Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults. We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5-19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5-19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity). Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m2 per decade; 95% credible interval -0·42 to 0·39, posterior probability [PP] of the observed decrease being a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m2 per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m2 per decade (0·64-1·25, PP>0·9999) in Polynesia and Micronesia. The range for boys was from a non-significant increase of 0·09 kg/m2 per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m2 per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. By contrast, the rise in BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. Global age-standardised prevalence of obesity increased from 0·7% (0·4-1·2) in 1975 to 5·6% (4·8-6·5) in 2016 in girls, and from 0·9% (0·5-1·3) in 1975 to 7·8% (6·7-9·1) in 2016 in boys; the prevalence of moderate and severe underweight decreased from 9·2% (6·0-12·9) in 1975 to 8·4% (6·8-10·1) in 2016 in girls and from 14·8% (10·4-19·5) in 1975 to 12·4% (10·3-14·5) in 2016 in boys. Prevalence of moderate and severe underweight was highest in India, at 22·7% (16·7-29·6) among girls and 30·7% (23·5-38·0) among boys. Prevalence of obesity was more than 30% in girls in Nauru, the Cook Islands, and Palau; and boys in the Cook Islands, Nauru, Palau, Niue, and American Samoa in 2016. Prevalence of obesity was about 20% or more in several countries in Polynesia and Micronesia, the Middle East and north Africa, the Caribbean, and the USA. In 2016, 75 (44-117) million girls and 117 (70-178) million boys worldwide were moderately or severely underweight. In the same year, 50 (24-89) million girls and 74 (39-125) million boys worldwide were obese. The rising trends in children's and adolescents' BMI have plateaued in many high-income countries, albeit at high levels, but have accelerated in parts of Asia, with trends no longer correlated with those of adults. Wellcome Trust, AstraZeneca Young Health Programme.

(1) Background: Emotional eating is considered as the propensity to eat in response to emotions. It is considered as a critical risk factor for recurrent weight gain. Such overeating is able to affect general health due to excess energy intake and mental health. So far, there is still considerable controversy on the effect of the emotional eating concept. The objective of this study is to summarize and evaluate the interconnections among emotional eating and overweight/obesity, depression, anxiety/stress, and dietary patterns; (2) Methods: This is a thorough review of the reported associations among emotional eating and overweight/obesity, depression, anxiety/stress, and dietary patterns. We compressively searched the most precise scientific online databases, e.g., PubMed, Scopus, Web of Science and Google Scholar to obtain the most up-to-date data from clinical studies in humans from the last ten years (2013–2023) using critical and representative keywords. Several inclusion and exclusion criteria were applied for scrutinizing only longitudinal, cross-sectional, descriptive, and prospective clinical studies in Caucasian populations; (3) Results: The currently available findings suggest that overeating/obesity and unhealthy eating behaviors (e.g., fast food consumption) are associated with emotional eating. Moreover, the increase in depressive symptoms seems to be related with more emotional eating. Psychological distress is also related with a greater risk for emotional eating. However, the most common limitations are the small sample size and their lack of diversity. In addition, a cross-sectional study was performed in the majority of them; (4) Conclusions: Finding coping mechanisms for the negative emotions and nutrition education can prevent the prevalence of emotional eating. Future studies should further explain the underlying mechanisms of the interconnections among emotional eating and overweight/obesity, depression, anxiety/stress, and dietary patterns.

Sarcopenia is an age-related disease which leads to a decline in muscle mass and function and is one of the most important health issues in elderly people with a high rate and variety of adverse outcomes.

Osteoporosis and sarcopenia are diseases which affect the myoskeletal system and often occur in older adults. They are characterized by low bone density and loss of muscle mass and strength, factors which reduce the quality of life and mobility. Recently, apart from pharmaceutical interventions, many studies have focused on non-pharmaceutical approaches for the prevention of osteoporosis and sarcopenia with exercise and nutrition to being the most important and well studied of those. The purpose of the current narrative review is to describe the role of exercise and nutrition on prevention of osteoporosis and sarcopenia in older adults and to define the incidence of osteosarcopenia. Most of the publications which were included in this review show that resistance and endurance exercises prevent the development of osteoporosis and sarcopenia. Furthermore, protein and vitamin D intake, as well as a healthy diet, present a protective role against the development of the above bone diseases. However, current scientific data are not sufficient for reaching solid conclusions. Although the roles of exercise and nutrition on osteoporosis and sarcopenia seem to have been largely evaluated in literature over the recent years, most of the studies which have been conducted present high heterogeneity and small sample sizes. Therefore, they cannot reach final conclusions. In addition, osteosarcopenia seems to be caused by the effects of osteoporosis and sarcopenia on elderly. Larger meta-analyses and randomized controlled trials are needed designed based on strict inclusion criteria, in order to describe the exact role of exercise and nutrition on osteoporosis and sarcopenia.

Sarcopenia, a geriatric syndrome characterized by progressive skeletal muscle mass and function decline, poses a significant health risk among the elderly, contributing to frailty, falls, hospitalization, loss of independence and mortality. The prevalence of sarcopenia varies significantly based on various factors, such as living status, demographics, measurement techniques and diagnostic criteria. Although the overall prevalence is reported at 10% in individuals aged 60 and above, disparities exist across settings, with higher rates in nursing homes and hospitals. Additionally, the differences in prevalence between Asian and non-Asian countries highlight the impact of cultural and ethnic factors, and variations in diagnostic criteria, cut-off values and assessment methods contribute to the observed heterogeneity in reported rates. This review outlines diverse diagnostic criteria and several measurement techniques supporting decision making in clinical practice. Moreover, it facilitates the selection of appropriate tools to assess sarcopenia, emphasizing its multifactorial nature. Various scientific groups, including the European Working Group of Sarcopenia in Older People (EWGSOP), the International Working Group on Sarcopenia (IWGS), the Asian Working Group on Sarcopenia (AWGS), the American Foundation for the National Institutes of Health (FNIH) and the Sarcopenia Definition and Outcomes Consortium (SDOC), have published consensus papers outlining diverse definitions of sarcopenia. The choice of diagnostic criteria should be aligned with the specific objectives of the study or clinical practice, considering the characteristics of the study population and available resources.

Background: Artificial Intelligence (AI) technologies are now essential as the agenda of nutrition research expands its scope to look at the intricate connection between food and health in both an individual and a community context. AI also helps in tracing and offering solutions in dietary assessment, personalized and clinical nutrition, as well as disease prediction and management, such as cardiovascular diseases, diabetes, cancer, and obesity. This review aims to investigate and assess the different applications and roles of AI in nutrition and research and understand its potential future impact. Methods: We used PubMed, Scopus, Web of Science, Google Scholar, and EBSCO databases for our search. Results: Our findings indicate that AI is reshaping the field of nutrition in ways that were previously unimaginable. By enhancing how we assess diets, customize nutrition plans, and manage complex health conditions, AI has become an essential tool. Technologies like machine learning models, wearable devices, and chatbot applications are revolutionizing the accuracy of dietary tracking, making it easier than ever to provide tailored solutions for individuals and communities. These innovations are proving invaluable in combating diet-related illnesses and encouraging healthier eating habits. One breakthrough has been in dietary assessment, where AI has significantly reduced errors that are common in traditional methods. Tools that use visual recognition, deep learning, and mobile applications have made it possible to analyze the nutrient content of meals with incredible precision. Conclusions: Moving forward, collaboration between tech developers, healthcare professionals, policymakers, and researchers will be essential. By focusing on high-quality data, addressing ethical challenges, and keeping user needs at the forefront, AI can truly revolutionize nutrition science. The potential is enormous. AI is set to make healthcare not only more effective and personalized but also more equitable and accessible for everyone.