While there is an increasing prevalence of dieting in the overall population, weight loss (WL) practices could be a risk factor for weight gain (WG) in normal-weight (NW) individuals. The aim of the present work was to systematically review all the studies implicating diet restriction and body weight (BW) evolution in NW people. The literature search was registered in PROSPERO (CRD42021281442) and was performed in three databases from April 2021 to June 2022 for articles involving healthy NW adults. From a total of 1487 records initially identified, eighteen were selected in the systematic review. Of the eight dieting interventional studies, only one found a higher BW after weight recovery, but 75 % of them highlighted metabolic adaptations in response to WL favouring weight regain and persisting during/after BW recovery. Eight of the ten observational studies showed a relationship between dieting and major later WG, while the meta-analysis of observational studies results indicated that ‘dieters’ have a higher BW than ‘non-dieters’. However, considering the high methodological heterogeneity and the publication bias of the studies, this result should be taken with caution. Moreover, the term ‘diet’ was poorly described, and we observed a large heterogeneity of the methods used to assess dieting status. Present results suggest that dieting could be a major risk factor for WG in the long term in NW individuals. There is, however, a real need for prospective randomised controlled studies, specifically assessing the relationship between WL induced by diet and subsequent weight in this population.

Studies exploring the accuracy of equations calculating resting energy expenditure (REE) in patients with Crohn’s disease (CD) are lacking. The aim of this study was to investigate the accuracy of REE predictive equations against indirect calorimetry in CD patients. REE was measured using indirect calorimetry (mREE) after an overnight fasting. Fourteen predictive equations, with and without body composition analysis parameters, were compared with mREE using different body weight approaches. Body composition analysis was performed using dual X-ray absorptiometry. One hundred and eighty-six CD outpatients (102 males) with mean age 41·3 (sd 14·1) years and 37·6 % with active disease were evaluated. Mean mREE in the total sample was 7255 (sd 1854) kJ/day. All equations underpredicted REE and showed moderate correlations with mREE (Pearson’s r or Spearman’s rho 0·600–0·680 for current weight, all P-values < 0·001). Accuracy was low for all equations at the individual level (28–42 and 25–40 % for current and adjusted body weight, respectively, 19–33 % for equations including body composition parameters). At the group level, accuracy showed wide limits of agreement and proportional biases. Accuracy remained low when sample was studied according to disease activity, sex, BMI and medication use. All predictive equations underestimated REE and showed low accuracy. Indirect calorimetry remains the best method for estimating REE of patients with CD.

The observation that 64% of English adults are overweight or obese despite a rising prevalence in weight-loss attempts suggests our understanding of energy balance is fundamentally flawed. Weight-loss is induced through a negative energy balance; however, we typically view weight change as a static function, in that energy intake and energy expenditure are independent variables, resulting in a fixed rate of weight-loss assuming a constant energy deficit. Such static modelling provides the basis for the clinical assumption that a 14644 kJ (3500 kcal) deficit translates to a 1 lb weight-loss. However, this ‘3500 kcal (14644 kJ) rule’ is consistently shown to significantly overestimate weight-loss. Static modelling disregards obligatory changes in energy expenditure associated with the loss of metabolically active tissue, i.e. skeletal muscle. Additionally, it disregards the presence of adaptive thermogenesis, the underfeeding-associated fall in resting energy expenditure beyond that caused by loss of fat-free mass. This metabolic manipulation of energy expenditure is observed from the onset of energy restriction to maintain weight at a genetically pre-determined set point. As a result, the observed magnitude of weight-loss is disproportionally less, followed by earlier weight plateau, despite strict compliance to a dietary intervention. By simulating dynamic changes in energy expenditure associated with underfeeding, mathematical modelling may provide a more accurate method of weight-loss prediction. However, accuracy at an individual level is limited due to difficulty estimating energy requirements, physical activity and dietary intake in free-living individuals. In the present paper, we aim to outline the contribution of dynamic changes in energy expenditure to weight-loss resistance and weight plateau.

Reducing sedentary behaviour (SB) and increasing physical activity (PA) by sitting less and standing/walking more is advised to prevent chronic diseases. However, the mechanisms underlying this recommendation are not well established, especially in individuals with obesity living in low-income regions. The present study evaluated whether there are associations between PA indicators (PAI – standing time, walking time and the number of steps/d) and SB indicators (SBI – sitting/lying down time) with the hormonal profile and resting energy expenditure (REE) of adult women living in a low-income region. This is a cross-sectional study. We collected data on hormones (insulin resistance, leptin and thyroid axis), body composition (tetrapolar bioimpedance), REE (indirect calorimetry), and PAI and SBI (triaxial accelerometers, ActivPAL). Multivariable linear models adjusting for age and fat-free mass were performed. Fifty-eight women (mean age of 31 years and BMI of 33 kg/m2) were included. The mean sitting/lying down time and standing time were 16·08 and 5·52 h/d, respectively. Sitting/lying down time showed a direct association with free thyroxine (FT4) (β = 0·56 ng/dl; 95 % CI = −1·10, −0·02). Standing time showed a direct association with FT4 (β = 0·75 ng/dl; 95 % CI = 0·01; 1·48) and inverse association with free triiodothyronine (β = −2·83 pg/ml 95 % CI = −5·56, −0·10). There were no associations between PAI and SBI with the REE, insulin resistance, leptin and thyroid-stimulating hormone. Thus, decreased SB is associated with thyroid hormones levels but not with REE, insulin resistance or leptin in women with obesity living in low-income regions.

Adaptive thermogenesis (AT) has been proposed to be a compensatory response that may resist weight loss (WL) and promote weight regain. This systematic review examined the existence of AT in adults after a period of negative energy balance (EB) with or without a weight stabilisation phase. Studies published until 15 May 2020 were identified from PubMed, Cochrane Library, EMBASE, MEDLINE, SCOPUS and Web of Science. Inclusion criteria included statistically significant WL, observational with follow-up or experimental studies, age > 18y, sample size ≥10 participants, intervention period ≥ 1week, published in English, objective measures of total daily energy expenditure (EE) (TDEE), resting EE (REE) and sleeping EE(SEE). The systematic review was registered at PROSPERO (2020 CRD42020165348). A total of thirty-three studies comprising 2528 participants were included. AT was observed in twenty-seven studies. Twenty-three studies showed significant values for AT for REE (82·8 %), four for TDEE (80·0 %) and two for SEE (100 %). A large heterogeneity in the methods used to quantify AT and between subjects and among studies regarding the magnitude of WL and/or of AT was reported. Well-designed studies reported lower or non-significant values for AT. These findings suggest that although WL may lead to AT in some of the EE components, these values may be small or non-statistically significant when higher-quality methodological designs are used. Furthermore, AT seems to be attenuated, or non-existent, after periods of weight stabilisation/neutral EB. More high-quality studies are warranted not only to disclose the existence of AT but also to understand its clinical implications on weight management outcomes.

The objective was to investigate which predictive equations provide the best estimates of resting energy expenditure (REE) in postpartum women with overweight and obesity. Lactating women with overweight or obesity underwent REE measurement by indirect calorimetry, and fat-free mass (FFM) was assessed by dual-energy X-ray absorptiometry at three postpartum stages. Predictive equations based on body weight and FFM were obtained from the literature. Performance of the predictive equations were analysed as the percentage of women whose REE was accurately predicted, defined as a predicted REE within ±10 % of measured REE. REE data were available for women at 10 weeks (n 71), 24 weeks (n 64) and 15 months (n 57) postpartum. Thirty-six predictive equations (twenty-five weight-based and eleven FFM-based) were validated. REE was accurately predicted in ≥80 % of women at all postpartum visits by six predictive equations (two weight-based and four FFM-based). The weight-based equation with the highest performance was that of Henry (weight, height, age 30–60 years) (HenryWH30−60), with an overall mean of 83 % accurate predictions. The HenryWH30−60 equation was highly suitable for predicting REE at all postpartum visits (irrespective of the women's actual age), and the performance was sustained across changes in weight and lactation status. No FFM-based equation was remarkably superior to HenryWH30−60 for the total postpartum period.

The purpose of the present study was to compare next-morning responses of RMR and appetite to pre-sleep consumption of casein protein (CP) in pre- and postmenopausal women. The study was a randomised, crossover, double-blind, placebo-controlled trial. Seven sedentary premenopausal (age: 19·9 (sd 1·2) years; BMI: 23·1 (sd 2·6) kg/m2) and seven sedentary postmenopausal (age: 56·4 (sd 4·9) years; BMI: 26·3 (sd 3·5) kg/m2) women participated. During visit one, anthropometrics and body composition were measured. Following visit one, subjects consumed either CP (25 g) or placebo (PL) ≥2 h after their last meal and ≤30 min prior to sleep on the night before visits two and three. Visits two and three occurred ≥1 week after visit one and were 48 h apart. During visits two and three, RMR (VO2), RER and appetite were measured via indirect calorimetry and visual analogue scale, respectively. Anthropometrics and body composition were analysed by one-way ANOVA. RMR and measures of appetite were analysed using a 2 × 2 (menopause status × CP/PL) repeated-measures ANOVA. Significance was accepted at P ≤ 0·05. RMR was significantly lower in postmenopausal compared with premenopausal women under both conditions (P = 0·003). When consumed pre-sleep CP did not alter RMR, RER or appetite compared with PL when assessed next morning in pre- and postmenopausal women. These data contribute to growing evidence that pre-sleep consumption of protein is not harmful to next-morning metabolism or appetite. In addition, these data demonstrate that menopause may not alter next-morning RMR, RER or appetite after pre-sleep consumption of CP.

Skeletal muscle is integral to the metabolism and utilisation of macronutrients; however, substantial muscle loss and morphological changes occur with ageing. These are associated with loss of muscle function and accelerate rapidly from the age of 60 years, leading to the conditions of sarcopenia and frailty. As the relationship between muscle ageing and macronutrient metabolism and utilisation has seen limited research to date, this review focuses on the interactions between skeletal muscle changes during ageing, metabolism and utilisation of fat, carbohydrates and overall energy expenditure.

Skeletal muscle contributes less to resting energy expenditure during ageing, potentially contributing to onset of obesity from middle age. Age-related changes to skeletal muscle lead to glucose dysregulation, with consequent reduction in glycaemic control, increased insulin resistance and ultimately onset of type-2 diabetes. Recent studies indicate that high total fat and SFA intake are detrimental to skeletal muscle, while higher intakes of PUFA are protective. Age-associated changes in skeletal muscle may also reduce total fatty acid utilisation.

In conclusion, further research is needed to understand the relationships between macronutrient metabolism and utilisation and age-related changes to skeletal muscle. No dietary recommendations exist specifically for skeletal muscle health during ageing, but we advise individuals to follow healthy eating guidelines, by consuming sufficient protein, fruit and vegetables, and limited SFA and to maintain physically active lifestyles. Clinicians responsible for managing type-2 diabetes need to be aware of growing evidence relating age-related skeletal muscle changes to diabetes onset and progression.

The purpose of this study was to determine the effect of a whole-food protein (cottage cheese, CC) consumed before sleep on next-morning resting energy expenditure (REE), RER and appetite compared with an isoenergetic/isonitrogenous casein protein (CP) supplement and placebo (PL) in active women. In a beverage-blinded, randomised, cross-over design, ten active women (age, 23·1 (sd 1·9) years; body fat, 22·0 (sd 4·6) %) consumed pre-sleep CC (30 g of protein, 10 g of carbohydrate and 0 g of fat) or energy- and protein-matched liquid CP or PL (0 kJ). Participants arrived at 18.00 hours for an overnight stay in the laboratory. At 30–60 min before normal bed time (2 h post standard meal), participants consumed CC, CP or PL before measurement of REE. Upon waking (05.00–08.00 hours), REE was repeated and subjective appetite was recorded. Statistical analyses were conducted using repeated-measures ANOVA (SPSS). Significance was accepted at P≤0·05. There were no significant differences in acute REE (CC, 7217 (sd 1368); CP, 7188 (SD 895); PL, 7075 (sd 1108) kJ/d, P=0·95), acute RER (0·79 (sd 0·05), P=0·56), morning REE (CC, 5840 (sd 1225); CP, 5694 (sd 732); PL, 5991 (sd 903) kJ/d, P=0·79) or morning RER (0·77 (sd 0·03), P=0·52). Subjective measures of appetite were not different between groups. In active women, pre-sleep consumption of CC does not alter REE or RER more than a CP or PL beverage. These data suggest that the metabolic response from whole-food protein do not differ from the metabolic response of liquid protein.

Non-exercise physical activity (NEPA) and/or non-exercise activity thermogenesis (NEAT) reductions may occur from diet and/or exercise-induced negative energy balance interventions, resulting in less-than-expected weight loss. This systematic review describes the effects of prescribed diet and/or physical activity (PA)/exercise on NEPA and/or NEAT in adults. Studies were identified from PubMed, web-of-knowledge, Embase, SPORTDiscus, ERIC and PsycINFO searches up to 1 March 2017. Eligibility criteria included randomised controlled trials (RCT), randomised trials (RT) and non-randomised trials (NRT); objective measures of PA and energy expenditure; data on NEPA, NEAT and spontaneous PA; ≥10 healthy male/female aged>18 years; and ≥7 d length. The trial is registered at PROSPERO-2017-CRD42017052635. In all, thirty-six articles (RCT-10, RT-9, NRT-17) with a total of seventy intervention arms (diet, exercise, combined diet/exercise), with a total of 1561 participants, were included. Compensation was observed in twenty-six out of seventy intervention arms (fifteen studies out of thirty-six reporting declines in NEAT (eight), NEPA (four) or both (three)) representing 63, 27 and 23 % of diet-only, combined diet/exercise, and exercise-only intervention arms, respectively. Weight loss observed in participants who decreased NEAT was double the weight loss found in those who did not compensate, suggesting that the energy imbalance degree may lead to energy conservation. Although these findings do not support the hypothesis that prescribed diet and/or exercise results in decreased NEAT and NEPA in healthy adults, the underpowered trial design and the lack of state-of-the-art methods may limit these conclusions. Future studies should explore the impact of weight-loss magnitude, energetic restriction degree, exercise dose and participant characteristics on NEAT and/or NEPA.

This study was a randomised, double-blind, placebo-controlled cross-over trial examining the effects of β-hydroxy β-methylbutyrate free acid (HMB-FA) supplementation on muscle protein breakdown, cortisol, testosterone and resting energy expenditure (REE) during acute fasting. Conditions consisted of supplementation with 3 g/d HMB-FA or placebo during a 3-d meat-free diet followed by a 24-h fast. Urine was collected before and during the 24-h fast for analysis of 3-methylhistidine:creatinine ratio (3MH:CR). Salivary cortisol, testosterone, their ratio (T:C), and the cortisol awakening response were assessed. ANOVA was used to analyse all dependent variables, and linear mixed models were used to confirm the absence of carryover effects. Eleven participants (six females, five males) completed the study. Urinary HMB concentrations confirmed compliance with supplementation. 3MH:CR was unaffected by fasting and supplementation, but the cortisol awakening response differed between conditions. In both conditions, cortisol increased from awakening to 30 min post-awakening (P=0·01). Cortisol was reduced from 30 to 45 min post-awakening with HMB-FA (−32 %, d=−1·0, P=0·04), but not placebo (PL) (−6 %, d=−0·2, P=0·14). In males, T:C increased from 0 to 24 h of fasting with HMB-FA (+162 %, d=3·0, P=0·001), but not placebo (+13 %, d=0·4, P=0·60), due to reductions in cortisol. REE was higher at 24 h of fasting than 16 h of fasting independent of supplementation (+4·0 %, d=0·3, P=0·04). In conclusion, HMB-FA may affect cortisol responses, but not myofibrillar proteolysis, during acute 24-h fasting.

The intermittent energy restriction (IER) approach to weight loss involves short periods of substantial (>70 %) energy restriction (ER) interspersed with normal eating. Studies to date comparing IER to continuous energy restriction (CER) have predominantly measured fasting indices of cardiometabolic risk. This study aimed to compare the effects of IER and CER on postprandial glucose and lipid metabolism following matched weight loss. In all, twenty-seven (thirteen male) overweight/obese participants (46 (sem 3) years, 30·1 (sem 1·0) kg/m2) who were randomised to either an IER intervention (2638 kJ for 2 d/week with an overall ER of 22 (sem 0·3) %, n 15) or a CER intervention (2510 kJ below requirements with overall ER of 23 (sem 0·8) %) completed the study. Postprandial responses to a test meal (over 360 min) and changes in anthropometry (fat mass, fat-free mass, circumferences) were assessed at baseline and upon attainment of 5 % weight loss, following a 7-d period of weight stabilisation. The study found no statistically significant difference in the time to attain a 5 % weight loss between groups (median 59 d (interquartile range (IQR) 41–80) and 73 d (IQR 48–128), respectively, P=0·246), or in body composition (P≥0·437). For postprandial measures, neither diet significantly altered glycaemia (P=0·266), whereas insulinaemia was reduced comparatively (P=0·903). The reduction in C-peptide tended (P=0·057) to be greater following IER (309 128 (sem23 268) to 247781 (sem20 709) pmol×360 min/l) v. CER (297 204 (sem25 112) to 301 655 (sem32 714) pmol×360 min/l). The relative reduction in TAG responses was greater (P=0·045) following IER (106 (sem30) to 68 (sem 15) mmol×360 min/l) compared with CER (117 (sem 43) to 130 (sem 31) mmol×360 min/l). In conclusion, these preliminary findings highlight underlying differences between IER and CER, including a superiority of IER in reducing postprandial lipaemia, which now warrant targeted mechanistic evaluation within larger study cohorts.

Low energy and protein intakes have been associated with an increased risk of malnutrition in outpatients with chronic obstructive pulmonary disease (COPD). We aimed to assess the energy and protein intakes of hospitalised COPD patients according to nutritional risk status and requirements, and the relative contribution from meals, snacks, drinks and oral nutritional supplements (ONS), and to examine whether either energy or protein intake predicts outcomes. Subjects were COPD patients (n 99) admitted to Landspitali University Hospital in 1 year (March 2015–March 2016). Patients were screened for nutritional risk using a validated screening tool, and energy and protein intake for 3 d, 1–5 d after admission to the hospital, was estimated using a validated plate diagram sheet. The percentage of patients reaching energy and protein intake ≥75 % of requirements was on average 59 and 37 %, respectively. Malnourished patients consumed less at mealtimes and more from ONS than lower-risk patients, resulting in no difference in total energy and protein intakes between groups. No clear associations between energy or protein intake and outcomes were found, although the association between energy intake, as percentage of requirement, and mortality at 12 months of follow-up was of borderline significance (OR 0·12; 95 % CI 0·01, 1·15; P=0·066). Energy and protein intakes during hospitalisation in the study population failed to meet requirements. Further studies are needed on how to increase energy and protein intakes during hospitalisation and after discharge and to assess whether higher intake in relation to requirement of hospitalised COPD patients results in better outcomes.

Short bowel syndrome (SBS) represents a serious intestinal absorption disorder, and patients may be prone to severe malnutrition. Dietetic therapy is critically important both for immediate prognosis and successful long-term rehabilitation. To maintain energy balance, an accurate assessment of energy intake is required. Our objective was to compare energy intake (EI) assessed by 24-h dietary recalls (EIrecall), a standard clinical assessment, with the total energy expenditure measured by the doubly labelled water (TEEdlw) method in SBS patients and matched controls. A total of twenty-two participants (eleven each in the SBS and control groups (CG), six female and five male) were evaluated; CG were matched to SBS patients on the basis of age, BMI and sex. TEE was measured by DLW and compared with EI determined by four 24-h dietary recalls using the USDA Automated Multiple-Pass Method. Bland–Altman plots and paired Student’s t test were used to compare EIrecall with TEEdlw (P<0·05). Participants’ mean age was 53 (sd 8) years. TEEdlw (7·85 (SD 1·16) MJ/d, 0·14 (SD 0·02) MJ/kg per d) was significantly lower (P=0·014) compared with EIrecall (11·07 (SD 3·45) MJ/d, 0·21 (SD 0·08) MJ/kg per d) in the SBS group. On the other hand, in the CG group TEEdlw (10·02 (SD 1·86) MJ/d, 0·18 (SD 0·03) MJ/kg per d) was significantly higher (P=0·001) compared with EIrecall (7·19 (SD 1·68) MJ/d, 0·13 (SD 0·03) MJ/kg per d). In SBS patients, reported EI is higher than DLW-measured EI. Therefore, providing or prescribing energetic intake based on EIrecall without accounting for potential malabsorption-related losses can compromise the energy needs in SBS patients and affect nutritional status in the long term.

The doubly labelled water method for the measurement of total daily energy expenditure (TDEE) over 1–3 weeks under daily living conditions is the indicated method to study effects of exercise and extreme environments on energy balance. Subjects consume a measured amount of doubly labelled water (2H218O) to increase background enrichment of body water for 18O and 2H, and the subsequent difference in elimination rate between 18O and 2H, as measured in urine, saliva or blood samples, is a measure for carbon dioxide production and thus allows calculation of TDEE. The present review describes research showing that physical activity level (PAL), calculated as TDEE (assessed with doubly labelled water) divided by resting energy expenditure (REE, PAL = TDEE/REE), reaches a maximum value of 2·00–2·40 in subjects with a vigorously active lifestyle. Higher PAL values, while maintaining energy balance, are observed in professional athletes consuming additional energy dense foods to compete at top level. Exercise training can increase TDEE/REE in young adults to a value of 2·00–2·40, when energy intake is unrestricted. Furthermore, the review shows an exercise induced increase in activity energy expenditure can be compensated by a reduction in REE and by a reduction in non-exercise physical activity, especially at a negative energy balance. Additionally, in untrained subjects, an exercise-induced increase in activity energy expenditure is compensated by a training-induced increase in exercise efficiency.

Lifestyle-related problems are becoming a major health threat in East Asian countries. Therefore, finding an efficacious nutraceutical for this population is important. One candidate is fucoxanthin (Fx), a carotenoid abundantly found in edible brown seaweed that has been associated with a number of valuable health-promoting benefits. Unfortunately, clinical studies of Fx are limited. In the present study, we aimed to evaluate the effects of Fx on obesity-related parameters in Japanese subjects harbouring an SNP associated with lifestyle-related problems. In all, sixty normal-weight and obese Japanese adults with BMI over 22 kg/m2 were single-blinded and randomly assigned to three Fx-dose cohorts and administered Fx-enriched akamoku oil containing Fx at 0, 1 or 2 mg/d for 8 weeks (n 20 per group). Parameters relating to obesity and serum Fx metabolites were measured before and after intervention, but no significant differences were observed between and within the groups. Despite no changes in visceral fat areas and resting energy expenditures after intervention, we observed a significant decline in HbA1c levels in the 2 mg/d Fx group compared with that in the 0 mg/d group (P < 0·05), which was correlated with an increase in serum fucoxanthinol (Fx metabolite) levels. In addition, HbA1c levels declined more significantly in subjects with G/G alleles of the uncoupling protein 1 (UCP1) gene than in those with the A/A and A/G alleles (P < 0·05). We conclude that although Fx supplementation does not affect visceral fat areas, it may reduce HbA1c levels in those harbouring the thrifty allele of UCP1-3826A/G.

Assessing energy requirements is a fundamental activity in clinical dietetic practice. The aim of this study was to investigate which resting energy expenditure (REE) predictive equations are the best alternatives to indirect calorimetry before and after an interdisciplinary therapy in Brazilian obese women. In all, twelve equations based on weight, height, sex, age, fat-free mass and fat mass were tested. REE was measured by indirect calorimetry. The interdisciplinary therapy consisted of nutritional, physical exercise, psychological and physiotherapy support during the course of 1 year. The average differences between measured and predicted REE, as well as the accuracy at the ±10 % level, were evaluated. Statistical analysis included paired t tests, intraclass correlation coefficients and Bland–Altman plots. Validation was based on forty obese women (BMI 30–39·9 kg/m2). Our major findings demonstrated a wide variation in the accuracy of REE predictive equations before and after weight loss in non-morbid, obese women. The equations reported by Harris–Benedict and FAO/WHO/United Nations University (UNU) were the only ones that did not show significant differences compared with indirect calorimetry and presented a bias <5 %. The Harris–Benedict equation provided 40 and 47·5 % accurate predictions before and after therapy, respectively. The FAO equation provided 35 and 47·5 % accurate predictions. However, the Bland–Altman analysis did not show good agreement between these equations and indirect calorimetry. Therefore, the Harris–Benedict and FAO/WHO/UNU equations should be used with caution for obese women. The need to critically re-assess REE data and generate regional and more homogeneous REE databases for the target population is reinforced.

Dietary mycoprotein decreases energy intake in lean individuals. The effects in overweight individuals are unclear, and the mechanisms remain to be elucidated. This study aimed to investigate the effect of mycoprotein on energy intake, appetite regulation, and the metabolic phenotype in overweight and obese volunteers. In two randomised-controlled trials, fifty-five volunteers (age: 31 (95 % CI 27, 35) years), BMI: 28·0 (95 % CI 27·3, 28·7) kg/m2) consumed a test meal containing low (44 g), medium (88 g) or high (132 g) mycoprotein or isoenergetic chicken meals. Visual analogue scales and blood samples were collected to measure appetite, glucose, insulin, peptide tyrosine-tyrosine (PYY) and glucagon-like peptide-1 (GLP-1). Ad libitum energy intake was assessed after 3 h in part A (n 36). Gastric emptying by the paracetamol method, resting energy expenditure and substrate oxidation were recorded in part B (n 14). Metabonomics was used to compare plasma and urine samples in response to the test meals. Mycoprotein reduced energy intake by 10 % (280 kJ (67 kcal)) compared with chicken at the high content (P=0·009). All mycoprotein meals reduced insulin concentrations compared with chicken (incremental AUClow (IAUClow): −8 %, IAUCmedium: −12 %, IAUChigh: −21 %, P=0·004). There was no significant difference in glucose, PYY, GLP-1, gastric emptying rate and energy expenditure. Following chicken intake, paracetamol-glucuronide was positively associated with fullness. After mycoprotein, creatinine and the deamination product of isoleucine, α-keto-β-methyl-N-valerate, were inversely related to fullness, whereas the ketone body, β-hydroxybutyrate, was positively associated. In conclusion, mycoprotein reduces energy intake and insulin release in overweight volunteers. The mechanism does not involve changes in PYY and GLP-1. The metabonomics analysis may bring new understanding to the appetite regulatory properties of food.

Better understanding is needed regarding the effects of exercise alone, without any imposed dietary regimens, as a single tool for body-weight regulation. Thus, we evaluated the effects of an 8-week increase in activity energy expenditure (AEE) on ad libitum energy intake (EI), body mass and composition in healthy participants with baseline physical activity levels (PAL) in line with international recommendations. Forty-six male adults (BMI = 19·7–29·3 kg/m2) participated in an intervention group, and ten (BMI = 21·0–28·4 kg/m2) in a control group. Anthropometric measures, cardiorespiratory fitness, EI, AEE and exercise intensity were recorded at baseline and during the 1st, 5th and 8th intervention weeks, and movement was recorded throughout. Body composition was measured at the beginning and at the end of the study, and resting energy expenditure was measured after the study. The intervention group increased PAL from 1·74 (se 0·03) to 1·93 (se 0·03) (P < 0·0001) and cardiorespiratory fitness from 41·4 (se 0·9) to 45·7 (se 1·1) ml O2/kg per min (P = 0·001) while decreasing body mass (−1·36 (se 0·2) kg; P = 0·001) through adipose tissue mass loss (ATM) (−1·61 (se 0·2) kg; P = 0·0001) compared with baseline. The control group did not show any significant changes in activity, body mass or ATM. EI was unchanged in both groups. The results indicate that in normal-weight and overweight men, increasing PAL from 1·7 to 1·9 while keeping EI ad libitum over an 8-week period produces a prolonged negative energy balance. Replication using a longer period (and/or more intense increase in PAL) is needed to investigate if and at what body composition the increase in AEE is met by an equivalent increase in EI.

Circumstantial evidence suggests that substitution of glucose or sucrose by the low-glycaemic index sugar galactose in the diet may lead to greater thermogenesis and/or fat oxidation. Using ventilated hood indirect calorimetry, we investigated, in twelve overnight-fasted adults, the resting energy expenditure (REE) and respiratory quotient (RQ) for 30 min before and 150 min after ingestion of 500 ml of water containing 60 g of glucose, fructose or galactose in a randomised cross-over design. REE increased similarly with all three sugars, reaching peak values after 50–60 min, but its subsequent fall towards baseline values was faster with galactose and glucose than with fructose (P < 0·001). RQ increased with all three sugars, but to a much greater extent with galactose and fructose than with glucose, particularly after 1 h post-ingestion. When ingested as a sugary drink, postprandial thermogenesis and utilisation of fat after galactose are not higher than after glucose or fructose.