Perspective: Do Scientists Become Part of the Obesity Problem?

Obesity is fundamentally a condition where physiology and behavior of individuals meet the environment, and the emerging global obesity pandemic reflects the contribution of a wide range of cultural, societal, economic and systemic driving forces. Today, different areas of obesity research are relatively separated from each other in discrete silos, with biomedical research determining most of our understanding and solution strategies. This has led to the Y in the road, which means the questionable assumption that effective drug treatment of individual patients is also an effective measure to improve population health. Since human obesity is a condition of population health and planetary impact a better integration of biomedical and public health approaches is based on critical (self-)reflection and communicative understanding of scientists from various research areas who should be on an equal footing.

Effect of exogenous and endogenous ketones on respiratory exchange ratio and glucose metabolism in healthy subjects.

This study examined the effect of exogenous ketone bodies (KB) on oxygen consumption (V̇o2), carbon dioxide production (V̇co2), and glucose metabolism. The data were compared with the effects of endogenous ketonemia during both, a ketogenic diet or fasting. Eight healthy individuals [24.1 ± 2.5 yr, body mass index (BMI) 24.3 ± 3.1 kg/m2] participated in a crossover intervention study and were studied in a whole-room indirect calorimeter (WRIC) to assess macronutrient oxidation following four 24-h interventions: isocaloric controlled mixed diet (ISO), ISO supplemented with ketone salts (38.7 g of ß-hydroxybutyrate/day, EXO), isocaloric ketogenic diet (KETO), and total fasting (FAST). A physical activity level of 1.65 was obtained. In addition to plasma KB, 24-h C-peptide and KB excretion rates in the urine and postprandial glucose and insulin levels were measured. Although 24-h KB excretion increased in response to KETO and FAST, there was a modest increase in response to EXO only (P < 0.05). When compared with ISO, V̇o2 significantly increased in KETO (P < 0.01) and EXO (P < 0.001), whereas there was no difference in FAST. V̇co2 increased in EXO but decreased in KETO (both P < 0.01) and FAST (P < 0.001), resulting in 24-h respiratory exchange ratios (RER) of 0.828 ± 0.024 (ISO) and 0.811 ± 0.024 (EXO) (P < 0.05). In response to EXO there were no differences in basal and postprandial glucose and insulin levels, as well as in insulin sensitivity. When compared with ISO, EXO, and KETO, FAST increased homeostatic model assessment ß-cell function (HOMA-B) (all P < 0.05). In conclusion, at energy balance exogenous ketone salts decreased respiratory exchange ratio without affecting glucose tolerance.NEW & NOTEWORTHY Our findings revealed that during isocaloric nutrition, additional exogenous ketone salts increased V̇o2 and V̇co2 while lowering the respiratory exchange ratio (RER). Ketone salts had no effect on postprandial glucose metabolism.

Proportion of caloric restriction-induced weight loss as skeletal muscle.

OBJECTIVE: This study's objective was to develop models predicting the relative reduction in skeletal muscle (SM) mass during periods of voluntary calorie restriction (CR) and to validate model predictions in longitudinally monitored samples. METHODS: The model development group included healthy nonexercising adults (n = 897) who had whole-body SM mass measured with magnetic resonance imaging. Model predictions of relative SM changes with CR were evaluated in two longitudinal studies, one 12 to 14 weeks in duration (n = 74) and the other 12 months in duration (n = 26). RESULTS: A series of SM prediction models were developed in a sample of 415 males and 482 females. Model-predicted changes in SM mass relative to changes in body weight (i.e., ΔSM/Δbody weight) with a representative model were (mean ± SE) 0.26 ± 0.013 in males and 0.14 ± 0.007 in females (sex difference, p < 0.001). The actual mean proportions of weight loss as SM in the longitudinal studies were 0.23 ± 0.02/0.20 ± 0.06 in males and 0.10 ± 0.02/0.17 ± 0.03 in females, similar to model-predicted values. CONCLUSIONS: Nonelderly males and females with overweight and obesity experience respective reductions in SM mass with voluntary CR in the absence of a structured exercise program of about 2 to 2.5 kg and 1 to 1.5 kg per 10-kg weight loss, respectively. These estimates are predicted to be influenced by interactions between age and body mass index in males, a hypothesis that needs future testing.

Impact of one-day fasting, ketogenic diet or exogenous ketones on control of energy balance in healthy participants.

BACKGROUND & AIMS: Oral ketone supplements may mimic the beneficial effects of endogenous ketones on energy metabolism as ß-hydroxybutyrate has been proposed to increase energy expenditure and improve body weight regulation. Therefore, our objective was to compare the effects of a one-day isocaloric ketogenic diet, fasting and supplementation with ketone salts on energy expenditure and appetite perception. METHODS: Eight healthy young adults (4 women, 4 men, age 24 ± 3 years, BMI 24.3 ± 3.1 kg/m2) participated in a randomized cross-over trial with four 24 h-interventions in a whole room indirect calorimeter at a physical activity level of 1.65: (i) total fasting (FAST), (ii) isocaloric ketogenic diet (3.1% energy from carbohydrates (CHO), KETO), (iii) isocaloric control diet (47.4% energy from CHO, ISO), and (iv) ISO supplemented with 38.7 g/d ketone salts (exogenous ketones, EXO). Effects on serum ketone levels (15 h-iAUC), energy metabolism (total energy expenditure, TEE; sleeping energy expenditure, SEE; macronutrient oxidation) and subjective appetite were measured. RESULTS: Compared to ISO, ketone levels were considerably higher with FAST and KETO and little higher with EXO (all p > 0.05). Total and sleeping energy expenditure did not differ between ISO, FAST and EXO whereas KETO increased TEE (+110 ± 54 kcal/d vs. ISO, p < 0.05) and SEE (+201 ± 90 kcal/d vs. ISO, p < 0.05). CHO oxidation was slightly decreased with EXO compared to ISO (-48 ± 27 g/d, p < 0.05) resulting in a positive CHO balance (p < 0.05). No differences between the interventions were found for subjective appetite ratings (all p > 0.05). CONCLUSION: A 24 h-ketogenic diet may contribute to maintain a neutral energy balance by increasing energy expenditure. Exogenous ketones in addition to an isocaloric diet did not improve regulation of energy balance. CLINICAL TRIAL REGISTRATION: NCT04490226 https://clinicaltrials.gov/.

Changes in body composition and homeostatic control of resting energy expenditure during dietary weight loss.

Adaptive thermogenesis (AT) is the mass-independent decrease in energy expenditure (EE) in response to caloric restriction and weight loss. AT becomes manifest throughout all periods of weight loss and persists during subsequent weight maintenance. AT occurs in resting and nonresting energy expenditure as ATREE and ATNREE , respectively. ATREE appears in different phases of weight loss, each with likely different mechanisms. By contrast, during weight maintenance after weight loss, ATNREE exceeds ATREE . Some of the mechanisms of AT are known now and others are not. Future studies on AT will need an appropriate conceptual framework within which to design experiments and interpret results.

Determinants of bone mass in older adults with normal- and overweight derived from the crosstalk with muscle and adipose tissue.

Lower bone mass in older adults may be mediated by the endocrine crosstalk between muscle, adipose tissue and bone. In 150 community-dwelling adults (59-86 years, BMI 17-37 kg/m2; 58.7% female), skeletal muscle mass index, adipose tissue and fat mass index (FMI) were determined. Levels of myokines, adipokines, osteokines, inflammation markers and insulin were measured as potential determinants of bone mineral content (BMC) and density (BMD). FMI was negatively associated with BMC and BMD after adjustment for mechanical loading effects of body weight (r-values between -0.37 and -0.71, all p < 0.05). Higher FMI was associated with higher leptin levels in both sexes, with higher hsCRP in women and with lower adiponectin levels in men. In addition to weight and FMI, sclerostin, osteocalcin, leptin × sex and adiponectin were independent predictors of BMC in a stepwise multiple regression analysis. Muscle mass, but not myokines, showed positive correlations with bone parameters that were weakened after adjusting for body weight (r-values between 0.27 and 0.58, all p < 0.01). Whereas the anabolic effect of muscle mass on bone in older adults may be partly explained by mechanical loading, the adverse effect of obesity on bone is possibly mediated by low-grade inflammation, higher leptin and lower adiponectin levels.

Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models.

Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R2s (0.88-0.93; all p < 0.001) and small root-mean square errors (1.74, 0.41, and 0.95 kg) with no bias in the validation sample (N = 95). The new total body SM prediction model (SM = 1.12 × ALM - 0.63) showed good performance, with some bias, against previously reported DXA-ALM prediction models. These new total body and extremity SM prediction models, developed and validated in a large sample, afford an important and practical opportunity to evaluate SM mass in research and clinical settings.

Resting Energy Expenditure in the Critically Ill and Healthy Elderly-A Retrospective Matched Cohort Study.

The use of indirect calorimetry to measure resting energy expenditure (mREE) is widely recommended as opposed to calculating REE (cREE) by predictive equations (PE). The aim of this study was to compare mREE with cREE in critically ill, mechanically ventilated patients aged ≥ 75 years and a healthy control group matched by age, gender and body mass index. The primary outcome was the PE accuracy rate of mREE/cREE, derived using Bland Altman plots. Secondary analyses included linear regression analyses for determinants of intraindividual mREE/cREE differences in the critically ill and interindividual mREE differences in the matched healthy cohort. In this retrospective study, 90 critically ill patients (median age 80 years) and 58 matched healthy persons were included. Median mREE was significantly higher in the critically ill (1457 kcal/d) versus the healthy cohort (1351 kcal/d), with low PE accuracy rates (21% to 49%). Independent predictors of mREE/cREE differences in the critically ill were body temperature, heart rate, FiO2, hematocrit, serum sodium and urea. Body temperature, respiratory rate, and FiO2 were independent predictors of interindividual mREE differences (critically ill versus healthy control). In conclusion, the commonly used PE in the elderly critically ill are inaccurate. Respiratory, metabolic and energy homeostasis variables may explain intraindividual mREE/cREE as well as interindividual mREE differences.

Analysis of the adiponectin paradox in healthy older people.

BACKGROUND: It remains unknown why adiponectin levels are associated with poor physical functioning, skeletal muscle mass and increased mortality in older populations. METHODS: In 190 healthy adults (59-86 years, BMI 17-37 kg/m2 , 56.8% female), whole body skeletal muscle mass (normalized by height, SMI, kg/m2 ), muscle and liver fat were determined by magnetic resonance imaging. Bone mineral content (BMC) and density (BMD) were assessed by dual X-ray absorptiometry (n = 135). Levels of insulin-like growth factor 1 (IGF-1), insulin, inflammation markers, leptin and fibroblast growth factor 21 were measured as potential determinants of the relationship between adiponectin and body composition. RESULTS: Higher adiponectin levels were associated with a lower SMI (r = -0.23, P < 0.01), BMC (r = -0.17, P < 0.05) and liver fat (r = -0.20, P < 0.05) in the total population and with higher muscle fat in women (r = 0.27, P < 0.01). By contrast, IGF-1 showed positive correlations with SMI (r = 0.33), BMD (r = 0.37) and BMC (r = 0.33) (all P < 0.01) and a negative correlation with muscle fat (r = -0.17, P < 0.05). IGF-1 was negatively associated with age (r = -0.21, P < 0.01) and with adiponectin (r = -0.15, P < 0.05). Stepwise regression analyses revealed that IGF-1, insulin and leptin explained 18% of the variance in SMI, and IGF-1, leptin and age explained 16% of the variance in BMC, whereas adiponectin did not contribute to these models. CONCLUSIONS: Associations between higher adiponectin levels and lower muscle or bone mass in healthy older adults may be explained by a decrease in IGF-1 with increasing adiponectin levels.

Issues related to the assessment of energy balance during short-term over-, under- and refeeding in normal weight men.

BACKGROUND: In humans, it is unclear how different estimates of energy balance (EB) compare with each other and whether the resulting changes in body weight (bw) and body composition (BC) are predictable and reproducible. METHODS: This is a secondary data analysis of effects of sequential 7d over- (OF), 21d under- (UF) and 14d refeeding (RF) on EB. Energy intake (EI) was controlled at +/- 50% of energy needs in a 32 normal weight men (see Am J Clin Nutr. 2015; 102:807-819). EB was calculated (i) directly from the difference between EI and energy expenditure (EE) and (ii) indirectly from changes in BC. Changes in fat mass (FM) were compared with predicted changes according to Hall et al. (Lancet 2011; 378:826-37). Finally, within-subject reproducibility of changes in bw and BC was tested in a subgroup. RESULTS: There were interindividual and day-by-day variabilities in changes in bw and BC. During OF and RF, the two estimates of EB were similar while with UF the indirect approach underestimated the direct estimate by 10593 ± 7506 kcal/21d (p < 0.001). Considerable differences became evident between measured and predicted changes in FM. Adjusting measured for predicted values did not reduce their interindividual variance. During UF, changes in bw and BC were reproducible, while corresponding changes during OF were not. CONCLUSION: During hypercaloric nutrition the direct estimate of EB corresponded to the indirect estimate whereas this was not true during UF. Changes in bw and BC in response to OF were not reproducible while they were during UF.

Validation of energy expenditure and macronutrient oxidation measured by two new whole-room indirect calorimeters.

OBJECTIVE: The aim of this study was to validate two new whole-room indirfect calorimeters according to Room Indirect Calorimetry Operating and Reporting Standards (RICORS 1.0). METHODS: For technical validation, 16 propane combustion tests were performed to determine accuracy and precision of energy expenditure (EE) and ventilation rates of oxygen (VO2 ), carbon dioxide (VCO2 ), and respiratory exchange ratio (VCO2 /VO2 ). For biological validation, eight participants (mean [SD], age 24.1 [2.5] years; BMI 24.3 [3.1] kg/m2 ) underwent four 24-hour protocols under highly standardized conditions: (1) isocaloric sedentary, (2) fasting sedentary, (3) isocaloric active, and (4) fasting active. Reliability (coefficients of variation [CV]) and minimal detectable changes (MDC) were calculated for 24-hour EE, sleeping metabolic rate (SMR), physical activity energy expenditure (PAEE), thermic effect of food (TEF), and macronutrient oxidation rates. RESULTS: Technical validation showed high reliability and recovery rates for VO2 (0.75% and 100.8%, respectively), VCO2 (0.49% and 100.6%), and EE (0.54% and 98.2%). Biological validation revealed CV and MDC for active conditions of 1.4% and 4.3% for 24-hour EE, 1.7% and 5.9% for SMR, and 30.2% and 38.4% for TEF, as well as 5.8% and 10.5% for PAEE, respectively. Mean CV and MDC for macronutrient oxidation rates were 9.9% and 22.9%, respectively. CONCLUSIONS: The precision of 24-hour EE and SMR was high, whereas it was lower for PAEE and poor for TEF.

What Is a 2021 Reference Body?

The historical 1975 Reference Man is a 'model' that had been used as a basis for the calculation of radiation doses, metabolism, pharmacokinetics, sizes for organ transplantation and ergonomic optimizations in the industry, e.g., to plan dimensions of seats and other formats. The 1975 Reference Man was not an average individual of a population; it was based on the multiple characteristics of body compositions that at that time were available, i.e., mainly from autopsy data. Faced with recent technological advances, new mathematical models and socio-demographic changes within populations characterized by an increase in elderly and overweight subjects a timely 'state-of-the-art' 2021 Reference Body are needed. To perform this, in vivo human body composition data bases in Kiel, Baton Rouge, San Francisco and Honolulu were analyzed and detailed 2021 Reference Bodies, and they were built for both sexes and two age groups (≤40 yrs and >40 yrs) at BMIs of 20, 25, 30 and 40 kg/m2. We have taken an integrative approach to address 'structure−structure' and 'structure−function' relationships at the whole-body level using in depth body composition analyses as assessed by gold standard methods, i.e., whole body Magnetic Resonance Imaging (MRI) and the 4-compartment (4C-) model (based on deuterium dilution, dual-energy X-ray absorptiometry and body densitometry). In addition, data obtained by a three-dimensional optical scanner were used to assess body shape. The future applications of the 2021 Reference Body relate to mathematical modeling to address complex metabolic processes and pharmacokinetics using a multi-level/multi-scale approach defining health within the contexts of neurohumoral and metabolic control.

Associations between high-metabolic rate organ masses and fasting hunger: A study using whole-body magnetic resonance imaging in healthy males.

BACKGROUND: Fat-free mass (FFM) has been shown to be positively associated with hunger and energy intake, an association mediated by resting metabolic rate (RMR). However, FFM comprises a heterogeneous group of tissues with distinct metabolic rates, and it remains unknown how specific high-metabolic rate organs contribute to the degree of perceived hunger. OBJECTIVE: To examine whether FFM and its anatomical components were associated with fasting hunger when assessed at the tissue-organ level. DESIGN: Body composition (quantitative magnetic resonance and magnetic resonance imaging), RMR and whole-body glucose oxidation (indirect calorimetry), HOMA-index as a marker of insulin sensitivity, nitrogen balance and fasting hunger (visual analogue scales) were assessed in 21 healthy males (age = 25 ± 3y; BMI = 23.4 ± 2.1 kg/m2) after 3 days of controlled energy balance. RESULTS: FFM (rs = 0.39; p = 0.09), RMR (rs = 0.52; p = 0.02) and skeletal muscle mass (rs = 0.57; p = 0.04), but not fat mass (rs = -0.01; p = 0.99), were positively associated with fasting hunger. The association between the combined mass of high-metabolic rate organs (i.e., brain, liver, kidneys and heart; rs = 0.58; p = 0.006) and fasting hunger was stronger than with FFM as a uniform body component. The strongest individual association was between liver mass and fasting hunger (rs = 0.51; p = 0.02). No associations were observed between glucose parameters, markers of insulin sensitivity and fasting hunger. The encephalic measure, an index of brain-to-body energy allocation, was negatively associated with fasting hunger (rs = -0.51; p = 0.02). CONCLUSIONS: Fasting hunger was more strongly associated with the combined mass of high-metabolic rate organs than with FFM as a uniform body component, highlighting the importance of integrating individual tissue-organ masses and their functional correlates into homeostatic models of human appetite. The association between liver mass and fasting hunger may reflect its role in ensuring the brain's basal energy needs are met.

Phenotypic differences between people varying in muscularity.

BACKGROUND: Body mass is the primary metabolic compartment related to a vast number of clinical indices and predictions. The extent to which skeletal muscle (SM), a major body mass component, varies between people of the same sex, weight, height, and age is largely unknown. The current study aimed to explore the magnitude of muscularity variation present in adults and to examine if variation in muscularity associates with other body composition and metabolic measures. METHODS: Muscularity was defined as the difference (residual) between a person's actual and model-predicted SM mass after controlling for their weight, height, and age. SM prediction models were developed using data from a convenience sample of 492 healthy non-Hispanic (NH) White adults (ages 18-80 years) who had total body SM and SM surrogate, appendicular lean soft tissue (ALST), measured with magnetic resonance imaging and dual-energy X-ray absorptiometry, respectively; residual SM (SMR ) and ALST were expressed in kilograms and kilograms per square meter. ALST mass was also evaluated in a population sample of 8623 NH-White adults in the 1999-2006 National Health and Nutrition Examination Survey. Associations between muscularity and variation in the residual mass of other major organs and tissues and resting energy expenditure were evaluated in the convenience sample. RESULTS: The SM, on average, constituted the largest fraction of body weight in men and women up to respective BMIs of 35 and 25 kg/m2 . SM in the convenience sample varied widely with a median of 31.2 kg and an SMR inter-quartile range/min/max of 3.35 kg/-10.1 kg/9.0 kg in men and 21.1 kg and 2.59 kg/-7.2 kg/7.5 kg in women; per cent of body weight as SM at 25th and 75th percentiles for men were 33.1% and 39.6%; corresponding values in women were 24.2% and 30.8%; results were similar for SMR indices and for ALST measures in the convenience and population samples. Greater muscularity in the convenience sample was accompanied by a smaller waist circumference (men/women: P < 0.001/=0.085) and visceral adipose tissue (P = 0.014/0.599), larger liver (P = 0.065/<0.001), kidneys (P = 0.051/<0.009), and bone mineral (P < 0.001/<0.001), and larger magnitude resting energy expenditure (P < 0.001/<0.001) than predicted for the same sex, age, weight, and height. CONCLUSIONS: Muscle mass is the largest body compartment in most adults without obesity and is widely variable in mass across people of similar body size and age; and high muscularity is accompanied by distinct body composition and metabolic characteristics. This previously unrecognized heterogeneity in muscularity in the general population has important clinical and research implications.

What Is the Impact of Energy Expenditure on Energy Intake?

Coupling energy intake (EI) to increases in energy expenditure (EE) may be adaptively, compensatorily, or maladaptively leading to weight gain. This narrative review examines if functioning of the homeostatic responses depends on the type of physiological perturbations in EE (e.g., due to exercise, sleep, temperature, or growth), or if it is influenced by protein intake, or the extent, duration, timing, and frequency of EE. As different measures to increase EE could convey discrepant neuronal or humoral signals that help to control food intake, the coupling of EI to EE could be tight or loose, which implies that some ways to increase EE may have advantages for body weight regulation. Exercise, physical activity, heat exposure, and a high protein intake favor weight loss, whereas an increase in EE due to cold exposure or sleep loss likely contributes to an overcompensation of EI, especially in vulnerable thrifty phenotypes, as well as under obesogenic environmental conditions, such as energy dense high fat-high carbohydrate diets. Irrespective of the type of EE, transient elevations in the metabolic rate seem to be general risk factors for weight gain, because a subsequent decrease in energy requirement is not compensated by an adequate adaptation of appetite and EI.