Does basal metabolic rate drive eating rate?

Seasonal variation of serum potassium in hemodialysis patients: myth or reality? A narrative review of literature

Research has shown that patients undergoing hemodialysis experience seasonal variations in their serum potassium levels. There was inconsistent seasonal fluctuation in serum potassium levels among the hemodialysis population across different locations. In the form of narrative review for the first time, the article discusses the seasonal changes of serum potassium in this population and its potential reasons, this article demonstrates that it is primarily attributable to seasonal dietary potassium intake. However, existing studies have not quantified seasonal dietary potassium intake, so the results are still speculative. Furthermore, future research ought to further expound upon the clinical implications of seasonal variations in serum potassium levels among dialysis patients, as well as other influencing mechanisms such as the pathophysiological causes of these seasonal changes, particularly those pertaining to dietary, geographical, and regional factors. These findings contribute to a more thorough interpretation of laboratory results in hemodialysis patients and provide important guidance for their individualized dietary management.

Food oral processing and eating behavior from infancy to childhood: evidence on the role of food texture in the development of healthy eating behavior

Eating behaviors develop in early life and refine during childhood, shaping long-term food choice and dietary habits, which underpin optimum growth and health. The development of Food Oral Processing (FOP) is of major importance in the establishment of eating behaviors at two scale levels: for the initial acceptance of food texture and for the longer-term development of eating behaviors associated to food intake. To date, both processes have been studied as independent topics and the current review proposes a parallel vision on their development from the onset of complementary feeding to later childhood. Individual factors affecting these FOP-related behaviors as they relate to food texture acceptance are discussed, alongside examples of interventions aiming at modifying them. Opportunity to better consider food textures when designing foods for children is addressed. Altogether, the review demonstrates the critical role of food texture in the development of a child's FOP skills, eating habits, and dietary patterns. These scientific knowledges need to be considered for the development of healthier eating behavior. We identify research gaps that need to be addressed and highlight the need to design foods that can support the development of healthy oral processing and eating behaviors among infants and children.

Causal Effects of Basal Metabolic Rate on Cardiovascular Disease: A Bidirectional Mendelian Randomization Study

BACKGROUND

Despite the health effects of basal metabolic rate (BMR), the causal effect of BMR on cardiovascular diseases (CVDs) remains undetermined. To elucidate the causal nature, Mendelian randomization (MR) analyses were performed.

METHODS AND RESULTS

Summary genome-wide association statistics regarding BMR and 5 CVDs were obtained from European databases. A 2-sample bidirectional MR was performed to assess the causal association between BMR and CVDs. The causal effects were estimated using inverse variance weighting. Simultaneously, multiple sensitivity analyses were performed to validate the robustness and reliability of the results. Our results indicated that genetically predicted BMR was significantly positively associated with the risk of heart failure (odds ratio, 1.53 [95% CI, 1.39-1.67]; P<0.001), atrial fibrillation and flutter (odds ratio, 2.12 [95% CI, 1.87-2.40]; P<0.001), and aortic aneurysm (odds ratio, 1.64 [95% CI, 1.41-1.92]; P<0.001). Genetically predicted BMR may not be causally associated with coronary artery disease and ischemic stroke risk. Furthermore, a significant causal effect of CVDs on BMR was not found in the reverse MR analysis. Multivariable MR was applied to further assess the direct effect of BMR on CVDs. Multivariable MR indicated that a high level of BMR still increased the risk of heart failure and atrial fibrillation and flutter after adjustment independent of possible confounders. However, the P value of aortic aneurysm was not significant.

CONCLUSIONS

The present study provides robust evidence that genetically predicted BMR is independently causally associated with heart failure and atrial fibrillation and flutter but not vice versa. These findings have implications for the prevention and treatment of CVDs in clinical practice.

The Fully Understanding Eating and Lifestyle Behaviors (FUEL) trial: Protocol for a cohort study harnessing digital health tools to phenotype dietary non-adherence behaviors during lifestyle intervention

Objective

Lifestyle intervention can produce clinically significant weight loss and reduced disease risk/severity for many individuals with overweight/obesity. Dietary lapses, instances of non-adherence to the recommended dietary goal(s) in lifestyle intervention, are associated with less weight loss and higher energy intake. There are distinct "types" of dietary lapse (e.g., eating an off-plan food, eating a larger portion), and behavioral, psychosocial, and contextual mechanisms may differ across dietary lapse types. Some lapse types also appear to impact weight more than others. Elucidating clear lapse types thus has potential for understanding and improving adherence to lifestyle intervention.

Methods

This 18-month observational cohort study will use real-time digital assessment tools within a multi-level factor analysis framework to uncover "lapse phenotypes" and understand their impact on clinical outcomes. Adults with overweight/obesity (n = 150) will participate in a 12-month online lifestyle intervention and 6-month weight loss maintenance period. Participants will complete 14-day lapse phenotyping assessment periods at baseline, 3, 6, 12, and 18 months in which smartphone surveys, wearable devices, and geolocation will assess dietary lapses and relevant phenotyping characteristics. Energy intake (via 24-h dietary recall) and weight will be collected at each assessment period.

Results

This trial is ongoing; data collection began on 31 October 2022 and is scheduled to complete by February 2027.

Conclusion

Results will inform novel precision tools to improve dietary adherence in lifestyle intervention, and support updated theoretical models of adherence behavior. Additionally, these phenotyping methods can likely be leveraged to better understand non-adherence to other health behavior interventions.

Trial Registration

This study was prospectively registered https://clinicaltrials.gov/study/NCT05562427.

Factors associated with eating rate: a systematic review and narrative synthesis informed by socio-ecological model

Accumulating evidence shows associations between rapid eating and overweight. Modifying eating rate might be a potential weight management strategy without imposing additional dietary restrictions. A comprehensive understanding of factors associated with eating speed will help with designing effective interventions. The aim of this review was to synthesise the current state of knowledge on the factors associated with eating rate. The socio-ecological model (SEM) was utilised to scaffold the identified factors. A comprehensive literature search of eleven databases was conducted to identify factors associated with eating rate. The 104 studies that met the inclusion criteria were heterogeneous in design and methods of eating rate measurement. We identified thirty-nine factors that were independently linked to eating speed and mapped them onto the individual, social and environmental levels of the SEM. The majority of the reported factors pertained to the individual characteristics (n = 20) including demographics, cognitive/psychological factors and habitual food oral processing behaviours. Social factors (n = 11) included eating companions, social and cultural norms, and family structure. Environmental factors (n = 8) included food texture and presentation, methods of consumption or background sounds. Measures of body weight, food form and characteristics, food oral processing behaviours and gender, age and ethnicity were the most researched and consistent factors associated with eating rate. A number of other novel and underresearched factors emerged, but these require replication and further research. We highlight directions for further research in this space and potential evidence-based candidates for interventions targeting eating rate.

Eating rate and bite size were related to food intake across meals varying in portion size: A randomized crossover trial in adults

Serving larger portions leads to increased food intake, but behavioral factors that influence the magnitude of this portion size effect have not been well characterized. We investigated whether measures of eating microstructure such as eating rate and bite size moderated the portion size effect. We also explored how sensory-specific satiety (SSS; the relative hedonic decline of a food as it is eaten) was affected by eating microstructure and larger portions. In a randomized crossover design, 44 adults aged 18-68 y (66% women; 46% with overweight and obesity) ate lunch in the laboratory once a week for 4 weeks. The meal consisted of pasta that was varied in portion size (400, 500, 600, or 700 g) and 700 g of water. Meals were video-recorded to assess bite count and meal duration, which were used to calculate mean eating rate (g/min) and mean bite size (g/bite). At each meal participants also completed an assessment of SSS. The results showed that as larger portions were served, meal intake increased in a curvilinear manner (p < 0.0001). Measures of eating microstructure did not moderate the portion size effect but were related to intake across all portions; faster eating rate, larger bite size, higher bite count, and longer meal duration were associated with greater consumption at all meals (all p < 0.0001). SSS was not influenced by any measure of eating microstructure or by portion size (all p > 0.10). In summary, the portion size effect was not moderated by eating microstructure, but relatively faster eating rates and larger bite sizes at meals, along with large portions, combined to increase food intake.

Impact of Individual Differences in Eating Rate on Oral Processing, Bolus Properties and Post-Meal Glucose Responses

PURPOSE

Modifying food texture has been shown to influence oral processing behaviour. We explored the impact of food texture on oral processing, bolus formation and post-prandial glucose responses (PPG) among fast and slow eaters.

METHODS

Male participants (N=39) were split into fast or slow eaters based on natural differences in eating rate when consuming two carbohydrate-equivalent test-meals differing in texture (white rice and rice cake). PPG and satiety responses were compared for fast and slow eaters over 120-min for each test-meal. Each groups test-meal PPG was compared for bolus and saliva properties at the point of swallow.

RESULTS

White rice displayed lower instrumental hardness, chewiness and Young's modulus and was perceived less chewy, springy and sticky than rice cake. Slow eaters (n=24, white rice: 13.3 g/min; rice cake: 15.1 g/min) required an average 42% more chews per bite (p < 0.001), had 60% longer oral exposure time (OET), and consumed both test-meals (p < 0.001) at half the eating rate of fast eaters (n=15). Slow eaters had higher PPG following the rice cake meal at 15 (p = 0.046) and 45 min (p = 0.034) than fast eaters. A longer OET was a positive predictor of early PPG at 30-min after the white rice meal (β = 0.178, p = 0.041) and saliva uptake was a significant predictor (β = 0.458, p = 0.045) of PPG for slow eaters when consuming rice cake. Increasing food hardness and stiffness (Young's modulus) had a greater impact on eating rate for slow eaters than fast eaters.

CONCLUSIONS

Eating rate, oral exposure time and bolus saliva uptake were the predictors of an individual's post-prandial glycaemic response amongst slow eaters. Increasing the number of chews per bite with a longer oral exposure time increased saliva uptake in the bolus at the moment of swallowing and enhanced temporal changes in PPG, leading to greater glycaemic peaks in rice cake meal. Differences in eating rate between slow and fast eaters when consuming rice cake meal influenced temporal changes in PPG but not total PPG, and bolus properties did not differ between eating rate groups.

Fast Eating Is Associated with Increased BMI among High-School Students

Fast self-reported eating rate (SRER) has been associated with increased adiposity in children and adults. No studies have been conducted among high-school students, and SRER has not been validated vs. objective eating rate (OBER) in such populations. The objectives were to investigate (among high-school student populations) the association between OBER and BMI z-scores (BMIz), the validity of SRER vs. OBER, and potential differences in BMIz between SRER categories. Three studies were conducted. Study 1 included 116 Swedish students (mean ± SD age: 16.5 ± 0.8, 59% females) who were eating school lunch. Food intake and meal duration were objectively recorded, and OBER was calculated. Additionally, students provided SRER. Study 2 included students (n = 50, mean ± SD age: 16.7 ± 0.6, 58% females) from Study 1 who ate another objectively recorded school lunch. Study 3 included 1832 high-school students (mean ± SD age: 15.8 ± 0.9, 51% females) from Sweden (n = 748) and Greece (n = 1084) who provided SRER. In Study 1, students with BMIz ≥ 0 had faster OBER vs. students with BMIz < 0 (mean difference: +7.7 g/min or +27%, p = 0.012), while students with fast SRER had higher OBER vs. students with slow SRER (mean difference: +13.7 g/min or +56%, p = 0.001). However, there was “minimal” agreement between SRER and OBER categories (κ = 0.31, p < 0.001). In Study 2, OBER during lunch 1 had a “large” correlation with OBER during lunch 2 (r = 0.75, p < 0.001). In Study 3, fast SRER students had higher BMIz vs. slow SRER students (mean difference: 0.37, p < 0.001). Similar observations were found among both Swedish and Greek students. For the first time in high-school students, we confirm the association between fast eating and increased adiposity. Our validation analysis suggests that SRER could be used as a proxy for OBER in studies with large sample sizes on a group level. With smaller samples, OBER should be used instead. To assess eating rate on an individual level, OBER can be used while SRER should be avoided.

[Effect of eating speed modification techniques and strategies on food or energy intake: a systematic review and meta-analysis]

Introduction

Scientific evidence indicates that eating slowly reduces food and energy intake. However, few investigations have studied the effect of techniques and strategies that modify eating speed on intake. The objective of this study is to analyze the relationship between these techniques and food and/or energy intake. Therefore, a systematic review of 15 human studies and a meta-analysis of 7 studies with 11 experimental and 1 observational manipulations were carried out. Only the results of two conditions were included, "slow" vs. "fast" of eating speed and ingestion. The estimation of the effect was expressed in OR with a 95 % CI under a random effects model, and heterogeneity was assessed with I2. Publication bias was also assessed with a funnel plot and Egger's linear regression test. The results indicate that eating slowly is a protective factor (OR = 0.73) from excessive intake. Additionally, eating small bites with a small spoon (OR = 0.315), serving food preparations on separate plates (OR = 0.860 and OR = 0.831), using a vibrotactile feedback fork (OR = 0.847), and eating hard-textured foods (OR = 0.831) are the techniques and strategies that modify eating speed and decrease food or energy intake. The present study confirms the premise that eating slowly can reduce excessive food and energy intake.

Combined Impact of a Faster Self-Reported Eating Rate and Higher Dietary Energy Intake Rate on Energy Intake and Adiposity

Eating more quickly and consuming foods with a higher energy-intake-rate (EIR: kcal/min) is associated with greater energy intake and adiposity. However, it remains unclear whether individuals who eat more quickly are more likely to consume foods with higher EIR. We investigated the overlap between self-reported eating rate (SRER) and the consumption of higher EIR foods, and their combined impact on daily energy intake and adiposity in a population-based Asian cohort (n = 7011; 21-75y). Food consumption was assessed using a validated Food Frequency Questionnaire. Moderated regression with simple slope analysis was conducted to evaluate whether SRER modified the association between dietary EIR and total dietary energy intakes. Faster eaters consumed a significantly higher proportion of energy from higher EIR foods among overweight individuals, but not among normal-weight individuals. Associations between dietary EIR and total energy intake were stronger among medium (β = 15.04, 95%CI: 13.00-17.08) and fast (β = 15.69, 95%CI: 12.61-18.78) eaters, compared with slower eaters (β = 9.89, 95%CI: 5.11-14.67; p-interaction = 0.032). Higher dietary EIR also tended to be more strongly associated with BMI in fast eaters (β = 0.025, 95%CI: 0.011-0.038) than in slow eaters (β = 0.017, 95%CI: -0.007-0.040). These findings suggest that the combination of eating more quickly and selecting a greater proportion of energy from higher EIR foods (i.e., softly textured, energy dense), promoted higher dietary energy intakes and adiposity.

Effects of Sweet-Liking on Body Composition Depend on Age and Lifestyle: A Challenge to the Simple Sweet-Liking-Obesity Hypothesis

Taste hedonics drive food choices, and food choices affect weight maintenance. Despite this, the idea that hyper-palatability of sweet foods is linked to obesity development has been controversial for decades. Here, we investigate whether interpersonal differences in sweet-liking are related to body composition. Healthy adults aged 18–34 years from the UK (n = 148) and the US (n = 126) completed laboratory-based sensory tests (sucrose taste tests) and anthropometric measures (body mass index; BMI, body fat; fat-free mass; FFM, waist/hips circumferences). Habitual beverage intake and lifestyle and behavioural characteristics were also assessed. Using hierarchical cluster analysis, we classified participants into three phenotypes: sweet liker (SL), sweet disliker (SD), and inverted-U (liking for moderate sweetness). Being a SD was linked to higher body fat among those younger than 21 years old, while in the older group, SLs had the highest BMI and FFM; age groups reflected different levels of exposure to the obesogenic environment. FFM emerged as a better predictor of sweet-liking than BMI and body fat. In the older group, sweetened beverage intake partially explained the phenotype–anthropometry associations. Collectively, our findings implicate underlying energy needs as an explanation for the variation in sweet-liking; the moderating roles of age and obesogenic environment require additional consideration.

How Important Is Eating Rate in the Physiological Response to Food Intake, Control of Body Weight, and Glycemia?

The link between eating rate and energy intake has long been a matter of extensive research. A better understanding of the effect of food intake speed on body weight and glycemia in the long term could serve as a means to prevent weight gain and/or dysglycemia. Whether a fast eating rate plays an important role in increased energy intake and body weight depends on various factors related to the studied food such as texture, viscosity and taste, but seems to be also influenced by the habitual characteristics of the studied subjects as well. Hunger and satiety quantified via test meals in acute experiments with subsequent energy intake measurements and their association with anorexigenic and orexigenic regulating peptides provide further insight to the complicated pathogenesis of obesity. The present review examines data from the abundant literature on the subject of eating rate, and highlights the main findings in people with normal weight, obesity, and type 2 diabetes, with the aim of clarifying the association between rate of food intake and hunger, satiety, glycemia, and energy intake in the short and long term.

Relating oral physiology and anatomy of consumers varying in age, gender and ethnicity to food oral processing behavior

The aim of this study was to link parameters describing oral physiology and anatomy of consumers varying in age, gender and ethnicity to food oral processing behavior. Three groups of healthy consumers were compared: Dutch, Caucasian adults (18-30 yrs, n =32), Chinese, Asian adults (18-30 yrs, n =32) and Dutch, Caucasian older adults (65-85 yrs, n =32). Mastication performance, salivary flow rate (stimulated and unstimulated) and dental status were quantified to characterize oral physiology. Volume of oral cavity, tongue dimensions, facial anthropometry, height and weight were quantified to characterize anatomy. Oral processing behavior of three solid foods (carrot, cheese and sausage) was quantified by video recordings and eating rate (g/s), average consumption time (s), chews per bite (-) and average bite size (g) were determined. Dutch, Caucasian older adults had smaller volume of oral cavity, lower number of teeth and larger head width compared to Dutch, Caucasian adults. Chinese, Asian adults showed significantly higher mastication performance and larger head width compared to Dutch, Caucasian consumers, while dental status did not significantly differ between groups. Males had significantly larger volumes of oral cavity and larger head height and width compared to females. Dutch, Caucasian adults had a shorter average consumption time (s), less chews per bite and consumed the three foods with higher eating rate (g/s) compared to Dutch, Caucasian older adults. Chinese, Asian adults had a significantly longer average consumption time (s), more chews per bite, smaller average bite size (g) and lower eating rate (g/s) compared to Dutch, Caucasian adults. Twenty-one significant relationships were found between oral physiological and anatomical parameters and oral processing behavior. Body weight resulted in the largest β-values, indicating to be the anatomical parameter of largest influence on oral processing behavior. We conclude that only few oral physiological and anatomical parameters related with food oral processing behavior. We suggest that other factors, including cultural factors contribute to variation in food oral processing behavior between different consumer groups more than saliva flow, volume of oral cavity, mastication performance and dental status.