This study verified the accuracy of the international BMI references and the allometric BMI reference to diagnose obesity in children and adolescents from the USA. Data from 17 313 subjects were obtained from the National Health and Nutrition Examination Survey between the years 1999–2006 and 2011–2018. Fat Mass Index, Allometric Fat Mass Index and fat mass/fat-free mass were calculated. Receiver operating characteristic curve, AUC, sensitivity, specificity, positive likelihood ratio and negative likelihood ratio were estimated to evaluate the accuracy of the growth references for diagnosing obesity. The International Obesity Task Force, MULT BMI 17 years, MULT BMI 18 years and allometric BMI 19 years achieved the best sensitivity-specificity trade-off for boys, with sensitivities ranging from 0·92 to 0·96 and specificities of 0·94, with positive likelihood ratio of 15·51, 16·17, 13·46 and 18·01, respectively. The negative likelihood ratios were notably low, ranging from 0·04 to 0·08. In girls, the International Obesity Task Force, MULT BMI 17 years and MULT allometric BMI 17 years also demonstrated high sensitivity (0·95–0·97) and specificity (0·92), with positive likelihood ratio values of 11·54, 11·82 and 11·77, respectively and low negative likelihood ratio values (0·03–0·05). In summary, these international growth references presented satisfactory performance to diagnose obesity. However, the MULT growth reference performed better, and the MULT allometric BMI was the only indicator capable of detecting that girls have a higher proportion of fat mass than boys for the same index values. These findings suggest that the MULT growth reference may be a better tool to assess the nutritional status of children and adolescents internationally.

This study verified the diagnostic accuracy of the nutritional status classified by the international height and BMI references of the World Health Organization (WHO) (WHO/2007), International Obesity Task Force (IOTF/2012) and MULT (2023). The data pool was composed by 22 737 subjects aged five to 16 years from the Santos and Porto Alegre surveys. A correlation matrix between the z-scores of the BMI references and the skinfold measurements was calculated through the Pearson correlation coefficient (r), and the subject’s nutritional status was classified according to the international growth references. The accuracy for diagnosing obesity was performed separately by sex and using the 95th percentile of the triceps and subscapular skinfold sum, while Lin’s concordance coefficient, Bland–Altman method and the Cohen’s Kappa coefficient (Kappa) were used to verify the concordance and reliability among the BMI references. The correlation matrix showed a high positive correlation among the BMI z-scores (r ≥ 0·99) and among the skinfold measurements (r ≥ 0·86). The prevalence of stunting was higher when applying the MULT reference (3·4 %) compared with the WHO reference (2·3 %). The Bland–Altman plots showed the lowest critical difference (CD) between the height references of WHO and MULT (CD = 0·22). Among the BMI references, the WHO obesity percentile presented lower performance than MULT for boys, presenting a lower +LR value (WHO = 6·99/MULT 18 years = 10·99; 19 years = 8·99; 20 years = 8·09) for the same −LR values (0·04). Therefore, MULT reference holds promise as a valuable tool for diagnosing childhood obesity, particularly when considering sex differences. This enhances its suitability for assessing the nutritional status of Brazilian schoolchildren.

Quality of Recovery-15 (QoR-15) has received attention as a postoperative patient-reported outcome measure. Preoperative nutritional status has negative effects on postoperative outcomes; however, these associations have not yet been investigated. We included inpatients aged ≥ 65 years who underwent elective abdominal cancer surgery under general anaesthesia between 1 June 2021 and 7 April 2022 at our hospital. Preoperative nutritional status was assessed using the Mini Nutritional Assessment Short-Form (MNA-SF), and patients with an MNA-SF score ≤ 11 were categorised into the poor nutritional group. The outcomes in this study were the QoR-15 scores at 2 d, 4 d and 7 d after surgery, which were compared between groups by unpaired t test. Multiple regression analysis was applied to assess the effects of poor preoperative nutritional status on the QoR-15 score on postoperative day 2 (POD 2). Of the 230 included patients, 33·9 % (78/230) were categorised into the poor nutritional status group. The mean QoR-15 value was significantly lower in the poor nutritional group than in the normal nutritional group at all postoperative time points (POD 2:117 v. 99, P = 0·002; POD 4:124 v. 113, P < 0·001; POD 7:133 v. 115, P < 0·001). Multiple analyses showed that poor preoperative nutritional status was associated with the QoR-15 score on POD 2 (adjusted partial regression coefficient, −7·8; 95 % CI −14·9, −0·72). We conclude that patients with a poor preoperative nutritional status were more likely to have a lower QoR-15 score after abdominal cancer surgery.

The prevalence of malnutrition is high among oncology patients in Northern China. Malnutrition is related to the longer hospital stay, and it can be used to predict the prognostic outcome of patients. This work focused on investigating the relationship of nutritional condition with the length of hospital stay (LOS) in Northern Chinese patients with lung adenocarcinoma (LUAD). The Patient-Generated Subjective Global Assessment (PG-SGA), Nutritional Risk Screening 2002 (NRS 2002) score, recent weight loss and BMI were assessed in a probabilistic sample of 389 LUAD patients without epidermal growth factor receptor (EGFR) mutations. This study collected the demographic and clinical features of patients in a prospective manner. Then, we examined the association of nutritional status with LOS among the population developing LUAD. According to the PG-SGA, 63 (16·3 %), 174 (44·7 %) and 78 (20·1 %) patients were at risk for undernutrition, moderate undernutrition and severe undernutrition, respectively. Nutritional risk was found in 141 (36·2 %) patients based on the NRS 2002. The average LOS for tumour patients in Northern China was 12·5 d. At admission, a risk of undernutrition or undernutrition according to the PG-SGA (P < 0·001), NRS 2002 (P < 0·001) and latest weight loss (P < 0·001) predicted the longer LOS. LOS was related to nutritional status and hospitalisation expenses (P < 0·001). LUAD patients who stayed in the ICU had a poorer nutritional status and a longer LOS (P < 0·001). In Northern Chinese patients with LUAD, a risk for undernutrition evaluated by the PG-SGA, the NRS 2002 and recent weight loss, but not BMI, could predict a longer LOS.

From 2008, the UK’s National Diet and Nutrition Survey (NDNS) changed the method of dietary data collection from a 7-d weighed diary to a 4-d unweighed diary, partly to reduce participant burden. This study aimed to test whether self-reported energy intake changed significantly over the 4-d recording period of the NDNS rolling programme. Analyses used data from the NDNS years 1 (2008/2009) to 8 (2015/2016) inclusive, from participants aged 13 years and older. Dietary records from participants who reported unusual amounts of food and drink consumed on one or more days were excluded, leaving 6932 participants. Mean daily energy intake was 7107 kJ (1698 kcal), and there was a significant decrease of 164 kJ (39 kcal) between days 1 and 4 (P < 0·001). There was no significant interaction of sex or low-energy reporter status (estimated from the ratio of reported energy intake:BMR) with the change in reported energy intake. The decrease in reported energy intake on day 4 compared with day 1 was greater (P < 0·019) for adults with higher BMI (>30 kg/m2) than it was for leaner adults. Reported energy intake decreased over the 4-d recording period of the NDNS rolling programme suggesting that participants change their diet more, or report less completely, with successive days of recording their diet. The size of the effect was relatively minor, however.

Objective measurement of RMR may be important for optimal nutritional care but is hindered by the price and practicality of the metabolic monitoring device. This study compared two metabolic monitoring devices for measuring RMR and VO2 and compared the measured RMR with the predicted RMR calculated from equations. RMR was measured using QUARK RMR (reference device) and Fitmate GS (COSMED) in a random order for 30 min, each on fasted participants. In total, sixty-eight adults participated (median age 22 years, interquartile range 21–32). Pearson correlation showed that RMR (r 0·86) and VO2 (r 0·86) were highly correlated between the two devices (P < 0·05). Intraclass correlation coefficients (ICC) showed good relative agreements regarding RMR (ICC = 0·84) and VO2 (ICC = 0·84) (P < 0·05). RMR measured by QUARK RMR was significantly higher (649 (sd 753) kJ/d) than Fitmate GS. Equations significantly overpredicted RMR. Accurate RMR (i.e. within ±10 % of the RMR measured by QUARK RMR) was found among 38 % of the participants for Fitmate GS and among 46–68 % depending on the equations. Bland–Altman analysis showed a low absolute agreement with QUARK RMR at an individual level for both Fitmate GS (limits of agreement (LOA): −828 to +2125 kJ/d) and equations (LOA ranged from −1979 to +1879 kJ/d). In conclusion, both Fitmate GS and predictive equations had low absolute agreements with QUARK RMR at an individual level. Therefore, these limitations should be considered when determining RMR using Fitmate GS or equations.

Malnutrition risk screening in cirrhotic patients is crucial, as poor nutritional status negatively affects disease prognosis and survival. Given that a variety of malnutrition screening tools is usually used in routine clinical practice, the effectiveness of eight screening tools in detecting malnutrition risk in cirrhotic patients was sought. A total of 170 patients (57·1 % male, 59·4 (sd 10·5) years, 50·6 % decompensated ones) with cirrhosis of various aetiologies were enrolled. Nutritional screening was performed using the Malnutrition Universal Screening Tool, Nutritional Risk Index, Malnutrition Screening Tool, Nutritional Risk Screening (NRS-2002), Birmingham Nutritional Risk Score, Short Nutritional Assessment Questionnaire, Royal Free Hospital Nutritional Prioritizing Tool (RFH-NPT) and Liver Disease Undernutrition Screening Tool (LDUST). Malnutrition diagnosis was defined using the Subjective Global Assessment (SGA). Data on 1-year survival were available for 145 patients. The prevalence of malnutrition risk varied according to the screening tools used, with a range of 13·5–54·1 %. RFH-NPT and LDUST were the most accurate in detecting malnutrition (AUC = 0·885 and 0·892, respectively) with a high sensitivity (97·4 and 94·9 %, respectively) and fair specificity (73·3 and 58 %, respectively). Malnutrition according to SGA was an independent prognostic factor of within 1-year mortality (relative risk was 2·17 (95 % CI 1·0, 4·7), P = 0·049) after adjustment for sex, age, disease aetiology and Model for End-stage Liver Disease score, whereas nutrition risk according to RFH-NPT, LDUST and NRS-2002 showed no association. RFH-NPT and LDUST were the only screening tools that proved to be accurate in detecting malnutrition in cirrhotic patients.

We discuss efforts in improving the value of nutrition research. We organised the paper in five research stages: Stage 1: research priority setting; Stage 2: research design, conduct and analysis; Stage 3: research regulation and management; Stage 4: research accessibility and Stage 5: research reporting and publishing. Along the stages of the research cycle, varied initiatives exist to improve the quality and added value of nutrition research. However, efforts are focused on single stages of the research cycle without vision of the research system as a whole. Although research on nutrition research has been limited, it has potential to improve the quality of nutrition research and develop new tools and instruments for this purpose. A comprehensive assessment of the magnitude of research waste in nutrition and consensus on priority actions is needed. The nutrition research community at large needs to have open discussions on the usefulness of these tools and lead suitable efforts to enhance nutrition research across the stages of the research cycle. Capacity building is essential and considerations of nutrition research quality are vital to be integrated in training efforts of nutrition researchers.

The advent of the internet and smartphone technology has allowed dietary assessment to reach the 21st century! The variety of foods available on the supermarket shelf is now greater than ever before. New approaches to measuring diet may help to reduce measurement error and advance our understanding of nutritional determinants of disease. This advance provides the potential to capture detailed dietary data on large numbers of individuals without the need for costly and time-consuming manual nutrition coding. This aim of the present paper is to review the need for new technologies to measure diet with an overview of tools available. The three main areas will be addressed: (1) development of web-based tools to measure diet; (2) use of smartphone apps to self-monitor diet; (3) improving the quality of dietary assessment through development of an online library of tools. A practical example of the development of a web-based tool to assess diet myfood24 (www.myfood24.org) will be given exploring its potential, limitations and challenges. The development of a new food composition database using back-of-pack information will be described. Smartphone apps used to measure diet with a focus on obesity will be reviewed. Many apps are unreliable in terms of tracking, and most are not evaluated. Accurate and consistent measurement of diet is needed for public health and epidemiology. The choice of the most appropriate dietary assessment method tends to rely on experience. The DIET@NET partnership has developed best practice guidelines for selection of dietary assessment tools, which aim to improve the quality, consistency and comparability of dietary data. These developments provide us with a step-change in our ability to reliably characterise food and nutrient intake in population studies. The need for high-quality, validated systems will be important to fully realise the benefits of new technologies.

A single question (SQ) and a twenty-eight-item FFQ to measure takeaway meal intake were compared with two 7-d estimated food records (EFR; reference method). Test methods were completed after the reference period and repeated 6–8 d later for repeatability. The SQ asked about intake of high-SFA takeaway meals. FFQ items included low- and high-SFA meals. Test methods were compared with EFR for sensitivity, specificity, and positive and negative predictive values, using a goal of ≤1 high-SFA weekly takeaway meals. Bland–Altman analyses were used to check agreement between measurement approaches, the κ coefficient was used to summarise the observed level of agreement, and Spearman’s correlation was used to assess the degree to which instruments ranked individuals. Young adults were recruited from two universities, and 109 participants (61 % female) completed the study. The mean age was 24·4 (sd 4·9) years, and the mean BMI was 23·5 (sd 3·7) kg/m2. The SQ and the FFQ had a sensitivity of 97 and 83 % and a specificity of 46 and 92 %, respectively. Both methods exhibited moderate correlation for measuring total and high-SFA takeaway meal intakes (rs ranging from 0·64 to 0·80). Neither instrument could measure precise, absolute intake at the group or individual level. Test methods ranged from fair (κw=0·24) to moderate agreement (κw=0·59). The repeatability for all was acceptable. The FFQ identified excessive high-SFA takeaway meal intake and measured individuals’ category for total and high-SFA takeaway intakes. Both methods are suitable for ranking individuals for total or high-SFA takeaway meal intakes.

Preliminary research has suggested that wearable cameras may reduce under-reporting of energy intake (EI) in self-reported dietary assessment. The aim of the present study was to test the validity of a wearable camera-assisted 24 h dietary recall against the doubly labelled water (DLW) technique. Total energy expenditure (TEE) was assessed over 15 d using the DLW protocol among forty adults (n 20 males, age 35 (sd 17) years, BMI 27 (sd 4) kg/m2 and n 20 females, age 28 (sd 7) years, BMI 22 (sd 2) kg/m2). EI was assessed using three multiple-pass 24 h dietary recalls (MP24) on days 2–4, 8–10 and 13–15. On the days before each nutrition assessment, participants wore an automated wearable camera (SenseCam (SC)) in free-living conditions. The wearable camera images were viewed by the participants following the completion of the dietary recall, and their changes in self-reported intakes were recorded (MP24+SC). TEE and EI assessed by the MP24 and MP24+SC methods were compared. Among men, the MP24 and MP24+SC measures underestimated TEE by 17 and 9 %, respectively (P< 0·001 and P= 0·02). Among women, these measures underestimated TEE by 13 and 7 %, respectively (P< 0·001 and P= 0·004). The assistance of the wearable camera (MP24+SC) reduced the magnitude of under-reporting by 8 % for men and 6 % for women compared with the MP24 alone (P< 0·001 and P< 0·001). The increase in EI was predominantly from the addition of 265 unreported foods (often snacks) as revealed by the participants during the image review. Wearable cameras enhance the accuracy of self-report by providing passive and objective information regarding dietary intake. High-definition image sensors and increased imaging frequency may improve the accuracy further.