Out-of-Pocket Expenses in Households of People Living with Obesity in France.

BACKGROUND/OBJECTIVES: Overweight and obesity result in a substantial economic burden in both low- and high-income countries. Moreover, this burden is often underestimated because it only partially accounts for unreimbursed out-of-pocket expenses (OOPE) related to obesity. The objective of our study was not only to evaluate OOPE incurred by people with obesity in relation to their disease with respect to direct medical expenditures and direct non-medical expenditures but also the proportion of people living with obesity who have forgone obesity-related healthcare due to the costs of such care. METHODS: An observational descriptive survey was conducted among people with class II/III obesity attending six obesity treatment centers in France. Volunteer adult participants completed a written/phone questionnaire on their related expenditures over the last 6 months for current expenditures and over the last 5 years for occasional ones. The costs were expressed in 2022 EUR. RESULTS: 299 people participated (age: 46 years [SD: 13.9], women: 72%, BMI ≥40 kg/m2: 62% and 48% with comorbidities). 65% had a professional activity. 83% declared that they had OOPE related to obesity representing annually EUR 2027/individual on average (5% of the household revenue), including weight loss and nutritional products, vitamins, meal programs, gym memberships, psychologists, but mainly adapted clothing, additional travel costs, and others. 15% of the respondents had to modify their professional activity due to obesity and 15% forwent some medical care in the last 12 months. CONCLUSIONS: OOPE is a significant part of the economic burden of obesity. Despite some limitations due to the specificities of the participants and because some costs may be more related to social activities affected by obesity than to healthcare, it seems important to consider these expenditures in cost estimates for obesity.

Energy Expenditure in Older People Hospitalized for an Acute Episode.

Weight loss and worsening of nutritional state is a frequent downfall of acute hospitalization in older people. It is usually accepted that acute inflammation is responsible for hypercatabolism. However, several studies suggest, on the contrary, a reduction in resting energy expenditure (REE). This study aimed to obtain a reliable measure of REE and total energy expenditure (TEE) in older patients hospitalized for an acute episode in order to better assess patients' energy requirements and help understand the mechanisms of weight loss in this situation. Nineteen hospitalized older patients (mean age 83 years) with C-reactive protein (CRP) level >20mg/L were recruited. REE and TEE were measured using gold standard methods of indirect calorimetry and doubly labeled water (DLW), respectively. REE was then compared to data from a previous study on aged volunteers from nursing homes who were free of an acute stressor event. Energy requirements measured by DLW were confirmed at 1.3 × REE. Energy intake covered the needs but did not prevent weight loss in these patients. TEE was not increased in hospitalized patients and was not influenced by inflammation, while the relationship between REE and inflammation was uncertain. Our results suggest that lean mass remains the major determinant of REE in hospitalized older people and that weight loss may not be explained solely by a state of hypercatabolism.

Physical activity, energy expenditure and sedentary parameters in overfeeding studies - a systematic review.

BACKGROUND: It has been proposed that compensations in physical activity, energy expenditure and sedentary parameters can occur as a result of overfeeding studies in order to maintain body weight; however, the evidence has not yet been systematically reviewed. METHODS: The current study systematically reviewed the literature on this subject to determine the common tools used in overfeeding studies and to explore whether overfeeding produces changes in physical activity, energy expenditure and sedentary parameters. Eight electronic databases were searched to identify experimental studies using keywords pertaining to overfeeding, exercise, physical activity and sedentariness. Articles included healthy adults (aged 18-64 years) participating in an overfeeding study that examined at least one parameter of sedentary, energy expenditure or physical activity. Of 123 full-text articles reviewed, 15 met the inclusion criteria. RESULTS: The common tools used in overfeeding studies were doubly labeled water (n = 6), room calorimeter (n = 4), accelerometer (n = 7), pedometer (n = 3), radar sensor (n = 4) and survey (n = 1). Parameters partaining to energy expenditure increased between 7 to 50% with different overfeeding duration. Physical activity parameters, such as number of steps and spontaneous activity, increased or decreased significantly in three studies, while five studies showed no significant change. Sedentary parameters were examined by only one study and its results were not significant after 3 days of overfeeding. Methodological issues existed concerning the small number of studies, disparities in sedentary and physical activity parameters and various definitions of free-living experimental conditions and physical activity limits. CONCLUSIONS: There is actually a use of many tools and a large variation of parameters for physical activity in overfeeding studies. Contradictory findings showed changes in physical activity parameters following overfeeding and limited findings support the absence of changes in sedentariness. While energy expenditure parameters are more numerous and all show an increase after an overfeeding period, further studies are required to confirm changes in physical activity and sedentary parameters.

Comparison of MRI-derived vs. traditional estimations of fatty acid composition from MR spectroscopy signals.

INTRODUCTION: The composition of fatty acids in the body is gaining increasing interest, and can be followed up noninvasively by quantitative magnetic resonance spectroscopy (MRS). However, current MRS quantification methods have been shown to provide different quantitative results in terms of lipid signals, with possible varying outcomes for a given biological examination. Quantitative magnetic resonance imaging using multigradient echo sequence (MGE-MRI) has recently been added to MRS approaches. In contrast, these methods fit the undersampled magnetic resonance temporal signal with a simplified model function (expressing the triglyceride [TG] spectrum with only three TG parameters), specific implementations and prior knowledge. In this study, an adaptation of an MGE-MRI method to MRS lipid quantification is proposed. METHODS: Several versions of the method - with time data fully or undersampled, including or excluding the spectral peak T2 knowledge in the fitting - were compared theoretically and on Monte Carlo studies with a time-domain, peak-fitting approach. Robustness, repeatability and accuracy were also inspected on in vitro oil acquisitions and test-retest in vivo subcutaneous adipose tissue acquisitions, adding results from the reference LCModel method. RESULTS: On simulations, the proposed method provided TG parameter estimates with the smallest variability, but with a possible bias, which was mitigated by fitting on undersampled data and considering peak T2 values. For in vitro measurements, estimates for all approaches were correlated with theoretical values and the best concordance was found for the usual MRS method (LCModel and peak fitting). Limited in vivo test-retest variability was found (4.1% for PUFAindx, 0.6% for MUFAindx and 3.6% for SFAindx), as for LCModel (7.6% for PUFAindx, 7.8% for MUFAindx and 3.0% for SFAindx). CONCLUSION: This study shows that fitting the three TG parameters directly on MRS data is one valuable solution to circumvent the poor conditioning of the MRS quantification problem.

An artificial neural network to predict resting energy expenditure in obesity.

BACKGROUND & AIMS: The resting energy expenditure (REE) determination is important in nutrition for adequate dietary prescription. The gold standard i.e. indirect calorimetry is not available in clinical settings. Thus, several predictive equations have been developed, but they lack of accuracy in subjects with extreme weight including obese populations. Artificial neural networks (ANN) are useful predictive tools in the area of artificial intelligence, used in numerous clinical fields. The aim of this study was to determine the relevance of ANN in predicting REE in obesity. METHODS: A Multi-Layer Perceptron (MLP) feed-forward neural network with a back propagation algorithm was created and cross-validated in a cohort of 565 obese subjects (BMI within 30-50 kg m-2) with weight, height, sex and age as clinical inputs and REE measured by indirect calorimetry as output. The predictive performances of ANN were compared to those of 23 predictive REE equations in the training set and in two independent sets of 100 and 237 obese subjects for external validation. RESULTS: Among the 23 established prediction equations for REE evaluated, the Harris & Benedict equations recalculated by Roza were the most accurate for the obese population, followed by the USA DRI, Müller and the original Harris & Benedict equations. The final 5-fold cross-validated three-layer 4-3-1 feed-forward back propagation ANN model developed in that study improved precision and accuracy of REE prediction over linear equations (precision = 68.1%, MAPE = 8.6% and RMSPE = 210 kcal/d), independently from BMI subgroups within 30-50 kg m-2. External validation confirmed the better predictive performances of ANN model (precision = 73% and 65%, MAPE = 7.7% and 8.6%, RMSPE = 187 kcal/d and 200 kcal/d in the 2 independent datasets) for the prediction of REE in obese subjects. CONCLUSIONS: We developed and validated an ANN model for the prediction of REE in obese subjects that is more precise and accurate than established REE predictive equations independent from BMI subgroups. For convenient use in clinical settings, we provide a simple ANN-REE calculator available at: https://www.crnh-rhone-alpes.fr/fr/ANN-REE-Calculator.

Barriers to the conduct of randomised clinical trials within all disease areas.

BACKGROUND: Randomised clinical trials are key to advancing medical knowledge and to enhancing patient care, but major barriers to their conduct exist. The present paper presents some of these barriers. METHODS: We performed systematic literature searches and internal European Clinical Research Infrastructure Network (ECRIN) communications during face-to-face meetings and telephone conferences from 2013 to 2017 within the context of the ECRIN Integrating Activity (ECRIN-IA) project. RESULTS: The following barriers to randomised clinical trials were identified: inadequate knowledge of clinical research and trial methodology; lack of funding; excessive monitoring; restrictive privacy law and lack of transparency; complex regulatory requirements; and inadequate infrastructures. There is a need for more pragmatic randomised clinical trials conducted with low risks of systematic and random errors, and multinational cooperation is essential. CONCLUSIONS: The present paper presents major barriers to randomised clinical trials. It also underlines the value of using a pan-European-distributed infrastructure to help investigators overcome barriers for multi-country trials in any disease area.

Activity energy expenditure is a major determinant of dietary fat oxidation and trafficking, but the deleterious effect of detraining is more marked than the beneficial effect of training at current recommendations.

BACKGROUND: Previous studies suggested that physical activity energy expenditure (AEE) is a major determinant of dietary fat oxidation, which is a central component of fat metabolism and body weight regulation. OBJECTIVE: We tested this hypothesis by investigating the effect of contrasted physical activity levels on dietary saturated and monounsaturated fatty acid oxidation in relation to insulin sensitivity while controlling energy balance. DESIGN: Sedentary lean men (n = 10) trained for 2 mo according to the current guidelines on physical activity, and active lean men (n = 9) detrained for 1 mo by reducing structured and spontaneous activity. Dietary [d31]palmitate and [1-¹³C]oleate oxidation and incorporation into triglyceride-rich lipoproteins and nonesterified fatty acid, AEE, and muscle markers were studied before and after interventions. RESULTS: Training increased palmitate and oleate oxidation by 27% and 20%, respectively, whereas detraining reduced them by 31% and 13%, respectively (P < 0.05 for all). Changes in AEE were positively correlated with changes in oleate (R² = 0.62, P < 0.001) and palmitate (R² = 0.66, P < 0.0001) oxidation. The d31-palmitate appearance in nonesterified fatty acid and very-low-density lipoprotein pools was negatively associated with changes in fatty acid translocase CD36 (R² = 0.30), fatty acid transport protein 1 (R² = 0.24), and AcylCoA synthetase long chain family member 1 (ACSL1) (R² = 0.25) expressions and with changes in fatty acid binding protein expression (R² = 0.33). The d31-palmitate oxidation correlated with changes in ACSL1 (R² = 0.39) and carnitine palmitoyltransferase 1 (R² = 0.30) expressions (P < 0.05 for all). Similar relations were observed with oleate. Insulin response was associated with AEE (R² = 0.34, P = 0.02) and oleate (R² = 0.52, P < 0.01) and palmitate (R² = 0.62, P < 001) oxidation. CONCLUSION: Training and detraining modified the oxidation of the 2 most common dietary fats, likely through a better trafficking and uptake by the muscle, which was negatively associated with whole-body insulin sensitivity.

Energy expenditure adjusted for body composition differentiates constitutional thinness from both normal subjects and anorexia nervosa.

Constitutional thinness (CT) is characterized by a low and stable body mass index (BMI) without any hormonal abnormality. To understand the weight steadiness, energetic metabolism was evaluated. Seven CT, seven controls, and six anorexia nervosa (AN) young women were compared. CT and AN had a BMI <16.5 kg/m(2). Four criteria were evaluated: 1) energy balance including diet record, resting metabolic rate (RMR) (indirect calorimetry), total energy expenditure (TEE) (doubly labeled water), physical activity; 2) body composition (dual-energy X-ray absorptiometry); 3) biological markers (leptin, IGF-I, free T3); 4) psychological profile of eating behavior. The normality of free T3 (3.7 +/- 0.5 pmol/l), IGF-I (225 +/- 93 ng/ml), and leptin (8.3 +/- 3.4 ng/ml) confirmed the absence of undernutrition in CT. Their psychological profiles revealed a weight gain desire. TEE (kJ/day) in CT (8,382 +/- 988) was not found significantly different from that of controls (8,793 +/- 845) and AN (8,001 +/- 2,152). CT food intake (7,565 +/- 908 kJ/day) was found similar to that of controls (7,961 +/- 1,452 kJ/day) and higher than in AN (4,894 +/- 703 kJ/day), thus explaining the energy metabolism balance. Fat-free mass (FFM) (kg) was similar in CT and AN (32.5 +/- 2.9 vs. 34.1 +/- 1.9) and higher in controls (37.8 +/- 1.6). While RMR absolute values (kJ/day) were lower in CT (4,839 +/- 473) than in controls (5,576 +/- 209), RMR values adjusted for FFM were the highest in CT. TEE-to-FFM ratio was also higher in CT than in controls. Energetic metabolism balance maintains a stable low weight in CT. An increased energy expenditure-to-FFM ratio differentiates CT from controls and could account for the resistance to weight gain observed in CT.