size: Participants were randomized by a computer algorithm. There were no previous studies to estimate the potential effect size of pecans as compared to tortilla chips on subjective appetite or food intake in this study. We determined the sample size to ensure at least 80% power at a 5% significance to detect a clinically meaningful effect between the two snack conditions for subjective appetite and food intake, and to ensure this study would have a Williams design ([45] even number of participants). No adjustment of type 1 error for multiple outcomes was used because of the exploratory nature of this study. Mean and SD for energy intake at lunch were assumed to be 705 kcal and 299 kcal, respectively, taken from a recently completed study of 44 participants of similar age and BMI range performed in Dr. Cornier’s lab [46]. Mean and SD for VAS measures were taken from a weight loss study performed by our group [47]. If we assume that the SD is the same for two visits and a typical correlation between measures at two different visits is 0.75, then using the NQuery module of power analysis for 2 × 2 crossover design, a sample size of 10 per sequence group (total of 20) is required to have 84% power at 5% significance to detect effect sizes of 7–8 mm on a 100 mm scale for hunger and fullness (which have been meaningful in previous studies from our group, e.g., [46,47]), and 142 kcal for energy intake at lunch. At least 24 participants needed to be enrolled to allow for 20% attrition.
Analysis of outcome variables: Separate analyses were conducted for outcome measures evaluated over post-breakfast, post-snack, and post-lunch intervals. Using the trapezoidal rule, individual repeated measures of laboratory and VAS variables over each follow-up interval were, respectively, summarized using the area under the curve (AUC) and AUC increment (iAUC), mean, maximum, and nadir over the corresponding interval. These summary variables for repeated outcome measures and outcomes without repeated measures such as energy intake were analyzed using the Linear mixed effects model (LMM) with random subject effect to test the difference in the outcome between two experimental conditions. The model consists of sequence group (pecan-tortilla chips or chips-pecan), period (1st or 2nd visit), and treatment (pecan or tortilla chips) as fixed effects. The effect of pecans as compared to tortilla chips was assessed by testing the between-condition difference in the least square means from the model. In addition, we modeled the repeated measure data in the raw scale by introducing a time effect and interaction term of time by treatment in the abovementioned LMM model, to delineate the profiles of trajectory and assess the difference between two experimental conditions. Analyses from both approaches produced consistent results. The appropriateness of the normal assumption of the LMM model was examined by graphically reviewing residual plots. The ninety-percent confidence interval was estimated from the LMM model. p-values < 0.05 were deemed statistically significant. No adjustment for multiple outcomes as well as multiple a priori comparisons for a given outcome were applied. SAS 9.4 software (SAS Institute Inc., Cary, NC, USA) was used for all the analyses. Of particular note, there is a participant whose glucose response after the pecan snack was 3 to 4 times higher for several repeated measures as compared to the rest of the participants. Sensitivity LMM analysis excluding this participant produced opposite response patterns and statistical testing results. Therefore, we reported glucose results from the analyses excluding this influential participant.

3. Results

3.1. Participant Characteristics

Fourteen female and six male participants completed this study as shown in Table 2. The mean age of participants was 35.8 years and the mean body mass index (BMI, kg/m2) was 30.9 with a range of 27.2–39.2, encompassing the study inclusion criteria of 27–40. Baseline blood markers (glucose, insulin, FFA, TG, ghrelin, peptide YY, GLP-1, and leptin were all within normal ranges and were not significantly different between visits. Participants were also not insulin resistant with HOMA-IR values ≤ 2.

3.2. Subjective Appetite Measures

Subjective reports of hunger, fullness, desire to eat, and prospective consumption were not significantly different between the tortilla chip and pecan conditions before and after breakfast, snack, and lunch meals (see Appendix A, Figure A3, Figure A4, Figure A5 and Figure A6). Visual analog responses for each of the measures followed the expected patterns of change following food consumption, with hunger, desire to eat, and prospective consumption declining and then increasing before the next eating occasion, and fullness increasing and then declining before the next meal.

3.3. Breakfast, Snack, and Self-Selected Lunch Consumption

Participants consumed on average all of the breakfast and the entire snack as instructed. There were no differences in breakfast or snack intake as a function of condition (pecan or tortilla chip snack) or of visit order. Likewise, there were no significant differences in energy intake, weight of food consumed, or macronutrient composition at lunch between the two snack treatment conditions (Figure 2A–F).

3.4. Plasma Metabolites and Appetite Hormones

3.4.1. Glucose

There were no differences in participants’ glucose levels either before or after the standardized breakfast on either testing day (Figure 3A). Consumption of tortilla chips caused a significantly greater increase in blood glucose at all time points compared to pecans (Figure 3B), and a similar significant treatment difference was observed when examined as an area under the response curve, which was performed to account for any potential effect of multiple comparisons. Glucose responses following lunch were not different between the two treatments (Figure 3C).

3.4.2. Insulin

Insulin responses to consumption of the standardized breakfast did not differ on the two treatment days (Figure 4A). Consumption of tortilla chips provoked a significant increase in insulin both compared to time zero and to the pecan response. The pecan snack did not increase insulin and there was a downward trend over time since breakfast. (Figure 4B). There were no significant differences in insulin following lunch between either treatment, and insulin increased under both conditions (Figure 4C). The initial values were nearly significantly greater for the chip condition reflecting a carryover from the mid-morning snack effect.

3.4.3. Free Fatty Acids

Free fatty acids declined in the post-breakfast period and there were no differences between treatment conditions (Figure 5A). Pecan consumption caused a significant rise in FFA levels both from time zero and compared to tortilla chips (Figure 5B). Following lunch, there was a significant decline in FFA in the pecan condition starting from a high-level carryover from the snack and remaining above the level seen in the chip condition throughout the measurement period (Figure 5C).

3.4.4. Triglycerides

Triglycerides were significantly greater in the chip condition compared to the pecan condition before and after breakfast (Figure 6A); however, they did not differ at the start of the mid-morning snack and were not different between conditions following the snack (Figure 6B). After lunch, triglycerides significantly increased in the pecan condition when compared to the chip condition and were still greater compared to the chip treatment when the measurement period stopped (Figure 6C).

3.4.5. Ghrelin

There was no difference in ghrelin response to the standardized breakfast between the two conditions (Figure 7A). Ghrelin was significantly greater following the pecan snack consumption compared to the tortilla chips although the increase compared to time zero was not significant (Figure 7B). There were no differences between treatment conditions in ghrelin levels following lunch and there was a meal-related decline throughout the measurement period (Figure 7C).

3.4.6. Peptide YY

Peptide YY was greater at baseline in the chip condition compared to the pecan condition and declined after breakfast and was not different between conditions two hours later (Figure 8A). Levels of PYY increased after lunch and were not different between treatment conditions (Figure 8B). Following lunch, PYY levels increased in both conditions, and the increase was significantly greater in the pecan condition, possibly owing to a carryover from the effect of the pecan snack on circulating FFA, which are potent stimulators of PYY (Figure 8C).

3.4.7. GLP-1

GLP-1 increased after breakfast, and there was no difference between the two snack conditions (Figure 9A). There was a significant increase in GLP-1 following snack consumption and there was a greater rise following the pecan treatment compared to tortilla chips (Figure 9B). Following lunch, GLP-1 increased significantly, and there was no difference between the treatment conditions (Figure 9C).

3.5. Resting and Postprandial Energy Expenditure

Resting energy expenditure was not different at baseline (before breakfast) under either snack condition and there were no differences between conditions in the response to consumption of the standardized breakfast (Figure 10A), whether expressed as an average of energy expenditure over the measurement period or as an area under the curve. Resting energy expenditure increased from baseline by 7.4% in the pecan condition and by 10.9% in the tortilla chip condition, although these were not significantly different. The response measured after snack consumption represents both the residual response to breakfast as well as the response to snack. Because the breakfast was a fixed composition, any difference in response after the snack should reflect the effect of the particular snack fed. The RQ response to breakfast and snack was also not significantly different between conditions (Figure 10B), although the mean RQ increased following the tortilla chip snack while there was no change after consuming pecans.

4. Discussion

In this study, we characterized the acute appetitive and metabolic responses to two common snack foods with quite different nutritional compositions, pecans, which are high in fat and low in carbohydrate, and tortilla chips, which are high in carbohydrate and moderate in fat content. Both snacks had similar protein content. Tree nuts, like pecans, and tortilla chips are popular snacks, and it was of interest to understand if one or the other is more effective at reducing hunger and appetite as well as to document their effects on markers of metabolic health and disease risk. This may be especially important for individuals with overweight and obesity who may be at risk of developing type 2 diabetes [48].
We found that a single exposure to a 250 kcal isocaloric snack of either tortilla chips or pecans did not differentially affect subjective measures of hunger, fullness, desire to eat, or prospective consumption. The treatments also did not affect the amount of food, energy, or macronutrients consumed at a self-selected lunch meal. We also observed high energy intake at lunch (approximately 1000 kcal) after participants had already consumed 510 kcal at breakfast and snack. Our sample consisted of mainly women (14/20) and their daily calorie intake to maintain body mass would be approximately 2100 kcal for light exercise. Thus, leaving room for only 600 kcal for the rest of the day. The high intake at lunch is typical when a large self-selection assortment is offered [43] and this test condition may obscure any small difference in lunch intake that might result from the different snack treatments.
The pattern of subjective appetite responses following the meals and snacks was consistent with what would be expected following the consumption of food energy [49]. The lack of a differential effect of the two mid-morning snacks on subjective appetite and intake at the subsequent lunch meal may not be surprising since the caloric load consumed was the same. However, the weight and volume of the tortilla chips were significantly greater than that of the pecans, owing to their lower caloric density, 4.99 kcal/g for chips vs. 7.14 kcal/g for pecans. It has been observed that the weight, volume, and energy density of a food can affect satiety and satiation independent of the energy content [50,51,52,53,54], suggesting that the smaller weight and volume of the pecan snack could have been less satiating than the larger amount of tortilla chips, although this was not the case.
It is also possible that familiarity, previous experience, and expectation of particular subjective feelings following consumption of the two snacks may have dominated the response rather than any effect of the snack composition on physiological drivers of satiety and food intake. Our group has shown that despite no variable changes in measures of appetite with over or underfeeding, significant changes are seen in the neuronal responses to food-related cues [55,56]. Other investigators have found that intravenous co-infusion of the satiety hormones GLP-1 and PYY caused a significant reduction in food intake but did not affect subjective measures of appetite [57]. Intravenous infusion of the appetite hormones versus a food-provoked increase would eliminate any expected changes in subjective appetite ratings based on the appearance, amount, and any previously experienced appetite sensations, perhaps explaining why there was no effect. Expectations about satiety and satiation are conditioned upon multiple exposures to a food over time [58], and a single exposure under experimental conditions would likely not be expected to provoke a differential response to the two snacks. Furthermore, subjective ratings of appetite have not been shown to be good predictors of food or energy intake [43].
Given that we observed a significant increase in GLP-1 after pecan snack intake and an increase in PYY following lunch intake compared to the tortilla chip condition suggests that a rise in these satiety hormones after a single exposure may not be sufficient to affect subjective feelings of fullness and reduced hunger. It may be necessary to have repeated exposure to these snack foods over time so that changes in the satiety hormones are consistently associated with changes in internal feelings of hunger and satiety, affecting expectations and ultimately VAS appetite scores.
Other authors have found a similar discordance between changes in blood satiety hormones and subjective appetite following a single nut-enriched meal (walnuts) compared to a nut-free reference meal [59]. By contrast, feeding pecan-enriched diets for 8 weeks was associated with reduced overall appetite, desire to eat, prospective consumption, and greater fullness compared to a nut-free diet [4], suggesting that repeated exposure to the effects of different foods can produce changes in subjective appetite measures.
Although subjective hunger and appetite were not differentially affected by the two snacks, there were significant differences in metabolic markers and appetite hormones. We observed significant differences in the responses of glucose, insulin, fatty acids, and triglycerides to consumption of the snacks, which were consistent with their carbohydrate and fat composition. Tortilla chips provoked a more marked increase in glucose and insulin than did pecans owing to the much greater carbohydrate content of the snack fed (34 g for tortilla chips vs. 5 g for pecans). Tortilla chips have a medium Glycemic Index of approximately 60 [60], and given the 34 g serving, the glycemic load would be approximately 20.4, which would be considered a high glycemic snack [61]. The rise in insulin following the chip snack carried over to lunch two hours later while insulin declined slightly after the pecan snack. The greater elevation of glucose and insulin after consuming the tortilla chip snack might suggest that such high-carbohydrate snacks could be a risk factor in the development of insulin resistance and type 2 diabetes [62].
The pecan snack was associated with a prolonged rise in serum FFA over the snack and lunch period that was not observed after the tortilla chip snack, where FFA were unchanged. The rise in FFA after the pecan snack was likely due to the lack of insulin stimulation, which would eliminate insulin action to suppress lipoprotein lipase and hence the release of FFA from TG hydrolysis [63,64]. The consecutive consumption of the tortilla chip snack and lunch provoked a prolonged rise in insulin across the 4 h of measurement (from the start of snack to the end of lunch), effectively suppressing TG hydrolysis and FFA release during the entire period.
The pecan condition was also associated with a significant rise in TG (compared to tortilla chips) beginning late after snack consumption and becoming significant 40 min after the start of lunch. This rise was likely the combined effect of consuming the high-fat snack (26 g fat) plus an additional amount of fat (approximately 40 g) at lunch. Peak blood TG levels occur approximately 4–5 h after a high-fat meal [65], timing which is consistent with the peak TG levels occurring approximately 3.5 h after consumption of the high-fat pecan snack.
Ghrelin is often thought of as the hunger hormone, with its level being elevated before a meal [66], and declining after food consumption [67]. Plasma ghrelin levels were significantly greater following pecan consumption compared to tortilla chips, suggesting that the chips suppressed hunger to a greater extent than pecans. This is consistent with other studies demonstrating that a high-carbohydrate meal is more effective at suppressing ghrelin than a high-fat meal [68]. Despite this finding, VAS hunger ratings were not different between the two snack conditions. Other studies have found that ghrelin or changes in ghrelin do not predict or associate with hunger ratings [69]. In addition, ghrelin responses to the lunch meal were not different and showed the expected decline following food intake [67,70], and there were no differences in total food and energy intakes.
PYY is a satiety hormone released from intestinal enteroendocrine L cells in response to food intake, with levels rising within 15 min and reaching a plateau within 1–2 h after a meal [71]. Dietary protein, fat, and to a lesser extent carbohydrate stimulate PYY secretion [72,73], We observed the expected rise in PYY after both snack and lunch consumption in both treatment conditions. However, the increase in PYY was greater after lunch in the pecan condition which reflects a carryover from a rise occurring late after the snack (Figure 8B,C). The pattern of PYY elevation in the pecan condition followed the pattern of TG increase (Figure 6B,C), which may have resulted from the absorption of fat contained in both the snack and lunch. This response is consistent with the known effects of dietary fat on stimulating PYY secretion [74,75].
GLP-1 is a satiety hormone also secreted by the L cells of the distal gastrointestinal tract and its most potent dietary secretagogues are carbohydrates and fat [76,77]. We observed the expected increase in GLP-1 following food ingestion, with a significantly greater rise following the pecan snack compared to the tortilla snack between 60 and 120 min (Figure 9B). The response to the lunch meal was not different between conditions (Figure 9C), consistent with the observation that the nutrient composition of the self-selected lunch was not different between conditions. Despite the significant difference in GLP-1 level after the snack, there was no difference in any of the subjective appetite measures, a finding consistent with other studies showing changes in appetite hormones without associated changes in subjective appetite [4,57].
Resting energy expenditure was increased by breakfast and snack intake as would be expected due to the thermic effect of food [78]. The increase was not significantly different between the two snack conditions, although the mean rise was greater after tortilla chips (approximately 11%) compared to pecans (approximately 7%). Carbohydrates are known to stimulate the thermic effect more than fats [78] and our findings are consistent with this expectation. Other investigators have reported that 8 weeks of consumption of a pecan-enriched diet led to significant increases in the thermic effect of food and fat oxidation following a high-fat test meal compared to values at baseline or compared to a control diet [79]. It is possible that long-term consumption of pecans may increase the thermic effect in response to fat, but it still may not exceed the effect of a high-carbohydrate treatment. The RQ in our study was also not significantly different between treatment conditions either after snack or lunch, although the RQ was numerically greater after the chips compared to the pecans, reflecting increased oxidation of the absorbed carbohydrates from the high-carbohydrate tortilla chips.
This study has several strengths, including the crossover design with each subject being exposed to both snack treatments, and using a wide range of measures, both subjective appetite, objective food intake, blood measures of important metabolites, appetite hormones, and postprandial energy expenditure. It is the first comparison, to our knowledge, of the appetitive and metabolic effects of two commercially available snack foods that are widely consumed. Finally, the participants all had overweight and obesity which is a population that might be at greater risk for undesirable metabolic effects of different snack foods.
This study also had several limitations, including the largely female participant population, making it difficult to ascertain any sex differences in treatment response due to power limitations. We did not document and control for habitual smoking or exercise behaviors, factors that could affect appetite and metabolic measures. Also, the single-meal challenge nature of the treatment was insufficient to allow conditioning of the physiological response to the treatments to the subjective feelings experienced.

5. Conclusions

A single exposure to an isocaloric snack of either pecans or tortilla chips did not differentially affect subjective hunger, satiety, desire to eat, or prospective consumption. The treatments also did not differentially affect intake at a self-selected lunch. However, there were significant differential effects on blood markers of satiety and energy metabolism, with the chip treatment stimulating a prolonged elevation of glucose and insulin, while the pecan treatment caused little if any increase. Pecans also significantly increased PYY and GLP-1 compared to tortilla chips, which might lead to changes in subjective appetite and energy intake over time. Further studies are needed to explore this possibility. The more favorable post-ingestive profile of glucose and insulin after consuming pecans suggests that they may be beneficial to individuals at risk of developing metabolic dysfunction and type 2 diabetes.

Author Contributions

Conceptualization, methodology, investigation, data curation, formal analysis, writing—review and editing, supervision and funding acquisition, J.C.P. and M.-A.C.; medical supervision, J.N.; investigation resources, data curation, project administration and writing—review and editing, J.C.P. and J.A.B.; formal analysis, visualization, J.C.P., M.-A.C., J.N. and Z.P. All authors have read and agreed to the published version of the manuscript.

Funding

J.C.P. and M.-A.C. received funding from the American Pecan Council, award 202604. This project and publication are supported by NIH/NCATS, Colorado CTSA Grant Number UL1 TR002535, and by NIH/NCATS Colorado CTSA Grant Number UM1 TR004399. Contents are the authors’ sole responsibility and do not necessarily represent official NIH views.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki, reviewed and approved by the Colorado Multiple Institutional Review Board of the University of Colorado, Denver (protocol COMIRB #20-0048).

Informed Consent Statement

Informed consent was obtained from all participants involved in this study.

Data Availability Statement

Data described in this article can be requested by any qualified researcher and will be provided upon reasonable request.

Acknowledgments

We thank the staff of the Clinical Trials Unit at the Anschutz Health and Wellness Center for their assistance with participant recruitment, screening and enrollment, meal service, data collection, and data entry. We also thank the staff of the CCTSI CTRC Nutrition Core for test meal preparation and food consumption data collection, and the CCTSI outpatient CTRC for hosting the test day visits. Study data were collected and managed using REDCap electronic data capture [80] tools hosted at the University of Colorado Denver. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. The conduct of this study and the content of this paper are solely the responsibility of the authors. This study was registered at ClinTrials.gov (accessed on 26 June 2021), trial NCT04484974.

Appendix A

Figure A1. Nutrition facts panel for pecans fed in this study.
Figure A1. Nutrition facts panel for pecans fed in this study.
Nutrients 16 02084 g0a1
Figure A2. Nutrition facts panel for the two tortilla chip products used in this study.
Figure A2. Nutrition facts panel for the two tortilla chip products used in this study.
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Subjective appetite measures.
Figure A3. How hungry are you right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure A3. How hungry are you right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Nutrients 16 02084 g0a3
Figure A4. How full do you feel right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure A4. How full do you feel right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Nutrients 16 02084 g0a4
Figure A5. How strong is your desire to eat right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) Before and after snack; (C) Before and after lunch.
Figure A5. How strong is your desire to eat right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) Before and after snack; (C) Before and after lunch.
Nutrients 16 02084 g0a5
Figure A6. How much do you think you could eat right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) Before and after snack; (C) Before and after lunch.
Figure A6. How much do you think you could eat right now? Visual analog scale appetite scores on a 0–100 mm scale. (A) Before and after breakfast; (B) Before and after snack; (C) Before and after lunch.
Nutrients 16 02084 g0a6

References

  1. Kim, Y.; Keogh, J.B.; Clifton, P.M. Benefits of Nut Consumption on Insulin Resistance and Cardiovascular Risk Factors: Multiple Potential Mechanisms of Actions. Nutrients 2017, 9, 1271. [Google Scholar] [CrossRef] [PubMed]
  2. Altamimi, M.; Zidan, S.; Badrasawi, M. Effect of Tree Nuts Consumption on Serum Lipid Profile in Hyperlipidemic Individuals: A Systematic Review. Nutr. Metab. Insights 2020, 13, 1178638820926521. [Google Scholar] [CrossRef]
  3. Kris-Etherton, P.M.; Hu, F.B.; Ros, E.; Sabate, J. The role of tree nuts and peanuts in the prevention of coronary heart disease: Multiple potential mechanisms. J. Nutr. 2008, 138, 1746S–1751S. [Google Scholar] [CrossRef] [PubMed]
  4. Guarneiri, L.L.; Paton, C.M.; Cooper, J.A. Appetite responses to pecan-enriched diets. Appetite 2022, 173, 106003. [Google Scholar] [CrossRef]
  5. Cogan, B.; Pearson, R.C.; Jenkins, N.T.; Paton, C.M.; Cooper, J.A. A pecan-enriched diet reduced postprandial appetite intensity and enhanced peptide YY secretion: A randomized control trial. Clin. Nutr. ESPEN 2023, 56, 25–35. [Google Scholar] [CrossRef] [PubMed]
  6. Guarneiri, L.L.; Cooper, J.A. Intake of Nuts or Nut Products Does Not Lead to Weight Gain, Independent of Dietary Substitution Instructions: A Systematic Review and Meta-Analysis of Randomized Trials. Adv. Nutr. 2020, 12, 384–401. [Google Scholar] [CrossRef] [PubMed]
  7. Guarneiri, L.L.; Paton, C.M.; Cooper, J.A. Changes in body weight in response to pecan-enriched diets with and without substitution instructions: A randomised, controlled trial. J. Nutr. Sci. 2022, 11, e16. [Google Scholar] [CrossRef]
  8. Delgadillo-Puga, C.; Torre-Villalvazo, I.; Noriega, L.G.; Rodríguez-López, L.A.; Alemán, G.; Torre-Anaya, E.A.; Cariño-Cervantes, Y.Y.; Palacios-Gonzalez, B.; Furuzawa-Carballeda, J.; Tovar, A.R.; et al. Pecans and Its Polyphenols Prevent Obesity, Hepatic Steatosis and Diabetes by Reducing Dysbiosis, Inflammation, and Increasing Energy Expenditure in Mice Fed a High-Fat Diet. Nutrients 2023, 15, 2591. [Google Scholar] [CrossRef]
  9. Woźniak, M.; Waśkiewicz, A.; Ratajczak, I. The Content of Phenolic Compounds and Mineral Elements in Edible Nuts. Molecules 2022, 27, 4326. [Google Scholar] [CrossRef]
  10. Alvarez-Parrilla, E.; Urrea-López, R.; de la Rosa, L.A. Bioactive components and health effects of pecan nuts and their byproducts: A review. J. Food Bioact. 2018, 1, 56–92. [Google Scholar] [CrossRef]
  11. Bolling, B.W.; Chen, C.Y.; McKay, D.L.; Blumberg, J.B. Tree nut phytochemicals: Composition, antioxidant capacity, bioactivity, impact factors. A systematic review of almonds, Brazils, cashews, hazelnuts, macadamias, pecans, pine nuts, pistachios and walnuts. Nutr. Res. Rev. 2011, 24, 244–275. [Google Scholar] [CrossRef] [PubMed]
  12. Atanasov, A.G.; Sabharanjak, S.M.; Zengin, G.; Mollica, A.; Szostak, A.; Simirgiotis, M.; Huminiecki, Ł.; Horbanczuk, O.K.; Nabavi, S.M.; Mocan, A. Pecan nuts: A review of reported bioactivities and health effects. Trends Food Sci. Technol. 2018, 71, 246–257. [Google Scholar] [CrossRef]
  13. Villarreal-Lozoya, J.E.; Lombardini, L.; Cisneros-Zevallos, L. Phytochemical constituents and antioxidant capacity of different pecan [Carya illinoinensis (Wangenh.) K. Koch] cultivars. Food Chem. 2007, 102, 1241–1249. [Google Scholar] [CrossRef]
  14. Sabate, J.; Wien, M. Nuts, blood lipids and cardiovascular disease. Asia Pac. J. Clin. Nutr. 2010, 19, 131–136. [Google Scholar] [PubMed]
  15. Casas-Agustench, P.; Lopez-Uriarte, P.; Bullo, M.; Ros, E.; Cabre-Vila, J.J.; Salas-Salvado, J. Effects of one serving of mixed nuts on serum lipids, insulin resistance and inflammatory markers in patients with the metabolic syndrome. Nutr. Metab. Cardiovasc. Dis. NMCD 2011, 21, 126–135. [Google Scholar] [CrossRef] [PubMed]
  16. Del Gobbo, L.C.; Falk, M.C.; Feldman, R.; Lewis, K.; Mozaffarian, D. Effects of tree nuts on blood lipids, apolipoproteins, and blood pressure: Systematic review, meta-analysis, and dose-response of 61 controlled intervention trials. Am. J. Clin. Nutr. 2015, 102, 1347–1356. [Google Scholar] [CrossRef] [PubMed]
  17. Kim, Y.; Keogh, J.; Clifton, P.M. Nuts and Cardio-Metabolic Disease: A Review of Meta-Analyses. Nutrients 2018, 10, 1935. [Google Scholar] [CrossRef] [PubMed]
  18. Xiao, Y.; Xia, J.; Ke, Y.; Cheng, J.; Yuan, J.; Wu, S.; Lv, Z.; Huang, S.; Kim, J.H.; Wong, S.Y.; et al. Effects of nut consumption on selected inflammatory markers: A systematic review and meta-analysis of randomized controlled trials. Nutrition 2018, 54, 129–143. [Google Scholar] [CrossRef] [PubMed]
  19. Morgillo, S.; Hill, A.M.; Coates, A.M. The Effects of Nut Consumption on Vascular Function. Nutrients 2019, 11, 116. [Google Scholar] [CrossRef]
  20. Neale, E.P.; Tapsell, L.C.; Guan, V.; Batterham, M.J. The effect of nut consumption on markers of inflammation and endothelial function: A systematic review and meta-analysis of randomised controlled trials. BMJ Open 2017, 7, e016863. [Google Scholar] [CrossRef]
  21. McKay, D.L.; Eliasziw, M.; Chen, C.Y.O.; Blumberg, J.B. A Pecan-Rich Diet Improves Cardiometabolic Risk Factors in Overweight and Obese Adults: A Randomized Controlled Trial. Nutrients 2018, 10, 339. [Google Scholar] [CrossRef] [PubMed]
  22. Rajaram, S.; Burke, K.; Connell, B.; Myint, T.; Sabaté, J. A Monounsaturated Fatty Acid–Rich Pecan-Enriched Diet Favorably Alters the Serum Lipid Profile of Healthy Men and Women. J. Nutr. 2001, 131, 2275–2279. [Google Scholar] [CrossRef] [PubMed]
  23. Novotny, J.A.; Gebauer, S.K.; Baer, D.J. Discrepancy between the Atwater factor predicted and empirically measured energy values of almonds in human diets. Am. J. Clin. Nutr. 2012, 96, 296–301. [Google Scholar] [CrossRef] [PubMed]
  24. Baer, D.J.; Gebauer, S.K.; Novotny, J.A. Walnuts Consumed by Healthy Adults Provide Less Available Energy than Predicted by the Atwater Factors. J. Nutr. 2016, 146, 9–13. [Google Scholar] [CrossRef] [PubMed]
  25. Hull, S.; Re, R.; Chambers, L.; Echaniz, A.; Wickham, M.S.J. A mid-morning snack of almonds generates satiety and appropriate adjustment of subsequent food intake in healthy women. Eur. J. Nutr. 2015, 54, 803–810. [Google Scholar] [CrossRef] [PubMed]
  26. Sayer, R.D.; Dhillon, J.; Tamer, G.G.; Cornier, M.-A.; Chen, N.; Wright, A.J.; Campbell, W.W.; Mattes, R.D. Consuming Almonds vs. Isoenergetic Baked Food Does Not Differentially Influence Postprandial Appetite or Neural Reward Responses to Visual Food Stimuli. Nutrients 2017, 9, 807. [Google Scholar] [CrossRef] [PubMed]
  27. Mattes, R.D.; Dreher, M.L. Nuts and healthy body weight maintenance mechanisms. Asia Pac. J. Clin. Nutr. 2010, 19, 137–141. [Google Scholar] [PubMed]
  28. Tan, S.Y.; Dhillon, J.; Mattes, R.D. A review of the effects of nuts on appetite, food intake, metabolism, and body weight. Am. J. Clin. Nutr. 2014, 100 (Suppl. S1), 412S–422S. [Google Scholar] [CrossRef] [PubMed]
  29. Lawton, C.L.; Delargy, H.J.; Brockman, J.; Smith, F.C.; Blundell, J.E. The degree of saturation of fatty acids influences post-ingestive satiety. Br. J. Nutr. 2000, 83, 473–482. [Google Scholar] [CrossRef]
  30. Polley, K.R.; Kamal, F.; Paton, C.M.; Cooper, J.A. Appetite responses to high-fat diets rich in mono-unsaturated versus poly-unsaturated fats. Appetite 2019, 134, 172–181. [Google Scholar] [CrossRef]
  31. Stevenson, J.L.; Clevenger, H.C.; Cooper, J.A. Hunger and satiety responses to high-fat meals of varying fatty acid composition in women with obesity. Obesity 2015, 23, 1980–1986. [Google Scholar] [CrossRef] [PubMed]
  32. Clevenger, H.C.; Kozimor, A.L.; Paton, C.M.; Cooper, J.A. Acute effect of dietary fatty acid composition on postprandial metabolism in women. Exp. Physiol. 2014, 99, 1182–1190. [Google Scholar] [CrossRef] [PubMed]
  33. Casas-Agustench, P.; Lopez-Uriarte, P.; Bullo, M.; Ros, E.; Gomez-Flores, A.; Salas-Salvado, J. Acute effects of three high-fat meals with different fat saturations on energy expenditure, substrate oxidation and satiety. Clin. Nutr. 2009, 28, 39–45. [Google Scholar] [CrossRef] [PubMed]
  34. Kang, H.W.; Lee, S.G.; Otieno, D.; Ha, K. Flavonoids, Potential Bioactive Compounds, and Non-Shivering Thermogenesis. Nutrients 2018, 10, 1168. [Google Scholar] [CrossRef] [PubMed]
  35. Flores-Mateo, G.; Rojas-Rueda, D.; Basora, J.; Ros, E.; Salas-Salvadó, J. Nut intake and adiposity: Meta-analysis of clinical trials. Am. J. Clin. Nutr. 2013, 97, 1346–1355. [Google Scholar] [CrossRef]
  36. Sabate, J. Nut consumption and body weight. Am. J. Clin. Nutr. 2003, 78, 647s–650s. [Google Scholar] [CrossRef] [PubMed]
  37. Rajaram, S.; Sabate, J. Nuts, body weight and insulin resistance. Br. J. Nutr. 2006, 96 (Suppl. S2), S79–S86. [Google Scholar] [CrossRef] [PubMed]
  38. Wien, M.A.; Sabate, J.M.; Ikle, D.N.; Cole, S.E.; Kandeel, F.R. Almonds vs complex carbohydrates in a weight reduction program. Int. J. Obes. Relat. Metab. Disord. 2003, 27, 1365–1372. [Google Scholar] [CrossRef]
  39. Fraser, G.E.; Bennett, H.W.; Jaceldo, K.B.; Sabate, J. Effect on body weight of a free 76 Kilojoule (320 calorie) daily supplement of almonds for six months. J. Am. Coll. Nutr. 2002, 21, 275–283. [Google Scholar] [CrossRef]
  40. Baer, D.J.; Dalton, M.; Blundell, J.; Finlayson, G.; Hu, F.B. Nuts, Energy Balance and Body Weight. Nutrients 2023, 15, 1162. [Google Scholar] [CrossRef]
  41. Hall, K.D.; Ayuketah, A.; Brychta, R.; Cai, H.; Cassimatis, T.; Chen, K.Y.; Chung, S.T.; Costa, E.; Courville, A.; Darcey, V.; et al. Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake. Cell Metab. 2019, 30, 67–77.e3. [Google Scholar] [CrossRef] [PubMed]
  42. Ludwig, D.S.; Ebbeling, C.B. The Carbohydrate-Insulin Model of Obesity: Beyond “Calories In, Calories Out”. JAMA Intern. Med. 2018, 178, 1098–1103. [Google Scholar] [CrossRef] [PubMed]
  43. Cornier, M.-A.; Grunwald, G.K.; Johnson, S.L.; Bessesen, D.H. Effects of short-term overfeeding on hunger, satiety, and energy intake in thin and reduced-obese individuals. Appetite 2004, 43, 253–259. [Google Scholar] [CrossRef] [PubMed]
  44. Sama, S.; Jain, G.; Kant, R.; Bhadoria, A.S.; Naithani, M.; Kumar, A. Quantifying the Homeostatic Model Assessment of Insulin Resistance to Predict Mortality in Multi-organ Dysfunction Syndrome. Indian J. Crit. Care Med. 2021, 25, 1364–1369. [Google Scholar] [CrossRef]
  45. Wang, B.-S.; Wang, X.-J.; Gong, L.-K. The Construction of a Williams Design and Randomization in Cross-Over Clinical Trials Using SAS. J. Stat. Softw. Code Snippets 2009, 29, 1–10. [Google Scholar] [CrossRef]
  46. Purcell, S.A.; Legget, K.T.; Halliday, T.M.; Pan, Z.; Creasy, S.A.; Blankenship, J.M.; Hild, A.; Tregellas, J.R.; Melanson, E.L.; Cornier, M.A. Appetitive and Metabolic Responses to an Exercise versus Dietary Intervention in Adults with Obesity. Transl. J. Am. Coll. Sports Med. 2022, 7, e000211. [Google Scholar] [CrossRef] [PubMed]
  47. Sayer, R.D.; Peters, J.C.; Pan, Z.; Wyatt, H.R.; Hill, J.O. Hunger, Food Cravings, and Diet Satisfaction are Related to Changes in Body Weight during a 6-Month Behavioral Weight Loss Intervention: The Beef WISE Study. Nutrients 2018, 10, 700. [Google Scholar] [CrossRef] [PubMed]
  48. Wu, Y.; Ding, Y.; Tanaka, Y.; Zhang, W. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int. J. Med. Sci. 2014, 11, 1185–1200. [Google Scholar] [CrossRef] [PubMed]
  49. Horner, K.M.; Byrne, N.M.; King, N.A. Reproducibility of subjective appetite ratings and ad libitum test meal energy intake in overweight and obese males. Appetite 2014, 81, 116–122. [Google Scholar] [CrossRef]
  50. Rolls, B.J. Dietary energy density: Applying behavioural science to weight management. Nutr. Bull. 2017, 42, 246–253. [Google Scholar] [CrossRef]
  51. Rolls, B.J. The relationship between dietary energy density and energy intake. Physiol. Behav. 2009, 97, 609–615. [Google Scholar] [CrossRef]
  52. Bell, E.A.; Castellanos, V.H.; Pelkman, C.L.; Thorwart, M.L.; Rolls, B.J. Energy density of foods affects energy intake in normal-weight women. Am. J. Clin. Nutr. 1998, 67, 412–420. [Google Scholar] [CrossRef] [PubMed]
  53. Gray, R.W.; French, S.J.; Robinson, T.M.; Yeomans, M.R. Dissociation of the effects of preload volume and energy content on subjective appetite and food intake. Physiol. Behav. 2002, 76, 57–64. [Google Scholar] [CrossRef] [PubMed]
  54. Bell, E.A.; Rolls, B.J. Energy density of foods affects energy intake across multiple levels of fat content in lean and obese women. Am. J. Clin. Nutr. 2001, 73, 1010–1018. [Google Scholar] [CrossRef]
  55. Cornier, M.A.; Salzberg, A.K.; Endly, D.C.; Bessesen, D.H.; Rojas, D.C.; Tregellas, J.R. The effects of overfeeding on the neuronal response to visual food cues in thin and reduced-obese individuals. PLoS ONE 2009, 4, e6310. [Google Scholar] [CrossRef]
  56. Cornier, M.A.; Von Kaenel, S.S.; Bessesen, D.H.; Tregellas, J.R. Effects of overfeeding on the neuronal response to visual food cues. Am. J. Clin. Nutr. 2007, 86, 965–971. [Google Scholar] [CrossRef]
  57. Schmidt, J.B.; Gregersen, N.T.; Pedersen, S.D.; Arentoft, J.L.; Ritz, C.; Schwartz, T.W.; Holst, J.J.; Astrup, A.; Sjödin, A. Effects of PYY3–36 and GLP-1 on energy intake, energy expenditure, and appetite in overweight men. Am. J. Physiol.-Endocrinol. Metab. 2014, 306, E1248–E1256. [Google Scholar] [CrossRef] [PubMed]
  58. Fiszman, S.; Tarrega, A. Expectations of food satiation and satiety reviewed with special focus on food properties. Food Funct. 2017, 8, 2686–2697. [Google Scholar] [CrossRef] [PubMed]
  59. Rock, C.L.; Flatt, S.W.; Barkai, H.S.; Pakiz, B.; Heath, D.D. A walnut-containing meal had similar effects on early satiety, CCK, and PYY, but attenuated the postprandial GLP-1 and insulin response compared to a nut-free control meal. Appetite 2017, 117, 51–57. [Google Scholar] [CrossRef]
  60. Atkinson, F.S.; Brand-Miller, J.C.; Foster-Powell, K.; Buyken, A.E.; Goletzke, J. International tables of glycemic index and glycemic load values 2021: A systematic review. Am. J. Clin. Nutr. 2021, 114, 1625–1632. [Google Scholar] [CrossRef]
  61. Kim, D. Chapter 14—Glycemic index. In Obesity; Mehrzad, R., Ed.; Elsevier: Amsterdam, The Netherlands, 2020; pp. 183–189. [Google Scholar]
  62. Willett, W.; Manson, J.; Liu, S. Glycemic index, glycemic load, and risk of type 2 diabetes1,2,3. Am. J. Clin. Nutr. 2002, 76, 274S–280S. [Google Scholar] [CrossRef]
  63. Laws, A.; Hoen, H.M.; Selby, J.V.; Saad, M.F.; Haffner, S.M.; Howard, B.V. Differences in Insulin Suppression of Free Fatty Acid Levels by Gender and Glucose Tolerance Status. Arterioscler. Thromb. Vasc. Biol. 1997, 17, 64–71. [Google Scholar] [CrossRef]
  64. Campbell, P.J.; Carlson, M.G.; Hill, J.O.; Nurjhan, N. Regulation of free fatty acid metabolism by insulin in humans: Role of lipolysis and reesterification. Am. J. Physiol.-Endocrinol. Metab. 2006, 263, E1063–E1069. [Google Scholar] [CrossRef]
  65. Samson, C.E.; Galia, A.L.; Llave, K.I.; Zacarias, M.B.; Mercado-Asis, L.B. Postprandial Peaking and Plateauing of Triglycerides and VLDL in Patients with Underlying Cardiovascular Diseases Despite Treatment. Int. J. Endocrinol. Metab. 2012, 10, 587–593. [Google Scholar] [CrossRef]
  66. Cummings, D.E.; Purnell, J.Q.; Frayo, R.S.; Schmidova, K.; Wisse, B.E.; Weigle, D.S. A preprandial rise in plasma ghrelin levels suggests a role in meal initiation in humans. Diabetes 2001, 50, 1714–1719. [Google Scholar] [CrossRef]
  67. Tschöp, M.; Wawarta, R.; Riepl, R.L.; Friedrich, S.; Bidlingmaier, M.; Landgraf, R.; Folwaczny, C. Post-prandial decrease of circulating human ghrelin levels. J. Endocrinol. Investig. 2001, 24, Rc19–Rc21. [Google Scholar] [CrossRef]
  68. Monteleone, P.; Bencivenga, R.; Longobardi, N.; Serritella, C.; Maj, M. Differential responses of circulating ghrelin to high-fat or high-carbohydrate meal in healthy women. J. Clin. Endocrinol. Metab. 2003, 88, 5510–5514. [Google Scholar] [CrossRef]
  69. Thomas, E.A.; Bechtell, J.L.; Vestal, B.E.; Johnson, S.L.; Bessesen, D.H.; Tregellas, J.R.; Cornier, M.A. Eating-related behaviors and appetite during energy imbalance in obese-prone and obese-resistant individuals. Appetite 2013, 65, 96–102. [Google Scholar] [CrossRef]
  70. Müller, T.D.; Nogueiras, R.; Andermann, M.L.; Andrews, Z.B.; Anker, S.D.; Argente, J.; Batterham, R.L.; Benoit, S.C.; Bowers, C.Y.; Broglio, F.; et al. Ghrelin. Mol. Metab. 2015, 4, 437–460. [Google Scholar] [CrossRef]
  71. Stanley, S.; Wynne, K.; Bloom, S. Gastrointestinal satiety signals III. Glucagon-like peptide 1, oxyntomodulin, peptide YY, and pancreatic polypeptide. Am. J. Physiol. Gastrointest. Liver Physiol. 2004, 286, G693–G697. [Google Scholar] [CrossRef]
  72. Spreckley, E.; Murphy, K.G. The L-Cell in Nutritional Sensing and the Regulation of Appetite. Front. Nutr. 2015, 2, 23. [Google Scholar] [CrossRef]
  73. Cooper, J.A. Factors affecting circulating levels of peptide YY in humans: A comprehensive review. Nutr. Res. Rev. 2014, 27, 186–197. [Google Scholar] [CrossRef]
  74. Helou, N.; Obeid, O.; Azar, S.T.; Hwalla, N. Variation of postprandial PYY3–36Response following ingestion of differing macronutrient meals in obese females. Ann. Nutr. Metab. 2008, 52, 188–195. [Google Scholar] [CrossRef]
  75. Essah, P.A.; Levy, J.R.; Sistrun, S.N.; Kelly, S.M.; Nestler, J.E. Effect of macronutrient composition on postprandial peptide YY levels. J. Clin. Endocrinol. Metab. 2007, 92, 4052–4055. [Google Scholar] [CrossRef]
  76. Brubaker, P.L. The glucagon-like peptides: Pleiotropic regulators of nutrient homeostasis. Ann. N. Y. Acad. Sci. 2006, 1070, 10–26. [Google Scholar] [CrossRef]
  77. Baggio, L.L.; Drucker, D.J. Biology of Incretins: GLP-1 and GIP. Gastroenterology 2007, 132, 2131–2157. [Google Scholar] [CrossRef]
  78. Calcagno, M.; Kahleova, H.; Alwarith, J.; Burgess, N.N.; Flores, R.A.; Busta, M.L.; Barnard, N.D. The Thermic Effect of Food: A Review. J. Am. Coll. Nutr. 2019, 38, 547–551. [Google Scholar] [CrossRef]
  79. Guarneiri, L.L.; Paton, C.M.; Cooper, J.A. Pecan-enriched diets increase energy expenditure and fat oxidation in adults at-risk for cardiovascular disease in a randomised, controlled trial. J. Hum. Nutr. Diet. 2022, 35, 774–785. [Google Scholar] [CrossRef]
  80. Harris, P.A.; Taylor, R.; Thielke, R.; Payne, J.; Gonzalez, N.; Conde, J.G. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 2009, 42, 377–381. [Google Scholar] [CrossRef]
Figure 1. Consort Diagram.
Figure 1. Consort Diagram.
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Figure 2. Nutritional composition of self-selected lunch. (A) Energy consumed (kcal); (B) weight of food consumed (g); (C) protein consumed (g); (D) carbohydrate consumed (g); (E) fat consumed (g); (F) fiber consumed (g).
Figure 2. Nutritional composition of self-selected lunch. (A) Energy consumed (kcal); (B) weight of food consumed (g); (C) protein consumed (g); (D) carbohydrate consumed (g); (E) fat consumed (g); (F) fiber consumed (g).
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Figure 3. Plasma glucose (mg/dL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure 3. Plasma glucose (mg/dL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
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Figure 4. Serum insulin (μU/mL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure 4. Serum insulin (μU/mL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
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Figure 5. Serum free fatty acids (μmol/L) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure 5. Serum free fatty acids (μmol/L) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
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Figure 6. Plasma triglycerides (mg/dL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure 6. Plasma triglycerides (mg/dL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
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Figure 7. Plasma ghrelin (pg/mL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure 7. Plasma ghrelin (pg/mL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
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Figure 8. Plasma Peptide YY (pg/mL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure 8. Plasma Peptide YY (pg/mL) response to meals. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
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Figure 9. Plasma GLP-1 (pmol/L) response to meal. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
Figure 9. Plasma GLP-1 (pmol/L) response to meal. (A) Before and after breakfast; (B) before and after snack; (C) before and after lunch.
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Figure 10. Resting and post-snack energy expenditure (REE, kcal/d), and respiratory quotient (RQ). (A) REE, before breakfast and after snack; (B) RQ, before breakfast and after snack.
Figure 10. Resting and post-snack energy expenditure (REE, kcal/d), and respiratory quotient (RQ). (A) REE, before breakfast and after snack; (B) RQ, before breakfast and after snack.
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Table 1. Test snack, meal feeding, and outcomes assessment schedule.
Table 1. Test snack, meal feeding, and outcomes assessment schedule.
Time (min)−300154060901201540609012015406090120
Meal B’fast Snack Lunch
Glucose X X XXXX XXXX
Insulin X X XXXX XXXX
FFA X X XXXX XXXX
TG X X XXXX XXXX
Leptin X
Ghrelin, PYY, GLP1 X X XXXX XXXX
Appetite ratings XXXXXXXXXXXXXXXX
CalorimetryX X
Table 2. Participant characteristics.
Table 2. Participant characteristics.
Characteristic(N = 20)
Sex n, (%)Female 14
Male 6
Age, mean (SD 1, range)
Age, median
35.8 (8.6; 24–51)
38.5
Ethnicity n, (%)Hispanic/Latino 5 (25)
Non-Hispanic/Latino 15 (75)
Race n, (%)White 13 (65)
Black or AA 2 (10)
Asian 3 (15)
Other 2 (10)
Height (cm) mean (SD)165.0 (9.3)
Body weight (kg) mean (SD)84.7 (15.9)
BMI 2 (kg/m2) mean (SD, range)
BMI median
30.9 (3.3, 27.2–39.2)
29.8
Leptin (ng/mL) mean (SD); Visit 1;
Visit 2
37.4 (27.5)
34.9 (22.3)
Glucose (mg/dL) mean (SD); Visit 1
Visit 2
85.8 (6.6)
87.3 (12.7)
Insulin (µU/mL) mean (SD); Visit 1
Visit 2
7.9 (6.0)
6.9 (5.3)
HOMA-IR mean (SD); Visit 1
Visit 2
1.7 (1.4)
1.6 (1.4)
FFA (µmol/L) mean (SD); Visit 1
Visit 2
443.0 (191.0)
470.8 (161.8)
Triglycerides (mg/dL) mean (SD); Visit 1,
Visit 2
143.9 (170.2)
133.9 (118.8)
Ghrelin (pg/mL) mean (SD); Visit 1
Visit 2
697.7 (289.2)
694.7 (319.0)
Peptide YY (pg/mL) mean (SD); Visit 1,
Visit 2
105.9 (33.1)
98.5 (28.8)
GLP-1 (pmol/L) mean (SD); Visit 1
Visit 2
4.6 (4.3)
8.1 (19.7)
1 SD, standard deviation; 2 BMI, body mass index (kg/m2).
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Peters, J.C.; Breen, J.A.; Pan, Z.; Nicklas, J.; Cornier, M.-A. A Randomized, Crossover Trial Assessing Appetite, Energy Metabolism, Blood Biomarkers, and Ad Libitum Food Intake Responses to a Mid-Morning Pecan Snack vs. an Equicaloric High-Carbohydrate Snack in Healthy Volunteers with Overweight/Obesity. Nutrients 2024, 16, 2084. https://doi.org/10.3390/nu16132084

AMA Style

Peters JC, Breen JA, Pan Z, Nicklas J, Cornier M-A. A Randomized, Crossover Trial Assessing Appetite, Energy Metabolism, Blood Biomarkers, and Ad Libitum Food Intake Responses to a Mid-Morning Pecan Snack vs. an Equicaloric High-Carbohydrate Snack in Healthy Volunteers with Overweight/Obesity. Nutrients. 2024; 16(13):2084. https://doi.org/10.3390/nu16132084

Chicago/Turabian Style

Peters, John C., Jeanne Anne Breen, Zhaoxing Pan, Jacinda Nicklas, and Marc-Andre Cornier. 2024. "A Randomized, Crossover Trial Assessing Appetite, Energy Metabolism, Blood Biomarkers, and Ad Libitum Food Intake Responses to a Mid-Morning Pecan Snack vs. an Equicaloric High-Carbohydrate Snack in Healthy Volunteers with Overweight/Obesity" Nutrients 16, no. 13: 2084. https://doi.org/10.3390/nu16132084

APA Style

Peters, J. C., Breen, J. A., Pan, Z., Nicklas, J., & Cornier, M. -A. (2024). A Randomized, Crossover Trial Assessing Appetite, Energy Metabolism, Blood Biomarkers, and Ad Libitum Food Intake Responses to a Mid-Morning Pecan Snack vs. an Equicaloric High-Carbohydrate Snack in Healthy Volunteers with Overweight/Obesity. Nutrients, 16(13), 2084. https://doi.org/10.3390/nu16132084

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