Objective: To facilitate the Food and Agriculture Organization/World Health Organization/United Nations University Joint (FAO/WHO/UNU) Expert Consultation on Energy and Protein Requirements which met in Rome in 1981, Schofieldet al.reviewed the literature and produced predictive equations for both sexes for the following ages: 0–3, 3–10, 10–18, 18–30, 30–60 and >60 years. These formed the basis for the equations used in 1985 FAO/WHO/UNU document,Energy and Protein Requirements.While Schofield's analysis has served a significant role in re-establishing the importance of using basal metabolic rate (BMR) to predict human energy requirements, recent workers have subsequently queried the universal validity and application of these equations. A survey of the most recent studies (1980–2000) in BMR suggests that in most cases the current FAO/WHO/UNU predictive equations overestimate BMR in many communities. The FAO/WHO/UNU equations to predict BMR were developed using a database that contained a disproportionate number – 3388 out of 7173 (47%) – of Italian subjects. The Schofield database contained relatively few subjects from the tropical region.The objective here is to review the historical development in the measurement and application of BMR and to critically review the Schofieldet al.BMR database presenting a series of new equations to predict BMR.Design: This division, while arbitrary, will enable readers who wish to omit the historical review of BMR to concentrate on the evolution of the new BMR equations.Setting: BMR data collected from published and measured values.Subjects: A series of new equations (Oxford equations) have been developed using a data set of 10 552 BMR values that (1) excluded all the Italian subjects and (2) included a much larger number (4018) of people from the tropics.Results: In general, the Oxford equations tend to produce lower BMR values than the current FAO/WHO/UNU equations in 18–30 and 30–60 year old males and in all females over 18 years of age.Conclusions: This is an opportune moment to re-examine the role and place of BMR measurements in estimating total energy requirements today. The Oxford equations' future use and application will surely depend on their ability to predict more accurately the BMR in contemporary populations.

Protein calories consumed by people all over the world approximate 15–20% of their energy intake. This makes protein a major nutritional imperative. Today, we are facing an unprecedented challenge to produce and distribute adequate protein to feed over nine billion people by 2050, in an environmentally sustainable and affordable way. Plant-based proteins present a promising solution to our nutritional needs due to their long history of crop use and cultivation, lower cost of production, and easy access in many parts of the world. However, plant proteins have comparatively poor functionality, defined as poor solubility, foaming, emulsifying, and gelling properties, limiting their use in food products. Relative to animal proteins, including dairy products, plant protein technology is still in its infancy. To bridge this gap, advances in plant protein ingredient development and the knowledge to construct plant-based foods are sorely needed. This review focuses on some salient features in the science and technology of plant proteins, providing the current state of the art and highlighting new research directions. It focuses on how manipulating plant protein structures during protein extraction, fractionation, and modification can considerably enhance protein functionality. To create novel plant-based foods, important considerations such as protein–polysaccharide interactions, the inclusion of plant protein-generated flavors, and some novel techniques to structure plant proteins are discussed. Finally, the attention to nutrition as a compass to navigate the plant protein roadmap is also considered.

Objective. Recent reports have suggested that a low glycemic index (GI) diet may have a role in the management of obesity through its ability to increase the satiety value of food and modulate appetite. To date, no long-term clinical trials have examined the effect of dietary GI on body weight regulation. The majority of evidence comes from single-day studies, most of which have been conducted in adults. The purpose of this study was to investigate the effect of 3 test breakfasts—low-GI, low-GI with 10% added sucrose, and high-GI—on ad libitum lunch intake, appetite, and satiety and to compare these with baseline values when habitual breakfast was consumed. Methods. A 3-way crossover study using block randomization of breakfast type was conducted in a school that already ran a breakfast club. A total of 37 children aged 9 to 12 years (15 boys and 22 girls) completed the study. The proportion of nonoverweight to overweight/obese children was 70:30. Children were divided into 5 groups, and a rolling program was devised whereby, week by week, each group would randomly receive 1 of 3 test breakfasts for 3 consecutive days, with a minimum of 5 weeks between the test breakfasts. Participants acted as their own control. The 3 test breakfasts were devised to match the energy and nutritional content of an individual’s habitual breakfast as far as possible. All test breakfasts were composed of fruit juice, cereal, and milk with/without bread and margarine; foods with an appropriate GI value were selected. After each test breakfast, children were instructed not to eat or drink anything until lunchtime, except water and a small serving of fruit supplying approximately 10 g of carbohydrate, which was provided. Breakfast palatability, satiation after breakfast, and satiety before lunch were measured using rating scales based on previously used tools. Lunch was a buffet-style meal, and children were allowed free access to a range of foods. Lunch was served in the school hall where the rest of the schoolchildren were eating. Food intake at lunch was unobtrusively observed and recorded. Leftovers and food swapping were recorded, and plate waste was estimated. Lunch intakes were analyzed using a multilevel regression model for repeated measures data. The likelihood ratio statistic was used to determine whether the type of breakfast eaten had a significant effect on lunch intake after allowing for sex and weight status. Results. The type of breakfast eaten had a statistically significant effect on mean energy intake at lunchtime: lunch intake was lower after low-GI and low-GI with added sucrose breakfasts compared with lunch intake after high-GI and habitual breakfasts (which were high-GI). Overweight and sex did not have a significant effect on lunch intake. Pairwise comparisons among the 3 types of test breakfasts and between each test breakfast and habitual breakfast were made. Lunch intake after the high-GI breakfast was significantly higher than after the low-GI breakfast and low-GI breakfast with added sucrose. The details of the pairwise comparisons were as follows: high-GI versus low-GI = 145 ± 54 kcal; high-GI versus low-GI plus sucrose = 119 ± 53 kcal; low-GI plus sucrose versus low-GI = 27 ± 54 kcal. Lunch intake after the low-GI breakfast and the low-GI breakfast with added sucrose was significantly lower than after the habitual breakfast. The details of the pairwise comparisons were as follows: low-GI versus habitual = −109 ± 75 kcal; low-GI plus sucrose versus habitual = −83 ± 75 kcal; high-GI versus habitual = 36 ± 75 kcal. There were no significant differences between the test breakfasts in immediate satiation. The high-GI breakfasts were rated to be more palatable than the low-GI breakfasts. At lunchtime, hunger ratings were greater after the high-GI breakfast compared with the other 2 test breakfasts on 2 of the 3 experimental days. Prelunch satiety scales were inversely related to subsequent food intake. Conclusions. These results suggest that low-GI foods eaten at breakfast have a significant impact on food intake at lunch. This is the first study to observe such an effect in a group of normal and overweight children and adds to the growing body of evidence that low-GI foods may have an important role in weight control and obesity management. The potentially confounding effect of differences in the macronutrient and dietary fiber content of the test breakfasts warrants additional study. In addition, the impact of GI on food intake and body weight regulation in the long term needs to be investigated.

Circadian rhythms are 24-h cycles regulated by endogeneous molecular oscillators called the circadian clock. The effects of diet on circadian rhythmicity clearly involves a relationship between factors such as meal timings and nutrients, known as chrononutrition. Chrononutrition is influenced by an individual’s “chronotype”, whereby “evening chronotypes” or also termed “later chronotype” who are biologically driven to consume foods later in the day. Research in this area has suggested that time of day is indicative of having an influence on the postprandial glucose response to a meal, therefore having a major effect on type 2 diabetes. Cross-sectional and experimental studies have shown the benefits of consuming meals early in the day than in the evening on postprandial glycaemia. Modifying the macronutrient composition of night meals, by increasing protein and fat content, has shown to be a simple strategy to improve postprandial glycaemia. Low glycaemic index (GI) foods eaten in the morning improves glycaemic response to a greater effect than when consumed at night. Timing of fat and protein (including amino acids) co-ingested with carbohydrate foods, such as bread and rice, can reduce glycaemic response. The order of food presentation also has considerable potential in reducing postprandial blood glucose (consuming vegetables first, followed by meat and then lastly rice). These practical recommendations could be considered as strategies to improve glycaemic control, rather than focusing on the nutritional value of a meal alone, to optimize dietary patterns of diabetics. It is necessary to further elucidate this fascinating area of research to understand the circadian system and its implications on nutrition that may ultimately reduce the burden of type 2 diabetes.

Background: Improving the carbohydrate quality of the diet by replacing the common cereal staple white rice (WR) with brown rice (BR) could have beneficial effects on reducing the risk for diabetes and related complications. Hence we aimed to compare the effects of BR, WR, and BR with legumes (BRL) diets on 24-h glycemic and insulinemic responses among overweight Asian Indians. Subjects and Methods: Fifteen overweight (body mass index, ≥23 kg/m ² ) Asian Indians without diabetes who were 25–45 years old participated in a randomized crossover study. Test meals (nonisocaloric, ad libitum) were identical except for the type of rice and the addition of legumes (50 g/day) and were provided for 5 consecutive days. Glucose profiles were assessed using the Medtronic MiniMed (Northridge, CA) iPro™2 continuous glucose monitoring device. The mean positive change from baseline glucose concentration was calculated as the daily incremental area under the curve (IAUC) on each test day for 5 days and averaged. Fasting serum insulin was measured prior to and at the end of each test diet. Results: The percentage difference in 5-day average IAUC was 19.8% lower in the BR group than in the WR group ( P =0.004). BRL further decreased the glycemic response (22.9% lower compared with WR ( P =0.02). The 5-day percentage change in fasting insulin was 57% lower ( P =0.0001) for the BR group and 54% lower for the BRL group compared with the 5-day percentage change observed in the WR group. The glycemic and insulinemic responses to the BR and BRL diets were not significantly different. Conclusions: Consumption of BR in place of WR can help reduce 24-h glucose and fasting insulin responses among overweight Asian Indians.