We sought to examine the effects of daily consumption of macadamia nuts on body weight and composition, plasma lipids and glycaemic parameters in a free-living environment in overweight and obese adults at elevated cardiometabolic risk. Utilising a randomised cross-over design, thirty-five adults with abdominal obesity consumed their usual diet plus macadamia nuts (~15 % of daily calories) for 8 weeks (intervention) and their usual diet without nuts for 8 weeks (control), with a 2-week washout. Body composition was determined by bioelectrical impedance; dietary intake was assessed with 24-h dietary recalls. Consumption of macadamia nuts led to increased total fat and MUFA intake while SFA intake was unaltered. With mixed model regression analysis, no significant changes in mean weight, BMI, waist circumference, percent body fat or glycaemic parameters, and non-significant reductions in plasma total cholesterol of 2⋅1 % (−4⋅3 mg/dl; 95 % CI −14⋅8, 6⋅1) and low-density lipoprotein (LDL-C) of 4 % (−4⋅7 mg/dl; 95 % CI −14⋅3, 4⋅8) were observed. Cholesterol-lowering effects were modified by adiposity: greater lipid lowering occurred in those with overweight v. obesity, and in those with less than the median percent body fat. Daily consumption of macadamia nuts does not lead to gains in weight or body fat under free-living conditions in overweight or obese adults; non-significant cholesterol lowering occurred without altering saturated fat intake of similar magnitude to cholesterol lowering seen with other nuts.

Clinical Trial Registry Number and Website: NCT03801837 https://clinicaltrials.gov/ct2/show/NCT03801837?term = macadamia + nut&draw = 2&rank = 1

The European Food Safety Authority has suggested that EU countries implement the 2 × 24 h diet recall (2 × 24 h DR) method and physical activity (PA) measurements for national dietary surveys. Since 2000, Denmark has used 7 d food diaries (7 d FD) with PA questionnaires and measurements. The accuracy of the reported energy intakes (EI) from the two diet methods, pedometer-determined step counts and self-reported time spent in moderate-to-vigorous PA (MVPA) were compared with total energy expenditure measured by the doubly labelled water (TEEDLW) technique and with PA energy expenditure (PAEE), respectively. The study involved fifty-two male and sixty-eight female volunteers aged 18–60 years who were randomly assigned to start with either the 24 h DR or the web-based 7 d FD, and wore a pedometer for the first 7 d and filled in a step diary. The mean TEEDLW (11·5 MJ/d) was greater than the mean reported EI for the 7 d FD (9·5 MJ/d (P < 0·01)) but the same as the 2 × 24 h DR (11·5 MJ/d). The proportion of under-reporters was 34 % (7 d FD) and 4 % (2 × 24 h DR). Most participants preferred the 7 d DR as it was more flexible, despite altering their eating habits. Pearson’s correlation between steps corrected for cycling and PAEE was r = 0·44, P < 0·01. Spearman’s correlation for self-reported hours spent in MVPA and PAEE was r = 0·58, P < 0·01. The 2 × 24 h DR performs better than the existing 7 d FD method. Pedometer-determined steps and self-reported MVPA are good predictors of PAEE in adult Danes.

Exercise and dietary interventions have been described to positively affect metabolic syndrome (MetS) via molecular-induced changes. The purpose of this study was to investigate the effects of dietary carbohydrate restriction and aerobic exercise (AE) on retinol binding protein 4 (RBP4) and fatty acid binding protein 5 (FABP5) in middle-aged men with MetS. The study had a randomised, double-blinded, parallel-controlled design. Forty middle-aged men with MetS (age: 53·97 ± 2·85 years, BMI = 31·09 ± 1·04 kg/m2) were randomly assigned to four groups, AE (n 10), ketogenic diet (KD; n 10), AE combined with KD (AE + KD; n 10) or control (C; n 10). RBP4, FABP5, body composition (body mass, BMI and body fat), insulin resistance, insulin sensitivity and MetS factors were evaluated prior to and after the 12-week intervention. AE + KD significantly decreased the body fat percentage (P = 0·006), BMI (P = 0·001), Zmets (P = 0·017), RBP4 (P = 0·017) and the homeostasis model of insulin resistance (HOMA-IR) (P = 0·001) as compared with control group and marginally significantly decreased the Zmets as compared with exercise group (P = 0·086). KD significantly decreased RBP4 levels as compared with control group (P = 0·041). Only the AE intervention (P = 0·045) significantly decreased FABP5 levels. Combining intervention of carbohydrate restriction with AE compared with carbohydrate restriction and AE alone improved RBP4, HOMA-IR as well as different body composition and MetS factors in middle-aged men with MetS.

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.

Prebiotic supplements and high-protein (HP) diets reduce body weight and modulate intestinal microbiota. Our aim was to elucidate the combined effect of an inulin/oligofructose (FOS) and HP diet on body weight gain, energy metabolism and faecal microbiota. Forty male C57BL/6NCrl mice were fed a control (C) diet for 2 weeks and allocated to a C or HP (40 % protein) diet including no or 10 % inulin/FOS (C + I and HP + I) for 4 weeks. Inulin/FOS was added in place of starch and cellulose. Body weight, food intake, faecal energy and nitrogen were determined. Indirect calorimetry and faecal microbiota analysis were performed after 3 weeks on diets. Body weight gain of HP-fed mice was 36 % lower than HP + I- and C-fed mice (P < 0⋅05). Diet digestibility and food conversion efficiency were higher in HP + I- than HP-fed mice (P < 0⋅01), while food intake was comparable between groups. Total energy expenditure (heat production) was 25 % lower in HP + I- than in C-, HP- and C + I-fed mice (P < 0⋅001). Carbohydrate oxidation tended to be 24 % higher in HP- than in HP + I-fed mice (P < 0⋅05). Faecal nitrogen excretion was 31–45 % lower in C-, C + I- and HP + I- than in HP-fed mice (P < 0⋅05). Faecal Bacteroides–Prevotella DNA was 2⋅3-fold higher in C + I- and HP + I- relative to C-fed mice (P < 0⋅05), but Clostridium leptum DNA abundances was 79 % lower in HP + I- than in HP-fed mice (P < 0⋅05). We suggest that the higher conversion efficiency of dietary energy of HP + I but not C + I-fed mice is caused by higher digestibility and lower heat production, resulting in increased body mass.

P ingestion has been found to alter energy balance, while regular physical exercise (E) was reported to be associated with energy compensation. However, it is not clear whether dietary P would affect energy compensation following structured E. Two experiments were performed, low P (LP) (0·1, 0·2 and 0·3 %P) and high P (HP) (0·3 , 0·6 and 1·2 %P) diets. In each experiment, male rats were randomly divided into three groups (n 8), in which a sedentary or a moderate-intensity exercise routine (30 min 5 d a week) was implemented. Energy intake (EI); efficiency and stores; body measures and total energy expenditure (TEEx) were monitored for 6 weeks. In the LP experiment, EI and weight gain were the lowest in the 0·1 and 0·2 %P as compared with the 0·3 %P. In the HP experiment, EI was highest in the high P (0·6 and 1·2 %P) groups, while weight gain was reduced. In both experiments, exercise was able to reduce body fat accumulation and to maintain a higher % lean body mass. In the LP diets experiment, the similarity in TEEx between the sedentary and exercising groups suggests the probability of a reduction in normal daily activities, which indicates the presence of compensation for the energy expended during exercise by a subsequent reduction in EE. In contrast, the elevated TEEx in the HP exercising groups (0·6 and 1·2 %P) argue against the presence of energy compensation. In conclusion, high dietary P decreases the body’s capability to compensate for the energy deficit induced by E, consequently maintaining an elevated TEEx.

Physical activity questionnaires (PAQ) could be suitable tools in free-living people for measures of physical activity, total and activity energy expenditure (TEE and AEE). This meta-analysis was performed to determine valid PAQ for estimating TEE and AEE using doubly labelled water (DLW). We identified data from relevant studies by searching Google Scholar, PubMed and Scopus databases. This revealed thirty-eight studies that had validated PAQ with DLW and reported the mean differences between PAQ and DLW measures of TEE (TEEDLW − TEEPAQ) and AEE (AEEDLW − AEEPAQ). We assessed seventy-eight PAQ consisting of fifty-nine PAQ that assessed TEE and thirty-five PAQ that examined AEE. There was no significant difference between TEEPAQ and TEEDLW with a weighted mean difference of –243·3 and a range of –841·4 to 354·6 kJ/d, and a significant weighted mean difference of AEEDLW – AEE PAQ 414·6 and a range of 78·7–750·5. To determine whether any PAQ was a valid tool for estimating TEE and AEE, we carried out a subgroup analysis by type of PAQ. Only Active-Q, administered in two seasons, and 3-d PA diaries were correlated with TEE by DLW at the population level; however, these two PAQ did not demonstrate an acceptable limit of agreement at individual level. For AEE, no PAQ was correlated with DLW either at the population or at the individual levels. Active-Q and 3-d PA diaries were identified as the only valid PAQ for TEE estimation. Further well-designed studies are needed to verify this result and identify additional valid PAQ.

This review seeks to synthesise our knowledge about changes in hunger and satiety that occur during diet-induced weight loss and during weight loss maintenance, with a particular focus on youth with obesity. Mechanisms of appetite responses to weight loss rely heavily on the adult literature. Physiological mechanisms that control appetite and satiety via the gut–brain axis have been elucidated but we have an incomplete picture of changes in gut hormones and peptides in youth with obesity. In adolescents, the role of the brain in long-term sensing of body composition and modifying appetite and satiety changes is easily over-ridden by hedonic influences for the reward of highly palatable sweet foods and encourages over-consumption. Accordingly, reward cues and hyper-responsiveness to palatable foods lead to a pattern of food choices. Different reward systems are necessary that are substantial enough to reward the continued individual effort required to sustain new behaviours, that need to be adopted to support a reduced body weight. Periods of growth and development during childhood provide windows of opportunity for interventions to influence body weight trajectory but long-term studies are lacking. More emphasis needs to be placed on anticipatory guidance on how to manage powerful hedonic influences of food choice, essential to cope with living in our obesogenic environment and managing hunger which comes with the stronger desire to eat after weight has been lost.

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.

Body weight control is thought to be improved when physical activity and energy intake are both high (high energy turnover (ET)). The aim of the present study was to investigate the short-term impact of ET on fat balance during zero energy balance (EB), energetic restriction (ER) and overfeeding (OF). In a randomised crossover study, nine healthy men (BMI: 23·0 (SD 2·1) kg/m2, 26·6 (SD 3·5) years) passed 3 × 3 d in a metabolic chamber: three levels of ET (low, medium and high; physical activity level = 1·3−1·4, 1·5−1·6 and 1·7−1·8) were performed at zero EB, ER and OF (100, 75 and 125 % of individual energy requirement). Different levels of ET were obtained by walking (4 km/h) on a treadmill (0, 165 and 330 min). Twenty-four-hour macronutrient oxidation and relative macronutrient balance (oxidation relative to intake) was calculated, and NEFA, 24-h insulin and catecholamine secretion were analysed as determinants of fat oxidation. During EB and OF, 24-h fat oxidation increased with higher ET. This resulted in a higher relative fat balance at medium ET (EB: +17 %, OF: +14 %) and high ET (EB: +23 %, OF: +17 %) compared with low ET (all P < 0·05). In contrast, ER led to a stimulation of 24-h fat oxidation irrespective of ET (no differences in relative fat balance between ET levels, P > 0·05). In conclusion, under highly controlled conditions, a higher ET improved relative fat balance in young healthy men during OF and EB compared with a sedentary state.

Low-income women are the group with the highest levels of obesity worldwide. In low-income settings, the use of predictive equations, which yield a measure of the individuals’ BMR, is a feasible approach to estimate the individuals’ total energy expenditure (TEE), using the factorial method (calculated-TEE = BMR × physical activity level), an important step of the obesity nutritional care. The present study aimed to identify the predictive equation that, in conjunction with metabolic equivalents of tasks (MET) data from accelerometers, yields the calculated-TEE with better agreement compared with the TEE measured by doubly labelled water (TEE-DLW). Forty-five women aged 19–45 years, with excess weight and mothers of undernourished children, were included. They received DLW to determine TEE (14 d); at the same time, they used triaxial accelerometers (7 d) to estimate their MET. The Bland–Altman method, paired-sample t tests, concordance correlation coefficient and root-mean-square error were used to assess the agreement. Maximum allowed differences were defined as 24 %, based on the within-variance coefficient of the energy intake of the sample. Eleven equations were studied. The calculated-TEE obtained by five equations showed non-significant bias: Dietary Reference Intake (Institute of Medicine (2005) Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids), FAO/WHO/UNU ((2001) Food and Nutrition Technical Report Series), Harris & Benedict ((1919) Proc Natl Acad Sci USA4, 370–373), Henry & Rees ((1991) Eur J Clin Nutr45, 177–185) and Schofield ((1985) Hum Nutr Clin Nutr39, 5–41). The mean percentage differences were –1·5, –0·8, 2·2, –2·2 and 2·0 %, respectively. Considering all parameters, FAO/WHO/UNU ((2001) Food and Nutrition Technical Report Series) equation performed slightly better than the others; nevertheless, no equation in conjunction with the estimated-MET showed a calculated-TEE with its CI for the Bland–Altman limits of agreement inside the pre-defined acceptable range.

Online self-reported 24-h dietary recall systems promise increased feasibility of dietary assessment. Comparison against interviewer-led recalls established their convergent validity; however, reliability and criterion-validity information is lacking. The validity of energy intakes (EI) reported using Intake24, an online 24-h recall system, was assessed against concurrent measurement of total energy expenditure (TEE) using doubly labelled water in ninety-eight UK adults (40–65 years). Accuracy and precision of EI were assessed using correlation and Bland–Altman analysis. Test–retest reliability of energy and nutrient intakes was assessed using data from three further UK studies where participants (11–88 years) completed Intake24 at least four times; reliability was assessed using intra-class correlations (ICC). Compared with TEE, participants under-reported EI by 25 % (95 % limits of agreement −73 % to +68 %) in the first recall, 22 % (−61 % to +41 %) for average of first two, and 25 % (−60 % to +28 %) for first three recalls. Correlations between EI and TEE were 0·31 (first), 0·47 (first two) and 0·39 (first three recalls), respectively. ICC for a single recall was 0·35 for EI and ranged from 0·31 for Fe to 0·43 for non-milk extrinsic sugars (NMES). Considering pairs of recalls (first two v. third and fourth recalls), ICC was 0·52 for EI and ranged from 0·37 for fat to 0·63 for NMES. EI reported with Intake24 was moderately correlated with objectively measured TEE and underestimated on average to the same extent as seen with interviewer-led 24-h recalls and estimated weight food diaries. Online 24-h recall systems may offer low-cost, low-burden alternatives for collecting dietary information.

For the same BMI, South Asians have a higher body fat percentage than Caucasians. There might be differences in the fatty acid (FA) handling in adipose tissue when both ethnicities are exposed to high-fat overfeeding. The objective of the present study was to investigate the molecular adaptation in relation to FA metabolism in response to overfeeding with a high-fat diet (OHFD) in South Asian and Caucasian men. Ten South Asian men (BMI 18–29 kg/m2) and ten Caucasian men (BMI 22–33 kg/m2), matched for body fat percentage, aged 20–40 years were included. A weight-maintenance diet (30 % fat, 55 % carbohydrate and 15 % protein) was given for 3 d followed by 3 d of overfeeding (150 % energy requirement) with a high-fat diet (60 % fat, 25 % carbohydrate and 15 % protein) while staying in a respiration chamber. Before and after overfeeding, abdominal subcutaneous fat biopsies were taken. Proteins were isolated, analysed and quantified for short-chain 3-hydroxyacyl-CoA dehydrogenase (HADH), carnitine palmitoyl-transferase 1α (CPT1a), adipose TAG lipase, perilipin A (PLINA), perilipin B, lipoprotein lipase and fatty acid binding protein 4 using Western blotting. OHFD decreased the HADH level (P < 0·05) in Caucasians more than in Asians (P < 0·05), but the baseline and after intervention HADH level was relatively higher in Caucasians. The level of CPT1a decreased in South Asians and increased in Caucasians (P < 0·05). PLINA did not change with diet but the level was higher in South Asians (P < 0·05). The observed differences in HADH and PLINA levels as well as in CPT1a response may be important for differences in the long-term regulation of energy (fat) metabolism in these populations.

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.

Excess weight loss while minimising fat-free mass (FFM) loss is important for health. Travel is a particular period at risk for weight gain and for which the effects of a short-term intensive weight loss programme have not been studied. Therefore, we studied the effect of a novel, 1-week supervised health travel programme combining high volume, low-to-moderate intensity exercise and energy intake restriction on weight, body composition and health outcomes in adults. Weight was also monitored for 12 weeks after the programme. In all, thirty-six subjects (nineteen men, seventeen women) consisting of sixteen excess-weight (BMI: 27·1 (sd 1·7) kg/m2) and twenty healthy-weight (BMI: 22·3 (sd 1·8) kg/m2) individuals participated. Subjects performed 1 h of slow-paced intermittent jogging three times per d and other leisure activities, whereas consuming only provided foods without water restriction. Body mass significantly decreased from pre- to post-intervention in excess-weight and healthy-weight individuals (−3·5 (sd 1·5) and −3·5 (sd 1·3) %, respectively; P<0·001 for both), and losses were maintained at 12 weeks post-intervention in both groups (−6·3 (sd 3·8) and −1·7 (sd 4·0) %, respectively; P<0·01 for both). Fat mass also significantly decreased in both groups (excess weight: −9·2 (sd 4·6) %: healthy weight: −13·4 (sd 9·0) %; P<0·01 for both), whereas FFM was maintained. Similar improvements were observed for blood biochemistry and pressure in both groups. This short-term weight loss intervention yielded favourable outcomes in both excess- and healthy-weight adults, particularly a 3·5 % weight loss with no significant change to FFM. In addition, participants maintained weight loss for at least 12 weeks. Of multiple programme choices, the Health Tourism weight loss programme’s results indicate that it is a viable option.

The aim of the study was to assess whether a simple substitution of carbohydrate in the conventionally recommended diet with protein and fat would result in a clinically meaningful reduction in postprandial hyperglycaemia in subjects with type 2 diabetes mellitus (T2DM). In all, sixteen subjects with T2DM treated with metformin only, fourteen male, with a median age of 65 (43–70) years, HbA1c of 6·5 % (47 mmol/l) (5·5–8·3 % (37–67 mmol/l)) and a BMI of 30 (sd 4·4) kg/m2 participated in the randomised, cross-over study. A carbohydrate-reduced high-protein (CRHP) diet was compared with an iso-energetic conventional diabetes (CD) diet. Macronutrient contents of the CRHP/CD diets consisted of 31/54 % energy from carbohydrate, 29/16 % energy from protein and 40/30 % energy from fat, respectively. Each diet was consumed on 2 consecutive days in a randomised order. Postprandial glycaemia, pancreatic and gut hormones, as well as satiety, were evaluated at breakfast and lunch. Compared with the CD diet, the CRHP diet reduced postprandial AUC of glucose by 14 %, insulin by 22 % and glucose-dependent insulinotropic polypeptide by 17 % (all P<0·001), respectively. Correspondingly, glucagon AUC increased by 33 % (P<0·001), cholecystokinin by 24 % (P=0·004) and satiety scores by 7 % (P=0·035), respectively. A moderate reduction in carbohydrate with an increase in fat and protein in the diet, compared with an energy-matched CD diet, greatly reduced postprandial glucose excursions and resulted in increased satiety in patients with well-controlled T2DM.

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 aim of this study was to validate the estimated habitual dietary intake from a newly developed web-based FFQ (WebFFQ), for use in an adult population in Norway. In total, ninety-two individuals were recruited. Total energy expenditure (TEE) measured by doubly labelled water was used as the reference method for energy intake (EI) in a subsample of twenty-nine women, and multiple 24-h recalls (24HR) were used as the reference method for the relative validation of macronutrients and food groups in the entire sample. Absolute differences, ratios, crude and deattenuated correlations, cross-classifications, Bland–Altman plot and plots between misreporting of EI (EI–TEE) and the relative misreporting of food groups (WebFFQ–24HR) were used to assess the validity. Results showed that EI on group level was not significantly different from TEE measured by doubly labelled water (0·7 MJ/d), but ranking abilities were poor (r −0·18). The relative validation showed an overestimation for the majority of the variables using absolute intakes, especially for the food groups ‘vegetables’ and ‘fish and shellfish’, but an improved agreement between the test and reference tool was observed for energy adjusted intakes. Deattenuated correlation coefficients were between 0·22 and 0·89, and low levels of grossly misclassified individuals (0–3 %) were observed for the majority of the energy adjusted variables for macronutrients and food groups. In conclusion, energy estimates from the WebFFQ should be used with caution, but the estimated absolute intakes on group level and ranking abilities seem acceptable for macronutrients and most food groups.

For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.

Subjective energy intake (sEI) is often misreported, providing unreliable estimates of energy consumed. Therefore, relating sEI data to health outcomes is difficult. Recently, Börnhorst et al. compared various methods to correct sEI-based energy intake estimates. They criticised approaches that categorise participants as under-reporters, plausible reporters and over-reporters based on the sEI:total energy expenditure (TEE) ratio, and thereafter use these categories as statistical covariates or exclusion criteria. Instead, they recommended using external predictors of sEI misreporting as statistical covariates. We sought to confirm and extend these findings. Using a sample of 190 adolescent boys (mean age=14), we demonstrated that dual-energy X-ray absorptiometry-measured fat-free mass is strongly associated with objective energy intake data (onsite weighted breakfast), but the association with sEI (previous 3-d dietary interview) is weak. Comparing sEI with TEE revealed that sEI was mostly under-reported (74 %). Interestingly, statistically controlling for dietary reporting groups or restricting samples to plausible reporters created a stronger-than-expected association between fat-free mass and sEI. However, the association was an artifact caused by selection bias – that is, data re-sampling and simulations showed that these methods overestimated the effect size because fat-free mass was related to sEI both directly and indirectly via TEE. A more realistic association between sEI and fat-free mass was obtained when the model included common predictors of misreporting (e.g. BMI, restraint). To conclude, restricting sEI data only to plausible reporters can cause selection bias and inflated associations in later analyses. Therefore, we further support statistically correcting sEI data in nutritional analyses. The script for running simulations is provided.