Appetite Response among Those Susceptible or Resistant to Obesity

Using pre-prandial blood glucose to assess eating in the absence of hunger in free-living individuals

Our ability to understand and intervene on eating in the absence of hunger (EAH) as it occurs in peoples' natural environments is hindered by biased methods that lack ecological validity. One promising indicator of EAH that does not rely on self-report and is easily assessed in free-living individuals is glucose. Here, we hypothesize that elevated pre-prandial blood glucose concentrations (PPBG), which reflect a source of readily-available, short-term energy, are a biological indicator of EAH. This was a 7-day observational study of N = 41, 18-24 year old men and women with BMI < 25 kg/m² (60%) or BMI ≥ 25 kg/m² (40%). We collected data using ecological momentary assessment from people in their natural environments. We defined EAH by self-report (perceived EAH) and by PPBG thresholds using two methods (standardized, PPBG < 85 mg/dl; personalized, PPBG < individual fasting levels). Multilevel modeling was used to analyze the data. N = 963 eating events were reported. There were significantly (p < .05) fewer perceived EAH events (25%) as compared to standardized (62%) and personalized PPBG-defined EAH events (51%). Consistent with published literature, perceived EAH was more likely to occur at a higher PPBG (p < .01), particularly among participants with a BMI ≥ 25 kg/m² (p_int < .01). Additionally, discordance between perceived EAH and PPBG-defined EAH, indicating a perception of hunger at an eating event when PPBS was elevated, was less likely among participants with a BMI < 25 kg/m² vs. those with a BMI ≥ 25 kg/m² (p_int < .01) as well as at snacks vs. meals (p_int < .01). These findings provide preliminary support for using PPBG as a biological indicator of EAH in free-living individuals.

Prediction Equations Overestimate the Energy Requirements More for Obesity-Susceptible Individuals

Predictive equations to estimate resting metabolic rate (RMR) are often used in dietary counseling and by online apps to set energy intake goals for weight loss. It is critical to know whether such equations are appropriate for those susceptible to obesity. We measured RMR by indirect calorimetry after an overnight fast in 26 obesity susceptible (OSI) and 30 obesity resistant (ORI) individuals, identified using a simple 6-item screening tool. Predicted RMR was calculated using the FAO/WHO/UNU (Food and Agricultural Organisation/World Health Organisation/United Nations University), Oxford and Miflin-St Jeor equations. Absolute measured RMR did not differ significantly between OSI versus ORI (6339 vs. 5893 kJ·d⁻¹, p = 0.313). All three prediction equations over-estimated RMR for both OSI and ORI when measured RMR was ≤5000 kJ·d⁻¹. For measured RMR ≤7000 kJ·d⁻¹ there was statistically significant evidence that the equations overestimate RMR to a greater extent for those classified as obesity susceptible with biases ranging between around 10% to nearly 30% depending on the equation. The use of prediction equations may overestimate RMR and energy requirements particularly in those who self-identify as being susceptible to obesity, which has implications for effective weight management.

Exploring the Relationship between Body Composition and Eating Behavior Using the Three Factor Eating Questionnaire (TFEQ) in Young New Zealand Women

Obesity is a leading cause of morbidity and mortality, yet is preventable. This study aimed to investigate associations between body mass index, body fat percentage and obesity-related eating behaviors. Women (n = 116; 18–44 years) were measured for height, weight and body fat using air displacement plethysmography (BodPod). Women completed the validated Three Factor Eating Questionnaire to assess their eating behaviors using Restraint, Disinhibition and Hunger eating factor categories and sub-categories. The eating behavior data were analyzed for associations with body mass index and body fat percentage, and comparisons across body mass index and body fat percentage categories (< vs. ≥25 kg/m²; < vs. ≥30%, respectively). Women had a mean (standard deviation) body mass index of 23.4 (3.5) kg/m², and body fat percentage of 30.5 (7.6)%. Disinhibition was positively associated with both body mass index (p < 0.001) and body fat percentage (p < 0.001). Emotional Disinhibition was positively associated with body fat percentage (p < 0.028). Women with low Restraint and high Disinhibition had significantly higher body mass index and body fat percentage than women with high Restraint and low Disinhibition. Disinhibition seems likely to be an important contributor to obesity. Tailored intervention strategies focused on counteracting Disinhibition should be a key target area for managing weight/fat gain.

Development of an ecological momentary assessment scale for appetite

Background

An understanding of eating behaviors is an important element of health education and treatment in clinical populations. To understand the biopsychosocial profile of eating behaviors in an ecologically valid way, ecological momentary assessment (EMA) is appropriate because its use is able to overcome the recall bias in patient-reported outcomes (PROs). As appetite is a key PRO associated with eating behaviors, this study was done to develop an EMA scale to evaluate the within-individual variation of momentary appetite and uses this scale to discuss the relationships between appetite and various psychological factors.

Methods

Twenty healthy participants (age 23.6 ± 4.2 years old) wore a watch-type computer for a week. Several times a day, including just before and after meals, they recorded their momentary psychological stress, mood states, and ten items related to appetite. In addition, they recorded everything they ate and drank into a personal digital assistant (PDA)-based food diary. Multilevel factor analysis was used to investigate the factor structure of the scale, and the reliability and validity of the scale were also explored.

Results

Multilevel factor analyses found two factors at the within-individual level (hunger/fullness and cravings) and one factor at the between-individual level. Medians for the individually calculated Cronbach’s alphas were 0.89 for hunger/fullness, 0.71 for cravings, and 0.86 for total appetite (the sum of all items). Hunger/fullness, cravings, and total appetite all decreased significantly after meals compared with those before meals, and hunger/fullness, cravings, and total appetite before meals were positively associated with energy intake. There were significant negative associations between both hunger/fullness and total appetite and anxiety and depression as well as between cravings, and depression, anxiety and stress.

Conclusions

The within-individual reliability of the EMA scale to assess momentary appetite was confirmed in most subjects and it was also validated as a useful tool to understand eating behaviors in daily settings. Further refinement of the scale is necessary and further investigations need to be conducted, particularly on clinical populations.