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Body composition assessment is often used in clinical practice for nutritional evaluation and monitoring. The standard method, dual-energy X-ray absorptiometry (DXA), is hardly feasible in routine clinical practice contrary to Bioelectrical Impedance Analysis (BIA) method. We thus aimed to compare body composition assessment by DXA and BIA according to the body mass index (BMI) in a large cohort. Retrospectively, we analysed DXA and BIA measures in patients followed in a Nutrition Unit from 2010 to 2016. Body composition was assessed under standardized conditions in the morning, after a fasting period of 12 h, by DXA (Lunar Prodigy Advance) and BIA (Bodystat QuadScan 4000, Manufacturer's equation). Bland-Altman test was performed for each class of BMI (kg/m2) and fat mass and fat free mass values were compared using Kruskal-Wallis test. Pearson correlations were also performed and the concordance coefficient of Lin was calculated. Whatever the BMI, BIA and DXA methods reported higher concordance for values of FM than FFM. Body composition values were very closed for patients with BMI between 16 and 18,5 (difference < 1kg). For BMI > 18,5 and BMI < 40, BIA overestimated fat free mass from 3,38 to 8,28 kg, and underestimated fat mass from 2,51 to 5,67 kg compared with DXA method. For BMI ≥ 40, differences vary with BMI. For BMI < 16, BIA underestimated fat free mass by 2,25 kg, and overestimated fat mass by 2,57 kg. However, limits of agreement were very large either for FM and FFM values, irrespective of BMI. The small bias, particularly in patients with BMI between 16 and 18, suggests that BIA and DXA methods are interchangeable at a population level. However, concordance between BIA and DXA methods at the individual level is lacking, irrespective of BMI.

Background Eating disorders (ED) are a public health concern due to their increasing prevalence and severe associated comorbidities. The aim of this study was to identify mental health and health behaviours associated with each form of EDs. Methods A case–control study was performed: cases were patients with EDs managed for the first time in a specialized nutrition department and controls without EDs were matched on age and gender with cases. Participants of this study filled self-administered paper questionnaire (EDs group) or online questionnaire (non-ED group). Collected data explored socio-demographics, mental health including anxiety and depression, body image, life satisfaction, substances and internet use and presence of IBS (Irritable Bowel Syndrome). Results 248 ED patients (broad categories: 66 Restrictive, 22 Bulimic and 160 Compulsive) and 208 non-ED subjects were included in this study. Mean age was 36.0 (SD 13.0) and 34.8 (SD 11.6) in ED and non-ED groups, respectively. Among patients and non-ED subjects, 86.7% and 83.6% were female, respectively. Body Shape Questionnaire mean score was between 103.8 (SD 46.1) and 125.0 (SD 36.2) for EDs and non-ED group, respectively ( p  < 0.0001). ED patients had a higher risk of unsatisfactory friendly life, anxiety, depression and IBS than non-ED s (all p  < 0.0001) Higher risk of anxiety, depression and IBS was found for the three categories of EDs. Higher risk of smoking was associated only with restrictive ED, while or assault history and alcohol abuse problems were associated only with bulimic ED. The risk of binge drinking was lower in all EDs categories than in non-ED. Conclusion This study highlights the common comorbidities shared by all EDs patients and also identifies some specific features related to ED categories. These results should contribute to the conception of future screening and prevention programs in at risk young population as well as holistic care pathways for ED patients. Plain English summary This case–control study evaluated mental health and health behaviours associated with the main categories of Eating Disorders (EDs). Cases were patients with EDs initiating care in a specialized nutrition department and controls without ED were matched on age and gender with cases. Self-administered paper questionnaires were filled by ED 248 patients (66 Restrictive, 22 Bulimic and 160 Compulsive) and online questionnaire by 241 non-ED controls. Body image satisfaction was significantly worse in ED patients than in controls. ( p  < 0.0001). Dissatisfactory life, anxiety, depression and irritable bowel syndrome were more found in patients with all EDs categories than in non-ED ( p  < 0.0001). Smoking risk was increased only in restrictive patients while and assault history and alcohol abuse was increased only in bulimic patients. These results highlight the global burden of ED and related comorbidities and provide useful information for future screening, prevention and care programs.

Micronutrient status in Anorexia Nervosa (AN) has been poorly documented and previous data are often contradictory. We aimed to assess micronutrient status in a large population of AN patients. The relationships between micronutrient status and body composition were also determined. Anthropometric, biochemical parameters and body composition data were collected at referral in 153 patients with AN (28.5 ± 11 years). At least one trace element deficit was observed in almost half of patients; the most frequent was selenium deficit (40% of patients). At least one vitamin deficit was observed in 45.7% of patients, mostly vitamin A and B9. Albumin, transthyretin and CRP were within normal range in most patients. No correlations were found between body composition and micronutrient status. Our study suggests that micronutrient status is often altered in AN patients, which may contribute to neuropsychiatric dysfunction. Monitoring of micronutrients and correction of deficits should be included in the routine care of AN patients.

Quality of life (QoL) is impaired in obesity, but the roles of eating behavior and psychological distress need to be more documented. One hundred thirty consecutive obese patients seeking medical care filled out questionnaires evaluating QoL, the presence of an eating disorder (ED), levels of anxiety and depression, and perception of body image. Global QoL was poor in 16.4% and intermediate in 61.8% of the patients. EDs were present in 58% of patients who were more (P = 0.05) overweight; 24.2% of patients had binging. EDs impaired significantly the global and specific dimensions of QoL; binging impaired physical and sexual QoLs (both P < 0.02). Anxiety and depression were found in 73.6% and 50.4% of patients, respectively; depression was more frequent in women (P = 0.007) and in patients with EDs. Anxiety and/or depression impaired global (P < 0.001) and specific dimensions of QoL. Body shape concern was marked in 86.4% of women and associated with poor global (P < 0.001) and specific QoL, and with anxiety and depression. The impairment of QoL in obese patients is increased by the presence of an ED, anxiety, and/or depression and marked body shape concern. These psychological factors should be assessed more carefully and taken into account in global strategies aiming to improve the well-being of obese patients.

Body composition assessment is often used in clinical practice for nutritional evaluation and monitoring. The standard method, dual-energy X-ray absorptiometry (DXA), is hardly feasible in routine clinical practice contrary to Bioelectrical Impedance Analysis (BIA) method. We thus aimed to compare body composition assessment by DXA and BIA according to the body mass index (BMI) in a large cohort. Retrospectively, we analysed DXA and BIA measures in patients followed in a Nutrition Unit from 2010 to 2016. Body composition was assessed under standardized conditions in the morning, after a fasting period of 12 h, by DXA (Lunar Prodigy Advance) and BIA (Bodystat QuadScan 4000, Manufacturer's equation). Bland-Altman test was performed for each class of BMI (kg/m.sup.2) and fat mass and fat free mass values were compared using Kruskal-Wallis test. Pearson correlations were also performed and the concordance coefficient of Lin was calculated. Whatever the BMI, BIA and DXA methods reported higher concordance for values of FM than FFM. Body composition values were very closed for patients with BMI between 16 and 18,5 (difference 18,5 and BMI < 40, BIA overestimated fat free mass from 3,38 to 8,28 kg, and underestimated fat mass from 2,51 to 5,67 kg compared with DXA method. For BMI [greater than or equal to] 40, differences vary with BMI. For BMI < 16, BIA underestimated fat free mass by 2,25 kg, and overestimated fat mass by 2,57 kg. However, limits of agreement were very large either for FM and FFM values, irrespective of BMI. The small bias, particularly in patients with BMI between 16 and 18, suggests that BIA and DXA methods are interchangeable at a population level. However, concordance between BIA and DXA methods at the individual level is lacking, irrespective of BMI.

Body composition assessment is often used in clinical practice for nutritional evaluation and monitoring. The standard method, dual-energy X-ray absorptiometry (DXA), is hardly feasible in routine clinical practice contrary to Bioelectrical Impedance Analysis (BIA) method. We thus aimed to compare body composition assessment by DXA and BIA according to the body mass index (BMI) in a large cohort. Retrospectively, we analysed DXA and BIA measures in patients followed in a Nutrition Unit from 2010 to 2016. Body composition was assessed under standardized conditions in the morning, after a fasting period of 12 h, by DXA (Lunar Prodigy Advance) and BIA (Bodystat QuadScan 4000, Manufacturer's equation). Bland-Altman test was performed for each class of BMI (kg/m.sup.2) and fat mass and fat free mass values were compared using Kruskal-Wallis test. Pearson correlations were also performed and the concordance coefficient of Lin was calculated. Whatever the BMI, BIA and DXA methods reported higher concordance for values of FM than FFM. Body composition values were very closed for patients with BMI between 16 and 18,5 (difference 18,5 and BMI < 40, BIA overestimated fat free mass from 3,38 to 8,28 kg, and underestimated fat mass from 2,51 to 5,67 kg compared with DXA method. For BMI [greater than or equal to] 40, differences vary with BMI. For BMI < 16, BIA underestimated fat free mass by 2,25 kg, and overestimated fat mass by 2,57 kg. However, limits of agreement were very large either for FM and FFM values, irrespective of BMI. The small bias, particularly in patients with BMI between 16 and 18, suggests that BIA and DXA methods are interchangeable at a population level. However, concordance between BIA and DXA methods at the individual level is lacking, irrespective of BMI.

Background: In patients with obesity and metabolic syndrome (MetS), lifestyle interventions combining diet, in particular, and physical exercise are recommended as the first line treatment. Previous studies have suggested that leucine or arginine supplementation may have beneficial effects on the body composition or insulin sensitivity and endothelial function, respectively. We thus conducted a randomized controlled study to evaluate the effects of a supervised adapted physical activity program associated or not with oral supplementation with leucine and arginine in MetS-complicated patients with obesity. Methods: Seventy-nine patients with obesity and MetS were randomized in four groups: patients receiving arginine and leucine supplementation (ALs group, n = 20), patients on a supervised adapted physical activity program (APA group, n = 20), patients combining ALs and APA (ALs+APA group, n = 20), and a control group (n = 19). After the baseline evaluation (m0), patients received ALs and/or followed the APA program for 6 months (m6). Body composition, MetS parameters, lipid and glucose metabolism markers, inflammatory markers, and a cardiopulmonary exercise test (CPET) were assessed at m0, m6, and after a 3-month wash-out period (m9). Results: After 6 months of intervention, we did not observe variable changes in body weight, body composition, lipid and glucose metabolism markers, inflammatory parameters, or quality of life scores between the four groups. However, during the CPET, the maximal power (Pmax and Ppeak), power, and O2 consumption at the ventilatory threshold (P(VT) and O2(VT)) were improved in the APA and ALs+APA groups (p < 0.05), as well as the forced vital capacity (FVC). Between m6 and m9, a gain in fat mass was only observed in patients in the APA and ALs+APA groups. Conclusion: In our randomized controlled trial, arginine and leucine supplementation failed to improve MetS in patients with obesity, as did the supervised adapted physical activity program and the combination of both. Only the cardiorespiratory parameters were improved by exercise training.

Predictive equations have been specifically developed for obese patients to estimate resting energy expenditure (REE). Body composition (BC) assessment is needed for some of these equations. We assessed the impact of BC methods on the accuracy of specific predictive equations developed in obese patients. REE was measured (mREE) by indirect calorimetry and BC assessed by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). mREE, percentages of prediction accuracy (±10% of mREE) were compared. Predictive equations were studied in 2588 obese patients. Mean mREE was 1788 ± 6.3 kcal/24 h. Only the Müller (BIA) and Harris & Benedict (HB) equations provided REE with no difference from mREE. The Huang, Müller, Horie-Waitzberg, and HB formulas provided a higher accurate prediction (>60% of cases). The use of BIA provided better predictions of REE than DXA for the Huang and Müller equations. Inversely, the Horie-Waitzberg and Lazzer formulas provided a higher accuracy using DXA. Accuracy decreased when applied to patients with BMI ≥ 40, except for the Horie-Waitzberg and Lazzer (DXA) formulas. Müller equations based on BIA provided a marked improvement of REE prediction accuracy than equations not based on BC. The interest of BC to improve REE predictive equations accuracy in obese patients should be confirmed.

Eating disorders (ED) are a public health concern due to their increasing prevalence and severe associated comorbidities. The aim of this study was to identify mental health and health behaviours associated with each form of EDs. A case-control study was performed: cases were patients with EDs managed for the first time in a specialized nutrition department and controls without EDs were matched on age and gender with cases. Participants of this study filled self-administered paper questionnaire (EDs group) or online questionnaire (non-ED group). Collected data explored socio-demographics, mental health including anxiety and depression, body image, life satisfaction, substances and internet use and presence of IBS (Irritable Bowel Syndrome). 248 ED patients (broad categories: 66 Restrictive, 22 Bulimic and 160 Compulsive) and 208 non-ED subjects were included in this study. Mean age was 36.0 (SD 13.0) and 34.8 (SD 11.6) in ED and non-ED groups, respectively. Among patients and non-ED subjects, 86.7% and 83.6% were female, respectively. Body Shape Questionnaire mean score was between 103.8 (SD 46.1) and 125.0 (SD 36.2) for EDs and non-ED group, respectively (p < 0.0001). ED patients had a higher risk of unsatisfactory friendly life, anxiety, depression and IBS than non-ED s (all p < 0.0001) Higher risk of anxiety, depression and IBS was found for the three categories of EDs. Higher risk of smoking was associated only with restrictive ED, while or assault history and alcohol abuse problems were associated only with bulimic ED. The risk of binge drinking was lower in all EDs categories than in non-ED. This study highlights the common comorbidities shared by all EDs patients and also identifies some specific features related to ED categories. These results should contribute to the conception of future screening and prevention programs in at risk young population as well as holistic care pathways for ED patients.

Eating disorders (EDs) are increasingly frequent. Their pathophysiology involves disturbance of peptide signaling and the microbiota–gut–brain axis. This study analyzed peptides and corresponding immunoglobulin (Ig) concentrations in groups of ED. In 120 patients with restrictive (R), bulimic (B), and compulsive (C) ED, the plasma concentrations of leptin, glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and insulin were analyzed by Milliplex and those of acyl ghrelin (AG), des-acyl ghrelin (DAG), and α-melanocyte-stimulating hormone (α-MSH) by ELISA kits. Immunoglobulin G (in response to an antigen) concentrations were analyzed by ELISA, and their affinity for the respective peptide was measured by surface plasmon resonance. The concentrations of leptin, insulin, GLP-1, and PYY were higher in C patients than in R patients. On the contrary, α-MSH, DAG, and AG concentrations were higher in R than in C patients. After adjustment for body mass index (BMI), differences among peptide concentrations were no longer different. No difference in the concentrations of the IgG was found, but the IgG concentrations were correlated with each other. Although differences of peptide concentrations exist among ED subtypes, they may be due to differences in BMI. Changes in the concentration and/or affinity of several anti-peptide IgG may contribute to the physiopathology of ED or may be related to fat mass.