How much may I eat? Calorie estimates based upon energy expenditure prediction equations

Quantification of the effect of GLP-1R agonists on body weight using in vitro efficacy information: An extension of the Hall body composition model

Obesity has become a major public health concern worldwide. Pharmacological interventions with the glucagon-like peptide-1 receptor agonists (GLP-1RAs) have shown promising results in facilitating weight loss and improving metabolic outcomes in individuals with obesity. Quantifying drug effects of GLP-1RAs on energy intake (EI) and body weight (BW) using a QSP modeling approach can further increase the mechanistic understanding of these effects, and support obesity drug development. An extensive literature-based dataset was created, including data from several diet, liraglutide and semaglutide studies and their effects on BW and related parameters. The Hall body composition model was used to quantify and predict effects on EI. The model was extended with (1) a lifestyle change/placebo effect on EI, (2) a weight loss effect on activity for the studies that included weight management support, and (3) a GLP-1R agonistic effect using in vitro potency efficacy information. The estimated reduction in EI of clinically relevant dosages of semaglutide (2.4 mg) and liraglutide (3.0 mg) was 34.5% and 13.0%, respectively. The model adequately described the resulting change in BW over time. At 20 weeks the change in BW was estimated to be -17% for 2.4 mg semaglutide and -8% for 3 mg liraglutide, respectively. External validation showed the model was able to predict the effect of semaglutide on BW in the STEP 1 study. The GLP-1RA body composition model can be used to quantify and predict the effect of novel GLP-1R agonists on BW and changes in underlying processes using early in vitro efficacy information.

Life expectancy gains from dietary modifications: a comparative modeling study in 7 countries

BACKGROUND

Eating healthier is associated with a range of favorable health outcomes. Our previous model estimated the impact of dietary changes on life expectancy gains but did not consider height, weight, or physical activity.

OBJECTIVES

We aimed to estimate the increase in life expectancy resulting from the transition from typical national dietary patterns to longevity-optimizing dietary changes, more feasible dietary modifications, and optimized vegan dietary changes in China, France, Germany, Iran, Norway, the United Kingdom, and the United States.

METHODS

Our modeling study used data from meta-analyses presenting dose-response relationships between intake of 15 food groups and mortality. Background mortality data were from the Global Burden of Disease Study. We used national food intake data and adjusted for height, weight, and physical activity level.

RESULTS

For 40-y-olds, estimated life expectancy gains ranged from 6.2 y (with uncertainty interval [UI]: 5.7, 7.5 y) for Chinese females to 9.7 y (UI: 8.1, 11.3 y) for United States males following sustained changes from typical country-specific dietary patterns to longevity-optimized dietary changes, and from 5.2 y (UI: 4.0, 6.5 y) for Chinese females to 8.7 y (UI: 7.1, 10.3 y) for United States males following changes to optimized vegan dietary changes.

CONCLUSIONS

A sustained change from country-specific typical dietary pattern patterns to longevity-optimized dietary changes, more feasible dietary changes, or optimized vegan dietary changes are all projected to result in substantial life expectancy gains across ages and countries. These changes included more whole grains, legumes, and nuts and less red/processed meats and sugars and sugar-sweetened beverages. The largest gains from dietary changes would be in the United States.

The comparison of total energy and protein intake relative to estimated requirements in chronic spinal cord injury

In chronic spinal cord injury (SCI), individuals experience dietary inadequacies complicated by an understudied research area. Our objectives were to assess (1) the agreement between methods of estimating energy requirement (EER) and estimated energy intake (EEI) and (2) whether dietary protein intake met SCI-specific protein guidelines. Persons with chronic SCI (n = 43) completed 3-day food records to assess EEI and dietary protein intake. EER was determined with the Long and Institute of Medicine (IOM) methods and the SCI-specific Farkas method. Protein requirements were calculated as 0·8-1·0 g/kg of body weight (BW)/d. Reporting accuracy and bias were calculated and correlated to body composition. Compared with IOM and Long methods (P < 0·05), the SCI-specific method did not overestimate the EEI (P = 0·200). Reporting accuracy and bias were best for SCI-specific (98·9 %, -1·12 %) compared with Long (94·8 %, -5·24 %) and IOM (64·1 %, -35·4 %) methods. BW (r = -0·403), BMI (r = -0·323) and total fat mass (r = -0·346) correlated with the IOM reporting bias (all, P < 0·05). BW correlated with the SCI-specific and Long reporting bias (r = -0·313, P = 0·041). Seven (16 %) participants met BW-specific protein guidelines. The regression of dietary protein intake on BW demonstrated no association between the variables (β = 0·067, P = 0·730). In contrast, for every 1 kg increase in BW, the delta between total and required protein intake decreased by 0·833 g (P = 0·0001). The SCI-specific method for EER had the best agreement with the EEI. Protein intake decreased with increasing BW, contrary to protein requirements for chronic SCI.

Deciphering the relationship between temperature and immunity

Fever is a hallmark symptom of disease across the animal kingdom. Yet, despite the evidence linking temperature fluctuation and immune response, much remains to be discovered about the molecular mechanisms governing these interactions. In patients with rheumatoid arthritis, for instance, it is clinically accepted that joint temperature can predict disease progression. But it was only recently demonstrated that the mitochondria of stimulated T cells can rise to an extreme 50°C, potentially indicating a cellular source of these localized 'fevers'. A challenge to dissecting these mechanisms is a bidirectional interplay between temperature and immunity. Heat shock response is found in virtually all organisms, activating protective pathways when cells are exposed to elevated temperatures. However, the temperature threshold that activates these pathways can vary within the same organism, with human immune cells, in particular, demonstrating differential sensitivity to heat. Such inter-cellular variation may be clinically relevant given the small but significant temperature differences seen between tissues, ages, and sexes. Greater understanding of how such small temperature perturbations mediate immune responses may provide new explanations for persistent questions in disease such as sex disparity in disease prevalence. Notably, the prevalence and severity of many maladies are rising with climate change, suggesting temperature fluctuations can interact with disease on multiple levels. As global temperatures are rising, and our body temperatures are falling, questions regarding temperature-immune interactions are increasingly critical. Here, we review this aspect of environmental interplay to better understand temperature's role in immune variation and subsequent risk of disease.

Decreasing human body temperature in the United States since the industrial revolution

In the US, the normal, oral temperature of adults is, on average, lower than the canonical 37°C established in the 19^th century. We postulated that body temperature has decreased over time. Using measurements from three cohorts—the Union Army Veterans of the Civil War (N = 23,710; measurement years 1860–1940), the National Health and Nutrition Examination Survey I (N = 15,301; 1971–1975), and the Stanford Translational Research Integrated Database Environment (N = 150,280; 2007–2017)—we determined that mean body temperature in men and women, after adjusting for age, height, weight and, in some models date and time of day, has decreased monotonically by 0.03°C per birth decade. A similar decline within the Union Army cohort as between cohorts, makes measurement error an unlikely explanation. This substantive and continuing shift in body temperature—a marker for metabolic rate—provides a framework for understanding changes in human health and longevity over 157 years.

Energy Metabolism and Intermittent Fasting: The Ramadan Perspective

Intermittent fasting (IF) has been gaining popularity as a means of losing weight. The Ramadan fast (RF) is a form of IF practiced by millions of adult Muslims globally for a whole lunar month every year. It entails a major shift from normal eating patterns to exclusive nocturnal eating. RF is a state of intermittent liver glycogen depletion and repletion. The earlier (morning) part of the fasting day is marked by dominance of carbohydrate as the main fuel, but lipid becomes more important towards the afternoon and as the time for breaking the fast at sunset (iftar) gets closer. The practice of observing Ramadan fasting is accompanied by changes in sleeping and activity patterns, as well as circadian rhythms of hormones including cortisol, insulin, leptin, ghrelin, growth hormone, prolactin, sex hormones, and adiponectin. Few studies have investigated energy expenditure in the context of RF including resting metabolic rate (RMR) and total energy expenditure (TEE) and found no significant changes with RF. Changes in activity and sleeping patterns however do occur and are different from non-Ramadan days. Weight changes in the context of Ramadan fast are variable and typically modest with wise inter-individual variation. As well as its direct relevance to many religious observers, understanding intermittent fasting may have implications on weight loss strategies with even broader potential implications. This review examines current knowledge on different aspects of energy balance in RF, as a common model to learn from and also map out strategies for healthier outcomes in such settings.

Ultra-long-term human salt balance studies reveal interrelations between sodium, potassium, and chloride intake and excretion

BACKGROUND

The intake of sodium, chloride, and potassium is considered important to healthy nutrition and cardiovascular disease risk. Estimating the intake of these electrolytes is difficult and usually predicated on urine collections, commonly for 24 h, which are considered the gold standard. We reported on data earlier for sodium but not for potassium or chloride.

OBJECTIVE

We were able to test the value of 24-h urine collections in a unique, ultra-long-term balance study conducted during a simulated trip to Mars.

DESIGN

Four healthy men were observed while ingesting 12 g salt/d, 9 g salt/d, and 6 g salt/d, while their potassium intake was maintained at 4 g/d for 105 d. Six healthy men were studied while ingesting 12 g salt/d, 9 g salt/d, and 6 g salt/d, with a re-exposure of 12 g/d, while their potassium intake was maintained at 4 g/d for 205 d. Food intake and other constituents were recorded every day for each subject. All urine output was collected daily.

RESULTS

Long-term urine recovery rates for all 3 electrolytes were very high. Rather than the expected constant daily excretion related to daily intake, we observed remarkable daily variation in excretion, with a 7-d infradian rhythm at a relatively constant intake. We monitored 24-h aldosterone excretion in these studies and found that aldosterone appeared to be the regulator for all 3 electrolytes. We report Bland-Altman analyses on the value of urine collections to estimate intake.

CONCLUSIONS

A single 24-h urine collection cannot predict sodium, potassium, or chloride intake; thus, multiple collections are necessary. This information is important when assessing electrolyte intake in individuals.

Agreement between 24-hour salt ingestion and sodium excretion in a controlled environment

Accurately collected 24-hour urine collections are presumed to be valid for estimating salt intake in individuals. We performed 2 independent ultralong-term salt balance studies lasting 105 (4 men) and 205 (6 men) days in 10 men simulating a flight to Mars. We controlled dietary intake of all constituents for months at salt intakes of 12, 9, and 6 g/d and collected all urine. The subjects' daily menus consisted of 27 279 individual servings, of which 83.0% were completely consumed, 16.5% completely rejected, and 0.5% incompletely consumed. Urinary recovery of dietary salt was 92% of recorded intake, indicating long-term steady-state sodium balance in both studies. Even at fixed salt intake, 24-hour urine collection for sodium excretion (UNaV) showed infradian rhythmicity. We defined a ±25 mmol deviation from the average difference between recorded sodium intake and UNaV as the prediction interval to accurately classify a 3-g difference in salt intake. Because of the biological variability in UNaV, only every other daily urine sample correctly classified a 3-g difference in salt intake (49%). By increasing the observations to 3 consecutive 24-hour collections and sodium intakes, classification accuracy improved to 75%. Collecting seven 24-hour urines and sodium intake samples improved classification accuracy to 92%. We conclude that single 24-hour urine collections at intakes ranging from 6 to 12 g salt per day were not suitable to detect a 3-g difference in individual salt intake. Repeated measurements of 24-hour UNaV improve precision. This knowledge could be relevant to patient care and the conduct of intervention trials.

Meal-based enhancement of protein quality and quantity during weight loss in obese older adults with mobility limitations: rationale and design for the MEASUR-UP trial

Obese older adults with even modest functional limitations are at a disadvantage for maintaining their independence into late life. However, there is no established intervention for obesity in older individuals. The Measuring Eating, Activity, and Strength: Understanding the Response - Using Protein (MEASUR-UP) trial is a randomized controlled pilot study of obese women and men aged ≥60 years with mild to moderate functional impairments. Changes in body composition (lean and fat mass) and function (Short Physical Performance Battery) in an enhanced protein weight reduction (Protein) arm will be compared to those in a traditional weight loss (Control) arm. The Protein intervention is based on evidence that older adults achieve optimal rates of muscle protein synthesis when consuming about 25-30 g of high quality protein per meal; these participants will consume ~30 g of animal protein at each meal via a combination of provided protein (beef) servings and diet counseling. This trial will provide information on the feasibility and efficacy of enhancing protein quantity and quality in the context of a weight reduction regimen and determine the impact of this intervention on body weight, functional status, and lean muscle mass. We hypothesize that the enhancement of protein quantity and quality in the Protein arm will result in better outcomes for function and/or lean muscle mass than in the Control arm. Ultimately, we hope our findings will help identify a safe weight loss approach that can delay or prevent late life disability by changing the trajectory of age-associated functional impairment associated with obesity.

Validation of a novel protocol for calculating estimated energy requirements and average daily physical activity ratio for the US population: 2005-2006

OBJECTIVE

To validate the PAR protocol, a novel method for calculating population-level estimated energy requirements (EERs) and average physical activity ratio (APAR), in a nationally representative sample of US adults.

METHODS

Estimates of EER and APAR values were calculated via a factorial equation from a nationally representative sample of 2597 adults aged 20 and 74 years (US National Health and Nutrition Examination Survey; data collected between January 1, 2005, and December 31, 2006). Validation of the PAR protocol-derived EER (EER(PAR)) values was performed via comparison with values from the Institute of Medicine EER equations (EER(IOM)).

RESULTS

The correlation between EER(PAR) and EER(IOM) was high (0.98; P<.001). The difference between EER(PAR) and EER(IOM) values ranged from 40 kcal/d (1.2% higher than EER(IOM)) in obese (body mass index [BMI] ≥30) men to 148 kcal/d (5.7% higher) in obese women. The 2005-2006 EERs for the US population were 2940 kcal/d for men and 2275 kcal/d for women and ranged from 3230 kcal/d in obese (BMI ≥30) men to 2026 kcal/d in normal weight (BMI <25) women. There were significant inverse relationships between APAR and both obesity and age. For men and women, the APAR values were 1.53 and 1.52, respectively. Obese men and women had lower APAR values than normal weight individuals (P¼.023 and P¼.015, respectively) [corrected], and younger individuals had higher APAR values than older individuals (P<.001).

CONCLUSION

The PAR protocol is an accurate method for deriving nationally representative estimates of EER and APAR values. These descriptive data provide novel quantitative baseline values for future investigations into associations of physical activity and health.

The role of sleep duration in the regulation of energy balance: effects on energy intakes and expenditure

Short sleep duration and obesity are common occurrence in today's society. An extensive literature from cross-sectional and longitudinal epidemiological studies shows a relationship between short sleep and prevalence of obesity and weight gain. However, causality cannot be inferred from such studies. Clinical intervention studies have examined whether reducing sleep in normal sleepers, typically sleeping 7-9 h/night, can affect energy intake, energy expenditure, and endocrine regulators of energy balance. The aim of this review is to evaluate studies that have assessed food intake, energy expenditure, and leptin and ghrelin levels after periods of restricted and normal sleep. Most studies support the notion that restricting sleep increases food intake, but the effects on energy expenditure are mixed. Differences in methodology and component of energy expenditure analyzed may account for the discrepancies. Studies examining the effects of sleep on leptin and ghrelin have provided conflicting results with increased, reduced, or unchanged leptin and ghrelin levels after restricted sleep compared to normal sleep. Energy balance of study participants and potential sex differences may account for the varied results. Studies should strive for constant energy balance and feeding schedules when assessing the role of sleep on hormonal profile. Although studies suggest that restricting sleep may lead to weight gain via increased food intake, research is needed to examine the impact on energy expenditure and endocrine controls. Also, studies have been of short duration, and there is little knowledge on the reverse question: does increasing sleep duration in short sleepers lead to negative energy balance?

Reduced carbohydrate diet to improve metabolic outcomes and decrease adiposity in obese peripubertal African American girls

OBJECTIVE

Obesity prevalence among African American (AA) girls is higher than that in other groups. Because typical energy-restriction obesity treatment strategies have had limited success, alterations in macronutrient composition may effectively improve metabolic outcomes in this population and affect future body composition trajectories. The objective was to evaluate the efficacy of a moderately restricted carbohydrate (CHO) versus a standard CHO diet on weight/fat loss and metabolic parameters in overweight/obese AA girls ages 9 to 14 years.

METHODS

A total of 26 AA girls (ranging from 92nd body mass index percentile and above) were assigned to either a reduced- (SPEC: 42% energy from CHO, n = 12) or a standard- (STAN: 55% of energy from CHO, n = 14) CHO diet (protein held constant) for 16 weeks. All of the meals were provided and clinically tailored to meet the estimated energy requirements (resting energy expenditure × 1.2 in eucaloric phase and resting energy expenditure × 1.2 - 1000 kcal in energy deficit phase). The first 5 weeks encompassed a eucaloric phase evaluating metabolic changes in the absence of weight change. The subsequent 11 weeks were hypocaloric (1000 kcal/day deficit) to promote weight/fat loss. Meal tests were performed during the eucaloric phase for metabolic analyses. Dual-energy x-ray absorptiometry was used to evaluate body composition.

RESULTS

Both groups experienced reductions in weight/adiposity, but the difference did not reach significance. The solid meal test indicated improved glucose/insulin homeostasis on the SPEC diet up to 3 hours postingestion. In addition, significantly lower triglycerides (P < 0.001) were observed on the SPEC diet.

CONCLUSIONS

Dietary CHO reduction favorably influences metabolic parameters but did not result in greater weight/fat loss relative to a standard diet in obese AA girls. Future research is needed to determine long-term effectiveness of a reduced CHO diet on glucose and insulin homeostasis and how it may apply to weight maintenance/fat loss during development alone and/or in combination with additional weight loss/metabolic improvement strategies.

Human brain mass: similar body composition associations as observed across mammals

OBJECTIVES

A classic association is the link between brain mass and body mass across mammals that has now been shown to derive from fat-free mass (FFM) and not fat mass (FM). This study aimed to establish for the first time the associations between human brain mass and body composition and to compare these relations with those established for liver as a reference organ.

METHODS

Subjects were 112 men and 148 women who had brain and liver mass measured by magnetic resonance imaging with FM and FFM measured by dual-energy X-ray absorptiometry.

RESULTS

Brain mass scaled to height (H) with powers of ≤0.6 in men and women; liver mass and FFM both scaled similarly as H(~2) . The fraction of FFM as brain thus scaled inversely to height (P < 0.001) while liver mass/FFM was independent of height. After controlling for age, brain, and liver mass were associated with FFM while liver was additionally associated with FM (all models P ≤ 0.01). After controlling for age and sex, FFM accounted for ~5% of the variance in brain mass while levels were substantially higher for liver mass (~60%). Brain mass was significantly larger (P < 0.001) in men than in women, even after controlling for age and FFM.

CONCLUSIONS

As across mammals, human brain mass associates significantly, although weakly, with FFM and not FM; the fraction of FFM as brain relates inversely to height; brain differs in these relations from liver, another small high metabolic rate organ; and the sexual dimorphism in brain mass persists even after adjusting for age and FFM.

Nutritional treatment of obesity

The focus of this article is nutritional strategies for weight loss. Following a review of general nutritional principles, the evidence behind specific nutritional weight-loss strategies is presented. These strategies include nutritional supplements, nutrient-limited diets, and energy-limited diets. A brief discussion of nutritional considerations relevant to other weight-loss strategies--pharmacologic, surgical, and exercise-based--is included. Specific evidence-based recommendations are presented.

Modeling weight-loss maintenance to help prevent body weight regain

BACKGROUND

Lifestyle intervention can successfully induce weight loss in obese persons, at least temporarily. However, there currently is no way to quantitatively estimate the changes of diet or physical activity required to prevent weight regain. Such a tool would be helpful for goal-setting, because obese patients and their physicians could assess at the outset of an intervention whether long-term adherence to the calculated lifestyle change is realistic.

OBJECTIVE

We aimed to calculate the expected change of steady-state body weight arising from a given change in dietary energy intake and, conversely, to calculate the modification of energy intake required to maintain a particular body-weight change.

DESIGN

We developed a mathematical model using data from 8 longitudinal weight-loss studies representing 157 subjects with initial body weights ranging from 68 to 160 kg and stable weight losses between 7 and 54 kg.

RESULTS

Model calculations closely matched the change data (R(2) = 0.83, chi(2) = 2.1, P < 0.01 for weight changes; R(2) = 0.91, chi(2) = 0.87, P < 0.0004 for energy intake changes). Our model performed significantly better than the previous models for which chi(2) values were 10-fold those of our model. The model also accurately predicted the proportion of weight change resulting from the loss of body fat (R(2) = 0.90).

CONCLUSIONS

Our model provides realistic calculations of body-weight change and of the dietary modifications required for weight-loss maintenance. Because the model was implemented by using standard spreadsheet software, it can be widely used by physicians and weight-management professionals.